Dataset Information

Therapy-Induced Evolution of Human Lung Cancer Revealed by Single-Cell RNA Sequencing.

ABSTRACT: Lung cancer, the leading cause of cancer mortality, exhibits heterogeneity that enables adaptability, limits therapeutic success, and remains incompletely understood. Single-cell RNA sequencing (scRNA-seq) of metastatic lung cancer was performed using 49 clinical biopsies obtained from 30 patients before and during targeted therapy. Over 20,000 cancer and tumor microenvironment (TME) single-cell profiles exposed a rich and dynamic tumor ecosystem. scRNA-seq of cancer cells illuminated targetable oncogenes beyond those detected clinically. Cancer cells surviving therapy as residual disease (RD) expressed an alveolar-regenerative cell signature suggesting a therapy-induced primitive cell-state transition, whereas those present at on-therapy progressive disease (PD) upregulated kynurenine, plasminogen, and gap-junction pathways. Active T-lymphocytes and decreased macrophages were present at RD and immunosuppressive cell states characterized PD. Biological features revealed by scRNA-seq were biomarkers of clinical outcomes in independent cohorts. This study highlights how therapy-induced adaptation of the multi-cellular ecosystem of metastatic cancer shapes clinical outcomes.

SUBMITTER: Maynard A

PROVIDER: S-EPMC7484178 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Therapy-Induced Evolution of Human Lung Cancer Revealed by Single-Cell RNA Sequencing.

Maynard Ashley A McCoach Caroline E CE Rotow Julia K JK Harris Lincoln L Haderk Franziska F Kerr D Lucas DL Yu Elizabeth A EA Schenk Erin L EL Tan Weilun W Zee Alexander A Tan Michelle M Gui Philippe P Lea Tasha T Wu Wei W Urisman Anatoly A Jones Kirk K Sit Rene R Kolli Pallav K PK Seeley Eric E Gesthalter Yaron Y Le Daniel D DD Yamauchi Kevin A KA Naeger David M DM Bandyopadhyay Sourav S Shah Khyati K Cech Lauren L Thomas Nicholas J NJ Gupta Anshal A Gonzalez Mayra M Do Hien H Tan Lisa L Bacaltos Bianca B Gomez-Sjoberg Rafael R Gubens Matthew M Jahan Thierry T Kratz Johannes R JR Jablons David D Neff Norma N Doebele Robert C RC Weissman Jonathan J Blakely Collin M CM Darmanis Spyros S Bivona Trever G TG

Cell 20200820 5

Lung cancer, the leading cause of cancer mortality, exhibits heterogeneity that enables adaptability, limits therapeutic success, and remains incompletely understood. Single-cell RNA sequencing (scRNA-seq) of metastatic lung cancer was performed using 49 clinical biopsies obtained from 30 patients before and during targeted therapy. Over 20,000 cancer and tumor microenvironment (TME) single-cell profiles exposed a rich and dynamic tumor ecosystem. scRNA-seq of cancer cells illuminated targetable ...[more]

PMID: 32822576

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Project description:BackgroundSevere acute pancreatitis (SAP) is characterized by inflammation, with inflammatory immune cells playing a pivotal role in disease progression. This study aims to understand variations in specific immune cell subtypes in SAP, uncover their mechanisms of action, and identify potential biological markers for predicting Acute Pancreatitis (AP) severity.MethodsWe collected peripheral blood from 7 untreated SAP patients and employed single-cell RNA sequencing for the first time to construct a transcriptome atlas of peripheral blood mononuclear cells (PBMCs) in SAP. Integrating SAP transcriptomic data with 6 healthy controls from the GEO database facilitated the analysis of immune cell roles in SAP. We obtained comprehensive transcriptomic datasets from AP samples in the GEO database and identified potential biomarkers associated with AP severity using the "Scissor" tool in single-cell transcriptomic data.ResultsThis study presents the inaugural construction of a peripheral blood single-cell atlas for SAP patients, identifying 20 cell subtypes. Notably, there was a significant decrease in effector T cell subsets and a noteworthy increase in monocytes compared to healthy controls. Moreover, we identified a novel monocyte subpopulation expressing high levels of PPBP and PF4 which was significantly elevated in SAP. The proportion of monocyte subpopulations with high CCL3 expression was also markedly increased compared to healthy controls, as verified by flow cytometry. Additionally, cell communication analysis revealed insights into immune and inflammation-related signaling pathways in SAP patient monocytes. Finally, our findings suggest that the subpopulation with high CCL3 expression, along with upregulated pro-inflammatory genes such as S100A12, IL1B, and CCL3, holds promise as biomarkers for predicting AP severity.ConclusionThis study reveals monocytes' crucial role in SAP initiation and progression, characterized by distinct pro-inflammatory features intricately linked to AP severity. A monocyte subpopulation with elevated PPBP and CCL3 levels emerges as a potential biomarker and therapeutic target.

Dataset Information

Therapy-Induced Evolution of Human Lung Cancer Revealed by Single-Cell RNA Sequencing.

Publications

Therapy-Induced Evolution of Human Lung Cancer Revealed by Single-Cell RNA Sequencing.

Similar Datasets

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