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 Synonymous mutations reveal genome-wide driver mutation rates in healthy tissues

2020 ◽  
Author(s):  
Gladys Poon ◽  
Caroline J. Watson ◽  
Daniel S. Fisher ◽  
Jamie R. Blundell
Keyword(s):  
Cancer Risk ◽  
Allele Frequency ◽  
Genetic Alterations ◽  
Driver Mutation ◽  
Variant Allele ◽  
Driver Mutations ◽  
Total Rate ◽  
Variant Allele Frequency ◽  
Synonymous Mutations ◽  
Passenger Mutations

Genetic alterations that drive clonal expansions in ostensibly healthy tissues have implications for cancer risk. However, the total rate at which clonal expansions occur in healthy tissues remains unknown. Synonymous passenger mutations that hitchhike to high variant allele frequency due to a linked driver mutation can be used to estimate the total rate of positive selection across the genome. Because these synonymous hitchhikers are influenced by all mutations under selection, regardless of type or location, they can be used to estimate how many driver mutations are missed by narrow gene-focused sequencing panels. Here we analyse the variant allele frequency spectrum of synonymous passenger mutations to estimate the total rate at which mutations driving clonal expansions occur in healthy tissues. By applying our framework to data from physiologically healthy blood, we find that a large fraction of mutations driving clonal expansions occur outside of canonical cancer driver genes. In contrast, analysis of data from healthy oesophagus reveals little evidence for many driver mutations outside of those in NOTCH1 and TP53. Our framework, which generalizes to other tissues, sheds light on the fraction of drivers mutations that remain undiscovered and has implications for cancer risk prediction.

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 A tug-of-war between driver and passenger mutations in cancer and other adaptive processes

2014 ◽  
Author(s):  
Christopher Dennis McFarland ◽  
Leonid A Mirny ◽  
Kirill S Korolev
Keyword(s):  
Mutation Rate ◽  
Cancer Progression ◽  
Evolutionary Dynamics ◽  
Cancer Genomics ◽  
Treatment Strategies ◽  
Driver Mutations ◽  
Fitness Advantage ◽  
Adaptive Processes ◽  
Passenger Mutations ◽  
Stochastic Population Model

Cancer progression is an example of a rapid adaptive process where evolving new traits is essential for survival and requires a high mutation rate. Precancerous cells acquire a few key mutations that drive rapid population growth and carcinogenesis. Cancer genomics demonstrates that these few ‘driver’ mutations occur alongside thousands of random ‘passenger’ mutations––a natural consequence of cancer's elevated mutation rate. Some passengers can be deleterious to cancer cells, yet have been largely ignored in cancer research. In population genetics, however, the accumulation of mildly deleterious mutations has been shown to cause population meltdown. Here we develop a stochastic population model where beneficial drivers engage in a tug-of-war with frequent mildly deleterious passengers. These passengers present a barrier to cancer progression that is described by a critical population size, below which most lesions fail to progress, and a critical mutation rate, above which cancers meltdown. We find support for the model in cancer age-incidence and cancer genomics data that also allow us to estimate the fitness advantage of drivers and fitness costs of passengers. We identify two regimes of adaptive evolutionary dynamics and use these regimes to rationalize successes and failures of different treatment strategies. We find that a tumor’s load of deleterious passengers can explain previously paradoxical treatment outcomes and suggest that it could potentially serve as a biomarker of response to mutagenic therapies. The collective deleterious effect of passengers is currently an unexploited therapeutic target. We discuss how their effects might be exacerbated by both current and future therapies.

Establishing Adrenocortical Carcinoma Specific Prognostic Genes Signature

2020 ◽  
Vol 154 (Supplement_1) ◽  
pp. S148-S149
Author(s):  
A R Patil ◽  
D S Dabrowski ◽  
J Cotelingam ◽  
D Veillon ◽  
M Ong ◽  
...  
Keyword(s):  
Median Survival ◽  
Poor Prognosis ◽  
Cancer Genomics ◽  
Disease Free Survival ◽  
Genetic Alterations ◽  
Malignant Neoplasms ◽  
Free Survival ◽  
Signature Genes ◽  
Disease Free ◽  
Disease Specific

Abstract Introduction/Objective Adrenal Cortical Carcinoma (ACC) is a rare malignant neoplasms originating from adrenal cortical tissue with an annual incidence rate of 1 to 2 cases per million individuals. These tumors have poor prognosis with 5-year disease free survival being 30% after complete resection in Stage I to Stage III patients. Hence, there is a need for identifying prognostic markers for effective management of disease in these patients. Methods We analyzed the data in The Cancer Genome Atlas of 1141 ACC individuals, using cbioportal.org, a web- based platform for analysis of large-scale cancer genomics data sets, and derived correlation between prognosis and genetic alterations in approximately 51,309 genes. Results We identified 15 signature genes (NOTCH1, TP53, ZNRF3, LRP1, KIF5A, MDM2, LETMD1, MTOR, NOTCH3, RERE, SMARCC2, LDLR, HRNR, AVPR1A and PCDH15), alterations in which indicated a poor prognosis for ACC individuals. Analysis of 15 signature genes demonstrated that disease specific median survival for the patients with ACC, was reduced to 39.5 months (p value < 8 x 10 -9 and sensitivity of 93%) when any one or more of these genes was altered. Whereas, disease specific median survival was greater than 180 months (90% survival being 180 months) with no alteration in our signature genes. In addition, our analysis of our signature genes demonstrates reduced overall survival, disease free survival and progression free survival in individuals having alterations in our signature genes. Moreover, our set of 15 genes belonged mainly to MDM2-TP53, NOTCH and mTOR pathways, and small molecule modulators of these pathways are in process of development. Conclusion Our 15 gene signature was not only able to predict poor prognosis in ACC, but also has the potential to serve as a molecular marker set for initiation of NOTCH and mTOR specific targeted therapies in these patients.

scholarly journals Paired analysis of tumor mutation burden for lung adenocarcinoma and associated idiopathic pulmonary fibrosis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yasuto Yoneshima ◽  
Eiji Iwama ◽  
Shingo Matsumoto ◽  
Taichi Matsubara ◽  
Testuzo Tagawa ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Lung Adenocarcinoma ◽  
Genetic Alterations ◽  
Driver Mutations ◽  
Somatic Variant ◽  
Tumor Mutation Burden ◽  
Mutation Burden ◽  
And Oxidative Stress

AbstractGenetic alterations underlying the development of lung cancer in individuals with idiopathic pulmonary fibrosis (IPF) have remained unclear. To explore whether genetic alterations in IPF tissue contribute to the development of IPF-associated lung cancer, we here evaluated tumor mutation burden (TMB) and somatic variants in 14 paired IPF and tumor samples from patients with IPF-associated lung adenocarcinoma. We also determined TMB for 22 samples of lung adenocarcinoma from patients without IPF. TMB for IPF-associated lung adenocarcinoma was significantly higher than that for matched IPF tissue (median of 2.94 vs. 1.26 mutations/Mb, P = 0.002). Three and 102 somatic variants were detected in IPF and matched lung adenocarcinoma samples, respectively, with only one pair of specimens sharing one somatic variant. TMB for IPF-associated lung adenocarcinoma was similar to that for lung adenocarcinoma samples with driver mutations (median of 2.94 vs. 2.51 mutations/Mb) and lower than that for lung adenocarcinoma samples without known driver mutations (median of 2.94 vs. 5.03 mutations/Mb, P = 0.130) from patients without IPF. Our findings suggest that not only the accumulation of somatic mutations but other factors such as inflammation and oxidative stress might contribute to the development and progression of lung cancer in patients with IPF.

Genetic Alterations in Chinese Resected Lung Cancer with Invasive Mucinous Adenocarcinoma: Genomic Profiling and Prognostic Value Analysis

2021 ◽  
Author(s):  
James D. Klingensmith
Keyword(s):  
Mucinous Adenocarcinoma ◽  
Pi3k Pathway ◽  
Genetic Alterations ◽  
Egfr Mutations ◽  
Driver Mutations ◽  
Genetic Profile ◽  
Kras Mutations ◽  
Genetic Characteristics ◽  
Value Analysis ◽  
Invasive Mucinous Adenocarcinoma

Lung invasive mucinous adenocarcinoma (IMA) is a unique histological subtype with different clinical and pathological characteristics. Despite prior genomic investigations on lung IMA, little is known about the genetic features and prognosis-related biomarkers in Chinese surgically resected lung IMA. IMA showed a distinct genetic profile, with more diversified driver mutations and co-occurrence of tumor drivers/suppressors than non-IMA. From non-IMA to mixed-IMA to pure-IMA, the frequency of EGFR (72.0 percent vs. 40.0 percent vs. 23.1 percent, p=0.002) and ALK (undetected vs. 20.0 percent vs. 26.9%, p=0.015) changes exhibited a trend of steady decline and rise, respectively. KRAS mutations were more common in pure-IMA than in mixed-IMA, however the difference was statistically insignificant (23.1 percent vs. 4.0 percent, p=0.10). Pure-IMA had a lower rate of TP53 mutation than mixed-IMA and non-IMA (23.1 percent vs. 52.0 percent vs. 56.0 percent, p=0.03). Furthermore, IMA had fewer arm-level amplifications (p=0.04) and more arm-level deletions (p=0.004) than non-IMA, with a steady drop in amplification and rise in deletion frequency from non-IMA to mixed-IMA to pure-IMA, respectively. Patients with EGFR mutations (mDFS=30.3 vs. 16.0 months, HR=0.19, P=0.027) and PI3K pathway mutations (mDFS=36.0 vs. 16.0 months, HR=0.12, P=0.023) had longer DFS than patients with poorly differentiated tumors (mDFS=14.1 vs. 28.0 months, HR=3.75, p=0.037) or KRAS mutations (mDFS=13 KRAS mutations, PI3K pathway changes, and tumor differentiation status were all shown to be independent predictors with statistically significant effects on IMA patients' clinical outcomes in multivariate analysis. Our research shed light on the genomics of Chinese lung IMA that had been surgically removed. In IMA patients with stage III illness, we also discovered many genetic characteristics that might be used as indicators for postoperative recurrence.

scholarly journals Genetic Abnormalities, Clonal Evolution, and Cancer Stem Cells of Brain Tumors

2018 ◽  
Vol 6 (4) ◽  
pp. 85 ◽  
Author(s):  
Ugo Testa ◽  
Germana Castelli ◽  
Elvira Pelosi
Keyword(s):  
Brain Tumors ◽  
Clonal Evolution ◽  
Pediatric Brain Tumors ◽  
Genetic Alterations ◽  
World Health ◽  
Driver Mutations ◽  
Low Grade ◽  
High Grade ◽  
Genetic Profiling ◽  
Health Organization

Brain tumors are highly heterogeneous and have been classified by the World Health Organization in various histological and molecular subtypes. Gliomas have been classified as ranging from low-grade astrocytomas and oligodendrogliomas to high-grade astrocytomas or glioblastomas. These tumors are characterized by a peculiar pattern of genetic alterations. Pediatric high-grade gliomas are histologically indistinguishable from adult glioblastomas, but they are considered distinct from adult glioblastomas because they possess a different spectrum of driver mutations (genes encoding histones H3.3 and H3.1). Medulloblastomas, the most frequent pediatric brain tumors, are considered to be of embryonic derivation and are currently subdivided into distinct subgroups depending on histological features and genetic profiling. There is emerging evidence that brain tumors are maintained by a special neural or glial stem cell-like population that self-renews and gives rise to differentiated progeny. In many instances, the prognosis of the majority of brain tumors remains negative and there is hope that the new acquisition of information on the molecular and cellular bases of these tumors will be translated in the development of new, more active treatments.

scholarly journals Burnout level and associated factors in a Sub-Saharan African medical setting: prospective cross-sectional survey.

2020 ◽  
Author(s):  
Jean-Rodolphe MACKANGA ◽  
Emeline Gracia MOUENDOU MOULOUNGUI ◽  
Josaphat IBA-BA ◽  
Pierre POTTIER ◽  
Jean-Baptiste MOUSSAVOU KOMBILA ◽  
...  
Keyword(s):  
Associated Factors ◽  
University Hospital ◽  
Hospital Environment ◽  
Easy Access ◽  
Cross Sectional ◽  
Middle Income ◽  
Medical Context ◽  
Sub Saharan ◽  
High Level ◽  
Hospital Center

Abstract Background: burnout in the hospital environment is a problem that affects care and training. Often explored in the high-income medical context, burnout is poorly studied in low and middle-income countries characterized by a precarious hospital situation and a high stake linked to the Millennium Development Goals. The aim of our study was to determine in medical practitioners, in a sub-Saharan African country’s medical context, the burnout level and associated factors. Methods: a prospective cross-sectional study by using a self-administered Likert-scale questionnaire addressed to doctors and doctoral medical students in Gabon. Maslach Burnout Inventory scale has been used. Burnout symptoms were defined by high level in at least one of the 3 dimensions. Severe burnout defined by high level in all dimensions. Explored factors: socio-demographic and psychometric. Multiple logistic regression has been performed. Results: among 104 participants, severe burnout prevailed at 1.9% (95% CI: 0.2% -6.8%) and burnout symptoms at 34.6% (95% CI: 25, 6% -44.6%). The associated factors with burnout symptoms: age (OR = 0.86, p = 0.004), clinical activity in a university hospital center (OR = 5.19, p = 0.006), the easy access to the hospital (OR = 0.59, p = 0.012), number of elderly dependents living with the practitioner (OR = 0.54, p = 0.012), to live in the borough where the hospital is located (OR = 0.24, p = 0.039) and to be favorable to traditional medicine (OR = 1.82, p = 0.087). Nagelkerke’s R-squared:53.1%. Conclusion: in Gabon, middle-income country, almost one practitioner in two has burnout symptoms. The young age, the university hospital center, the difficulty to access to hospital and to live in the borough where the hospital is located increase the probability of burnout symptoms. These results must put question to relevant authorities regarding health and medical education, to set up: a public transport for practitioners, an optimal primary health care system, a regulation of medical tasks in hospitals, a training in clinical supervision.

scholarly journals Future Perspective of Chemotherapy and Pharmacotherapy in Thymic Carcinoma

Cancers ◽  
2021 ◽  
Vol 13 (20) ◽  
pp. 5239
Author(s):  
Rui Kitadai ◽  
Yusuke Okuma
Keyword(s):  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Thymic Carcinoma ◽  
Checkpoint Inhibitors ◽  
Genetic Alterations ◽  
Cytotoxic Agents ◽  
Future Perspective ◽  
Driver Mutations ◽  
Thymic Epithelial Cells ◽  
Thymic Epithelial Tumors

Thymic carcinoma is a rare cancer that arises from thymic epithelial cells. Its nature and pathology differ from that of benign thymoma, presenting a poorer prognosis. If surgically resectable, surgery alone or surgery followed by chemoradiotherapy or radiotherapy is recommended by the National Comprehensive Cancer Network Guidelines. Metastatic and refractory thymic carcinomas require systemic pharmacotherapy. Combined carboplatin and paclitaxel, and cisplatin and anthracycline-based regimens have been shown a fair response rate and survival to provide a de facto standard of care when compared with other drugs employed as first-line chemotherapy. Cytotoxic agents have been pivotal for treating thymic carcinoma, as little is known regarding its tumorigenesis. In addition, genetic alterations, including driver mutations, which play an important role in treatments, have not yet been discovered. However, molecular pathways and biomarker studies assessing thymic epithelial tumors have been reported recently, resulting in the development of new agents, such as molecular targeted agents and immune checkpoint inhibitors. As treatment options are currently limited and the prognosis remains poor in metastases and recurrent thymic carcinoma, genetic alterations need to be assessed. In the present review, we focused on the current role of targeted therapies and immune checkpoint inhibitors in treating thymic carcinoma.

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.

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