Enhancer somatic mutations with functional impact in lung cancers identified by leveraging the tissue-specific enhancer-target genes regulatory network
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE228832 | GEO | 2023/09/27
REPOSITORIES: GEO
Similar Datasets
Project description:Enhancers are non-coding genomic features that regulate the transcriptional output of their target genes. Their dysregulation has been associated with various diseases including cancer. However, identification and characterisation of non-coding mutations that are relevant for tumorigenesis and prognosis remain a major challenge. Here we present the detection and characterisation of enhancer mutations in a genome-wide analysis of three lung cancer subtypes. We carefully define lung tissue-specific enhancers across the genome by integrating novel experimental data and reference public datasets of epigenomic signatures from eight lung cell lines and primary tissue. We observe that in lung cancer, the mutation burden at enhancers and exons is similar, whereas their corresponding mutation signatures show stark differences. Our results indicate that recurrent mutations in individual enhancers significantly impact the expression of target genes with potential relevance for prognosis. We also demonstrate that the genes enriched for mutated enhancers recurrently converge on the regulation of key biological process and pathways.
2023-09-27 | GSE228831 | GEO
Project description:Enhancers are non-coding genomic features that regulate the transcriptional output of their target genes. Their dysregulation has been associated with various diseases including cancer. However, identification and characterisation of non-coding mutations that are relevant for tumorigenesis and prognosis remain a major challenge. Here we present the detection and characterisation of enhancer mutations in a genome-wide analysis of three lung cancer subtypes. We carefully define lung tissue-specific enhancers across the genome by integrating novel experimental data and reference public datasets of epigenomic signatures from eight lung cell lines and primary tissue. We observe that in lung cancer, the mutation burden at enhancers and exons is similar, whereas their corresponding mutation signatures show stark differences. Our results indicate that recurrent mutations in individual enhancers significantly impact the expression of target genes with potential relevance for prognosis. We also demonstrate that the genes enriched for mutated enhancers recurrently converge on the regulation of key biological process and pathways.
2023-09-27 | GSE228830 | GEO
Project description:Enhancers are noncoding regulatory DNA regions that modulate the transcription of target genes, often over large distances along with the genomic sequence. Enhancer alterations have been associated with various pathological conditions, including cancer. However, the identification and characterization of somatic mutations in noncoding regulatory regions with a functional effect on tumorigenesis and prognosis remain a major challenge. Here, we present a strategy for detecting and characterizing enhancer mutations in a genome-wide analysis of patient cohorts, across three lung cancer subtypes. Lung tissue-specific enhancers were defined by integrating experimental data and public epigenomic profiles, and the genome-wide enhancer-target gene regulatory network of lung cells was constructed by integrating chromatin three-dimensional architecture data. Lung cancers possessed a similar mutation burden at tissue-specific enhancers and exons but with differences in their mutation signatures. Functionally relevant alterations were prioritized on the basis of the pathway-level integration of the effect of a mutation and the frequency of mutations on individual enhancers. The genes enriched for mutated enhancers converged on the regulation of key biological processes and pathways relevant to tumor biology. Recurrent mutations in individual enhancers also affected the expression of target genes, with potential relevance for patient prognosis. Together, these findings show that noncoding regulatory mutations have a potential relevance for cancer pathogenesis and can be exploited for patient classification.SignificanceMapping enhancer-target gene regulatory interactions and analyzing enhancer mutations at the level of their target genes and pathways reveal convergence of recurrent enhancer mutations on biological processes involved in tumorigenesis and prognosis.
| S-EPMC10758689 | biostudies-literature
Project description:Enhancer somatic mutations with functional impact in lung cancers identified by leveraging the tissue-specific enhancer-target genes regulatory network
| PRJNA951701 | ENA
Project description:Enhancer somatic mutations with functional impact in lung cancers identified by leveraging the tissue-specific enhancer-target genes regulatory network [ChIP-seq]
| PRJNA951706 | ENA
Project description:Enhancer somatic mutations with functional impact in lung cancers identified by leveraging the tissue-specific enhancer-target genes regulatory network [ATAC-seq]
| PRJNA951707 | ENA
Project description:Recent technological advances in sequencing have flooded the field of cancer research with knowledge about somatic mutations for many different cancer types. Most cancer genomics studies focus on mutations that alter the amino acid sequence, ignoring the potential impact of synonymous mutations. However, accumulating experimental evidence has demonstrated clear consequences for gene function, leading to a widespread recognition of the functional role of synonymous mutations and their causal connection to various diseases. Here, we review the evidence supporting the direct impact of synonymous mutations on gene function via gene splicing; mRNA stability, folding, and translation; protein folding; and miRNA-based regulation of expression. These results highlight the functional contribution of synonymous mutations to oncogenesis and the need to further investigate their detection and prioritization for experimental assessment.
| S-EPMC4834044 | biostudies-literature
Project description:A number of large-scale cancer somatic genome sequencing projects are now identifying genetic alterations in cancers. Evaluation of the effects of these mutations is essential for understanding their contribution to tumorigenesis. We have used SNPs3D, a software suite originally developed for analyzing nonsynonymous germ-line variants, to identify single-base mutations with a high impact on protein structure and function. Two machine learning methods are used: one identifying mutations that destabilize protein three-dimensional structure and the other utilizing sequence conservation and detecting all types of effects on in vivo protein function. Incorporation of detailed structure information into the analysis allows detailed interpretation of the functional effects of mutations in specific cases. Data from a set of breast and colorectal tumors were analyzed. In known cancer genes, mutations approaching 100% of mutations are found to impact protein function, supporting the view that these methods are appropriate for identifying driver mutations. Overall, 50-60% of all somatic missense mutations are predicted to have a high impact on structural stability or to more generally affect the function of the corresponding proteins. This value is similar to the fraction of all possible missense mutations that have a high impact and is much higher than the corresponding one for human population single-nucleotide polymorphisms, at about 30%. The majority of mutations in tumor suppressors destabilize protein structure, while mutations in oncogenes operate in more varied ways, including destabilization of less active conformational states. The set of high-impact mutations encompasses the possible drivers.
| S-EPMC4177034 | biostudies-literature
Project description:Serine/Threonine Kinase 11 (STK11) encodes an important tumor suppressor that is frequently mutated in lung adenocarcinoma. Clinical studies have shown that mutations in STK11 resulting in loss of function correlate with resistance to anti-PD-1 monoclonal antibody therapy in KRAS-driven non-small cell lung cancer (NSCLC), but the molecular mechanisms responsible remain unclear. Despite this uncertainty, STK11 functional status is emerging as a reliable biomarker for predicting non-response to anti-PD-1 therapy in NSCLC patients. The clinical utility of this biomarker ultimately depends upon accurate classification of STK11 variants. For nonsense variants occurring early in the STK11 coding region, this assessment is straightforward. However, rigorously demonstrating the functional impact of missense variants remains an unmet challenge. Here we present data characterizing four STK11 splice-site variants by analyzing tumor mRNA, and 28 STK11 missense variants using an in vitro kinase assay combined with a cell-based p53-dependent luciferase reporter assay. The variants we report were identified in primary human NSCLC biopsies in collaboration with the University of Vermont Genomic Medicine group. Additionally, we compare our experimental results with data from 22 in silico predictive algorithms. Our work highlights the power, utility and necessity of functional variant assessment and will aid STK11 variant curation, provide a platform to assess novel STK11 variants and help guide anti-PD-1 therapy utilization in KRAS-driven NSCLCs.
| S-EPMC8727739 | biostudies-literature
Project description:BackgroundMalignant transformation requires the interaction of cancer cells with their microenvironment, including infiltrating leukocytes. However, somatic mutational studies have focused on alterations in cancer cells, assuming that the microenvironment is genetically normal. Because we hypothesized that this might not be a valid assumption, we performed exome sequencing and targeted sequencing to investigate for the presence of pathogenic mutations in tumor-associated leukocytes in breast cancers.MethodsWe used targeted sequencing and exome sequencing to evaluate the presence of mutations in sorted tumor-infiltrating CD45-positive cells from primary untreated breast cancers. We used high-depth sequencing to determine the presence/absence of the mutations we identified in breast cancer-infiltrating leukocytes in purified tumor cells and in circulating blood cells.ResultsCapture-based sequencing of 15 paired tumor-infiltrating leukocytes and matched germline DNA identified variants in known cancer genes in all 15 primary breast cancer patients in our cohort. We validated the presence of mutations identified by targeted sequencing in infiltrating leukocytes through orthogonal exome sequencing. Ten patients harbored alterations previously reported as somatically acquired variants, including in known leukemia genes (DNTM3A, TET2, and BCOR). One of the mutations observed in the tumor-infiltrating leukocytes was also detected in the circulating leukocytes of the same patients at a lower allele frequency than observed in the tumor-infiltrating cells.ConclusionsHere we show that somatic mutations, including mutations in known cancer genes, are present in the leukocytes infiltrating a subset of primary breast cancers. This observation allows for the possibility that the cancer cells interact with mutant infiltrating leukocytes, which has many potential clinical implications.
| S-EPMC5515194 | biostudies-literature