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Genome-scale knockout simulation and clustering analysis of drug-resistant breast cancer cells reveal drug sensitization targets

ABSTRACT: Anticancer chemotherapy is an essential part of cancer treatment, but the emergence of resistance remains a major hurdle. Metabolic reprogramming is a notable phenotype associated with the acquisition of drug resistance. Here, we develop a computational framework that predicts metabolic gene targets capable of reverting the metabolic state of drug-resistant cells to that of drug-sensitive parental cells, thereby sensitizing the resistant cells. The computational framework performs single-gene knockout simulation of genome-scale metabolic models that predicts genome-wide metabolic flux distribution in drug-resistant cells, and clusters the resulting knockout flux data using uniform manifold approximation and projection. From the clustering analysis, knockout genes that lead to the flux data near that of drug-sensitive cells are considered drug sensitization targets. This computational approach is demonstrated using doxorubicin- and paclitaxel-resistant MCF7 breast cancer cells. Drug sensitization targets are further refined based on proteome and metabolome data, which generate GOT1 for doxorubicin-resistant MCF7, GPI for paclitaxel-resistant MCF7, and SLC1A5 as a common target. These targets are experimentally validated where inhibiting their expression results in increased sensitivity of drug-resistant cells to doxorubicin or paclitaxel. Taken together, the computational framework predicts drug sensitization targets in an intuitive and cost-efficient manner and can be applied to overcome drug-resistant cells associated with various cancers and other metabolic diseases.

ORGANISM(S): Homo sapiens

PROVIDER: GSE288840 | GEO | 2025/04/30

REPOSITORIES: GEO

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Project description:Silencing of genes that suppress the malignant phenotype by DNA methylation spurred an interest in the clinical use of epigenetic reprogramming agents. Single therapy is unlikely to be curative in the context of a heterogeneous disease such as Diffuse Large B cell Lymphomas (DLBCL). The combination of DNA demethylating drugs could increase the chance to respond to classical and new treatments. We found that DLBCL cell lines respond heterogeneously to DNA demethylating agents. In sensitive cell lines, 5-aza-2’-deoxycytidine induced a genomic signature similar to that of doxorubicin, the most important drug of the combinatorial chemotherapy regimen for DLBCL treatment. Accordingly, the combination of 5-aza-2’-deoxycytidine and doxorubicin proved to be synergistic in cell killing in vitro and in vivo for DLBCL cell lines individually responsive to these drugs. In doxorubicin resistant cell lines, long-term exposure to low-dose of 5-aza-2’-deoxycytidine induces DNA demethylation and subsequent doxorubicin sensitization in vitro and in vivo. This later effect correlates with SMAD1 demethylation. SMAD1 is epigenetically silenced in doxorubicin-resistant DLBCL cells and DLBCL patients with poor prognostic. In addition, we found that DNA demethylating agents can sensitize primary DLBCL cells to doxorubicin. Primary cells obtained from a DLBCL patient treated with 5-azacytidine shows SMAD1 demethylation and ex vivo sensitization to multiple drugs. Therefore, DNA demethylating drugs can reprogram otherwise resistant DLBCL cells to respond to chemotherapy agents without increasing the toxicity to normal tissues. Our data also indicate that DNA methylation and consequent suppression of SMAD1 expression represent a previously undescribed molecular mechanism of chemoresistance in DLBCL that can be further exploit for therapy. A microarray study using genomic DNA from different DLBCL cell lines before any treatment. Two to four biological replicates by cell line. The HELP data wil be used to find genes hypermethylated in resistant cell lines compared to sensitive cell lines to doxorubicin and other drugs.

Project description:Silencing of genes that suppress the malignant phenotype by DNA methylation spurred an interest in the clinical use of epigenetic reprogramming agents. Single therapy is unlikely to be curative in the context of a heterogeneous disease such as Diffuse Large B cell Lymphomas (DLBCL). The combination of DNA demethylating drugs could increase the chance to respond to classical and new treatments. We found that DLBCL cell lines respond heterogeneously to DNA demethylating agents. In sensitive cell lines, 5-aza-2M-bM-^@M-^Y-deoxycytidine induced a genomic signature similar to that of doxorubicin, the most important drug of the combinatorial chemotherapy regimen for DLBCL treatment. Accordingly, the combination of 5-aza-2M-bM-^@M-^Y-deoxycytidine and doxorubicin proved to be synergistic in cell killing in vitro and in vivo for DLBCL cell lines individually responsive to these drugs. In doxorubicin resistant cell lines, long-term exposure to low-dose of 5-aza-2M-bM-^@M-^Y-deoxycytidine induces DNA demethylation and subsequent doxorubicin sensitization in vitro and in vivo. This later effect correlates with SMAD1 demethylation. SMAD1 is epigenetically silenced in doxorubicin-resistant DLBCL cells and DLBCL patients with poor prognostic. In addition, we found that DNA demethylating agents can sensitize primary DLBCL cells to doxorubicin. Primary cells obtained from a DLBCL patient treated with 5-azacytidine shows SMAD1 demethylation and ex vivo sensitization to multiple drugs. Therefore, DNA demethylating drugs can reprogram otherwise resistant DLBCL cells to respond to chemotherapy agents without increasing the toxicity to normal tissues. Our data also indicate that DNA methylation and consequent suppression of SMAD1 expression represent a previously undescribed molecular mechanism of chemoresistance in DLBCL that can be further exploit for therapy. A microarray study using double-stranded cDNA from different DLBCL cell lines before any treatment. Two biological replicates by cell line. The gene expression will be used to find gene expression signatures between sensitive and resistant cell lines to chemotherapeutics.

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Genome-scale knockout simulation and clustering analysis of drug-resistant breast cancer cells reveal drug sensitization targets

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