The Long Non Coding RNA SAMMSON is a regulator of chemosensitivity and metabolic orientation in doxorubicin resistant breast cancer cells
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ABSTRACT:
PROVIDER: PRJNA778738 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR16854231.fastq.gz | Fastqsanger.gz | |||
| SRR16854232.fastq.gz | Fastqsanger.gz | |||
| SRR16854233.fastq.gz | Fastqsanger.gz | |||
| SRR16854234.fastq.gz | Fastqsanger.gz | |||
| SRR16854235.fastq.gz | Fastqsanger.gz |
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Project description:Despite improvements in therapeutic strategies for treating breast cancers, tumor relapse and chemoresistance remain major issues in patient outcomes. Indeed, cancer cells display a metabolic plasticity allowing a quick adaptation to tumoral microenvironment and to cellular stresses induced by chemotherapy. Recently, long non-coding RNA molecules (lncRNAs) have emerged as important regulators of cellular metabolic orientation. In the present study, we addressed the role of the long non-coding RNA molecule (lncRNA) SAMMSON on the metabolic reprogramming and chemoresistance of MCF-7 breast cancer cells resistant to doxorubicin (MCF-7dox). Our results showed an overexpression of SAMMSON in MCF-7dox compared to doxorubicin-sensitive cells (MCF-7). Silencing of SAMMSON expression by siRNA in MCF-7dox cells resulted in a metabolic rewiring with improvement of oxidative metabolism, decreased mitochondrial ROS production, increased mitochondrial replication, transcription and translation and an attenuation of chemoresistance. These results highlight the role of SAMMSON in the metabolic adaptations leading to the development of chemoresistance in breast cancer cells. Thus, targeting SAMMSON expression levels represents a promising therapeutic route to circumvent doxorubicin resistance in breast cancers.
2021-11-10 | GSE188404 | GEO
Project description:Despite improvements in therapeutic strategies for treating breast cancers, tumor relapse and chemoresistance remain major issues in patient outcomes. Indeed, cancer cells display a metabolic plasticity allowing a quick adaptation to the tumoral microenvironment and to cellular stresses induced by chemotherapy. Recently, long non-coding RNA molecules (lncRNAs) have emerged as important regulators of cellular metabolic orientation. In the present study, we addressed the role of the long non-coding RNA molecule (lncRNA) SAMMSON on the metabolic reprogramming and chemoresistance of MCF-7 breast cancer cells resistant to doxorubicin (MCF-7dox). Our results showed an overexpression of SAMMSON in MCF-7dox compared to doxorubicin-sensitive cells (MCF-7). Silencing of SAMMSON expression by siRNA in MCF-7dox cells resulted in a metabolic rewiring with improvement of oxidative metabolism, decreased mitochondrial ROS production, increased mitochondrial replication, transcription and translation and an attenuation of chemoresistance. These results highlight the role of SAMMSON in the metabolic adaptations leading to the development of chemoresistance in breast cancer cells. Thus, targeting SAMMSON expression levels represents a promising therapeutic route to circumvent doxorubicin resistance in breast cancers.
| S-EPMC8615054 | biostudies-literature
Project description:Transarterial chemoembolization or systemic chemotherapy with doxorubicin has been the treatment of choice for unresectable hepatocellular carcinoma (HCC) conferring the best survival benefit. However, HCC is notorious for its predisposition to develop therapeutic tolerance. Thus, Affymetrix microarray analysis was performed on doxorubicin-resistant hepatoma cells to identify the drug resistance-related genes. The RNA isolated from primary hepatoma cells and their doxorubicin-resistant counterparts, then subjected to Affymetrix microarray analysis to identify the differential expression profiles of drug resistance-related genes.
2019-01-17 | GSE125180 | GEO
Project description:In an effort to develop a genomics-based approach to the prediction of drug response, we have developed an algorithm for classification of cell line chemosensitivity based on gene expression profiles alone. Using oligonucleotide microarrays, the expression levels of 6,817 genes were measured in a panel of 60 human cancer cell lines (the NCI-60) for which the chemosensitivity profiles of thousands of chemical compounds have been determined. We sought to determine whether the gene expression signatures of untreated cells were sufficient for the prediction of chemosensitivity. Gene expression-based classifiers of sensitivity or resistance for 232 compounds were generated and then evaluated on independent sets of data. The classifiers were designed to be independent of the cells' tissue of origin. The accuracy of chemosensitivity prediction was considerably better than would be expected by chance. Eighty-eight of 232 expression-based classifiers performed accurately (with P < 0.05) on an independent test set, whereas only 12 of the 232 would be expected to do so by chance. These results suggest that at least for a subset of compounds genomic approaches to chemosensitivity prediction are feasible. golub-00299 Assay Type: Gene Expression Provider: Affymetrix Array Designs: Hu6800 Organism: Homo sapiens (ncbitax) Tissue Sites: Kidney, Brain, Blood, Lung, Skin, Colon, Breast, Prostate, Ovary Material Types: cell, synthetic_RNA, whole_organism, total_RNA Disease States: Carcinoma, Glioblastoma, Lymphoma, Adenocarcinoma, Melanoma, Amelanotic Melanoma, Large Cell Carcinoma, Precursor Lymphoblastic Leukemia, Carcinosarcoma, Myeloid Leukemia, Plasma Cell Myeloma, Bronchogenic Carcinoma, Chronic Myelogenous Leukemia, Squamous Cell Carcinoma
2015-05-16 | E-GEOD-68936 | biostudies-arrayexpress
Project description:In an effort to develop a genomics-based approach to the prediction of drug response, we have developed an algorithm for classification of cell line chemosensitivity based on gene expression profiles alone. Using oligonucleotide microarrays, the expression levels of 6,817 genes were measured in a panel of 60 human cancer cell lines (the NCI-60) for which the chemosensitivity profiles of thousands of chemical compounds have been determined. We sought to determine whether the gene expression signatures of untreated cells were sufficient for the prediction of chemosensitivity. Gene expression-based classifiers of sensitivity or resistance for 232 compounds were generated and then evaluated on independent sets of data. The classifiers were designed to be independent of the cells' tissue of origin. The accuracy of chemosensitivity prediction was considerably better than would be expected by chance. Eighty-eight of 232 expression-based classifiers performed accurately (with P < 0.05) on an independent test set, whereas only 12 of the 232 would be expected to do so by chance. These results suggest that at least for a subset of compounds genomic approaches to chemosensitivity prediction are feasible.
2015-05-16 | GSE68936 | GEO
Project description:The transcriptomic profiles of two resistant (HT and OCI-LY3) and two sensitive (SUDHL5 and OCI-LY19) DLBCL cell lines before and after doxorubicin treatment were analysed by RNA-seq. To further investigate the molecular basis underlying the development of doxorubicin resistance, acquired doxorubicin-resistant cells (OCI-LY19R) were generated by periodically treating the parental doxorubicin-sensitive OCI-LY19 cells (OCI-LY19S) with increasing doses of doxorubicin over a prolonged period till its IC50 exceeded 200 nM. RNA-seq analysis was then performed using OCI-LY19R and OCI-LY19S cell lines to examine the transcriptomic changes following acquisition of doxorubicin resistance.
2022-12-01 | GSE215900 | GEO
Project description:Expression data from doxorubicin-resistant hepatoma cells
| PRJNA515485 | ENA
Project description:Doxorubicin resistance remains a major therapeutic challenge leading to treatment failure and poor survival prognosis in breast cancer. Although doxorubicin induces massive changes in the transcriptional landscape accompanied by alterations of chromatin accessibility are well known, potential diagnostic or therapeutic targets associated with three-dimensional (3D) genome reorganization in doxorubicin-resistant breast cancer cells have not yet been systematically investigated. Here we performed integrated analyses combining in situ high-throughput chromosome conformation capture (Hi-C), ATAC-seq and mHi-C data on doxorubicin-resistant MCF7 human breast cancer cells compared to parental cells. It revealed that A/B compartment switching was positively correlated to genome-wide differential gene expression, and the genome was spatially reorganized into smaller topologically associating domains (TADs) and loops. We also revealed the contribution of increased chromatin accessibility and potential transcription factor families, including CTCF and BORIS, to gained TAD boundaries and loop anchors. Intriguingly, we observed two condensed genomic regions (~20kb) with decreased chromatin accessibility flanking TAD boundaries, which might play a critical role in the formation or maintenance of TADs. Moreover, we identified a number of gained and lost enhancer-promoter interactions associated with differentially expressed genes, including FA2H, FOXA1, JRKL and EZH, some of which involved in chromatin organization and breast cancer signaling pathways. This study uncovered a close connection between 3D genome reorganization, chromatin accessibility as well as gene transcription, and provides resources and novel insights into the epigenomic mechanisms with potential therapeutic implications for doxorubicin resistance in breast cancer.
2022-06-14 | GSE205874 | GEO
Project description:Doxorubicin is considered to be the most effective chemotherapeutic drug used to treat breast cancer. Unfortunately, resistance to this drug is common, resulting in poor patient prognosis and survival. Dynamically reorganized chromatin allows rapid access of the gene regulatory machinery to open genomic regions facilitating subsequent gene expression through direct transcription factor (TF) activation and regulatory element binding. To better understand the regulatory network underlying doxorubicin resistance in breast cancer cells, we explored the systematic alterations of chromatin accessibility and gene expression by the assay for transposase-accessible chromatin using sequencing (ATAC-seq) in combination with RNA sequencing, followed by integrative analysis to identify potential regulators and their targets associated with differentially accessible regions (DARs) in doxorubicin-resistant MCF7 (MCF7-DR) cells. A total of 3963 differentially expressed genes (DEGs) related to doxorubicin resistance were identified, including dramatically up-regulated MT1E, GSTP1, LDHB, significantly down-regulated TFF1, UBB, DSCAM-AS1, and histone-modifying enzyme coding genes HDAC2, EZH2, PRMT5, etc. By integrating with transcriptomic datasets, we identified 18,228 DARs in MCF7-DR cells compared to control, which were positively (r = 0.6) correlated with their nearest DEGs. There were 11,686 increased chromatin-accessible regions, which were enriched in up-regulated genes related to diverse KEGG pathways, such as the cell cycle, regulation of actin cytoskeleton, signaling pathways of MAPK, PI3K/Akt and Hippo, which play essential roles in regulating cell apoptosis, proliferation, metabolism, and inflammatory responses. The 6,542 decreased chromatin-accessible regions were considered to be related to declined doxorubicin-associated biological processes, for instance, endocrine and insulin resistance, central carbon metabolism, signaling pathways of TGF-beta and P53. Analyses of the DAR sequences showed that, besides the AP-1 family, TEAD and FOX family TF DNA-binding motifs were highly enriched in hyper- and hypo-accessible regions respectively. Moreover, critical TFs and their potential targets associated with DARs were identified, such as TEAD1, RUNX1, GRHL2 and FOXA1. In addition, we put forward that the loss of FOXA1/GRHL2 collaboration might be responsible for acquired resistance to doxorubicin in breast cancer. These data provided clear insights and resources for an improved understanding of the non-genetic landscape of doxorubicin-resistant breast cancer cells based on chromatin accessibility and transcript levels, which allowed for detection of critical TFs, potential cis-regulatory elements, and therapeutic targets.
2021-05-12 | GSE174152 | GEO