PLEKHA8P1 Promotes Tumor Progression and Indicates Poor Prognosis of Liver Cancer

Pathological roles of miRNAs and pseudogene-derived lncRNAs in human cancers, and their comparison as prognosis/diagnosis biomarkers

This review examines and compares the diagnostic and prognostic capabilities of miRNAs and lncRNAs derived from pseudogenes in cancer patients. Additionally, it delves into their roles in cancer pathogenesis. Both miRNAs and pseudogene-derived lncRNAs have undergone thorough investigation as remarkably sensitive and specific cancer biomarkers, offering significant potential for cancer detection and monitoring. . Extensive research is essential to gain a complete understanding of the precise roles these non-coding RNAs play in cancer, allowing the development of novel targeted therapies and biomarkers for improved cancer detection and treatment approaches.

Evaluation and Application of Drug Resistance by Biomarkers in the Clinical Treatment of Liver Cancer

Liver cancer is one of the most lethal cancers in the world, mainly owing to the lack of effective means for early monitoring and treatment. Accordingly, there is considerable research interest in various clinically applicable methods for addressing these unmet needs. At present, the most commonly used biomarker for the early diagnosis of liver cancer is alpha-fetoprotein (AFP), but AFP is sensitive to interference from other factors and cannot really be used as the basis for determining liver cancer. Treatment options in addition to liver surgery (resection, transplantation) include radiation therapy, chemotherapy, and targeted therapy. However, even more expensive targeted drug therapies have a limited impact on the clinical outcome of liver cancer. One of the big reasons is the rapid emergence of drug resistance. Therefore, in addition to finding effective biomarkers for early diagnosis, an important focus of current discussions is on how to effectively adjust and select drug strategies and guidelines for the treatment of liver cancer patients. In this review, we bring this thought process to the drug resistance problem faced by different treatment strategies, approaching it from the perspective of gene expression and molecular biology and the possibility of finding effective solutions.

Comprehensive analysis of the differences between left- and right-side colorectal cancer and respective prognostic prediction

Background

Previous studies have reported that the tumor heterogeneity and complex oncogenic mechanisms of proximal and distal colon cancer (CRC) are divergent. Therefore, we aim to analyze the differences between left-sided CRC (L_cancer) and right-sided CRC (R_cancer), as well as constructing respective nomograms.

Methods

We enrolled 335 colon cancer patients (146 L_cancer patients and 189 R_cancer patients) from The Cancer Genome Atlas (TCGA) data sets, and 102 pairs of color cancer tissue and adjacent normal tissue (51 L_cancer patients and 51 R_cancer patients) from our hospital. Firstly, we analyzed the differences between the L_cancer patients and R_cancer patients, and then established the L_cancer and R_cancer prognostic models using LASSO Cox.

Results

R_cancer patients had lower survival than L_cancer patients. R_cancer patients had higher ESTIMATE and immune scores and lower tumor purity. These patterns of expression of immune checkpoint-related genes and TMB level were higher in R_cancer than in L_cancer patients. Finally, we using Lasso Cox regression analyses established a prognostic model for L_cancer patients and a prognostic model for R_cancer patients. The AUC values of the risk score for OS in L_cancer were 0.862 in the training set and 0.914 in the testing set, while those in R_cancer were 0.835 in the training set and 0.857 in the testing set. The AUC values in fivefold cross-validation were between 0.727 and 0.978, proving that the two prognostic models have great stability. The nomogram of L_cancer included prognostic genes, age, pathological M, pathological stage, and gender, the AUC values of which were 0.800 in the training set and 0.905 in the testing set. Meanwhile, the nomogram of R_cancer comprised prognostic genes, pathological N, pathological T, and age, the AUC values of which were 0.836 in the training set and 0.850 in the testing set. In the R_cancer patients, high-risk patients had a lower proportion of ‘B cells memory’, ‘Dendritic cells resting’, immune score, ESTIMATE score, immune checkpoint-related genes, and HLA-family genes, and a higher proportion of ‘T cells follicular helper’, ‘Dendritic cells activated’, and ‘Mast cells activated’.

Conclusions

We found significant differences between L_cancer and R_cancer patients and established a clinical predictive nomogram for L_cancer patients and a nomogram for R_cancer patients. Additionally, R_cancer patients in low-risk groups may be more beneficial from immunotherapy.

Pseudogenes and the associated ceRNA network as potential prognostic biomarkers for colorectal cancer

Colorectal cancer (CRC) is one of the most common and malignant carcinomas. Many long noncoding RNAs (lncRNAs) have been reported to play important roles in the tumorigenesis of CRC by influencing the expression of some mRNAs via competing endogenous RNA (ceRNA) networks and interacting with miRNAs. Pseudogene is one kind of lncRNA and can act as RNA sponges for miRNAs and regulate gene expression via ceRNA networks. However, there are few studies about pseudogenes in CRC. In this study, 31 differentially expressed (DE) pseudogenes, 17 DE miRNAs and 152 DE mRNAs were identified by analyzing the expression profiles of colon adenocarcinoma obtained from The Cancer Genome Atlas. A ceRNA network was constructed based on these RNAs. Kaplan-Meier analysis showed that 7 pseudogenes, 4 miRNAs and 30 mRNAs were significantly associated with overall survival. Then multivariate Cox regression analysis of the ceRNA-related DE pseudogenes was performed and a 5-pseudogene signature with the greatest prognostic value for CRC was identified. Moreover, the results were validated by the Gene Expression Omnibus database, and quantitative real-time PCR in 113 pairs of CRC tissues and colon cancer cell lines. This study provides a pseudogene-associated ceRNA network, 7 prognostic pseudogene biomarkers, and a 5-pseudogene prognostic risk signature that may be useful for predicting the survival of CRC patients.

Alisol B 23-Acetate Increases the Antitumor Effect of Bufalin on Liver Cancer through Inactivating Wnt/β-Catenin Axis

Objective

Liver cancer seriously threatens the health of people. Meanwhile, it has been reported that bufalin could act as an inhibitor in liver cancer. In addition, alisol B 23-acetate is a natural product derived from Alisma plantago-aquatica Linn which has an antitumor effect. In this study, we aimed to explore whether alisol B 23-acetate could increase the antitumor effect of bufalin on liver cancer.

Methods

In order to detect the effect of alisol B 23-acetate in combination with bufalin on liver cancer, human liver cancer SMMC-7721 and MHCC97 cells were used as subjects. Bufalin and alisol B 23-acetate were performed on cells. Cell viability was tested by MTT assay. In addition, flow cytometry was performed to assess the cell apoptosis. Autophagy-related protein levels were tested by western blotting.

Results

The data revealed that bufalin significantly decreased the viability of liver cancer cells, and the inhibitory effect was further increased by alisol B 23-acetate. In addition, alisol B 23-acetate notably enhanced the apoptotic effect of bufalin on liver cancer cells through mediation of Mcl-1, Bax, Bcl-2, and cleaved caspase-3. Meanwhile, alisol B 23-acetate in combination with bufalin induced the autophagy in liver cancer cells through mediation of Beclin-1 and p62. Furthermore, alisol B 23-acetate in combination with bufalin significantly downregulated the level of GSK-3β and increased the expression of β-catenin in liver cancer cells.

Conclusion

In summary, these findings provide the first evidence that alisol B 23-acetate improves the anticancer activity of bufalin on liver cancer through activation of the Wnt/β-catenin axis, and these outcomes might shed new lights on exploring the new methods against liver cancer.