Somatic Mutations in miRNA Genes in Lung Cancer—Potential Functional Consequences of Non-Coding Sequence Variants

A growing body of evidence indicates that miRNAs may either drive or suppress oncogenesis. However, little is known about somatic mutations in miRNA genes. To determine the frequency and potential consequences of miRNA gene mutations, we analyzed whole exome sequencing datasets of 569 lung adenocarcinoma (LUAD) and 597 lung squamous cell carcinoma (LUSC) samples generated in The Cancer Genome Atlas (TCGA) project. Altogether, we identified 1091 somatic sequence variants affecting 522 different miRNA genes and showed that half of all cancers had at least one such somatic variant/mutation. These sequence variants occurred in most crucial parts of miRNA precursors, including mature miRNA and seed sequences. Due to our findings, we hypothesize that seed mutations may affect miRNA:target interactions, drastically changing the pool of predicted targets. Mutations may also affect miRNA biogenesis by changing the structure of miRNA precursors, DROSHA and DICER cleavage sites, and regulatory sequence/structure motifs. We identified 10 significantly overmutated hotspot miRNA genes, including the miR-379 gene in LUAD enriched in mutations in the mature miRNA and regulatory sequences. The occurrence of mutations in the hotspot miRNA genes was also shown experimentally. We present a comprehensive analysis of somatic variants in miRNA genes and show that some of these genes are mutational hotspots, suggesting their potential role in cancer.

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Somatic mutations in miRNA genes in lung cancer – potential functional consequences of non-coding sequence variants

10.1101/579011 ◽

2019 ◽

Cited By ~ 1

Author(s):

Paulina Galka-Marciniak ◽

Martyna Olga Urbanek-Trzeciak ◽

Paulina Maria Nawrocka ◽

Agata Dutkiewicz ◽

Maciej Giefing ◽

...

Keyword(s):

Somatic Mutations ◽

Mirna Gene ◽

Gene Mutations ◽

Lung Squamous Cell Carcinoma ◽

Mirna Biogenesis ◽

Regulatory Sequence ◽

Regulatory Sequences ◽

Mirna Genes ◽

Mutational Hotspots ◽

Dicer Cleavage

AbstractA growing body of evidence indicates that miRNAs may either drive or suppress oncogenesis. However, little is known about somatic mutations in miRNA genes. To determine the frequency and potential consequences of miRNA gene mutations, we analyzed whole exome sequencing datasets of ∼500 lung adenocarcinoma (LUAD) and ∼500 lung squamous cell carcinoma (LUSC) samples generated in the TCGA. Altogether, we identified >1000 mutations affecting ∼500 different miRNA genes and showed that half of all cancers had at least one such mutation. Mutations occurred in most crucial parts of miRNA precursors, including mature miRNA and seed sequences. We showed that seed mutations strongly affected miRNA:target interactions, drastically changing the pool of predicted targets. Mutations may also affect miRNA biogenesis by changing the structure of miRNA precursors, DROSHA and DICER cleavage sites, and regulatory sequence/structure motifs. We identified 10 significantly overmutated hotspot miRNA genes, including themiR-379gene in LUAD enriched in mutations in the mature miRNA and regulatory sequences. The occurrence of mutations in the hotspot miRNA genes was also shown experimentally. We present a comprehensive analysis of somatic mutations in miRNA genes and show that some of these genes are mutational hotspots, suggesting their potential role in cancer.

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Evaluation of a regularly updated knowledge base for curation of somatic mutations detected in whole exomes of melanoma and lung, colorectal, and breast cancers.

Journal of Clinical Oncology ◽

10.1200/jco.2020.38.15_suppl.e14072 ◽

2020 ◽

Vol 38 (15_suppl) ◽

pp. e14072-e14072

Author(s):

Stephanie J. Yaung ◽

Jian Li ◽

Adeline Pek ◽

Lili Niu ◽

John F. Palma ◽

...

Keyword(s):

Knowledge Base ◽

Somatic Mutations ◽

Lung Squamous Cell Carcinoma ◽

The United States ◽

Geographic Region ◽

The Cancer Genome Atlas ◽

Breast Cancers ◽

Single Nucleotide Variants ◽

Medical Guidelines ◽

Tier I

e14072 Background: Evolving medical guidelines and complex multi-variant data from next-generation sequencing (NGS) testing of cancer samples make routine clinical interpretation of somatic variants challenging. We assessed the ability of NAVIFY(R) Mutation Profiler*, a CE-IVD somatic variant interpretation tool, to yield accurate time- and geography-specific clinical content on 2511 samples from The Cancer Genome Atlas (TCGA) across six solid tumor types. Methods: Whole exomes from lung adenocarcinoma (n = 469), lung squamous cell carcinoma (n = 325), colon adenocarcinoma (n = 368), rectum adenocarcinoma (n = 149), breast invasive carcinoma (n = 806), and skin cutaneous melanoma (n = 394) cases were analyzed. We utilized TCGA data from the Multi-Center Mutation Calling in Multiple Cancers (MC3) project to obtain consensus calling results of single nucleotide variants and indels. The open-access Mutation Annotation Format (MAF) file (v0.2.8) that stores variant calls was lifted to human reference genome GRCh38 and converted to individual Variant Call Format (VCF) files per case. VCF files were uploaded to NAVIFY Mutation Profiler to interpret actionable mutations according to a highly curated and up-to-date knowledge base (Roche Content v2.13.0 released December 6, 2019). We further assessed the accuracy of interpreting co-occurrences of actionable mutations. Results: Over 1.24 million somatic mutations across 20,590 genes were assessed with NAVIFY Mutation Profiler, which reported tier classifications of variants based on consensus recommendations from AMP, ASCO, CAP, and ACMG. 86% of cases had variants of strong (Tier I-A or I-B) or potential (Tier II-C or II-D) clinical significance; 56% of these cases had Tier I classifications, supported by robust clinical evidence. Potentially actionable variant-variant interactions were found in 14% of cases. The tool also identified appropriate tier classifications by geographic region in accordance with local medical guidelines. Conclusions: To benchmark against other tools, we utilized available exome data from TCGA MC3 to assess NAVIFY Mutation Profiler. While this study likely underestimates the fraction of cases with actionable mutations, given that copy number alterations or rearrangements are also present in TCGA samples, we found a higher yield of potentially actionable annotation than other published methods. * This product has not been evaluated by the Food and Drug Administration and is not commercially available in the United States.

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HEDGEHOG/GLI Modulates the PRR11-SKA2 Bidirectional Transcription Unit in Lung Squamous Cell Carcinomas

Genes ◽

10.3390/genes12010120 ◽

2021 ◽

Vol 12 (1) ◽

pp. 120

Author(s):

Yiyun Sun ◽

Dandan Xu ◽

Chundong Zhang ◽

Yitao Wang ◽

Lian Zhang ◽

...

Keyword(s):

Rna Sequencing ◽

Squamous Cell ◽

Gene Pair ◽

Gene List ◽

Ectopic Expression ◽

Lung Squamous Cell Carcinoma ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Sequencing Data ◽

Gene Set

We previously demonstrated that proline-rich protein 11 (PRR11) and spindle and kinetochore associated 2 (SKA2) constituted a head-to-head gene pair driven by a prototypical bidirectional promoter. This gene pair synergistically promoted the development of non-small cell lung cancer. However, the signaling pathways leading to the ectopic expression of this gene pair remains obscure. In the present study, we first analyzed the lung squamous cell carcinoma (LSCC) relevant RNA sequencing data from The Cancer Genome Atlas (TCGA) database using the correlation analysis of gene expression and gene set enrichment analysis (GSEA), which revealed that the PRR11-SKA2 correlated gene list highly resembled the Hedgehog (Hh) pathway activation-related gene set. Subsequently, GLI1/2 inhibitor GANT-61 or GLI1/2-siRNA inhibited the Hh pathway of LSCC cells, concomitantly decreasing the expression levels of PRR11 and SKA2. Furthermore, the mRNA expression profile of LSCC cells treated with GANT-61 was detected using RNA sequencing, displaying 397 differentially expressed genes (203 upregulated genes and 194 downregulated genes). Out of them, one gene set, including BIRC5, NCAPG, CCNB2, and BUB1, was involved in cell division and interacted with both PRR11 and SKA2. These genes were verified as the downregulated genes via RT-PCR and their high expression significantly correlated with the shorter overall survival of LSCC patients. Taken together, our results indicate that GLI1/2 mediates the expression of the PRR11-SKA2-centric gene set that serves as an unfavorable prognostic indicator for LSCC patients, potentializing new combinatorial diagnostic and therapeutic strategies in LSCC.

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Inactivating Mutations of the IK Gene Weaken Ku80/Ku70-Mediated DNA Repair and Sensitize Endometrial Cancer to Chemotherapy

Cancers ◽

10.3390/cancers13102487 ◽

2021 ◽

Vol 13 (10) ◽

pp. 2487

Author(s):

Chao Gao ◽

Guangxu Jin ◽

Elizabeth Forbes ◽

Lingegowda S. Mangala ◽

Yingmei Wang ◽

...

Keyword(s):

Dna Repair ◽

Endometrial Cancer ◽

Protein Interactions ◽

Somatic Mutations ◽

The Cancer Genome Atlas ◽

Response To Chemotherapy ◽

Tcga Dataset ◽

Inactivating Mutations

IK is a mitotic factor that promotes cell cycle progression. Our previous investigation of 271 endometrial cancer (EC) samples from the Cancer Genome Atlas (TCGA) dataset showed IK somatic mutations were enriched in a cluster of patients with high-grade and high-stage cancers, and this group had longer survival. This study provides insight into how IK somatic mutations contribute to EC pathophysiology. We analyzed the somatic mutational landscape of IK gene in 547 EC patients using expanded TCGA dataset. Co-immunoprecipitation and mass spectrometry were used to identify protein interactions. In vitro and in vivo experiments were used to evaluate IK’s role in EC. The patients with IK-inactivating mutations had longer survival during 10-year follow-up. Frameshift and stop-gain were common mutations and were associated with decreased IK expression. IK knockdown led to enrichment of G2/M phase cells, inactivation of DNA repair signaling mediated by heterodimerization of Ku80 and Ku70, and sensitization of EC cells to cisplatin treatment. IK/Ku80 mutations were accompanied by higher mutation rates and associated with significantly better overall survival. Inactivating mutations of IK gene and loss of IK protein expression were associated with weakened Ku80/Ku70-mediated DNA repair, increased mutation burden, and better response to chemotherapy in patients with EC.

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Mutation Profile of Aggressive Pheochromocytoma and Paraganglioma with Comparison of TCGA Data

Cancers ◽

10.3390/cancers13102389 ◽

2021 ◽

Vol 13 (10) ◽

pp. 2389

Author(s):

Yun Mi Choi ◽

Jinyeong Lim ◽

Min Ji Jeon ◽

Yu-Mi Lee ◽

Tae-Yon Sung ◽

...

Keyword(s):

Somatic Mutations ◽

The Cancer Genome Atlas ◽

Sequencing Analysis ◽

Poor Overall Survival ◽

Sdhb Mutation ◽

Targeted Next Generation Sequencing ◽

Mutation Profile ◽

Next Generation Sequencing Analysis ◽

Number Variation ◽

Frequent Mutations

In pheochromocytoma and paraganglioma (PPGL), germline or somatic mutations in one of the known susceptibility genes are identified in up to 60% patients. However, the peculiar genetic events that drive the aggressive behavior including metastasis in PPGL are poorly understood. We performed targeted next-generation sequencing analysis to characterize the mutation profile in fifteen aggressive PPGL patients and compared accessible data of aggressive PPGLs from The Cancer Genome Atlas (TCGA) with findings of our cohort. A total of 115 germline and 34 somatic variants were identified with a median 0.58 per megabase tumor mutation burden in our cohort. The most frequent mutation was SDHB germline mutation (27%) and the second frequent mutations were somatic mutations for SETD2, NF1, and HRAS (13%, respectively). Patients were subtyped into three categories based on the kind of mutated genes: pseudohypoxia (n = 5), kinase (n = 5), and unknown (n = 5) group. In copy number variation analysis, deletion of chromosome arm 1p harboring SDHB gene was the most frequently observed. In our cohort, SDHB mutation and pseudohypoxia subtype were significantly associated with poor overall survival. In conclusion, subtyping of mutation profile can be helpful in aggressive PPGL patients with heterogeneous prognosis to make relevant follow-up plan and achieve proper treatment.

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UBE2D1 RNA Expression Was an Independent Unfavorable Prognostic Indicator in Lung Adenocarcinoma, but Not in Lung Squamous Cell Carcinoma

Disease Markers ◽

10.1155/2018/4108919 ◽

2018 ◽

Vol 2018 ◽

pp. 1-8 ◽

Cited By ~ 3

Author(s):

Liyan Hou ◽

Yingbo Li ◽

Ying Wang ◽

Dongqiang Xu ◽

Hailing Cui ◽

...

Keyword(s):

Lung Cancer ◽

Squamous Cell Carcinoma ◽

Lung Adenocarcinoma ◽

Cell Carcinoma ◽

Squamous Cell ◽

Survival Data ◽

Lung Squamous Cell Carcinoma ◽

Prognostic Indicator ◽

The Cancer Genome Atlas ◽

Rna Expression

In this study, we investigated the potential prognostic value of ubiquitin-conjugating enzyme E2D1 (UBE2D1) RNA expression in different histological subtypes of non-small-cell lung cancer (NSCLC). A retrospective study was performed by using molecular, clinicopathological, and survival data in the Cancer Genome Atlas (TCGA)—Lung Cancer. Results showed that both lung adenocarcinoma (LUAD) (N=514) and lung squamous cell carcinoma (LUSC) (N=502) tissues had significantly elevated UBE2D1 RNA expression compared to the normal tissues (p<0.001 and p=0.036, respectively). UBE2D1 RNA expression was significantly higher in LUAD than in LUSC tissues. Increased UBE2D1 RNA expression was independently associated with shorter OS (HR: 1.359, 95% CI: 1.031–1.791, p=0.029) and RFS (HR: 1.842, 95% CI: 1.353–2.508, p<0.001) in LUAD patients, but not in LUSC patients. DNA amplification was common in LUAD patients (88/551, 16.0%) and was associated with significantly upregulated UBE2D1 RNA expression. Based on these findings, we infer that UBE2D1 RNA expression might only serve as an independent prognostic indicator of unfavorable OS and RFS in LUAD, but not in LUSC.

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Integrating Genetic and Transcriptomic Data to Reveal Pathogenesis and Prognostic Markers of Pancreatic Adenocarcinoma

Frontiers in Genetics ◽

10.3389/fgene.2021.747270 ◽

2021 ◽

Vol 12 ◽

Author(s):

Kaisong Bai ◽

Tong Zhao ◽

Yilong Li ◽

Xinjian Li ◽

Zhantian Zhang ◽

...

Keyword(s):

Gene Expression ◽

Pancreatic Adenocarcinoma ◽

Somatic Mutation ◽

Somatic Mutations ◽

Prognostic Markers ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Genomic Variation ◽

The Cancer Genome Atlas ◽

Driver Genes

Pancreatic adenocarcinoma (PAAD) is one of the deadliest malignancies and mortality for PAAD have remained increasing under the conditions of substantial improvements in mortality for other major cancers. Although multiple of studies exists on PAAD, few studies have dissected the oncogenic mechanisms of PAAD based on genomic variation. In this study, we integrated somatic mutation data and gene expression profiles obtained by high-throughput sequencing to characterize the pathogenesis of PAAD. The mutation profile containing 182 samples with 25,470 somatic mutations was obtained from The Cancer Genome Atlas (TCGA). The mutation landscape was generated and somatic mutations in PAAD were found to have preference for mutation location. The combination of mutation matrix and gene expression profiles identified 31 driver genes that were closely associated with tumor cell invasion and apoptosis. Co-expression networks were constructed based on 461 genes significantly associated with driver genes and the hub gene FAM133A in the network was identified to be associated with tumor metastasis. Further, the cascade relationship of somatic mutation-Long non-coding RNA (lncRNA)-microRNA (miRNA) was constructed to reveal a new mechanism for the involvement of mutations in post-transcriptional regulation. We have also identified prognostic markers that are significantly associated with overall survival (OS) of PAAD patients and constructed a risk score model to identify patients’ survival risk. In summary, our study revealed the pathogenic mechanisms and prognostic markers of PAAD providing theoretical support for the development of precision medicine.

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A Statistical Framework for Evolutionary Analysis of Recurrent Somatic Mutations in Cancers

10.1101/2020.04.10.036095 ◽

2020 ◽

Author(s):

Xun Gu

Keyword(s):

Somatic Mutations ◽

Cancer Genomics ◽

Computational Procedure ◽

The Cancer Genome Atlas ◽

Component Model ◽

Evolutionary Analysis ◽

Cancer Genes ◽

Component Mixture ◽

Two Component ◽

Empirical Bayesian Method

AbstractCurrent cancer genomics databases have accumulated millions of somatic mutations that remain to be further explored, faciltating enormous high throuput analyses to explore the underlying mechanisms that may contribute to malignant initiation or progression. In the context of over-dominant passenger mutations (unrelated to cancers), the challenge is to identify somatic mutations that are cancer-driving. Under the notion that carcinogenesis is a form of somatic-cell evolution, we developed a two-component mixture model that enables to accomplish the following analyses. (i) We formulated a quasi-likelihood approach to test whether the two-component model is significantly better than a single-component model, which can be used for new cancer gene predicting. (ii) We implemented an empirical Bayesian method to calculate the posterior probabilities of a site to be cancer-driving for all sites of a gene, which can be used for new driving site predicting. (iii) We developed a computational procedure to calculate the somatic selection intensity at driver sites and passenger sites, respectively, as well as site-specific profiles for all sites. Using these newly-developed methods, we comprehensively analyzed 294 known cancer genes based on The Cancer Genome Atlas (TCGA) database.

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Combination the Gene Expression of Adjacent Normal and Tumor Makes more Robust Gene Signature as Cancer Prognosis Biomarker

10.21203/rs.3.rs-132449/v1 ◽

2020 ◽

Author(s):

Wei Ma ◽

Dandan Li ◽

Changjian Zhang ◽

Ming Xiong ◽

Yuanyuan Qiao

Keyword(s):

Expression Profile ◽

Normal Tissue ◽

Cox Regression ◽

Expression Profiles ◽

Lung Squamous Cell Carcinoma ◽

Enrichment Analysis ◽

Gene Signature ◽

The Cancer Genome Atlas ◽

Cancer Prognosis ◽

Adjacent Normal Tissue

Abstract Purpose: We tried to explore new gene signature via the combination of tumor-derived expression profile and the adjacent normal-derived expression profile to find more robust cancer biomarker. Methods: Log2 transformed ratio of tumor tissue and the adjacent normal tissue (Log2TN) expression, tumor-derived expression, and normal-derived expression were used to do univariate Cox regression in The Cancer Genome Atlas (TCGA) lung squamous cell carcinoma (LUSC) respectively. Then, we used factor analysis and least absolute shrinkage and selection operator Cox (LASSO-Cox) to select gene signature in TCGA LUSC for Log2TN, tumor, and adjacent normal respectively.Results: By comparing Log2TN with tumor and adjacent normal in LUSC, we found that genes derived from Log2TN show more robust (p = 0.006 and p = 0.001) and have lower p-values (p < 0.001). Gene signature selected from Log2TN shows the best generalization in the three GEO datasets even though only tumor-derived expression profiles were available in the three datasets. Enrichment analysis showed that the tumor cells mainly focus on proliferation with losing functional of metabolism.Conclusions: These results indicate that (1) Log2TN could get more robust genes and gene signature than tumor-derived expression profiles used traditionally; (2) the adjacent-normal tissue may also play an important role in the progress and outcome of the tumor.Implications for Cancer Survivors: By combined of tumor-derived expression profile and the adjacent normal-derived expression profile, we could find more robust gene signature than traditionally method. Using these robust gene signatures, robust cancer biomarkers could be constructed and will do great help to improve cancer prognosis.

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Association of mutation signature effectuating processes with mutation hotspots in driver genes and non-coding regions

Nature Communications ◽

10.1038/s41467-021-27792-6 ◽

2022 ◽

Vol 13 (1) ◽

Author(s):

John K. L. Wong ◽

Christian Aichmüller ◽

Markus Schulze ◽

Mario Hlevnjak ◽

Shaymaa Elgaafary ◽

...

Keyword(s):

Somatic Hypermutation ◽

Regulatory Elements ◽

Cancer Genome ◽

The Cancer Genome Atlas ◽

Driver Mutations ◽

Base Substitution ◽

Single Nucleotide Variants ◽

Mutational Signatures ◽

Coding Regions ◽

Mutational Hotspots

AbstractCancer driving mutations are difficult to identify especially in the non-coding part of the genome. Here, we present sigDriver, an algorithm dedicated to call driver mutations. Using 3813 whole-genome sequenced tumors from International Cancer Genome Consortium, The Cancer Genome Atlas Program, and a childhood pan-cancer cohort, we employ mutational signatures based on single-base substitution in the context of tri- and penta-nucleotide motifs for hotspot discovery. Knowledge-based annotations on mutational hotspots reveal enrichment in coding regions and regulatory elements for 6 mutational signatures, including APOBEC and somatic hypermutation signatures. APOBEC activity is associated with 32 hotspots of which 11 are known and 11 are putative regulatory drivers. Somatic single nucleotide variants clusters detected at hypermutation-associated hotspots are distinct from translocation or gene amplifications. Patients carrying APOBEC induced PIK3CA driver mutations show lower occurrence of signature SBS39. In summary, sigDriver uncovers mutational processes associated with known and putative tumor drivers and hotspots particularly in the non-coding regions of the genome.

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