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 Mutated p53 in HGSC—From a Common Mutation to a Target for Therapy

Cancers ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 3465
Author(s):  
Aya Saleh ◽  
Ruth Perets
Keyword(s):  
Cancer Progression ◽  
Target Genes ◽  
P53 Protein ◽  
Genetic Alterations ◽  
Common Mutation ◽  
Missense Mutations ◽  
P53 Expression ◽  
Histologic Subtype ◽  
Tp53 Mutations

Mutations in tumor suppressor gene TP53, encoding for the p53 protein, are the most ubiquitous genetic variation in human ovarian HGSC, the most prevalent and lethal histologic subtype of epithelial ovarian cancer (EOC). The majority of TP53 mutations are missense mutations, leading to loss of tumor suppressive function of p53 and gain of new oncogenic functions. This review presents the clinical relevance of TP53 mutations in HGSC, elaborating on several recently identified upstream regulators of mutant p53 that control its expression and downstream target genes that mediate its roles in the disease. TP53 mutations are the earliest genetic alterations during HGSC pathogenesis, and we summarize current information related to p53 function in the pathogenesis of HGSC. The role of p53 is cell autonomous, and in the interaction between cancer cells and its microenvironment. We discuss the reduction in p53 expression levels in tumor associated fibroblasts that promotes cancer progression, and the role of mutated p53 in the interaction between the tumor and its microenvironment. Lastly, we discuss the potential of TP53 mutations to serve as diagnostic biomarkers and detail some more advanced efforts to use mutated p53 as a therapeutic target in HGSC.

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 Widespread alteration of protein autoinhibition in human cancers

2018 ◽  
Author(s):  
Ashwani Jha ◽  
Jennifer M. Bui ◽  
Dokyun Na ◽  
Jörg Gsponer
Keyword(s):  
Cancer Cells ◽  
Molecular Mechanisms ◽  
Signal Propagation ◽  
Genetic Alterations ◽  
Missense Mutations ◽  
Pathway Activation ◽  
Tumorigenic Potential ◽  
Significant Enrichment ◽  
Cancer Types ◽  
Cancer Drivers

ABSTRACTAutoinhibition is a prevalent allosteric regulatory mechanism in signaling proteins as it prevents spurious pathway activation and primes for signal propagation only under appropriate inputs. Altered functioning of inhibitory allosteric switches underlies the tumorigenic potential of numerous cancer drivers. However, whether protein autoinhibition is altered generically in cancer cells remains elusive. Here, we reveal that cancer-associated missense mutations and fusion breakpoints are found with significant enrichment within inhibitory allosteric switches across all cancer types, which in the case of the fusion breakpoints is specific to cancer and not present in other diseases. Recurrently disrupted or mutated allosteric switches identify established and new cancer drivers. Cancer-specific mutations in allosteric switches are associated with distinct changes in signaling, and suggest molecular mechanisms for altered protein regulation, which in the case of ASK1, DAPK2 and EIF4G1 were supported by biophysical simulations. Our results demonstrate that autoinhibition-modulating genetic alterations are positively selected for by cancer cells, and that their study provides valuable insights into molecular mechanisms of cancer misregulation.

scholarly journals Dissimilar Appearances Are Deceptive–Common microRNAs and Therapeutic Strategies in Liver Cancer and Melanoma

Cells ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 114
Author(s):  
Lisa Linck-Paulus ◽  
Claus Hellerbrand ◽  
Anja K. Bosserhoff ◽  
Peter Dietrich
Keyword(s):  
Cancer Progression ◽  
Molecular Mechanisms ◽  
Current Knowledge ◽  
Therapeutic Targets ◽  
Genetic Alterations ◽  
Therapeutic Strategies ◽  
The Future ◽  
Associated Proteins ◽  
Cancer Types ◽  
Novel Therapeutic Strategies

In this review, we summarize the current knowledge on miRNAs as therapeutic targets in two cancer types that were frequently described to be driven by miRNAs—melanoma and hepatocellular carcinoma (HCC). By focusing on common microRNAs and associated pathways in these—at first sight—dissimilar cancer types, we aim at revealing similar molecular mechanisms that are evolved in microRNA-biology to drive cancer progression. Thereby, we also want to outlay potential novel therapeutic strategies. After providing a brief introduction to general miRNA biology and basic information about HCC and melanoma, this review depicts prominent examples of potent oncomiRs and tumor-suppressor miRNAs, which have been proven to drive diverse cancer types including melanoma and HCC. To develop and apply miRNA-based therapeutics for cancer treatment in the future, it is essential to understand how miRNA dysregulation evolves during malignant transformation. Therefore, we highlight important aspects such as genetic alterations, miRNA editing and transcriptional regulation based on concrete examples. Furthermore, we expand our illustration by focusing on miRNA-associated proteins as well as other regulators of miRNAs which could also provide therapeutic targets. Finally, design and delivery strategies of miRNA-associated therapeutic agents as well as potential drawbacks are discussed to address the question of how miRNAs might contribute to cancer therapy in the future.

scholarly journals Integrative Bayesian Network Analysis of Genomic Data

2014 ◽  
Vol 13s2 ◽  
pp. CIN.S13786 ◽  
Author(s):  
Yang Ni ◽  
Francesco C. Stingo ◽  
Veerabhadran Baladandayuthapani
Keyword(s):  
Bayesian Network ◽  
Cancer Progression ◽  
Rapid Development ◽  
Genomic Data ◽  
Biological Knowledge ◽  
Network Approach ◽  
Computationally Efficient ◽  
Efficient Manner ◽  
New Genes ◽  
Genome Wide

Rapid development of genome-wide profiling technologies has made it possible to conduct integrative analysis on genomic data from multiple platforms. In this study, we develop a novel integrative Bayesian network approach to investigate the relationships between genetic and epigenetic alterations as well as how these mutations affect a patient's clinical outcome. We take a Bayesian network approach that admits a convenient decomposition of the joint distribution into local distributions. Exploiting the prior biological knowledge about regulatory mechanisms, we model each local distribution as linear regressions. This allows us to analyze multi-platform genome-wide data in a computationally efficient manner. We illustrate the performance of our approach through simulation studies. Our methods are motivated by and applied to a multi-platform glioblastoma dataset, from which we reveal several biologically relevant relationships that have been validated in the literature as well as new genes that could potentially be novel biomarkers for cancer progression.

Approaches for the identification of driver mutations in cancer: A tutorial from a computational perspective

2020 ◽  
Vol 18 (03) ◽  
pp. 2050016 ◽  
Author(s):  
Jorge Francisco Cutigi ◽  
Adriane Feijo Evangelista ◽  
Adenilso Simao
Keyword(s):  
Computational Methods ◽  
Complex Disease ◽  
Cancer Genomics ◽  
Genetic Alterations ◽  
Driver Mutations ◽  
Easy Access ◽  
Computational Perspective ◽  
High Level ◽  
Passenger Mutations ◽  
Cancer Bioinformatics

Cancer is a complex disease caused by the accumulation of genetic alterations during the individual’s life. Such alterations are called genetic mutations and can be divided into two groups: (1) Passenger mutations, which are not responsible for cancer and (2) Driver mutations, which are significant for cancer and responsible for its initiation and progression. Cancer cells undergo a large number of mutations, of which most are passengers, and few are drivers. The identification of driver mutations is a key point and one of the biggest challenges in Cancer Genomics. Many computational methods for such a purpose have been developed in Cancer Bioinformatics. Such computational methods are complex and are usually described in a high level of abstraction. This tutorial details some classical computational methods, from a computational perspective, with the transcription in an algorithmic format towards an easy access by researchers.

scholarly journals Genetic Mouse Models as In Vivo Tools for Cholangiocarcinoma Research

Cancers ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 1868 ◽  
Author(s):  
Oihane Erice ◽  
Adrian Vallejo ◽  
Mariano Ponz-Sarvise ◽  
Michael Saborowski ◽  
Arndt Vogel ◽  
...  
Keyword(s):  
Mouse Models ◽  
Molecular Mechanisms ◽  
Complex Disease ◽  
Current Knowledge ◽  
Genetic Alterations ◽  
In Vivo Model ◽  
In Vivo Models ◽  
Dismal Prognosis ◽  
Genetic Mouse Models

Cholangiocarcinoma (CCA) is a genetically and histologically complex disease with a highly dismal prognosis. A deeper understanding of the underlying cellular and molecular mechanisms of human CCA will increase our current knowledge of the disease and expedite the eventual development of novel therapeutic strategies for this fatal cancer. This endeavor is effectively supported by genetic mouse models, which serve as sophisticated tools to systematically investigate CCA pathobiology and treatment response. These in vivo models feature many of the genetic alterations found in humans, recapitulate multiple hallmarks of cholangiocarcinogenesis (encompassing cell transformation, preneoplastic lesions, established tumors and metastatic disease) and provide an ideal experimental setting to study the interplay between tumor cells and the surrounding stroma. This review is intended to serve as a compendium of CCA mouse models, including traditional transgenic models but also genetically flexible approaches based on either the direct introduction of DNA into liver cells or transplantation of pre-malignant cells, and is meant as a resource for CCA researchers to aid in the selection of the most appropriate in vivo model system.

Molecular changes in epidermal growth factor receptor (EGFR) in non-small cell lung cancer (NSCLC) biopsies at time of progression compared to initial biopsy

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. e22066-e22066
Author(s):  
G. Speranza ◽  
V. Cohen ◽  
J. S. Agulnik ◽  
G. Chong ◽  
F. Meilleur ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Progression ◽  
Kinase Inhibitors ◽  
Genetic Alterations ◽  
Egfr Mutations ◽  
Missense Mutations ◽  
Molecular Changes ◽  
Mutational Status ◽  
Exon 19 Deletion ◽  
Exon 19

e22066 Background: EGFR mutations predict sensitivity and clinical outcome to tyrosine kinase inhibitors (TKI) in NSCLC. The two most commonly described mutations are Exon 19 deletion and Exon 21 L858R missense mutations. Genetic alterations over time have been described in other tumour types, but studies assessing EGFR genotypic changes with lung cancer progression are lacking. We sought to compare EGFR mutational status from lung tumors at time of recurrence or progression with the primary tumor. Methods: Using the Jewish General Hospital lung cancer database, of all patients diagnosed with NSCLC since 1999, those with biopsies at two different points in time were identified. All tumour samples were genotyped for EGFR exons 19 and 21 mutations using denaturing high performance liquid chromatography (dHPLC). Results: 29 patients were identified. Data for 12 patients, whose time of recurrence or progression varied between 4 months and 6 years, are available at this time. Of 12 patients, one had EGFR exon 19 mutation at time of diagnosis. One patient who initially displayed no EGFR mutation was found to have an exon 19 deletion at time of recurrence. The one with exon 19 at time of initial diagnosis continued to express exon 19 in the second biopsy. Conclusions: To our knowledge, this is the only study assessing changes in molecular genotype using dHPLC between primary and recurrent or progressive lung cancer biopsy specimens. Although sample size is small, it is evident that changes in EGFR mutational status can occur. Further prospective studies are required to determine how commonly molecular changes occur. No significant financial relationships to disclose.

scholarly journals Identification of Altered Genes in Gallbladder Cancer as Potential Driver Mutations for Diagnostic and Prognostic Purposes: A Computational Approach

2020 ◽  
Vol 19 ◽  
pp. 117693512092215
Author(s):  
Vívian D’Afonseca ◽  
Ariel D Arencibia ◽  
Alex Echeverría-Vega ◽  
Leslie Cerpa ◽  
Juan P Cayún ◽  
...  
Keyword(s):  
Gallbladder Cancer ◽  
The United States ◽  
Genetic Alterations ◽  
Treatment Modalities ◽  
Driver Mutations ◽  
Missense Mutations ◽  
Loss Of Function ◽  
Northern India ◽  
High Incidence ◽  
Public Repositories

Prognostic markers for cancer can assist in the evaluation of survival probability of patients and help clinicians to assess the available treatment modalities. Gallbladder cancer (GBC) is a rare tumor that causes 165 087 deaths in the world annually. It is the most common cancer of the biliary tract and has a particularly high incidence in Chile, Japan, and northern India. Currently, there is no accurate diagnosis test or effective molecular markers for GBC identification. Several studies have focused on the discovery of genetic alterations in important genes associated with GBC to propose novel diagnosis pathways and to create prognostic profiles. To achieve this, we performed data-mining of GBC in public repositories, harboring 133 samples of GBC, allowing us to describe relevant somatic mutations in important genes and to propose a genetic alteration atlas for GBC. In our results, we reported the 14 most altered genes in GBC: arid1a, arid2, atm, ctnnb1, erbb2, erbb3, kmt2c, kmt2d, kras, pik3ca, smad4, tert, tp53, and znf521 in samples from Japan, the United States, Chile, and China. Missense mutations are common among these genes. The annotations of many mutations revealed their importance in cancer development. The observed annotations mentioned that several mutations found in this repository are probably oncogenic, with a putative loss-of-function. In addition, they are hotspot mutations and are probably linked to poor prognosis in other cancers. We identified another 11 genes, which presented a copy number alteration in gallbladder database samples, which are ccnd1, ccnd3, ccne1, cdk12, cdkn2a, cdkn2b, erbb2, erbb3, kras, mdm2, and myc. The findings reported here can help to detect GBC cancer through the development of systems based on genetic alterations, for example, the development of a mutation panel specifically for GBC diagnosis, as well as the creation of prognostic profiles to accomplish the development of GBC and its prevalence.

scholarly journals DARPP-32 promotes ERBB3-mediated resistance to molecular targeted therapy in EGFR-mutated lung adenocarcinoma

2021 ◽  
Author(s):  
Sk. Kayum Alam ◽  
Yongchang Zhang ◽  
Li Wang ◽  
Zhu Zhu ◽  
Christina E. Hernandez ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Disease Progression ◽  
Cancer Progression ◽  
Lung Tumor ◽  
Genetic Alterations ◽  
In Vivo Studies ◽  
Driver Mutations ◽  
Egfr Tki ◽  
Egfr Tkis

AbstractWhile molecular targeted therapies have improved prognoses of advanced stage lung adenocarcinoma expressing oncogenic driver mutations, acquired therapeutic resistance continues to be a major problem. Epidermal growth factor receptor (EGFR) activating mutations are among the most common targetable genetic alterations in lung adenocarcinoma, and EGFR tyrosine kinase inhibitors (TKIs) are recommended first-line therapy for EGFR mutation positive cancer patients. Unfortunately, most patients develop resistance to EGFR TKIs and rapid disease progression occurs. A better mechanistic understanding of therapy refractory cancer progression is necessary to develop new therapeutic approaches to predict and prevent acquired resistance to EGFR TKIs. Here, we identify a new mechanism of ERBB3-mediated resistance to EGFR TKIs in human lung adenocarcinoma. Specifically, we show that dopamine and cyclic AMP-regulated phosphoprotein, Mr 32000 (DARPP-32) physically recruits ERBB3 to EGFR to mediate a switch from EGFR homodimers to EGFR:ERBB3 heterodimers to bypass EGFR TKI-mediated inhibition to potentiate ERBB3-dependent activation of oncogenic AKT and ERK signaling that drives therapy refractory tumor cell survival. In a cohort of paired tumor specimens derived from 30 lung adenocarcinoma patients before and after the development of EGFR TKI refractory disease progression, we reveal that DARPP-32 as well as kinase-activated EGFR and ERBB3 proteins are overexpressed upon acquired EGFR TKI resistance. In vivo studies suggest that ablation of DARPP-32 protein activity sensitizes gefitinib-resistant lung tumor xenografts to EGFR TKI treatment, while DARPP-32 overexpression increases gefitinib-refractory lung cancer progression in gefitinib-sensitive lung tumors orthotopically xenografted into mice. Taken together, our findings introduce a DARPP-32-mediated, ERBB3-dependent mechanism used by lung tumor cells to evade EGFR TKI-induced cell death, potentially paving the way for the development of new therapies to prevent or overcome therapy-refractory lung adenocarcinoma progression.

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