On June 3, 2020 BostonGene Corporation, a biomedical software company focused on defining optimal precision medicine-based therapies for cancer patients, reported that three abstracts were selected for poster presentations at the 2020 American Association for Cancer Research (AACR) (Free AACR Whitepaper) Virtual Annual Meeting II, which will be conducted from June 22 – 24, 2020 (Press release, BostonGene, JUN 3, 2020, View Source [SID1234560803]).
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The presentations describe findings obtained by using BostonGene’s technologies and analytical tools designed to improve diagnosis and treatment decisions for cancer patients. Results include validation of bulk RNAseq utility for accurate reconstruction of tumor microenvironment and identification of four prominent microenvironment types conserved among solid tumors. Application of BostonGene computational tools lead to better understanding of the role of microenvironment compartments in tumor pathogenesis and supporting clinical decision making for the treatment of cancer.
"We are excited to present at the 2020 AACR (Free AACR Whitepaper) Virtual Annual Meeting to share the clinical utility of the BostonGene solution and demonstrate how it improves diagnosis and treatment decisions for cancer patients," said Andrew Feinberg, President and CEO of BostonGene.
Details of the poster presentations are as follows:
Abstract Number: 6168
Title: Integrated whole exome and transcriptome analyses of the tumor and microenvironment provide new opportunities for rational design of cancer therapy
Session: Tumor Heterogeneity and Microenvironment: Next-Generation Sequencing, Single Cell, and Imaging
Poster: 4418
Presenter: Alexander Bagaev, BostonGene
BostonGene developed and validated a new analytic platform for multi-parametric analyses of malignant and nonmalignant tumor compartments using genomic and transcriptomic sequencing data. Application of BostonGene platform to more than 8,500 patient data sets revealed four types of tumor microenvironment (TME) that are conserved across cancer types and demonstrate high prognostic significance and differential response to immunotherapy. This novel Molecular-Functional (MF) portrait platform, involving analytic and visualization methods, provides a robust tool for prediction of response to immunotherapy and for future tailoring of personalized therapeutic combinations.
Abstract Number: 6997
Title: Novel machine learning based deconvolution algorithm results in accurate description of tumor microenvironment from bulk RNAseq
Session: Machine Learning and Artificial Intelligence for Omics, Imaging, and Diagnostics
Poster: 853
Presenter: Alexander Bagaev, BostonGene
BostonGene developed a novel machine learning-based algorithm for cellular deconvolution of tumor microenvironment (TME) from bulk RNAseq data. This tool accurately reconstructs proportions of major immune and stromal cell populations, as well as T cell subtypes and M1 and M2 macrophages. Validation of BostonGene algorithm performance by comparison of flow cytometry, single cell RNAseq and bulk RNAseq analysis performed on samples from different tissues will be presented. The result demonstrates utility of bulk RNAseq for accurate and robust reconstruction of TME composition and paves the road for application of the BostonGene computational tool for support of clinical decision making for the treatment of cancer.
Research conducted with Massachusetts General Hospital
Abstract Number: 7544
Title: HER2 expression and M2-like tumor infiltrating macrophages associated with Cabazitaxel activity in gastric cancer
Session: Predictive Biomarkers for Treatment Efficacy 1
Poster: 2011
Presenter: Sandipto Sarkar, Weill Cornell Medicine
In the clinical study of cabazitaxel efficacy in gastric cancer, comprehensive whole exome sequencing (WES) and RNAseq data analysis identified genetic aberrations and tumor microenvironment signatures associated with favorable response. In particular, this analysis resulted in identification of two novel biomarkers, HER2 overexpression and M2-high tumor macrophage signature, both of which associated with improved outcomes. RNAseq-based deconvolution demonstrating M2 macrophages enrichment in patients with improved PFS, was further validated by immunohistochemistry using M1 and M2 macrophage-specific markers.
Research conducted with Weill Cornell Medicine
The e-poster website will be launched June 22, 2020, the first day of the AACR (Free AACR Whitepaper) Virtual Annual Meeting II. All e-posters will be made available for browsing on this date.
Additionally the abstracts will be published in an online-only Proceedings supplement to the AACR (Free AACR Whitepaper) journal Cancer Research after the completion of the AACR (Free AACR Whitepaper) Virtual Annual Meeting II.