scholarly journals Mutational analysis of driver genes with tumor suppressive and oncogenic roles in gastric cancer

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3585 ◽  
Author(s):  
Tianfang Wang ◽  
Yining Liu ◽  
Min Zhao
Keyword(s):  
Gastric Cancer ◽  
Cancer Progression ◽  
Complex Disease ◽  
Mutational Analysis ◽  
Driver Mutations ◽  
Driver Genes ◽  
Protein Coding ◽  
Mirna Genes ◽  
Genetic Mechanisms ◽  
New Treatment

Gastric cancer (GC) is a complex disease with heterogeneous genetic mechanisms. Genomic mutational profiling of gastric cancer not only expands our knowledge about cancer progression at a fundamental genetic level, but also could provide guidance on new treatment decisions, currently based on tumor histology. The fact that precise medicine-based treatment is successful in a subset of tumors indicates the need for better identification of clinically related molecular tumor phenotypes, especially with regard to those driver mutations on tumor suppressor genes (TSGs) and oncogenes (ONGs). We surveyed 313 TSGs and 160 ONGs associated with 48 protein coding and 19 miRNA genes with both TSG and ONG roles. Using public cancer mutational profiles, we confirmed the dual roles of CDKN1A and CDKN1B. In addition to the widely recognized alterations, we identified another 82 frequently mutated genes in public gastric cancer cohort. In summary, these driver mutation profiles of individual GC will form the basis of personalized treatment of gastric cancer, leading to substantial therapeutic improvements.

scholarly journals Genome-Wide Characterization of RNA Editing Sites in Primary Gastric Adenocarcinoma through RNA-seq Data Analysis

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Javad Behroozi ◽  
Shirin Shahbazi ◽  
Mohammad Reza Bakhtiarizadeh ◽  
Habibollah Mahmoodzadeh
Keyword(s):  
Gastric Cancer ◽  
Rna Editing ◽  
Gastric Adenocarcinoma ◽  
Cancer Progression ◽  
Variant Calling ◽  
Distinct Pattern ◽  
Rna Seq ◽  
Comprehensive Overview ◽  
Protein Coding ◽  
Cancer Tissues

RNA editing is a posttranscriptional nucleotide modification in humans. Of the various types of RNA editing, the adenosine to inosine substitution is the most widespread in higher eukaryotes, which is mediated by the ADAR family enzymes. Inosine is recognized by the biological machinery as guanosine; therefore, editing could have substantial functional effects throughout the genome. RNA editing could contribute to cancer either by exclusive editing of tumor suppressor/promoting genes or by introducing transcriptomic diversity to promote cancer progression. Here, we provided a comprehensive overview of the RNA editing sites in gastric adenocarcinoma and highlighted some of their possible contributions to gastric cancer. RNA-seq data corresponding to 8 gastric adenocarcinoma and their paired nontumor counterparts were retrieved from the GEO database. After preprocessing and variant calling steps, a stringent filtering pipeline was employed to distinguish potential RNA editing sites from SNPs. The identified potential editing sites were annotated and compared with those in the DARNED database. Totally, 12362 high-confidence adenosine to inosine RNA editing sites were detected across all samples. Of these, 12105 and 257 were known and novel editing events, respectively. These editing sites were unevenly distributed across genomic regions, and nearly half of them were located in 3 ′ UTR. Our results revealed that 4868 editing sites were common in both normal and cancer tissues. From the remaining sites, 3985 and 3509 were exclusive to normal and cancer tissues, respectively. Further analysis revealed a significant number of differentially edited events among these sites, which were located in protein coding genes and microRNAs. Given the distinct pattern of RNA editing in gastric adenocarcinoma and adjacent normal tissue, edited sites have the potential to serve as the diagnostic biomarkers and therapeutic targets in gastric cancer.

An in silico model of LINE-1-mediated neoplastic evolution

2020 ◽  
Vol 36 (14) ◽  
pp. 4144-4153
Author(s):  
Jack LeBien ◽  
Gerald McCollam ◽  
Joel Atallah
Keyword(s):  
Population Dynamics ◽  
Cancer Progression ◽  
Sequence Data ◽  
Human Cancer ◽  
Lesion Size ◽  
Supplementary Information ◽  
Driver Genes ◽  
Protein Coding ◽  
Somatic Evolution ◽  
Cancer Types

Abstract Motivation Recent research has uncovered roles for transposable elements (TEs) in multiple evolutionary processes, ranging from somatic evolution in cancer to putatively adaptive germline evolution across species. Most models of TE population dynamics, however, have not incorporated actual genome sequence data. The effect of site integration preferences of specific TEs on evolutionary outcomes and the effects of different selection regimes on TE dynamics in a specific genome are unknown. We present a stochastic model of LINE-1 (L1) transposition in human cancer. This system was chosen because the transposition of L1 elements is well understood, the population dynamics of cancer tumors has been modeled extensively, and the role of L1 elements in cancer progression has garnered interest in recent years. Results Our model predicts that L1 retrotransposition (RT) can play either advantageous or deleterious roles in tumor progression, depending on the initial lesion size, L1 insertion rate and tumor driver genes. Small changes in the RT rate or set of driver tumor-suppressor genes (TSGs) were observed to alter the dynamics of tumorigenesis. We found high variation in the density of L1 target sites across human protein-coding genes. We also present an analysis, across three cancer types, of the frequency of homozygous TSG disruption in wild-type hosts compared to those with an inherited driver allele. Availability and implementation Source code is available at https://github.com/atallah-lab/neoplastic-evolution. Contact [email protected] Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Comprehensive Characterization of RNA Editing in Primary Gastric Adenocarcinoma through RNA-seq Data Analysis

2020 ◽  
Author(s):  
Javad Behroozi ◽  
Shirin Shahbazi ◽  
Mohammad Reza Bakhtiarizadeh ◽  
Habibollah Mahmoodzadeh
Keyword(s):  
Gastric Cancer ◽  
Rna Editing ◽  
Gastric Adenocarcinoma ◽  
Cancer Progression ◽  
Variant Calling ◽  
Distinct Pattern ◽  
Rna Seq ◽  
Comprehensive Overview ◽  
Protein Coding ◽  
Genomic Regions

Abstract RNA editing is a post-transcriptional nucleotide modification in humans. Of the various types of RNA editing, the adenosine to inosine substitution is the most widespread in higher eukaryotes, which is mediated by ADAR family enzyme. Inosine is recognized by the biological machineries as guanosine, therefore, editing can potentially rendering substantial functional effects throughout the genome, depending on where it located. RNA editing could contribute to cancer by either exclusive editing of tumor suppressor/promoting genes or by introducing transcriptomic diversity to promote cancer progression. Here, we provided a comprehensive overview of the RNA editing sites in gastric adenocarcinoma and highlighted some of their possible contributions to gastric cancer. RNA-seq data corresponding to 8 gastric adenocarcinoma and their paired non-tumor counterparts were retrieved from GEO database. After pre-possessing and variant calling steps, a stringent filtering pipeline was employed to distinguish potential RNA editing sites from SNPs. The identified potential editing sites were annotated and compared with those in DARNED database. Totally, 12362 high-confidence adenosine to inosine RNA editing sites were detected across all samples. Of these, 12105 and 257 were known and novel editing events, respectively. These editing sites were unevenly distributed across genomic regions, nearly half of them were located in 3´UTR. Indeed, 4868, 3985 and 3509 editing sites were found to be common in both tissue, normal specific and cancer specific, respectively. Further analysis revealed significant number of differentially edited events among these sites, which were located in protein coding genes and microRNAs. Given the distinct pattern of RNA editing in gastric adenocarcinoma and adjacent normal tissue, edited sites have the potential to serve as biomarkers and therapeutic targets in gastric cancer diagnose, management and treatment.

scholarly journals MicroRNAs: Diverse Mechanisms of Action and Their Potential Applications as Cancer Epi-Therapeutics

Biomolecules ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 1285
Author(s):  
Anna Sadakierska-Chudy
Keyword(s):  
Tumor Suppressor ◽  
Cancer Progression ◽  
Therapeutic Potential ◽  
Translation Regulation ◽  
Gene Promoters ◽  
Protein Coding ◽  
Mirna Genes ◽  
Potential Applications

Usually, miRNAs function post-transcriptionally, by base-pairing with the 3′UTR of target mRNAs, repressing protein synthesis in the cytoplasm. Furthermore, other regions including gene promoters, as well as coding and 5′UTR regions of mRNAs are able to interact with miRNAs. In recent years, miRNAs have emerged as important regulators of both translational and transcriptional programs. The expression of miRNA genes, similar to protein-coding genes, can be epigenetically regulated, in turn miRNA molecules (named epi-miRs) are able to regulate epigenetic enzymatic machinery. The most recent line of evidence indicates that miRNAs can influence physiological processes, such as embryonic development, cell proliferation, differentiation, and apoptosis as well as pathological processes (e.g., tumorigenesis) through epigenetic mechanisms. Some tumor types show repression of tumor-suppressor epi-miRs resulting in cancer progression and metastasis, hence these molecules have become novel therapeutic targets in the last few years. This review provides information about miRNAs involvement in the various levels of transcription and translation regulation, as well as discusses therapeutic potential of tumor-suppressor epi-miRs used in in vitro and in vivo anti-cancer therapy.

scholarly journals Mutational Analysis of Field Cancerization in Bladder Cancer

2020 ◽  
Vol 6 (3) ◽  
pp. 253-264 ◽  
Author(s):  
Trine Strandgaard ◽  
Iver Nordentoft ◽  
Philippe Lamy ◽  
Emil Christensen ◽  
Mathilde Borg Houlberg Thomsen ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Normal Tissue ◽  
Mutational Analysis ◽  
Read Depth ◽  
Field Cancerization ◽  
Driver Mutations ◽  
Driver Genes ◽  
Bladder Tissue ◽  
Cancer Driver ◽  
Multifocal Disease

BACKGROUND: Morphologically normal tissue, adjacent to tumors, contains multiple molecular changes, the so-called field cancerization. The multifocal and recurrent nature of bladder cancer has been hypothesized to originate from this. However, further studies are required to explore the mutational composition of normal tissue adjacent to tumors. OBJECTIVE: To analyze field cancerization in bladder cancer patients using a non-tumor guided approach. METHODS: We investigated the mutational landscape of normal appearing urothelium and paired bladder tumors from four patients by applying deep-targeted sequencing. RESULTS: Sequencing of 509 cancer driver genes revealed the presence of 2– 13 mutations exclusively localized in normal tissue (average target read depth 634×). Furthermore, 6– 13 mutations were shared between tumor and normal samples and 8– 75 mutations were exclusively detected in tumor samples. More mutations were observed in normal samples from patients with multifocal disease compared to patients with unifocal disease. Mutations in normal samples had lower variant allele fractions (VAF) compared to tumor mutations (p < 2.2*10–16). Furthermore, significant differences in the type of nucleotide changes between tumor, normal and shared mutations (p = 2.2*10–5) were observed, and mutations in APOBEC context were observed primarily among tumor mutations (p = 0.02). No differences in functional impact between normal, shared and tumor mutations were observed (p = 0.61). CONCLUSION: Overall, these findings support the presence of more than one field in the bladder, and document non-tumor specific driver mutations to be present in normal appearing bladder tissue.

scholarly journals Early and multiple origins of metastatic lineages within primary tumors

2016 ◽  
Vol 113 (8) ◽  
pp. 2140-2145 ◽  
Author(s):  
Zi-Ming Zhao ◽  
Bixiao Zhao ◽  
Yalai Bai ◽  
Atila Iamarino ◽  
Stephen G. Gaffney ◽  
...  
Keyword(s):  
Cancer Progression ◽  
Cancer Biology ◽  
Tumor Development ◽  
Evolutionary Process ◽  
Driver Mutations ◽  
Cancer Evolution ◽  
Driver Genes ◽  
Genetic Changes ◽  
Primary Tumors ◽  
Multiple Origins

Many aspects of the evolutionary process of tumorigenesis that are fundamental to cancer biology and targeted treatment have been challenging to reveal, such as the divergence times and genetic clonality of metastatic lineages. To address these challenges, we performed tumor phylogenetics using molecular evolutionary models, reconstructed ancestral states of somatic mutations, and inferred cancer chronograms to yield three conclusions. First, in contrast to a linear model of cancer progression, metastases can originate from divergent lineages within primary tumors. Evolved genetic changes in cancer lineages likely affect only the proclivity toward metastasis. Single genetic changes are unlikely to be necessary or sufficient for metastasis. Second, metastatic lineages can arise early in tumor development, sometimes long before diagnosis. The early genetic divergence of some metastatic lineages directs attention toward research on driver genes that are mutated early in cancer evolution. Last, the temporal order of occurrence of driver mutations can be inferred from phylogenetic analysis of cancer chronograms, guiding development of targeted therapeutics effective against primary tumors and metastases.

scholarly journals Mutational likeliness and entropy help to identify driver mutations and their functional role in cancer

2018 ◽  
Author(s):  
Giorgio Mattiuz ◽  
Salvatore Di Giorgio ◽  
Lorenzo Tofani ◽  
Antonio Frandi ◽  
Francesco Donati ◽  
...  
Keyword(s):  
Cancer Progression ◽  
Somatic Mutations ◽  
Driver Mutations ◽  
Cancer Evolution ◽  
Loss Of Function ◽  
Driver Genes ◽  
Cancer Driver ◽  
Cancer Genomes ◽  
Passenger Mutations ◽  
Mutational Processes

AbstractAlterations in cancer genomes originate from mutational processes taking place throughout oncogenesis and cancer progression. We show that likeliness and entropy are two properties of somatic mutations crucial in cancer evolution, as cancer-driver mutations stand out, with respect to both of these properties, as being distinct from the bulk of passenger mutations. Our analysis can identify novel cancer driver genes and differentiate between gain and loss of function mutations.

scholarly journals Unique genomic features and deeply-conserved functions of long non-coding RNAs in the Cancer LncRNA Census (CLC)

2017 ◽  
Author(s):  
Joana Carlevaro-Fita ◽  
Andrés Lanzós ◽  
Lars Feuerbach ◽  
Chen Hong ◽  
David Mas-Ponte ◽  
...  
Keyword(s):  
Cancer Progression ◽  
Cancer Genomics ◽  
De Novo ◽  
Cancer Type ◽  
Cancer Genes ◽  
Driver Genes ◽  
Protein Coding ◽  
Evidence Type ◽  
Non Coding Rnas ◽  
Functional Screens

AbstractLong non-coding RNAs (lncRNAs) that drive tumorigenesis are a growing focus of cancer genomics studies. To facilitate further discovery, we have created the “Cancer LncRNA Census” (CLC), a manually-curated and strictly-defined compilation of lncRNAs with causative roles in cancer. CLC has two principle applications: first, as a resource for training and benchmarking de novo identification methods; and second, as a dataset for studying the fundamental properties of these genes.CLC Version 1 comprises 122 lncRNAs implicated in 29 distinct cancers. LncRNAs are included based on functional or genetic evidence for causative roles in cancer progression. All belong to the GENCODE reference annotation, to enable integration across projects and datasets. For each entry, the evidence type, biological activity (oncogene or tumour suppressor), source reference and cancer type are recorded. Supporting its usefulness, CLC genes are significantly enriched amongst de novo predicted driver genes from PCAWG. CLC genes are distinguished from other lncRNAs by a series of features consistent with biological function, including gene length, high expression and sequence conservation of both exons and promoters. We identify a trend for CLC genes to be co-localised with known protein-coding cancer genes along the human genome. Finally, by integrating data from transposon-mutagenesis functional screens, we show that mouse orthologues of CLC genes tend also to be cancer genes.Thus CLC represents a valuable resource for research into long non-coding RNAs in cancer. Their evolutionary and genomic properties have implications for understanding disease mechanisms and point to conserved functions across ~80 million years of evolution.

scholarly journals Computational Approaches to Prioritize Cancer Driver Missense Mutations

2018 ◽  
Vol 19 (7) ◽  
pp. 2113 ◽  
Author(s):  
Feiyang Zhao ◽  
Lei Zheng ◽  
Alexander Goncearenco ◽  
Anna Panchenko ◽  
Minghui Li
Keyword(s):  
Cancer Progression ◽  
Conformational Changes ◽  
Molecular Mechanisms ◽  
Complex Disease ◽  
Rapid Development ◽  
Genomic Data ◽  
Genetic Alterations ◽  
Driver Mutations ◽  
Missense Mutations ◽  
Computational Approaches

Cancer is a complex disease that is driven by genetic alterations. There has been a rapid development of genome-wide techniques during the last decade along with a significant lowering of the cost of gene sequencing, which has generated widely available cancer genomic data. However, the interpretation of genomic data and the prediction of the association of genetic variations with cancer and disease phenotypes still requires significant improvement. Missense mutations, which can render proteins non-functional and provide a selective growth advantage to cancer cells, are frequently detected in cancer. Effects caused by missense mutations can be pinpointed by in silico modeling, which makes it more feasible to find a treatment and reverse the effect. Specific human phenotypes are largely determined by stability, activity, and interactions between proteins and other biomolecules that work together to execute specific cellular functions. Therefore, analysis of missense mutations’ effects on proteins and their complexes would provide important clues for identifying functionally important missense mutations, understanding the molecular mechanisms of cancer progression and facilitating treatment and prevention. Herein, we summarize the major computational approaches and tools that provide not only the classification of missense mutations as cancer drivers or passengers but also the molecular mechanisms induced by driver mutations. This review focuses on the discussion of annotation and prediction methods based on structural and biophysical data, analysis of somatic cancer missense mutations in 3D structures of proteins and their complexes, predictions of the effects of missense mutations on protein stability, protein-protein and protein-nucleic acid interactions, and assessment of conformational changes in protein conformations induced by mutations.

scholarly journals Germline and somatic genetic variants in the p53 pathway interact to affect cancer risk, progression and drug response

2019 ◽  
Author(s):  
Ping Zhang ◽  
Isaac Kitchen-Smith ◽  
Lingyun Xiong ◽  
Giovanni Stracquadanio ◽  
Katherine Brown ◽  
...  
Keyword(s):  
Treatment Response ◽  
Cancer Progression ◽  
Genetic Variants ◽  
Cancer Susceptibility ◽  
Driver Mutations ◽  
Precision Oncology ◽  
Driver Genes ◽  
P53 Pathway ◽  
Cancer Driver ◽  
Cancer Management

AbstractInsights into oncogenesis derived from cancer susceptibility loci could facilitate better cancer management and treatment through precision oncology. However, therapeutic applications have thus far been limited by our current lack of understanding regarding both their interactions with somatic cancer driver mutations and their influence on tumorigenesis. Here, by integrating germline datasets relating to cancer susceptibility with tumour data capturing somatically-acquired genetic variation, we provide evidence that single nucleotide polymorphism (SNPs) and somatic mutations in the p53 tumor suppressor pathway can interact to influence cancer development, progression and treatment response. We go on to provide human genetic evidence of a tumor-promoting role for the pro-survival activities of p53, which supports the development of more effective therapy combinations through their inhibition in cancers retaining wild-type p53.SignificanceWe describe significant interactions between heritable and somatic genetic variants in the p53 pathway that affect cancer susceptibility, progression and treatment response. Our results offer evidence of how cancer susceptibility SNPs can interact with cancer driver genes to affect cancer progression and identify novel therapeutic targets.

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