TRGAted: A web tool for survival analysis using protein data in the Cancer Genome Atlas.

Reverse-phase protein arrays (RPPAs) are a highthroughput approach to protein quantification utilizing an antibody-based micro-to-nano scale dot blot. Within the Cancer Genome Atlas (TCGA), RPPAs were used to quantify over 200 proteins in 8,167 tumor or metastatic samples. This protein-level data has particular advantages in assessing putative prognostic or therapeutic targets in tumors. However, many of the available pipelines do not allow for the partitioning of clinical and RPPA information to make meaningful conclusions. We developed a cloud-based application, TRGAted to enable researchers to better examine survival based on single or multiple proteins across 31 cancer types in the TCGA. TRGAted contains up-to-date overall survival, disease-specific survival, disease-free interval and progression-free interval information. Furthermore, survival information for primary tumor samples can be stratified based on gender, age, tumor stage, histological type, and subtype, allowing for highly adaptive and intuitive user experience. The code and processed data is open sourced and available on github and with a tutorial built into the application for assisting users.

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TRGAted: A web tool for survival analysis using protein data in the Cancer Genome Atlas.

F1000Research ◽

10.12688/f1000research.15789.2 ◽

2018 ◽

Vol 7 ◽

pp. 1235 ◽

Cited By ~ 2

Author(s):

Nicholas Borcherding ◽

Nicholas L. Bormann ◽

Andrew P. Voigt ◽

Weizhou Zhang

Keyword(s):

Tumor Stage ◽

Cancer Genome ◽

Protein Quantification ◽

The Cancer Genome Atlas ◽

Dot Blot ◽

Link Type ◽

Free Interval ◽

Level Data ◽

Cancer Genome Atlas ◽

Genome Atlas

Reverse-phase protein arrays (RPPAs) are a highthroughput approach to protein quantification utilizing antibody-based micro-to-nano scale dot blot. Within the Cancer Genome Atlas (TCGA), RPPAs were used to quantify over 200 proteins in 8,167 tumor and metastatic samples. Protein-level data has particular advantages in assessing putative prognostic or therapeutic targets in tumors. However, many of the available pipelines do not allow for the partitioning of clinical and RPPA information to make meaningful conclusions. We developed a cloud-based application, TRGAted to enable researchers to better examine patient survival based on single or multiple proteins across 31 cancer types in the TCGA. TRGAted contains up-to-date overall survival, disease-specific survival, disease-free interval and progression-free interval information. Furthermore, survival information for primary tumor samples can be stratified based on gender, age, tumor stage, histological type, and subtype, allowing for highly adaptive and intuitive user experience. The code and processed data are open sourced and available on github and contains a tutorial built into the application for assisting users.

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Special Report: The Cancer Genome Atlas Begins with 3-Year, $100 Million Pilot

PsycEXTRA Dataset ◽

10.1037/e481292006-009 ◽

2005 ◽

Author(s):

Keyword(s):

Cancer Genome ◽

The Cancer Genome Atlas ◽

Special Report ◽

Cancer Genome Atlas ◽

Genome Atlas

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Differences in endometrial cancer molecular portraits based on ethnicity in The Cancer Genome Atlas

10.26226/morressier.59ba7298d462b80296ca20c6 ◽

2017 ◽

Author(s):

David Guttery

Keyword(s):

Endometrial Cancer ◽

Cancer Genome ◽

The Cancer Genome Atlas ◽

Cancer Genome Atlas ◽

Genome Atlas

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Exceptional Chemotherapy Response in Metastatic Colorectal Cancer Associated With Hyper-Indel–Hypermutated Cancer Genome and Comutation of POLD1 and MLH1

JCO Precision Oncology ◽

10.1200/po.16.00015 ◽

2017 ◽

pp. 1-12

Author(s):

Manish R. Sharma ◽

James T. Auman ◽

Nirali M. Patel ◽

Juneko E. Grilley-Olson ◽

Xiaobei Zhao ◽

...

Keyword(s):

Colorectal Cancer ◽

Colon Cancer ◽

Somatic Mutation ◽

Mutation Rate ◽

Germ Line ◽

Cancer Genome ◽

The Cancer Genome Atlas ◽

Response To Chemotherapy ◽

Cancer Genome Atlas ◽

Genome Atlas

Purpose A 73-year-old woman with metastatic colon cancer experienced a complete response to chemotherapy with dose-intensified irinotecan that has been durable for 5 years. We sequenced her tumor and germ line DNA and looked for similar patterns in publicly available genomic data from patients with colorectal cancer. Patients and Methods Tumor DNA was obtained from a biopsy before therapy, and germ line DNA was obtained from blood. Tumor and germline DNA were sequenced using a commercial panel with approximately 250 genes. Whole-genome amplification and exome sequencing were performed for POLE and POLD1. A POLD1 mutation was confirmed by Sanger sequencing. The somatic mutation and clinical annotation data files from the colon (n = 461) and rectal (n = 171) adenocarcinoma data sets were downloaded from The Cancer Genome Atlas data portal and analyzed for patterns of mutations and clinical outcomes in patients with POLE- and/or POLD1-mutated tumors. Results The pattern of alterations included APC biallelic inactivation and microsatellite instability high (MSI-H) phenotype, with somatic inactivation of MLH1 and hypermutation (estimated mutation rate > 200 per megabase). The extremely high mutation rate led us to investigate additional mechanisms for hypermutation, including loss of function of POLE. POLE was unaltered, but a related gene not typically associated with somatic mutation in colon cancer, POLD1, had a somatic mutation c.2171G>A [p.Gly724Glu]. Additionally, we noted that the high mutation rate was largely composed of dinucleotide deletions. A similar pattern of hypermutation (dinucleotide deletions, POLD1 mutations, MSI-H) was found in tumors from The Cancer Genome Atlas. Conclusion POLD1 mutation with associated MSI-H and hyper-indel–hypermutated cancer genome characterizes a previously unrecognized variant of colon cancer that was found in this patient with an exceptional response to chemotherapy.

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