Development and clinical validation of a 3-miRNA signature to predict prognosis of gastric cancer

MiR-1275 Targeting SPARC Promotes Gambogic Acid-Induced Inhibition of Gastric Cancer

Gambogic acid (GA) has been observed to effectively impede the progression of numerous types of cancers. In this study, we investigated the effects of miR-1275 and Secreted Protein Acidic and Cysteine Rich (SPARC) on GA in gastric cancer (GC). miR-1275 and SPARC expression were determined in GC cell lines and tissues using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). The correlation between miR-1275 and SPARC expression was ascertained using Pearson's correlation coefficient. Cell proliferation was assessed using the cell counting kit-8 (CCK-8) assay. The Transwell assay was conducted to examine cell migration. A dual-luciferase reporter assay was used to verify the regulatory relationship between miR-1275 and SPARC. The levels of SPARC, Bcl-2, and Bax proteins were estimated using western blotting. To verify the effects of GA on the growth of GC cells in vivo, a tumorigenesis experiment was performed in nude mice. GA suppressed GC cell viability and migration, facilitated apoptosis, and inhibited tumor growth in vivo and in vitro. Low levels of miR-1275 been observed in GC cell lines and tissues. GA-treated GC cells manifested high miR-1275 levels. In functional experiments, miR-1275 enhanced the influence of GA on cell apoptosis, migration, and proliferation. Furthermore, GA treatment suppressed SPARC upregulation in GC cell lines and tissues. Pearson's correlation coefficient revealed that miR-1275 expression negatively correlated with SPARC expression. Mechanistically, miR-1275 promoted growth inhibition in GA-treated GC cells by targeting SPARC. Our study indicates that miR-1275 enhances the suppressive effect of GA on GC progression by inhibiting SPARC expression. Through this study, we contribute to the knowledge of a new mechanism by which GA suppresses GC progression.

A nomogram model based on the number of examined lymph nodes-related signature to predict prognosis and guide clinical therapy in gastric cancer

BACKGROUND

Increasing evidence suggests that the number of examined lymph nodes (ELNs) is strongly linked to the survivorship of gastric cancer (GC). The goal of this study was to assess the prognostic implications of the ELNs number and to construct an ELNs-based risk signature and nomogram model to predict overall survival (OS) characteristics in GC patients.

METHODS

This inception cohort study included 19,317 GC patients from the U.S. Surveillance, Epidemiology, and End Results (SEER) database, who were separated into a training group and an internal validation group. The nomogram was built with the training set, then internally verified with SEER data, and externally validated with two different data sets. Based on the RNA-seq data, ELNs-related DERNAs (DElncRNAs, DEmiRNAs, andDEmRNAs) and immune cells were identified. The LASSO-Cox regression analysis was utilized to construct ELNs-related DERNAs and immune cell prognostic signature in The Cancer Genome Atlas (TCGA) cohort. The OS of subgroups with high- and low-ELN signature was compared using the Kaplan-Meier (K-M) analysis. A nomogram was successfully constructed based on the ELNs signature and other clinical characteristics. The concordance index (C-index), calibration plot, receiver operating characteristic curve, and decision curve analysis (DCA) were all used to evaluate the nomogram model. The meta-analysis, the Gene Expression Profiling Interactive Analysis database, and reverse transcription-quantitative PCR (RT-qPCR) were utilized to validate the RNA expression or abundance of prognostic genes and immune cells between GC tissues and normal gastric tissues, respectively. Finally, we analyzed the correlations between immune checkpoints, chemotherapy drug sensitivity, and risk score.

RESULTS

The multivariate analysis revealed that the high ELNs improved OS compared with low ELNs (hazard ratio [HR] = 0.659, 95% confidence interval [CI]: 0.626-0.694, p < 0.0001). Using the training set, a nomogram incorporating ELNs was built and proven to have good calibration and discrimination (C-index [95% CI], 0.714 [0.710-0.718]), which was validated in the internal validation set (C-index [95% CI], 0.720 [0.714-0.726]), the TCGA set (C-index [95% CI], 0.693 [0.662-0.724]), and the Chinese set (C-index [95% CI], 0.750 [0.720-0.782]). An ELNs-related signature model based on ELNs group, regulatory T cells (Tregs), neutrophils, CDKN2B-AS1, H19, HOTTIP, LINC00643, MIR663AHG, TMEM236, ZNF705A, and hsa-miR-135a-5p was constructed by the LASSO-Cox regression analysis. The result showed that OS was remarkably lower in patients with high-ELNs signature compared with those with low-ELN signature (HR = 2.418, 95% CI: 1.804-3.241, p < 0.001). This signature performed well in predicting 1-, 3-, and 5-year survival (AUC [95% CI] = 0.688 [0.612-0.763], 0.744 [0.659-0.830], and 0.778 [0.647-0.909], respectively). The multivariate Cox analysis illustrated that the risk score was an independent predictor of survival for patients with GC. Moreover, the expression of prognostic genes (LINC00643, TMEM236, and hsa-miR-135a-5p) displayed differences between GC tissues and adjacent non-tumor tissues. The C-index of the nomogram that can be used to predict the OS of GC patients was 0.710 (95% CI: 0.663-0.753). Both the calibration plots and DCA showed that the nomogram has good predictive performance. Moreover, the signature was significantly correlated with the N stage and T stage. According to our analysis, GC patients in the low-ELN signature group may have a better immunotherapy response and OS outcome.

CONCLUSIONS

We explored the prognostic role of ELNs in GC and successfully constructed an ELNs signature linked to the GC prognosis in TCGA. The findings manifested that the signature is a powerful predictive indicator for patients with GC. The signature might contain potential biomarkers for treatment response prediction for GC patients. Additionally, we identified a novel and robust nomogram combining the characteristics of ELNs and clinical factors for predicting 1-, 3-, and 5-year OS in GC patients, which will facilitate personalized survival prediction and aid clinical decision-making in GC patients.

Overview of MicroRNAs as Diagnostic and Prognostic Biomarkers for High-Incidence Cancers in 2021

MicroRNAs (miRNAs) are small non-coding RNAs (ncRNAs) about 22 nucleotides in size, which play an important role in gene regulation and are involved in almost all major cellular physiological processes. In recent years, the abnormal expression of miRNAs has been shown to be associated with human diseases including cancer. In the past ten years, the link between miRNAs and various cancers has been extensively studied, and the abnormal expression of miRNAs has been reported in various malignant tumors, such as lung cancer, gastric cancer, colorectal cancer, liver cancer, breast cancer, and prostate cancer. Due to the high malignancy grade of these cancers, it is more necessary to develop the related diagnostic and prognostic methods. According to the study of miRNAs, many potential cancer biomarkers have been proposed for the diagnosis and prognosis of diseases, especially cancer, thus providing a new theoretical basis and perspective for cancer screening. The use of miRNAs as biomarkers for diagnosis or prognosis of cancer has the advantages of being less invasive to patients, with better accuracy and lower price. In view of the important clinical significance of miRNAs in human cancer research, this article reviewed the research status of miRNAs in the above-mentioned cancers in 2021, especially in terms of diagnosis and prognosis, and provided some new perspectives and theoretical basis for the diagnosis and treatment of cancers.

MiR-711 regulates gastric cancer progression by targeting CD44

BACKGROUND

MicroRNAs (miRNAs) have been reported to play an important role in tumor progression by regulating the expression of target genes.

OBJECTIVE

This study attempted to verify the role of miR-711 in gastric cancer (GC) progression by in vitro and in vivo assays.

METHODS

The expression of miR-711 in tumor tissues and cells was detected by real-time quantitative PCR (qRT-PCR). Expression of MiR-711 in NCI-N87 and SNU-1 cells was detected by FISH. We transfected GC cells with miR-711 mimics or inhibitors. The effects of miR-711 on the proliferation and metastasis of GC cells were detected by CCK-8, wound healing and transwell assays. Dual-luciferase reporter gene assay was used to verify the targeting relationship between miR-711 and CD44. Xenograft assays was used to verify the regulatory effect of miR-711 on tumor growth.

RESULTS

In GC tissues and cell lines, the expression of miR-711 was down-regulated when compare with adjacent tissues or normal epithelial cells. The results indicated that overexpressing of miR-711 could suppress the GC cell proliferation, migration, and invasion through targeting CD44. The knockdown of CD44 showed similar effects as miR-711 overexpression in GC cells. Moreover, we confirmed these effects in the in vivo assays. Furthermore, we found that miR-711 could play a role by influencing tumor cell stemness.

CONCLUSION

MiR-711 plays vital roles as a tumor-suppressor by targeting CD44 and may be a therapeutic target for GC treatment.

Identification of a chromatin regulator signature and potential candidate drugs for bladder cancer

Background

Bladder cancer (BLCA) is a malignant tumor with a dismay outcome. Increasing evidence has confirmed that chromatin regulators (CRs) are involved in cancer progression. Therefore, we aimed to explore the function and prognostic value of CRs in BLCA patients.

Methods

Chromatin regulators (CRs) were acquired from the previous top research. The mRNA expression and clinical information were downloaded from TCGA and GEO datasets. Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis were performed to select the prognostic gene and construct the risk model for predicting outcome in BLCA. The Kaplan-Meier analysis was used to assess the prognosis between high- and low-risk groups. We also investigated the drug sensitivity difference between high- and low-risk groups. CMAP dataset was performed to screen the small molecule drugs for treatment.

Results

We successfully constructed and validated an 11 CRs-based model for predicting the prognosis of patients with BLCA. Moreover, we also found 11 CRs-based model was an independent prognostic factor. Functional analysis suggested that CRs were mainly enriched in cancer-related signaling pathways. The CR-based model was also correlated with immune cells infiltration and immune checkpoint. Patients in the high-risk group were more sensitive to several drugs, such as mitomycin C, gemcitabine, cisplatin. Eight small molecule drugs could be beneficial to treatment for BLCA patients.

Conclusion:

In conclusion, our study provided novel insights into the function of CRs in BLCA. We identified a reliable prognostic biomarker for the survival of patients with BLCA.

Identification of a novel signature based on unfolded protein response-related gene for predicting prognosis in bladder cancer

BACKGROUND

The unfolded protein response (UPR) served as a vital role in the progression of tumors, but the molecule mechanisms of UPR in bladder cancer (BLCA) have been not fully investigated.

METHODS

We identified differentially expressed unfolded protein response-related genes (UPRRGs) between BLCA samples and normal bladder samples in the Cancer Genome Atlas (TCGA) database. Univariate Cox analysis and the least absolute shrinkage and selection operator penalized Cox regression analysis were used to construct a prognostic signature in the TCGA set. We implemented the validation of the prognostic signature in GSE13507 from the Gene Expression Omnibus database. The ESTIMATE, CIBERSORT, and ssGSEA algorithms were used to explore the correlation between the prognostic signature and immune cells infiltration as well as key immune checkpoints (PD-1, PD-L1, CTLA-4, and HAVCR2). GDSC database analyses were conducted to investigate the chemotherapy sensitivity among different groups. GSEA analysis was used to explore the potential mechanisms of UPR-based signature.

RESULTS

A prognostic signature comprising of seven genes (CALR, CRYAB, DNAJB4, KDELR3, CREB3L3, HSPB6, and FBXO6) was constructed to predict the outcome of BLCA. Based on the UPRRGs signature, the patients with BLCA could be classified into low-risk groups and high-risk groups. Patients with BLCA in the low-risk groups showed the more favorable outcomes than those in the high-risk groups, which was verified in GSE13507 set. This signature could serve as an autocephalous prognostic factor in BLCA. A nomogram based on risk score and clinical characteristics was established to predict the over survival of BLCA patients. Furthermore, the signature was closely related to immune checkpoints (PD-L1, CTLA-4, and HAVCR2) and immune cells infiltration including CD8⁺ T cells, follicular helper T cells, activated dendritic cells, and M2 macrophages. GSEA analysis indicated that immune and carcinogenic pathways were enriched in high-risk group.

CONCLUSIONS

We identified a novel unfolded protein response-related gene signature which could predict the over survival, immune microenvironment, and chemotherapy response of patients with bladder cancer.

Unveiling the tumour-regulatory roles of miR-1275 in cancer

The rapid development of small RNA and molecular biology research in the past 20 years has enabled scientists to discover many new miRNAs that are proven to play essential roles in regulating the development of different cancer types. Among these miRNAs, miR-1275 is one of the well-studied miRNAs that has been described to act as a tumour-promoting or tumour-suppressing miRNA in various cancer types. Even though miR-1275 has been widely reported in different original research articles on its roles in modulating the progression of different cancer types, however, there is scarce an in-depth review that could constructively summarize the findings from different studies on the regulatory roles of miR-1275 in different cancer types. To fill up this literature gap, therefore, this review was aimed to provide an overview and summary of the roles of miR-1275 in modulating the development of different cancers and to unravel the mechanism of how miR-1275 regulates cancer progression. Based on the findings summarized from various sources, it was found that miR-1275 plays a vital role in regulating various cellular signaling pathways like the PI3K/AKT, ERK/JNK, MAPK, and Wnt signaling pathways, and the dysregulation of this miRNA has been shown to contribute to the development of multiple cancer types such as cancers of the liver, breast, lung, gastrointestinal tract and genitourinary tract. Therefore, miR-1275 has great potential to be employed as a biomarker to diagnose cancer and to predict the prognosis of cancer patients. In addition, by inhibiting the expression of its unique downstream targets that are involved in regulating the mentioned cellular pathways, this miRNA could also be utilized as a novel therapeutic agent to halt cancer development.