Pan-cancer analysis of somatic mutations across 21 neuroendocrine tumor types.
Ontology highlight
ABSTRACT:
SUBMITTER: Cao Y
PROVIDER: S-EPMC5951840 | biostudies-literature | 2018 May
REPOSITORIES: biostudies-literature
Publications
Pan-cancer analysis of somatic mutations across 21 neuroendocrine tumor types.
Cao Yanan Y Zhou Weiwei W Li Lin L Wang Jiaqian J Gao Zhibo Z Jiang Yiran Y Jiang Xiuli X Shan Aijing A Bailey Matthew H MH Huang Kuan-Lin KL Sun Sam Q SQ McLellan Michael D MD Niu Beifang B Wang Weiqing W Ding Li L Ning Guang G
Cell research 20180305 5
Similar Datasets
Project description:BackgroundThe advent of high throughput sequencing has enabled researchers to systematically evaluate the genetic variations in cancer, identifying many cancer-associated genes. Although cancers in the same tissue are widely categorized in the same group, they demonstrate many differences concerning their mutational profiles. Hence, there is no definitive treatment for most cancer types. This reveals the importance of developing new pipelines to identify cancer-associated genes accurately and re-classify patients with similar mutational profiles. Classification of cancer patients with similar mutational profiles may help discover subtypes of cancer patients who might benefit from specific treatment types.ResultsIn this study, we propose a new machine learning pipeline to identify protein-coding genes mutated in many samples to identify cancer subtypes. We apply our pipeline to 12,270 samples collected from the international cancer genome consortium, covering 19 cancer types. As a result, we identify 17 different cancer subtypes. Comprehensive phenotypic and genotypic analysis indicates distinguishable properties, including unique cancer-related signaling pathways.ConclusionsThis new subtyping approach offers a novel opportunity for cancer drug development based on the mutational profile of patients. Additionally, we analyze the mutational signatures for samples in each subtype, which provides important insight into their active molecular mechanisms. Some of the pathways we identified in most subtypes, including the cell cycle and the Axon guidance pathways, are frequently observed in cancer disease. Interestingly, we also identified several mutated genes and different rates of mutation in multiple cancer subtypes. In addition, our study on "gene-motif" suggests the importance of considering both the context of the mutations and mutational processes in identifying cancer-associated genes. The source codes for our proposed clustering pipeline and analysis are publicly available at: https://github.com/bcb-sut/Pan-Cancer .
| S-EPMC9316662 | biostudies-literature
Project description:To discover functional gene clusters across cancers, we performed a systematic pan-cancer analysis of 33 cancer types. We identified genes that were associated with somatic mutations and were the cores of a co-expression network. We found that multiple cancer types have relatively exclusive hub genes individually; however, the hub genes cooperate with each other based on their functional relationship. When we built a protein-protein interaction network of hub genes and found nine functional gene clusters across cancer types, the gene clusters divided not only the region of the network map, but also the function of the network by their distinct roles related to the development and progression of cancer. This functional relationship between the clusters and cancers was underpinned by the high expression of module genes and enrichment of programmed cell death, and known candidate cancer genes. In addition to protein-coding hub genes, non-coding hub genes had a possible relationship with cancer. Overall, our approach of investigating cancer genes enabled finding pan-cancer hub genes and common functional gene clusters shared by multiple cancer types based on the expression status of the primary tumour and the functional relationship of genes in the biological network.
| S-EPMC5902616 | biostudies-literature
Project description:BackgroundmiRNAs are considered important players in oncogenesis, serving either as oncomiRs or suppressormiRs. Although the accumulation of somatic alterations is an intrinsic aspect of cancer development and many important cancer-driving mutations have been identified in protein-coding genes, the area of functional somatic mutations in miRNA genes is heavily understudied.MethodsHere, based on the analysis of large genomic datasets, mostly the whole-exome sequencing of over 10,000 cancer/normal sample pairs deposited within the TCGA repository, we undertook an analysis of somatic mutations in miRNA genes.FindingsWe identified and characterized over 10,000 somatic mutations and showed that some of the miRNA genes are overmutated in Pan-Cancer and/or specific cancers. Nonrandom occurrence of the identified mutations was confirmed by a strong association of overmutated miRNA genes with KEGG pathways, most of which were related to specific cancer types or cancer-related processes. Additionally, we showed that mutations in some of the overmutated genes correlate with miRNA expression, cancer staging, and patient survival.InterpretationOur study is the first comprehensive Pan-Cancer study of cancer somatic mutations in miRNA genes. It may help to understand the consequences of mutations in miRNA genes and the identification of miRNA functional mutations. The results may also be the first step (form the basis and provide the resources) in the development of computational and/or statistical approaches/tools dedicated to the identification of cancer-driver miRNA genes.FundingThis work was supported by research grants from the Polish National Science Centre 2016/22/A/NZ2/00184 and 2015/17/N/NZ3/03629.
| S-EPMC7648123 | biostudies-literature
Project description:It is widely accepted that some messenger RNAs are evolutionarily conserved across species, both in sequence and tissue-expression specificity. To date, however, little effort has been made to exploit the transcriptome divergence between cancer and adjacent normal tissue at the pan-organ level. In this work, a transcriptome sequencing dataset from 675 normal-tumor pairs, representing 21 solid organs in The Cancer Genome Atlas, is used to evaluate expression evolution. The results show that in most cancer types, gene expression divergence and organ-specificity are reduced in cancer tissue compared to adjacent normal tissue. Furthermore, we observe that all cancers share cell cycle dysregulation through interrogating differentially expressed protein coding genes. Meanwhile, weighted correlation network analysis is used to detect of the gene module structure variation between cancer and adjacent normal tissue. And modules consisting of tightly co-regulated genes in cancer change substantially compared with those in adjacent normal tissue. We thus assume that the destruction of a coordinated regulatory network might result in tumorigenesis and tumor progression. Our results provide new insights into the complex cancer biology and shed light on the mysterious regulation mode for cancer.
| S-EPMC5351671 | biostudies-literature
Project description:G Protein-coupled receptors (GPCRs) are the most frequently exploited drug target family, moreover they are often found mutated in cancer. Here we used a dataset of mutations found in patient samples derived from the Genomic Data Commons and compared it to the natural human variance as exemplified by data from the 1000 genomes project. We explored cancer-related mutation patterns in all GPCR classes combined and individually. While the location of the mutations across the protein domains did not differ significantly in the two datasets, a mutation enrichment in cancer patients was observed among class-specific conserved motifs in GPCRs such as the Class A "DRY" motif. A Two-Entropy Analysis confirmed the correlation between residue conservation and cancer-related mutation frequency. We subsequently created a ranking of high scoring GPCRs, using a multi-objective approach (Pareto Front Ranking). Our approach was confirmed by re-discovery of established cancer targets such as the LPA and mGlu receptor families, but also discovered novel GPCRs which had not been linked to cancer before such as the P2Y Receptor 10 (P2RY10). Overall, this study presents a list of GPCRs that are amenable to experimental follow up to elucidate their role in cancer.
| S-EPMC9747925 | biostudies-literature
Project description:Recent evidence shows that the disruption of constitutive insulated neighbourhoods might lead to oncogene dysregulation. We present here a systematic pan-cancer characterisation of the associations between constitutive boundaries and genome alterations in cancer. Specifically, we investigate the enrichment of somatic mutation, abnormal methylation, and copy number alteration events in the proximity of CTCF bindings overlapping with topological boundaries (junctions) in 26 cancer types. Focusing on CTCF motifs that are both in-boundary (overlapping with junctions) and active (overlapping with peaks of CTCF expression), we find a significant enrichment of somatic mutations in several cancer types. Furthermore, mutated junctions are significantly conserved across cancer types, and we also observe a positive selection of transversions rather than transitions in many cancer types. We also analyzed the mutational signature found on the different classes of CTCF motifs, finding some signatures (such as SBS26) to have a higher weight within in-boundary than off-bounday motifs. Regarding methylation, we find a significant number of over-methylated active in-boundary CTCF motifs in several cancer types; similarly to somatic-mutated junctions, they also have a significant conservation across cancer types. Finally, in several cancer types we observe that copy number alterations tend to overlap with active junctions more often than in matched normal samples. While several articles have recently reported a mutational enrichment at CTCF binding sites for specific cancer types, our analysis is pan-cancer and investigates abnormal methylation and copy number alterations in addition to somatic mutations. Our method is fully replicable and suggests several follow-up tumour-specific analyses.
| S-EPMC6964824 | biostudies-literature
Project description:Recent evidence shows that the disruption of constitutive insulated neighbourhoods might lead to oncogene dysregulation. We present here a systematic pan-cancer characterisation of the associations between constitutive boundaries and genome alterations in cancer. Specifically, we investigate the enrichment of somatic mutation, abnormal methylation, and copy number alteration events in the proximity of CTCF bindings overlapping with topological boundaries (junctions) in 26 cancer types. Focusing on CTCF motifs that are both in-boundary (overlapping with junctions) and active (overlapping with peaks of CTCF expression), we find a significant enrichment of somatic mutations in several cancer types. Furthermore, mutated junctions are significantly conserved across cancer types, and we also observe a positive selection of transversions rather than transitions in many cancer types. We also analyzed the mutational signature found on the different classes of CTCF motifs, finding some signatures (such as SBS26) to have a higher weight within in-boundary than off-bounday motifs. Regarding methylation, we find a significant number of over-methylated active in-boundary CTCF motifs in several cancer types; similarly to somatic-mutated junctions, they also have a significant conservation across cancer types. Finally, in several cancer types we observe that copy number alterations tend to overlap with active junctions more often than in matched normal samples. While several articles have recently reported a mutational enrichment at CTCF binding sites for specific cancer types, our analysis is pan-cancer and investigates abnormal methylation and copy number alterations in addition to somatic mutations. Our method is fully replicable and suggests several follow-up tumour-specific analyses.
| S-EPMC6964824 | biostudies-literature
Project description:Cancer-associated muscle wasting is a widespread syndrome in people with cancer and is characterized by weight loss and muscle atrophy, leading to increased morbidity and mortality. However, the tumor-derived factors that affect the development of muscle wasting and the mechanism by which they act remain unknown. To address this knowledge gap, we aimed to delineate differences in tumor molecular characteristics (especially secretion characteristics) between patients with and without sarcopenia across 10 tumor types from The Cancer Genome Atlas (TCGA). We integrated radiological characteristics from CT scans of TCGA cancer patients, which allowed us to calculate skeletal muscle area (SMA) to confirm sarcopenia. We combined TCGA and GTEx (The Genotype-Tissue Expression) data to analyze upregulated secretory genes in 10 tumor types compared with normal tissues. Upregulated secretory genes in the tumor microenvironment and their relation to SMA were analyzed to identify potential muscle wasting biomarkers (560 samples). Meanwhile, their predictive values for patient survival was validated in 3530 samples in 10 tumor types. A total of 560 participants with transcriptomic data and SMA were included. Among those, 136 participants (24.28%) were defined as having sarcopenia based on SMA. Enrichment analysis for upregulated secretory genes in cancers revealed that pathways associated with muscle wasting were strongly enriched in tumor types with a higher prevalence of sarcopenia. A series of SMA-associated secretory protein-coding genes were identified in cancers, which showed distinct gene expression profiles according to tumor type, and could be used to predict prognosis in cancers (p value ≤ 0.002). Unfortunately, those genes were different and rarely overlapped across tumor types. Tumor secretome characteristics were closely related to sarcopenia. Highly expressed secretory mediators in the tumor microenvironment were associated with SMA and could affect the overall survival of cancer patients, which may provide a valuable starting point for the further understanding of the molecular basis of muscle wasting in cancers. More importantly, tumor-derived pro-sarcopenic factors differ across tumor types and genders, which implies that mechanisms of cancer-associated muscle wasting are complex and diverse across tumors, and may require individualized treatment approaches.
| S-EPMC10887289 | biostudies-literature
Project description:In this study we use somatic cancer mutations to identify important functional residues within sets of related genes. We focus on protein kinases, a superfamily of phosphotransferases that share homologous sequences and structural motifs and have many connections to cancer. We develop several statistical tests for identifying Significantly Mutated Positions (SMPs), which are positions in an alignment with mutations that show signs of selection. We apply our methods to 21,917 mutations that map to the alignment of human kinases and identify 23 SMPs. SMPs occur throughout the alignment, with many in the important A-loop region, and others spread between the N and C lobes of the kinase domain. Since mutations are pooled across the superfamily, these positions may be important to many protein kinases. We select eleven mutations from these positions for functional validation. All eleven mutations cause a reduction or loss of function in the affected kinase. The tested mutations are from four genes, including two tumor suppressors (TGFBR1 and CHEK2) and two oncogenes (KDR and ERBB2). They also represent multiple cancer types, and include both recurrent and non-recurrent events. Many of these mutations warrant further investigation as potential cancer drivers.
| S-EPMC5527104 | biostudies-literature
Project description:Recent genomic data points to a growing role for somatic mutations altering core histone and linker histone-encoding genes in cancer. However, the prevalence and the clinical and biological implications of histone gene mutations in malignant tumors remain incompletely defined. To address these knowledge gaps, we analyzed somatic mutations in 88 linker and core histone genes across 12,743 tumors from pediatric, adolescent and young adult (AYA), and adult cancer patients. We established a pan-cancer histone mutation atlas contextualized by patient age, survival outcome, and tumor location. Overall, 11% of tumors harbored somatic histone mutations, with the highest rates observed among chondrosarcoma (67%), pediatric high-grade glioma (pHGG, >60%), and lymphoma (>30%). Previously unreported histone mutations were discovered in pHGG and other pediatric brain tumors, extending the spectrum of histone gene alterations associated with these cancers. Histone mutation status predicted patient survival outcome in tumor entities including adrenocortical carcinoma. Recurrent pan-cancer histone mutation hotspots were defined and shown to converge on evolutionarily conserved and functional residues. Moreover, we studied histone gene mutations in 1700 pan-cancer cell lines to validate the prevalence and spectrum of histone mutations seen in primary tumors and derived histone-associated drug response profiles, revealing candidate drugs targeting histone mutant cancer cells. This study presents the first-of-its-kind atlas of both core and linker histone mutations across pediatric, AYA, and adult cancers, providing a framework by which specific cancers may be redefined in the context of histone and chromatin alterations.
| S-EPMC10462747 | biostudies-literature