Long non-coding RNA HANR as a biomarker for the diagnosis and prognosis of colorectal cancer

LncRNAs in colorectal cancer: Biomarkers to therapeutic targets

Colorectal cancer (CRC) is the third leading cause of cancer-related death in men and women worldwide. As early detection is associated with lower mortality, novel biomarkers are urgently needed for timely diagnosis and appropriate management of patients to achieve the best therapeutic response. Long noncoding RNAs (lncRNAs) have been reported to play essential roles in CRC progression. Accordingly, the regulatory roles of lncRNAs should be better understood in general and for identifying diagnostic, prognostic and predictive biomarkers in CRC specifically. In this review, the latest advances on the potential diagnostic and prognostic lncRNAs as biomarkers in CRC samples were highlighted, Current knowledge on dysregulated lncRNAs and their potential molecular mechanisms were summarized. The potential therapeutic implications and challenges for future and ongoing research in the field were also discussed. Finally, novel insights on the underlying mechanisms of lncRNAs were examined as to their potential role as biomarkers and therapeutic targets in CRC. This review may be used to design future studies and advanced investigations on lncRNAs as biomarkers for the diagnosis, prognosis and therapy in CRC.

Identification of a Prognostic Transcriptome Signature for Hepatocellular Carcinoma with Lymph Node Metastasis

Hepatocellular carcinoma (HCC) is one of the most aggressive malignant tumors, and the prognosis of HCC patients with lymph node metastasis (LNM) is poor. However, robust biomarkers for predicting the prognosis of HCC LNM are still lacking. This study used weighted gene coexpression network analysis of GSE28248 (N = 80) microarray data to identify gene modules associated with HCC LNM and validated in GSE40367 dataset (N = 18). The prognosis-related genes in the HCC LNM module were further screened based on the prognostic curves of 371 HCC samples from TCGA. We finally developed a prognostic signature, PSG-30, as a prognostic-related biomarker in HCC LNM. The HCC subtypes identified by PSG-30-based consensus clustering analysis showed significant differences in prognosis, clinicopathological stage, m6A modification, ferroptosis activation, and immune characteristics. In addition, RAD54B was selected by regression model as an independent risk factor affecting the prognosis of HCC patients with LNM, and its expression was significantly positively correlated with tumor mutational burden and microsatellite instability in high-risk subtypes. Patients with high RAD54B expression had a better prognosis in the immune checkpoint inhibitor-treated cohorts but had a poor prognosis in the HCC sorafenib-treated group. The association of high RAD54B expression with LNM in breast cancer (BRCA) and cholangiocarcinoma and its prognostic effect in BRCA LNM cases suggest the value of RAD54B at the pancancer level. In conclusion, PSG-30 can effectively identify HCC LNM population with poor prognosis, and high-risk patients with high RAD54B expression may be more suitable for immunotherapy.

Identification of Three Prognosis-Related Differentially Expressed lncRNAs Driven by Copy Number Variation in Thyroid Cancer

Thyroid cancer as the malignant tumor with the highest incidence in the endocrine system also shows a fast growth and development. In this work, we developed a new method to identify copy number variation- (CNV-) driven differentially expressed lncRNAs in thyroid cancer for predicting cancer prognosis. The data of RNA sequencing, CNV, methylation, mutation, and clinical details of thyroid cancer were obtained from the Cancer Genome Atlas database (TCGA). Molecular subtypes were clustered by iClusterPlus. Weighted gene co-expression network analysis (WGCNA) was employed to show co-expression modules. DEseq2 was conducted to identify protein coding genes (PCGs) and differentially expressed lncRNAs. CNV was detected using GISTIC 2.0. Three molecular subtypes were identified, and 68 differentially expressed lncRNAs (DElncRNAs) related to cancer were found among different molecular subtypes. CNV of FOXD2-AS1, FAM181A-AS1, and RNF157-AS1 was associated with overall survival and was involved in cancer-related pathways. These three DElncRNAs discovered based on CNV could serve as prognostic biomarkers to predict prognosis for thyroid cancer and new targets to explore molecular drugs.

CDK3, CDK5 and CDK8 Proteins as Prognostic and Potential Biomarkers in Colorectal Cancer Patients

Introduction

Methods

Results

Conclusion

Clinical diagnostic value of long non-coding RNAs in Colorectal Cancer: A systematic review and meta-analysis

Background: Histopathological diagnosis remains the gold standard for the diagnosis of cancer, including colorectal cancer, but it is infeasible when tumor tissue is not available. With the recognition of long non-coding RNAs (lncRNAs), the expression of lncRNAs in serum or tissue samples has been reported as a diagnosis method for some cancers, however, the diagnostic value of lncRNAs for colorectal cancer remains unclear.

Methods: A systematic review and meta-analysis were conducted. Eligible studies were identified through a comprehensive literature search in PubMed, PubMed Central, Web of Science, Embase, and Cochrane Library (up to May 05, 2020) according to the selection criteria. Meta-DiSc, Review Manager and STATA were used to analyze the association between lncRNAs expression and the diagnosis of colorectal cancer.

Results: Fifteen studies that analyzed the expression of 15 lncRNAs in 1434 CRC patients were included. The summary area under the curve (AUC) of lncRNA for the diagnosis efficacy between patients with and without CRC was estimated to be 0.8629, corresponding to a weighted sensitivity of 0.75 (95% CI: 0.72 - 0.77), specificity of 0.80 (95%CI: 0.78 - 0.82). Subgroup analysis illustrated that the AUC of blood-based detection of lncRNA showed 0.8820, pooled DOR: 18.57, while tissue-based analysis showed 0.8203, pooled DOR: 10.47. Blood-based tests were then divided into two categories, plasma-based and serum-based lncRNA testing. Results revealed that the AUC of serum-based detection was 0.9077, pooled DOR: 26.64, and plasma-based detection was 0.5000, pooled DOR: 11.80.

Conclusions: This meta-analysis indicates that the aberrantly expressed lncRNAs might serve as potential diagnostic biomarkers for CRC patients and blood-based lncRNA analysis is of higher diagnostic accuracy than tissue-based testing. Moreover, serum-based lncRNA testing achieved higher diagnostic efficacy than plasma-based analysis.