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Thean LF, Wong M, Lo M, Tan I, Wong E, Gao F, Tan E, Tang CL, Cheah PY. Functional annotation with expression validation identifies novel metastasis-relevant genes from post-GWAS risk loci in sporadic colorectal carcinomas. J Med Genet 2024; 61:276-283. [PMID: 37890997 DOI: 10.1136/jmg-2023-109517] [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: 07/17/2023] [Accepted: 09/25/2023] [Indexed: 10/29/2023]
Abstract
BACKGROUND Colorectal cancer (CRC) is the third highest incidence cancer and is the leading cause of cancer mortality worldwide. Metastasis to distal organ is the major cause of cancer mortality. However, the underlying genetic factors are unclear. This study aimed to identify metastasis-relevant genes and pathways for better management of metastasis-prone patients. METHODS A case-case genome-wide association study comprising 2677 sporadic Chinese CRC cases (1282 metastasis-positive vs 1395 metastasis-negative) was performed using the Human SNP6 microarray platform and analysed with the correlation/trend test based on the additive model. SNP variants with association testing -log10 p value ≥5 were imported into Functional Mapping and Annotation (FUMA) for functional annotation. RESULTS Glycolysis was uncovered as the top hallmark gene set. Transcripts from two of the five genes profiled, hematopoietic substrate 1 associated protein X 1 (HAX1) and hyaluronan-mediatedmotility receptor (HMMR), were significantly upregulated in the metastasis-positive tumours. In contrast to disease-risk variants, HAX1 appeared to act synergistically with HMMR in significantly impacting metastasis-free survival. Examining the subtype datasets with FUMA and Ingenuity Pathway Analysis (IPA) identified distinct pathways demonstrating sexual dimorphism in CRC metastasis. CONCLUSIONS Combining genome-wide association testing with in silico functional annotation and wet-bench validation identified metastasis-relevant genes that could serve as features to develop subtype-specific metastasis-risk signatures for tailored management of patients with stage I-III CRC.
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Affiliation(s)
- Lai Fun Thean
- Department of Colorectal Surgery, Singapore General Hospital, Singapore
| | - Michelle Wong
- Department of Colorectal Surgery, Singapore General Hospital, Singapore
| | - Michelle Lo
- Department of Colorectal Surgery, Singapore General Hospital, Singapore
| | - Iain Tan
- Division of Medical Oncology, National Cancer Centre Singapore, Singapore
| | - Evelyn Wong
- Division of Medical Oncology, National Cancer Centre Singapore, Singapore
| | - Fei Gao
- National Heart Research Institute Singapore, National Heart Centre Singapore, Singapore
- Duke-NUS Medical School, National University of Singapore, Singapore
| | - Emile Tan
- Department of Colorectal Surgery, Singapore General Hospital, Singapore
| | - Choong Leong Tang
- Department of Colorectal Surgery, Singapore General Hospital, Singapore
| | - Peh Yean Cheah
- Department of Colorectal Surgery, Singapore General Hospital, Singapore
- Duke-NUS Medical School, National University of Singapore, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
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Chen Y, Xue J, Yan X, Fang DG, Li F, Tian X, Yan P, Feng Z. Identification of crucial genes related to heart failure based on GEO database. BMC Cardiovasc Disord 2023; 23:376. [PMID: 37507655 PMCID: PMC10385922 DOI: 10.1186/s12872-023-03400-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: 03/21/2023] [Accepted: 07/15/2023] [Indexed: 07/30/2023] Open
Abstract
BACKGROUND The molecular biological mechanisms underlying heart failure (HF) remain poorly understood. Therefore, it is imperative to use innovative approaches, such as high-throughput sequencing and artificial intelligence, to investigate the pathogenesis, diagnosis, and potential treatment of HF. METHODS First, we initially screened Two data sets (GSE3586 and GSE5406) from the GEO database containing HF and control samples from the GEO database to establish the Train group, and selected another dataset (GSE57345) to construct the Test group for verification. Next, we identified the genes with significantly different expression levels in patients with or without HF and performed functional and pathway enrichment analyses. HF-specific genes were identified, and an artificial neural network was constructed by Random Forest. The ROC curve was used to evaluate the accuracy and reliability of the constructed model in the Train and Test groups. Finally, immune cell infiltration was analyzed to determine the role of the inflammatory response and the immunological microenvironment in the pathogenesis of HF. RESULTS In the Train group, 153 significant differentially expressed genes (DEGs) associated with HF were found to be abnormal, including 81 down-regulated genes and 72 up-regulated genes. GO and KEGG enrichment analyses revealed that the down-regulated genes were primarily enriched in organic anion transport, neutrophil activation, and the PI3K-Akt signaling pathway. The upregulated genes were mainly enriched in neutrophil activation and the calcium signaling. DEGs were identified using Random Forest, and finally, 16 HF-specific genes were obtained. In the ROC validation and evaluation, the area under the curve (AUC) of the Train and Test groups were 0.996 and 0.863, respectively. CONCLUSIONS Our research revealed the potential functions and pathways implicated in the progression of HF, and designed an RNA diagnostic model for HF tissues using machine learning and artificial neural networks. Sensitivity, specificity, and stability were confirmed by ROC curves in the two different cohorts.
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Affiliation(s)
- Yongliang Chen
- Department of Cardiac Surgery, Affiliated Hospital of Chengde Medical University, 36 Nanyingzi Street, Chengde, Hebei, 067000, China
| | - Jing Xue
- Experimental Center of Morphology, College of Basic Medicine, Chengde Medical University, Chengde, Hebei, China
| | - Xiaoli Yan
- Experimental Center of Morphology, College of Basic Medicine, Chengde Medical University, Chengde, Hebei, China
| | - Da-Guang Fang
- Department of Cardiac Surgery, Affiliated Hospital of Chengde Medical University, 36 Nanyingzi Street, Chengde, Hebei, 067000, China
| | - Fangliang Li
- Experimental Center of Morphology, College of Basic Medicine, Chengde Medical University, Chengde, Hebei, China
| | - Xuefei Tian
- Department of Cardiac Surgery, Affiliated Hospital of Chengde Medical University, 36 Nanyingzi Street, Chengde, Hebei, 067000, China
| | - Peng Yan
- Experimental Center of Morphology, College of Basic Medicine, Chengde Medical University, Chengde, Hebei, China
| | - Zengbin Feng
- Department of Cardiac Surgery, Affiliated Hospital of Chengde Medical University, 36 Nanyingzi Street, Chengde, Hebei, 067000, China.
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Yang H, Yue GGL, Yuen KK, Gao S, Leung PC, Wong CK, Lau CBS. Mechanistic insights into the anti-tumor and anti-metastatic effects of Patrinia villosa aqueous extract in colon cancer via modulation of TGF-β R1-smad2/3-E-cadherin and FAK-RhoA-cofilin pathways. PHYTOMEDICINE : INTERNATIONAL JOURNAL OF PHYTOTHERAPY AND PHYTOPHARMACOLOGY 2023; 117:154900. [PMID: 37269754 DOI: 10.1016/j.phymed.2023.154900] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 05/13/2023] [Accepted: 05/22/2023] [Indexed: 06/05/2023]
Abstract
BACKGROUND Patrinia villosa, a traditional medicinal herb commonly used for treating intestinal-related diseases, has been commonly prescribed by Chinese medicine practitioners as a key component herb to treat colon cancer, although its anti-tumor effect and mechanisms of action have not been fully elucidated. HYPOTHESIS/PURPOSE This study aimed to investigate the anti-tumor and anti-metastatic effects of Patrinia villosa aqueous extract (PVW), and its underlying mechanisms. METHOD The chemical profile of PVW was analysed by high-performance liquid chromatography with photodiode-array detection (HPLC-DAD) method. Cell-based functional assays MTT, BrdU, scratch, and transwell were conducted to evaluate the effects of PVW on human colon cancer HCT116 and murine colon26-luc cells, assessing cytotoxicity, cell proliferation, motility, and migration, respectively. Western blotting was performed to assess the effect of PVW on the expression of key intracellular signaling proteins. In vivo studies were conducted using zebrafish embryos and tumor-bearing mice to evaluate the anti-tumor, anti-angiogenesis, and anti-metastatic effects of PVW in colon cancer. RESULTS Five chemical markers were identified and quantified in PVW. PVW exhibited significant cytotoxicity and anti-proliferative activity, as well as inhibitory effects on cell motility and migration in both HCT116 and colon 26-luc cancer cells via modulating protein expressions of TGF-β R1, smad2/3, snail, E-cadherin, FAK, RhoA, and cofilin. PVW (0.01-0.1 mg/ml) could significantly decrease the length of subintestinal vessels of zebrafish embryos through decreasing mRNA expressions of FLT1, FLT4, KDRL, VEGFaa, VEGFc, and Tie1. PVW (> 0.05 mg/ml) also significantly suppressed colon cancer cells migration in the zebrafish embryos. Furthermore, oral administration of PVW (1.6 g/kg) significantly inhibited tumor growth by decreasing the expressions of tumor activation marker Ki-67 and CD 31 in tumor tissues of HCT116 tumor-bearing mice. PVW could also significantly inhibit lung metastasis in colon 26-luc tumor-bearing mice by modulating their tumor microenvironment, including immune cells populations (T cells and MDSCs), levels of cytokines (IL-2, IL-12, and IFN-γ), as well as increasing the relative abundance of gut microbiota. CONCLUSION This study revealed for the first time the anti-tumor and anti-metastatic effects of PVW through regulation of TGF-β-smad2/3-E-cadherin, and FAK-cofilin pathways in colon cancer. These findings provide scientific evidence to support the clinical use of P. villosa in patients with colon cancer.
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Affiliation(s)
- Huihai Yang
- Institute of Chinese Medicine, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China; State Key Laboratory of Research on Bioactivities and Clinical Applications of Medicinal Plants, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China
| | - Grace Gar-Lee Yue
- Institute of Chinese Medicine, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China; State Key Laboratory of Research on Bioactivities and Clinical Applications of Medicinal Plants, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China
| | - Ka-Ki Yuen
- Institute of Chinese Medicine, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China; State Key Laboratory of Research on Bioactivities and Clinical Applications of Medicinal Plants, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China
| | - Si Gao
- Institute of Chinese Medicine, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China; State Key Laboratory of Research on Bioactivities and Clinical Applications of Medicinal Plants, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China
| | - Ping Chung Leung
- Institute of Chinese Medicine, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China; State Key Laboratory of Research on Bioactivities and Clinical Applications of Medicinal Plants, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China
| | - Chun Kwok Wong
- Institute of Chinese Medicine, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China; State Key Laboratory of Research on Bioactivities and Clinical Applications of Medicinal Plants, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China; Department of Chemical Pathology, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China
| | - Clara Bik-San Lau
- Institute of Chinese Medicine, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China; State Key Laboratory of Research on Bioactivities and Clinical Applications of Medicinal Plants, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China.
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Chen Z, Liang B, Wu Y, Zhou H, Wang Y, Wu H. Identifying driver modules based on multi-omics biological networks in prostate cancer. IET Syst Biol 2022; 16:187-200. [PMID: 36039671 PMCID: PMC9675413 DOI: 10.1049/syb2.12050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2022] [Revised: 07/31/2022] [Accepted: 08/13/2022] [Indexed: 01/11/2023] Open
Abstract
The development of sequencing technology has promoted the expansion of cancer genome data. It is necessary to identify the pathogenesis of cancer at the molecular level and explore reliable treatment methods and precise drug targets in cancer by identifying carcinogenic functional modules in massive multi-omics data. However, there are still limitations to identifying carcinogenic driver modules by utilising genetic characteristics simply. Therefore, this study proposes a computational method, NetAP, to identify driver modules in prostate cancer. Firstly, high mutual exclusivity, high coverage, and high topological similarity between genes are integrated to construct a weight function, which calculates the weight of gene pairs in a biological network. Secondly, the random walk method is utilised to reevaluate the strength of interaction among genes. Finally, the optimal driver modules are identified by utilising the affinity propagation algorithm. According to the results, the authors' method identifies more validated driver genes and driver modules compared with the other previous methods. Thus, the proposed NetAP method can identify carcinogenic driver modules effectively and reliably, and the experimental results provide a powerful basis for cancer diagnosis, treatment and drug targets.
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Affiliation(s)
- Zhongli Chen
- Tibet Center for Disease Control and PreventionLhasaChina,School of SoftwareShandong UniversityJinanChina,School of Information EngineeringNorthwest A&F UniversityYanglingChina
| | - Biting Liang
- School of Information EngineeringNorthwest A&F UniversityYanglingChina
| | - Yingfu Wu
- School of Information EngineeringNorthwest A&F UniversityYanglingChina
| | - Haoru Zhou
- School of Information EngineeringNorthwest A&F UniversityYanglingChina
| | - Yuchen Wang
- School of SoftwareShandong UniversityJinanChina
| | - Hao Wu
- School of SoftwareShandong UniversityJinanChina
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