Dataset Information

Single-cell mRNA sequencing identifies subclonal heterogeneity in anti-cancer drug responses of lung adenocarcinoma cells.

ABSTRACT: BACKGROUND:Intra-tumoral genetic and functional heterogeneity correlates with cancer clinical prognoses. However, the mechanisms by which intra-tumoral heterogeneity impacts therapeutic outcome remain poorly understood. RNA sequencing (RNA-seq) of single tumor cells can provide comprehensive information about gene expression and single-nucleotide variations in individual tumor cells, which may allow for the translation of heterogeneous tumor cell functional responses into customized anti-cancer treatments. RESULTS:We isolated 34 patient-derived xenograft (PDX) tumor cells from a lung adenocarcinoma patient tumor xenograft. Individual tumor cells were subjected to single cell RNA-seq for gene expression profiling and expressed mutation profiling. Fifty tumor-specific single-nucleotide variations, including KRAS(G12D), were observed to be heterogeneous in individual PDX cells. Semi-supervised clustering, based on KRAS(G12D) mutant expression and a risk score representing expression of 69 lung adenocarcinoma-prognostic genes, classified PDX cells into four groups. PDX cells that survived in vitro anti-cancer drug treatment displayed transcriptome signatures consistent with the group characterized by KRAS(G12D) and low risk score. CONCLUSIONS:Single-cell RNA-seq on viable PDX cells identified a candidate tumor cell subgroup associated with anti-cancer drug resistance. Thus, single-cell RNA-seq is a powerful approach for identifying unique tumor cell-specific gene expression profiles which could facilitate the development of optimized clinical anti-cancer strategies.

SUBMITTER: Kim KT

PROVIDER: S-EPMC4506401 | biostudies-literature | 2015 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Single-cell mRNA sequencing identifies subclonal heterogeneity in anti-cancer drug responses of lung adenocarcinoma cells.

Kim Kyu-Tae KT Lee Hye Won HW Lee Hae-Ock HO Kim Sang Cheol SC Seo Yun Jee YJ Chung Woosung W Eum Hye Hyeon HH Nam Do-Hyun DH Kim Junhyong J Joo Kyeung Min KM Park Woong-Yang WY

Genome biology 20150619

<h4>Background</h4>Intra-tumoral genetic and functional heterogeneity correlates with cancer clinical prognoses. However, the mechanisms by which intra-tumoral heterogeneity impacts therapeutic outcome remain poorly understood. RNA sequencing (RNA-seq) of single tumor cells can provide comprehensive information about gene expression and single-nucleotide variations in individual tumor cells, which may allow for the translation of heterogeneous tumor cell functional responses into customized anti ...[more]

PMID: 26084335

Similar Datasets

Project description:ObjectiveSynovial membrane inflammation is common in osteoarthritis (OA) and increases cartilage injury. However, synovial fluid and histology studies suggest that OA inflammatory responses are not homogeneous. Greater understanding of these responses may provide new insights into OA disease mechanisms. We undertook this study to develop a novel multiparameter approach to phenotype synovial responses in knee OA.MethodsCell composition and soluble protein production were measured by flow cytometry and multiplex enzyme-linked immunosorbent assay in synovium collected from OA patients undergoing knee replacement surgery (n = 35).ResultsTesting disaggregation conditions showed that aggressive digestion improved synovial cell yield and mesenchymal staining by flow cytometry, but it negatively impacted CD4+ T cell and CD56+ natural killer cell staining. Less aggressive digestion preserved these markers and showed highly variable T cell infiltration (range 0-43%; n = 32). Correlation analysis identified mesenchymal subpopulations associated with different nonmesenchymal populations, including macrophages and T cells (CD45+CD11b+HLA-DR+ myeloid cells with PDPN+CD73+CD90-CD34- mesenchymal cells [r = 0.65, P < 0.0001]; and CD45+CD3+ T cells with PDPN+CD73+CD90+CD34+ mesenchymal cells [r = 0.50, P = 0.003]). Interleukin-6 (IL-6) measured by flow cytometry strongly correlated with IL-6 released by ex vivo culture of synovial tissue (r = 0.59, P = 0.0012) and was highest in mesenchymal cells coexpressing CD90 and CD34. IL-6, IL-8, complement factor D, and IL-10 release correlated positively with tissue cellularity (P = 0.0042, P = 0.018, P = 0.0012, and P = 0.038, respectively). Additionally, increased CD8+ T cell numbers correlated with retinol binding protein 4 (P = 0.033). Finally, combining flow cytometry and multiplex data identified patient clusters with different types of inflammatory responses.ConclusionWe used a novel approach to analyze OA synovium, identifying patient-specific inflammatory clusters. Our findings indicate that phenotyping synovial inflammation may provide new insights into OA patient heterogeneity and biomarker development.

Dataset Information

Single-cell mRNA sequencing identifies subclonal heterogeneity in anti-cancer drug responses of lung adenocarcinoma cells.

Publications

Single-cell mRNA sequencing identifies subclonal heterogeneity in anti-cancer drug responses of lung adenocarcinoma cells.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets