RNAseq-based Biomarkers for Ex Vivo Drug Response

The approach begins with a bone marrow specimen donated by a multiple myeloma patient, which is sorted for CD138+ (surface marker for plasma cells) cells. These patient-derived tumor cells are profiled functionally (ex vivo framework), molecularly (transcriptomic framework), and the association between the two assessed.

 

Ex Vivo Framework: Patient-derived CD138+ cells are co-cultured with bone marrow stromal cells and patient plasma in an ex vivo reconstruction of the tumor microenvironment and seeded with over 31 drugs, at five different concentrations, in a multi-well plate, where each well is live-imaged once every 30 minutes for upto 6 days. These images are analyzed to quantify a patient’s ex vivo cell viability for several drugs. Over the past few years, we were able to quantify ex vivo drug sensitivity to over 500 myeloma patients tested with several standard-of-care and experimental drugs. For more details on the ex vivo framework, please see EMMA.

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Transcriptomic Framework: Patient-derived CD138+ cells are molecularly characterized by sequencing tumor RNA. Gene expression profiles from 844 patients were used to create a transcriptomic landscape (tSNE) of multiple myeloma featuring 16,738 protein coding genes and co-expressing gene programs using fuzzy c-means clustering are identified.

 

Molecular - Functional Relationship: Each co-expressing gene program's functionals association with ex vivo response to a given drug is determined by carrying out gene set enrichment analysis (GSEA) , where the enrichment scores are determined by estimating  running-sum statistics of correlation between expression of genes in each program and ex vivo response. Gene programs shown in red are enriched for ex vivo resistance and gene programs shown in blue are enriched for ex vivo sensitivity.

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Associations between gene programs enriched for ex vivo resistance/sensitivity and known biological pathways such as Cancer Hallmarks and KEGG pathways can be determined using hypergeometric tests of representation. More importantly, the gene programs have the potential to represent yet to be discovered biology associated with mechanisms of response to drugs in multiple myeloma. The discovery of this unknown biology is explored by studying the underlying Gene Regulatory Networks.