IMPACT: a whole-exome sequencing analysis pipeline for integrating molecular profiles with actionable therapeutics in clinical samples

Hintzsche, Jennifer D.; Kim, Jihye; Yadav, Vinod Kumar; Amato, Carol; Robinson, Steven E.; Seelenfreund, Eric; Shellman, Yiqun G.; Wisell, J.; Applegate, Allison; McCarter, Martin D.; Box, Neil F.; Tentler, John J.; De, Subhajyoti; Robinson, William A.; Tan, Aik Choon

doi:10.1093/jamia/ocw022

Cited by 34 publications

(29 citation statements)

References 32 publications

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“…To that end, a variety of tools have been developed for analysis of the sequences including different methods, and functionalities that vary from general purpose to more targeted analysis. Some of the most popular tools for WES analysis are: SeqMule [7], which is a tool that performs alignment and variant calling and is used in this study, Impact [8], which performs computation of variants and Copy Number Variations in order to perform drug response predictions, and, WEP [9] which performs a complete analysis for data cleaning and alignment and variant detection. For further exploration of these pipelines, variant annotation tools are available with the most popular being ANNOVAR [10] which offers a great variety of annotations.…”

Section: -1-literature Reviewmentioning

confidence: 99%

Developing an Integrated Genomic Profile for Cancer Patients with the Use of NGS Data

2019

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Next Generation Sequencing (NGS) technologies has revolutionized genomics data research by facilitating high-throughput sequencing of genetic material that comes from different sources, such as Whole Exome Sequencing (WES) and RNA Sequencing (RNAseq). The exploitation and integration of this wealth of heterogeneous sequencing data remains a major challenge. There is a clear need for approaches that attempt to process and combine the aforementioned sources in order to create an integrated profile of a patient that will allow us to build the complete picture of a disease. This work introduces such an integrated profile using Chronic Lymphocytic Leukemia (CLL) as the exemplary cancer type. The approach described in this paper links the various NGS sources with the patients’ clinical data. The resulting profile efficiently summarizes the large-scale datasets, links the results with the clinical profile of the patient and correlates indicators arising from different data types. With the use of state-of-the-art machine learning techniques and the association of the clinical information with these indicators, which served as the feature pool for the classification, it has been possible to build efficient predictive models. To ensure reproducibility of the results, open data were exclusively used in the classification assessment. The final goal is to design a complete genomic profile of a cancer patient. The profile includes summarization and visualization of the results of WES and RNAseq analysis (specific variants and significantly expressed genes, respectively) and the clinical profile, integration/comparison of these results and a prediction regarding the disease trajectory. Concluding, this work has managed to produce a comprehensive clinico-genetic profile of a patient by successfully integrating heterogeneous data sources. The proposed profile can contribute to the medical research providing new possibilities in personalized medicine and prognostic views.

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Section: -1-literature Reviewmentioning

confidence: 99%

Developing an Integrated Genomic Profile for Cancer Patients with the Use of NGS Data

2019

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“…Here, we review three recent sequencing pipelines SeqMule [79], Fastq2vcf [80], and IMPACT [81] that assimilate some of the tools described in previous sections.…”

Section: Wes Analysis Pipelinesmentioning

confidence: 99%

“…IMPACT (Integrating Molecular Profiles with ACtionable Therapeutics) WES data analysis pipeline was developed to take this analysis a step further by linking a filtered VCF to actionable therapeutics [81]. The IMPACT pipeline contains four analytical modules: detecting somatic variants; calling copy number alterations; predicting drugs against the deleterious variants; and tumor heterogeneity analysis.…”

Section: Wes Analysis Pipelinesmentioning

confidence: 99%

“…IMPACT has been applied to longitudinal samples obtained from a melanoma patient and identified novel acquired resistance mutations to treatment. IMPACT analysis revealed loss of CDKN2A as a novel resistance mechanism to the combination of dabrafenib and trametinib treatment and predicted potential drugs for further pharmacological and biological studies [81]. …”

Section: Wes Analysis Pipelinesmentioning

confidence: 99%

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A Survey of Computational Tools to Analyze and Interpret Whole Exome Sequencing Data

Hintzsche

Robinson

Tan

2016

International Journal of Genomics

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Whole Exome Sequencing (WES) is the application of the next-generation technology to determine the variations in the exome and is becoming a standard approach in studying genetic variants in diseases. Understanding the exomes of individuals at single base resolution allows the identification of actionable mutations for disease treatment and management. WES technologies have shifted the bottleneck in experimental data production to computationally intensive informatics-based data analysis. Novel computational tools and methods have been developed to analyze and interpret WES data. Here, we review some of the current tools that are being used to analyze WES data. These tools range from the alignment of raw sequencing reads all the way to linking variants to actionable therapeutics. Strengths and weaknesses of each tool are discussed for the purpose of helping researchers make more informative decisions on selecting the best tools to analyze their WES data.

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“…The integrating molecular profiles with actionable therapeutics ( 16 ) is an analysis pipeline that combines mutation calling from sequencing data with drug prioritization based on detected mutations. However, it utilizes a gene–drug interaction based strategy to make drug predictions and is limited to only U.S. Food and Drug Administration-approved drugs.…”

Section: Introductionmentioning

confidence: 99%

mTCTScan: a comprehensive platform for annotation and prioritization of mutations affecting drug sensitivity in cancers

Plewczynski

Yao

Huang

et al. 2017

Nucleic Acids Research

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Cancer therapies have experienced rapid progress in recent years, with a number of novel small-molecule kinase inhibitors and monoclonal antibodies now being widely used to treat various types of human cancers. During cancer treatments, mutations can have important effects on drug sensitivity. However, the relationship between tumor genomic profiles and the effectiveness of cancer drugs remains elusive. We introduce Mutation To Cancer Therapy Scan (mTCTScan) web server (http://jjwanglab.org/mTCTScan) that can systematically analyze mutations affecting cancer drug sensitivity based on individual genomic profiles. The platform was developed by leveraging the latest knowledge on mutation-cancer drug sensitivity associations and the results from large-scale chemical screening using human cancer cell lines. Using an evidence-based scoring scheme based on current integrative evidences, mTCTScan is able to prioritize mutations according to their associations with cancer drugs and preclinical compounds. It can also show related drugs/compounds with sensitivity classification by considering the context of the entire genomic profile. In addition, mTCTScan incorporates comprehensive filtering functions and cancer-related annotations to better interpret mutation effects and their association with cancer drugs. This platform will greatly benefit both researchers and clinicians for interrogating mechanisms of mutation-dependent drug response, which will have a significant impact on cancer precision medicine.

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IMPACT: a whole-exome sequencing analysis pipeline for integrating molecular profiles with actionable therapeutics in clinical samples

Cited by 34 publications

References 32 publications

Developing an Integrated Genomic Profile for Cancer Patients with the Use of NGS Data

Developing an Integrated Genomic Profile for Cancer Patients with the Use of NGS Data

A Survey of Computational Tools to Analyze and Interpret Whole Exome Sequencing Data

mTCTScan: a comprehensive platform for annotation and prioritization of mutations affecting drug sensitivity in cancers

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