Connective Tissue Growth Factor, a Potential Prognostic Marker of Triple Negative Breast Cancer treatment
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA820464 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR18497320_1.fastq.gz | Fastqsanger.gz | |||
| SRR18497320_2.fastq.gz | Fastqsanger.gz | |||
| SRR18497321_1.fastq.gz | Fastqsanger.gz | |||
| SRR18497321_2.fastq.gz | Fastqsanger.gz | |||
| SRR18497322_1.fastq.gz | Fastqsanger.gz |
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Project description:Triple negative breast cancer (TNBC) patient with high level of connective tissue growth factor (CTGF) show poor survival and prognosis. Identification of novel target contributes to the development of TNBC treatment. Kahweol, a coffee diterpene molecule, is a natural compound with pharmacological activities such as anti-inflammatory, anti-angiogenetic, and apoptotic effect in several cancer cells. In this study, we demonstrated the involvement of CTGF expression level in TNBC treatment. Experiments were performed on MDA-MB 231, a TNBC cell line. Firstly, functional annotation and gene set enrichment analysis found that the CTGF involves in migratory pathways in TNBC treatment. We also investigated that kahweol regulates CTGF expression and functions as antitumor compound resulting in inhibition of cell migration and colony formation in TNBC. Next, CTGF knockdown synergically suppressed cell motility with kahweol. Migratory ability and colony conformation were also performed in vitro to confirm the results from functional annotation assay. Overall, our results suggest that CTGF is a potential target as a prognostic marker predicting the prognosis of TNBC treatment, and kahweol is a potential antitumor compound to regulate CTGF expression for TNBC.
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Project description:There are no widely-accepted prognostic markers currently available to predict outcomes in patients with triple-negative breast cancer (TNBC), and no targeted therapies with confirmed benefit. We have used MALDI mass spectrometry imaging (MSI) of tryptic peptides to compare regions of cancer and benign tissue in 10 formalin-fixed, paraffin-embedded sections of TNBC tumors. Proteins were identified by reference to a peptide library constructed by LC-MALDI-MS/MS analyses of the same tissues. The prognostic significance of proteins that distinguished between cancer and benign regions was estimated by Kaplan-Meier analysis of their gene expression from public databases. Among peptides that distinguished between cancer and benign tissue in at least 3 tissues with a ROC area under the curve >0.7, 14 represented proteins identified from the reference library, including proteins not previously associated with breast cancer. Initial network analysis using the STRING database showed no obvious functional relationships except among collagen subunits COL1A1, COL1A2, and COL63A, but manual curation, including the addition of EGFR to the analysis, revealed a unique network connecting 10 of the 14 proteins. Kaplan-Meier survival analysis to examine the relationship between tumor expression of genes encoding the 14 proteins, and recurrence-free survival (RFS) in patients with basal-like TNBC showed that, compared to low expression, high expression of nine of the genes was associated with significantly worse RFS, most with hazard ratios >2. In contrast, in estrogen receptor-positive tumors, high expression of these genes showed only low, or no, association with worse RFS. These proteins are proposed as putative markers of RFS in TNBC, and some may also be considered as possible targets for future therapies.
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Project description:Triple negative breast cancers (TNBCs) comprise a heterogeneous group of cancers with varying prognoses, presenting a challenge for effective clinical management. Epigenetic alterations in the cancer methylome are common in breast cancer and provide novel options for tumor stratification on the basis of prognosis. Advances in genome-wide DNA methylation technology have enabled more comprehensive identification of potential epigenetic diagnostic and prognostic cancer biomarkers. Here, we use MBDCap-Seq to perform genome-wide DNA methylation profiling from archival TNBC and matched normal DNA samples. We identified 822 differentially methylated regions (DMRs) comprising 308 genes affected by cancer-specific promoter hypermethylation. Notably, 51 of these genes are also recurrently mutated in breast cancer, seven of which include members of the axon guidance pathway recently implicated in tumor initiation and progression. Using TCGA methylation data as an independent validation cohort for TNBCs (n= 73), we showed that 36 genomic regions were specific for TNBCs, including both promoter and gene body hypermethyled loci. Importantly, we stratified TNBCs into three distinct methylation clusters associated with better or worse prognosis. Furthermore, we identified a “survival” methylation signature consisting of 17 DMRs that show strong regional association with overall survival, 16 of which overlap DNase1 hypersensitive sites. Notably three of these “survival” DMRs are located in the bi-directional promoter and gene bodies of WT1 gene and its anti-sense counter-part WT1-AS. Together, our data identifies for the first time a cancer DNA methylation diagnostic and prognostic signature that promises to stratify TNBCs for more personalized management.
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