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Saadh MJ, Omar TM, Ballal S, Mahdi MS, Chahar M, Verma R, A Al-Hussein RK, Adil M, Jawad MJ, Al-Nuaimi AMA. Notch signaling and cancer: Insights into chemoresistance, immune evasion, and immunotherapy. Gene 2025; 955:149461. [PMID: 40164241 DOI: 10.1016/j.gene.2025.149461] [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: 10/06/2024] [Revised: 03/21/2025] [Accepted: 03/28/2025] [Indexed: 04/02/2025]
Abstract
The Notch signaling pathway is a fundamental and highly conserved cell-to-cell communication system vital for embryonic development and tissue maintenance. However, its dysregulation has been associated with the initiation, progression, and chemoresistance of various cancers. In this comprehensive review, we will take an in-depth look at the multiple roles of the Notch family in cancer pathogenesis, immune response, and resistance to chemotherapy. We delve into the complicated mechanisms by which Notch signaling promotes tumor growth and development, including its influence on TME remodeling and immune evasion strategies. We will also be discussing recent studies that shed light on the connection between cancer stemness and chemoresistance mediated through the activation of Notch signaling pathways. Elucidation of the interplay between the Notch pathway and major constituents of the TME, including immune cells and cancer-associated fibroblasts, is necessary for the development of targeted therapies against Notch-driven tumors. We further discuss the potential of targeting Notch signaling alone or in combination with standard chemotherapy and immunotherapy as a potent strategy to overcome chemoresistance and improve patient outcomes. We conclude by discussing the challenges and future prospects of using Notch signaling as a therapeutic target in cancer treatment, focusing on how precision medicine and combination approaches are important.
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Affiliation(s)
- Mohamed J Saadh
- Faculty of Pharmacy, Middle East University, Amman 11831, Jordan
| | - Thabit Moath Omar
- Department of Medical Laboratory Technics, College of Health and Medical Technology, Alnoor University, Mosul, Iraq.
| | - Suhas Ballal
- Department of Chemistry and Biochemistry, School of Sciences, JAIN (Deemed to be University), Bangalore, Karnataka, India
| | | | - Mamata Chahar
- Department of Chemistry, NIMS Institute of Engineering & Technology, NIMS University Rajasthan, Jaipur, India
| | - Rajni Verma
- Department of Applied Sciences, Chandigarh Engineering College, Chandigarh Group of Colleges, Jhanjeri, Mohali 140307, Punjab, India
| | | | - Mohaned Adil
- College of Pharmacy, Al-Farahidi University, Baghdad, Iraq
| | | | - Ali M A Al-Nuaimi
- Department of Pharmacy, Gilgamesh Ahliya University, Baghdad 10022, Iraq
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Bahramibanan F, Taherkhani A, Najafi R, Alizadeh N, Ghadimipour H, Barati N, Derakhshandeh K, Soleimani M. Prognostic markers and molecular pathways in primary colorectal cancer with a high potential of liver metastases: a systems biology approach. Res Pharm Sci 2025; 20:121-141. [PMID: 40190820 PMCID: PMC11972027 DOI: 10.4103/rps.rps_128_23] [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: 07/12/2023] [Revised: 03/03/2024] [Accepted: 03/11/2024] [Indexed: 04/09/2025] Open
Abstract
Background and purpose Colorectal cancer (CRC) holds the position of being the third most prevalent cancer and the second primary cause of cancer-related fatalities on a global scale. Approximately 65% of CRC patients survive for 5 years following diagnosis. Metastasis and recurrence frequently occur in half of CRC patients diagnosed at the late stage. This study used bioinformatics analysis to identify key signaling pathways, hub genes, transcription factors, and protein kinases involved in transforming primary CRC with liver metastasis potential. Prognostic markers in CRC were also identified. Experimental approach The GSE81582 dataset was re-analyzed to identify differentially expressed genes (DEGs) in early CRC compared to non-tumoral tissues. A protein interaction network (PIN) was constructed, revealing significant modules and hub genes. Prognostic markers, transcription factors, and protein kinases were determined. Boxplot and gene set enrichment analyses were performed. Findings/Results This study identified 1113 DEGs in primary CRC compared to healthy controls. PIN analysis revealed 75 hub genes and 8 significant clusters associated with early CRC. The down-regulation of SUCLG2 and KPNA2 correlated with poor prognosis. SIN3A and CDK6 played crucial roles in early CRC transformation, affecting rRNA processing pathways. Conclusion and implications This study demonstrated several pathways, biological processes, and genes mediating the malignant transformation of healthy colorectal tissues to primary CRC and may help the prognosis and treatment of patients with early CRC.
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Affiliation(s)
- Fatemeh Bahramibanan
- Department of Medical Biotechnology, School of Advanced Medical Sciences and Technologies, Hamadan University of Medical Sciences, Hamadan, I.R. Iran
| | - Amir Taherkhani
- Research Center for Molecular Medicine, Institute of Cancer, Avicenna Health Research Institute, Hamadan University of Medical Sciences, Hamadan, I.R. Iran
| | - Rezvan Najafi
- Research Center for Molecular Medicine, Institute of Cancer, Avicenna Health Research Institute, Hamadan University of Medical Sciences, Hamadan, I.R. Iran
| | - Neda Alizadeh
- Department of Anesthesiology and Critical Care, School of Medicine, Hamadan University of Medical Sciences, Hamadan, I.R. Iran
| | - Hamidreza Ghadimipour
- Department of Pathology, School of Medicine, Hamadan University of Medical Sciences, Hamadan, I.R. Iran
| | - Nastaran Barati
- Department of Pharmaceutical Biotechnology, School of Pharmacy, Hamadan University of Medical Sciences, Hamadan, I.R. Iran
| | - Katayoun Derakhshandeh
- Department of Pharmaceutics, School of Pharmacy, Hamadan University of Medical Sciences, Hamadan, I.R. Iran
| | - Meysam Soleimani
- Department of Pharmaceutical Biotechnology, School of Pharmacy, Hamadan University of Medical Sciences, Hamadan, I.R. Iran
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Hu S, Qin J, Ding M, Gao R, Xiao Q, Lou J, Chen Y, Wang S, Pan Y. Bulk integrated single-cell-spatial transcriptomics reveals the impact of preoperative chemotherapy on cancer-associated fibroblasts and tumor cells in colorectal cancer, and construction of related predictive models using machine learning. Biochim Biophys Acta Mol Basis Dis 2025; 1871:167535. [PMID: 39374811 DOI: 10.1016/j.bbadis.2024.167535] [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: 01/16/2024] [Revised: 09/08/2024] [Accepted: 09/30/2024] [Indexed: 10/09/2024]
Abstract
BACKGROUND Preoperative chemotherapy (PC) is an important component of Colorectal cancer (CRC) treatment, but its effects on the biological functions of fibroblasts and epithelial cells in CRC are unclear. METHODS This study utilized bulk, single-cell, and spatial transcriptomic sequencing data from 22 independent cohorts of CRC. Through bioinformatics analysis and in vitro experiments, the research investigated the impact of PC on fibroblast and epithelial cells in CRC. Subpopulations associated with PC and CRC prognosis were identified, and a predictive model was constructed using machine learning. RESULTS PC significantly attenuated the pathways related to tumor progression in fibroblasts and epithelial cells. NOTCH3 + Fibroblast (NOTCH3 + Fib), TNNT1 + Epithelial (TNNT1 + Epi), and HSPA1A + Epithelial (HSPA1A + Epi) subpopulations were identified in the adjacent spatial region and were associated with poor prognosis in CRC. PC effectively diminished the presence of these subpopulations, concurrently inhibiting pathway activity and intercellular crosstalk. A risk signature model, named the Preoperative Chemotherapy Risk Signature Model (PCRSM), was constructed using machine learning. PCRSM emerged as an independent prognostic indicator for CRC, impacting both overall survival (OS) and recurrence-free survival (RFS), surpassing the performance of 89 previously published CRC risk signatures. Additionally, patients with a high PCRSM risk score showed sensitivity to fluorouracil-based adjuvant chemotherapy (FOLFOX) but resistance to single chemotherapy drugs (such as Bevacizumab and Oxaliplatin). Furthermore, this study predicted that patients with high PCRSM were resistant to anti-PD1therapy. CONCLUSION In conclusion, this study identified three cell subpopulations (NOTCH3 + Fib, TNNT1 + Epi, and HSPA1A + Epi) associated with PC, which can be targeted to improve the prognosis of CRC patients. The PCRSM model shows promise in enhancing the survival and treatment of CRC patients.
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Affiliation(s)
- Shangshang Hu
- School of Medicine, Southeast University, Nanjing 210009, Jiangsu, China
| | - Jian Qin
- School of Medicine, Southeast University, Nanjing 210009, Jiangsu, China
| | - Muzi Ding
- School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing 211122, Jiangsu, China
| | - Rui Gao
- School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing 211122, Jiangsu, China
| | - QianNi Xiao
- School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing 211122, Jiangsu, China
| | - Jinwei Lou
- School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing 211122, Jiangsu, China
| | - Yuhan Chen
- School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing 211122, Jiangsu, China
| | - Shukui Wang
- School of Medicine, Southeast University, Nanjing 210009, Jiangsu, China; General Clinical Research Center, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, Jiangsu, China; Jiangsu Collaborative Innovation Center on Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211100, Jiangsu, China.
| | - Yuqin Pan
- General Clinical Research Center, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, Jiangsu, China; Jiangsu Collaborative Innovation Center on Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211100, Jiangsu, China.
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Joyce T, Tasci E, Jagasia S, Shephard J, Chappidi S, Zhuge Y, Zhang L, Cooley Zgela T, Sproull M, Mackey M, Camphausen K, Krauze AV. Serum CD133-Associated Proteins Identified by Machine Learning Are Connected to Neural Development, Cancer Pathways, and 12-Month Survival in Glioblastoma. Cancers (Basel) 2024; 16:2740. [PMID: 39123468 PMCID: PMC11311306 DOI: 10.3390/cancers16152740] [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: 06/17/2024] [Revised: 07/24/2024] [Accepted: 07/26/2024] [Indexed: 08/12/2024] Open
Abstract
Glioma is the most prevalent type of primary central nervous system cancer, while glioblastoma (GBM) is its most aggressive variant, with a median survival of only 15 months when treated with maximal surgical resection followed by chemoradiation therapy (CRT). CD133 is a potentially significant GBM biomarker. However, current clinical biomarker studies rely on invasive tissue samples. These make prolonged data acquisition impossible, resulting in increased interest in the use of liquid biopsies. Our study, analyzed 7289 serum proteins from 109 patients with pathology-proven GBM obtained prior to CRT using the aptamer-based SOMAScan® proteomic assay technology. We developed a novel methodology that identified 24 proteins linked to both serum CD133 and 12-month overall survival (OS) through a multi-step machine learning (ML) analysis. These identified proteins were subsequently subjected to survival and clustering evaluations, categorizing patients into five risk groups that accurately predicted 12-month OS based on their protein profiles. Most of these proteins are involved in brain function, neural development, and/or cancer biology signaling, highlighting their significance and potential predictive value. Identifying these proteins provides a valuable foundation for future serum investigations as validation of clinically applicable GBM biomarkers can unlock immense potential for diagnostics and treatment monitoring.
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Affiliation(s)
- Thomas Joyce
- Radiation Oncology Branch, Center for Cancer Research, National Cancer Institute NIH, 9000 Rockville Pike, Bethesda, MD 20892, USA; (T.J.); (S.J.); (J.S.); (S.C.); (Y.Z.); (L.Z.); (T.C.Z.); (M.S.); (M.M.); (K.C.)
| | - Erdal Tasci
- Radiation Oncology Branch, Center for Cancer Research, National Cancer Institute NIH, 9000 Rockville Pike, Bethesda, MD 20892, USA; (T.J.); (S.J.); (J.S.); (S.C.); (Y.Z.); (L.Z.); (T.C.Z.); (M.S.); (M.M.); (K.C.)
| | - Sarisha Jagasia
- Radiation Oncology Branch, Center for Cancer Research, National Cancer Institute NIH, 9000 Rockville Pike, Bethesda, MD 20892, USA; (T.J.); (S.J.); (J.S.); (S.C.); (Y.Z.); (L.Z.); (T.C.Z.); (M.S.); (M.M.); (K.C.)
| | - Jason Shephard
- Radiation Oncology Branch, Center for Cancer Research, National Cancer Institute NIH, 9000 Rockville Pike, Bethesda, MD 20892, USA; (T.J.); (S.J.); (J.S.); (S.C.); (Y.Z.); (L.Z.); (T.C.Z.); (M.S.); (M.M.); (K.C.)
| | - Shreya Chappidi
- Radiation Oncology Branch, Center for Cancer Research, National Cancer Institute NIH, 9000 Rockville Pike, Bethesda, MD 20892, USA; (T.J.); (S.J.); (J.S.); (S.C.); (Y.Z.); (L.Z.); (T.C.Z.); (M.S.); (M.M.); (K.C.)
- Department of Computer Science and Technology, University of Cambridge, 15 JJ Thomson Ave, Cambridge CB3 0FD, UK
| | - Ying Zhuge
- Radiation Oncology Branch, Center for Cancer Research, National Cancer Institute NIH, 9000 Rockville Pike, Bethesda, MD 20892, USA; (T.J.); (S.J.); (J.S.); (S.C.); (Y.Z.); (L.Z.); (T.C.Z.); (M.S.); (M.M.); (K.C.)
| | - Longze Zhang
- Radiation Oncology Branch, Center for Cancer Research, National Cancer Institute NIH, 9000 Rockville Pike, Bethesda, MD 20892, USA; (T.J.); (S.J.); (J.S.); (S.C.); (Y.Z.); (L.Z.); (T.C.Z.); (M.S.); (M.M.); (K.C.)
| | - Theresa Cooley Zgela
- Radiation Oncology Branch, Center for Cancer Research, National Cancer Institute NIH, 9000 Rockville Pike, Bethesda, MD 20892, USA; (T.J.); (S.J.); (J.S.); (S.C.); (Y.Z.); (L.Z.); (T.C.Z.); (M.S.); (M.M.); (K.C.)
| | - Mary Sproull
- Radiation Oncology Branch, Center for Cancer Research, National Cancer Institute NIH, 9000 Rockville Pike, Bethesda, MD 20892, USA; (T.J.); (S.J.); (J.S.); (S.C.); (Y.Z.); (L.Z.); (T.C.Z.); (M.S.); (M.M.); (K.C.)
| | - Megan Mackey
- Radiation Oncology Branch, Center for Cancer Research, National Cancer Institute NIH, 9000 Rockville Pike, Bethesda, MD 20892, USA; (T.J.); (S.J.); (J.S.); (S.C.); (Y.Z.); (L.Z.); (T.C.Z.); (M.S.); (M.M.); (K.C.)
| | - Kevin Camphausen
- Radiation Oncology Branch, Center for Cancer Research, National Cancer Institute NIH, 9000 Rockville Pike, Bethesda, MD 20892, USA; (T.J.); (S.J.); (J.S.); (S.C.); (Y.Z.); (L.Z.); (T.C.Z.); (M.S.); (M.M.); (K.C.)
| | - Andra V. Krauze
- Radiation Oncology Branch, Center for Cancer Research, National Cancer Institute NIH, 9000 Rockville Pike, Bethesda, MD 20892, USA; (T.J.); (S.J.); (J.S.); (S.C.); (Y.Z.); (L.Z.); (T.C.Z.); (M.S.); (M.M.); (K.C.)
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Zhao N, Ruan M, Koestler DC, Lu J, Marsit CJ, Kelsey KT, Platz EA, Michaud DS. Epigenome-wide scan identifies differentially methylated regions for lung cancer using pre-diagnostic peripheral blood. Epigenetics 2021; 17:460-472. [PMID: 34008478 DOI: 10.1080/15592294.2021.1923615] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022] Open
Abstract
BACKGROUND DNA methylation markers have been associated with lung cancer risk and may identify aetiologically relevant genomic regions, or alternatively, be markers of disease risk factors or biological processes associated with disease development. METHODS In a nested case-control study, we measured blood leukocyte DNA methylation levels in pre-diagnostic samples collected from 430 participants (208 cases; 222 controls) in the 1989 CLUE II cohort. We compared DNA methylation levels with case/control status to identify novel genomic regions, both single CpG sites and differentially methylated regions (DMRs), while controlling for known DNA methylation changes associated with smoking using a previously described pack-years-based smoking methylation score. Stratification analyses were conducted over time from blood draw to diagnosis, histology, and smoking status. RESULTS We identified 16 single CpG sites and 40 DMRs significantly associated with lung cancer risk (q < 0.05). The identified genomic regions were associated with genes including H19, HOXA3/HOXA4, RUNX3, BRICD5, PLXNB2, and RP13. For the single CpG sites, the strongest association was noted for cg09736286 in the DIABLO gene (OR [for 1 SD] = 2.99, 95% CI: 1.95-4.59, P-value = 4.81 × 10-7). We found that CpG sites in the HOXA3/HOXA4 region were hypermethylated in cases compared to controls. CONCLUSION The single CpG sites and DMRs that we identified represented significant measurable differences in lung cancer risk, providing potential biomarkers for lung cancer risk stratification. Future studies will need to examine whether these regions are causally related to lung cancer.
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Affiliation(s)
- Naisi Zhao
- Department of Public Health & Community Medicine, Tufts University School of Medicine, Tufts University, Boston, MA, USA
| | - Mengyuan Ruan
- Department of Public Health & Community Medicine, Tufts University School of Medicine, Tufts University, Boston, MA, USA
| | - Devin C Koestler
- Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS, USA.,University of Kansas Cancer Center, University of Kansas Medical Center, Kansas City, KS, USA
| | - Jiayun Lu
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Carmen J Marsit
- Department of Environmental Health and Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Karl T Kelsey
- Department of Epidemiology, Brown University, Providence, RI, USA.,Department of Pathology and Laboratory Medicine, Brown University, Providence, RI, USA
| | - Elizabeth A Platz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.,The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD, USA
| | - Dominique S Michaud
- Department of Public Health & Community Medicine, Tufts University School of Medicine, Tufts University, Boston, MA, USA.,Department of Epidemiology, Brown University, Providence, RI, USA
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