PMID: 26776204Jan 19, 2016Paper

ONE-CLASS DETECTION OF CELL STATES IN TUMOR SUBTYPES

Pacific Symposium on Biocomputing
Artem SokolovJoshua M Stuart

Abstract

The cellular composition of a tumor greatly influences the growth, spread, immune activity, drug response, and other aspects of the disease. Tumor cells are usually comprised of a heterogeneous mixture of subclones, each of which could contain their own distinct character. The presence of minor subclones poses a serious health risk for patients as any one of them could harbor a fitness advantage with respect to the current treatment regimen, fueling resistance. It is therefore vital to accurately assess the make-up of cell states within a tumor biopsy. Transcriptome-wide assays from RNA sequencing provide key data from which cell state signatures can be detected. However, the challenge is to find them within samples containing mixtures of cell types of unknown proportions. We propose a novel one-class method based on logistic regression and show that its performance is competitive to two established SVM-based methods for this detection task. We demonstrate that one-class models are able to identify specific cell types in heterogeneous cell populations better than their binary predictor counterparts. We derive one-class predictors for the major breast and bladder subtypes and reaffirm the connection between these two tissues. In...Continue Reading

Related Concepts

Related Feeds

Bladder Carcinoma In Situ

Bladder Carcinoma In Situ is a superficial bladder cancer that occurs on the surface layer of the bladder. Discover the latest research on this precancerous condition in this feed.

CZI Human Cell Atlas Seed Network

The aim of the Human Cell Atlas (HCA) is to build reference maps of all human cells in order to enhance our understanding of health and disease. The Seed Networks for the HCA project aims to bring together collaborators with different areas of expertise in order to facilitate the development of the HCA. Find the latest research from members of the HCA Seed Networks here.

Cancer -Omics

A variety of different high-throughput technologies can be used to identify the complete catalog of changes that characterize the molecular profile of cohorts of tumor samples. Discover the latest insights gained from cancer 'omics' in this feed.