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Xie R, Lin J, Li W, Chen H, Zhang J, Zhong M, Xue J, Mo C, Chen L, Zhu Y, Chen X, Xu S. Homogentisic acid metabolism inhibits papillary thyroid carcinoma proliferation through ROS and p21-induced cell cycle arrest. Life Sci 2024; 347:122682. [PMID: 38702025 DOI: 10.1016/j.lfs.2024.122682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Revised: 04/09/2024] [Accepted: 04/28/2024] [Indexed: 05/06/2024]
Abstract
Thyroid cancer is one of the most common primary endocrine malignancies worldwide, and papillary thyroid carcinoma (PTC) is the predominant histological type observed therein. Although PTC has been studied extensively, our understanding of the altered metabolism and metabolic profile of PTC tumors is limited. We identified that the content of metabolite homogentisic acid (HGA) in PTC tissues was lower than that in adjacent non-cancerous tissues. We evaluated the potential of HGA as a novel molecular marker in the diagnosis of PTC tumors, as well as its ability to indicate the degree of malignancy. Studies have further shown that HGA contributes to reactive oxygen species (ROS) associated oxidative stress, leading to toxicity and inhibition of proliferation. In addition, HGA caused an increase in p21 expression levels in PTC cells and induced G1 arrest. Moreover, we found that the low HGA content in PTC tumors was due to the low expression levels of tyrosine aminotransferase (TAT) and p-hydroxyphenylpyruvate hydroxylase (HPD), which catalyze the conversion of tyrosine to HGA. The low expression levels of TAT and HPD are strongly associated with a higher probability of PTC tumor invasion and metastasis. Our study demonstrates that HGA could be used to diagnose PTC and provides mechanisms linking altered HGA levels to the biological behavior of PTC tumors.
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Affiliation(s)
- Ruiwang Xie
- Department of Thyroid and Breast Surgery, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China
| | - Junyu Lin
- Department of Thyroid and Breast Surgery, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China
| | - Weiwei Li
- Department of Thyroid and Breast Surgery, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China
| | - Huaying Chen
- Department of Thyroid and Breast Surgery, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China
| | - Junsi Zhang
- Department of Thyroid and Breast Surgery, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China
| | - Minjie Zhong
- Department of Thyroid and Breast Surgery, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China
| | - Jiajie Xue
- Department of Thyroid and Breast Surgery, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China
| | - Caiqin Mo
- Department of Thyroid and Breast Surgery, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China
| | - Ling Chen
- Department of Thyroid and Breast Surgery, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China
| | - Youzhi Zhu
- Department of Thyroid and Breast Surgery, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China; Department of Thyroid and Breast Surgery, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China.
| | - Xiangjin Chen
- Department of Thyroid and Breast Surgery, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China; Department of Thyroid and Breast Surgery, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China.
| | - Sunwang Xu
- Department of Thyroid and Breast Surgery, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China; Department of Thyroid and Breast Surgery, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China; Fujian Provincial Key Laboratory of Precision Medicine for Cancer, Fuzhou, China.
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Yang S, Zheng L, Li L, Zhang J, Wang J, Zhao H, Chen Y, Liu X, Gan H, Chen J, Yan M, He C, Li K, Ding C, Li Y. Integrative multiomics analysis identifies molecular subtypes and potential targets of hepatocellular carcinoma. Clin Transl Med 2024; 14:e1727. [PMID: 38804617 PMCID: PMC11131356 DOI: 10.1002/ctm2.1727] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Revised: 05/10/2024] [Accepted: 05/15/2024] [Indexed: 05/29/2024] Open
Abstract
BACKGROUND The liver is anatomically divided into eight segments based on the distribution of Glisson's triad. However, the molecular mechanisms underlying each segment and its association with hepatocellular carcinoma (HCC) heterogeneity are not well understood. In this study, our objective is to conduct a comprehensive multiomics profiling of the segmentation atlas in order to investigate potential subtypes and therapeutic approaches for HCC. METHODS A high throughput liquid chromatography-tandem mass spectrometer strategy was employed to comprehensively analyse proteome, lipidome and metabolome data, with a focus on segment-resolved multiomics profiling. To classify HCC subtypes, the obtained data with normal reference profiling were integrated. Additionally, potential therapeutic targets for HCC were identified using immunohistochemistry assays. The effectiveness of these targets were further validated through patient-derived organoid (PDO) assays. RESULTS A multiomics profiling of 8536 high-confidence proteins, 1029 polar metabolites and 3381 nonredundant lipids was performed to analyse the segmentation atlas of HCC. The analysis of the data revealed that in normal adjacent tissues, the left lobe was primarily involved in energy metabolism, while the right lobe was associated with small molecule metabolism. Based on the normal reference atlas, HCC patients with segment-resolved classification were divided into three subtypes. The C1 subtype showed enrichment in ribosome biogenesis, the C2 subtype exhibited an intermediate phenotype, while the C3 subtype was closely associated with neutrophil degranulation. Furthermore, using the PDO assay, exportin 1 (XPO1) and 5-lipoxygenase (ALOX5) were identified as potential targets for the C1 and C3 subtypes, respectively. CONCLUSION Our extensive analysis of the segmentation atlas in multiomics profiling defines molecular subtypes of HCC and uncovers potential therapeutic strategies that have the potential to enhance the prognosis of HCC.
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Affiliation(s)
- Shuai Yang
- Department of Hematology & OncologyJiangbei CampusThe First Affiliated Hospital of Army Medical UniversityChongqingChina
| | - Lu Zheng
- Department of Hepatobiliary SurgeryXinqiao HospitalArmy Medical UniversityChongqingChina
| | - Lingling Li
- State Key Laboratory of Genetic EngineeringInstitutes of Biomedical SciencesHuman Phenome InstituteSchool of Life SciencesZhongshan HospitalFudan UniversityShanghaiChina
| | - Jiangang Zhang
- Department of Medical OncologyChongqing University Cancer HospitalChongqingChina
| | - Jingchun Wang
- Department of GastroenterologyXinqiao Hospital, Army Medical UniversityChongqingChina
| | - Huakan Zhao
- Department of Medical OncologyChongqing University Cancer HospitalChongqingChina
| | - Yu Chen
- Department of Medical OncologyChongqing University Cancer HospitalChongqingChina
| | - Xudong Liu
- Department of Medical OncologyChongqing University Cancer HospitalChongqingChina
| | - Hui Gan
- Department of RadiologyXinqiao HospitalArmy Medical UniversityChongqingChina
| | - Junying Chen
- Department of PathologyJiangbei CampusThe First Affiliated Hospital of Army Medical UniversityChongqingChina
| | - Mei Yan
- Department of PathologyJiangbei CampusThe First Affiliated Hospital of Army Medical UniversityChongqingChina
| | - Chuanyin He
- Department of PathologyJiangbei CampusThe First Affiliated Hospital of Army Medical UniversityChongqingChina
| | - Kai Li
- State Key Laboratory of Genetic EngineeringInstitutes of Biomedical SciencesHuman Phenome InstituteSchool of Life SciencesZhongshan HospitalFudan UniversityShanghaiChina
| | - Chen Ding
- State Key Laboratory of Genetic EngineeringInstitutes of Biomedical SciencesHuman Phenome InstituteSchool of Life SciencesZhongshan HospitalFudan UniversityShanghaiChina
| | - Yongsheng Li
- Department of Medical OncologyChongqing University Cancer HospitalChongqingChina
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Tu L, Chen S, Yuan Z, Xiong Y, Luo B, Chen Y, Hou Z, Ke S, Lin N, Li C, Ye S. Amino acid-based metallo-supramolecular nanoassemblies capable of regulating cellular redox homeostasis for tumoricidal chemo-/photo-/catalytic combination therapy. J Colloid Interface Sci 2024; 663:810-824. [PMID: 38447396 DOI: 10.1016/j.jcis.2024.02.197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2023] [Revised: 02/27/2024] [Accepted: 02/27/2024] [Indexed: 03/08/2024]
Abstract
Nanozymes, as nanomaterials with natural enzyme activities, have been widely applied to deliver various therapeutic agents to synergistically combat the progression of malignant tumors. However, currently common inorganic nanozyme-based drug delivery systems still face challenges such as suboptimal biosafety, inadequate stability, and inferior tumor selectivity. Herein, a super-stable amino acid-based metallo-supramolecular nanoassembly (FPIC NPs) with peroxidase (POD)- and glutathione oxidase (GSHOx)-like activities was fabricated via Pt4+-driven coordination co-assembly of l-cysteine derivatives, the chemotherapeutic drug curcumin (Cur), and the photosensitizer indocyanine green (ICG). The superior POD- and GSHOx-like activities could not only catalyze the decomposition of endogenous hydrogen peroxide into massive hydroxyl radicals, but also deplete the overproduced glutathione (GSH) in cancer cells to weaken intracellular antioxidant defenses. Meanwhile, FPIC NPs would undergo degradation in response to GSH to specifically release Cur, causing efficient mitochondrial damage. In addition, FPIC NPs intrinsically enable fluorescence/photoacoustic imaging to visualize tumor accumulation of encapsulated ICG in real time, thereby determining an appropriate treatment time point for tumoricidal photothermal (PTT)/photodynamic therapy (PDT). In vitro and in vivo findings demonstrated the quadruple orchestration of catalytic therapy, chemotherapeutics, PTT, and PDT offers conspicuous antineoplastic effects with minimal side reactions. This work may provide novel ideas for designing supramolecular nanoassemblies with multiple enzymatic activities and therapeutic functions, allowing for wider applications of nanozymes and nanoassemblies in biomedicine.
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Affiliation(s)
- Li Tu
- Department of Biomaterials, The Higher Educational Key Laboratory for Biomedical Engineering of Fujian Province, Research Center of Biomedical Engineering of Xiamen, College of Materials, Xiamen University, Xiamen 361005, PR China
| | - Shengqiang Chen
- Department of Biomaterials, The Higher Educational Key Laboratory for Biomedical Engineering of Fujian Province, Research Center of Biomedical Engineering of Xiamen, College of Materials, Xiamen University, Xiamen 361005, PR China
| | - Zhikang Yuan
- The Key Laboratory for Innovative Drug Target Research of Fujian Province, School of Pharmaceutical Sciences, Xiamen University, Xiamen 361102, PR China
| | - Yeqi Xiong
- Department of Biomaterials, The Higher Educational Key Laboratory for Biomedical Engineering of Fujian Province, Research Center of Biomedical Engineering of Xiamen, College of Materials, Xiamen University, Xiamen 361005, PR China
| | - Bingkun Luo
- Department of Biomaterials, The Higher Educational Key Laboratory for Biomedical Engineering of Fujian Province, Research Center of Biomedical Engineering of Xiamen, College of Materials, Xiamen University, Xiamen 361005, PR China
| | - Ying Chen
- Department of Surgery, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen 361004, PR China
| | - Zhenqing Hou
- Department of Biomaterials, The Higher Educational Key Laboratory for Biomedical Engineering of Fujian Province, Research Center of Biomedical Engineering of Xiamen, College of Materials, Xiamen University, Xiamen 361005, PR China
| | - Sunkui Ke
- Department of Surgery, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen 361004, PR China
| | - Naibo Lin
- Department of Biomaterials, The Higher Educational Key Laboratory for Biomedical Engineering of Fujian Province, Research Center of Biomedical Engineering of Xiamen, College of Materials, Xiamen University, Xiamen 361005, PR China.
| | - Chao Li
- Departmentof Surgery, Haicang Hospital, Xiamen Medical College, Xiamen 361026, PR China.
| | - Shefang Ye
- Department of Biomaterials, The Higher Educational Key Laboratory for Biomedical Engineering of Fujian Province, Research Center of Biomedical Engineering of Xiamen, College of Materials, Xiamen University, Xiamen 361005, PR China.
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Taunk K, Jajula S, Bhavsar PP, Choudhari M, Bhanuse S, Tamhankar A, Naiya T, Kalita B, Rapole S. The prowess of metabolomics in cancer research: current trends, challenges and future perspectives. Mol Cell Biochem 2024:10.1007/s11010-024-05041-w. [PMID: 38814423 DOI: 10.1007/s11010-024-05041-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 05/18/2024] [Indexed: 05/31/2024]
Abstract
Cancer due to its heterogeneous nature and large prevalence has tremendous socioeconomic impacts on populations across the world. Therefore, it is crucial to discover effective panels of biomarkers for diagnosing cancer at an early stage. Cancer leads to alterations in cell growth and differentiation at the molecular level, some of which are very unique. Therefore, comprehending these alterations can aid in a better understanding of the disease pathology and identification of the biomolecules that can serve as effective biomarkers for cancer diagnosis. Metabolites, among other biomolecules of interest, play a key role in the pathophysiology of cancer whose levels are significantly altered while 'reprogramming the energy metabolism', a cellular condition favored in cancer cells which is one of the hallmarks of cancer. Metabolomics, an emerging omics technology has tremendous potential to contribute towards the goal of investigating cancer metabolites or the metabolic alterations during the development of cancer. Diverse metabolites can be screened in a variety of biofluids, and tumor tissues sampled from cancer patients against healthy controls to capture the altered metabolism. In this review, we provide an overview of different metabolomics approaches employed in cancer research and the potential of metabolites as biomarkers for cancer diagnosis. In addition, we discuss the challenges associated with metabolomics-driven cancer research and gaze upon the prospects of this emerging field.
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Affiliation(s)
- Khushman Taunk
- Proteomics Lab, National Centre for Cell Science, Ganeshkhind, Pune, Maharashtra, 411007, India
- Department of Biotechnology, Maulana Abul Kalam Azad University of Technology, West Bengal, NH12 Simhat, Haringhata, Nadia, West Bengal, 741249, India
| | - Saikiran Jajula
- Proteomics Lab, National Centre for Cell Science, Ganeshkhind, Pune, Maharashtra, 411007, India
| | - Praneeta Pradip Bhavsar
- Proteomics Lab, National Centre for Cell Science, Ganeshkhind, Pune, Maharashtra, 411007, India
| | - Mahima Choudhari
- Proteomics Lab, National Centre for Cell Science, Ganeshkhind, Pune, Maharashtra, 411007, India
| | - Sadanand Bhanuse
- Proteomics Lab, National Centre for Cell Science, Ganeshkhind, Pune, Maharashtra, 411007, India
| | - Anup Tamhankar
- Department of Surgical Oncology, Deenanath Mangeshkar Hospital and Research Centre, Erandawne, Pune, Maharashtra, 411004, India
| | - Tufan Naiya
- Department of Biotechnology, Maulana Abul Kalam Azad University of Technology, West Bengal, NH12 Simhat, Haringhata, Nadia, West Bengal, 741249, India
| | - Bhargab Kalita
- Proteomics Lab, National Centre for Cell Science, Ganeshkhind, Pune, Maharashtra, 411007, India.
- Amrita School of Nanosciences and Molecular Medicine, Amrita Institute of Medical Sciences and Research Centre, Amrita Vishwa Vidyapeetham, Ponekkara, Kochi, Kerala, 682041, India.
| | - Srikanth Rapole
- Proteomics Lab, National Centre for Cell Science, Ganeshkhind, Pune, Maharashtra, 411007, India.
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Huang S, Yao D, Shan C, Du X, Pan L, Wang N, Wang Y, Duan X, Peng D. The protective mechanism of Tao Hong Si Wu decoction against breast cancer through regulation of EGFR/ERK1/2 signaling. JOURNAL OF ETHNOPHARMACOLOGY 2024; 332:118339. [PMID: 38777083 DOI: 10.1016/j.jep.2024.118339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 05/02/2024] [Accepted: 05/11/2024] [Indexed: 05/25/2024]
Abstract
ETHNOPHARMACOLOGICAL RELEVANCE Tao Hong Si Wu Decoction (THSWD), a traditional Chinese herbal medicine, is widely utilized in clinical settings, either alone or in combination with other medications, for the treatment of breast cancer. AIM OF THE STUDY The specific targeting molecule(s) of THSWD and its associated molecular mechanisms remain unclear. This research aims to elucidate the underlying molecular mechanisms of THSWD in the treatment of breast cancer. MATERIALS AND METHODS The pharmacological properties of THSWD were investigated in breast cancer cells and tumor tissues using a range of methods including Acridine Orange/Ethidium Bromide (AO/EB) staining, Transwell assay, flow cytometry, immunofluorescence assay, and breast cancer mice models. RESULTS Our findings demonstrate that THSWD induces necrosis and/or apoptosis in breast cancer cells, while significantly inhibiting cell migration. Target proteins of THSWD in anticancer activity include EGFR, RAS, and others. THSWD treatment for breast cancer is associated with the EGFR/ERK1/2 signaling pathway. CONCLUSION Our findings offer initial insights into the primary mechanism of action of THSWD in breast cancer treatment, indicating its potential as a complementary therapy deserving further investigation.
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Affiliation(s)
- Shi Huang
- The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, PR China; State Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing, PR China
| | - Dan Yao
- The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, PR China; College of Pharmacy, Anhui University of Chinese Medicine, Hefei, PR China
| | - Chun Shan
- State Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing, PR China
| | - Xiuli Du
- State Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing, PR China
| | - Linyu Pan
- The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, PR China
| | - Ni Wang
- The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, PR China; College of Pharmacy, Anhui University of Chinese Medicine, Hefei, PR China
| | - Yongzhong Wang
- The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, PR China
| | - Xianchun Duan
- The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, PR China.
| | - Daiyin Peng
- College of Pharmacy, Anhui University of Chinese Medicine, Hefei, PR China.
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Gupta A, Roy AM, Gupta K, Attwood K, Gandhi A, Edge S, Takabe K, Repasky E, Yao S, Gandhi S. Impact of environmental temperature on the survival outcomes of breast cancer: A SEER-based study. Breast Cancer Res Treat 2024:10.1007/s10549-024-07369-9. [PMID: 38767787 DOI: 10.1007/s10549-024-07369-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Accepted: 04/25/2024] [Indexed: 05/22/2024]
Abstract
BACKGROUND Experimental evidence in tumor-bearing mouse models shows that exposure to cool, that is, sub-thermoneutral environmental temperature is associated with a higher tumor growth rate and an immunosuppressive tumor immune microenvironment than seen at thermoneutral temperatures. However, the translational significance of these findings in humans is unclear. We hypothesized that breast cancer patients living in warmer climates will have better survival outcomes than patients living in colder climates. METHODS A retrospective population-based analysis was conducted on 270,496 stage I-III breast cancer patients, who were retrieved from the Surveillance, Epidemiology and End Results (SEER) over the period from 1996 to 2017. The average annual temperature (AAT) was calculated based on city level data from the National Centers for Environmental Information. RESULTS A total of 270, 496 patients were analyzed. Temperature as assessed in quartiles. After adjusting for potential confounders, patients who lived in the 3rd and 4th quartile temperature regions with AAT 56.7-62.5°F (3rd quartile) and > 62.5°F (4th quartile) had a 7% increase in the OS compared to patients living at AAT < 48.5°F (1st quartile) (HR 0.93, 95% CI 0.90-0.95 and HR 0.93, 95% CI 0.91-0.96, respectively). For DSS, When comparing AAT quartiles, patients living with AAT in the range of 56.7-62.5°F and > 62.5°F demonstrated a 7% increase each in DSS after adjustment (HR 0.93, 95% CI 0.90-0.96 and HR 0.93, 95% CI 0.90-0.96). CONCLUSIONS Higher environmental temperatures are associated with significantly better OS and DSS in breast cancer patients. Future research is warranted to confirm this observation using large datasets to elucidate the underlying mechanisms and investigate novel therapeutic strategies to minimize this geographic disparity in clinical outcomes.
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Affiliation(s)
- Ashish Gupta
- Department of Medicine, Roswell Park Comprehensive Cancer Center, Elm and Carlton Streets, Buffalo, NY, 14203, USA
| | - Arya Mariam Roy
- Department of Medicine, Roswell Park Comprehensive Cancer Center, Elm and Carlton Streets, Buffalo, NY, 14203, USA
| | - Kush Gupta
- Department of Medicine, University of Massachusetts Medical School-Baystate, Springfield, MA, USA
| | - Kristopher Attwood
- Department of Biostatistics and Bioinformatics, Roswell Park Comprehensive Cancer Center, 665 Elm Street, Buffalo, NY, 14203, USA
| | - Asha Gandhi
- Department of Physiology, SGT University, Ghaziabad, India
| | - Stephen Edge
- Department of Surgical Oncology, Roswell Park Comprehensive Cancer Center, Elm and Carlton Streets, Buffalo, NY, 14203, USA
| | - Kazuaki Takabe
- Department of Surgical Oncology, Roswell Park Comprehensive Cancer Center, Elm and Carlton Streets, Buffalo, NY, 14203, USA
| | - Elizabeth Repasky
- Department of Immunology, Roswell Park Comprehensive Cancer Center, 665 Elm Street, Buffalo, NY, 14203, USA
| | - Song Yao
- Department of Cancer Prevention and Control, Roswell Park Comprehensive Cancer Center, 665 Elm Street, Buffalo, NY, 14203, USA
| | - Shipra Gandhi
- Department of Medicine, Roswell Park Comprehensive Cancer Center, Elm and Carlton Streets, Buffalo, NY, 14203, USA.
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Patel R, Cooper DE, Kadakia KT, Allen A, Duan L, Luo L, Williams NT, Liu X, Locasale JW, Kirsch DG. Targeting glutamine metabolism improves sarcoma response to radiation therapy in vivo. Commun Biol 2024; 7:608. [PMID: 38769385 PMCID: PMC11106276 DOI: 10.1038/s42003-024-06262-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 04/29/2024] [Indexed: 05/22/2024] Open
Abstract
Diverse tumor metabolic phenotypes are influenced by the environment and genetic lesions. Whether these phenotypes extend to rhabdomyosarcoma (RMS) and how they might be leveraged to design new therapeutic approaches remains an open question. Thus, we utilized a Pax7Cre-ER-T2/+; NrasLSL-G12D/+; p53fl/fl (P7NP) murine model of sarcoma with mutations that most frequently occur in human embryonal RMS. To study metabolism, we infuse 13C-labeled glucose or glutamine into mice with sarcomas and show that sarcomas consume more glucose and glutamine than healthy muscle tissue. However, we reveal a marked shift from glucose consumption to glutamine metabolism after radiation therapy (RT). In addition, we show that inhibiting glutamine, either through genetic deletion of glutaminase (Gls1) or through pharmacological inhibition of glutaminase, leads to significant radiosensitization in vivo. This causes a significant increase in overall survival for mice with Gls1-deficient compared to Gls1-proficient sarcomas. Finally, Gls1-deficient sarcomas post-RT elevate levels of proteins involved in natural killer cell and interferon alpha/gamma responses, suggesting a possible role of innate immunity in the radiosensitization of Gls1-deficient sarcomas. Thus, our results indicate that glutamine contributes to radiation response in a mouse model of RMS.
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Affiliation(s)
- Rutulkumar Patel
- Department of Radiation Oncology, Baylor College of Medicine, 7200 Cambridge St, Houston, TX, 77030, USA
| | - Daniel E Cooper
- Department of Radiation Oncology, Duke University, Box 3085, Duke Cancer Center, Medicine Circle, Durham, NC, 27710, USA
| | - Kushal T Kadakia
- Department of Radiation Oncology, Duke University, Box 3085, Duke Cancer Center, Medicine Circle, Durham, NC, 27710, USA
| | - Annamarie Allen
- Department of Pharmacology and Cancer Biology, Duke University, Box 3813, 308 Research Drive, Durham, NC, 27710, USA
| | - Likun Duan
- Department of Pharmacology and Cancer Biology, Duke University, Box 3813, 308 Research Drive, Durham, NC, 27710, USA
- Department of Molecular and Structural Biochemistry, NC State University, Box 7622, 128 Polk Hall, Raleigh, NC, 27695, USA
| | - Lixia Luo
- Department of Radiation Oncology, Duke University, Box 3085, Duke Cancer Center, Medicine Circle, Durham, NC, 27710, USA
| | - Nerissa T Williams
- Department of Radiation Oncology, Duke University, Box 3085, Duke Cancer Center, Medicine Circle, Durham, NC, 27710, USA
| | - Xiaojing Liu
- Department of Molecular and Structural Biochemistry, NC State University, Box 7622, 128 Polk Hall, Raleigh, NC, 27695, USA
| | - Jason W Locasale
- Department of Pharmacology and Cancer Biology, Duke University, Box 3813, 308 Research Drive, Durham, NC, 27710, USA
- Department of Molecular and Structural Biochemistry, NC State University, Box 7622, 128 Polk Hall, Raleigh, NC, 27695, USA
| | - David G Kirsch
- Department of Radiation Oncology, Duke University, Box 3085, Duke Cancer Center, Medicine Circle, Durham, NC, 27710, USA.
- Department of Pharmacology and Cancer Biology, Duke University, Box 3813, 308 Research Drive, Durham, NC, 27710, USA.
- Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, 610 University Avenue, Toronto, ON, M5G 2M9, Canada.
- Department of Radiation Oncology, University of Toronto, 149 College Street, Suite 504, Toronto, ON, M5T 1P5, Canada.
- Department of Medical Biophysics, University of Toronto, 101 College Street, Room 15-701, Toronto, ON, M5G 1L7, Canada.
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Zhang XY, Shi JB, Jin SF, Wang RJ, Li MY, Zhang ZY, Yang X, Ma HL. Metabolic landscape of head and neck squamous cell carcinoma informs a novel kynurenine/Siglec-15 axis in immune escape. Cancer Commun (Lond) 2024. [PMID: 38734931 DOI: 10.1002/cac2.12545] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 03/30/2024] [Accepted: 04/18/2024] [Indexed: 05/13/2024] Open
Abstract
BACKGROUND Metabolic reprograming and immune escape are two hallmarks of cancer. However, how metabolic disorders drive immune escape in head and neck squamous cell carcinoma (HNSCC) remains unclear. Therefore, the aim of the present study was to investigate the metabolic landscape of HNSCC and its mechanism of driving immune escape. METHODS Analysis of paired tumor tissues and adjacent normal tissues from 69 HNSCC patients was performed using liquid/gas chromatography-mass spectrometry and RNA-sequencing. The tumor-promoting function of kynurenine (Kyn) was explored in vitro and in vivo. The downstream target of Kyn was investigated in CD8+ T cells. The regulation of CD8+ T cells was investigated after Siglec-15 overexpression in vivo. An engineering nanoparticle was established to deliver Siglec-15 small interfering RNA (siS15), and its association with immunotherapy response were investigated. The association between Siglec-15 and CD8+ programmed cell death 1 (PD-1)+ T cells was analyzed in a HNSCC patient cohort. RESULTS A total of 178 metabolites showed significant dysregulation in HNSCC, including carbohydrates, lipids and lipid-like molecules, and amino acids. Among these, amino acid metabolism was the most significantly altered, especially Kyn, which promoted tumor proliferation and metastasis. In addition, most immune checkpoint molecules were upregulated in Kyn-high patients based on RNA-sequencing. Furthermore, tumor-derived Kyn was transferred into CD8+ T cells and induced T cell functional exhaustion, and blocking Kyn transporters restored its killing activity. Accroding to the results, mechanistically, Kyn transcriptionally regulated the expression of Siglec-15 via aryl hydrocarbon receptor (AhR), and overexpression of Siglec-15 promoted immune escape by suppressing T cell infiltration and activation. Targeting AhR in vivo reduced Kyn-mediated Siglec-15 expression and promoted intratumoral CD8+ T cell infiltration and killing capacity. Finally, a NH2-modified mesoporous silica nanoparticle was designed to deliver siS15, which restored CD8+ T cell function status and enhanced anti-PD-1 efficacy in tumor-bearing immunocompetent mice. Clinically, Siglec-15 was positively correlated with AhR expression and CD8+PD-1+ T cell infiltration in HNSCC tissues. CONCLUSIONS The findings describe the metabolic landscape of HNSCC comprehensively and reveal that the Kyn/Siglec-15 axis may be a novel potential immunometabolism mechanism, providing a promising therapeutic strategy for cancers.
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Affiliation(s)
- Xin-Yu Zhang
- Department of Oral Maxillofacial-Head and Neck Oncology, Shanghai Ninth People's Hospital, College of Stomatology, Shanghai Jiao Tong University School of Medicine, Shanghai, P. R. China
- National Clinical Research Center for Oral Diseases, Shanghai, P. R. China
- Shanghai Key Laboratory of Stomatology & Shanghai Research Institute of Stomatology, Shanghai, P. R. China
| | - Jian-Bo Shi
- Department of Oral Maxillofacial-Head and Neck Oncology, Shanghai Ninth People's Hospital, College of Stomatology, Shanghai Jiao Tong University School of Medicine, Shanghai, P. R. China
- National Clinical Research Center for Oral Diseases, Shanghai, P. R. China
- Shanghai Key Laboratory of Stomatology & Shanghai Research Institute of Stomatology, Shanghai, P. R. China
| | - Shu-Fang Jin
- National Clinical Research Center for Oral Diseases, Shanghai, P. R. China
- Shanghai Key Laboratory of Stomatology & Shanghai Research Institute of Stomatology, Shanghai, P. R. China
- Department of Second Dental Center, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine; College of Stomatology, Shanghai Jiao Tong University, Shanghai, P. R. China
| | - Rui-Jie Wang
- Department of Oral Maxillofacial-Head and Neck Oncology, Shanghai Ninth People's Hospital, College of Stomatology, Shanghai Jiao Tong University School of Medicine, Shanghai, P. R. China
- National Clinical Research Center for Oral Diseases, Shanghai, P. R. China
- Shanghai Key Laboratory of Stomatology & Shanghai Research Institute of Stomatology, Shanghai, P. R. China
| | - Ming-Yu Li
- Department of Oral Maxillofacial-Head and Neck Oncology, Shanghai Ninth People's Hospital, College of Stomatology, Shanghai Jiao Tong University School of Medicine, Shanghai, P. R. China
- National Clinical Research Center for Oral Diseases, Shanghai, P. R. China
- Shanghai Key Laboratory of Stomatology & Shanghai Research Institute of Stomatology, Shanghai, P. R. China
| | - Zhi-Yuan Zhang
- Department of Oral Maxillofacial-Head and Neck Oncology, Shanghai Ninth People's Hospital, College of Stomatology, Shanghai Jiao Tong University School of Medicine, Shanghai, P. R. China
- National Clinical Research Center for Oral Diseases, Shanghai, P. R. China
- Shanghai Key Laboratory of Stomatology & Shanghai Research Institute of Stomatology, Shanghai, P. R. China
| | - Xi Yang
- Department of Oral Maxillofacial-Head and Neck Oncology, Shanghai Ninth People's Hospital, College of Stomatology, Shanghai Jiao Tong University School of Medicine, Shanghai, P. R. China
- National Clinical Research Center for Oral Diseases, Shanghai, P. R. China
- Shanghai Key Laboratory of Stomatology & Shanghai Research Institute of Stomatology, Shanghai, P. R. China
| | - Hai-Long Ma
- Department of Oral Maxillofacial-Head and Neck Oncology, Shanghai Ninth People's Hospital, College of Stomatology, Shanghai Jiao Tong University School of Medicine, Shanghai, P. R. China
- National Clinical Research Center for Oral Diseases, Shanghai, P. R. China
- Shanghai Key Laboratory of Stomatology & Shanghai Research Institute of Stomatology, Shanghai, P. R. China
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9
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Tang J, Liu Y, Wang Y, Zhang Z, Nie J, Wang X, Ai S, Li J, Gao Y, Li C, Cheng C, Su S, Chen S, Zhang P, Lu R. Deciphering metabolic heterogeneity in retinoblastoma unravels the role of monocarboxylate transporter 1 in tumor progression. Biomark Res 2024; 12:48. [PMID: 38730450 PMCID: PMC11088057 DOI: 10.1186/s40364-024-00596-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2024] [Accepted: 05/02/2024] [Indexed: 05/12/2024] Open
Abstract
BACKGROUND Tumors exhibit metabolic heterogeneity, influencing cancer progression. However, understanding metabolic diversity in retinoblastoma (RB), the primary intraocular malignancy in children, remains limited. METHODS The metabolic landscape of RB was constructed based on single-cell transcriptomic sequencing from 11 RB and 5 retina samples. Various analyses were conducted, including assessing overall metabolic activity, metabolic heterogeneity, and the correlation between hypoxia and metabolic pathways. Additionally, the expression pattern of the monocarboxylate transporter (MCT) family in different cell clusters was examined. Validation assays of MCT1 expression and function in RB cell lines were performed. The therapeutic potential of targeting MCT1 was evaluated using an orthotopic xenograft model. A cohort of 47 RB patients was analyzed to evaluate the relationship between MCT1 expression and tumor invasion. RESULTS Distinct metabolic patterns in RB cells, notably increased glycolysis, were identified. This metabolic heterogeneity correlated closely with hypoxia. MCT1 emerged as the primary monocarboxylate transporter in RB cells. Disrupting MCT1 altered cell viability and energy metabolism. In vivo studies using the MCT1 inhibitor AZD3965 effectively suppressed RB tumor growth. Additionally, a correlation between MCT1 expression and optic nerve invasion in RB samples suggested prognostic implications. CONCLUSIONS This study enhances our understanding of RB metabolic characteristics at the single-cell level, highlighting the significance of MCT1 in RB pathogenesis. Targeting MCT1 holds promise as a therapeutic strategy for combating RB, with potential prognostic implications.
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Affiliation(s)
- Junjie Tang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China
| | - Yaoming Liu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China
| | - Yinghao Wang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China
| | - Zhihui Zhang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China
| | - Jiahe Nie
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China
| | - Xinyue Wang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China
| | - Siming Ai
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China
| | - Jinmiao Li
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China
| | - Yang Gao
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China
| | - Cheng Li
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China
| | - Chao Cheng
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China
| | - Shicai Su
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China
| | - Shuxia Chen
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China
| | - Ping Zhang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China
| | - Rong Lu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China.
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10
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Zheng W, Tang X, Dong J, Feng J, Chen M, Zhu X. Metabolomic screening of radioiodine refractory thyroid cancer patients and the underlying chemical mechanism of iodine resistance. Sci Rep 2024; 14:10546. [PMID: 38719979 PMCID: PMC11079026 DOI: 10.1038/s41598-024-61067-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Accepted: 04/30/2024] [Indexed: 05/12/2024] Open
Abstract
Radioiodine refractory (RAIR) patients do not benefit from iodine-131 therapy. Thus, timely identification of RAIR patients is critical for avoiding ineffective radioactive iodine therapy. In addition, determining the causes of iodine resistance will facilitate the development of novel treatment strategies. This study was comprised of 20 RAIR and 14 non-radioiodine refractory (non-RAIR) thyroid cancer patients. Liquid chromatography-mass spectrometry was used to identify differences in the serum metabolites of RAIR and non-RAIR patients. In addition, chemical assays were performed to determine the effects of the differential metabolites on iodine uptake. Metabolic pathway enrichment analysis of the differential metabolites revealed significant differences in the phenylalanine and tyrosine metabolic pathways. Notably, quinate and shikimic acid, metabolites of the tyrosine pathway, were significantly increased in the RAIR group. In contrast, the phenylalanine pathway metabolites, hippuric acid and 2-phenylacetamide, were markedly decreased in the RAIR group. Thyroid peroxidase plays an important role in catalyzing the iodination of tyrosine residues, while the ionic state of iodine promotes the iodination reaction. Quinate, shikimic acid, hippuric acid, and 2-phenylacetamide were found to be involved in the iodination of tyrosine, which is a key step in thyroid hormone synthesis. Specifically, quinate and shikimic acid were found to inhibit iodination, while hippuric acid and 2-phenylacetamide promoted iodination. Abnormalities in phenylalanine and tyrosine metabolic pathways are closely associated with iodine resistance. Tyrosine is required for thyroid hormone synthesis and could be a potential cause of iodine resistance.
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Affiliation(s)
- Weihui Zheng
- Key Laboratory of Head and Neck Cancer Translational Research of Zhejiang Province, Zhejiang Cancer Hospital, Hangzhou, 310022, Zhejiang, China
- Thyroid Surgery Department, Zhejiang Cancer Hospital, Hangzhou, 310022, Zhejiang, China
| | - Xi Tang
- Key Laboratory of Head and Neck Cancer Translational Research of Zhejiang Province, Zhejiang Cancer Hospital, Hangzhou, 310022, Zhejiang, China
| | - Jinyun Dong
- Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, 310018, Zhejiang, China
| | - Jianguo Feng
- Institute of Research Center, Zhejiang Cancer Hospital, Hangzhou, 310022, Zhejiang, China
| | - Min Chen
- Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, 310018, Zhejiang, China.
- Chongqing Institute of Advanced Pathology, Jinfeng Laboratory, Chongqing, 401329, China.
| | - Xin Zhu
- Key Laboratory of Head and Neck Cancer Translational Research of Zhejiang Province, Zhejiang Cancer Hospital, Hangzhou, 310022, Zhejiang, China.
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11
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Lin C, Tian Q, Guo S, Xie D, Cai Y, Wang Z, Chu H, Qiu S, Tang S, Zhang A. Metabolomics for Clinical Biomarker Discovery and Therapeutic Target Identification. Molecules 2024; 29:2198. [PMID: 38792060 PMCID: PMC11124072 DOI: 10.3390/molecules29102198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2024] [Revised: 04/10/2024] [Accepted: 04/25/2024] [Indexed: 05/26/2024] Open
Abstract
As links between genotype and phenotype, small-molecule metabolites are attractive biomarkers for disease diagnosis, prognosis, classification, drug screening and treatment, insight into understanding disease pathology and identifying potential targets. Metabolomics technology is crucial for discovering targets of small-molecule metabolites involved in disease phenotype. Mass spectrometry-based metabolomics has implemented in applications in various fields including target discovery, explanation of disease mechanisms and compound screening. It is used to analyze the physiological or pathological states of the organism by investigating the changes in endogenous small-molecule metabolites and associated metabolism from complex metabolic pathways in biological samples. The present review provides a critical update of high-throughput functional metabolomics techniques and diverse applications, and recommends the use of mass spectrometry-based metabolomics for discovering small-molecule metabolite signatures that provide valuable insights into metabolic targets. We also recommend using mass spectrometry-based metabolomics as a powerful tool for identifying and understanding metabolic patterns, metabolic targets and for efficacy evaluation of herbal medicine.
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Affiliation(s)
- Chunsheng Lin
- Graduate School and Second Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin 150040, China; (C.L.); (S.G.); (Y.C.); (Z.W.)
| | - Qianqian Tian
- Faculty of Social Sciences, The University of Hong Kong, Hong Kong 999077, China;
| | - Sifan Guo
- Graduate School and Second Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin 150040, China; (C.L.); (S.G.); (Y.C.); (Z.W.)
- International Advanced Functional Omics Platform, Scientific Experiment Center, International Joint Research Center on Traditional Chinese and Modern Medicine, Hainan Engineering Research Center for Biological Sample Resources of Major Diseases (First Affiliated Hospital of Hainan Medical University), Key Laboratory of Tropical Cardiovascular Diseases Research of Hainan Province, Hainan Medical University, Xueyuan Road 3, Haikou 571199, China; (D.X.); (S.Q.); (S.T.)
| | - Dandan Xie
- International Advanced Functional Omics Platform, Scientific Experiment Center, International Joint Research Center on Traditional Chinese and Modern Medicine, Hainan Engineering Research Center for Biological Sample Resources of Major Diseases (First Affiliated Hospital of Hainan Medical University), Key Laboratory of Tropical Cardiovascular Diseases Research of Hainan Province, Hainan Medical University, Xueyuan Road 3, Haikou 571199, China; (D.X.); (S.Q.); (S.T.)
| | - Ying Cai
- Graduate School and Second Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin 150040, China; (C.L.); (S.G.); (Y.C.); (Z.W.)
- International Advanced Functional Omics Platform, Scientific Experiment Center, International Joint Research Center on Traditional Chinese and Modern Medicine, Hainan Engineering Research Center for Biological Sample Resources of Major Diseases (First Affiliated Hospital of Hainan Medical University), Key Laboratory of Tropical Cardiovascular Diseases Research of Hainan Province, Hainan Medical University, Xueyuan Road 3, Haikou 571199, China; (D.X.); (S.Q.); (S.T.)
| | - Zhibo Wang
- Graduate School and Second Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin 150040, China; (C.L.); (S.G.); (Y.C.); (Z.W.)
- International Advanced Functional Omics Platform, Scientific Experiment Center, International Joint Research Center on Traditional Chinese and Modern Medicine, Hainan Engineering Research Center for Biological Sample Resources of Major Diseases (First Affiliated Hospital of Hainan Medical University), Key Laboratory of Tropical Cardiovascular Diseases Research of Hainan Province, Hainan Medical University, Xueyuan Road 3, Haikou 571199, China; (D.X.); (S.Q.); (S.T.)
| | - Hang Chu
- Department of Biomedical Sciences, Beijing City University, Beijing 100193, China;
| | - Shi Qiu
- International Advanced Functional Omics Platform, Scientific Experiment Center, International Joint Research Center on Traditional Chinese and Modern Medicine, Hainan Engineering Research Center for Biological Sample Resources of Major Diseases (First Affiliated Hospital of Hainan Medical University), Key Laboratory of Tropical Cardiovascular Diseases Research of Hainan Province, Hainan Medical University, Xueyuan Road 3, Haikou 571199, China; (D.X.); (S.Q.); (S.T.)
| | - Songqi Tang
- International Advanced Functional Omics Platform, Scientific Experiment Center, International Joint Research Center on Traditional Chinese and Modern Medicine, Hainan Engineering Research Center for Biological Sample Resources of Major Diseases (First Affiliated Hospital of Hainan Medical University), Key Laboratory of Tropical Cardiovascular Diseases Research of Hainan Province, Hainan Medical University, Xueyuan Road 3, Haikou 571199, China; (D.X.); (S.Q.); (S.T.)
| | - Aihua Zhang
- Graduate School and Second Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin 150040, China; (C.L.); (S.G.); (Y.C.); (Z.W.)
- International Advanced Functional Omics Platform, Scientific Experiment Center, International Joint Research Center on Traditional Chinese and Modern Medicine, Hainan Engineering Research Center for Biological Sample Resources of Major Diseases (First Affiliated Hospital of Hainan Medical University), Key Laboratory of Tropical Cardiovascular Diseases Research of Hainan Province, Hainan Medical University, Xueyuan Road 3, Haikou 571199, China; (D.X.); (S.Q.); (S.T.)
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Al-Daffaie FM, Al-Mudhafar SF, Alhomsi A, Tarazi H, Almehdi AM, El-Huneidi W, Abu-Gharbieh E, Bustanji Y, Alqudah MAY, Abuhelwa AY, Guella A, Alzoubi KH, Semreen MH. Metabolomics and Proteomics in Prostate Cancer Research: Overview, Analytical Techniques, Data Analysis, and Recent Clinical Applications. Int J Mol Sci 2024; 25:5071. [PMID: 38791108 PMCID: PMC11120916 DOI: 10.3390/ijms25105071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Revised: 04/26/2024] [Accepted: 04/26/2024] [Indexed: 05/26/2024] Open
Abstract
Prostate cancer (PCa) is a significant global contributor to mortality, predominantly affecting males aged 65 and above. The field of omics has recently gained traction due to its capacity to provide profound insights into the biochemical mechanisms underlying conditions like prostate cancer. This involves the identification and quantification of low-molecular-weight metabolites and proteins acting as crucial biochemical signals for early detection, therapy assessment, and target identification. A spectrum of analytical methods is employed to discern and measure these molecules, revealing their altered biological pathways within diseased contexts. Metabolomics and proteomics generate refined data subjected to detailed statistical analysis through sophisticated software, yielding substantive insights. This review aims to underscore the major contributions of multi-omics to PCa research, covering its core principles, its role in tumor biology characterization, biomarker discovery, prognostic studies, various analytical technologies such as mass spectrometry and Nuclear Magnetic Resonance, data processing, and recent clinical applications made possible by an integrative "omics" approach. This approach seeks to address the challenges associated with current PCa treatments. Hence, our research endeavors to demonstrate the valuable applications of these potent tools in investigations, offering significant potential for understanding the complex biochemical environment of prostate cancer and advancing tailored therapeutic approaches for further development.
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Affiliation(s)
- Fatima M. Al-Daffaie
- Department of Medicinal Chemistry, College of Pharmacy, University of Sharjah, Sharjah 27272, United Arab Emirates; (F.M.A.-D.); (S.F.A.-M.); (A.A.); (H.T.); (A.M.A.)
- Research Institute of Medical and Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates; (W.E.-H.); (E.A.-G.); (A.Y.A.); (K.H.A.)
| | - Sara F. Al-Mudhafar
- Department of Medicinal Chemistry, College of Pharmacy, University of Sharjah, Sharjah 27272, United Arab Emirates; (F.M.A.-D.); (S.F.A.-M.); (A.A.); (H.T.); (A.M.A.)
| | - Aya Alhomsi
- Department of Medicinal Chemistry, College of Pharmacy, University of Sharjah, Sharjah 27272, United Arab Emirates; (F.M.A.-D.); (S.F.A.-M.); (A.A.); (H.T.); (A.M.A.)
| | - Hamadeh Tarazi
- Department of Medicinal Chemistry, College of Pharmacy, University of Sharjah, Sharjah 27272, United Arab Emirates; (F.M.A.-D.); (S.F.A.-M.); (A.A.); (H.T.); (A.M.A.)
- Research Institute of Medical and Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates; (W.E.-H.); (E.A.-G.); (A.Y.A.); (K.H.A.)
| | - Ahmed M. Almehdi
- Department of Medicinal Chemistry, College of Pharmacy, University of Sharjah, Sharjah 27272, United Arab Emirates; (F.M.A.-D.); (S.F.A.-M.); (A.A.); (H.T.); (A.M.A.)
- Research Institute of Medical and Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates; (W.E.-H.); (E.A.-G.); (A.Y.A.); (K.H.A.)
| | - Waseem El-Huneidi
- Research Institute of Medical and Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates; (W.E.-H.); (E.A.-G.); (A.Y.A.); (K.H.A.)
- Department of Basic Medical Sciences, College of Medicine, University of Sharjah, Sharjah 27272, United Arab Emirates;
| | - Eman Abu-Gharbieh
- Research Institute of Medical and Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates; (W.E.-H.); (E.A.-G.); (A.Y.A.); (K.H.A.)
- Department of Clinical Sciences, College of Medicine, University of Sharjah, Sharjah 27272, United Arab Emirates
- School of Pharmacy, The University of Jordan, Amman 11942, Jordan
| | - Yasser Bustanji
- Department of Basic Medical Sciences, College of Medicine, University of Sharjah, Sharjah 27272, United Arab Emirates;
- School of Pharmacy, The University of Jordan, Amman 11942, Jordan
| | - Mohammad A. Y. Alqudah
- Department of Pharmacy Practice and Pharmacotherapeutics, College of Pharmacy, University of Sharjah, Sharjah 27272, United Arab Emirates;
- Department of Clinical Pharmacy, Faculty of Pharmacy, Jordan University of Science and Technology, Irbid 22110, Jordan
| | - Ahmad Y. Abuhelwa
- Research Institute of Medical and Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates; (W.E.-H.); (E.A.-G.); (A.Y.A.); (K.H.A.)
- Department of Pharmacy Practice and Pharmacotherapeutics, College of Pharmacy, University of Sharjah, Sharjah 27272, United Arab Emirates;
| | - Adnane Guella
- Nephrology Department, University Hospital Sharjah, Sharjah 27272, United Arab Emirates;
| | - Karem H. Alzoubi
- Research Institute of Medical and Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates; (W.E.-H.); (E.A.-G.); (A.Y.A.); (K.H.A.)
- Department of Pharmacy Practice and Pharmacotherapeutics, College of Pharmacy, University of Sharjah, Sharjah 27272, United Arab Emirates;
| | - Mohammad H. Semreen
- Department of Medicinal Chemistry, College of Pharmacy, University of Sharjah, Sharjah 27272, United Arab Emirates; (F.M.A.-D.); (S.F.A.-M.); (A.A.); (H.T.); (A.M.A.)
- Research Institute of Medical and Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates; (W.E.-H.); (E.A.-G.); (A.Y.A.); (K.H.A.)
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Septaningsih DA, Suparto IH, Achmadi SS, Heryanto R, Rafi M. Untargeted metabolomics using UHPLC-Q-Orbitrap HRMS for identifying cytotoxic compounds on MCF-7 breast cancer cells from Annona muricata Linn leaf extracts as potential anticancer agents. PHYTOCHEMICAL ANALYSIS : PCA 2024. [PMID: 38708435 DOI: 10.1002/pca.3373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Accepted: 04/21/2024] [Indexed: 05/07/2024]
Abstract
INTRODUCTION The leaves of Annona muricata L., known as "soursop" or "sirsak" in Indonesia, are used traditionally for cancer treatment. However, the bioactive components remain largely unidentified. OBJECTIVE This study used untargeted liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based metabolomics to identify potential cytotoxic compounds in A. muricata leaf extracts on MCF-7 breast cancer cells in vitro. METHODS A. muricata leaves were macerated with water, 99% ethanol, and aqueous mixtures containing 30%, 50%, and 80% ethanol. Cytotoxic activity of the extracts against MCF-7 breast cancer cells was determined using the MTT assay. Ultra-high-performance liquid chromatography-Q-Orbitrap high-resolution mass spectroscopy (UHPLC-Q-Orbitrap-HRMS) was used to characterize the metabolite composition of each extract. The correlations between metabolite profile and cytotoxic activities were evaluated using orthogonal partial least square discriminant analysis (OPLS-DA). The binding of these bioactive compounds to the tumorigenic alpha-estrogen receptor (3ERT) was then evaluated by in silico docking simulations. RESULTS Ninety-nine percent ethanol extracts demonstrated the greatest potency for reducing MCF-7 cell viability (IC50 = 22 μg/ml). We detected 35 metabolites in ethanol extracts, including alkaloids, flavonoids, and acetogenins. OPLS-DA predicted that annoreticuin, squadiolin C, and xylopine, and six unknown acetogenin metabolites, might reduce MCF-7 cell viability. In silico analysis predicted that annoreticuin, squadiolin C, and xylopine bind to 3ERT with an affinity comparable to doxorubicin. CONCLUSION Untargeted metabolomics and in silico modeling identified cytotoxic compounds on MCF-7 cells and binding affinity to 3ERT in A. muricata leaf extracts. The findings need to be further verified to prove the screening results.
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Affiliation(s)
- Dewi Anggraini Septaningsih
- Department of Chemistry, Faculty of Mathematics and Natural Sciences, IPB University, Bogor, Indonesia
- Advance Research Laboratory, IPB University, Bogor, Indonesia
- Department of Chemistry, Faculty of Military Mathematics and Natural Sciences, Indonesian Defense University, Bogor, Indonesia
| | - Irma Herawati Suparto
- Department of Chemistry, Faculty of Mathematics and Natural Sciences, IPB University, Bogor, Indonesia
- Tropical Biopharmaca Research Center, IPB University, Bogor, Indonesia
- Primate Research Center, IPB University, Bogor, Indonesia
| | - Suminar Setiati Achmadi
- Department of Chemistry, Faculty of Mathematics and Natural Sciences, IPB University, Bogor, Indonesia
- Tropical Biopharmaca Research Center, IPB University, Bogor, Indonesia
| | - Rudi Heryanto
- Department of Chemistry, Faculty of Mathematics and Natural Sciences, IPB University, Bogor, Indonesia
- Advance Research Laboratory, IPB University, Bogor, Indonesia
- Tropical Biopharmaca Research Center, IPB University, Bogor, Indonesia
| | - Mohamad Rafi
- Department of Chemistry, Faculty of Mathematics and Natural Sciences, IPB University, Bogor, Indonesia
- Advance Research Laboratory, IPB University, Bogor, Indonesia
- Tropical Biopharmaca Research Center, IPB University, Bogor, Indonesia
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Li S, Che J, Gu B, Li Y, Han X, Sun T, Pan K, Lv J, Zhang S, Wang C, Zhang T, Wang J, Xue F. Metabolites, Healthy Lifestyle, and Polygenic Risk Score Associated with Upper Gastrointestinal Cancer: Findings from the UK Biobank Study. J Proteome Res 2024; 23:1679-1688. [PMID: 38546438 DOI: 10.1021/acs.jproteome.3c00827] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/04/2024]
Abstract
Previous metabolomics studies have highlighted the predictive value of metabolites on upper gastrointestinal (UGI) cancer, while most of them ignored the potential effects of lifestyle and genetic risk on plasma metabolites. This study aimed to evaluate the role of lifestyle and genetic risk in the metabolic mechanism of UGI cancer. Differential metabolites of UGI cancer were identified using partial least-squares discriminant analysis and the Wilcoxon test. Then, we calculated the healthy lifestyle index (HLI) score and polygenic risk score (PRS) and divided them into three groups, respectively. A total of 15 metabolites were identified as UGI-cancer-related differential metabolites. The metabolite model (AUC = 0.699) exhibited superior discrimination ability compared to those of the HLI model (AUC = 0.615) and the PRS model (AUC = 0.593). Moreover, subgroup analysis revealed that the metabolite model showed higher discrimination ability for individuals with unhealthy lifestyles compared to that with healthy individuals (AUC = 0.783 vs 0.684). Furthermore, in the genetic risk subgroup analysis, individuals with a genetic predisposition to UGI cancer exhibited the best discriminative performance in the metabolite model (AUC = 0.770). These findings demonstrated the clinical significance of metabolic biomarkers in UGI cancer discrimination, especially in individuals with unhealthy lifestyles and a high genetic risk.
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Affiliation(s)
- Shuting Li
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan 250012, China
| | - Jiajing Che
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan 250012, China
| | - Bingbing Gu
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan 250012, China
| | - Yunfei Li
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan 250012, China
| | - Xinyue Han
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan 250012, China
| | - Tiantian Sun
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan 250012, China
| | - Keyu Pan
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan 250012, China
| | - Jiali Lv
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan 250012, China
| | - Shuai Zhang
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan 250012, China
| | - Cheng Wang
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan 250012, China
| | - Tao Zhang
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan 250012, China
| | - Jialin Wang
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, China
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan 250117, China
| | - Fuzhong Xue
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, China
- Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan 250012, China
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15
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Fu Y, Wang C, Wu Z, Zhang X, Liu Y, Wang X, Liu F, Chen Y, Zhang Y, Zhao H, Wang Q. Discovery of the potential biomarkers for early diagnosis of endometrial cancer via integrating metabolomics and transcriptomics. Comput Biol Med 2024; 173:108327. [PMID: 38552279 DOI: 10.1016/j.compbiomed.2024.108327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Revised: 03/07/2024] [Accepted: 03/17/2024] [Indexed: 04/17/2024]
Abstract
Endometrial cancer (EC) is one of the most common malignant tumors in women, and the increasing incidence and mortality pose a serious threat to the public health. Early diagnosis of EC could prolong the survival period and optimize the survivorship, greatly alleviating patients' suffering and social medical pressure. In this study, we collected urine and serum samples from the recruited patients, analyzed the samples using LC-MS approach, and identified the differential metabolites through metabolomic analysis. Then, the differentially expressed genes were identified through the systematic transcriptomic analysis of EC-related dataset from Gene Expression Omnibus (GEO), followed by network profiling of metabolic-reaction-enzyme-gene. In this experiment, a total of 83 differential metabolites and 19 hub genes were discovered, of which 10 different metabolites and 3 hub genes were further evaluated as more potential biomarkers based on network analysis. According to the KEGG enrichment analysis, the potential biomarkers and gene-encoded proteins were found to be involved in the arginine and proline metabolism, histidine metabolism, and pyrimidine metabolism, which was of significance for the early diagnosis of EC. In particular, the combination of metabolites (histamine, 1-methylhistamine, and methylimidazole acetaldehyde) as well as the combination of RRM2, TYMS and TK1 exerted more accurate discrimination abilities between EC and healthy groups, providing more criteria for the early diagnosis of EC.
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Affiliation(s)
- Yan Fu
- School of Pharmacy, Hebei Medical University, Shijiazhuang, 050017, China; Core Facilities and Centers, Hebei Medical University, Shijiazhuang, 050017, China
| | - Chengzhao Wang
- College of Basic Medicine, Hebei Medical University, Shijiazhuang, 050017, China
| | - Zhimin Wu
- School of Pharmacy, Hebei Medical University, Shijiazhuang, 050017, China
| | - Xiaoguang Zhang
- Core Facilities and Centers, Hebei Medical University, Shijiazhuang, 050017, China; College of Basic Medicine, Hebei Medical University, Shijiazhuang, 050017, China
| | - Yan Liu
- School of Pharmacy, Hebei Medical University, Shijiazhuang, 050017, China
| | - Xu Wang
- School of Pharmacy, Hebei Medical University, Shijiazhuang, 050017, China
| | - Fangfang Liu
- School of Pharmacy, Hebei Medical University, Shijiazhuang, 050017, China
| | - Yujuan Chen
- School of Pharmacy, Hebei Medical University, Shijiazhuang, 050017, China
| | - Yang Zhang
- School of Pharmacy, Hebei Medical University, Shijiazhuang, 050017, China.
| | - Huanhuan Zhao
- Department of Obstetrics and Gynecology, The Fourth Hospital of Hebei Medical University, 050011, China.
| | - Qiao Wang
- School of Pharmacy, Hebei Medical University, Shijiazhuang, 050017, China.
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16
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Zhang J, Teng F, Hu B, Liu W, Huang Y, Wu J, Wang Y, Su H, Yang S, Zhang L, Guo L, Lei Z, Yan M, Xu X, Wang R, Bao Q, Dong Q, Long J, Qian K. Early Diagnosis and Prognosis Prediction of Pancreatic Cancer Using Engineered Hybrid Core-Shells in Laser Desorption/Ionization Mass Spectrometry. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024; 36:e2311431. [PMID: 38241281 DOI: 10.1002/adma.202311431] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 01/11/2024] [Indexed: 01/21/2024]
Abstract
Effective detection of bio-molecules relies on the precise design and preparation of materials, particularly in laser desorption/ionization mass spectrometry (LDI-MS). Despite significant advancements in substrate materials, the performance of single-structured substrates remains suboptimal for LDI-MS analysis of complex systems. Herein, designer Au@SiO2@ZrO2 core-shell substrates are developed for LDI-MS-based early diagnosis and prognosis of pancreatic cancer (PC). Through controlling Au core size and ZrO2 shell crystallization, signal amplification of metabolites up to 3 orders is not only achieved, but also the synergistic mechanism of the LDI process is revealed. The optimized Au@SiO2@ZrO2 enables a direct record of serum metabolic fingerprints (SMFs) by LDI-MS. Subsequently, SMFs are employed to distinguish early PC (stage I/II) from controls, with an accuracy of 92%. Moreover, a prognostic prediction scoring system is established with enhanced efficacy in predicting PC survival compared to CA19-9 (p < 0.05). This work contributes to material-based cancer diagnosis and prognosis.
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Affiliation(s)
- Juxiang Zhang
- State Key Laboratory of Systems Medicine for Cancer, School of Biomedical Engineering, Institute of Medical Robotics and Shanghai Academy of Experimental Medicine, Shanghai Jiao Tong University, Shanghai, 200030, China
- Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China
| | - Fei Teng
- Department of Gastrointestinal Surgery, Minhang Hospital, Fudan University, Shanghai, 201199, China
- Key Laboratory of Whole-Period Monitoring and Precise Intervention of Digestive Cancer, Shanghai Municipal Health Commission, Minhang Hospital, Fudan University, Shanghai, 201199, China
| | - Beiyuan Hu
- Department of Pancreatic Surgery, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200080, China
| | - Wanshan Liu
- State Key Laboratory of Systems Medicine for Cancer, School of Biomedical Engineering, Institute of Medical Robotics and Shanghai Academy of Experimental Medicine, Shanghai Jiao Tong University, Shanghai, 200030, China
- Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China
| | - Yida Huang
- State Key Laboratory of Systems Medicine for Cancer, School of Biomedical Engineering, Institute of Medical Robotics and Shanghai Academy of Experimental Medicine, Shanghai Jiao Tong University, Shanghai, 200030, China
- Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China
| | - Jiao Wu
- State Key Laboratory of Systems Medicine for Cancer, School of Biomedical Engineering, Institute of Medical Robotics and Shanghai Academy of Experimental Medicine, Shanghai Jiao Tong University, Shanghai, 200030, China
- Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China
| | - Yuning Wang
- State Key Laboratory of Systems Medicine for Cancer, School of Biomedical Engineering, Institute of Medical Robotics and Shanghai Academy of Experimental Medicine, Shanghai Jiao Tong University, Shanghai, 200030, China
- Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China
| | - Haiyang Su
- State Key Laboratory of Systems Medicine for Cancer, School of Biomedical Engineering, Institute of Medical Robotics and Shanghai Academy of Experimental Medicine, Shanghai Jiao Tong University, Shanghai, 200030, China
- Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China
| | - Shouzhi Yang
- State Key Laboratory of Systems Medicine for Cancer, School of Biomedical Engineering, Institute of Medical Robotics and Shanghai Academy of Experimental Medicine, Shanghai Jiao Tong University, Shanghai, 200030, China
- Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China
| | - Lumin Zhang
- Key Laboratory of Whole-Period Monitoring and Precise Intervention of Digestive Cancer, Shanghai Municipal Health Commission, Minhang Hospital, Fudan University, Shanghai, 201199, China
| | - Lingchuan Guo
- Department of Pathology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, 215006, China
| | - Zhe Lei
- Department of Pathology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, 215006, China
| | - Meng Yan
- Department of Pathology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, 215006, China
| | - Xiaoyu Xu
- State Key Laboratory of Systems Medicine for Cancer, School of Biomedical Engineering, Institute of Medical Robotics and Shanghai Academy of Experimental Medicine, Shanghai Jiao Tong University, Shanghai, 200030, China
- Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China
| | - Ruimin Wang
- State Key Laboratory of Systems Medicine for Cancer, School of Biomedical Engineering, Institute of Medical Robotics and Shanghai Academy of Experimental Medicine, Shanghai Jiao Tong University, Shanghai, 200030, China
- Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China
| | - Qingui Bao
- Fosun Diagnostics (Shanghai) Co., Ltd, Shanghai, 200435, China
| | - Qiongzhu Dong
- Key Laboratory of Whole-Period Monitoring and Precise Intervention of Digestive Cancer, Shanghai Municipal Health Commission, Minhang Hospital, Fudan University, Shanghai, 201199, China
| | - Jiang Long
- Department of Pancreatic Surgery, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200080, China
| | - Kun Qian
- State Key Laboratory of Systems Medicine for Cancer, School of Biomedical Engineering, Institute of Medical Robotics and Shanghai Academy of Experimental Medicine, Shanghai Jiao Tong University, Shanghai, 200030, China
- Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China
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17
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Berrell N, Sadeghirad H, Blick T, Bidgood C, Leggatt GR, O'Byrne K, Kulasinghe A. Metabolomics at the tumor microenvironment interface: Decoding cellular conversations. Med Res Rev 2024; 44:1121-1146. [PMID: 38146814 DOI: 10.1002/med.22010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Revised: 11/08/2023] [Accepted: 12/07/2023] [Indexed: 12/27/2023]
Abstract
Cancer heterogeneity remains a significant challenge for effective cancer treatments. Altered energetics is one of the hallmarks of cancer and influences tumor growth and drug resistance. Studies have shown that heterogeneity exists within the metabolic profile of tumors, and personalized-combination therapy with relevant metabolic interventions could improve patient response. Metabolomic studies are identifying novel biomarkers and therapeutic targets that have improved treatment response. The spatial location of elements in the tumor microenvironment are becoming increasingly important for understanding disease progression. The evolution of spatial metabolomics analysis now allows scientists to deeply understand how metabolite distribution contributes to cancer biology. Recently, these techniques have spatially resolved metabolite distribution to a subcellular level. It has been proposed that metabolite mapping could improve patient outcomes by improving precision medicine, enabling earlier diagnosis and intraoperatively identifying tumor margins. This review will discuss how altered metabolic pathways contribute to cancer progression and drug resistance and will explore the current capabilities of spatial metabolomics technologies and how these could be integrated into clinical practice to improve patient outcomes.
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Affiliation(s)
- Naomi Berrell
- Frazer Institute, Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia
| | - Habib Sadeghirad
- Frazer Institute, Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia
| | - Tony Blick
- Frazer Institute, Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia
| | - Charles Bidgood
- APCRC-Q, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Graham R Leggatt
- Frazer Institute, Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia
| | - Ken O'Byrne
- Princess Alexandra Hospital, Woolloongabba, Queensland, Australia
| | - Arutha Kulasinghe
- Frazer Institute, Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia
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18
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Chan DSM, Cariolou M, Markozannes G, Balducci K, Vieira R, Kiss S, Becerra-Tomás N, Aune D, Greenwood DC, González-Gil EM, Copson E, Renehan AG, Bours M, Demark-Wahnefried W, Hudson MM, May AM, Odedina FT, Skinner R, Steindorf K, Tjønneland A, Velikova G, Baskin ML, Chowdhury R, Hill L, Lewis SJ, Seidell J, Weijenberg MP, Krebs J, Cross AJ, Tsilidis KK. Post-diagnosis dietary factors, supplement use and colorectal cancer prognosis: A Global Cancer Update Programme (CUP Global) systematic literature review and meta-analysis. Int J Cancer 2024. [PMID: 38692645 DOI: 10.1002/ijc.34906] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Revised: 12/15/2023] [Accepted: 01/17/2024] [Indexed: 05/03/2024]
Abstract
The role of diet in colorectal cancer prognosis is not well understood and specific lifestyle recommendations are lacking. We searched for randomised controlled trials (RCTs) and longitudinal observational studies on post-diagnosis dietary factors, supplement use and colorectal cancer survival outcomes in PubMed and Embase from inception until 28th February 2022. Random-effects dose-response meta-analyses were conducted when at least three studies had sufficient information. The evidence was interpreted and graded by the CUP Global independent Expert Committee on Cancer Survivorship and Expert Panel. Five RCTs and 35 observational studies were included (30,242 cases, over 8700 all-cause and 2100 colorectal cancer deaths, 3700 progression, recurrence, or disease-free events). Meta-analyses, including 3-10 observational studies each, were conducted for: whole grains, nuts/peanuts, red and processed meat, dairy products, sugary drinks, artificially sweetened beverages, coffee, alcohol, dietary glycaemic load/index, insulin load/index, marine omega-3 polyunsaturated fatty acids, supplemental calcium, circulating 25-hydroxyvitamin D (25[OH]D) and all-cause mortality; for alcohol, supplemental calcium, circulating 25(OH)D and colorectal cancer-specific mortality; and for circulating 25(OH)D and recurrence/disease-free survival. The overall evidence was graded as 'limited'. The inverse associations between healthy dietary and/or lifestyle patterns (including diets that comprised plant-based foods), whole grains, total, caffeinated, or decaffeinated coffee and all-cause mortality and the positive associations between unhealthy dietary patterns, sugary drinks and all-cause mortality provided 'limited-suggestive' evidence. All other exposure-outcome associations provided 'limited-no conclusion' evidence. Additional, well-conducted cohort studies and carefully designed RCTs are needed to develop specific lifestyle recommendations for colorectal cancer survivors.
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Affiliation(s)
- Doris S M Chan
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Margarita Cariolou
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Georgios Markozannes
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece
| | - Katia Balducci
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Rita Vieira
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Sonia Kiss
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Nerea Becerra-Tomás
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Dagfinn Aune
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Department of Nutrition, Oslo New University College, Oslo, Norway
- Department of Research, The Cancer Registry of Norway, Oslo, Norway
| | - Darren C Greenwood
- Leeds Institute for Data Analytics, Faculty of Medicine and Health, University of Leeds, Leeds, UK
| | - Esther M González-Gil
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Ellen Copson
- Cancer Sciences Academic Unit, Faculty of Medicine, University of Southampton, Southampton, UK
| | - Andrew G Renehan
- The Christie NHS Foundation Trust, Manchester Cancer Research Centre, NIHR Manchester Biomedical Research Centre, Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Martijn Bours
- Department of Epidemiology, GROW School for Oncology and Reproduction, Maastricht University, Maastricht, The Netherlands
| | - Wendy Demark-Wahnefried
- O'Neal Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Melissa M Hudson
- Department of Oncology, St Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - Anne M May
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | | | - Roderick Skinner
- Department of Paediatric and Adolescent Haematology/Oncology, Great North Children's Hospital and Translational and Clinical Research Institute, and Centre for Cancer, Newcastle University, Newcastle upon Tyne, UK
| | - Karen Steindorf
- Division of Physical Activity, Prevention and Cancer, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany
| | - Anne Tjønneland
- Danish Cancer Society Research Center, Diet, Cancer and Health, Copenhagen, Denmark
- Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Galina Velikova
- School of Medicine, Faculty of Medicine and Health, University of Leeds, Leeds, UK
| | | | - Rajiv Chowdhury
- Department of Global Health, Robert Stempel College of Public Health and Social Work, Florida International University, Miami, Florida, USA
| | - Lynette Hill
- World Cancer Research Fund International, London, UK
| | - Sarah J Lewis
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Jaap Seidell
- Department of Health Sciences, Faculty of Science, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Matty P Weijenberg
- Department of Epidemiology, GROW School for Oncology and Reproduction, Maastricht University, Maastricht, The Netherlands
| | - John Krebs
- Department of Biology, University of Oxford, Oxford, UK
| | - Amanda J Cross
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Konstantinos K Tsilidis
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece
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19
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Hang D, Du M, Wang L, Wang K, Fang Z, Khandpur N, Rossato SL, Steele EM, Chan AT, Hu FB, Meyerhardt JA, Mozaffarian D, Ogino S, Sun Q, Wong JB, Zhang FF, Song M. Ultra-processed food consumption and mortality among patients with stages I-III colorectal cancer: a prospective cohort study. EClinicalMedicine 2024; 71:102572. [PMID: 38572081 PMCID: PMC10990709 DOI: 10.1016/j.eclinm.2024.102572] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 02/24/2024] [Accepted: 03/13/2024] [Indexed: 04/05/2024] Open
Abstract
Background Ultra-processed foods (UPFs) are emerging as a risk factor for colorectal cancer (CRC), yet how post-diagnostic UPF intake may impact CRC prognosis remains unexplored. Methods Data collected from food frequency questionnaires were used to estimate intakes of total UPFs and UPF subgroups (serving/d) at least 6 months but less than 4 years post-diagnosis among 2498 patients diagnosed with stages I-III CRC within the Nurses' Health Study and Health Professionals Follow-up Study during 1980-2016. Hazard ratios (HR) and 95% confidence intervals (CIs) of all-cause, CRC- and cardiovascular disease (CVD)-specific mortality in association with UPF consumption were estimated using an inverse probability weighted multivariable Cox proportional hazards regression model, adjusted for confounders. Findings The mean (SD) age of patients at diagnosis was 68.5 (9.4) years. A total of 1661 deaths were documented, including 321 from CRC and 335 from CVD. Compared to those in the lowest quintile (median = 3.6 servings/d), patients in the highest quintile (median = 10 servings/d) of post-diagnostic UPF intake had higher CVD mortality (HR = 1.65, 95% CI = 1.13-2.40) but not CRC or all-cause mortality. Among UPF subgroups, higher consumption of fats/condiments/sauces was associated with a higher risk of CVD-specific mortality (highest vs. lowest quintile of intake, HR = 1.96, 95% CI = 1.41-2.73), and higher intake of ice cream/sherbet was associated with an increased risk of CRC-specific mortality (highest vs. lowest quintile, HR = 1.86, 95% CI: 1.33-2.61). No statistically significant association was found between UPF subgroups and overall mortality. Interpretation Higher post-diagnostic intake of total UPFs and fats/condiments/sauces in CRC survivors is associated with higher CVD mortality, and higher ice cream/sherbet intake is linked to higher CRC mortality. Funding US National Institutes of Health and the American Cancer Society.
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Affiliation(s)
- Dong Hang
- Department of Epidemiology, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, China
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Mengxi Du
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
- Clinical and Translational Epidemiology Unit and Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Lu Wang
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
| | - Kai Wang
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Zhe Fang
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Neha Khandpur
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Division of Human Nutrition and Health, Wageningen University, Netherlands
- Department of Nutrition, School of Public Health, University of São Paulo, São Paulo, Brazil
| | - Sinara Laurini Rossato
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Institute of Geography, Universidade Federal de Uberlândia, Minas Gerais, Brazil
| | - Eurídice Martínez Steele
- Department of Nutrition, School of Public Health, University of São Paulo, São Paulo, Brazil
- Center for Epidemiological Studies in Health and Nutrition (NUPENS), Faculty of Public Health, University of São Paulo, Brazil
| | - Andrew T. Chan
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Clinical and Translational Epidemiology Unit and Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Frank B. Hu
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Jeffrey A. Meyerhardt
- Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA
| | - Dariush Mozaffarian
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
- Tufts School of Medicine and Division of Cardiology, Tufts Medical Center, Boston, MA, USA
| | - Shuji Ogino
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Program in MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women’s Hospital, and Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Nutrition, Harvard Medical School, Boston, MA, USA
- Tokyo Medical and Dental University (Institute of Science Tokyo), Tokyo, Japan
| | - Qi Sun
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - John B. Wong
- Division of Clinical Decision Making, Tufts Medical Center, Boston, MA, USA
| | - Fang Fang Zhang
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
| | - Mingyang Song
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Clinical and Translational Epidemiology Unit and Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
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20
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Ponce LF, Bishop SL, Wacker S, Groves RA, Lewis IA. SCALiR: A Web Application for Automating Absolute Quantification of Mass Spectrometry-Based Metabolomics Data. Anal Chem 2024; 96:6566-6574. [PMID: 38642077 DOI: 10.1021/acs.analchem.3c04988] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/22/2024]
Abstract
Quantitative liquid chromatography-mass spectrometry (LC-MS)-based metabolomics is becoming an important approach for studying complex biological systems but presents several technical challenges that limit its widespread use. Computing metabolite concentrations using standard curves generated from standard mixtures of known concentrations is a labor-intensive process that is often performed manually. Currently, there are few options for open-source software tools that can automatically calculate metabolite concentrations. Herein, we introduce SCALiR (standard curve application for determining linear ranges), a new web-based software tool specifically built for this task, which allows users to automatically transform LC-MS signals into absolute quantitative data (https://www.lewisresearchgroup.org/software). SCALiR uses an algorithm that automatically finds the equation of the line of best fit for each standard curve and uses this equation to calculate compound concentrations from the LC-MS signal. Using a standard mix containing 77 metabolites, we show a close correlation between the concentrations calculated by SCALiR and the expected concentrations of each compound (R2 = 0.99 for a y = x curve fitting). Moreover, we demonstrate that SCALiR reproducibly calculates concentrations of midrange standards across ten analytical batches (average coefficient of variation 0.091). SCALiR can be used to calculate metabolite concentrations either using external calibration curves or by using internal standards to correct for matrix effects. This open-source and vendor agnostic software offers users several advantages in that (1) it requires only 10 s of analysis time to compute concentrations of >75 compounds, (2) it facilitates automation of quantitative workflows, and (3) it performs deterministic evaluations of compound quantification limits. SCALiR therefore provides the metabolomics community with a simple and rapid tool that enables rigorous and reproducible quantitative metabolomics studies.
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Affiliation(s)
- Luis F Ponce
- Alberta Centre for Advanced Diagnostics, Department of Biological Sciences, University of Calgary, 2500 University Dr NW, Calgary, AB T2N 1N4, Canada
| | - Stephanie L Bishop
- Alberta Centre for Advanced Diagnostics, Department of Biological Sciences, University of Calgary, 2500 University Dr NW, Calgary, AB T2N 1N4, Canada
| | - Soren Wacker
- Alberta Centre for Advanced Diagnostics, Department of Biological Sciences, University of Calgary, 2500 University Dr NW, Calgary, AB T2N 1N4, Canada
| | - Ryan A Groves
- Alberta Centre for Advanced Diagnostics, Department of Biological Sciences, University of Calgary, 2500 University Dr NW, Calgary, AB T2N 1N4, Canada
| | - Ian A Lewis
- Alberta Centre for Advanced Diagnostics, Department of Biological Sciences, University of Calgary, 2500 University Dr NW, Calgary, AB T2N 1N4, Canada
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21
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Davies E, Chetwynd A, McDowell G, Rao A, Oni L. The current use of proteomics and metabolomics in glomerulonephritis: a systematic literature review. J Nephrol 2024:10.1007/s40620-024-01923-w. [PMID: 38689160 DOI: 10.1007/s40620-024-01923-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2023] [Accepted: 02/24/2024] [Indexed: 05/02/2024]
Abstract
BACKGROUND Glomerulonephritis inherently leads to the development of chronic kidney disease. It is the second most common diagnosis in patients requiring renal replacement therapy in the United Kingdom. Metabolomics and proteomics can characterise, identify and quantify an individual's protein and metabolite make-up. These techniques have been optimised and can be performed on samples including kidney tissue, blood and urine. Utilising omic techniques in nephrology can uncover disease pathophysiology and transform the diagnostics and treatment options for glomerulonephritis. OBJECTIVES To evaluate the utility of metabolomics and proteomics using mass spectrometry and nuclear magnetic resonance in glomerulonephritis. METHODS The systematic review was registered on PROSPERO (CRD42023442092). Standard and extensive Cochrane search methods were used. The latest search date was March 2023. Participants were of any age with a histological diagnosis of glomerulonephritis. Descriptive analysis was performed, and data presented in tabular form. An area under the curve or p-value was presented for potential biomarkers discovered. RESULTS Twenty-seven studies were included (metabolomics (n = 9)), and (proteomics (n = 18)) with 1818 participants. The samples analysed were urine (n = 19) blood (n = 4) and biopsy (n = 6). The typical outcome themes were potential biomarkers, disease phenotype, risk of progression and treatment response. CONCLUSION This review shows the potential of metabolomic and proteomic analysis to discover new disease biomarkers that may influence diagnostics and disease management. Further larger-scale research is required to establish the validity of the study outcomes, including the several proposed biomarkers.
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Affiliation(s)
- Elin Davies
- Department of Women's and Children's Health, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, UK.
- Department of Nephrology, Liverpool University Hospitals NHS Foundation Trust, Liverpool, UK.
| | - Andrew Chetwynd
- Centre for Proteome Research, Department of Biochemistry, Cell and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
| | - Garry McDowell
- Liverpool Centre for Cardiovascular Science, University of Liverpool, Liverpool John Moores University and Liverpool Heart and Chest Hospital, Liverpool, UK
- Clinical Directorate, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, UK
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Liverpool, UK
- Research Laboratory, Liverpool Heart and Chest Hospital, Liverpool, UK
| | - Anirudh Rao
- Department of Nephrology, Liverpool University Hospitals NHS Foundation Trust, Liverpool, UK
- Liverpool Centre for Cardiovascular Science, University of Liverpool, Liverpool John Moores University and Liverpool Heart and Chest Hospital, Liverpool, UK
- Clinical Directorate, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, UK
| | - Louise Oni
- Department of Women's and Children's Health, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, UK
- Department of Paediatric Nephrology, Alder Hey Children's, NHS Foundation Trust Hospital, Eaton Road, Liverpool, UK
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22
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Liang G, Cao W, Tang D, Zhang H, Yu Y, Ding J, Karges J, Xiao H. Nanomedomics. ACS NANO 2024; 18:10979-11024. [PMID: 38635910 DOI: 10.1021/acsnano.3c11154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/20/2024]
Abstract
Nanomaterials have attractive physicochemical properties. A variety of nanomaterials such as inorganic, lipid, polymers, and protein nanoparticles have been widely developed for nanomedicine via chemical conjugation or physical encapsulation of bioactive molecules. Superior to traditional drugs, nanomedicines offer high biocompatibility, good water solubility, long blood circulation times, and tumor-targeting properties. Capitalizing on this, several nanoformulations have already been clinically approved and many others are currently being studied in clinical trials. Despite their undoubtful success, the molecular mechanism of action of the vast majority of nanomedicines remains poorly understood. To tackle this limitation, herein, this review critically discusses the strategy of applying multiomics analysis to study the mechanism of action of nanomedicines, named nanomedomics, including advantages, applications, and future directions. A comprehensive understanding of the molecular mechanism could provide valuable insight and therefore foster the development and clinical translation of nanomedicines.
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Affiliation(s)
- Ganghao Liang
- Beijing National Laboratory for Molecular Sciences, Laboratory of Polymer Physics and Chemistry, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, P. R. China
- University of Chinese Academy of Sciences, Beijing 100049, P. R. China
| | - Wanqing Cao
- Key Laboratory of Polymer Ecomaterials, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, 5625 Renmin Street, Changchun 130022, P. R. China
- School of Applied Chemistry and Engineering, University of Science and Technology of China, 96 Jinzhai Road, Hefei 230026, P. R. China
| | - Dongsheng Tang
- Beijing National Laboratory for Molecular Sciences, Laboratory of Polymer Physics and Chemistry, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, P. R. China
- University of Chinese Academy of Sciences, Beijing 100049, P. R. China
| | - Hanchen Zhang
- Beijing National Laboratory for Molecular Sciences, Laboratory of Polymer Physics and Chemistry, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, P. R. China
- University of Chinese Academy of Sciences, Beijing 100049, P. R. China
| | - Yingjie Yu
- State Key Laboratory of Organic-Inorganic Composites, Beijing Laboratory of Biomedical Materials, Beijing University of Chemical Technology, Beijing 100029, P. R. China
| | - Jianxun Ding
- Key Laboratory of Polymer Ecomaterials, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, 5625 Renmin Street, Changchun 130022, P. R. China
- School of Applied Chemistry and Engineering, University of Science and Technology of China, 96 Jinzhai Road, Hefei 230026, P. R. China
| | - Johannes Karges
- Faculty of Chemistry and Biochemistry, Ruhr-University Bochum, Universitätsstrasse 150, 44780 Bochum, Germany
| | - Haihua Xiao
- Beijing National Laboratory for Molecular Sciences, Laboratory of Polymer Physics and Chemistry, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, P. R. China
- University of Chinese Academy of Sciences, Beijing 100049, P. R. China
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23
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Alosaimi ME, Alotaibi BS, Abduljabbar MH, Alnemari RM, Almalki AH, Serag A. Unveiling the altered metabolic pathways induced by nivolumab in non-small cell lung cancer via GC-MS metabolomics approach coupled with multivariate analysis. J Chromatogr B Analyt Technol Biomed Life Sci 2024; 1240:124144. [PMID: 38703714 DOI: 10.1016/j.jchromb.2024.124144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Revised: 04/01/2024] [Accepted: 04/28/2024] [Indexed: 05/06/2024]
Abstract
This research investigates the effects of the immunotherapeutic agent nivolumab on the metabolism of lung cancer cells (NCI-H1975) using GC-MS metabolomic profiling. Multivariate analysis such as unsupervised PCA and supervised OPLS-DA along with univariate analysis and pathway analysis were employed to explore the metabolomic data and identify altered metabolic pathways induced by nivolumab treatment. The study revealed distinct metabolic alterations in cancer cells, linked to proliferative and survival advantages, such as enhanced glycolysis, increased glutaminolysis, and modified amino acid metabolism. Key findings indicate elevated levels of glycolysis-related metabolites (glycine, alanine, pyruvate, and lactate) and TCA cycle intermediates (succinate, fumarate, malate) in cancer cells, with a significant decrease following nivolumab treatment. Additionally, lower levels of aspartic acid and citrate in cancer cells imply altered nucleotide synthesis and fatty acid production essential for tumor growth. Treatment with nivolumab also reduced oleic acid levels, indicative of its effect on disrupted lipid metabolism. Our research shows nivolumab's potential to modify metabolic pathways involved in lung cancer progression, suggesting its dual role in cancer therapy: as an immune response modulator and a metabolic pathway disruptor.
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Affiliation(s)
- Manal E Alosaimi
- Department of Basic Sciences, College of Medicine, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia
| | - Badriyah S Alotaibi
- Department of Pharmaceutical Sciences, College of Pharmacy, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia
| | - Maram H Abduljabbar
- Department of Pharmacology and Toxicology, College of Pharmacy, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia
| | - Reem M Alnemari
- Department of Pharmaceutics and Pharmaceutical Technology, College of Pharmacy, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia
| | - Atiah H Almalki
- Department of Pharmaceutical Chemistry, College of Pharmacy, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia; Addiction and Neuroscience Research Unit, Health Science Campus, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia
| | - Ahmed Serag
- Pharmaceutical Analytical Chemistry Department, Faculty of Pharmacy, Al-Azhar University, Nasr City 11751, Cairo, Egypt.
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24
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Chen Y, Gu Y, Rong J, Xu L, Huang X, Zhu J, Chen Z, Mao W. Plasma-based lipidomics reveals potential diagnostic biomarkers for esophageal squamous cell carcinoma: a retrospective study. PeerJ 2024; 12:e17272. [PMID: 38699187 PMCID: PMC11064858 DOI: 10.7717/peerj.17272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Accepted: 03/29/2024] [Indexed: 05/05/2024] Open
Abstract
Background Esophageal squamous cell carcinoma (ESCC) is highly prevalent and has a high mortality rate. Traditional diagnostic methods, such as imaging examinations and blood tumor marker tests, are not effective in accurately diagnosing ESCC due to their low sensitivity and specificity. Esophageal endoscopic biopsy, which is considered as the gold standard, is not suitable for screening due to its invasiveness and high cost. Therefore, this study aimed to develop a convenient and low-cost diagnostic method for ESCC using plasma-based lipidomics analysis combined with machine learning (ML) algorithms. Methods Plasma samples from a total of 40 ESCC patients and 31 healthy controls were used for lipidomics study. Untargeted lipidomics analysis was conducted through liquid chromatography-mass spectrometry (LC-MS) analysis. Differentially expressed lipid features were filtered based on multivariate and univariate analysis, and lipid annotation was performed using MS-DIAL software. Results A total of 99 differential lipids were identified, with 15 up-regulated lipids and 84 down-regulated lipids, suggesting their potential as diagnostic targets for ESCC. In the single-lipid plasma-based diagnostic model, nine specific lipids (FA 15:4, FA 27:1, FA 28:7, FA 28:0, FA 36:0, FA 39:0, FA 42:0, FA 44:0, and DG 37:7) exhibited excellent diagnostic performance, with an area under the curve (AUC) exceeding 0.99. Furthermore, multiple lipid-based ML models also demonstrated comparable diagnostic ability for ESCC. These findings indicate plasma lipids as a promising diagnostic approach for ESCC.
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Affiliation(s)
- Yang Chen
- Department of Medical Oncology, The Second Clinical Medical College of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
- Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, China
- Zhejiang Key Laboratory of Diagnosis and Treatment Technology on Thoracic Oncology, Hangzhou, Zhejiang, China
| | - Yixuan Gu
- Department of Medical Oncology, The Second Clinical Medical College of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
- Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, China
- Zhejiang Key Laboratory of Diagnosis and Treatment Technology on Thoracic Oncology, Hangzhou, Zhejiang, China
| | - Jinhua Rong
- Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, China
- Zhejiang Key Laboratory of Diagnosis and Treatment Technology on Thoracic Oncology, Hangzhou, Zhejiang, China
- College of Pharmaceutical Science, Zhejiang University of Technology, Hangzhou, Zhejiang, China
| | - Luyin Xu
- Department of Medical Oncology, The Second Clinical Medical College of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
- Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, China
- Zhejiang Key Laboratory of Diagnosis and Treatment Technology on Thoracic Oncology, Hangzhou, Zhejiang, China
| | - Xiancong Huang
- Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, China
- Zhejiang Key Laboratory of Diagnosis and Treatment Technology on Thoracic Oncology, Hangzhou, Zhejiang, China
| | - Jing Zhu
- Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, China
- Zhejiang Key Laboratory of Diagnosis and Treatment Technology on Thoracic Oncology, Hangzhou, Zhejiang, China
| | - Zhongjian Chen
- Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, China
- Zhejiang Key Laboratory of Diagnosis and Treatment Technology on Thoracic Oncology, Hangzhou, Zhejiang, China
| | - Weimin Mao
- Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, China
- Zhejiang Key Laboratory of Diagnosis and Treatment Technology on Thoracic Oncology, Hangzhou, Zhejiang, China
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25
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Xu Y, Cao L, Chen Y, Zhang Z, Liu W, Li H, Ding C, Pu J, Qian K, Xu W. Integrating Machine Learning in Metabolomics: A Path to Enhanced Diagnostics and Data Interpretation. SMALL METHODS 2024:e2400305. [PMID: 38682615 DOI: 10.1002/smtd.202400305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2024] [Revised: 04/07/2024] [Indexed: 05/01/2024]
Abstract
Metabolomics, leveraging techniques like NMR and MS, is crucial for understanding biochemical processes in pathophysiological states. This field, however, faces challenges in metabolite sensitivity, data complexity, and omics data integration. Recent machine learning advancements have enhanced data analysis and disease classification in metabolomics. This study explores machine learning integration with metabolomics to improve metabolite identification, data efficiency, and diagnostic methods. Using deep learning and traditional machine learning, it presents advancements in metabolic data analysis, including novel algorithms for accurate peak identification, robust disease classification from metabolic profiles, and improved metabolite annotation. It also highlights multiomics integration, demonstrating machine learning's potential in elucidating biological phenomena and advancing disease diagnostics. This work contributes significantly to metabolomics by merging it with machine learning, offering innovative solutions to analytical challenges and setting new standards for omics data analysis.
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Affiliation(s)
- Yudian Xu
- Department of Traditional Chinese Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, P. R. China
| | - Linlin Cao
- State Key Laboratory for Oncogenes and Related Genes, Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 160 Pujian Road, Shanghai, 200127, P. R. China
| | - Yifan Chen
- State Key Laboratory for Oncogenes and Related Genes, Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 160 Pujian Road, Shanghai, 200127, P. R. China
| | - Ziyue Zhang
- School of Biomedical Engineering, Institute of Medical Robotics and Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - Wanshan Liu
- School of Biomedical Engineering, Institute of Medical Robotics and Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - He Li
- Department of Traditional Chinese Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, P. R. China
| | - Chenhuan Ding
- Department of Traditional Chinese Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, P. R. China
| | - Jun Pu
- State Key Laboratory for Oncogenes and Related Genes, Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 160 Pujian Road, Shanghai, 200127, P. R. China
| | - Kun Qian
- State Key Laboratory for Oncogenes and Related Genes, Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 160 Pujian Road, Shanghai, 200127, P. R. China
- School of Biomedical Engineering, Institute of Medical Robotics and Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - Wei Xu
- State Key Laboratory for Oncogenes and Related Genes, Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 160 Pujian Road, Shanghai, 200127, P. R. China
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26
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Dong X, Qu Y, Sheng T, Fan Y, Chen S, Yuan Q, Ma G, Ge Y. HCMMD: systematic evaluation of metabolites in body fluids as liquid biopsy biomarker for human cancers. Aging (Albany NY) 2024; 16:7487-7504. [PMID: 38683118 PMCID: PMC11087094 DOI: 10.18632/aging.205779] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Accepted: 01/03/2024] [Indexed: 05/01/2024]
Abstract
Metabolomics is a rapidly expanding field in systems biology used to measure alterations of metabolites and identify metabolic biomarkers in response to disease processes. The discovery of metabolic biomarkers can improve early diagnosis, prognostic prediction, and therapeutic intervention for cancers. However, there are currently no databases that provide a comprehensive evaluation of the relationship between metabolites and cancer processes. In this review, we summarize reported metabolites in body fluids across pan-cancers and characterize their clinical applications in liquid biopsy. We conducted a search for metabolic biomarkers using the keywords ("metabolomics" OR "metabolite") AND "cancer" in PubMed. Of the 22,254 articles retrieved, 792 were deemed potentially relevant for further review. Ultimately, we included data from 573,300 samples and 17,083 metabolic biomarkers. We collected information on cancer types, sample size, the human metabolome database (HMDB) ID, metabolic pathway, area under the curve (AUC), sensitivity and specificity of metabolites, sample source, detection method, and clinical features were collected. Finally, we developed a user-friendly online database, the Human Cancer Metabolic Markers Database (HCMMD), which allows users to query, browse, and download metabolite information. In conclusion, HCMMD provides an important resource to assist researchers in reviewing metabolic biomarkers for diagnosis and progression of cancers.
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Affiliation(s)
- Xun Dong
- State Key Laboratory of Natural Medicines, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Yaoyao Qu
- State Key Laboratory of Natural Medicines, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Tongtong Sheng
- School of Public Health, Nanjing Medical University, Nanjing, China
| | - Yuanming Fan
- State Key Laboratory of Natural Medicines, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Silu Chen
- School of Public Health, Nanjing Medical University, Nanjing, China
| | - Qinbo Yuan
- Department of Urology, Wuxi Fifth People’s Hospital, Wuxi, China
| | - Gaoxiang Ma
- State Key Laboratory of Natural Medicines, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing, China
- The Clinical Metabolomics Center, China Pharmaceutical University, Nanjing, China
- Deparment of Oncology, Pukou Hospital of Chinese Medicine affiliated to China Pharmaceutical University, Nanjing, China
| | - Yuqiu Ge
- Department of Public Health and Preventive Medicine, Wuxi School of Medicine, Jiangnan University, Wuxi, China
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27
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Cui P, Li X, Huang C, Lin D. Metabolomics-driven discovery of therapeutic targets for cancer cachexia. J Cachexia Sarcopenia Muscle 2024. [PMID: 38644205 DOI: 10.1002/jcsm.13465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 12/07/2023] [Accepted: 01/09/2024] [Indexed: 04/23/2024] Open
Abstract
Cancer cachexia (CC) is a devastating metabolic syndrome characterized by skeletal muscle wasting and body weight loss, posing a significant burden on the health and survival of cancer patients. Despite ongoing efforts, effective treatments for CC are still lacking. Metabolomics, an advanced omics technique, offers a comprehensive analysis of small-molecule metabolites involved in cellular metabolism. In CC research, metabolomics has emerged as a valuable tool for identifying diagnostic biomarkers, unravelling molecular mechanisms and discovering potential therapeutic targets. A comprehensive search strategy was implemented to retrieve relevant articles from primary databases, including Web of Science, Google Scholar, Scopus and PubMed, for CC and metabolomics. Recent advancements in metabolomics have deepened our understanding of CC by uncovering key metabolic signatures and elucidating underlying mechanisms. By targeting crucial metabolic pathways including glucose metabolism, amino acid metabolism, fatty acid metabolism, bile acid metabolism, ketone body metabolism, steroid metabolism and mitochondrial energy metabolism, it becomes possible to restore metabolic balance and alleviate CC symptoms. This review provides a comprehensive summary of metabolomics studies in CC, focusing on the discovery of potential therapeutic targets and the evaluation of modulating specific metabolic pathways for CC treatment. By harnessing the insights derived from metabolomics, novel interventions for CC can be developed, leading to improved patient outcomes and enhanced quality of life.
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Affiliation(s)
- Pengfei Cui
- College of Food and Pharmacy, Xuchang University, Xuchang, China
| | - Xiaoyi Li
- Xuchang Central Hospital, Xuchang, China
| | - Caihua Huang
- Research and Communication Center of Exercise and Health, Xiamen University of Technology, Xiamen, China
| | - Donghai Lin
- Key Laboratory for Chemical Biology of Fujian Province, MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, China
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28
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Zhang Y, Ni M, Tao Y, Shen M, Xu W, Fan M, Shan J, Cheng H. Multiple-matrix metabolomics analysis for the distinct detection of colorectal cancer and adenoma. Metabolomics 2024; 20:47. [PMID: 38642214 DOI: 10.1007/s11306-024-02114-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 03/31/2024] [Indexed: 04/22/2024]
Abstract
OBJECTIVES Although colorectal cancer (CRC) is the leading cause of cancer-related morbidity and mortality, current diagnostic tests for early-stage CRC and colorectal adenoma (CRA) are suboptimal. Therefore, there is an urgent need to explore less invasive screening procedures for CRC and CRA diagnosis. METHODS Untargeted gas chromatography-mass spectrometry (GC-MS) metabolic profiling approach was applied to identify candidate metabolites. We performed metabolomics profiling on plasma samples from 412 subjects including 200 CRC patients, 160 CRA patients and 52 normal controls (NC). Among these patients, 45 CRC patients, 152 CRA patients and 50 normal controls had their fecal samples tested simultaneously. RESULTS Differential metabolites were screened in the adenoma-carcinoma sequence. Three diagnostic models were further developed to identify cancer group, cancer stage, and cancer microsatellite status using those significant metabolites. The three-metabolite-only classifiers used to distinguish the cancer group always keeps the area under the receiver operating characteristic curve (AUC) greater than 0.7. The AUC performance of the classifiers applied to discriminate CRC stage is generally greater than 0.8, and the classifiers used to distinguish microsatellite status of CRC is greater than 0.9. CONCLUSION This finding highlights potential early-driver metabolites in CRA and early-stage CRC. We also find potential metabolic markers for discriminating the microsatellite state of CRC. Our study and diagnostic model have potential applications for non-invasive CRC and CRA detection.
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Affiliation(s)
- Ye Zhang
- Department of Oncology, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
- The First Clinical Medical College, Nanjing University of Chinese Medicine, Nanjing, China
- Jiangsu Collaborative Innovation Center of Traditional Chinese Medicine in Prevention and Treatment of Tumor, Nanjing University of Chinese Medicine, Nanjing, China
| | - Mingxin Ni
- The First Clinical Medical College, Nanjing University of Chinese Medicine, Nanjing, China
- Jiangsu Collaborative Innovation Center of Traditional Chinese Medicine in Prevention and Treatment of Tumor, Nanjing University of Chinese Medicine, Nanjing, China
| | - Yuquan Tao
- The First Clinical Medical College, Nanjing University of Chinese Medicine, Nanjing, China
- Jiangsu Collaborative Innovation Center of Traditional Chinese Medicine in Prevention and Treatment of Tumor, Nanjing University of Chinese Medicine, Nanjing, China
| | - Meng Shen
- The First Clinical Medical College, Nanjing University of Chinese Medicine, Nanjing, China
- Jiangsu Collaborative Innovation Center of Traditional Chinese Medicine in Prevention and Treatment of Tumor, Nanjing University of Chinese Medicine, Nanjing, China
| | - Weichen Xu
- Jiangsu Key Laboratory of Pediatric Respiratory Disease, Institute of Pediatrics, Medical Metabolomics Center, Nanjing University of Chinese Medicine, Nanjing, China
| | - Minmin Fan
- The First Clinical Medical College, Nanjing University of Chinese Medicine, Nanjing, China.
- Jiangsu Collaborative Innovation Center of Traditional Chinese Medicine in Prevention and Treatment of Tumor, Nanjing University of Chinese Medicine, Nanjing, China.
| | - Jinjun Shan
- Jiangsu Key Laboratory of Pediatric Respiratory Disease, Institute of Pediatrics, Medical Metabolomics Center, Nanjing University of Chinese Medicine, Nanjing, China.
| | - Haibo Cheng
- Department of Oncology, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China.
- The First Clinical Medical College, Nanjing University of Chinese Medicine, Nanjing, China.
- Jiangsu Collaborative Innovation Center of Traditional Chinese Medicine in Prevention and Treatment of Tumor, Nanjing University of Chinese Medicine, Nanjing, China.
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29
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Chen H, Wen J, Zhang W, Ma W, Guo Y, Shen L, Zhang Z, Yang F, Zhang Y, Gao Y, Xu T, Yan Y, Li W, Zhang J, Mao S, Yao X. circKDM1A suppresses bladder cancer progression by sponging miR-889-3p/CPEB3 and stabilizing p53 mRNA. iScience 2024; 27:109624. [PMID: 38632984 PMCID: PMC11022052 DOI: 10.1016/j.isci.2024.109624] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 02/04/2024] [Accepted: 03/26/2024] [Indexed: 04/19/2024] Open
Abstract
Circular RNAs (circRNAs) play crucial biological functions in various tumors, including bladder cancer (BCa). However, the roles and underlying molecular mechanisms of circRNAs in the malignant proliferation of BCa are yet unknown. CircKDM1A was observed to be downregulated in BCa tissues and cells. Knockdown of circKDM1A promoted the proliferation of BCa cells and bladder xenograft growth, while the overexpression of circKDM1A exerts the opposite effect. The dual-luciferase reporter assay revealed that circKDM1A was directly bound to miR-889-3p, acting as its molecular sponge to downregulate CPEB3. In turn, the CPEB3 was bound to the CPE signal in p53 mRNA 3'UTR to stabilize its expression. Thus, circKDM1A-mediated CPEB3 downregulation inhibits the stability of p53 mRNA and promotes BCa malignant progression. In conclusion, circKDM1A functions as a tumor suppressor in the malignant proliferation of BCa via the miR-889-3p/CPEB3/p53 axis. CircKDM1A may be a potential prognostic biomarker and therapeutic target of BCa.
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Affiliation(s)
- Haotian Chen
- Department of Urology, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai, China
- Urologic Cancer Institute, School of Medicine, Tongji University, Shanghai, China
| | - Jing Wen
- Institute of Energy Metabolism and Health, Shanghai Tenth People’s Hospital, Tongji University School of Medicine Shanghai, Shanghai 200072, P.R. China
| | - Wentao Zhang
- Department of Urology, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai, China
- Urologic Cancer Institute, School of Medicine, Tongji University, Shanghai, China
| | - Wenchao Ma
- Department of Reproduction, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China
| | - Yadong Guo
- Department of Urology, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai, China
- Urologic Cancer Institute, School of Medicine, Tongji University, Shanghai, China
| | - Liliang Shen
- Department of Urology, The Affiliated People’s Hospital of Ningbo University, Ningbo, China
| | - Zhijin Zhang
- Department of Urology, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai, China
- Urologic Cancer Institute, School of Medicine, Tongji University, Shanghai, China
| | - Fuhan Yang
- Department of Urology, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai, China
- Urologic Cancer Institute, School of Medicine, Tongji University, Shanghai, China
| | - Yue Zhang
- Department of Central Laboratory, Clinical Medicine Scientific and Technical Innovation Park, Shanghai Tenth People’s Hospital, Shanghai 200435, China
| | - Yaohui Gao
- Department of Pathology, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Tianyuan Xu
- Department of Urology, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai, China
- Urologic Cancer Institute, School of Medicine, Tongji University, Shanghai, China
| | - Yang Yan
- Department of Urology, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai, China
- Urologic Cancer Institute, School of Medicine, Tongji University, Shanghai, China
| | - Wei Li
- Department of Urology, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai, China
- Urologic Cancer Institute, School of Medicine, Tongji University, Shanghai, China
| | - Junfeng Zhang
- Department of Urology, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai, China
- Urologic Cancer Institute, School of Medicine, Tongji University, Shanghai, China
| | - Shiyu Mao
- Department of Urology, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai, China
- Urologic Cancer Institute, School of Medicine, Tongji University, Shanghai, China
| | - Xudong Yao
- Department of Urology, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai, China
- Urologic Cancer Institute, School of Medicine, Tongji University, Shanghai, China
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Zheng L, Hu F, Huang L, Lu J, Yang X, Xu J, Wang S, Shen Y, Zhong R, Chu T, Zhang W, Li Y, Zheng X, Han B, Zhong H, Nie W, Zhang X. Association of metabolomics with PD-1 inhibitor plus chemotherapy outcomes in patients with advanced non-small-cell lung cancer. J Immunother Cancer 2024; 12:e008190. [PMID: 38641349 PMCID: PMC11029260 DOI: 10.1136/jitc-2023-008190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/02/2024] [Indexed: 04/21/2024] Open
Abstract
BACKGROUND Combining immune checkpoint inhibitors (ICIs) with chemotherapy has become a standard treatment for patients with non-small cell lung cancer (NSCLC) lacking driver gene mutations. Reliable biomarkers are essential for predicting treatment outcomes. Emerging evidence from various cancers suggests that early assessment of serum metabolites could serve as valuable biomarkers for predicting outcomes. This study aims to identify metabolites linked to treatment outcomes in patients with advanced NSCLC undergoing first-line or second-line therapy with programmed cell death 1 (PD-1) inhibitors plus chemotherapy. METHOD 200 patients with advanced NSCLC receiving either first-line or second-line PD-1 inhibitor plus chemotherapy, and 50 patients undergoing first-line chemotherapy were enrolled in this study. The 200 patients receiving combination therapy were divided into a Discovery set (n=50) and a Validation set (n=150). These sets were further categorized into respond and non-respond groups based on progression-free survival PFS criteria (PFS≥12 and PFS<12 months). Serum samples were collected from all patients before treatment initiation for untargeted metabolomics analysis, with the goal of identifying and validating biomarkers that can predict the efficacy of immunotherapy plus chemotherapy. Additionally, the validated metabolites were grouped into high and low categories based on their medians, and their relationship with PFS was analyzed using Cox regression models in patients receiving combination therapy. RESULTS After the impact of chemotherapy was accounted for, two significant differential metabolites were identified in both the Discovery and Validation sets: N-(3-Indolylacetyl)-L-alanine and methomyl (VIP>1 and p<0.05). Notably, upregulation of both metabolites was observed in the group with a poorer prognosis. In the univariate analysis of PFS, lower levels of N-(3-Indolylacetyl)-L-alanine were associated with longer PFS (HR=0.59, 95% CI, 0.41 to 0.84, p=0.003), and a prolonged PFS was also indicated by lower levels of methomyl (HR=0.67, 95% CI, 0.47 to 0.96, p=0.029). In multivariate analyses of PFS, lower levels of N-(3-Indolylacetyl)-L-alanine were significantly associated with a longer PFS (HR=0.60, 95% CI, 0.37 to 0.98, p=0.041). CONCLUSION Improved outcomes were associated with lower levels of N-(3-Indolylacetyl)-L-alanine in patients with stage IIIB-IV NSCLC lacking driver gene mutations, who underwent first-line or second-line therapy with PD-1 inhibitors combined with chemotherapy. Further exploration of the potential predictive value of pretreatment detection of N-(3-Indolylacetyl)-L-alanine in peripheral blood for the efficacy of combination therapy is warranted. STATEMENT The combination of ICIs and chemotherapy has established itself as the new standard of care for first-line or second-line treatment in patients with advanced NSCLC lacking oncogenic driver alterations. Therefore, identifying biomarkers that can predict the efficacy and prognosis of immunotherapy plus chemotherapy is of paramount importance. Currently, the only validated predictive biomarker is programmed cell death ligand-1 (PD-L1), but its predictive value is not absolute. Our study suggests that the detection of N-(3-Indolylacetyl)-L-alanine in patient serum with untargeted metabolomics prior to combined therapy may predict the efficacy of treatment. Compared with detecting PD-L1 expression, the advantage of our biomarker is that it is more convenient, more dynamic, and seems to work synergistically with PD-L1 expression.
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Affiliation(s)
- Liang Zheng
- Department of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School Of Medicine, Shanghai, China
| | - Fang Hu
- Department of Thoracic Medical Oncology, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Zhejiang, China
- Hangzhou Institute of Medicine (HlM), Chinese Academy of Sciences, Zhejiang, China
| | - Lin Huang
- Department of Clinical Laboratory Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School Of Medicine, Shanghai, China
- Shanghai Institute of Thoracic Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University School Of Medicine, Shanghai, China
| | - Jun Lu
- Department of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School Of Medicine, Shanghai, China
| | - Xiaohua Yang
- Central Laboratory, Shanghai Chest Hospital, Shanghai Jiao Tong University School Of Medicine, Shanghai, China
| | - Jianlin Xu
- Department of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School Of Medicine, Shanghai, China
| | - Shuyuan Wang
- Department of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School Of Medicine, Shanghai, China
| | - Yinchen Shen
- Department of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School Of Medicine, Shanghai, China
| | - Runbo Zhong
- Department of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School Of Medicine, Shanghai, China
| | - Tianqing Chu
- Department of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School Of Medicine, Shanghai, China
| | - Wei Zhang
- Department of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School Of Medicine, Shanghai, China
| | - Ying Li
- Department of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School Of Medicine, Shanghai, China
| | - Xiaoxuan Zheng
- Department of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School Of Medicine, Shanghai, China
| | - Baohui Han
- Department of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School Of Medicine, Shanghai, China
| | - Hua Zhong
- Department of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School Of Medicine, Shanghai, China
| | - Wei Nie
- Department of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School Of Medicine, Shanghai, China
| | - Xueyan Zhang
- Department of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School Of Medicine, Shanghai, China
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Fan R, Liu F, Gong Q, Liu D, Tang S, Shen D. KHDRBS1 as a novel prognostic signaling biomarker influencing hepatocellular carcinoma cell proliferation, migration, immune microenvironment, and drug sensitivity. Front Immunol 2024; 15:1393801. [PMID: 38660302 PMCID: PMC11041018 DOI: 10.3389/fimmu.2024.1393801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Accepted: 03/27/2024] [Indexed: 04/26/2024] Open
Abstract
Background Human tumors pose significant challenges, with targeted therapy against specific molecular targets or signaling pathways being a mainstay alongside surgical resection. Previous studies have implicated KHDRBS1 in the oncogenesis of certain human tumors such as colorectal and prostate cancers, underscoring its potential as a therapeutic target. However, the comprehensive expression pattern of KHDRBS1 in hepatocellular carcinoma (HCC) warrants further exploration. Methods Integrating and analyzing multi-omics, multi-cohort data from public databases, coupled with clinical samples and molecular biology validation, we elucidate the oncogenic role of KHDRBS1 in HCC progression. Additionally, leveraging HCC single-cell sequencing data, we segregate malignant cells into KHDRBS1-positive and negative subsets, uncovering significant differences in their expression profiles and functional roles. Results Our study identifies KHDRBS1 as a tumor-promoting factor in HCC, with its positivity correlating with tumor progression. Furthermore, we highlight the clinical significance of KHDRBS1-positive malignant cells, aiming to further propel its clinical utility. Conclusion KHDRBS1 plays a key role in HCC development. This study provides crucial insights for further investigation into KHDRBS1 as a therapeutic target in HCC.
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MESH Headings
- Humans
- Carcinoma, Hepatocellular/immunology
- Carcinoma, Hepatocellular/genetics
- Carcinoma, Hepatocellular/pathology
- Carcinoma, Hepatocellular/metabolism
- Liver Neoplasms/immunology
- Liver Neoplasms/genetics
- Liver Neoplasms/pathology
- Liver Neoplasms/metabolism
- Tumor Microenvironment/immunology
- Cell Proliferation
- Biomarkers, Tumor
- Cell Movement
- Prognosis
- Signal Transduction
- Cell Line, Tumor
- Gene Expression Regulation, Neoplastic
- RNA-Binding Proteins/genetics
- RNA-Binding Proteins/metabolism
- Drug Resistance, Neoplasm/genetics
- Adaptor Proteins, Signal Transducing/metabolism
- Adaptor Proteins, Signal Transducing/genetics
- Male
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Affiliation(s)
- Rui Fan
- Xiamen Cell Therapy Research Center, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Fahui Liu
- Xiamen Cell Therapy Research Center, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Qiming Gong
- Department of Nephrology, Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, China
- Baise Key Laboratory for Metabolic Diseases (Youjiang Medical University for Nationalities), Education Department of Guangxi Zhuang Autonomous Region, Baise, China
| | - Donghua Liu
- Xiamen Cell Therapy Research Center, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Shihang Tang
- Xiamen Cell Therapy Research Center, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Dongyan Shen
- Xiamen Cell Therapy Research Center, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
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Jin E, Yin Z, Zheng X, Yan C, Xu K, Eunice FY, Gao Y. Potential of Targeting TDO2 as the Lung Adenocarcinoma Treatment. J Proteome Res 2024; 23:1341-1350. [PMID: 38421152 DOI: 10.1021/acs.jproteome.3c00746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/02/2024]
Abstract
Tryptophan catabolism plays an important role in the metabolic reconnection in cancer cells to support special demands of tumor initiation and progression. The catabolic product of the tryptophan pathway, kynurenine, has the capability of suppressing the immune reactions of tumor cells. In this study, we conducted internal and external cohort studies to reveal the importance of tryptophan 2,3-dioxygenase (TDO) for lung adenocarcinoma (LUAD). Our study further demonstrated that the TDO2 expression was associated with the proliferation, survival, and invasion of LUAD cells, and targeting TDO2 for LUAD tumors could be a potential therapeutic strategy.
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Affiliation(s)
- Er Jin
- Department of Respiratory Medicine, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou 310002 Zhejiang Province, China
| | - Zhidong Yin
- Department of Pathology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009 Zhejiang Province, China
| | - Xiuxiu Zheng
- Department of Respiratory Medicine, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou 310002 Zhejiang Province, China
| | - Chenhong Yan
- Department of Respiratory Medicine, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou 310002 Zhejiang Province, China
| | - Kai Xu
- Department of Respiratory Medicine, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou 310002 Zhejiang Province, China
| | - Fouejio Yemele Eunice
- Department of Respiratory Medicine, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou 310002 Zhejiang Province, China
| | - Yue Gao
- Department of Geriatric, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou 310006 Zhejiang Province, China
- Zhejiang Provincial Key Laboratory of Traditional Chinese Medicine for the Prevention and Treatment of Major Chronic Disease in the Elderly, Hangzhou 310006 Zhejiang Province, China
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Ren F, Fei Q, Qiu K, Zhang Y, Zhang H, Sun L. Liquid biopsy techniques and lung cancer: diagnosis, monitoring and evaluation. J Exp Clin Cancer Res 2024; 43:96. [PMID: 38561776 PMCID: PMC10985944 DOI: 10.1186/s13046-024-03026-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Accepted: 03/24/2024] [Indexed: 04/04/2024] Open
Abstract
Lung cancer stands as the most prevalent form of cancer globally, posing a significant threat to human well-being. Due to the lack of effective and accurate early diagnostic methods, many patients are diagnosed with advanced lung cancer. Although surgical resection is still a potential means of eradicating lung cancer, patients with advanced lung cancer usually miss the best chance for surgical treatment, and even after surgical resection patients may still experience tumor recurrence. Additionally, chemotherapy, the mainstay of treatment for patients with advanced lung cancer, has the potential to be chemo-resistant, resulting in poor clinical outcomes. The emergence of liquid biopsies has garnered considerable attention owing to their noninvasive nature and the ability for continuous sampling. Technological advancements have propelled circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), extracellular vesicles (EVs), tumor metabolites, tumor-educated platelets (TEPs), and tumor-associated antigens (TAA) to the forefront as key liquid biopsy biomarkers, demonstrating intriguing and encouraging results for early diagnosis and prognostic evaluation of lung cancer. This review provides an overview of molecular biomarkers and assays utilized in liquid biopsies for lung cancer, encompassing CTCs, ctDNA, non-coding RNA (ncRNA), EVs, tumor metabolites, TAAs and TEPs. Furthermore, we expound on the practical applications of liquid biopsies, including early diagnosis, treatment response monitoring, prognostic evaluation, and recurrence monitoring in the context of lung cancer.
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Affiliation(s)
- Fei Ren
- Department of Geriatrics, The First Hospital of China Medical University, Shen Yang, 110000, China
| | - Qian Fei
- Department of Oncology, Shengjing Hospital of China Medical University, Shen Yang, 110000, China
| | - Kun Qiu
- Thoracic Surgery, The First Hospital of China Medical University, Shen Yang, 110000, China
| | - Yuanjie Zhang
- Thoracic Surgery, The First Hospital of China Medical University, Shen Yang, 110000, China
| | - Heyang Zhang
- Department of Hematology, The First Hospital of China Medical University, Shen Yang, 110000, China.
| | - Lei Sun
- Thoracic Surgery, The First Hospital of China Medical University, Shen Yang, 110000, China.
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Gong X, Fu Y, Zhou L, Wei A, Pan C, Zhu T, Li H. Decoding chronic rhinosinusitis: A metabolomics-based approach. Int Forum Allergy Rhinol 2024; 14:828-840. [PMID: 38343156 DOI: 10.1002/alr.23331] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 01/10/2024] [Accepted: 01/15/2024] [Indexed: 04/04/2024]
Abstract
BACKGROUND Chronic rhinosinusitis (CRS) is a common and intractable disease in otorhinolaryngology, laying a heavy burden on healthcare systems. The worldwide researchers are making efforts to find solutions to this disease. Metabolomics has recently gained more and more traction, and might become a promising tool to unravel the complexity of CRS. This paper provides an overview of current studies on the metabolomics of various CRS subtypes. METHODS We conducted a comprehensive literature search in PubMed, Web of Science, EMBASE, Google Scholar, and Cochrane Library, up to May 25, 2023. Search strategies incorporated key terms such as "chronic rhinosinusitis" and "metabolomics" with relevant synonyms and MeSH terms. Titles and abstracts of 86 screened articles were assessed for relevance to CRS and metabolomics. Methodological robustness, data reliability, and relevance were considered for shortlisted articles. RESULTS After the refined process, a total of 26 articles were included in this study and sorted out by research themes, methodology and pivotal discoveries. These included studies identified the metabolic pathways and markers related to the pathophysiology in each subtype of CRS. CONCLUSIONS Metabolomics helps to shed light on the complexity of CRS. The mentioned findings highlight the importance of specific metabolic pathways and markers in understanding the pathophysiology of CRS. Despite that, challenges and future directions in metabolomics research for CRS would be worth being further explored.
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Affiliation(s)
- Xinru Gong
- Health and Rehabilitation College, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Yijie Fu
- School of Preclinical Medicine, Chengdu University, Chengdu, Sichuan, China
| | - Lei Zhou
- Health and Rehabilitation College, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Aiming Wei
- Health and Rehabilitation College, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Chongsheng Pan
- Health and Rehabilitation College, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Tianmin Zhu
- Health and Rehabilitation College, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Hui Li
- School of Preclinical Medicine, Chengdu University, Chengdu, Sichuan, China
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Zhang M, Shi F, Chen Y, Yang C, Zhang X, Deng C, Sun N. Straightforward Creation of Multishell Hollow Hybrids for an Integrated Metabolic Monitoring System in Disease Management. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2024:e2400941. [PMID: 38529737 DOI: 10.1002/smll.202400941] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Revised: 03/08/2024] [Indexed: 03/27/2024]
Abstract
Multidimensional metabolic analysis has become a new trend in establishing efficient disease monitoring systems, as the constraints associated with relying solely on a single dimension in refined monitoring are increasingly pronounced. Here, coordination polymers are employed as derivative precursors to create multishell hollow hybrids, developing an integrated metabolic monitoring system. Briefly, metabolic fingerprints are extracted from hundreds of serum samples and urine samples, encompassing not only membranous nephropathy but also related diseases, using high-throughput mass spectrometry. With optimized algorithm and initial feature selection, the established combined panel demonstrates enhanced accuracy in both subtype differentiation (over 98.1%) and prognostic monitoring (over 95.6%), even during double blind test. This surpasses the serum biomarker panel (≈90.7% for subtyping, ≈89.7% for prognosis) and urine biomarker panel (≈94.4% for subtyping, ≈76.5% for prognosis). Moreover, after attempting to further refine the marker panel, the blind test maintains equal sensitivity, specificity, and accuracy, showcasing a comprehensive improvement over the single-fluid approach. This underscores the remarkable effectiveness and superiority of the integrated strategy in discriminating between MN and other groups. This work has the potential to significantly advance diagnostic medicine, leading to the establishment of more effective strategies for patient management.
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Affiliation(s)
- Man Zhang
- Department of Chemistry, Department of Institutes of Biomedical Sciences, Zhongshan Hospital, Fudan University, Shanghai, 200433, China
| | - Fangying Shi
- Department of Chemistry, Department of Institutes of Biomedical Sciences, Zhongshan Hospital, Fudan University, Shanghai, 200433, China
| | - Yijie Chen
- Department of Chemistry, Department of Institutes of Biomedical Sciences, Zhongshan Hospital, Fudan University, Shanghai, 200433, China
| | - Chenyu Yang
- Department of Chemistry, Department of Institutes of Biomedical Sciences, Zhongshan Hospital, Fudan University, Shanghai, 200433, China
| | - Xiangmin Zhang
- Department of Chemistry, Department of Institutes of Biomedical Sciences, Zhongshan Hospital, Fudan University, Shanghai, 200433, China
| | - Chunhui Deng
- Department of Chemistry, Department of Institutes of Biomedical Sciences, Zhongshan Hospital, Fudan University, Shanghai, 200433, China
- School of Chemistry and Chemical Engineering, Nanchang University, Nanchang, 330031, China
| | - Nianrong Sun
- Department of Gastroenterology and Hepatology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
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Zhou Z, Tang T, Li N, Zheng Q, Xiao T, Tian Y, Sun J, Zhang L, Wang X, Wang Y, Ye F, Chen Z, Zhang H, Zheng X, Cai Z, Liu L, Guan J. VLDL and LDL Subfractions Enhance the Risk Stratification of Individuals Who Underwent Epstein-Barr Virus-Based Screening for Nasopharyngeal Carcinoma: A Multicenter Cohort Study. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024:e2308765. [PMID: 38520712 DOI: 10.1002/advs.202308765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Revised: 03/04/2024] [Indexed: 03/25/2024]
Abstract
Serological tests for Epstein-Barr virus (EBV) antibodies have been widely conducted for the screening of nasopharyngeal carcinoma (NPC) in endemic areas. Further risk stratification of NPC can be achieved through plasma lipoprotein and metabolic profiles. A total of 297 NPC patients and 149 EBV-positive participants are enrolled from the NCT03919552 and NCT05682703 cohorts for plasma nuclear magnetic resonance (NMR) metabolomic analysis. Small, dense very low density lipoprotein particles (VLDL-5) and large, buoyant low density lipoprotein particles (LDL-1) are found to be closely associated with nasopharyngeal carcinogenesis. Herein, an NMR-based risk score (NRS), which combines lipoprotein subfractions and metabolic biomarkers relevant to NPC, is developed and well validated within a multicenter cohort. Combining the median cutoff value of the NRS (N50) with that of the serological test for EBV antibodies, the risk stratification model achieves a satisfactory performance in which the area under the curve (AUC) is 0.841 (95% confidence interval: 0.811-0.871), and the positive predictive value (PPV) reaches 70.08% in the combined cohort. These findings not only suggest that VLDL-5 and LDL-1 particles can serve as novel risk factors for NPC but also indicate that the NRS has significant potential in personalized risk prediction for NPC.
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Affiliation(s)
- Zhenhua Zhou
- Department of Radiation Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
- Chronic Airways Diseases Laboratory, Department of Respiratory and Critical Care Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Tingxi Tang
- Department of Radiation Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Nan Li
- Department of Radiation Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Qiaocong Zheng
- Department of Radiation Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
- Department of Radiation Oncology, Yangjiang People's Hospital, Yangjiang, Guangdong, China
| | - Ting Xiao
- Department of Radiation Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Yunming Tian
- Department of Radiation Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
- Department of Radiation Oncology, Huizhou People's Hospital, Huizhou, Guangdong, China
| | - Jianda Sun
- Department of Radiation Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
- Department of Radiation Oncology, Meizhou People's Hospital, Meizhou, Guangdong, China
| | - Longshan Zhang
- Department of Radiation Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Xiaoqing Wang
- Department of Radiation Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Yingqiao Wang
- Department of Radiation Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Feng Ye
- Department of Radiation Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Zekai Chen
- Department of Radiation Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Hanbin Zhang
- Department of Radiation Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Xiuting Zheng
- Department of Radiation Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Zhen Cai
- Department of Laboratory Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Laiyu Liu
- Chronic Airways Diseases Laboratory, Department of Respiratory and Critical Care Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Jian Guan
- Department of Radiation Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Province Key Laboratory of Molecular Tumor Pathology, Guangzhou, Guangdong, China
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Zhao Y, Ma C, Cai R, Xin L, Li Y, Ke L, Ye W, Ouyang T, Liang J, Wu R, Lin Y. NMR and MS reveal characteristic metabolome atlas and optimize esophageal squamous cell carcinoma early detection. Nat Commun 2024; 15:2463. [PMID: 38504100 PMCID: PMC10951220 DOI: 10.1038/s41467-024-46837-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Accepted: 03/06/2024] [Indexed: 03/21/2024] Open
Abstract
Metabolic changes precede malignant histology. However, it remains unclear whether detectable characteristic metabolome exists in esophageal squamous cell carcinoma (ESCC) tissues and biofluids for early diagnosis. Here, we conduct NMR- and MS-based metabolomics on 1,153 matched ESCC tissues, normal mucosae, pre- and one-week post-operative sera and urines from 560 participants across three hospitals, with machine learning and WGCNA. Aberrations in 'alanine, aspartate and glutamate metabolism' proved to be prevalent throughout the ESCC evolution, consistently identified by NMR and MS, and reflected in 16 serum and 10 urine metabolic signatures in both discovery and validation sets. NMR-based simplified panels of any five serum or urine metabolites outperform clinical serological tumor markers (AUC = 0.984 and 0.930, respectively), and are effective in distinguishing early-stage ESCC in test set (serum accuracy = 0.994, urine accuracy = 0.879). Collectively, NMR-based biofluid screening can reveal characteristic metabolic events of ESCC and be feasible for early detection (ChiCTR2300073613).
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Affiliation(s)
- Yan Zhao
- Radiology Department, Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China
- Central Laboratory, Clinical Research Center, Shantou Central Hospital, Shantou, Guangdong, China
| | - Changchun Ma
- Radiation Oncology Department, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, China
| | - Rongzhi Cai
- Radiology Department, Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China
| | - Lijing Xin
- Animal Imaging and Technology Core, Center for Biomedical Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Yongsheng Li
- Department of Medical Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Lixin Ke
- Radiology Department, Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China
| | - Wei Ye
- Radiology Department, Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China
| | - Ting Ouyang
- Radiology Department, Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China
| | - Jiahao Liang
- Radiology Department, Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China
| | - Renhua Wu
- Radiology Department, Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China.
| | - Yan Lin
- Radiology Department, Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China.
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Belloni S, Caruso R, Giacon C, Baroni I, Conte G, Magon A, Arrigoni C. Microbiome-Modifiers for Cancer-Related Fatigue Management: A Systematic Review. Semin Oncol Nurs 2024:151619. [PMID: 38503656 DOI: 10.1016/j.soncn.2024.151619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 02/06/2024] [Accepted: 02/10/2024] [Indexed: 03/21/2024]
Abstract
OBJECTIVES This study systematically investigates the evidence regarding the use of probiotics in managing cancer-related fatigue (CRF). STUDY DESIGN We conducted a systematic review of randomized controlled trials. DATA SOURCES The systematic search encompassed six databases: PubMed, CINHAL, Cochrane Database of Systematic Reviews, Web of Science, Scopus, and EMBASE, covering the period from inception to December 2023. The assessment of risk of bias employed the Cochrane risk of bias tool (RoB 2). A narrative synthesis and an exploratory meta-analysis were conducted to summarize the evidence. RESULTS Among 460 records, three studies met the eligibility criteria and were included in the review. These studies involved a total of 284 participants with colorectal and breast cancer. One study demonstrated a marginal improvement in CRF postchemotherapy in colorectal cancer patients using probiotics. Another study, also using probiotics, reported a significant reduction in CRF among colorectal cancer patients undergoing chemotherapy. Additionally, a study employing synbiotics showed a substantial decrease in CRF severity in breast cancer patients receiving chemotherapy. CONCLUSION The study presents initial but varied evidence suggesting the potential of probiotics and synbiotics as adjunctive therapies in managing CRF alongside anticancer treatments. IMPLICATIONS FOR NURSING PRACTICE In nursing practice, large-scale clinical trials are urgently needed to evaluate the effectiveness of probiotics in treating cancer-related fatigue during cancer therapy. Insights from this review could guide nurses in selecting appropriate probiotic strains and integrating microbiome modifiers into comprehensive care plans, potentially enhancing the quality of life for cancer patients.
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Affiliation(s)
- Silvia Belloni
- Gastroenterology Unit, IRCCS Humanitas Research Hospital, Rozzano, Italy
| | - Rosario Caruso
- Health Professions Research and Development Unit, IRCCS Policlinico San Donato, San Donato Milanese, Italy; Department of Biomedical Sciences for Health, University of Milan, Milan, Italy.
| | - Chiara Giacon
- Department of Public Health, Experimental and Forensic Medicine, Section of Hygiene, University of Pavia, Pavia, Italy
| | - Irene Baroni
- Health Professions Research and Development Unit, IRCCS Policlinico San Donato, San Donato Milanese, Italy
| | - Gianluca Conte
- Health Professions Research and Development Unit, IRCCS Policlinico San Donato, San Donato Milanese, Italy
| | - Arianna Magon
- Health Professions Research and Development Unit, IRCCS Policlinico San Donato, San Donato Milanese, Italy
| | - Cristina Arrigoni
- Department of Public Health, Experimental and Forensic Medicine, Section of Hygiene, University of Pavia, Pavia, Italy
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Sun Y, Liu W, Su M, Zhang T, Li X, Liu W, Cai Y, Zhao D, Yang M, Zhu Z, Wang J, Yu J. Purine salvage-associated metabolites as biomarkers for early diagnosis of esophageal squamous cell carcinoma: a diagnostic model-based study. Cell Death Discov 2024; 10:139. [PMID: 38485739 PMCID: PMC10940714 DOI: 10.1038/s41420-024-01896-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 02/23/2024] [Accepted: 02/27/2024] [Indexed: 03/18/2024] Open
Abstract
Esophageal squamous cell carcinoma (ESCC) remains an important health concern in developing countries. Patients with advanced ESCC have a poor prognosis and survival rate, and achieving early diagnosis remains a challenge. Metabolic biomarkers are gradually gaining attention as early diagnostic biomarkers. Hence, this multicenter study comprehensively evaluated metabolism dysregulation in ESCC through an integrated research strategy to identify key metabolite biomarkers of ESCC. First, the metabolic profiles were examined in tissue and serum samples from the discovery cohort (n = 162; ESCC patients, n = 81; healthy volunteers, n = 81), and ESCC tissue-induced metabolite alterations were observed in the serum. Afterward, RNA sequencing of tissue samples (n = 46) was performed, followed by an integrated analysis of metabolomics and transcriptomics. The potential biomarkers for ESCC were further identified by censoring gene-metabolite regulatory networks. The diagnostic value of the identified biomarkers was validated in a validation cohort (n = 220), and the biological function was verified. A total of 457 dysregulated metabolites were identified in the serum, of which 36 were induced by tumor tissues. The integrated analyses revealed significant alterations in the purine salvage pathway, wherein the abundance of hypoxanthine/xanthine exhibited a positive correlation with HPRT1 expression and tumor size. A diagnostic model was developed using two purine salvage-associated metabolites. This model could accurately discriminate patients with ESCC from normal individuals, with an area under the curve (AUC) (95% confidence interval (CI): 0.680-0.843) of 0.765 in the external cohort. Hypoxanthine and HPRT1 exerted a synergistic effect in terms of promoting ESCC progression. These findings are anticipated to provide valuable support in developing novel diagnostic approaches for early ESCC and enhance our comprehension of the metabolic mechanisms underlying this disease.
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Affiliation(s)
- Yawen Sun
- Department of Medical Epidemiology and Biostatistics, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, 250117, China
| | - Wenjuan Liu
- Shandong Provincial Key Laboratory of Radiation Oncology, Cancer Research Center, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, 250117, China
| | - Mu Su
- Berry Oncology Corporation, Beijing, 102206, China
| | - Tao Zhang
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China
| | - Xia Li
- Department of Public Health, Shandong Public Health Clinical Center, Shandong University, Jinan, Shandong, 250013, China
| | - Wenbin Liu
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 200032, China
| | - Yuping Cai
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 200032, China
| | - Deli Zhao
- Tumor Preventative and Therapeutic Base of Shandong Province, Feicheng People's Hospital, Feicheng, Shandong, 271600, China
| | - Ming Yang
- Shandong Provincial Key Laboratory of Radiation Oncology, Cancer Research Center, Shandong Cancer Hospital and Institute, Jinan, Shandong, 250117, China
| | - Zhengjiang Zhu
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 200032, China.
| | - Jialin Wang
- Department of Medical Epidemiology and Biostatistics, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, 250117, China.
| | - Jinming Yu
- Department of Radiation Oncology and Shandong Provincial Key Laboratory of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, 250117, China.
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Liu X, Gao Y, Fu L, Li X, Ma J. Cutaneous Melanoma and 486 Human Blood Metabolites: A Mendelian Randomization Study. Aesthetic Plast Surg 2024:10.1007/s00266-024-03873-x. [PMID: 38438761 DOI: 10.1007/s00266-024-03873-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 01/25/2024] [Indexed: 03/06/2024]
Abstract
BACKGROUND Cutaneous melanoma (CM) has long been recognized as a lethal form of cancer. Despite persistent research endeavors, the precise underlying pathological mechanisms remain largely unclear, and the optimal treatment for this patient population remains undetermined. OBJECTIVES This study aims to examine the causal associations between CM and 486 metabolites. METHODS A two-sample Mendelian randomization (MR) analysis was conducted to ascertain the causal relationship between blood metabolites and CM. The causality analysis involved the inverse variance weighted (IVW) method, followed by the MR-Egger and weighted median (WM) methods. To increase the robustness of our findings, several sensitivity analyses, including the MR-Egger intercept, Cochran's Q test, and MR-pleiotropy residual sum and outlier (MR-PRESSO), were performed. The robustness of our results was further validated in independent outcome samples followed by a meta-analysis. Additionally, a metabolic pathway analysis was carried out. RESULTS The two-sample MR analysis yielded a total of 27 metabolites as potential causal metabolites. After incorporating the outcomes of the sensitivity analyses, seven causal metabolites remained. Palmitoylcarnitine (OR 0.9903 95% CI 0.9848-0.9958, p = 0.0005) emerged as the sole metabolite with a significant causality after Bonferroni correction. Furthermore, the reverse MR analysis provided no evidence of reverse causality from CM to the identified metabolites. CONCLUSIONS This study suggested a causal relationship between seven human blood metabolites and the development of CM, thereby offering novel insights into the underlying mechanisms involved. NO LEVEL ASSIGNED This journal requires that authors assign a level of evidence to each submission to which Evidence-Based Medicine rankings are applicable. This excludes Review Articles, Book Reviews, and manuscripts that concern Basic Science, Animal Studies, Cadaver Studies, and Experimental Studies. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .
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Affiliation(s)
- Xuanchen Liu
- Department of Facial and Cervical Plastic Surgery, Plastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yuan Gao
- Department of Facial and Cervical Plastic Surgery, Plastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Li Fu
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xin Li
- Department of Facial and Cervical Plastic Surgery, Plastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
| | - Jiguang Ma
- Department of Facial and Cervical Plastic Surgery, Plastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
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Fei X, Du X, Wang J, Liu J, Gong Y, Zhao Z, Cao Z, Fu Q, Zhu Y, Dong L, Dong B, Pan J, Sun W, Xie S, Xue W. Precise diagnosis and risk stratification of prostate cancer by comprehensive serum metabolic fingerprints: a prediction model study. Int J Surg 2024; 110:1450-1462. [PMID: 38181121 PMCID: PMC10942223 DOI: 10.1097/js9.0000000000001033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 12/11/2023] [Indexed: 01/07/2024]
Abstract
OBJECTIVES Prostate cancer (PCa) is one of the most common malignancies in men worldwide and has caused increasing clinical morbidity and mortality, making timely diagnosis and accurate staging crucial. The authors introduced a novel approach based on mass spectrometry for precise diagnosis and stratification of PCa to facilitate clinical decision-making. METHODS Matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry analysis of trace blood samples was combined with machine learning algorithms to construct diagnostic and stratification models. A total of 367 subjects, comprising 181 with PCa and 186 with non-PCa were enrolled. Additional 60 subjects, comprising 30 with PCa and 30 with non-PCa were enrolled as an external cohort for validation. Subsequent metabolomic analysis was carried out using Autoflex MALDI-TOF, and the mass spectra were introduced into various algorithms to construct different models. RESULTS Serum metabolic fingerprints were successfully obtained from 181 patients with PCa and 186 patients with non-PCa. The diagnostic model based on the eight signals demonstrated a remarkable area under curve of 100% and was validated in the external cohort with the area under curve of 87.3%. Fifteen signals were selected for enrichment analysis, revealing the potential metabolic pathways that facilitate tumorigenesis. Furthermore, the stage prediction model with an overall accuracy of 85.9% precisely classified subjects with localized disease and those with metastasis. The risk stratification model, with an overall accuracy of 89.6%, precisely classified the subjects as low-risk and high-risk. CONCLUSIONS Our study facilitated the timely diagnosis and risk stratification of PCa and provided new insights into the underlying mechanisms of metabolic alterations in PCa.
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Affiliation(s)
| | | | | | | | | | - Zejun Zhao
- Department of Ultrasound, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine
| | - Zhibin Cao
- Medical Science and Technology Innovation Center, Shandong First Medical University and Shandong Academy of Medical Sciences, Shandong, People’s Republic of China
| | - Qibo Fu
- Medical Science and Technology Innovation Center, Shandong First Medical University and Shandong Academy of Medical Sciences, Shandong, People’s Republic of China
| | | | | | | | | | - Wenshe Sun
- Department of Urology, Jiading District Central Hospital, Shanghai University of Medicine and Health Sciences, Shanghai
| | - Shaowei Xie
- Department of Ultrasound, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine
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Xie Q, Liu S, Zhang S, Liao L, Xiao Z, Wang S, Zhang P. Research progress on the multi-omics and survival status of circulating tumor cells. Clin Exp Med 2024; 24:49. [PMID: 38427120 PMCID: PMC10907490 DOI: 10.1007/s10238-024-01309-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Accepted: 02/08/2024] [Indexed: 03/02/2024]
Abstract
In the dynamic process of metastasis, circulating tumor cells (CTCs) emanate from the primary solid tumor and subsequently acquire the capacity to disengage from the basement membrane, facilitating their infiltration into the vascular system via the interstitial tissue. Given the pivotal role of CTCs in the intricate hematogenous metastasis, they have emerged as an essential resource for a deeper comprehension of cancer metastasis while also serving as a cornerstone for the development of new indicators for early cancer screening and new therapeutic targets. In the epoch of precision medicine, as CTC enrichment and separation technologies continually advance and reach full fruition, the domain of CTC research has transcended the mere straightforward detection and quantification. The rapid advancement of CTC analysis platforms has presented a compelling opportunity for in-depth exploration of CTCs within the bloodstream. Here, we provide an overview of the current status and research significance of multi-omics studies on CTCs, including genomics, transcriptomics, proteomics, and metabolomics. These studies have contributed to uncovering the unique heterogeneity of CTCs and identifying potential metastatic targets as well as specific recognition sites. We also review the impact of various states of CTCs in the bloodstream on their metastatic potential, such as clustered CTCs, interactions with other blood components, and the phenotypic states of CTCs after undergoing epithelial-mesenchymal transition (EMT). Within this context, we also discuss the therapeutic implications and potential of CTCs.
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Affiliation(s)
- Qingming Xie
- NHC Key Laboratory of Cancer Proteomics, Department of Oncology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China
| | - Shilei Liu
- NHC Key Laboratory of Cancer Proteomics, Department of Oncology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China
| | - Sai Zhang
- NHC Key Laboratory of Cancer Proteomics, Department of Oncology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China
| | - Liqiu Liao
- Department of Breast Surgery, Hunan Clinical Meditech Research Center for Breast Cancer, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China
| | - Zhi Xiao
- Department of Breast Surgery, Hunan Clinical Meditech Research Center for Breast Cancer, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China
| | - Shouman Wang
- Department of Breast Surgery, Hunan Clinical Meditech Research Center for Breast Cancer, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China.
| | - Pengfei Zhang
- NHC Key Laboratory of Cancer Proteomics, Department of Oncology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China.
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China.
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Zhang M, Liu F, Shi F, Chen H, Hu Y, Sun H, Qi H, Xiong W, Deng C, Sun N. High-throughput detection allied with machine learning for precise monitoring of significant serum metabolic changes in Helicobacter pylori infection. Talanta 2024; 269:125483. [PMID: 38042145 DOI: 10.1016/j.talanta.2023.125483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 11/20/2023] [Accepted: 11/23/2023] [Indexed: 12/04/2023]
Abstract
High-throughput detection of large-scale samples is the foundation for rapidly accessing massive metabolic data in precision medicine. Machine learning is a powerful tool for uncovering valuable information hidden within massive data. In this work, we achieved the extraction of a single fingerprinting of 1 μL serum within 5 s through a high-throughput detection platform based on functionalized nanoparticles. We quickly obtained over a thousand serum metabolic fingerprintings (SMFs) including those of individuals with Helicobacter pylori (HP) infection. Combining four classical machine learning models and enrichment analysis, we attempted to extract and confirm useful information behind these SMFs. Based on all fingerprint signals, all four models achieved area under the curve (AUC) values of 0.983-1. In particular, orthogonal partial least squares discriminant analysis (OPLS-DA) model obtained value of 1 in both the discovery and validation sets. Fortunately, we identified six significant metabolic features, all of which can greatly contribute to the monitoring of HP infection, with AUC values ranging from 0.906 to 0.985. The combination of these six significant metabolic features can enable the precise monitoring of HP infection in serum, with over 95 % of accuracy, specificity and sensitivity. The OPLS-DA model displayed optimal performance and the corresponding scatter plot visualized the clear distinction between HP and HC. Interestingly, they exhibit a consistent reduction trend compared to healthy controls, prompting us to explore the possible metabolic pathways and potential mechanism. This work demonstrates the potential alliance between high-throughput detection and machine learning, advancing their application in precision medicine.
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Affiliation(s)
- Man Zhang
- Department of Chemistry, Department of Gastroenterology and Hepatology, Zhongshan Hospital, Fudan University, Shanghai, 200433, China
| | - Fenghua Liu
- Department of Gastroenterology, Shibei Hospital of Jing'an District of Shanghai, 4500 Gong He Xin Road, Shanghai, 200435, China
| | - Fangying Shi
- Department of Chemistry, Department of Gastroenterology and Hepatology, Zhongshan Hospital, Fudan University, Shanghai, 200433, China
| | - Haolin Chen
- Department of Chemistry, Department of Gastroenterology and Hepatology, Zhongshan Hospital, Fudan University, Shanghai, 200433, China
| | - Yi Hu
- Department of Emergency Shibei Hospital of Jing'an District of Shanghai, 4500 Gong He Xin Road, Shanghai, 200435, China
| | - Hong Sun
- Medical Examination Section, Shibei Hospital of Jing'an District of Shanghai, 4500 Gong He Xin Road, Shanghai, 200435, China
| | - Hongxia Qi
- Department of Gastroenterology, Shibei Hospital of Jing'an District of Shanghai, 4500 Gong He Xin Road, Shanghai, 200435, China
| | - Wenjian Xiong
- Department of Gastroenterology, Shibei Hospital of Jing'an District of Shanghai, 4500 Gong He Xin Road, Shanghai, 200435, China.
| | - Chunhui Deng
- Department of Chemistry, Department of Gastroenterology and Hepatology, Zhongshan Hospital, Fudan University, Shanghai, 200433, China; School of Chemistry and Chemical Engineering, Nanchang University, Nanchang, 330031, China.
| | - Nianrong Sun
- Department of Chemistry, Department of Gastroenterology and Hepatology, Zhongshan Hospital, Fudan University, Shanghai, 200433, China.
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Huang L, Li H, Zhang C, Chen Q, Liu Z, Zhang J, Luo P, Wei T. Unlocking the potential of T-cell metabolism reprogramming: Advancing single-cell approaches for precision immunotherapy in tumour immunity. Clin Transl Med 2024; 14:e1620. [PMID: 38468489 PMCID: PMC10928360 DOI: 10.1002/ctm2.1620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Revised: 02/20/2024] [Accepted: 02/22/2024] [Indexed: 03/13/2024] Open
Abstract
As single-cell RNA sequencing enables the detailed clustering of T-cell subpopulations and facilitates the analysis of T-cell metabolic states and metabolite dynamics, it has gained prominence as the preferred tool for understanding heterogeneous cellular metabolism. Furthermore, the synergistic or inhibitory effects of various metabolic pathways within T cells in the tumour microenvironment are coordinated, and increased activity of specific metabolic pathways generally corresponds to increased functional activity, leading to diverse T-cell behaviours related to the effects of tumour immune cells, which shows the potential of tumour-specific T cells to induce persistent immune responses. A holistic understanding of how metabolic heterogeneity governs the immune function of specific T-cell subsets is key to obtaining field-level insights into immunometabolism. Therefore, exploring the mechanisms underlying the interplay between T-cell metabolism and immune functions will pave the way for precise immunotherapy approaches in the future, which will empower us to explore new methods for combating tumours with enhanced efficacy.
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Affiliation(s)
- Lihaoyun Huang
- Department of OncologyZhujiang HospitalSouthern Medical UniversityGuangzhouChina
- The First Clinical Medical SchoolSouthern Medical UniversityGuangzhouChina
| | - Haitao Li
- Department of OncologyTaishan People's HospitalGuangzhouChina
| | - Cangang Zhang
- Department of Pathogenic Microbiology and ImmunologySchool of Basic Medical SciencesXi'an Jiaotong UniversityXi'anShaanxiChina
| | - Quan Chen
- Department of NeurosurgeryXiangya HospitalCentral South UniversityChangshaHunanChina
| | - Zaoqu Liu
- Key Laboratory of ProteomicsBeijing Proteome Research CenterNational Center for Protein Sciences (Beijing)Beijing Institute of LifeomicsBeijingChina
- Key Laboratory of Medical Molecular BiologyChinese Academy of Medical SciencesDepartment of PathophysiologyPeking Union Medical CollegeInstitute of Basic Medical SciencesBeijingChina
| | - Jian Zhang
- Department of OncologyZhujiang HospitalSouthern Medical UniversityGuangzhouChina
- The First Clinical Medical SchoolSouthern Medical UniversityGuangzhouChina
| | - Peng Luo
- Department of OncologyZhujiang HospitalSouthern Medical UniversityGuangzhouChina
- The First Clinical Medical SchoolSouthern Medical UniversityGuangzhouChina
| | - Ting Wei
- Department of OncologyZhujiang HospitalSouthern Medical UniversityGuangzhouChina
- The First Clinical Medical SchoolSouthern Medical UniversityGuangzhouChina
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Shao Y, Yesseyeva G, Zhi Y, Zhou J, Zong J, Zhou X, Fan X, Li S, Huang L, Zhang S, Dong F, Yang X, Zheng M, Sun J, Ma J. Comprehensive multi-omics analysis and experimental verification reveal PFDN5 is a novel prognostic and therapeutic biomarker for gastric cancer. Genomics 2024; 116:110821. [PMID: 38447684 DOI: 10.1016/j.ygeno.2024.110821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2023] [Revised: 02/28/2024] [Accepted: 03/02/2024] [Indexed: 03/08/2024]
Abstract
Prefoldin Subunit 5 (PFDN5) plays a critical role as a member of the prefoldins (PFDNs) in maintaining a finely tuned equilibrium between protein production and degradation. However, there has been no comprehensive analysis specifically focused on PFDN5 thus far. Here, a comprehensive multi-omics (transcriptomics, genomics, and proteomics) analysis, systematic molecular biology experiments (in vitro and in vivo), transcriptome sequencing and PCR Array were performed for identifying the value of PFDN5 in pan-cancer, especially in Gastric Cancer (GC). We found PFDN5 had the potential to serve as a prognostic and therapeutic biomarker in GC. And PFDN5 could promote the proliferation of GC cells, primarily by affecting the cell cycle, cell death and immune process etc. These findings provide novel insights into the molecular mechanisms and precise treatments of in GC.
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Affiliation(s)
- Yanfei Shao
- Department of General Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai Minimally Invasive Surgery Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai Institute of Digestive Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Galiya Yesseyeva
- Department of General Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai Minimally Invasive Surgery Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai Institute of Digestive Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yihao Zhi
- Department of General Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai Minimally Invasive Surgery Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai Institute of Digestive Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jiajie Zhou
- Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jiasheng Zong
- Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xueliang Zhou
- Department of General Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai Minimally Invasive Surgery Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai Institute of Digestive Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiaodong Fan
- Department of General Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai Minimally Invasive Surgery Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai Institute of Digestive Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Shuchun Li
- Department of General Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai Minimally Invasive Surgery Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai Institute of Digestive Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ling Huang
- Department of General Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai Minimally Invasive Surgery Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai Institute of Digestive Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Sen Zhang
- Department of General Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai Minimally Invasive Surgery Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Feng Dong
- Department of General Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai Minimally Invasive Surgery Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiao Yang
- Department of General Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai Minimally Invasive Surgery Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Minhua Zheng
- Department of General Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai Minimally Invasive Surgery Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Jing Sun
- Department of General Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai Minimally Invasive Surgery Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Junjun Ma
- Department of General Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai Minimally Invasive Surgery Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
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Wang S, Yu L, Chen L, Zeng T, Xing X, Wei Z. Discovery of metabolite biomarkers for odontogenic keratocysts. Metabolomics 2024; 20:30. [PMID: 38416246 DOI: 10.1007/s11306-024-02101-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Accepted: 02/06/2024] [Indexed: 02/29/2024]
Abstract
INTRODUCTION Odontogenic keratocysts (OKCs) are locally aggressive and have a high rate of recurrence, but the pathogenesis of OKCs is not fully understood. We aimed to investigate the serum metabolomic profile of OKCs and discover potential biomarkers. METHODS Metabolomic analysis was performed on 42 serum samples from 22 OKC patients and 20 healthy controls (HCs) using gas chromatography‒mass spectrometry to identify dysregulated metabolites in the OKC samples. LASSO regression and receiver operating characteristic (ROC) curve analyses were used to select and validate metabolic biomarkers and develop diagnostic models. RESULTS A total of 73 metabolites were identified in the serum samples, and 24 metabolites were dysregulated in the OKC samples, of which 4 were upregulated. Finally, a diagnostic panel of 10 metabolites was constructed that accurately diagnosed OKCs (sensitivity of 100%, specificity of 100%, area under the curve of 1.00). CONCLUSION This study is the first to investigate the metabolic characteristics and potential metabolic biomarkers in the serum of OKC patients using GC‒MS. Our study provides further evidence to explore the pathogenesis of OKC.
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Affiliation(s)
- Shuai Wang
- Central Laboratory of Stomatology, Nanjing Stomatological Hospital, Affiliated Hospital of Medical School, Institute of Stomatology, Nanjing University, Nanjing, 210008, Jiangsu, China
- Department of Oral and Maxillofacial Surgery, Nanjing Stomatological Hospital, Affiliated Hospital of Medical School, Institute of Stomatology, Nanjing University, Nanjing, 210008, Jiangsu, China
| | - Liyuan Yu
- Central Laboratory of Stomatology, Nanjing Stomatological Hospital, Affiliated Hospital of Medical School, Institute of Stomatology, Nanjing University, Nanjing, 210008, Jiangsu, China
| | - Lin Chen
- Central Laboratory of Stomatology, Nanjing Stomatological Hospital, Affiliated Hospital of Medical School, Institute of Stomatology, Nanjing University, Nanjing, 210008, Jiangsu, China
| | - Tao Zeng
- State Key Lab of Pharmaceutical Biotechnology, College of Life Sciences, Nanjing University, Nanjing, 210008, Jiangsu, China
| | - Xianghui Xing
- Pediatric Dentistry, Nanjing Stomatology Hospital, Affiliated Hospital of Medical School, Institute of Stomatology, Nanjing University, Nanjing, 210008, Jiangsu, China.
| | - Zheng Wei
- Pediatric Dentistry, Nanjing Stomatology Hospital, Affiliated Hospital of Medical School, Institute of Stomatology, Nanjing University, Nanjing, 210008, Jiangsu, China.
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47
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Liu H, Chen X, Wang P, Chen M, Deng C, Qian X, Bai J, Li Z, Yu X. PRMT1-mediated PGK1 arginine methylation promotes colorectal cancer glycolysis and tumorigenesis. Cell Death Dis 2024; 15:170. [PMID: 38402202 PMCID: PMC10894231 DOI: 10.1038/s41419-024-06544-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 02/05/2024] [Accepted: 02/06/2024] [Indexed: 02/26/2024]
Abstract
Many types of cancer cells, including colorectal cancer cells (CRC), can simultaneously enhance glycolysis and repress the mitochondrial tricarboxylic acid (TCA) cycle, which is called the Warburg effect. However, the detailed mechanisms of abnormal activation of the glycolysis pathway in colorectal cancer are largely unknown. In this study, we reveal that the protein arginine methyltransferase 1 (PRMT1) promotes glycolysis, proliferation, and tumorigenesis in CRC cells. Mechanistically, PRMT1-mediated arginine asymmetric dimethylation modification of phosphoglycerate kinase 1 (PGK1, the first ATP-producing enzyme in glycolysis) at R206 (meR206-PGK1) enhances the phosphorylation level of PGK1 at S203 (pS203-PGK1), which inhibits mitochondrial function and promotes glycolysis. We found that PRMT1 and meR206-PGK1 expression were positively correlated with pS203-PGK1 expression in tissues from colorectal cancer patients. Furthermore, we also confirmed that meR206-PGK1 expression is positively correlated with the poor survival of patients with colorectal cancer. Our findings show that PRMT1 and meR206-PGK1 may become promising predictive biomarkers for the prognosis of patients with CRC and that arginine methyltransferase inhibitors have great potential in colorectal cancer treatment.
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Affiliation(s)
- Hao Liu
- School of Medicine, Nankai University, Tianjin, China
- Cancer Institute, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Xintian Chen
- Department of Gastroenterology, the Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, China
| | - Pengfei Wang
- Department of Gastroenterology, the First People's Hospital of Shuyang County, Suqian, Jiangsu, China
| | - Miaolei Chen
- Cancer Institute, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Chuyin Deng
- Cancer Institute, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Xingyou Qian
- Cancer Institute, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Jin Bai
- Cancer Institute, Xuzhou Medical University, Xuzhou, Jiangsu, China.
- Center of Clinical Oncology, the Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, China.
- Jiangsu Center for the Collaboration and Innovation of Cancer Biotherapy, Cancer Institute, Xuzhou Medical University, Xuzhou, Jiangsu, China.
| | - Zhongwei Li
- Cancer Institute, Xuzhou Medical University, Xuzhou, Jiangsu, China.
- Laboratory of Tumor Epigenetics, Department of Pathophysiology, School of Basic Medical Sciences, Wannan Medical College, Wuhu, Anhui, China.
| | - Xiangyang Yu
- School of Medicine, Nankai University, Tianjin, China.
- Department of Gastrointestinal Surgery, the Hospital of Integrated Chinese and Western Medicine, Tianjin, China.
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48
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Jayakrishnan T, Mariam A, Farha N, Rotroff DM, Aucejo F, Barot SV, Conces M, Nair KG, Krishnamurthi SS, Schmit SL, Liska D, Khorana AA, Kamath SD. Plasma metabolomic differences in early-onset compared to average-onset colorectal cancer. Sci Rep 2024; 14:4294. [PMID: 38383634 PMCID: PMC10881959 DOI: 10.1038/s41598-024-54560-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 02/14/2024] [Indexed: 02/23/2024] Open
Abstract
Deleterious effects of environmental exposures may contribute to the rising incidence of early-onset colorectal cancer (eoCRC). We assessed the metabolomic differences between patients with eoCRC, average-onset CRC (aoCRC), and non-CRC controls, to understand pathogenic mechanisms. Patients with stage I-IV CRC and non-CRC controls were categorized based on age ≤ 50 years (eoCRC or young non-CRC controls) or ≥ 60 years (aoCRC or older non-CRC controls). Differential metabolite abundance and metabolic pathway analyses were performed on plasma samples. Multivariate Cox proportional hazards modeling was used for survival analyses. All P values were adjusted for multiple testing (false discovery rate, FDR P < 0.15 considered significant). The study population comprised 170 patients with CRC (66 eoCRC and 104 aoCRC) and 49 non-CRC controls (34 young and 15 older). Citrate was differentially abundant in aoCRC vs. eoCRC in adjusted analysis (Odds Ratio = 21.8, FDR P = 0.04). Metabolic pathways altered in patients with aoCRC versus eoCRC included arginine biosynthesis, FDR P = 0.02; glyoxylate and dicarboxylate metabolism, FDR P = 0.005; citrate cycle, FDR P = 0.04; alanine, aspartate, and glutamate metabolism, FDR P = 0.01; glycine, serine, and threonine metabolism, FDR P = 0.14; and amino-acid t-RNA biosynthesis, FDR P = 0.01. 4-hydroxyhippuric acid was significantly associated with overall survival in all patients with CRC (Hazards ratio, HR = 0.4, 95% CI 0.3-0.7, FDR P = 0.05). We identified several unique metabolic alterations, particularly the significant differential abundance of citrate in aoCRC versus eoCRC. Arginine biosynthesis was the most enriched by the differentially altered metabolites. The findings hold promise in developing strategies for early detection and novel therapies.
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Affiliation(s)
- Thejus Jayakrishnan
- Department of Hematology and Oncology, Taussig Cancer Institute, Cleveland Clinic, Cleveland, USA
| | - Arshiya Mariam
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, USA
- Center for Quantitative Metabolic Research, Cleveland Clinic, Cleveland, USA
| | - Nicole Farha
- Department of Hematology and Oncology, Taussig Cancer Institute, Cleveland Clinic, Cleveland, USA
| | - Daniel M Rotroff
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, USA
- Center for Quantitative Metabolic Research, Cleveland Clinic, Cleveland, USA
| | - Federico Aucejo
- Department of Surgery, Digestive Disease & Surgery Institute, Cleveland Clinic, Cleveland, USA
| | - Shimoli V Barot
- Department of Hematology and Oncology, Taussig Cancer Institute, Cleveland Clinic, Cleveland, USA
- Case Comprehensive Cancer Center, Cleveland, USA
| | - Madison Conces
- Case Comprehensive Cancer Center, Cleveland, USA
- Department of Hematology-Oncology, University Hospital Seidman Cancer Center, Cleveland, USA
| | - Kanika G Nair
- Department of Hematology and Oncology, Taussig Cancer Institute, Cleveland Clinic, Cleveland, USA
- Case Comprehensive Cancer Center, Cleveland, USA
- Center for Young-Onset Colorectal Cancer, Cleveland Clinic, Cleveland, USA
| | - Smitha S Krishnamurthi
- Department of Hematology and Oncology, Taussig Cancer Institute, Cleveland Clinic, Cleveland, USA
- Case Comprehensive Cancer Center, Cleveland, USA
- Center for Young-Onset Colorectal Cancer, Cleveland Clinic, Cleveland, USA
| | - Stephanie L Schmit
- Center for Young-Onset Colorectal Cancer, Cleveland Clinic, Cleveland, USA
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, USA
- Population and Cancer Prevention Program, Case Comprehensive Cancer Center, Cleveland, USA
| | - David Liska
- Case Comprehensive Cancer Center, Cleveland, USA
- Center for Young-Onset Colorectal Cancer, Cleveland Clinic, Cleveland, USA
- Department of Colorectal Surgery, Digestive Disease & Surgery Institute, Cleveland Clinic, Cleveland, USA
| | - Alok A Khorana
- Department of Hematology and Oncology, Taussig Cancer Institute, Cleveland Clinic, Cleveland, USA
- Case Comprehensive Cancer Center, Cleveland, USA
- Center for Young-Onset Colorectal Cancer, Cleveland Clinic, Cleveland, USA
| | - Suneel D Kamath
- Department of Hematology and Oncology, Taussig Cancer Institute, Cleveland Clinic, Cleveland, USA.
- Case Comprehensive Cancer Center, Cleveland, USA.
- Center for Young-Onset Colorectal Cancer, Cleveland Clinic, Cleveland, USA.
- Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, OH, USA.
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49
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Luo G, Wang S, Lu W, Ju W, Li J, Tan X, Zhao H, Han W, Yang X. Application of metabolomics in oral squamous cell carcinoma. Oral Dis 2024. [PMID: 38376209 DOI: 10.1111/odi.14895] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 01/17/2024] [Accepted: 02/02/2024] [Indexed: 02/21/2024]
Abstract
BACKGROUND Oral squamous cell carcinoma (OSCC) is a prevalent malignancy affecting the head and neck region. The prognosis for OSCC patients remains unfavorable due to the absence of precise and efficient early diagnostic techniques. Metabolomics offers a promising approach for identifying distinct metabolites, thereby facilitating early detection and treatment of OSCC. OBJECTIVE This review aims to provide a comprehensive overview of recent advancements in metabolic marker identification for early OSCC diagnosis. Additionally, the clinical significance and potential applications of metabolic markers for the management of OSCC are discussed. RESULTS This review summarizes metabolic changes during the occurrence and development of oral squamous cell carcinoma and reviews prospects for the clinical application of characteristic, differential metabolites in saliva, serum, and OSCC tissue. In this review, the application of metabolomic technology in OSCC research was summarized, and future research directions were proposed. CONCLUSION Metabolomics, detection technology that is the closest to phenotype, can efficiently identify differential metabolites. Combined with statistical data analyses and artificial intelligence technology, it can rapidly screen characteristic biomarkers for early diagnosis, treatment, and prognosis evaluations.
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Affiliation(s)
- Guanfa Luo
- Department of Oral and Maxillofacial Surgery, Affiliated Hospital of Jiangsu University, Zhenjiang, China
- Department of Burn and Plastic Surgery, Affiliated Hospital of Jiangsu University, Zhenjiang, China
| | - Shuai Wang
- Department of Oral and Maxillofacial Surgery, Nanjing Stomatological Hospital, Medical School of Nanjing University, Nanjing, China
| | - Wen Lu
- Department of Oral and Maxillofacial Surgery, Affiliated Hospital of Jiangsu University, Zhenjiang, China
| | - Wei Ju
- Department of Burn and Plastic Surgery, Affiliated Hospital of Jiangsu University, Zhenjiang, China
| | - Jianhong Li
- Department of Oral and Maxillofacial Surgery, Affiliated Hospital of Jiangsu University, Zhenjiang, China
| | - Xiao Tan
- Department of Oral and Maxillofacial Surgery, Affiliated Hospital of Jiangsu University, Zhenjiang, China
| | - Huiting Zhao
- Department of Oral and Maxillofacial Surgery, Affiliated Hospital of Jiangsu University, Zhenjiang, China
| | - Wei Han
- Department of Oral and Maxillofacial Surgery, Nanjing Stomatological Hospital, Medical School of Nanjing University, Nanjing, China
| | - Xihu Yang
- Department of Oral and Maxillofacial Surgery, Affiliated Hospital of Jiangsu University, Zhenjiang, China
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50
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More TH, Hiller K, Seifert M, Illig T, Schmidt R, Gronauer R, von Hahn T, Weilert H, Stang A. Metabolomics analysis reveals novel serum metabolite alterations in cancer cachexia. Front Oncol 2024; 14:1286896. [PMID: 38450189 PMCID: PMC10915872 DOI: 10.3389/fonc.2024.1286896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Accepted: 02/05/2024] [Indexed: 03/08/2024] Open
Abstract
Background Cachexia is a body wasting syndrome that significantly affects well-being and prognosis of cancer patients, without effective treatment. Serum metabolites take part in pathophysiological processes of cancer cachexia, but apart from altered levels of select serum metabolites, little is known on the global changes of the overall serum metabolome, which represents a functional readout of the whole-body metabolic state. Here, we aimed to comprehensively characterize serum metabolite alterations and analyze associated pathways in cachectic cancer patients to gain new insights that could help instruct strategies for novel interventions of greater clinical benefit. Methods Serum was sampled from 120 metastatic cancer patients (stage UICC IV). Patients were grouped as cachectic or non-cachectic according to the criteria for cancer cachexia agreed upon international consensus (main criterium: weight loss adjusted to body mass index). Samples were pooled by cachexia phenotype and assayed using non-targeted gas chromatography-mass spectrometry (GC-MS). Normalized metabolite levels were compared using t-test (p < 0.05, adjusted for false discovery rate) and partial least squares discriminant analysis (PLS-DA). Machine-learning models were applied to identify metabolite signatures for separating cachexia states. Significant metabolites underwent MetaboAnalyst 5.0 pathway analysis. Results Comparative analyses included 78 cachectic and 42 non-cachectic patients. Cachectic patients exhibited 19 annotable, significantly elevated (including glucose and fructose) or decreased (mostly amino acids) metabolites associating with aminoacyl-tRNA, glutathione and amino acid metabolism pathways. PLS-DA showed distinct clusters (accuracy: 85.6%), and machine-learning models identified metabolic signatures for separating cachectic states (accuracy: 83.2%; area under ROC: 88.0%). We newly identified altered blood levels of erythronic acid and glucuronic acid in human cancer cachexia, potentially linked to pentose-phosphate and detoxification pathways. Conclusion We found both known and yet unknown serum metabolite and metabolic pathway alterations in cachectic cancer patients that collectively support a whole-body metabolic state with impaired detoxification capability, altered glucose and fructose metabolism, and substrate supply for increased and/or distinct metabolic needs of cachexia-associated tumors. These findings together imply vulnerabilities, dependencies and targets for novel interventions that have potential to make a significant impact on future research in an important field of cancer patient care.
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Affiliation(s)
- Tushar H. More
- Department of Bioinformatics and Biochemistry, Braunschweig Integrated Centre of Systems Biology (BRICS), Technische Universität Braunschweig, Braunschweig, Germany
| | - Karsten Hiller
- Department of Bioinformatics and Biochemistry, Braunschweig Integrated Centre of Systems Biology (BRICS), Technische Universität Braunschweig, Braunschweig, Germany
| | - Martin Seifert
- Asklepios Precision Medicine, Asklepios Hospitals GmbH & Co KgaA, Königstein (Taunus), Germany
- Connexome GmbH, Fischen, Germany
| | - Thomas Illig
- Department of Human Genetics, Hannover Medical School, Hannover, Germany
- Hannover Unified Biobank (HUB), Hannover, Germany
| | - Rudi Schmidt
- Asklepios Precision Medicine, Asklepios Hospitals GmbH & Co KgaA, Königstein (Taunus), Germany
- Immunetrue, Cologne, Germany
| | - Raphael Gronauer
- Asklepios Precision Medicine, Asklepios Hospitals GmbH & Co KgaA, Königstein (Taunus), Germany
- Connexome GmbH, Fischen, Germany
| | - Thomas von Hahn
- Asklepios Hospital Barmbek, Department of Gastroenterology, Hepatology and Endoscopy, Hamburg, Germany
- Asklepios Tumorzentrum Hamburg, Hamburg, Germany
- Semmelweis University, Asklepios Campus Hamburg, Budapest, Hungary
| | - Hauke Weilert
- Asklepios Tumorzentrum Hamburg, Hamburg, Germany
- Semmelweis University, Asklepios Campus Hamburg, Budapest, Hungary
- Asklepios Hospital Barmbek, Department of Hematology, Oncology and Palliative Care Medicine, Hamburg, Germany
| | - Axel Stang
- Asklepios Tumorzentrum Hamburg, Hamburg, Germany
- Semmelweis University, Asklepios Campus Hamburg, Budapest, Hungary
- Asklepios Hospital Barmbek, Department of Hematology, Oncology and Palliative Care Medicine, Hamburg, Germany
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