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Dataset Information

Deep Transcriptome Profiling of Multiple Myeloma Using Quantitative Phenotypes.


ABSTRACT:

Background

Transcriptome studies are gaining momentum in genomic epidemiology, and the need to incorporate these data in multivariable models alongside other risk factors brings demands for new approaches.

Methods

Here we describe SPECTRA, an approach to derive quantitative variables that capture the intrinsic variation in gene expression of a tissue type. We applied the SPECTRA approach to bulk RNA sequencing from malignant cells (CD138+) in patients from the Multiple Myeloma Research Foundation CoMMpass study.

Results

A set of 39 spectra variables were derived to represent multiple myeloma cells. We used these variables in predictive modeling to determine spectra-based risk scores for overall survival, progression-free survival, and time to treatment failure. Risk s

SUBMITTER: Griffin R 

PROVIDER: S-EPMC10150248 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature