A Comprehensive Infrastructure for Big Data in Cancer Research: Accelerating Cancer Research and Precision Medicine

@article{Hinkson2017ACI,
  title={A Comprehensive Infrastructure for Big Data in Cancer Research: Accelerating Cancer Research and Precision Medicine},
  author={Izumi V. Hinkson and Tanja Davidsen and Juli D. Klemm and Ishwar Chandramouliswaran and Anthony R. Kerlavage and W. Kibbe},
  journal={Frontiers in Cell and Developmental Biology},
  year={2017},
  volume={5}
}
Advancements in next-generation sequencing and other -omics technologies are accelerating the detailed molecular characterization of individual patient tumors, and driving the evolution of precision medicine. Cancer is no longer considered a single disease, but rather, a diverse array of diseases wherein each patient has a unique collection of germline variants and somatic mutations. Molecular profiling of patient-derived samples has led to a data explosion that could help us understand the… 

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References

SHOWING 1-10 OF 34 REFERENCES

Comprehensive genomic characterization defines human glioblastoma genes and core pathways

TLDR
The interim integrative analysis of DNA copy number, gene expression and DNA methylation aberrations in 206 glioblastomas reveals a link between MGMT promoter methylation and a hypermutator phenotype consequent to mismatch repair deficiency in treated gliobeasts, demonstrating that it can rapidly expand knowledge of the molecular basis of cancer.

Proteogenomics connects somatic mutations to signaling in breast cancer

TLDR
It is demonstrated that proteogenomic analysis of breast cancer elucidates functional consequences of somatic mutations, narrows candidate nominations for driver genes within large deletions and amplified regions, and identifies therapeutic targets.

Implementing Genome-Driven Oncology

Proteogenomic characterization of human colon and rectal cancer

TLDR
Integrated proteogenomic analysis provides functional context to interpret genomic abnormalities and affords a new paradigm for understanding cancer biology.

Comprehensive molecular portraits of human breast tumors

TLDR
The ability to integrate information across platforms provided key insights into previously defined gene expression subtypes and demonstrated the existence of four main breast cancer classes when combining data from five platforms, each of which shows significant molecular heterogeneity.

A cloud-based workflow to quantify transcript-expression levels in public cancer compendia

TLDR
This work quantified transcript-expression levels for 12,307 RNA-Sequencing samples from the Cancer Cell Line Encyclopedia and The Cancer Genome Atlas and created open-source Docker containers that include all the software and scripts necessary to process such data in the cloud and to collect performance metrics.

Collaboration to Accelerate Proteogenomics Cancer Care: The Department of Veterans Affairs, Department of Defense, and the National Cancer Institute's Applied Proteogenomics OrganizationaL Learning and Outcomes (APOLLO) Network

TLDR
A tri‐federal initiative arising out of the Cancer Moonshot has resulted in the formation of a program to utilize advanced genomic and proteomic expression platforms on high‐quality human biospecimens in near‐real‐time in order to identify potentially actionable therapeutic molecular targets and accelerate novel clinical trials with biomarkers of prognostic and predictive value.

Integrated Genomic Analyses of Ovarian Carcinoma

TLDR
It is reported that high-grade serous ovarian cancer is characterized by TP53 mutations in almost all tumours (96%); low prevalence but statistically recurrent somatic mutations in nine further genes including NF1, BRCA1,BRCA2, RB1 and CDK12; 113 significant focal DNA copy number aberrations; and promoter methylation events involving 168 genes.

Integrated genomic and molecular characterization of cervical cancer.

TLDR
The extensive molecular characterization of 228 primary cervical cancers is reported, one of the largest comprehensive genomic studies of cervical cancer to date, and novel significantly mutated genes in cervical cancer are identified, revealing new potential therapeutic targets for cervical cancers.