Single-cell analysis of targeted transcriptome predicts drug sensitivity of single cells within human myeloma tumors

A. K. Mitra, U. K. Mukherjee, T. Harding, J. S. Jang, H. Stessman, Y. Li, Alexej Abyzov, Jin Jen, Shaji K Kumar, S Vincent Rajkumar, B. Van Ness

Research output: Contribution to journalArticle

23 Citations (Scopus)

Abstract

Multiple myeloma (MM) is characterized by significant genetic diversity at subclonal levels that have a defining role in the heterogeneity of tumor progression, clinical aggressiveness and drug sensitivity. Although genome profiling studies have demonstrated heterogeneity in subclonal architecture that may ultimately lead to relapse, a gene expression-based prediction program that can identify, distinguish and quantify drug response in sub-populations within a bulk population of myeloma cells is lacking. In this study, we performed targeted transcriptome analysis on 528 pre-treatment single cells from 11 myeloma cell lines and 418 single cells from 8 drug-naïve MM patients, followed by intensive bioinformatics and statistical analysis for prediction of proteasome inhibitor sensitivity in individual cells. Using our previously reported drug response gene expression profile signature at the single-cell level, we developed an R Statistical analysis package available at https://github.com/bvnlabSCATTome, SCATTome (single-cell analysis of targeted transcriptome), that restructures the data obtained from Fluidigm single-cell quantitative real-time-PCR analysis run, filters missing data, performs scaling of filtered data, builds classification models and predicts drug response of individual cells based on targeted transcriptome using an assortment of machine learning methods. Application of SCATT should contribute to clinically relevant analysis of intratumor heterogeneity, and better inform drug choices based on subclonal cellular responses.

Original languageEnglish (US)
Pages (from-to)1094-1102
Number of pages9
JournalLeukemia
Volume30
Issue number5
DOIs
StatePublished - May 1 2016

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Single-Cell Analysis
Transcriptome
Pharmaceutical Preparations
Neoplasms
Multiple Myeloma
Proteasome Inhibitors
Gene Expression Profiling
Computational Biology
Population
Real-Time Polymerase Chain Reaction
Genome
Gene Expression
Recurrence
Cell Line

ASJC Scopus subject areas

  • Hematology
  • Cancer Research
  • Anesthesiology and Pain Medicine

Cite this

Mitra, A. K., Mukherjee, U. K., Harding, T., Jang, J. S., Stessman, H., Li, Y., ... Van Ness, B. (2016). Single-cell analysis of targeted transcriptome predicts drug sensitivity of single cells within human myeloma tumors. Leukemia, 30(5), 1094-1102. https://doi.org/10.1038/leu.2015.361

Single-cell analysis of targeted transcriptome predicts drug sensitivity of single cells within human myeloma tumors. / Mitra, A. K.; Mukherjee, U. K.; Harding, T.; Jang, J. S.; Stessman, H.; Li, Y.; Abyzov, Alexej; Jen, Jin; Kumar, Shaji K; Rajkumar, S Vincent; Van Ness, B.

In: Leukemia, Vol. 30, No. 5, 01.05.2016, p. 1094-1102.

Research output: Contribution to journalArticle

Mitra, AK, Mukherjee, UK, Harding, T, Jang, JS, Stessman, H, Li, Y, Abyzov, A, Jen, J, Kumar, SK, Rajkumar, SV & Van Ness, B 2016, 'Single-cell analysis of targeted transcriptome predicts drug sensitivity of single cells within human myeloma tumors', Leukemia, vol. 30, no. 5, pp. 1094-1102. https://doi.org/10.1038/leu.2015.361
Mitra, A. K. ; Mukherjee, U. K. ; Harding, T. ; Jang, J. S. ; Stessman, H. ; Li, Y. ; Abyzov, Alexej ; Jen, Jin ; Kumar, Shaji K ; Rajkumar, S Vincent ; Van Ness, B. / Single-cell analysis of targeted transcriptome predicts drug sensitivity of single cells within human myeloma tumors. In: Leukemia. 2016 ; Vol. 30, No. 5. pp. 1094-1102.
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