Dataset Information

Drug-microenvironment perturbations reveal resistance mechanisms and prognostic subgroups in CLL.

ABSTRACT: The tumour microenvironment and genetic alterations collectively influence drug efficacy in cancer, but current evidence is limited and systematic analyses are lacking. Using chronic lymphocytic leukaemia (CLL) as a model disease, we investigated the influence of 17 microenvironmental stimuli on 12 drugs in 192 genetically characterised patient samples. Based on microenvironmental response, we identified four subgroups with distinct clinical outcomes beyond known prognostic markers. Response to multiple microenvironmental stimuli was amplified in trisomy 12 samples. Trisomy 12 was associated with a distinct epigenetic signature. Bromodomain inhibition reversed this epigenetic profile and could be used to target microenvironmental signalling in trisomy 12 CLL. We quantified the impact of microenvironmental stimuli on drug response and their dependence on genetic alterations, identifying interleukin 4 (IL4) and Toll-like receptor (TLR) stimulation as the strongest actuators of drug resistance. IL4 and TLR signalling activity was increased in CLL-infiltrated lymph nodes compared with healthy samples. High IL4 activity correlated with faster disease progression. The publicly available dataset can facilitate the investigation of cell-extrinsic mechanisms of drug resistance and disease progression.

SUBMITTER: Bruch PM

PROVIDER: S-EPMC9372727 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

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Drug-microenvironment perturbations reveal resistance mechanisms and prognostic subgroups in CLL.

Bruch Peter-Martin PM Giles Holly Ar HA Kolb Carolin C Herbst Sophie A SA Becirovic Tina T Roider Tobias T Lu Junyan J Scheinost Sebastian S Wagner Lena L Huellein Jennifer J Berest Ivan I Kriegsmann Mark M Kriegsmann Katharina K Zgorzelski Christiane C Dreger Peter P Zaugg Judith B JB Müller-Tidow Carsten C Zenz Thorsten T Huber Wolfgang W Dietrich Sascha S

Molecular systems biology 20220801 8

The tumour microenvironment and genetic alterations collectively influence drug efficacy in cancer, but current evidence is limited and systematic analyses are lacking. Using chronic lymphocytic leukaemia (CLL) as a model disease, we investigated the influence of 17 microenvironmental stimuli on 12 drugs in 192 genetically characterised patient samples. Based on microenvironmental response, we identified four subgroups with distinct clinical outcomes beyond known prognostic markers. Response to ...[more]

PMID: 35959629

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Project description:Objective: Acute myeloid leukemia (AML) is a malignant hematologic cancer with poor prognosis. Emerging evidence suggests a close association between AML progression and hypoxia. The purpose of this study was to establish a new risk prognostic model for AML based on hypoxia-related genes, and to explore the mechanisms by which hypoxia-related genes affect the prognosis of AML based on tumor immune microenvironment (TIME) and drug resistance. Methods: The AML patient samples obtained from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database were classified into C1 and C2 based on hypoxia-related genes, followed by analysis utilizing Gene Ontology (GO), Kyoto Encyclopaedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA). Through univariate and LASSO Cox regression analysis, the hypoxia-related hub genes 26S proteasome non-ATPase regulatory subunit 11 (PSMD11) and 26S proteasome non-ATPase regulatory subunit 14 (PSMD14) were identified to construct the model. AML patient samples were obtained from the TARGET and The Cancer Genome Atlas (TCGA) databases, serving as the training and the validation sets, and were stratified into high-risk and low-risk group according to the median risk score. The correlations between the model and TIME and anti-tumor drugs were analysed using CIBERSORT and Genomics of Drug Sensitivity in Cancer (GDSC) databases. The expressions of PSMD11/PSMD14 in clinical samples and AML sensitive and drug-resistant cell lines were detected by Western blot and real-time PCR. Results: The C1 group with high expression of hypoxia-related genes had lower overall survival (OS). Immune-related signaling pathways were different between C1/C2, and hypoxia was positively correlated with the activation of mammalian target of rapamycin (mTOR) signaling pathway. The model had good accuracy in both the training and the validation sets. The high-risk group exhibited lower OS and TIME activity, and was more sensitive to several anti-tumor drugs. PSMD11/PSMD14 were highly expressed in relapsed patients and AML drug-resistant cell lines. Conclusion: The established novel risk prognostic model and experiment results offer valuable insights for predicting AML prognosis and guiding drug selection. It also provides a fundamental framework for the mechanisms through which hypoxia impacts AML prognosis by modulating TIME and drug resistance.

Dataset Information

Drug-microenvironment perturbations reveal resistance mechanisms and prognostic subgroups in CLL.

Publications

Drug-microenvironment perturbations reveal resistance mechanisms and prognostic subgroups in CLL.

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