Analysis of multi-omics differences in left-side and right-side colon cancer

2020 ◽  
Author(s):  
Yanyi Huang ◽  
Jinzhong Duanmu ◽  
Yushu Liu ◽  
Mengyun Yan ◽  
Taiyuan Li ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Cancer Patients ◽  
Somatic Mutation ◽  
Clinical Characteristics ◽  
Transcriptome Data ◽  
Clinical Classification ◽  
Immune Microenvironment ◽  
Mutation Data ◽  
Testing Set

Abstract Background:Colon cancer is one of the common tumors of digestive tract. Studies of left-side colon cancer(LCC) and right-side colon cancer(RCC) show that these two subtypes had different prognosis, outcomes, and clinical response to chemotherapy. Therefore,it is necessary to explore the necessity of clinical classification of anatomic subtypes about colon cancer.Methods:We selected the transcriptome data, clinical information and somatic mutation data of colon cancer patients from the the Cancer Genome Atlas(TCGA )database portal.The transcriptome data included 390 colon cancer patients(172 LCC samples and 218 RCC samples),and the somatic mutation data included 142 LCC samples and 187 RCC samples.By conducting a multi-omics analysis of the LCC and RCC from the four aspects of clinical characteristics, immune microenvironment , transcriptomic differences and mutation differences, so as to compare the expression and prognosis difference of LCC and RCC.We are the first to construct prognostic signatures respectively for LCC and RCC respectively.The prognostic signatures is validated by internal testing set, complete set and external testing set(GSE39582).Additionally we also verified the independent prognostic value of the signature.Results:Clinical characteristics analysis results show that RCC had a significantly worse prognosis than LCC.Analysis the immune microenvironment analysis shows that RCC was more immune infiltration than LCC.The results of differential gene analysis showed that there were 360 differential expressed genes,with 142 up genes in LCC and 218 up genes in RCC.Correlation analysis of mutated genes showed that the expression of mutated genes in RCC was negatively correlated, while the expression of mutated genes in LCC was positively correlated, and the mutation frequency of RCC was generally higher than that of LCC.Meanwhile, our 4-mRNA LCC and 6-mRNA RCC prognostic signatures are highly predictive and can be used as independent prognostic factors.Conclusion:The clinical classification of anatomic subtypes of colon cancer is of great significance for its early diagnosis and prognostic risk assessment.Our study provides directions for individualized treatment of left and right colon cancer.

scholarly journals Analysis of multi-omics differences in left-side and right-side colon cancer

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11433
Author(s):  
Yanyi Huang ◽  
Jinzhong Duanmu ◽  
Yushu Liu ◽  
Mengyun Yan ◽  
Taiyuan Li ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Cancer Patients ◽  
Gene Mutation ◽  
Somatic Mutation ◽  
Transcriptome Data ◽  
Characteristic Analysis ◽  
Immune Microenvironment ◽  
Mutation Data ◽  
Upregulated Genes ◽  
Testing Set

Background Colon cancer is one of the most common tumors in the digestive tract. Studies of left-side colon cancer (LCC) and right-side colon cancer (RCC) show that these two subtypes have different prognoses, outcomes, and clinical responses to chemotherapy. Therefore, a better understanding of the importance of the clinical classifications of the anatomic subtypes of colon cancer is needed. Methods We collected colon cancer patients’ transcriptome data, clinical information, and somatic mutation data from the Cancer Genome Atlas (TCGA) database portal. The transcriptome data were taken from 390 colon cancer patients (172 LCC samples and 218 RCC samples); the somatic mutation data included 142 LCC samples and 187 RCC samples. We compared the expression and prognostic differences of LCC and RCC by conducting a multi-omics analysis of each using the clinical characteristics, immune microenvironment, transcriptomic differences, and mutation differences. The prognostic signatures was validated using the internal testing set, complete set, and external testing set (GSE39582). We also verified the independent prognostic value of the signature. Results The results of our clinical characteristic analysis showed that RCC had a significantly worse prognosis than LCC. The analysis of the immune microenvironment showed that immune infiltration was more common in RCC than LCC. The results of differential gene analysis showed that there were 360 differentially expressed genes, with 142 upregulated genes in LCC and 218 upregulated genes in RCC. The mutation frequency of RCC was generally higher than that of LCC. BRAF and KRAS gene mutations were the dominant genes mutations in RCC, and they had a strong mutual exclusion with APC, while APC gene mutation was the dominant gene mutation in LCC. This suggests that the molecular mechanisms of RCC and LCC differed. The 4-mRNA and 6-mRNA in the prognostic signatures of LCC and RCC, respectively, were highly predictive and may be used as independent prognostic factors. Conclusion The clinical classification of the anatomic subtypes of colon cancer is of great significance for early diagnosis and prognostic risk assessment. Our study provides directions for individualized treatment of left and right colon cancer.

scholarly journals Alteration in the immune microenvironment based on APC status in MSS/pMMR colon cancer data retrieved from TCGA

2020 ◽  
Author(s):  
Haishan Lin ◽  
Hongchao Zhen ◽  
Kun Shan ◽  
Xiaoting Ma ◽  
Bangwei Cao
Keyword(s):  
Colon Cancer ◽  
Cancer Patients ◽  
Enrichment Analysis ◽  
Tumor Immunotherapy ◽  
Immune Checkpoints ◽  
Immune Microenvironment ◽  
Cancer Data ◽  
T Cell Infiltration ◽  
Colon Cancers ◽  
Tumor Immune Microenvironment

Abstract Immunotherapy is currently the most advanced anti-tumor treatment approach. The efficacy of anti-tumor immunotherapy is closely related to the tumor immune microenvironment, including immune cells, infiltration of immune factors, and expression of immune checkpoints. At present, the biomarkers for predicting the efficacy of colon cancer immunotherapy do not cover all colon cancer patients suitable for immunotherapy. In this study, TCGA database was used to identify tumor genotypes suitable for anti-tumor immunotherapy. We found that some of the MSS/pMMR populations, that were initially considered unsuitable for immunotherapy, might actually be suitable. In APC-wt/MSS colon cancer, the expression of PD-1, PD-L1, CTLA4 and CYT（GZMA and PRF1）were increased. Based on calculations done by ESTIMATE and CIBERSORT algorithms, the ImmunoScore and the proportion of CT8+ T cell infiltration is increased in these patients. Enrichment analysis was done to screen signaling pathways involved in immune response, extracellular matrix, and cell adhesion. Tumors from 42 colon cancer patients, including 22 APC-mt/MSS and 20 APC-wt/MSS, were immunohistochemically evaluated for expression of CD8 and PD-L1. And APC-wt/MSS tumors showed significantly higher expression of CD8 and PD-L1 than APC-mt/MSS tumor. Based on the results, we found that some colon cancers of APC-wt/MSS are classified by Tumor Immune Microenvironment types (TIMTs) TMIT I. So that we speculate that APC-wt/MSS colon cancer patients could benefit from anti-tumor immunotherapy.

scholarly journals Classification of Colon Cancer Patients Based on the Methylation Patterns of Promoters

2016 ◽  
Vol 14 (2) ◽  
pp. 46 ◽  
Author(s):  
Wonyoung Choi ◽  
Jungwoo Lee ◽  
Jin-Young Lee ◽  
Sun-Min Lee ◽  
Da-Won Kim ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Cancer Patients ◽  
Methylation Patterns

scholarly journals Effect of Aging-Related Genes on the Prognosis of Colon Cancer

2021 ◽  
Author(s):  
Yushu Liu ◽  
Jiantao Gong ◽  
Yanyi Huang ◽  
Qunguang Jiang
Keyword(s):  
Colon Cancer ◽  
Cancer Patients ◽  
Clinical Characteristics ◽  
Cox Regression ◽  
Validation Cohort ◽  
External Validation ◽  
Predictive Ability ◽  
Lasso Regression ◽  
Internal Validation ◽  
Cox Regression Analysis

Abstract Background:Colon cancer is a common malignant cancer with high incidence and poor prognosis. Cell senescence and apoptosis are important mechanisms of tumor occurrence and development, in which aging-related genes(ARGs) play an important role. This study aimed to establish a prognostic risk model based on ARGs for diagnosis and prognosis prediction of colon cancer .Methods: We downloaded transcriptome data and clinical information of colon cancer patients from the Cancer Genome Atlas(TCGA) database and the microarray dataset(GSE39582) from the Gene Expression Omnibus(GEO) database. Univariate COX, least absolute shrinkage and selection operator(LASSO) regression algorithm and multivariate COX regression analysis were used to construct a 6-ARG prognosis model and calculated the riskScore. The prognostic signatures is validated by internal validation cohort and external validation cohort(GSE39582).In addition, functional enrichment pathways and immune microenvironment of aging-related genes(ARGs) were also analyzed. We also analyzed the correlation between rsikScore and clinical features and constructed a nomogram based on riskScore. We are the first to construct prognostic nomogram based on ARGs.Results: Through univariate COX,LASSO regression algorithm and multivariate COX regression analysis,6 prognostic ARGs (PDPK1,RAD52,GSR,IL7,BDNF and SERPINE1) were screened out and riskScore was constructed. We have verified that riskScore has good prognostic value in both internal validation cohort and external validation cohort. Pathway enrichment and immunoanalysis of ARGs provide a direction for the treatment of colon cancer patients. We also found that riskScore was closely related to the clinical characteristics of patients. Based on riskScore and related clinical features, we constructed a nomogram, which has good predictive performance.Conclusion: The 6-ARG prognostic signature we constructed has a certain clinical predictive ability. Its riskScore is also closely related to clinical characteristics, and nomogram based on this has stronger predictive ability than a single indicator. ARGs and the nomogram we constructed may provide a promising treatment for colon cancer patients.

scholarly journals Fusobacteria is Associated with a Th1 and Th17 Immune Microenvironment in Colon Cancer Patients and Germ‐Free Mice

2019 ◽  
Vol 33 (S1) ◽  
Author(s):  
Jada C Domingue ◽  
Julia L Drewes ◽  
Susan Bullman ◽  
Alina Corona ◽  
Christina DeStefano Shields ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Cancer Patients ◽  
Immune Microenvironment ◽  
Germ Free

scholarly journals ROKET: Associating Somatic Mutation with Clinical Outcomes through Kernel Regression and Optimal Transport

2021 ◽  
Author(s):  
Paul Little ◽  
Li Hsu ◽  
Wei Sun
Keyword(s):  
Cancer Patients ◽  
Clinical Outcomes ◽  
Somatic Mutation ◽  
Somatic Mutations ◽  
Optimal Transport ◽  
Kernel Regression ◽  
Multiple Genes ◽  
Cancer Types ◽  
Mutation Data ◽  
Gene Similarity

Somatic mutations in cancer patients are inherently sparse and potentially high dimensional. Cancer patients may share the same set of deregulated biological processes perturbed by different sets of somatically mutated genes. Therefore, when assessing the associations between somatic mutations and clinical outcomes, gene-by-gene analyses is often under-powered because it does not capture the complex disease mechanisms shared across cancer patients. Rather than testing genes one by one, an intuitive approach is to aggregate somatic mutation data of multiple genes to assess the joint association. The challenge is how to aggregate such information. Building on the optimal transport method, we propose a principled approach to estimate the similarity of somatic mutation profiles of multiple genes between tumor samples, while accounting for gene-gene similarity defined by gene annotations or empirical mutational patterns. Using such similarities, we can assess the associations between somatic mutations and clinical outcomes by kernel regression. We have applied our method to analyze somatic mutation data of 17 cancer types and identified at least three cancer types harboring associations between somatic mutations and overall survival, progression-free interval or cytolytic activity.

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