Extended transcriptome analysis reveals genome-wide lncRNA-mediated epigenetic dysregulation in colorectal cancer

Prognostic value of long non-coding RNA MALAT1 in hepatocellular carcinoma: A study based on multi-omics analysis and RT-PCR validation

Background: This study aimed to explore the relationship between MALAT1 and the prognosis of patients with hepatocellular carcinoma (HCC). Methods: We constructed a MALAT1 protein-protein interaction network using the STRING database and a network of competing endogenous RNAs (ceRNAs) using the StarBase database. Using data from the GEPIA2 database, we studied the association between genes in these networks and survival of patients with HCC. The potential mechanisms underlying the relationship between MALAT1 and HCC prognosis were studied using combined data from RNA sequencing, DNA methylation, and somatic mutation data from The Cancer Genome Atlas (TCGA) liver cancer cohort. Tumor tissues and 19 paired adjacent non-tumor tissues (PANTs) from HCC patients who underwent radical resection were analyzed for MALAT1 mRNA levels using real-time PCR, and associations of MALAT1 expression with clinicopathological features or prognosis of patients were analyzed using log-rank test and Gehan-Breslow-Wilcoxon test. Results: Five interacting proteins and five target genes of MALAT1 in the ceRNA network significantly correlated with poor survival of patients with HCC (p < 0.05). High MALAT1 expression was associated with mutations in two genes leading to poor prognosis and may upregulate some prognostic risk genes through methylation. MALAT1 was significantly co-expressed with various signatures of genes involved in HCC progression, including the cell cycle, DNA damage repair, mismatch repair, homologous recombination, molecular cancer m6A, exosome, ferroptosis, infiltration of lymphocyte (p < 0.05). The expression of MALAT1 was markedly upregulated in HCC tissues compared with PANTs. In Kaplan-Meier analysis, patients with high MALAT1 expression had significantly shorter progression-free survival (PFS) (p = 0.033) and overall survival (OS) (p = 0.023) than those with low MALAT1 expression. Median PFS was 19.2 months for patients with high MALAT1 expression and 52.8 months for patients with low expression, while the corresponding median OS was 40.5 and 78.3 months. In subgroup analysis of patients with vascular invasion, cirrhosis, and HBsAg positive or AFP positive, MALAT1 overexpression was significantly associated with shorter PFS and OS. Models for predicting PFS and OS constructed based on MALAT1 expression and clinicopathological features had moderate predictive power, with areas under the receiver operating characteristic curves of 0.661-0.731. Additionally, MALAT1 expression level was significantly associated with liver cirrhosis, vascular invasion, and tumor capsular infiltration (p < 0.05 for all). Conclusion: MALAT1 is overexpressed in HCC, and higher expression is associated with worse prognosis. MALAT1 mRNA level may serve as a prognostic marker for patients with HCC after hepatectomy.

DNA methylation-based diagnostic, prognostic, and predictive biomarkers in colorectal cancer

DNA methylation is an epigenetic mechanism regulating gene expression. Changes in DNA methylation were suggested to be useful biomarkers for diagnosis, and for the determination of prognosis and treatment response. Here, we provide an overview of methylation-based biomarkers in colorectal cancer. First, we start with the two methylation-based diagnostic biomarkers already approved for colorectal cancer, SEPT9 and the combination of NDRG4 and BMP3. Then, we provide a list-based overview of new biomarker candidates depending on the sample source including plasma, stool, urine, and surgically removed tumor tissues. The most often identified markers like SDC2, VIM, APC, MGMT, SFRP1, SFRP2, and NDRG4 have distinct functions previously linked to tumor progression. Although numerous studies have identified tumor-specific methylation changes, most of these alterations were observed in a single study only. The lack of validation in independent samples means low reproducibility and is a major limitation. The genome-wide determination of methylation status (methylome) can provide data to solve these issues. In the third section of the review, methylome studies focusing on different aspects related to CRC, including precancerous lesions, CRC-specific changes, molecular subtypes, aging, and chemotherapy response are summarized. Notably, techniques simultaneously analyzing a large set of regions can also uncover epigenetic regulation of genes which have not yet been associated with tumorigenesis previously. A remaining constraint of studies published to date is the low patient number utilized in these preventing the identification of clinically valuable biomarker candidates. Either future large-scale studies or the integration of already available methylome-level data will be necessary to uncover biomarkers sufficiently robust for clinical application.