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Biswas D, Liu YH, Herrero J, Wu Y, Moore DA, Karasaki T, Grigoriadis K, Lu WT, Veeriah S, Naceur-Lombardelli C, Magno N, Ward S, Frankell AM, Hill MS, Colliver E, de Carné Trécesson S, East P, Malhi A, Snell DM, O'Neill O, Leonce D, Mattsson J, Lindberg A, Micke P, Moldvay J, Megyesfalvi Z, Dome B, Fillinger J, Nicod J, Downward J, Szallasi Z, Hackshaw A, Jamal-Hanjani M, Kanu N, Birkbak NJ, Swanton C. Prospective validation of ORACLE, a clonal expression biomarker associated with survival of patients with lung adenocarcinoma. NATURE CANCER 2025; 6:86-101. [PMID: 39789179 PMCID: PMC11779643 DOI: 10.1038/s43018-024-00883-1] [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: 01/31/2024] [Accepted: 11/15/2024] [Indexed: 01/12/2025]
Abstract
Human tumors are diverse in their natural history and response to treatment, which in part results from genetic and transcriptomic heterogeneity. In clinical practice, single-site needle biopsies are used to sample this diversity, but cancer biomarkers may be confounded by spatiogenomic heterogeneity within individual tumors. Here we investigate clonally expressed genes as a solution to the sampling bias problem by analyzing multiregion whole-exome and RNA sequencing data for 450 tumor regions from 184 patients with lung adenocarcinoma in the TRACERx study. We prospectively validate the survival association of a clonal expression biomarker, Outcome Risk Associated Clonal Lung Expression (ORACLE), in combination with clinicopathological risk factors, and in stage I disease. We expand our mechanistic understanding, discovering that clonal transcriptional signals are detectable before tissue invasion, act as a molecular fingerprint for lethal metastatic clones and predict chemotherapy sensitivity. Lastly, we find that ORACLE summarizes the prognostic information encoded by genetic evolutionary measures, including chromosomal instability, as a concise 23-transcript assay.
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Grants
- C11496/A17786, C416/A21999 Cancer Research UK (CRUK)
- CC2041 Wellcome Trust
- CC2041 Arthritis Research UK
- Young Investigator Grant International Association for the Study of Lung Cancer (IASLC)
- 202060447 Japan Society for the Promotion of Science London (JSPS London)
- I4677 Austrian Science Fund (Fonds zur Förderung der Wissenschaftlichen Forschung)
- Wellcome Trust
- 220589/Z/20/Z Wellcome Trust (Wellcome)
- EDDCPJT\100008 Cancer Research UK (CRUK)
- UCL/12/0279 University College London (UCL)
- Bolyai Research Scholarship Hungarian Academy of Sciences | Magyar Tudományos Akadémia Számítástechnikai és Automatizálási Kutatóintézet (Számítástechnikai és Automatizálási Kutatóintézet)
- ID16584 Novo Nordisk Foundation Center for Basic Metabolic Research (NovoNordisk Foundation Center for Basic Metabolic Research)
- CTUQQR-DEC22/100009 Cancer Research UK
- Francis Crick Institute (Francis Crick Institute Limited)
- RCUK | Medical Research Council (MRC)
- Rosetrees Trust
- Breast Cancer Research Foundation (BCRF)
- Butterfield and Stoneygate Trusts National Institute for Health Research (NIHR) University College London Hospitals Biomedical Research Centre The Mark Foundation for Cancer Research Aspire Award (grant 21-029-ASP)
- Hungarian National Research, Development and Innovation Office (K129065)
- Hungarian National Research, Development, and Innovation Office (2020‐1.1.6‐JÖVŐ, TKP2021‐EGA‐33, FK‐143751 and FK-147045) New National Excellence Program of the Ministry for Innovation and Technology of Hungary (UNKP‐20‐3, UNKP‐21‐3 and UNKP-23-5)
- Lung Cancer Research Foundation (LCRF)
- DH | NIHR | Health Services Research Programme (NIHR Health Services Research Programme)
- NIH National Cancer Institute UKI NETs
- Hungarian National Research, Development, and Innovation Office (2020‐1.1.6‐JÖVŐ, TKP2021‐EGA‐33, FK‐143751 and FK-147045)
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Affiliation(s)
- Dhruva Biswas
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK.
- Bill Lyons Informatics Centre, University College London Cancer Institute, London, UK.
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK.
| | - Yun-Hsin Liu
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
| | - Javier Herrero
- Bill Lyons Informatics Centre, University College London Cancer Institute, London, UK
| | - Yin Wu
- Centre for Inflammation Biology and Cancer Immunology, King's College London, London, UK
- Department of Medical Oncology, Guy's Hospital, London, UK
| | - David A Moore
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
- Department of Cellular Pathology, University College London Hospitals, London, UK
| | - Takahiro Karasaki
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
- Cancer Metastasis Lab, University College London Cancer Institute, London, UK
- Department of Thoracic Surgery, Respiratory Center, Toranomon Hospital, Tokyo, Japan
| | - Kristiana Grigoriadis
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
- Cancer Genome Evolution Research Group, Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
| | - Wei-Ting Lu
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
| | - Selvaraju Veeriah
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
| | | | - Neil Magno
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
| | - Sophia Ward
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
- Genomics Science Technology Platform, The Francis Crick Institute, London, UK
| | - Alexander M Frankell
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
| | - Mark S Hill
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
| | - Emma Colliver
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
| | | | - Philip East
- Bioinformatics and Biostatistics, The Francis Crick Institute, London, UK
| | - Aman Malhi
- Cancer Research UK and University College London Cancer Trials Centre, University College London, London, UK
| | - Daniel M Snell
- Genomics Science Technology Platform, The Francis Crick Institute, London, UK
| | - Olga O'Neill
- Genomics Science Technology Platform, The Francis Crick Institute, London, UK
| | - Daniel Leonce
- Genomics Science Technology Platform, The Francis Crick Institute, London, UK
| | - Johanna Mattsson
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Amanda Lindberg
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Patrick Micke
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Judit Moldvay
- 1st Department of Pulmonology, National Koranyi Institute of Pulmonology, Budapest, Hungary
- Department of Pulmonology, University of Szeged Albert Szent-Gyorgyi Medical School, Szeged, Hungary
| | - Zsolt Megyesfalvi
- National Koranyi Institute of Pulmonology, Budapest, Hungary
- Department of Thoracic Surgery, Semmelweis University and National Institute of Oncology, Budapest, Hungary
- Department of Thoracic Surgery, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
| | - Balazs Dome
- National Koranyi Institute of Pulmonology, Budapest, Hungary
- Department of Thoracic Surgery, Semmelweis University and National Institute of Oncology, Budapest, Hungary
- Department of Thoracic Surgery, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
- Department of Translational Medicine, Lund University, Lund, Sweden
| | - János Fillinger
- National Koranyi Institute of Pulmonology, Budapest, Hungary
| | - Jerome Nicod
- Genomics Science Technology Platform, The Francis Crick Institute, London, UK
| | - Julian Downward
- Oncogene Biology Laboratory, The Francis Crick Institute, London, UK
| | - Zoltan Szallasi
- Computational Health Informatics Program, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Allan Hackshaw
- Cancer Research UK and University College London Cancer Trials Centre, University College London, London, UK
| | - Mariam Jamal-Hanjani
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Metastasis Lab, University College London Cancer Institute, London, UK
- Department of Oncology, University College London Hospitals, London, UK
| | - Nnennaya Kanu
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
| | - Nicolai J Birkbak
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK.
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK.
- Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark.
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.
| | - Charles Swanton
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK.
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK.
- Department of Oncology, University College London Hospitals, London, UK.
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2
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Zhang J, Zang X, Jiao P, Wu J, Meng W, Zhao L, Lv Z. Alterations of Ceramides, Acylcarnitines, GlyceroLPLs, and Amines in NSCLC Tissues. J Proteome Res 2024; 23:4343-4358. [PMID: 39317643 DOI: 10.1021/acs.jproteome.4c00344] [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: 09/26/2024]
Abstract
Abnormal lipid metabolism plays an important role in cancer development. In this study, nontargeted lipidomic study on 230 tissue specimens from 79 nonsmall cell lung cancer (NSCLC) patients was conducted using ultraperformance liquid chromatography-high-resolution mass spectrometry (UPLC-HRMS). Downregulation of sphingosine and medium-long-chain ceramides and short-medium-chain acylcarnitine, upregulation of long-chain acylcarnitine C20:0, and enhanced histamine methylation were revealed in NSCLC tissues. Compared with paired noncancerous tissues, adenocarcinoma (AC) tissues had significantly decreased levels of sphingosine, medium-long-chain ceramides (Cer d18:1/12:0 and Cer d16:1/14:0, Cer d18:0/16:0, Cer d18:1/16:0, Cer d18:2/16:0, Cer d18:2/18:0), short-medium-chain (C2-C16) acylcarnitines, LPC 20:0 and LPC 22:1, and significantly increased levels of the long-chain acylcarnitine C20:0, LPC 16:0, LPC P-16:0, LPC 20:1, LPC 20:2, glyceroPC, LPE 16:0, and LPE 18:2. In squamous cell carcinoma (SCC) tissues, sphingosine, Cer d18:2/16:0 and Cer d18:2/18:0, and short-medium-chain acylcarnitines had significantly lower levels, while long-chain acylcarnitines (C20:0, and C22:0 or C22:0 M), LPC 20:1, LPC 20:2, and N1,N12-diacetylspermine had significantly higher levels compared to controls. In AC and SCC tissues, the levels of LPG 18:0, LPG 18:1, and LPS 18:1 were significantly decreased, while the levels of ceramide-1-phosphate (C1P) d18:0/3:0 or LPE P-16:0, N1-acetylspermidine, and 1-methylhistamine were significantly increased than controls. Furthermore, an orthogonal partial least-squares-discriminant analysis (OPLS-DA) model based on a 4-lipid panel was established, showing good discrimination ability between cancerous and noncancerous tissues.
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Affiliation(s)
- Jie Zhang
- School of Medicine and Pharmacy, Ocean University of China, Qingdao, Shandong 266003, P. R. China
| | - Xiaoling Zang
- School of Medicine and Pharmacy, Ocean University of China, Qingdao, Shandong 266003, P. R. China
- Qingdao Marine Science and Technology Center, Qingdao, Shandong 266235, P. R. China
| | - Peng Jiao
- Department of Thoracic Surgery, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing 100730, P. R. China
| | - Jiangyu Wu
- Department of Thoracic Surgery, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing 100730, P. R. China
| | - Wei Meng
- School of Medicine and Pharmacy, Ocean University of China, Qingdao, Shandong 266003, P. R. China
| | - Lizhen Zhao
- College of Physics, Qingdao University, Qingdao, Shandong 266071, P. R. China
| | - Zhihua Lv
- School of Medicine and Pharmacy, Ocean University of China, Qingdao, Shandong 266003, P. R. China
- Qingdao Marine Science and Technology Center, Qingdao, Shandong 266235, P. R. China
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3
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Zakaria MA, Kiew MC, Rajab NF, Chua EW, Masre SF. Rigid Tissue Increases Cytoplasmic pYAP Expression in Pre-Malignant Stage of Lung Squamous Cell Carcinoma (SCC) In Vivo. Curr Issues Mol Biol 2022; 44:4528-4539. [PMID: 36286025 PMCID: PMC9600365 DOI: 10.3390/cimb44100310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 09/24/2022] [Accepted: 09/27/2022] [Indexed: 12/04/2022] Open
Abstract
Increased tissue rigidity is able to activate the Hippo signaling pathway, leading to YAP inactivation by phosphorylation and translocation into the cytoplasm. Accumulating evidence suggests that cytoplasmic pYAP serves as a tumor suppressor and could be a prognostic biomarker for several solid cancers. However, the relationship between tissue rigidity and cytoplasmic pYAP expression in the early stage of lung squamous cell carcinoma (SCC) remains elusive; this was determined in this study by using a mouse model. Female BALB/c mice were assigned into two groups (n = 6; the vehicle (VC) and the pre-malignant (PM) group, which received 70% acetone and 0.04 M N-nitroso-tris-chloroethylurea (NTCU) for 15 weeks, respectively. In this study, the formation of hyperplasia and metaplasia lesions was found in the PM group, indicating the pre-malignant stage of lung SCC. The pre-malignant tissue appeared to be more rigid as characterized by significantly higher (p < 0.05) epithelium thickness, proliferative activity, and collagen content than the VC group. The PM group also had a significantly higher (p < 0.05) cytoplasmic pYAP protein expression than the VC group. In conclusion, increased tissue rigidity may contribute to the upregulation of cytoplasmic pYAP expression, which may act as a tumor suppressor in the early stage of lung SCC.
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Affiliation(s)
- Muhammad Asyaari Zakaria
- Centre for Toxicology and Health Risk Studies, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Kuala Lumpur 50300, Malaysia
| | - May Chee Kiew
- Centre for Toxicology and Health Risk Studies, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Kuala Lumpur 50300, Malaysia
| | - Nor Fadilah Rajab
- Centre for Healthy Ageing and Wellness, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Kuala Lumpur 50300, Malaysia
| | - Eng Wee Chua
- Faculty of Pharmacy, Universiti Kebangsaan Malaysia, Kuala Lumpur 50300, Malaysia
| | - Siti Fathiah Masre
- Centre for Toxicology and Health Risk Studies, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Kuala Lumpur 50300, Malaysia
- Correspondence: ; Tel.: +60-137442907
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4
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Ullah MA, Islam NN, Moin AT, Park SH, Kim B. Evaluating the Prognostic and Therapeutic Potentials of the Proteasome 26S Subunit, ATPase ( PSMC) Family of Genes in Lung Adenocarcinoma: A Database Mining Approach. Front Genet 2022; 13:935286. [PMID: 35938038 PMCID: PMC9353525 DOI: 10.3389/fgene.2022.935286] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Accepted: 06/10/2022] [Indexed: 11/30/2022] Open
Abstract
This study explored the prognostic and therapeutic potentials of multiple Proteasome 26S Subunit, ATPase (PSMC) family of genes (PSMC1-5) in lung adenocarcinoma (LUAD) diagnosis and treatment. All the PSMCs were found to be differentially expressed (upregulated) at the mRNA and protein levels in LUAD tissues. The promoter and multiple coding regions of PSMCs were reported to be differentially and distinctly methylated, which may serve in the methylation-sensitive diagnosis of LUAD patients. Multiple somatic mutations (alteration frequency: 0.6-2%) were observed along the PSMC coding regions in LUAD tissues that could assist in the high-throughput screening of LUAD patients. A significant association between the PSMC overexpression and LUAD patients' poor overall and relapse-free survival (p < 0.05; HR: >1.3) and individual cancer stages (p < 0.001) was discovered, which justifies PSMCs as the ideal targets for LUAD diagnosis. Multiple immune cells and modulators (i.e., CD274 and IDO1) were found to be associated with the expression levels of PSMCs in LUAD tissues that could aid in formulating PSMC-based diagnostic measures and therapeutic interventions for LUAD. Functional enrichment analysis of neighbor genes of PSMCs in LUAD tissues revealed different genes (i.e., SLIRP, PSMA2, and NUDSF3) previously known to be involved in oncogenic processes and metastasis are co-expressed with PSMCs, which could also be investigated further. Overall, this study recommends that PSMCs and their transcriptional and translational products are potential candidates for LUAD diagnostic and therapeutic measure discovery.
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Affiliation(s)
- Md. Asad Ullah
- Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Jahangirnagar University, Dhaka, Bangladesh
| | - Nafisa Nawal Islam
- Department of Biotechnology and Genetic Engineering, Faculty of Biological Sciences, Jahangirnagar University, Dhaka, Bangladesh
| | - Abu Tayab Moin
- Department of Genetic Engineering and Biotechnology, Faculty of Biological Sciences, University of Chittagong, Chattogram, Bangladesh
| | - Su Hyun Park
- Department of Pathology, College of Korean Medicine, Kyung Hee University, Seoul, Korea
| | - Bonglee Kim
- Department of Pathology, College of Korean Medicine, Kyung Hee University, Seoul, Korea
- Korean Medicine-Based Drug Repositioning Cancer Research Center, College of Korean Medicine, Kyung Hee University, Seoul, Korea
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5
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Zang X, Zhang J, Jiao P, Xue X, Lv Z. Non-Small Cell Lung Cancer Detection and Subtyping by UPLC-HRMS-Based Tissue Metabolomics. J Proteome Res 2022; 21:2011-2022. [PMID: 35856400 DOI: 10.1021/acs.jproteome.2c00316] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Non-small cell lung cancer (NSCLC) is the prevalent histological subtype of lung cancer. In this study, we performed ultraperformance liquid chromatography-high-resolution mass spectrometry (UPLC-HRMS)-based metabolic profiling of 227 tissue samples from 79 lung cancer patients with adenocarcinoma (AC) or squamous cell carcinoma (SCC). Orthogonal partial least squares-discriminant analysis (oPLS-DA) analyses showed that AC, SCC, and NSCLC tumors were discriminated from adjacent noncancerous tissue (ANT) and distant noncancerous tissue (DNT) samples with good accuracies (91.3, 100, and 88.3%), sensitivities (85.7, 100, and 83.9%), and specificities (94.3, 100, and 90.7%), using 12, 4, and 7 discriminant metabolites, respectively. The discriminant panel for AC detection included valine, sphingosine, glutamic acid γ-methyl ester, and lysophosphatidylcholine (LPC) (16:0), levels of which in tumor tissues were significantly altered. Valine, sphingosine, LPC (18:1), and leucine derivatives were used for SCC detection. The discrimination between AC and SCC had 96.8% accuracy, 98.2% sensitivity, and 85.7% specificity using a five-metabolite panel, of which valine and creatine had significant differences. The classification models were further verified with external validation sets, showing a promising prospect for NSCLC tissue detection and subtyping.
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Affiliation(s)
- Xiaoling Zang
- School of Medicine and Pharmacy, Ocean University of China, Qingdao, Shandong 266003, P. R. China
| | - Jie Zhang
- School of Medicine and Pharmacy, Ocean University of China, Qingdao, Shandong 266003, P. R. China
| | - Peng Jiao
- Department of Thoracic Surgery, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing 100730, P. R. China
| | - Xuyan Xue
- College of Physics, Qingdao University, Qingdao, Shandong 266071, P. R. China
| | - Zhihua Lv
- School of Medicine and Pharmacy, Ocean University of China, Qingdao, Shandong 266003, P. R. China
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6
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Abstract
SummaryThe biology of non-small cell lung cancer (NSCLC) is driven by a complex mutational landscape, and the detection of driver molecular alterations by next-generation sequencing is key for identification of druggable alterations. Thus, broad molecular profiling displays a standard-of-care approach particularly in patients with advanced adenocarcinoma at the time of the initial diagnosis, but also at the time of acquired resistance to tyrosine kinase inhibitors, guiding further treatment choices. Sequencing of plasma-circulating tumor DNA is of increasing importance in NSCLC diagnostics due to the easy accessibility, representing an optimal tool for longitudinal monitoring of the disease course.
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7
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Georgakopoulou E, Evangelou K, Gorgoulis VG. Premalignant lesions and cellular senescence. CELLULAR SENESCENCE IN DISEASE 2022:29-60. [DOI: 10.1016/b978-0-12-822514-1.00001-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/04/2025]
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8
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Nie M, Yao K, Zhu X, Chen N, Xiao N, Wang Y, Peng B, Yao L, Li P, Zhang P, Hu Z. Evolutionary metabolic landscape from preneoplasia to invasive lung adenocarcinoma. Nat Commun 2021; 12:6479. [PMID: 34759281 PMCID: PMC8580984 DOI: 10.1038/s41467-021-26685-y] [Citation(s) in RCA: 64] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Accepted: 10/12/2021] [Indexed: 12/13/2022] Open
Abstract
Metabolic reprogramming evolves during cancer initiation and progression. However, thorough understanding of metabolic evolution from preneoplasia to lung adenocarcinoma (LUAD) is still limited. Here, we perform large-scale targeted metabolomics on resected lesions and plasma obtained from invasive LUAD and its precursors, and decipher the metabolic trajectories from atypical adenomatous hyperplasia (AAH) to adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA) and invasive adenocarcinoma (IAC), revealing that perturbed metabolic pathways emerge early in premalignant lesions. Furthermore, three panels of plasma metabolites are identified as non-invasive predictive biomarkers to distinguish IAC and its precursors with benign diseases. Strikingly, metabolomics clustering defines three metabolic subtypes of IAC patients with distinct clinical characteristics. We identify correlation between aberrant bile acid metabolism in subtype III with poor clinical features and demonstrate dysregulated bile acid metabolism promotes migration of LUAD, which could be exploited as potential targetable vulnerability and for stratifying patients. Collectively, the comprehensive landscape of the metabolic evolution along the development of LUAD will improve early detection and provide impactful therapeutic strategies.
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Affiliation(s)
- Meng Nie
- School of Pharmaceutical Sciences, Tsinghua-Peking Center for Life Sciences, Beijing Frontier Research Center for Biological Structure, Tsinghua University, Beijing, 100084, China
| | - Ke Yao
- School of Pharmaceutical Sciences, Tsinghua-Peking Center for Life Sciences, Beijing Frontier Research Center for Biological Structure, Tsinghua University, Beijing, 100084, China
| | - Xinsheng Zhu
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, 200433, China
| | - Na Chen
- School of Pharmaceutical Sciences, Tsinghua-Peking Center for Life Sciences, Beijing Frontier Research Center for Biological Structure, Tsinghua University, Beijing, 100084, China
| | - Nan Xiao
- School of Pharmaceutical Sciences, Tsinghua-Peking Center for Life Sciences, Beijing Frontier Research Center for Biological Structure, Tsinghua University, Beijing, 100084, China
| | - Yi Wang
- School of Pharmaceutical Sciences, Tsinghua-Peking Center for Life Sciences, Beijing Frontier Research Center for Biological Structure, Tsinghua University, Beijing, 100084, China
| | - Bo Peng
- School of Pharmaceutical Sciences, Tsinghua-Peking Center for Life Sciences, Beijing Frontier Research Center for Biological Structure, Tsinghua University, Beijing, 100084, China
| | - LiAng Yao
- School of Pharmaceutical Sciences, Tsinghua-Peking Center for Life Sciences, Beijing Frontier Research Center for Biological Structure, Tsinghua University, Beijing, 100084, China
| | - Peng Li
- Institute of Metabolism and Integrative Biology, Fudan University, Shanghai, 200438, China
- Shanghai Qi Zhi Institute, Shanghai, 200030, China
- School of Life Sciences, Tsinghua University, Beijing, 100084, China
| | - Peng Zhang
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, 200433, China.
| | - Zeping Hu
- School of Pharmaceutical Sciences, Tsinghua-Peking Center for Life Sciences, Beijing Frontier Research Center for Biological Structure, Tsinghua University, Beijing, 100084, China.
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9
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Ma C, Luo H, Cao J, Gao C, Fa X, Wang G. Independent prognostic implications of RRM2 in lung adenocarcinoma. J Cancer 2020; 11:7009-7022. [PMID: 33123291 PMCID: PMC7592001 DOI: 10.7150/jca.47895] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Accepted: 10/03/2020] [Indexed: 12/16/2022] Open
Abstract
Background: Ribonucleoside-diphosphate reductase subunit M2 (RRM2) is the catalytic subunit of ribonucleotide reductase and modulates the enzymatic activity, which is essential for DNA replication and repair. However, the role of RRM2 in lung adenocarcinoma (LUAD) remains unclear. Methods: In this study, we explored the expression pattern and prognostic value of RRM2 in LUAD across TCGA, GEO, Oncomine, UALCAN, PrognoScan, and Kaplan-Meier Plotter, and confirmed its independent prognostic value via Cox analyses. LinkedOmics and GEPIA2 were applied to investigate co-expression and functional networks associated with RRM2. Besides, we used TIMER to assess the correlation between RRM2 and the main six types of tumor-infiltrating immune cells. Lastly, the correlations between immune signatures of immunomodulators, chemokines, and 28 tumor-infiltrating lymphocytes (TILs) and RRM2 were examined by tumor purity-corrected partial Spearman's rank correlation coefficient through TIMER portal. Results:RRM2 was found upregulated in tumor tissues in TCGA-LUAD, and validated in multiple independent cohorts. Moreover, whether in TCGA or other cohorts, high RRM2 expression was found to be associated with poor survival. Cox analyses showed that high RRM2 expression was an independent risk factor for overall survival, disease-specific survival, and progression-free survival of LUAD. Functional network analysis suggested that RRM2 regulates RNA transport, oocyte meiosis, spliceosome, ribosome biogenesis in eukaryotes, and cellular senescence signaling through pathways involving multiple cancer-related kinases and E2F family. Also, RRM2 expression correlated with infiltrating levels of B cells, CD4+ T cells, and neutrophils. Subsequent analysis found that B cells and dendritic cells could predict the outcome of LUAD. B cells were identified as an independent risk factor among six types of immune cells through Cox analyses. At last, the correlation analysis showed RRM2 correlated with 67.68% (624/922) of the immune signatures we performed. Conclusion: Our research showed that RRM2 could independently predict the prognosis of LUAD and was associated with immune infiltration. In particular, the tight relationship between RRM2 and B cell marker genes are the potential epicenter of the immune response and one of the critical factors affecting the prognosis. Our findings laid the foundation for further research on the immunomodulatory role of RRM2 in LUAD.
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Affiliation(s)
- Chao Ma
- Department of Cardiothoracic Surgery, Second Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and the Berlin Institute of Health.,Charité - Universitätsmedizin Berlin, BCRT - Berlin Institute of Health Center for Regenerative Therapies, Berlin, Germany.,Department of Thoracic Surgery, the First Affiliated Hospital of Southern University of Sciences and Technology, Shenzhen People's Hospital, Shenzhen, China
| | - Huan Luo
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and the Berlin Institute of Health.,Klinik für Augenheilkunde, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Jing Cao
- Department of Human Anatomy, School of Basic Medicine, Zhengzhou University, Zhengzhou, China
| | - Chengshan Gao
- Department of Cardiothoracic Surgery, Second Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xianen Fa
- Department of Cardiothoracic Surgery, Second Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Guangsuo Wang
- Department of Thoracic Surgery, the First Affiliated Hospital of Southern University of Sciences and Technology, Shenzhen People's Hospital, Shenzhen, China
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Independent Prognostic Potential of GNPNAT1 in Lung Adenocarcinoma. BIOMED RESEARCH INTERNATIONAL 2020; 2020:8851437. [PMID: 33178836 PMCID: PMC7648248 DOI: 10.1155/2020/8851437] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Revised: 10/03/2020] [Accepted: 10/17/2020] [Indexed: 12/20/2022]
Abstract
Background Glucosamine-Phosphate N-Acetyltransferase 1 (GNPNAT1) is a critical enzyme in the biosynthesis of uridine diphosphate-N-acetylglucosamine. It has many important functions, such as protein binding, monosaccharide binding, and embryonic development and growth. However, the role of GNPNAT1 in lung adenocarcinoma (LUAD) remains unclear. Methods In this study, we explored the expression pattern and prognostic value of GNPNAT1 in LUAD across TCGA and GEO databases and assessed its independent prognostic value via Cox analysis. LinkedOmics and GEPIA2 were applied to investigate coexpression and functional networks associated with GNPNAT1. The TIMER web tool was deployed to assess the correlation between GNPNAT1 and the main six types of tumor-infiltrating immune cells. Besides, the correlations between GNPNAT1 and the LUAD common genetic mutations, TMB, and immune signatures were examined. Results GNPNAT1 was validated upregulated in tumor tissues in TCGA-LUAD and GEO cohorts. Moreover, in both TCGA and GEO cohorts, high GNPNAT1 expression was found to be associated with poor overall survival. Cox analysis showed that high GNPNAT1 expression was an independent risk factor for LUAD. Functional network analysis suggested that GNPNAT1 regulates cell cycle, ribosome, proteasome, RNA transport, and spliceosome signaling through pathways involving multiple cancer-related kinases and E2F family. In addition, GNPNAT1 correlated with infiltrating levels of B cells, CD4+ T cells, and dendritic cells. B cells and dendritic cells could predict the outcome of LUAD, and B cells and CD4+ T cells were significant independent risk factors. The TMB and mutations of KRAS, EGFR, STK11, and TP53 were correlated with GNPNAT1. At last, the correlation analysis showed GNPNAT1 correlated with most of the immune signatures we performed. Conclusion Our findings showed that GNPNAT1 was correlated to the prognosis and immune infiltration of LUAD. In particular, the tight relationship between GNPNAT1 and B cell marker genes may be the epicenter of the immune response and one of the key factors affecting the prognosis. Our findings laid the foundation for further research on the immunomodulatory role of GNPNAT1 in LUAD.
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The incidence and relative risk of PD-1/PD-L1 inhibitors-related colitis in non-small cell lung cancer: A meta-analysis of randomized controlled trials. Int Immunopharmacol 2019; 77:105975. [DOI: 10.1016/j.intimp.2019.105975] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2019] [Revised: 10/11/2019] [Accepted: 10/11/2019] [Indexed: 12/23/2022]
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