Long non-coding RNA FAM83H-AS1 as an emerging marker for diagnosis, prognosis and therapeutic targeting of cancer

Prognostic predictive modeling of non-small cell lung cancer associated with cadmium-related pathogenic genes

Persistent exposure to low-dose of cadmium is strongly linked to both the development and prognosis of non-small cell lung cancer (NSCLC), yet the precise molecular mechanism behind this relationship remains uncertain. In this study, cadmium-related pathogenic genes (CRPGs) in NSCLC were identified via differential expression analysis. NSCLC patient clusters related to CRPGs were constructed through univariate Cox and K-means clustering algorithms. Multivariate Cox and least absolute shrinkage and selection operator (LASSO) regression analyses were employed to determine the prognosis. Sixteen CRPGs showed a significant association with NSCLC. We found biological and prognostic differences between patients in clusters A and B. A predictive prognostic risk model for NSCLC revealed that FAM83H, MSMO1, and SNAI1 are central. Hence, the 3 hub genes were named. To further elucidate the role of CRPGs in NSCLC, A549 cells were exposed to CdCl2. The mRNA and protein expression levels of the 3 hub genes and cell invasion were detected. Moreover, 10 μM CdCl2 may increase the protein expression of 3 hub genes and enhance the invasive ability of A549 cells. This risk model may have established a theoretical foundation for investigating the mechanisms, treatment, and prognosis of NSCLC.

WTAP-Involved the m6A Modification of lncRNA FAM83H-AS1 Accelerates the Development of Gastric Cancer

The long noncoding RNA FAM83H-antisense RNA 1 (FAM83H-AS1) is involved in gastric cancer (GC) development. This study determined whether FAM83H-AS1 was regulated by N6-methyladenosine (m6A) modifications in GC. Real-time quantitative polymerase chain reaction was performed to determine the expression levels of FAM83H-AS1 and Wilms' tumor 1 associated protein (WTAP). The protein content of WTAP was evaluated using western blotting. To assess the m6A alterations in FAM83H-AS1, methylated RNA immunoprecipitation was performed to identify interactions between WTAP and FAM83H-AS1. Functionally, the proliferation, migration, and invasion of GC cells were measured using a Cell Counting Kit-8 and transwell assays, respectively. High expression levels of FAM83H-AS1 and WTAP were detected in GC samples and there was a positive correlation between them. In addition, WTAP mediates FAM83H-AS1 expression in an m6A-dependent manner. Further investigations indicated that WTAP silencing reversed the cancer-promoting role of FAM83H-AS1 overexpression in GC cell migration, proliferation, and invasion. Our results suggest that WTAP-mediated FAM83H-AS1 promotes GC development via m6A modification. Our findings provide new biomarkers for GC diagnosis and targeted therapy.

Development and validation of a prognostic 9-gene signature for colorectal cancer

Introduction

Colorectal cancer (CRC) is one of the most prevalent cancers globally with a high mortality rate. Predicting prognosis using disease progression and cancer pathologic stage is insufficient, and a prognostic factor that can accurately evaluate patient prognosis needs to be developed. In this study, we aimed to infer a prognostic gene signature to identify a functional signature associated with the prognosis of CRC patients.

Methods

First, we used univariate Cox regression, least absolute shrinkage and selection operator (lasso) regression, and multivariate Cox regression analyses to screen genes significantly associated with CRC patient prognosis, from colorectal cancer RNA sequencing data in The Cancer Genome Atlas (TCGA) database. We then calculated the risk score (RS) for each patient based on the expression of the nine candidate genes and developed a prognostic signature.

Results

Based on the optimal cut-off on the receiver operating characteristic (ROC) curve, patients were separated into high- and low-risk groups, and the difference in overall survival between the two groups was examined. Patients in the low-risk group had a better overall survival rate than those in the high-risk group. The results were validated using the GSE72970, GSE39582, and GSE17536 Gene Expression Omnibus (GEO) datasets, and the same conclusions were reached. ROC curve test of the RS signature also indicated that it had excellent accuracy. The RS signature was then compared with traditional clinical factors as a prognostic indicator, and we discovered that the RS signature had superior predictive ability.

Conclusion

The RS signature developed in this study has excellent predictive power for the prognosis of patients with CRC and broad applicability as a prognostic indicator for patients.

Antisense long non-coding RNAs in gastric cancer

Gastric cancer is a global health problem with high mortality. The incidence of gastric cancer has significant regional differences. Helicobacter pylori (H. pylori) infection and its interaction with epigenetics are closely related to the occurrence of gastric cancer. It is of great significance to explore the early diagnosis and effective therapeutic targets of gastric cancer. Emerging evidence indicates that antisense long non-coding RNAs (lncRNAs) are closely associated with various biological and functional aspects of gastric cancer. However, diverse antisense lncRNAs in gastric cancer have not been compiled and discussed. In this review, we summarize the predisposing factors and compile the interaction between H. pylori and epigenetics in gastric cancer. Moreover, we focus on the underlying molecular mechanism and regulatory role of each antisense lncRNA in gastric cancer. In addition, we provide a new insight into the potential diagnosis and treatment of antisense lncRNAs in gastric cancer.

An immune-related lncRNA risk coefficient model to predict the outcomes in clear cell renal cell carcinoma

Objective: Using model algorithms, we constructed an immune-related long non-coding RNAs (lncRNAs) risk coefficient model to predict outcomes for patients with clear cell renal cell carcinoma (ccRCC) to understand the infiltration of tumor immune cells and the sensitivity to immune-targeted drugs.

Methods: Open genes data were downloaded from The Cancer Genome Atlas and The Immunology Database and Analysis Portal, and immune-related lncRNAs were obtained through Pearson correlation analysis. R language software was used to obtain differentially expressed immune-related lncRNAs and immune-related lncRNA pairs. The model was constructed using least absolute shrinkage and selector operation regression analysis, and receiver operator characteristic curves were drawn. The Akaike information criterion was used to distinguish the high-risk from the low-risk group. We also conducted correlation analysis for the high- and low-risk subgroups.

Results: We identified 27 immune-related lncRNAs pairs, 16 of which were included in the model construction. After merging clinical data, the areas under the curve of 1 -year, 3-year, and 5-year survival times of ccRCC patients were 0.867, 0.832, and 0.838, respectively. Subgroup analyses were conducted according to the cut-off value. We found that the high-risk group was associated with poor outcomes. The risk score and tumor stage were independent predictors of the outcome of ccRCC. The risk model predicted specific immune cell infiltration, immune checkpoint gene expression levels, and high-risk groups more sensitive to sunitinib targeted therapy.

Conclusion: We obtained prognostic-related novel ccRCC markers and risk model that predicts the outcome of patients with ccRCC and helps identify those who can benefit from sunitinib.

Long Noncoding RNA 00472: A Novel Biomarker in Human Diseases

Long non-coding RNAs (lncRNAs) play important roles in human diseases. They control gene expression levels and influence various biological processes through multiple mechanisms. Functional abnormalities in lncRNAs are strongly associated with occurrence and development of various diseases. LINC00472, which is located on chromosome 6q13, is involved in several human diseases, particularly cancers of the breast, lung, liver, osteosarcoma, bladder, colorectal, ovarian, pancreatic and stomach. Importantly, LINC00472 can be used as a biomarker for breast cancer cell sensitivity to chemotherapeutic regimens, including doxorubicin. LINC00472 is regulated by microRNAs and several signaling pathways. However, the significance of LINC00472 in human diseases has not been clearly established. In this review, we elucidate on the significance of LINC00472 in various human diseases, indicating that LINC00472 may be a diagnostic, prognostic as well as therapeutic target for these diseases.