ABSTRACT
Widespread, comprehensive sequencing of patient tumors has facilitated the usage of precision medicine (PM) drugs to target specific genomic alterations. Therapeutic clinical trials are necessary to test new PM drugs to advance precision medicine, however, the abundance of patient sequencing data coupled with complex clinical trial eligibility has made it challenging to match patients to PM trials. To facilitate enrollment onto PM trials, we developed MatchMiner, an open-source platform to computationally match genomically profiled cancer patients to PM trials. Here, we describe MatchMiner's capabilities, outline its deployment at Dana-Farber Cancer Institute (DFCI), and characterize its impact on PM trial enrollment. MatchMiner's primary goals are to facilitate PM trial options for all patients and accelerate trial enrollment onto PM trials. MatchMiner can help clinicians find trial options for an individual patient or provide trial teams with candidate patients matching their trial's eligibility criteria. From March 2016 through March 2021, we curated 354 PM trials containing a broad range of genomic and clinical eligibility criteria and MatchMiner facilitated 166 trial consents (MatchMiner consents, MMC) for 159 patients. To quantify MatchMiner's impact on trial consent, we measured time from genomic sequencing report date to trial consent date for the 166 MMC compared to trial consents not facilitated by MatchMiner (non-MMC). We found MMC consented to trials 55 days (22%) earlier than non-MMC. MatchMiner has enabled our clinicians to match patients to PM trials and accelerated the trial enrollment process.
ABSTRACT
UNLABELLED: To manage and intelligently mine the avalanche of genomic sequences intuitive and user-friendly graphical interfaces are required. Here we present BlastXtract2 which exclusively facilitates early exploration of un-annotated genomic and metagenomic sequences. Various formats of translated searches, including the commonly used BlastX, of multiple sequences against multiple protein databases can be uploaded to a relational database server, which can be accessed via a locally installed web-server. There, an intuitive GUI allows straightforward data-mining and enables quick detection of potential frameshifts and poorly sequenced or assembled regions, thereby contributing in making BlastXtract2 a unique and valuable tool for early exploration of (meta)genomic sequences. AVAILABILITY: Source code, documentation and an online demo version are available at https://github.com/ ClaessonLab/BlastXtract2.
ABSTRACT
As the number of assembled genome and metagenome sequences continue to grow at an ever-increasing pace, so does the need for fast, flexible and automated pipelines for generating meaningful homologous relationships within and between these (meta)genomes. Such relationships, or lack thereof, are crucial for differentiating between microbial organisms and environments at compositional, functional and phylogenetic levels. Metaphor is a standalone application that identifies core genes, unique genes, orthologs and paralogs in complex genomic datasets. It is not only limited to isolate genomes, but can also be applied to metagenomes due to its flexible implementation of Bi-directional Best Hit analysis. Thus, Metaphor can be used for a variety of functional and phylogenetic applications on a multitude of (meta)genome datasets.
