Dataset Information

Precision Oncology in Sarcomas: Divide and Conquer.

ABSTRACT: Sarcomas are a heterogeneous group of rare malignancies that exhibit remarkable heterogeneity, with more than 50 subtypes recognized. Advances in next-generation sequencing technology have resulted in the discovery of genetic events in these mesenchymal tumors, which in addition to enhancing understanding of the biology, have opened up avenues for molecularly targeted therapy and immunotherapy. This review focuses on how incorporation of next-generation sequencing has affected drug development in sarcomas and strategies for optimizing precision oncology for these rare cancers. In a significant percentage of soft tissue sarcomas, which represent up to 40% of all sarcomas, specific driver molecular abnormalities have been identified. The challenge to evaluate these mutations across rare cancer subtypes requires the careful characterization of these genetic alterations to further define compelling drivers with therapeutic implications. Novel models of clinical trial design also are needed. This shift would entail sustained efforts by the sarcoma community to move from one-size-fits-all trials, in which all sarcomas are treated similarly, to divide-and-conquer subtype-specific strategies.

SUBMITTER: Carmagnani Pestana R

PROVIDER: S-EPMC7446356 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Publications

Precision Oncology in Sarcomas: Divide and Conquer.

Carmagnani Pestana Roberto R Groisberg Roman R Roszik Jason J Subbiah Vivek V

JCO precision oncology 20190425

Sarcomas are a heterogeneous group of rare malignancies that exhibit remarkable heterogeneity, with more than 50 subtypes recognized. Advances in next-generation sequencing technology have resulted in the discovery of genetic events in these mesenchymal tumors, which in addition to enhancing understanding of the biology, have opened up avenues for molecularly targeted therapy and immunotherapy. This review focuses on how incorporation of next-generation sequencing has affected drug development i ...[more]

PMID: 32914012

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Project description:Among proteins, orthologs are defined as those that are derived by vertical descent from a single progenitor in the last common ancestor of their host organisms. Our goal is to compute a complete set of protein orthologs derived from all currently available complete bacterial and archaeal genomes. Traditional approaches typically rely on all-against-all BLAST searching which is prohibitively expensive in terms of hardware requirements or computational time (requiring an estimated 18 months or more on a typical server). Here, we present xBASE-Orth, a system for ongoing ortholog annotation, which applies a "divide and conquer" approach and adopts a pragmatic scheme that trades accuracy for speed. Starting at species level, xBASE-Orth carefully constructs and uses pan-genomes as proxies for the full collections of coding sequences at each level as it progressively climbs the taxonomic tree using the previously computed data. This leads to a significant decrease in the number of alignments that need to be performed, which translates into faster computation, making ortholog computation possible on a global scale. Using xBASE-Orth, we analyzed an NCBI collection of 1,288 bacterial and 94 archaeal complete genomes with more than 4 million coding sequences in 5 weeks and predicted more than 700 million ortholog pairs, clustered in 175,531 orthologous groups. We have also identified sets of highly conserved bacterial and archaeal orthologs and in so doing have highlighted anomalies in genome annotation and in the proposed composition of the minimal bacterial genome. In summary, our approach allows for scalable and efficient computation of the bacterial and archaeal ortholog annotations. In addition, due to its hierarchical nature, it is suitable for incorporating novel complete genomes and alternative genome annotations. The computed ortholog data and a continuously evolving set of applications based on it are integrated in the xBASE database, available at http://www.xbase.ac.uk/.

Dataset Information

Precision Oncology in Sarcomas: Divide and Conquer.

Publications

Precision Oncology in Sarcomas: Divide and Conquer.

Similar Datasets

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