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Zhou X, Qian Y, Ling C, He Z, Shi P, Gao Y, Sui X. An integrated framework for prognosis prediction and drug response modeling in colorectal liver metastasis drug discovery. J Transl Med 2024; 22:321. [PMID: 38555418 PMCID: PMC10981831 DOI: 10.1186/s12967-024-05127-5] [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: 10/25/2023] [Accepted: 03/23/2024] [Indexed: 04/02/2024] Open
Abstract
BACKGROUND Colorectal cancer (CRC) is the third most prevalent cancer globally, and liver metastasis (CRLM) is the primary cause of death. Hence, it is essential to discover novel prognostic biomarkers and therapeutic drugs for CRLM. METHODS This study developed two liver metastasis-associated prognostic signatures based on differentially expressed genes (DEGs) in CRLM. Additionally, we employed an interpretable deep learning model utilizing drug sensitivity databases to identify potential therapeutic drugs for high-risk CRLM patients. Subsequently, in vitro and in vivo experiments were performed to verify the efficacy of these compounds. RESULTS These two prognostic models exhibited superior performance compared to previously reported ones. Obatoclax, a BCL-2 inhibitor, showed significant differential responses between high and low risk groups classified by prognostic models, and demonstrated remarkable effectiveness in both Transwell assay and CT26 colorectal liver metastasis mouse model. CONCLUSIONS This study highlights the significance of developing specialized prognostication approaches and investigating effective therapeutic drugs for patients with CRLM. The application of a deep learning drug response model provides a new drug discovery strategy for translational medicine in precision oncology.
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Affiliation(s)
- Xiuman Zhou
- School of Pharmaceutical Sciences (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong Province, 518107, China
| | - Yuzhen Qian
- School of Life Sciences, Zhengzhou University, Zhengzhou, 450001, China
| | - Chen Ling
- School of Pharmaceutical Sciences (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong Province, 518107, China
| | - Zhuoying He
- School of Pharmaceutical Sciences (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong Province, 518107, China
| | - Peishang Shi
- School of Life Sciences, Zhengzhou University, Zhengzhou, 450001, China
| | - Yanfeng Gao
- School of Pharmaceutical Sciences (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong Province, 518107, China.
| | - Xinghua Sui
- School of Pharmaceutical Sciences (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong Province, 518107, China.
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Liang J, Wang X, Yang J, Sun P, Sun J, Cheng S, Liu J, Ren Z, Ren M. Identification of disulfidptosis-related subtypes, characterization of tumor microenvironment infiltration, and development of a prognosis model in breast cancer. Front Immunol 2023; 14:1198826. [PMID: 38035071 PMCID: PMC10684933 DOI: 10.3389/fimmu.2023.1198826] [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: 04/02/2023] [Accepted: 10/31/2023] [Indexed: 12/02/2023] Open
Abstract
Introduction Breast cancer (BC) is now the most common type of cancer in women. Disulfidptosis is a new regulation of cell death (RCD). RCD dysregulation is causally linked to cancer. However, the comprehensive relationship between disulfidptosis and BC remains unknown. This study aimed to explore the predictive value of disulfidptosis-related genes (DRGs) in BC and their relationship with the TME. Methods This study obtained 11 disulfidptosis genes (DGs) from previous research by Gan et al. RNA sequencing data of BC were downloaded from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus database (GEO) databases. First, we examined the effect of DG gene mutations and copy number changes on the overall survival of breast cancer samples. We then used the expression profile data of 11 DGs and survival data for consensus clustering, and BC patients were divided into two clusters. Survival analysis, gene set variation analysis (GSVA) and ss GSEA were used to compare the differences between them. Subsequently, DRGs were identified between the clusters used to perform Cox regression and least absolute shrinkage and selection operator regression (LASSO) analyses to construct a prognosis model. Finally, the immune cell infiltration pattern, immunotherapy response, and drug sensitivity of the two subtypes were analyzed. CCK-8 and a colony assay obtained by knocking down genes and gene sequencing were used to validate the model. Result Two DG clusters were identified based on the expression of 11DGs. Then, 225 DRGs were identified between them. RS, composed of six genes, showed a significant relationship with survival, immune cell infiltration, clinical characteristics, immune checkpoints, immunotherapy response, and drug sensitivity. Low-RS shows a better prognosis and higher immunotherapy response than high-RS. A nomogram with perfect stability constructed using signature and clinical characteristics can predict the survival of each patient. CCK-8 and colony assay obtained by knocking down genes have demonstrated that the knockdown of high-risk genes in the RS model significantly inhibited cell proliferation. Discussion This study elucidates the potential relationship between disulfidptosis-related genes and breast cancer and provides new guidance for treating breast cancer.
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Affiliation(s)
- Jiahui Liang
- Department of Breast Surgery, Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Xin Wang
- Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
| | - Jing Yang
- Department of Breast Surgery, Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Peng Sun
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Jingjing Sun
- Department of Breast Surgery, Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Shengrong Cheng
- Department of Plastic Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Jincheng Liu
- Department of Breast Surgery, Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Zhiyao Ren
- Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
| | - Min Ren
- Department of Breast Surgery, Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
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Ma S, Ge Y, Xiong Z, Wang Y, Li L, Chao Z, Li B, Zhang J, Ma S, Xiao J, Liu B, Wang Z. A novel gene signature related to oxidative stress predicts the prognosis in clear cell renal cell carcinoma. PeerJ 2023; 11:e14784. [PMID: 36785707 PMCID: PMC9921988 DOI: 10.7717/peerj.14784] [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: 10/20/2022] [Accepted: 01/03/2023] [Indexed: 02/10/2023] Open
Abstract
Clear cell renal cell carcinoma (ccRCC) is considered to be related to the worse prognosis, which might in part be attributed to the early recurrence and metastasis, compared with other type of kidney cancer. Oxidative stress refers to an imbalance between production of oxidants and antioxidant defense. Accumulative studies have indicated that oxidative stress genes contribute to the tumor invasion, metastasis and drug sensitivity. However, the biological functions of oxidative stress genes in ccRCC remain largely unknown. In this study, we identified 1,399 oxidative stress genes from GeneCards with a relevance score ≥7. Data for analysis were accessed from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) database, and were utilized as training set and validation set respectively. Univariate Cox analysis, least absolute shrinkage and selection operator (LASSO) Cox regression and multivariate Cox were employed to construct a prognostic signature in ccRCC. Finally, a prognostic signature including four different oxidative stress genes was constructed from 1,399 genes, and its predictive performance was verified through Kaplan-Meier survival analysis and the receiver operating characteristic (ROC) curve. Interestingly, we found that there was significant correlation between the expression of oxidative stress genes and the immune infiltration and the sensitivity of tumor cells to chemotherapeutics. Moreover, the highest hazard ratio gene urocortin (UCN) was chosen for further study; some necessary vitro experiments proved that the UCN could promote the ability of ccRCC proliferation and migration and contribute to the degree of oxidative stress. In conclusion, it was promising to predict the prognosis of ccRCC through the four oxidative stress genes signature. UCN played oncogenic roles in ccRCC by influencing proliferation and oxidative stress pathway, which was expected to be the novel therapeutic target for ccRCC.
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Affiliation(s)
- Sheng Ma
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yue Ge
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Zezhong Xiong
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yanan Wang
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Le Li
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Zheng Chao
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Beining Li
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Junbiao Zhang
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Siquan Ma
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Jun Xiao
- Department of Thyroid and Breast Surgery, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Bo Liu
- Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Zhihua Wang
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
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Ai D, Wang M, Zhang Q, Cheng L, Wang Y, Liu X, Xia LC. Regularized survival learning and cross-database analysis enabled identification of colorectal cancer prognosis-related immune genes. Front Genet 2023; 14:1148470. [PMID: 36911403 PMCID: PMC9995717 DOI: 10.3389/fgene.2023.1148470] [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: 01/20/2023] [Accepted: 02/13/2023] [Indexed: 02/25/2023] Open
Abstract
Colon adenocarcinoma is the most common type of colorectal cancer. The prognosis of advanced colorectal cancer patients who received treatment is still very poor. Therefore, identifying new biomarkers for prognosis prediction has important significance for improving treatment strategies. However, the power of biomarker analyses was limited by the used sample size of individual database. In this study, we combined Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) databases to expand the number of healthy tissue samples. We screened differentially expressed genes between the GTEx healthy samples and TCGA tumor samples. Subsequently, we applied least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox analysis to identify nine prognosis-related immune genes: ANGPTL4, IDO1, NOX1, CXCL3, LTB4R, IL1RL2, CD72, NOS2, and NUDT6. We computed the risk scores of samples based on the expression levels of these genes and divided patients into high- and low-risk groups according to this risk score. Survival analysis results showed a significant difference in survival rate between the two risk groups. The high-risk group had a significantly lower overall survival rate and poorer prognosis. We found the receiver operating characteristic based on the risk score was showed to accurately predict patients' prognosis. These prognosis-related immune genes may be potential biomarkers for colorectal cancer diagnosis and treatment. Our open-source code is freely available from GitHub at https://github.com/gutmicrobes/Prognosis-model.git.
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Affiliation(s)
- Dongmei Ai
- School of Mathematics and Physics, University of Science and Technology Beijing, Beijing, China
| | - Mingmei Wang
- School of Mathematics and Physics, University of Science and Technology Beijing, Beijing, China
| | - Qingchuan Zhang
- National Engineering Laboratory for Agri-Product Quality Traceability, Beijing Technology and Business University, Beijing, China
| | - Longwei Cheng
- School of Mathematics and Physics, University of Science and Technology Beijing, Beijing, China
| | - Yishu Wang
- School of Mathematics and Physics, University of Science and Technology Beijing, Beijing, China
| | - Xiuqin Liu
- School of Mathematics and Physics, University of Science and Technology Beijing, Beijing, China
| | - Li C Xia
- School of Mathematics, South China University of Technology, Guangzhou, China
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Wang Z, Liu H, Gong Y, Cheng Y. Establishment and validation of an aging-related risk signature associated with prognosis and tumor immune microenvironment in breast cancer. Eur J Med Res 2022; 27:317. [PMID: 36581948 PMCID: PMC9798726 DOI: 10.1186/s40001-022-00924-4] [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: 09/26/2022] [Accepted: 12/01/2022] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Breast cancer (BC) is a highly malignant and heterogeneous tumor which is currently the cancer with the highest incidence and seriously endangers the survival and prognosis of patients. Aging, as a research hotspot in recent years, is widely considered to be involved in the occurrence and development of a variety of tumors. However, the relationship between aging-related genes (ARGs) and BC has not yet been fully elucidated. MATERIALS AND METHODS The expression profiles and clinicopathological data were acquired in the Cancer Genome Atlas (TCGA) and the gene expression omnibus (GEO) database. Firstly, the differentially expressed ARGs in BC and normal breast tissues were investigated. Based on these differential genes, a risk model was constructed composed of 11 ARGs via univariate and multivariate Cox analysis. Subsequently, survival analysis, independent prognostic analysis, time-dependent receiver operating characteristic (ROC) analysis and nomogram were performed to assess its ability to sensitively and specifically predict the survival and prognosis of patients, which was also verified in the validation set. In addition, functional enrichment analysis and immune infiltration analysis were applied to reveal the relationship between the risk scores and tumor immune microenvironment, immune status and immunotherapy. Finally, multiple datasets and real-time polymerase chain reaction (RT-PCR) were utilized to verify the expression level of the key genes. RESULTS An 11-gene signature (including FABP7, IGHD, SPIB, CTSW, IGKC, SEZ6, S100B, CXCL1, IGLV6-57, CPLX2 and CCL19) was established to predict the survival of BC patients, which was validated by the GEO cohort. Based on the risk model, the BC patients were divided into high- and low-risk groups, and the high-risk patients showed worse survival. Stepwise ROC analysis and Cox analyses demonstrated the good performance and independence of the model. Moreover, a nomogram combined with the risk score and clinical parameters was built for prognostic prediction. Functional enrichment analysis revealed the robust relationship between the risk model with immune-related functions and pathways. Subsequent immune microenvironment analysis, immunotherapy, etc., indicated that the immune status of patients in the high-risk group decreased, and the anti-tumor immune function was impaired, which was significantly different with those in the low-risk group. Eventually, the expression level of FABP7, IGHD, SPIB, CTSW, IGKC, SEZ6, S100B, CXCL1, IGLV6-57 and CCL19 was identified as down-regulated in tumor cell line, while CPLX2 up-regulated, which was mostly similar with the results in TCGA and Human Protein Atlas (HPA) via RT-PCR. CONCLUSIONS In summary, our study constructed a risk model composed of ARGs, which could be used as a solid model for predicting the survival and prognosis of BC patients. Moreover, this model also played an important role in tumor immunity, providing a new direction for patient immune status assessment and immunotherapy selection.
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Affiliation(s)
- Zitao Wang
- grid.412632.00000 0004 1758 2270Department of Obstetrics and Gynecology, Renmin Hospital of Wuhan University, Wuhan, Hubei China
| | - Hua Liu
- grid.412632.00000 0004 1758 2270Department of Obstetrics and Gynecology, Renmin Hospital of Wuhan University, Wuhan, Hubei China
| | - Yiping Gong
- grid.412632.00000 0004 1758 2270Department of Breast Surgery, Renmin Hospital of Wuhan University, Wuhan, Hubei China
| | - Yanxiang Cheng
- grid.412632.00000 0004 1758 2270Department of Obstetrics and Gynecology, Renmin Hospital of Wuhan University, Wuhan, Hubei China
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Yang W, Luo C, Chen S. Development and validation of a chromatin regulator prognostic signature in colon adenocarcinoma. Front Genet 2022; 13:986325. [PMID: 36506326 PMCID: PMC9727087 DOI: 10.3389/fgene.2022.986325] [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: 07/05/2022] [Accepted: 11/11/2022] [Indexed: 11/24/2022] Open
Abstract
Aberrant expression of chromatin regulators (CRs) could lead to the development of various diseases including cancer. However, the biological function and prognosis role of CRs in colon adenocarcinoma (COAD) remains unclear. We performed the clustering analyses for expression profiling of COAD downloaded from The Cancer Genome Atlas. We developed a chromatin regulator prognostic model, which was validated in an independent cohort data. Time-intendent receiver operating characteristics curve was used to evaluate predict ability of model. Univariate and multivariate cox regression were used to assess independence of risk score. Nomogram was established to assess individual risk. Gene ontology, and Kyoto Encyclopedia of genes and genomes, gene set variation analysis and gene set enrichment analysis were performed to explore the function of CRs. Immune infiltration and drug sensitivity were also performed to assess effect of CRs on treatment in COAD. COAD can be separated into two subtypes with different clinical characteristics and prognosis. The C2 had elevated immune infiltration levels and low tumor purity. Using 12 chromatin regulators, we developed and validated a prognostic model that can predict the overall survival of COAD patients. We built a risk score that can be an independent prognosis predictor of COAD. The nomogram score system achieved the best predict ability and were also confirmed by decision curve analysis. There were significantly different function and pathway enrichment, immune infiltration levels, and tumor mutation burden between high-risk and low-risk group. The external validation data also indicated that high-risk group had higher stable disease/progressive disease response rate and poorer prognosis than low-risk group. Besides, the signature genes included in the model could cause chemotherapy sensitivity to some small molecular compounds. Our integrative analyses for chromatin regulators could provide new insights for the risk management and individualized treatment in COAD.
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Affiliation(s)
- Wenlong Yang
- Department of Gastrointestinal Surgery, Third Xiangya Hospital, Central South University, Changsha, Hunan, China,*Correspondence: Wenlong Yang,
| | - Chenhua Luo
- Xiangya School of Medicine, Central South University, Changsha, Hunan, China
| | - Shan Chen
- Department of Pharmacy, Central South University, Changsha, Hunan, China
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Xu C, Liu Y, Zhang Y, Gao L. The role of a cuproptosis-related prognostic signature in colon cancer tumor microenvironment and immune responses. Front Genet 2022; 13:928105. [PMCID: PMC9596916 DOI: 10.3389/fgene.2022.928105] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 09/26/2022] [Indexed: 11/13/2022] Open
Abstract
Background: Colon adenocarcinoma (COAD) is a common malignant tumor of the digestive tract with poor clinical outcomes. Cuproptosis is a novel cell death mechanism and linked to mitochondrial respiration. However, the role of cuproptosis in colon cancer tumor microenvironment (TME) and immune responses remains unknown.Methods: We conducted difference analysis to identify the differential expressed cuproptosis-related genes (CRGs). According to the CRGs, the TCGA-COAD samples were categorized using consensus clustering. The LASSO regression analysis was utilized to develop the cuproptosis-related signature. We then verified the model reliability by Kaplan–Meier, PCA, and ROC analysis. The GES39582 cohort served as the validation set. GO and KEGG functional analyses were conducted to investigate the underlying mechanism. We compared the infiltration levels of immune cells, the expression levels of immune checkpoints, and microsatellite instability (MSI) status between the high- and low-risk groups. Additionally, the relationships between the risk signature and immune cells and cancer stem cell (CSC) were analyzed.Results: Finally, we identified 9 differentially expressed CRGs in COAD. According to the expression of CRGs, the TCGA-COAD samples were separated into two clusters. The 11-gene signature was established by LASSO, and it had excellent predictive power for COAD prognosis. Besides, we used the GSE39582 cohort to validate the prognostic value of the model. GO and KEGG results demonstrated that the survival differences between two risk groups was mainly linked to the extracellular matrix (ECM). Further immune characterization analysis showed the significant differences in the immune cell infiltration and immune responses between two risk groups.Conclusion: Overall, the novel cuproptosis-related signature was able to accurately predict COAD prognosis and played important roles in COAD tumor microenvironment and immune responses.
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Affiliation(s)
- Chenyang Xu
- Department of General Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Yonghao Liu
- Department of Imaging, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Yuxi Zhang
- Department of General Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Ling Gao
- Department of General Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China
- *Correspondence: Ling Gao,
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Zhou R, Gao Z, Ju Y. Novel six-gene prognostic signature based on colon adenocarcinoma immune-related genes. BMC Bioinformatics 2022; 23:418. [PMID: 36221049 PMCID: PMC9552517 DOI: 10.1186/s12859-022-04909-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Accepted: 08/23/2022] [Indexed: 12/05/2022] Open
Abstract
Background Colon adenocarcinoma (COAD) is one of the most common gastrointestinal tumors worldwide, and immunotherapy is one of the most promising treatments for it. Identifying immune genes involved in the development and maintenance of cancer is key to the use of tumor immunotherapy. This study aimed to determine the prognostic value of immune genes in patients with COAD and to establish an immune-related gene signature. Differentially expressed genes, immune-related genes (DEIGs), and transcription factors (DETFs) were screened using the following databases: Cistrome, The Cancer Genome Atlas (TCGA), the Immunology Database and Analysis Portal, and InnateDB. We constructed a network showing the regulation of DEIGs by DETFs. Using weighted gene co-expression network analysis, we prepared 5 co-expressed gene modules; 6 hub genes (CD1A, CD1B, FGF9, GRP, SERPINE1, and F2RL2) obtained using univariate and multivariate regression analysis were used to construct a risk model. Patients from TCGA database were divided into high- and low-risk groups based on whether their risk score was greater or less than the mean; the public dataset GSE40967, which contains gene expression profiles of 566 colon cancer patients, was used for validation. Results Survival analysis, somatic gene mutations, and tumor-infiltrating immune cells differed significantly between the high- and low-risk groups. Conclusions This immune-related gene signature could play an important role in guiding treatment, making prognoses, and potentially developing future clinical applications. Supplementary Information The online version contains supplementary material available at 10.1186/s12859-022-04909-2.
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Affiliation(s)
- Rui Zhou
- Surgical Department of Gastrointestinal Surgery, Shunde Hospital of Southern Medical University, No. 1 Jiazi Road, Shunde District, Foshan, 528399, Guangdong, China
| | - Zhuowei Gao
- Medical Department of Traditional Chinese Medicine, Shunde Hospital of Guangzhou University of Traditional Chinese Medicine, No. 12, Jinsha Avenue, Shunde District, Foshan, 510006, Guangdong, China
| | - Yongle Ju
- Surgical Department of Gastrointestinal Surgery, Shunde Hospital of Southern Medical University, No. 1 Jiazi Road, Shunde District, Foshan, 528399, Guangdong, China.
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Identification of Prognostic Fatty Acid Metabolism lncRNAs and Potential Molecular Targeting Drugs in Uveal Melanoma. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2022; 2022:3726351. [PMID: 36267302 PMCID: PMC9578887 DOI: 10.1155/2022/3726351] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/11/2022] [Revised: 09/17/2022] [Accepted: 09/24/2022] [Indexed: 11/25/2022]
Abstract
Background The aim of this study was to identify prognostic fatty acid metabolism lncRNAs and potential molecular targeting drugs in uveal melanoma through integrated bioinformatics analysis. Methods In the present study, we obtained the expression matrix of 309 FAM-mRNAs and identified 225 FAM-lncRNAs by coexpression network analysis. We then performed univariate Cox analysis, LASSO regression analysis, and cross-validation and finally obtained an optimized UVM prognosis prediction model composed of four PFAM-lncRNAs (AC104129.1, SOS1-IT1, IDI2-AS1, and DLGAP1-AS2). Results The survival curves showed that the survival time of UVM patients in the high-risk group was significantly lower than that in the low-risk group in the train cohort, test cohort, and all patients in the prognostic prediction model (P < 0.05). We further performed risk prognostic assessment, and the results showed that the risk scores of the high-risk group in the train cohort, test cohort, and all patients were significantly higher than those of the low-risk group (P < 0.05), patient survival decreased and the number of deaths increased with increasing risk scores, and AC104129.1, SOS1-IT1, and DLGAP1-AS2 were high-risk PFAM-lncRNAs, while IDI2-AS1 were low-risk PFAM-lncRNAs. Afterwards, we further verified the accuracy and the prognostic value of our model in predicting prognosis by PCA analysis and ROC curves. Conclusion We identified 24 potential molecularly targeted drugs with significant sensitivity differences between high- and low-risk UVM patients, of which 13 may be potential targeted drugs for high-risk patients. Our findings have important implications for early prediction and early clinical intervention in high-risk UVM patients.
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Luan L, Dai Y, Shen T, Yang C, Chen Z, Liu S, Jia J, Li Z, Fang S, Qiu H, Cheng X, Yang Z. Development of a novel hypoxia-immune–related LncRNA risk signature for predicting the prognosis and immunotherapy response of colorectal cancer. Front Immunol 2022; 13:951455. [PMID: 36189298 PMCID: PMC9516397 DOI: 10.3389/fimmu.2022.951455] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 08/22/2022] [Indexed: 11/21/2022] Open
Abstract
Background Colorectal cancer (CRC) is one of the most common digestive system tumors worldwide. Hypoxia and immunity are closely related in CRC; however, the role of hypoxia-immune–related lncRNAs in CRC prognosis is unknown. Methods Data used in the current study were sourced from the Gene Expression Omnibus and The Cancer Genome Atlas (TCGA) databases. CRC patients were divided into low- and high-hypoxia groups using the single-sample gene set enrichment analysis (ssGSEA) algorithm and into low- and high-immune groups using the Estimation of STromal and Immune cells in MAlignant Tumours using Expression data (ESTIMATE) algorithm. Differentially expressed lncRNAs (DElncRNAs) between low- and high-hypoxia groups, low- and high-immune groups, and tumor and control samples were identified using the limma package. Hypoxia-immune–related lncRNAs were obtained by intersecting these DElncRNAs. A hypoxia-immune–related lncRNA risk signature was developed using univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analyses. The tumor microenvironments in the low- and high-risk groups were evaluated using ssGSEA, ESTIMATE, and the expression of immune checkpoints. The therapeutic response in the two groups was assessed using TIDE, IPS, and IC50. A ceRNA network based on signature lncRNAs was constructed. Finally, we used RT-qPCR to verify the expression of hypoxia-immune–related lncRNA signatures in normal and cancer tissues. Results Using differential expression analysis, and univariate Cox and LASSO regression analyses, ZNF667-AS1, LINC01354, LINC00996, DANCR, CECR7, and LINC01116 were selected to construct a hypoxia-immune–related lncRNA signature. The performance of the risk signature in predicting CRC prognosis was validated in internal and external datasets, as evidenced by receiver operating characteristic curves. In addition, we observed significant differences in the tumor microenvironment and immunotherapy response between low- and high-risk groups and constructed a CECR7–miRNA–mRNA regulatory network in CRC. Furthermore, RT-qPCR results confirmed that the expression patterns of the six lncRNA signatures were consistent with those in TCGA-CRC cohort. Conclusion Our study identified six hypoxia-immune–related lncRNAs for predicting CRC survival and sensitivity to immunotherapy. These findings may enrich our understanding of CRC and help improve CRC treatment. However, large-scale long-term follow-up studies are required for verification.
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Affiliation(s)
- Likun Luan
- Department of Gastric and Intestinal Surgery, The Third Affiliated Hospital of Kunming Medical University/Yunnan Tumor Hospital, Kunming, China
| | - Youguo Dai
- Department of Gastric and Intestinal Surgery, The Third Affiliated Hospital of Kunming Medical University/Yunnan Tumor Hospital, Kunming, China
| | - Tao Shen
- Department of Colorectal Surgery, The Third Affiliated Hospital of Kunming Medical University/Yunnan Tumor Hospital, Kunming, China
| | - Changlong Yang
- Department of Gastric and Intestinal Surgery, The Third Affiliated Hospital of Kunming Medical University/Yunnan Tumor Hospital, Kunming, China
| | - Zhenpu Chen
- Tumor Institute, The Third Affiliated Hospital of Kunming Medical University/Yunnan Tumor Hospital, Kunming, China
| | - Shan Liu
- Departments of Combination of Traditional Chinese and Western Medicine, The Third Affiliated Hospital of Kunming Medical University/Yunnan Tumor Hospital, Kunming, China
| | - Junyi Jia
- Department of Gastric and Intestinal Surgery, The Third Affiliated Hospital of Kunming Medical University/Yunnan Tumor Hospital, Kunming, China
| | - Zhenhui Li
- Department of Radiology, The Third Affiliated Hospital of Kunming Medical University/Yunnan Tumor Hospital, Kunming, China
| | - Shaojun Fang
- Department of Colorectal Surgery, The Third Affiliated Hospital of Kunming Medical University/Yunnan Tumor Hospital, Kunming, China
| | - Hengqiong Qiu
- Department of Surgery Teaching Management, The Third Affiliated Hospital of Kunming Medical University/Yunnan Tumor Hospital, Kunming, China
| | - Xianshuo Cheng
- Department of Colorectal Surgery, The Third Affiliated Hospital of Kunming Medical University/Yunnan Tumor Hospital, Kunming, China
- *Correspondence: Xianshuo Cheng, ; Zhibin Yang,
| | - Zhibin Yang
- Department of Colorectal Surgery, The Third Affiliated Hospital of Kunming Medical University/Yunnan Tumor Hospital, Kunming, China
- *Correspondence: Xianshuo Cheng, ; Zhibin Yang,
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11
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Li J, Peng P, Lai KP. Therapeutic targets and functions of curcumol against COVID-19 and colon adenocarcinoma. Front Nutr 2022; 9:961697. [PMID: 35967794 PMCID: PMC9372556 DOI: 10.3389/fnut.2022.961697] [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: 06/05/2022] [Accepted: 08/01/2022] [Indexed: 11/29/2022] Open
Abstract
Since 2019, the coronavirus disease (COVID-19) has caused 6,319,395 deaths worldwide. Although the COVID-19 vaccine is currently available, the latest variant of the virus, Omicron, spreads more easily than earlier strains, and its mortality rate is still high in patients with chronic diseases, especially cancer patients. So, identifying a novel compound for COVID-19 treatment could help reduce the lethal rate of the viral infection in patients with cancer. This study applied network pharmacology and systematic bioinformatics analysis to determine the possible use of curcumol for treating colon adenocarcinoma (COAD) in patients infected with COVID-19. Our results showed that COVID-19 and COAD in patients shared a cluster of genes commonly deregulated by curcumol. The clinical pathological analyses demonstrated that the expression of gamma-aminobutyric acid receptor subunit delta (GABRD) was associated with the patients' hazard ratio. More importantly, the high expression of GABRD was associated with poor survival rates and the late stages of COAD in patients. The network pharmacology result identified seven-core targets, including solute carrier family 6 member 3, gamma-aminobutyric acid receptor subunit pi, butyrylcholinesterase, cytochrome P450 3A4, 17-beta-hydroxysteroid dehydrogenase type 2, progesterone receptor, and GABRD of curcumol for treating patients with COVID-19 and COAD. The bioinformatic analysis further highlighted their importance in the biological processes and molecular functions in gland development, inflammation, retinol, and steroid metabolism. The findings of this study suggest that curcumol could be an alternative compound for treating patients with COVID-19 and COAD.
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Affiliation(s)
- Jun Li
- The Pharmaceutical Department, The Second Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Peng Peng
- Department of Gastroenterology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Keng Po Lai
- Clinical Medicine Research Center, The Second Affiliated Hospital of Guangxi Medical University, Nanning, China
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12
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Song D, Zhang D, Chen S, Wu J, Hao Q, Zhao L, Ren H, Du N. Identification and validation of prognosis-associated DNA repair gene signatures in colorectal cancer. Sci Rep 2022; 12:6946. [PMID: 35484177 PMCID: PMC9050689 DOI: 10.1038/s41598-022-10561-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Accepted: 04/04/2022] [Indexed: 12/24/2022] Open
Abstract
Colorectal cancer (CRC) is the third most common malignant tumor. DNA damage plays a crucial role in tumorigenesis, and abnormal DNA repair pathways affect the occurrence and progression of CRC. In the current study, we aimed to construct a DNA repair-related gene (DRG) signature to predict the overall survival (OS) of patients with CRC patients. The differentially expressed DRGs (DE-DRGs) were analyzed using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The prognostic gene signature was identified by univariate Cox regression and least absolute shrinkage and selection operator (LASSO)-penalized Cox proportional hazards regression analysis. The predictive ability of the model was evaluated using the Kaplan–Meier curves and time-dependent receiver operating characteristic (ROC) curves. The gene set enrichment analysis (GSEA) was performed to explore the underlying biological processes and signaling pathways. ESTIMATE and CIBERSORT were implemented to estimate the tumor immune score and immune cell infiltration status between the different risk group. The half-maximal inhibitory concentration (IC50) was evaluated to representing the drug response of this signature. Nine DE-DRGs (ESCO2, AXIN2, PLK1, CDC25C, IGF1, TREX2, ALKBH2, ESR1 and MC1R) signatures was constructed to classify patients into high- and low-risk groups. The risk score was an independent prognostic indicator of OS (hazard ratio > 1, P < 0.001). The genetic alteration analysis indicated that the nine DE-DRGs in the signature were changed in 63 required samples (100%), and the major alteration was missense mutation. Function enrichment analysis revealed that the immune response and mtotic sister chromatid segregation were the main biological processes. The high-risk group had higher immune score than the low-risk group. What’s more, low-risk patients were more sensitive to selumetinib and dasatinib. The nine DE-DRGs signature was significantly associated with OS and provided a new insight for the diagnosis and treatment of CRC.
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Affiliation(s)
- Dingli Song
- Department of Thoracic Surgery, The First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China
| | - Dai Zhang
- Department of Oncology, The Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China
| | - Sisi Chen
- Department of Thoracic Surgery, The First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China
| | - Jie Wu
- Department of Thoracic Surgery, The First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China
| | - Qian Hao
- Department of Oncology, The Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China
| | - Lili Zhao
- Department of Neurology, The Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China
| | - Hong Ren
- Department of Thoracic Surgery, The First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China.
| | - Ning Du
- Department of Thoracic Surgery, The First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China.
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13
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Liang YC, Su Q, Liu YJ, Xiao H, Yin HZ. Centromere Protein A (CENPA) Regulates Metabolic Reprogramming in the Colon Cancer Cells by Transcriptionally Activating Karyopherin Subunit Alpha 2 (KPNA2). THE AMERICAN JOURNAL OF PATHOLOGY 2021; 191:2117-2132. [PMID: 34508688 DOI: 10.1016/j.ajpath.2021.08.010] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Revised: 08/09/2021] [Accepted: 08/11/2021] [Indexed: 02/07/2023]
Abstract
The karyopherin α2 subunit gene (KPNA2) has been reported as an oncogene and is involved in metabolic reprogramming in cancer. This study aimed to explore the function of KPNα2 in the growth and glycolysis in colon cancer (CC) cells. Genes from the Oncomine database that were differentially expressed in multiple CC types were screened. Bioinformatics analysis suggested that KPNA2 was highly expressed in CC: High expression of KPNA2 was detected in the CC cell lines. Down-regulation of KPNA2 reduced viability and DNA-replication ability, and it increased apoptosis of HCT116 and LoVo cells. It also reduced glucose consumption, extracellular acidification rate, and the ATP production in cells. Centromere protein A (CENPA) was confirmed as an upstream transcription activator of KPNA2. There was significant H3K27ac modification in the promoter region of KPNA2. CENPA mainly recruited histone acetyltransferase general control of amino acid synthesis (GCN)-5 to the promoter region of KPNA2 to induce transcription activation. Overexpression of either CENPA or GCN-5 blocked the role of short hairpin KPNα2 and restored growth and glycolysis in CC cells. To conclude, the findings from this study suggest that CENPA recruits GCN-5 to the promoter region of KPNA2 to induce KPNα2 activation, which strengthens growth and glycolysis in, and augments the development of, CC.
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Affiliation(s)
- Yi-Chao Liang
- Department of General Surgery, Shengjing Hospital of China Medical University, Shenyang, China
| | - Qi Su
- Department of General Surgery, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yu-Jie Liu
- Department of General Surgery, Shengjing Hospital of China Medical University, Shenyang, China
| | - Hong Xiao
- Department of General Surgery, Shengjing Hospital of China Medical University, Shenyang, China
| | - Hong-Zhuan Yin
- Department of General Surgery, Shengjing Hospital of China Medical University, Shenyang, China.
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14
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Deng D, Luo X, Zhang S, Xu Z. Immune cell infiltration-associated signature in colon cancer and its prognostic implications. Aging (Albany NY) 2021; 13:19696-19709. [PMID: 34349038 PMCID: PMC8386549 DOI: 10.18632/aging.203380] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Accepted: 07/15/2021] [Indexed: 02/05/2023]
Abstract
Tumor immune cell infiltration (ICI) has been reported in various studies to be correlated with tumor diagnosis, clinical treatment sensitivity and prognosis. It is an important direction to study the characteristics of immune cell infiltration and develop new prognostic markers to improve the treatment of colon cancer. In this paper, we systematically analyzed the ICI characteristics and obtained three ICI clusters. Then, the ICI scores were constructed and its prognostic implications were discussed. From the results, the ICI score patterns were linked to a great survival difference (p<0.001). A high ICI score was characterized by a higher fraction of plasma cells, CD8+ T cells, memory resting CD4+ T cells, monocytes, eosinophils and dendritic cells, which had better prognosis. Macrophages and neutrophils were increased in low ICI score patients with decreased overall survival. Immune checkpoint molecules (PDCD1, CD274, LAG3, IDO1, CTLA-4, TIGHT and HAVCR2) were found to be significantly overexpressed in the low ICI score subgroup. In addition, we also studied the correlation between the tumor mutation burden (TMB) and ICI score. This study indicated the ICI score could serve as a potential prognostic biomarker for colon cancer patients’ immunotherapy.
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Affiliation(s)
- Dan Deng
- Department of Cardiology, Zhuzhou Central Hospital, Zhuzhou 412007, China.,Department of Integrated Traditional Chinese and Western Internal Medicine, The Second Xiangya Hospital of Central South University, Changsha 410012, China
| | - Xin Luo
- Department of Cardiology, Zhuzhou Central Hospital, Zhuzhou 412007, China
| | - Sifang Zhang
- Department of Integrated Traditional Chinese and Western Internal Medicine, The Second Xiangya Hospital of Central South University, Changsha 410012, China
| | - Zhijie Xu
- Department of Pathology, Xiangya Hospital of Central South University, Changsha 410008, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410008, China
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15
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Xing XL, Zhang T, Yao ZY, Xing C, Wang C, Liu YW, Huang M. Immune-Related Gene Expression Analysis Revealed Three lncRNAs as Prognostic Factors for Colon Cancer. Front Genet 2021; 12:690053. [PMID: 34306030 PMCID: PMC8299306 DOI: 10.3389/fgene.2021.690053] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Accepted: 06/21/2021] [Indexed: 01/02/2023] Open
Abstract
Colorectal cancer (CRC) is one of the most common cancers. Almost 80% of CRC cases are colon adenocarcinomas (COADs). Several studies have indicated the role of immunotherapy in the treatment of various cancers. Our study aimed to identify immune-related long non-coding RNAs (lncRNAs) and to use them to construct a risk assessment model for evaluating COAD prognosis. Using differential expression, correlation, and Cox regression analyses, we identified three immune-related differentially expressed lncRNAs (IR-DELs) and used them to construct a risk assessment model. The area under the curve (AUC) for each receiver operating characteristic (ROC) curve at 3-, 5-, and 10-years were greater than 0.6. In addition, the risk assessment model was correlated with several immune cells and factors. The three IR-DELs (AC124067.4, LINC02604, and MIR4435-2HG) identified in this study can be used to predict outcomes for patients with COAD and might help in identifying those who can benefit from anti-tumor immunotherapy.
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Affiliation(s)
- Xiao-Liang Xing
- School of Public Health and Laboratory Medicine, Hunan University of Medicine, Huaihua, China
| | - Ti Zhang
- School of Public Health and Laboratory Medicine, Hunan University of Medicine, Huaihua, China
| | - Zhi-Yong Yao
- School of Public Health and Laboratory Medicine, Hunan University of Medicine, Huaihua, China
| | - Chaoqun Xing
- School of Public Health and Laboratory Medicine, Hunan University of Medicine, Huaihua, China
| | - Chunxiao Wang
- School of Public Health and Laboratory Medicine, Hunan University of Medicine, Huaihua, China
| | - Yuan-Wu Liu
- Beijing Advanced Innovation Center for Food Nutrition and Human Health, China Agricultural University, Beijing, China
| | - Minjiang Huang
- School of Public Health and Laboratory Medicine, Hunan University of Medicine, Huaihua, China
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16
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Kang X, Chen Y, Yi B, Yan X, Jiang C, Chen B, Lu L, Sun Y, Shi R. An integrative microenvironment approach for laryngeal carcinoma: the role of immune/methylation/autophagy signatures on disease clinical prognosis and single-cell genotypes. J Cancer 2021; 12:4148-4171. [PMID: 34093817 PMCID: PMC8176413 DOI: 10.7150/jca.58076] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Accepted: 04/27/2021] [Indexed: 12/14/2022] Open
Abstract
The effects of methylation/autophagy-related genes (MARGs) and immune infiltration in the tumor microenvironment on the prognosis of laryngeal cancer were comprehensively explored in this study. Survival analysis screened out 126 MARGs and 10 immune cells potentially associated with the prognosis of laryngeal carcinoma. Cox and lasso regression analyses were then used to select 8 MARGs (CAPN10, DAPK2, MBTPS2, ST13, CFLAR, FADD, PEX14 and TSC2) and 2 immune cells (Eosinophil and Mast cell) to obtain the prognostic risk scoring system (pRS). The pRS was used to establish a risk prediction model for the prognosis of laryngeal cancer. The predictive ability of the prediction model was evaluated by GEO datasets and our clinical samples. Further analysis revealed that pRS is highly associated with single nucleotide polymorphism (SNP), copy number variation (CNV), immune checkpoint blockade (ICB) therapy and tumor microenvironment. Moreover, the screened pRS-related ceRNA network and circ_0002951/miR-548k/HAS2 pathway provide potential therapeutic targets and biomarkers of laryngocarcinoma. Based on the clustering results of pRS-related genes, single cells were then genotyped and revealed by integrated scRNA-seq in laryngeal cancer samples. Fibroblasts were found enriched in high risk cell clusters at the scRNA-seq level. Fibroblast-related ligand-receptor interactions were then exposed and a neural network-based deep learning model based on these pRS-related hub gene signatures was also established with a high accuracy in cell type prediction. In conclusion, the combination of single-cell and transcriptome laryngeal carcinoma landscape analyses can investigate the link between the tumor microenvironmental and prognostic characteristics.
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Affiliation(s)
- Xueran Kang
- Department of Otolaryngology-Head and Neck Surgery, Shanghai ninth people's Hospital, Shanghai Jiao Tong University School of Medicine; Ear Institute, Shanghai JiaoTong University School of Medicine; Shanghai Key Laboratory of Translational Medicine on Ear and Nose diseases, Shanghai, China
| | - Yisheng Chen
- Department of Orthopedics, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Bin Yi
- Department of Otolaryngology-Head and Neck Surgery, Shanghai ninth people's Hospital, Shanghai Jiao Tong University School of Medicine; Ear Institute, Shanghai JiaoTong University School of Medicine; Shanghai Key Laboratory of Translational Medicine on Ear and Nose diseases, Shanghai, China
| | - Xiaojun Yan
- Department of Otolaryngology-Head and Neck Surgery, Shanghai ninth people's Hospital, Shanghai Jiao Tong University School of Medicine; Ear Institute, Shanghai JiaoTong University School of Medicine; Shanghai Key Laboratory of Translational Medicine on Ear and Nose diseases, Shanghai, China
| | - Chenyan Jiang
- Department of Otolaryngology-Head and Neck Surgery, Shanghai ninth people's Hospital, Shanghai Jiao Tong University School of Medicine; Ear Institute, Shanghai JiaoTong University School of Medicine; Shanghai Key Laboratory of Translational Medicine on Ear and Nose diseases, Shanghai, China
| | - Bin Chen
- Department of Otolaryngology-Head and Neck Surgery, Shanghai ninth people's Hospital, Shanghai Jiao Tong University School of Medicine; Ear Institute, Shanghai JiaoTong University School of Medicine; Shanghai Key Laboratory of Translational Medicine on Ear and Nose diseases, Shanghai, China
| | - Lixing Lu
- Department of Otolaryngology-Head and Neck Surgery, Shanghai ninth people's Hospital, Shanghai Jiao Tong University School of Medicine; Ear Institute, Shanghai JiaoTong University School of Medicine; Shanghai Key Laboratory of Translational Medicine on Ear and Nose diseases, Shanghai, China
| | - Yuxing Sun
- Department of Otolaryngology-Head and Neck Surgery, Shanghai ninth people's Hospital, Shanghai Jiao Tong University School of Medicine; Ear Institute, Shanghai JiaoTong University School of Medicine; Shanghai Key Laboratory of Translational Medicine on Ear and Nose diseases, Shanghai, China
| | - Runjie Shi
- Department of Otolaryngology-Head and Neck Surgery, Shanghai ninth people's Hospital, Shanghai Jiao Tong University School of Medicine; Ear Institute, Shanghai JiaoTong University School of Medicine; Shanghai Key Laboratory of Translational Medicine on Ear and Nose diseases, Shanghai, China
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17
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Li C, Yu H, Sun Y, Zeng X, Zhang W. Identification of the hub genes in gastric cancer through weighted gene co-expression network analysis. PeerJ 2021; 9:e10682. [PMID: 33717664 PMCID: PMC7938783 DOI: 10.7717/peerj.10682] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Accepted: 12/09/2020] [Indexed: 02/05/2023] Open
Abstract
Background Gastric cancer is one of the most lethal tumors and is characterized by poor prognosis and lack of effective diagnostic or therapeutic biomarkers. The aim of this study was to find hub genes serving as biomarkers in gastric cancer diagnosis and therapy. Methods GSE66229 from Gene Expression Omnibus (GEO) was used as training set. Genes bearing the top 25% standard deviations among all the samples in training set were performed to systematic weighted gene co-expression network analysis (WGCNA) to find candidate genes. Then, hub genes were further screened by using the “least absolute shrinkage and selection operator” (LASSO) logistic regression. Finally, hub genes were validated in the GSE54129 dataset from GEO by supervised learning method artificial neural network (ANN) algorithm. Results Twelve modules with strong preservation were identified by using WGCNA methods in training set. Of which, five modules significantly related to gastric cancer were selected as clinically significant modules, and 713 candidate genes were identified from these five modules. Then, ADIPOQ, ARHGAP39, ATAD3A, C1orf95, CWH43, GRIK3, INHBA, RDH12, SCNN1G, SIGLEC11 and LYVE1 were screened as the hub genes. These hub genes successfully differentiated the tumor samples from the healthy tissues in an independent testing set through artificial neural network algorithm with the area under the receiver operating characteristic curve at 0.946. Conclusions These hub genes bearing diagnostic and therapeutic values, and our results may provide a novel prospect for the diagnosis and treatment of gastric cancer in the future.
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Affiliation(s)
- Chunyang Li
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Cheng, China.,Medical Big Data Center, Sichuan University, Chengdu, China
| | - Haopeng Yu
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Cheng, China.,Medical Big Data Center, Sichuan University, Chengdu, China
| | - Yajing Sun
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Cheng, China.,Medical Big Data Center, Sichuan University, Chengdu, China
| | - Xiaoxi Zeng
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Cheng, China.,Medical Big Data Center, Sichuan University, Chengdu, China
| | - Wei Zhang
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Cheng, China.,Medical Big Data Center, Sichuan University, Chengdu, China
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