Characterization of potential driver mutations involved in human breast cancer by computational approaches

Rajendran, Barani Kumar; Deng, Chu‐Xia

doi:10.18632/oncotarget.17225

Cited by 55 publications

(42 citation statements)

References 170 publications

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“…For example, testing of actionable driver mutations (eg, EGFR inhibitor therapies for EGFR-mutated lung cancers), genes associated with mutagenesis (eg, POLE), and potential negative predictors of response (eg, mutated β2M, JAK1/2, PTEN, STK11). [75][76][77][78] We recommend that targeted gene panel assays that have larger genome coverage (ideally with~1 megabase being the lower limit) are used because they yield more reliable TMB estimation than smaller panels. [67][68][69] Of note, panels that cover less than 1 megabase are useful; however, accuracy may be reduced.…”

Section: Recommendations For Reliable Tmb Estimation and Reporting mentioning

confidence: 99%

Tumor mutational burden standardization initiatives: Recommendations for consistent tumor mutational burden assessment in clinical samples to guide immunotherapy treatment decisions

Stenzinger

Allen

Maas³

et al. 2019

Genes Chromosomes & Cancer

183

161

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Characterization of tumors utilizing next‐generation sequencing methods, including assessment of the number of somatic mutations (tumor mutational burden [TMB]), is currently at the forefront of the field of personalized medicine. Recent clinical studies have associated high TMB with improved patient response rates and survival benefit from immune checkpoint inhibitors; hence, TMB is emerging as a biomarker of response for these immunotherapy agents. However, variability in current methods for TMB estimation and reporting is evident, demonstrating a need for standardization and harmonization of TMB assessment methodology across assays and centers. Two uniquely placed organizations, Friends of Cancer Research (Friends) and the Quality Assurance Initiative Pathology (QuIP), have collaborated to coordinate efforts for international multistakeholder initiatives to address this need. Friends and QuIP, who have partnered with several academic centers, pharmaceutical organizations, and diagnostic companies, have adopted complementary, multidisciplinary approaches toward the goal of proposing evidence‐based recommendations for achieving consistent TMB estimation and reporting in clinical samples across assays and centers. Many factors influence TMB assessment, including preanalytical factors, choice of assay, and methods of reporting. Preliminary analyses highlight the importance of targeted gene panel size and composition, and bioinformatic parameters for reliable TMB estimation. Herein, Friends and QuIP propose recommendations toward consistent TMB estimation and reporting methods in clinical samples across assays and centers. These recommendations should be followed to minimize variability in TMB estimation and reporting, which will ensure reliable and reproducible identification of patients who are likely to benefit from immune checkpoint inhibitors.

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Section: Recommendations For Reliable Tmb Estimation and Reporting mentioning

confidence: 99%

Tumor mutational burden standardization initiatives: Recommendations for consistent tumor mutational burden assessment in clinical samples to guide immunotherapy treatment decisions

Stenzinger

Allen

Maas³

et al. 2019

Genes Chromosomes & Cancer

183

161

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“…The path to ITH is complex and involves a series of genetic and epigenetic events throughout the transformation process which permit normal human mammary epithelial cells (HMEC) to develop into fully malignant cancer cells [37][38][39][40][41][42][43][44] . Progress in RNA and DNA sequencing technologies have helped shape the evolutionary picture of HMEC; losing tumor suppressor function (TP53 mutations or RB loss) and acquiring oncogenic drivers (MYC, HER2, or CCND1 amplification or PIK3CA mutations) [45][46][47][48][49] . Genetic alterations lead to the expansion of a pre-malignant population which progressively acquires additional genetic and epigenetic changes until one or more cells become fully transformed [50,51] .…”

mentioning

confidence: 99%

Cellular plasticity and metastasis in breast cancer: a pre- and post-malignant problem

Smigiel

Taylor

Bryson

et al. 2019

JCMT

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As a field we have made tremendous strides in treating breast cancer, with a decline in the past 30 years of overall breast cancer mortality. However, this progress is met with little affect once the disease spreads beyond the primary site. With a 5-year survival rate of 22%, 10-year of 13%, for those patients with metastatic breast cancer (mBC), our ability to effectively treat wide spread disease is minimal. A major contributing factor to this ineffectiveness is the complex make-up, or heterogeneity, of the primary site. Within a primary tumor, secreted factors, malignant and pre-malignant epithelial cells, immune cells, stromal fibroblasts and many others all reside alongside each other creating a dynamic environment contributing to metastasis. Furthermore, heterogeneity contributes to our lack of understanding regarding the cells' remarkable ability to undergo epithelial/non-cancer stem cell (CSC) to mesenchymal/CSC (E-M/CSC) plasticity. The enhanced invasion & motility, tumor-initiating potential, and acquired therapeutic resistance which accompanies E-M/CSC plasticity implicates a significant role in metastasis. While most work trying to understand E-M/CSC plasticity has been done on malignant cells, recent evidence is emerging concerning the ability for pre-malignant cells to undergo E-M/CSC plasticity and contribute to the metastatic process. Here we will discuss the importance of E-M/CSC plasticity within malignant and pre-malignant populations of the tumor. Moreover, we will discuss how one may potentially target these populations, ultimately disrupting the metastatic cascade and increasing patient survival for those with mBC.

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“…Among the genes involved with the breast cancer incidence, mutations in BRCA1, BRCA2, TP53, STK11, CDH1 and PTEN play critical roles in the development and progression of cancer. 10 Mutations in BRIP1, CHEK2, PALB2 and ATM seem to have a moderate role, while mutations in the rest genes show a weak association. BRCA1, BRCA2 and TP53 are the most potent genes to predispose hereditary breast cancer development.…”

Section: Breast Cancermentioning

confidence: 99%

“…These variations are the basis of the initiation and progression for a tumor in the presence of enough growth signals with an insensitivity to the antigrowth signals, evasion from the programmed cell death, unlimited replicative potential, sustained angiogenesis, and finally the ability to invade and metastasize. 3 , 9 , 10 Despite considerable attempts and impressive advances to understand the molecular mechanisms of cancerous cells, it remains a major challenge for biomedical scientists.…”

Section: Breast Cancermentioning

confidence: 99%

Breast cancer vaccination comes to age: impacts of bioinformatics

Parvizpour¹,

Razmara²,

Omidi³

2018

Bioimpacts

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Introduction: Breast cancer, as one of the major causes of cancer death among women, is the central focus of this study. The recent advances in the development and application of computational tools and bioinformatics in the field of immunotherapy of malignancies such as breast cancer have emerged the new dominion of immunoinformatics, and therefore, next generation of immunomedicines . Methods: Having reviewed the most recent works on the applications of computational tools, we provide comprehensive insights into the breast cancer incidence and its leading causes as well as immunotherapy approaches and the future trends. Furthermore, we discuss the impacts of bioinformatics on different stages of vaccine design for the breast cancer, which can be used to produce much more efficient vaccines through a rationalized time- and cost-effective in silico approaches prior to conducting costly experiments. Results: The tools can be significantly used for designing the immune system-modulating drugs and vaccines based on in silico approaches prior to in vitro and in vivo experimental evaluations. Application of immunoinformatics in the cancer immunotherapy has shown its success in the pre-clinical models. This success returns back to the impacts of several powerful computational approaches developed during the last decade. Conclusion: Despite the invention of a number of vaccines for the cancer immunotherapy, more computational and clinical trials are required to design much more efficient vaccines against various malignancies, including breast cancer.

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Characterization of potential driver mutations involved in human breast cancer by computational approaches

Cited by 55 publications

References 170 publications

Tumor mutational burden standardization initiatives: Recommendations for consistent tumor mutational burden assessment in clinical samples to guide immunotherapy treatment decisions

Tumor mutational burden standardization initiatives: Recommendations for consistent tumor mutational burden assessment in clinical samples to guide immunotherapy treatment decisions

Cellular plasticity and metastasis in breast cancer: a pre- and post-malignant problem

Breast cancer vaccination comes to age: impacts of bioinformatics

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