LIN28B/IRS1 axis is targeted by miR-30a-5p and promotes tumor growth in colorectal cancer

Research on lncRNA CTBP1-DT as a potential therapeutic target to regulate cell function in colorectal cancer

BACKGROUND

Colorectal cancer, which originates from the human colon or rectum, is one of the leading causes of death worldwide. Timely diagnosis and interventional therapy can significantly improve the prognostic survival of colorectal cancer patients, making regular screening and early detection essential.

AIM

To investigate the regulatory function of lncRNA CTBP1-DT (CTBP1-DT) on colorectal cancer cells and to assess its diagnostic significance.

METHODS

A total of 102 patients with colorectal cancer and 92 healthy individuals were selected. The levels of CTBP1-DT and microRNA-30a-5p (miR-30a-5p) in serum and cell samples of the above subjects were compared by RT-qPCR. The effects of CTBP1-DT and miR-30a-5p dysregulation on the biological functions of colorectal cancer cells were analyzed via CCK-8, flow cytometry and Transwell assays. In addition, the ability of CTBP1-DT and miR-30a-5p to early identify colorectal cancer patients was determined through ROC curve.

RESULTS

Serum CTBP1-DT was elevated in patients with colorectal cancer, which was obviously higher than in healthy controls. The expression of serum miR-30a-5p was downregulated in colorectal cancer. Both CTBP1-DT and miR-30a-5p have the value of distinguishing colorectal cancer, and the combined diagnostic ability is higher. Knockdown of CTBP1-DT directly targeted miR-30a-5p to repress cell activity and metastatic ability, whereas deregulation of miR-30a-5p eliminated the above inhibitory effects.

CONCLUSION

Overexpression of CTBP1-DT has a certain application potential in the diagnosis of colorectal cancer and may be a therapeutic target for colorectal cancer.

From strings to signals: Unraveling the impact of miRNAs on diagnosis, and progression of colorectal cancer

Colorectal cancer (CRC) stands as the third most prevalent ailment globally and represents the primary cause of mortality associated with cancer. Significant advancements have been made in the clinical management of patients with CRC, encompassing the development of more streamlined methodologies and a diverse array of biomarkers utilized for prognostic, diagnostic, and predictive objectives. MicroRNAs (miRNAs, miRs) play a key role in the development of CRC by modulating the expression of their target genes, which govern a number of metabolic and cellular processes. They are related to malignant traits such as enhanced invasive and proliferative capacity, evasion of apoptosis, cell cycle aberration, and promotion of angiogenesis through dysregulation in their function. This review's objectives were to examine miRNA biogenesis, provide an updated list of oncogenic and tumor suppressor miRNAs, and discuss the likely causes of miRNA dysregulation in CRC. Additionally, we discuss the diagnostic and predictive functions of miRNAs in CRC and summarize their biological significance and clinical potential.

The role of LIN28B in tumor progression and metastasis in solid tumor entities

LIN28B is an RNA-binding protein that targets a broad range of microRNAs and modulates their maturation and activity. Under normal conditions, LIN28B is exclusively expressed in embryogenic stem cells, blocking differentiation and promoting proliferation. In addition, it can play a role in epithelial-to-mesenchymal transition by repressing the biogenesis of let-7 microRNAs. In malignancies, LIN28B is frequently overexpressed, which is associated with increased tumor aggressiveness and metastatic properties. In this review, we discuss the molecular mechanisms of LIN28B in promoting tumor progression and metastasis in solid tumor entities and its potential use as a clinical therapeutic target and biomarker.

MiRNA-disease association prediction based on meta-paths

Since miRNAs can participate in the posttranscriptional regulation of gene expression, they may provide ideas for the development of new drugs or become new biomarkers for drug targets or disease diagnosis. In this work, we propose an miRNA-disease association prediction method based on meta-paths (MDPBMP). First, an miRNA-disease-gene heterogeneous information network was constructed, and seven symmetrical meta-paths were defined according to different semantics. After constructing the initial feature vector for the node, the vector information carried by all nodes on the meta-path instance is extracted and aggregated to update the feature vector of the starting node. Then, the vector information obtained by the nodes on different meta-paths is aggregated. Finally, miRNA and disease embedding feature vectors are used to calculate their associated scores. Compared with the other methods, MDPBMP obtained the highest AUC value of 0.9214. Among the top 50 predicted miRNAs for lung neoplasms, esophageal neoplasms, colon neoplasms and breast neoplasms, 49, 48, 49 and 50 have been verified. Furthermore, for breast neoplasms, we deleted all the known associations between breast neoplasms and miRNAs from the training set. These results also show that for new diseases without known related miRNA information, our model can predict their potential miRNAs. Code and data are available at https://github.com/LiangYu-Xidian/MDPBMP.

LIN28 promotes tumorigenesis in colorectal cancer but is not associated with metastatic spread

BACKGROUND

Tumor stem cells play a role in metastatic spread in colorectal cancer (CRC). The oncogene LIN28A/B, a prognostic marker in CRC, is involved in tumorigenesis and maintains stem cell function. Therefore, it was the aim of the present study to clarify whether LIN28A/B is involved in metastatic spread in CRC.

METHODS

Expression of LIN28A/B was analyzed in patients with colon adenocarcinoma in a matched case-control study comparing patients with corresponding liver metastases (n = 42) and patients without hepatic spread within five years (n = 42) by applying immunohistochemistry. Further, LIN28A/B expression was correlated with stem cell associated markers (SOX2, CD133).

RESULTS

LIN28A and B expression significantly correlated with SOX2 expression (p = .02, and p = .04 respectively) but not with CD133 expression. This correlation between LIN28 A/B and SOX2 was not reflected in differences in hepatic spread. In this respect, there was no significant association between LIN28A/B expression and liver metastases.

CONCLUSION

LIN28A/B might be involved in tumor initiation and progression in CRC but is not associated with hepatic spread.

Integrated analysis of Solute carrier family-2 members reveals SLC2A4 as an independent favorable prognostic biomarker for breast cancer

Most of Solute carrier family-2 (SLC2) members play a key role of facilitative transporters, and glucose transporter (GLUT) proteins encoded by SLC2s can transport hexoses or polyols. However, the function and mechanism of SLC2s remain unclear in human cancers. Here, we explored the dysregulated expression, prognostic values, epigenetic, genetic alterations, and biomolecular network of SLC2s in human cancers. According to the data from public-omicsrepository, SLC2A4 (GLUT4) was found to be significantly downregulated in most cancers, and higher messenger RNA (mRNA) expression of SLC2A4 significantly associated with better prognosis of breast cancer (BRCA) patients. Moreover, DNA hypermethylation in the promoter of SLC2A4 may affect the regulation of its mRNA expression, and SLC2A4 was strongly correlated with pathways, including the translocation of SLC2A4 to the plasma membrane and PID INSULIN PATHWAY. In conclusion, these results provide insight into SLC2s in human cancers and suggest that SLC2A4 could be an unfavorable prognostic biomarker for the survival of BRCA patients.

LncRNA HIF1A-AS2 accelerates malignant phenotypes of renal carcinoma by modulating miR-30a-5p/SOX4 axis as a ceRNA

OBJECTIVE

Several reports have proposed that lncRNAs, as potential biomarkers, participate in the progression and growth of malignant tumors. HIF1A-AS2 is a novel lncRNA and potential biomarker, involved in the genesis and development of carcinomas. However, the molecular mechanism of HIF1A-AS2 in renal carcinoma is unclear.

METHODS

The relative expression levels of HIF1A-AS2 and miR-30a-5p were detected using RT-qPCR in renal carcinoma tissues and cell lines. Using loss-of-function and overexpression, the biological effects of HIF1A-AS2 and miR-30a-5p in kidney carcinoma progression were characterized. Dual luciferase reporter gene analysis and Western blot were used to detect the potential mechanism of HIF1A-AS2 in renal carcinomas.

RESULTS

HIF1A-AS2 was upregulated in kidney carcinoma tissues when compared with para-carcinoma tissues (P < 0.05). In addition, tumor size, tumor node mestastasis stage and differentiation were identified as being closely associated with HIF1A-AS2 expression (P < 0.05). Knockdown or overexpression of HIF1A-AS2 either restrained or promoted the malignant phenotype and WNT/β-catenin signaling in renal carcinoma cells (P < 0.05). MiR-30a-5p was downregulated in renal cancers and partially reversed HIF1A-AS2 functions in malignant renal tumor cells. HIF1A-AS2 acted as a microRNA sponge that actively regulated the relative expression of SOX4 in sponging miR-30a-5p and subsequently increased the malignant phenotypes of renal carcinomas. HIF1A-AS2 showed a carcinogenic effect and miR-30a-5p acted as an antagonist of the anti-oncogene effects in the pathogenesis of renal carcinomas.

CONCLUSIONS

The HIF1A-AS2-miR-30a-5p-SOX4 axis was associated with the malignant progression and development of renal carcinoma. The relative expression of HIF1A-AS2 was negatively correlated with the expression of miR-30a-5p, and was closely correlated with SOX4 mRNA levels in renal cancers.

An in silico approach to identify and prioritize miRNAs target sites polymorphisms in colorectal cancer and obesity

Colorectal cancer (CRC) and obesity are linked clinical entities with a series of complex processes being engaged in their development. MicroRNAs (miRNAs) participate in these processes through regulating CRC and obesity‐related genes. This study aimed to develop an in silico approach to systematically identify and prioritize miRNAs target sites polymorphisms in obesity and CRC. Data from genome‐wide association studies (GWASs) were used to retrieve CRC and obesity‐associated variants. The polymorphisms that were resided in experimentally verified or computationally predicted miRNA target sites were retrieved and prioritized using a range of bioinformatics analyses. We found 6284 CRC and 38931 obesity unique variants. For CRC 33 haplotypes variants in 134 interactions were in miRNA targetome, while for obesity we found more than 935 unique interactions. Functionally prioritized SNPs revealed that, SNPs in 153 obesity and 50 CRC unique interactions were have disruptive effects on miRNA:mRNA integration by changing on target RNA secondary structure. Structural accessibility of target sites were decreased in 418 and 103 unique interactions and increased in 516 and 79 interactions, for obesity and CRC, respectively. The miRNA:mRNA hybrid stability was increased in 127 and 17 unique interactions and decreased in 33 and 24 interactions for the effect of obesity and CRC SNPs, respectively. In this study, seven SNPs with 15 interactions and three SNPs with four interactions were prioritized for obesity and CRC, respectively. These SNPs could be used for future studies for finding potential biomarkers for diagnoses, prognosis, or treatment of CRC and obesity.

Bioinformatics analysis of prognostic value and prospective pathway signal of miR-30a in ovarian cancer

Objective

MicroRNAs (MiRNAs) is thought to play a critical role in the initiation and progress of ovarian cancer (OC). Although miRNAs has been widely recognized in ovarian cancer, the role of hsa-miR-30a-5p (miR-30a) in OC has not been fully elucidated.

Methods

Three mRNA datasets of normal ovarian tissue and OC, GSE18520,GSE14407 and GSE36668, were downloaded from Gene Expression Omnibus (GEO) to find the differentially expressed gene (DEG). Then the target genes of hsa-miR-30a-5p were predicted by miRWALK3.0 and TargetScan. Then, the gene overlap between DEG and the predicted target genes of miR-30a in OC was analyzed by Gene Ontology (GO) enrichment analysis. Protein-protein interaction (PPI) network was conducted by STRING and Cytoscape, and the effect of HUB gene on the outcome of OC was analyzed.

Results

A common pattern of up-regulation of miR-30a in OC was found. A total of 225 DEG, were identified, both OC-related and miR-30a-related. Many DEG are enriched in the interactions of intracellular matrix tissue, ion binding and biological process regulation. Among the 10 major Hub genes analyzed by PPI, five Hub genes were significantly related to the overall poor survival of OC patients, in which the low expression of ESR1,MAPK10, Tp53 and the high expression of YKT,NSF were related to poor prognosis of OC.

Conclusion

Our results indicate that miR-30a is of significance for the biological progress of OC.

An immune-related gene signature for determining Ewing sarcoma prognosis based on machine learning

PURPOSE

Ewing sarcoma (ES) is one of the most common malignant bone tumors in children and adolescents. The immune microenvironment plays an important role in the development of ES. Here, we developed an optimal signature for determining ES patient prognosis based on immune-related genes (IRGs).

METHODS

We analyzed the ES gene expression profile dataset, GSE17679, from the GEO database and extracted differential expressed IRGs (DEIRGs). Then, we conducted functional correlation and protein-protein interaction (PPI) analyses of the DEIRGs and used the machine learning algorithm-iterative Lasso Cox regression analysis to build an optimal DEIRG signature. In addition, we applied ES samples from the ICGC database to test the optimal gene signature. We performed univariate and multivariate Cox regressions on clinicopathological characteristics and optimal gene signature to evaluate whether signature is an important prognostic factor. Finally, we calculated the infiltration of 24 immune cells in ES using the ssGSEA algorithm, and analyzed the correlation between the DEIRGs in the optimal gene signature and immune cells.

RESULTS

A total of 249 DEIRGs were screened and an 11-gene signature with the strongest correlation with patient prognoses was analyzed using a machine learning algorithm. The 11-gene signature also had a high prognostic value in the ES external verification set. Univariate and multivariate Cox regression analyses showed that 11-gene signature is an independent prognostic factor. We found that macrophages and cytotoxic, CD8 T, NK, mast, B, NK CD56bright, TEM, TCM, and Th2 cells were significantly related to patient prognoses; the infiltration of cytotoxic and CD8 T cells in ES was significantly different. By correlating prognostic biomarkers with immune cell infiltration, we found that FABP4 and macrophages, and NDRG1 and Th2 cells had the strongest correlation.

CONCLUSION

Overall, the IRG-related 11-gene signature can be used as a reliable ES prognostic biomarker and can provide guidance for personalized ES therapy.

Ran GTPase: A Key Player in Tumor Progression and Metastasis

Ran (Ras-related nuclear protein) GTPase is a member of the Ras superfamily. Like all the GTPases, Ran cycles between an active (GTP-bound) and inactive (GDP-bound) state. However, Ran lacks the CAAX motif at its C-terminus, a feature of other small GTPases that ensures a plasma membrane localization, and largely traffics between the nucleus and the cytoplasm. Ran regulates nucleo-cytoplasmic transport of molecules through the nuclear pore complex and controls cell cycle progression through the regulation of microtubule polymerization and mitotic spindle formation. The disruption of Ran expression has been linked to cancer at different levels - from cancer initiation to metastasis. In the present review, we discuss the contribution of Ran in the acquisition of three hallmarks of cancer, namely, proliferative signaling, resistance to apoptosis, and invasion/metastasis, and highlight its prognostic value in cancer patients. In addition, we discuss the use of this GTPase as a therapeutic target in cancer.