Landscape of Genome-Wide DNA Methylation of Colorectal Cancer Metastasis.

Colorectal cancer is a heterogeneous disease caused by both genetic and epigenetics factors. Analysing DNA methylation changes occurring during colorectal cancer progression and metastasis formation is crucial for the identification of novel epigenetic markers of patient prognosis. Genome-wide methylation sequencing of paired samples of colon (normal adjacent, primary tumour and lymph node metastasis) showed global hypomethylation and CpG island (CGI) hypermethylation of primary tumours compared to normal. In metastasis we observed high global and non-CGI regions methylation, but lower CGI methylation, compared to primary tumours. Gene ontology analysis showed shared biological processes between hypermethylated CGIs in metastasis and primary tumours. After complementary analysis with The Cancer Genome Atlas (TCGA) cohort, FIGN, HTRA3, BDNF, HCN4 and STAC2 genes were found associated with poor survival. We mapped the methylation landscape of colon normal tissues, primary tumours and lymph node metastasis, being capable of identified methylation changes throughout the genome. Furthermore, we found five genes with potential for methylation biomarkers of poor prognosis in colorectal cancer patients

Landscape of Genome-Wide DNA Methylation of Colorectal Cancer Metastasis.

Colorectal cancer is a heterogeneous disease caused by both genetic and epigenetics factors. Analysing DNA methylation changes occurring during colorectal cancer progression and metastasis formation is crucial for the identification of novel epigenetic markers of patient prognosis. Genome-wide methylation sequencing of paired samples of colon (normal adjacent, primary tumour and lymph node metastasis) showed global hypomethylation and CpG island (CGI) hypermethylation of primary tumours compared to normal. In metastasis we observed high global and non-CGI regions methylation, but lower CGI methylation, compared to primary tumours. Gene ontology analysis showed shared biological processes between hypermethylated CGIs in metastasis and primary tumours. After complementary analysis with The Cancer Genome Atlas (TCGA) cohort, FIGN, HTRA3, BDNF, HCN4 and STAC2 genes were found associated with poor survival. We mapped the methylation landscape of colon normal tissues, primary tumours and lymph node metastasis, being capable of identified methylation changes throughout the genome. Furthermore, we found five genes with potential for methylation biomarkers of poor prognosis in colorectal cancer patients

Reprimo, a Potential p53-Dependent Tumor Suppressor Gene, Is Frequently Hypermethylated in Estrogen Receptor α-Positive Breast Cancer

Aberrant DNA methylation is a hallmark of many cancers. Currently, there are four intrinsic molecular subtypes in breast cancer (BC): Luminal A, B, Her2-positive, and triple negative (TNBC). Recently, The Cancer Genome Atlas (TCGA) project has revealed that Luminal subtypes have higher levels of genome-wide methylation that may be a result of Estrogen/Estrogen receptor α (E2/ERα) signaling pathway activation. In this study, we analyze promoter CpG-island (CGIs) of the Reprimo (RPRM) gene in breast cancers (n = 77), cell lines (n = 38), and normal breast tissue (n = 10) using a MBDCap-seq database. Then, a validation cohort (n = 26) was used to confirm the results found in the MBDCap-seq platform. A differential methylation pattern was found between BC and cell lines compared to normal breast tissue. In BC, a higher DNA methylation was observed in tissues that were ERα-positive than in ERα-negative ones; more precisely, subtypes Luminal A compared to TNBC. Also, significant reverse correlation was observed between DNA methylation and RPRM mRNA expression in BC. Our data suggest that ERα expression in BC may affect the DNA methylation of CGIs in the RPRM gene. This approach suggests that DNA methylation status in CGIs of some tumor suppressor genes could be driven by E2 availability, subsequently inducing the activation of the ERα pathway

Functional and transcriptomic characterization of carboplatin-resistant A2780 ovarian cancer cell line

Abstract Background Ovarian cancer is a significant cancer-related cause of death in women worldwide. The most used chemotherapeutic regimen is based on carboplatin (CBDCA). However, CBDCA resistance is the main obstacle to a better prognosis. An in vitro drug-resistant cell model would help in the understanding of molecular mechanisms underlying this drug-resistance phenomenon. The aim of this study was to characterize cellular and molecular changes of induced CBDCA-resistant ovarian cancer cell line A2780. Methods The cell selection strategy used in this study was a dose-per-pulse method using a concentration of 100 μM for 2 h. Once 20 cycles of exposure to the drug were completed, the cell cultures showed a resistant phenotype. Then, the ovarian cancer cell line A2780 was grown with 100 μM of CBDCA (CBDCA-resistant cells) or without CBDCA (parental cells). After, a drug sensitivity assay, morphological analyses, cell death assays and a RNA-seq analysis were performed in CBDCA-resistant A2780 cells. Results Microscopy on both parental and CBDCA-resistant A2780 cells showed similar characteristics in morphology and F-actin distribution within cells. In cell-death assays, parental A2780 cells showed a significant increase in phosphatidylserine translocation and caspase-3/7 cleavage compared to CBDCA-resistant A2780 cells (P < 0.05 and P < 0.005, respectively). Cell viability in parental A2780 cells was significantly decreased compared to CBDCA-resistant A2780 cells (P < 0.0005). The RNA-seq analysis showed 156 differentially expressed genes (DEGs) associated mainly to molecular functions. Conclusion CBDCA-resistant A2780 ovarian cancer cells is a reliable model of CBDCA resistance that shows several DEGs involved in molecular functions such as transmembrane activity, protein binding to cell surface receptor and catalytic activity. Also, we found that the Wnt/β-catenin and integrin signaling pathway are the main metabolic pathway dysregulated in CBDCA-resistant A2780 cells

Functional and transcriptomic characterization of cisplatin-resistant AGS and MKN-28 gastric cancer cell lines.

Gastric cancer (GC) is a significant cancer-related cause of death worldwide. The most used chemotherapeutic regimen in GC is based on platinum drugs such as cisplatin (CDDP). However, CDDP resistance reduces advanced GC survival. In vitro drug-resistant cell model would help in the understanding of molecular mechanisms underlying this drug-resistance phenomenon. The aim of this study was to characterize new models of CDDP-resistant GC cell lines (AGS R-CDDP and MKN-28 R-CDDP) obtained through a stepwise increasing drug doses method, in order to understand the molecular mechanisms underlying chemoresistance as well as identify new therapeutic targets for the treatment of GC. Cell viability assays, cell death assays and the expression of resistance molecular markers confirmed that AGS R-CDDP and MKN-28 R-CDDP are reliable CDDP-resistant models. RNA-seq and bioinformatics analyses identified a total of 189 DEGs, including 178 up-regulated genes and 11 down-regulated genes, associated mainly to molecular functions involved in CDDP-resistance. DEGs were enriched in 23 metabolic pathways, among which the most enriched was the inflammation mediated by chemokine and cytokine signaling pathway. Finally, the higher mRNA expression of SERPINA1, BTC and CCL5, three up-regulated DEGs associated to CDDP resistance found by RNA-seq analysis was confirmed. In summary, this study showed that AGS R-CDDP and MKN-28 R-CDDP are reliable models of CDDP resistance because resemble many of resistant phenotype in GC, being also useful to assess potential therapeutic targets for the treatment of gastric cancers resistant to CDDP. In addition, we identified several DEGs associated with molecular functions such as binding, catalytic activity, transcription regulator activity and transporter activity, as well as signaling pathways associated with inflammation process, which could be involved in the development of CDDP resistance in GC. Further studies are necessary to clarify the role of inflammatory processes in GC resistant to CDDP and these models could be useful for these purposes

Appendix A. Additional site descriptions, two method tables, two data tables, and four additional figures.

Additional site descriptions, two method tables, two data tables, and four additional figures