Javascript must be enabled to continue!
Pan-cancer analysis identified inflamed microenvironment associated multi-omics signatures
View through CrossRef
Abstract
Background
Immunotherapy has revolutionized cancer therapy. However, responses are not universal. The inflamed tumor microenvironment has been reported to correlate with response in tumor patients. However, how different tumors shape their tumor microenvironment remains a critical unsolved problem. A deeper insight into the molecular characteristics of inflamed tumor microenvironment may be needed.
Materials and methods
Here, based on single-cell RNA sequencing technology and TCGA pan-cancer cohort, we investigated multi-omics molecular features of tumor microenvironment phenotypes. Based on single-cell RNA-seq analysis, we classified pan-cancer tumor samples into inflamed or non-inflamed tumor and identified molecular features of these tumors. Analysis of integrating identified gene signatures with a drug-genomic perturbation database identified multiple drugs which may be helpful for converting non-inflamed tumors to inflamed tumors.
Results
Our results revealed several inflamed/non-inflamed tumor microenvironments-specific molecular characteristics. For example, inflamed tumors highly expressed miR-650 and lncRNA including MIR155HG and LINC00426, these tumors showed activated cytokines-related signaling pathways. Interestingly, non-inflamed tumors tended to express several genes related to neurogenesis. Multi-omics analysis demonstrated the neuro phenotype transformation may be induced by hypomethylated promoters of these genes and down-regulated miR-650. Drug discovery analysis revealed histone deacetylase inhibitors may be a potential choice for helping favorable tumor microenvironment phenotype transformation and aiding current immunotherapy.
Conclusion
Our results provide a comprehensive molecular-level understanding of tumor cell-immune cell interaction and may have profound clinical implications.
Title: Pan-cancer analysis identified inflamed microenvironment associated multi-omics signatures
Description:
Abstract
Background
Immunotherapy has revolutionized cancer therapy.
However, responses are not universal.
The inflamed tumor microenvironment has been reported to correlate with response in tumor patients.
However, how different tumors shape their tumor microenvironment remains a critical unsolved problem.
A deeper insight into the molecular characteristics of inflamed tumor microenvironment may be needed.
Materials and methods
Here, based on single-cell RNA sequencing technology and TCGA pan-cancer cohort, we investigated multi-omics molecular features of tumor microenvironment phenotypes.
Based on single-cell RNA-seq analysis, we classified pan-cancer tumor samples into inflamed or non-inflamed tumor and identified molecular features of these tumors.
Analysis of integrating identified gene signatures with a drug-genomic perturbation database identified multiple drugs which may be helpful for converting non-inflamed tumors to inflamed tumors.
Results
Our results revealed several inflamed/non-inflamed tumor microenvironments-specific molecular characteristics.
For example, inflamed tumors highly expressed miR-650 and lncRNA including MIR155HG and LINC00426, these tumors showed activated cytokines-related signaling pathways.
Interestingly, non-inflamed tumors tended to express several genes related to neurogenesis.
Multi-omics analysis demonstrated the neuro phenotype transformation may be induced by hypomethylated promoters of these genes and down-regulated miR-650.
Drug discovery analysis revealed histone deacetylase inhibitors may be a potential choice for helping favorable tumor microenvironment phenotype transformation and aiding current immunotherapy.
Conclusion
Our results provide a comprehensive molecular-level understanding of tumor cell-immune cell interaction and may have profound clinical implications.
Related Results
Why Pakistan Must Lead in Regional Multi-Omics Research for Precision Medicine
Why Pakistan Must Lead in Regional Multi-Omics Research for Precision Medicine
Precision medicine has emerged as one of the most transformative movements in global healthcare, shifting the clinical emphasis from generalized treatments to highly individualized...
Machine Learning-Based Comparative Analysis of Pan-Cancer and Pan-Normal Tissues Identifies Pan-Cancer Tissue-Enriched circRNAs Related to Cancer Mutations as Potential Exosomal Biomarkers
Machine Learning-Based Comparative Analysis of Pan-Cancer and Pan-Normal Tissues Identifies Pan-Cancer Tissue-Enriched circRNAs Related to Cancer Mutations as Potential Exosomal Biomarkers
A growing body of evidence has shown that circular RNA (circRNA) is a promising exosomal cancer biomarker candidate. However, global circRNA alterations in cancer and the underlyin...
Exploring the classification of cancer cell lines from multiple omic views
Exploring the classification of cancer cell lines from multiple omic views
Background
Cancer classification is of great importance to understanding its pathogenesis, making diagnosis and developing treatment. The accumulation of extensive o...
Benchmarking multi-omics integrative clustering methods for subtype identification in colorectal cancer
Benchmarking multi-omics integrative clustering methods for subtype identification in colorectal cancer
Abstract
Background and objectives
Colorectal cancer (CRC) represents a heterogeneous malignancy that has concerned global burden of incidence and mortality. The tradition...
Are Cervical Ribs Indicators of Childhood Cancer? A Narrative Review
Are Cervical Ribs Indicators of Childhood Cancer? A Narrative Review
Abstract
A cervical rib (CR), also known as a supernumerary or extra rib, is an additional rib that forms above the first rib, resulting from the overgrowth of the transverse proce...
Edoxaban and Cancer-Associated Venous Thromboembolism: A Meta-analysis of Clinical Trials
Edoxaban and Cancer-Associated Venous Thromboembolism: A Meta-analysis of Clinical Trials
Abstract
Introduction
Cancer patients face a venous thromboembolism (VTE) risk that is up to 50 times higher compared to individuals without cancer. In 2010, direct oral anticoagul...
Cancer signatures for reproducible gene expression analysis data: the computational way to achieve precision medicine
Cancer signatures for reproducible gene expression analysis data: the computational way to achieve precision medicine
Cancer is a complex disease, characterized by extensive genomic aberrations with an evident impact on gene expression regulation and cell biological processes. Many studies and som...
Substitution mutational signatures across pan-squamous cell carcinomas
Substitution mutational signatures across pan-squamous cell carcinomas
Abstract
Background
Squamous cell carcinoma (SCC) is a highly heterogeneous and aggressive cancer type with significant g...

