In Silico Identification and Validation of Cuproptosis-Related LncRNA Signature as a Novel Prognostic Model and Immune Function Analysis in Colon Adenocarcinoma

High expression levels of S1PR3 and PDGFRB indicates unfavorable clinical outcomes in colon adenocarcinoma

Background

Studies verified that sphingosine kinase 1 (SPHK1)/sphingosine 1-phosphate receptors (S1PRs) and platelet-derived growth factor receptors (PDGFRs) play important roles in tumor occurrence and progression. However, the expression and clinical value of SPHK1/S1PRs and PDGFRs in colon adenocarcinoma (COAD) remains unclear. This study aimed to explore the expression of SPHK1/S1PRs and PDGFRs in COAD and further investigate their roles in predicting the prognosis of patients with COAD.

Methods

SPHK1/S1PRs and PDGFRs expression in tissues from patient with COAD were analyzed using The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. Kaplan-Meier survival analysis was used to evaluate the prognostic roles of SPHK1/S1PRs and PDGFRs in patients with COAD. Spearman's correlation analysis was performed to assess the relationship between SPHK1/S1PRs and PDGFRs in COAD. Then, χ2 test was performed to analyze the correlation between SPHK1/S1PR3/PDGFRB and clinicopathological characteristics of the patients. Additionally, possible signaling pathways co-regulated by S1PR3 and PDGFRB were predicted using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses. Least absolute shrinkage and selection operator (LASSO) regression was used to identify hub genes that co-regulated S1PR3 and PDGFRB expression. A prognostic model based on hub genes was constructed for patients with COPD. Finally, the relationship between the hub genes and tumor immune cell infiltration was investigated.

Results

The expression levels of SPHK1 and PDGFRB were significantly upregulated in COAD patient tissues (P < 0.001 and P < 0.001, respectively). Moreover, Kaplan-Meier analysis showed that patients with COAD with high expression levels of SPHK1 and S1PR3 had shorter overall survival (OS) than those with low expression levels (P = 0.013 and P = 0.005, respectively). Spearman's correlation analysis verified a strong positive correlation (P < 0.001, r = 0.790) between the expression of S1PR3 and PDGFRB. In addition, we found that high SPHK1 and PDGGRB expression levels were associated with perineural invasion (P < 0.001 and P = 0.011, respectively). High expression of S1PR3 and PDGGRB was prominently associated with N stage (P = 0.002 and P = 0.021, respectively). High levels of SPHK1, S1PR3, and PDGFRB were associated with lymph node invasion. (P = 0.018, P = 0.004, and P = 0.001, respectively). GO and KEGG results revealed that S1PR3 and PDGFRB may participate in COAD cell extracellular matrix organization and cellular signal transduction. Five hub genes, SFRP2, GPRC5B, RSPO3, FGF14, and TCF7L1, were identified using LASSO regression. Survival analysis showed that the OS in the high-risk group was remarkably shorter than that in the low-risk group. The results indicated that tumor immune cells were significantly increased in the high-risk group compared to those in the low-risk group.

Conclusions

S1PR3 and PDGFRB may be important markers for predicting lymphatic metastasis and poor prognosis in patients with COAD. The underlying mechanisms may involve immune cell infiltration.

Construction and validation of a novel lysosomal signature for hepatocellular carcinoma prognosis, diagnosis, and therapeutic decision-making

Lysosomes is a well-recognized oncogenic driver and chemoresistance across variable cancer types, and has been associated with tumor invasiveness, metastasis, and poor prognosis. However, the significance of lysosomes in hepatocellular carcinoma (HCC) is not well understood. Lysosomes-related genes (LRGs) were downloaded from Genome Enrichment Analysis (GSEA) databases. Lysosome-related risk score (LRRS), including eight LRGs, was constructed via expression difference analysis (DEGs), univariate and LASSO-penalized Cox regression algorithm based on the TCGA cohort, while the ICGC cohort was obtained for signature validation. Based on GSE149614 Single-cell RNA sequencing data, model gene expression and liver tumor niche were further analyzed. Moreover, the functional enrichments, tumor microenvironment (TME), and genomic variation landscape between LRRSlow/LRRShigh subgroup were systematically investigated. A total of 15 Lysosomes-related differentially expressed genes (DELRGs) in HCC were detected, and then 10 prognosis DELRGs were screened out. Finally, the 8 optimal DELRGs (CLN3, GBA, CTSA, BSG, APLN, SORT1, ANXA2, and LAPTM4B) were selected to construct the LRRS prognosis signature of HCC. LRRS was considered as an independent prognostic factor and was associated with advanced clinicopathological features. LRRS also proved to be a potential marker for HCC diagnosis, especially for early-stage HCC. Then, a nomogram integrating the LRRS and clinical parameters was set up displaying great prognostic predictive performance. Moreover, patients with high LRRS showed higher tumor stemness, higher heterogeneity, and higher genomic alteration status than those in the low LRRS group and enriched in metabolism-related pathways, suggesting its underlying role in the progression and development of liver cancer. Meanwhile, the LRRS can affect the proportion of immunosuppressive cell infiltration, making it a vital immunosuppressive factor in the tumor microenvironment. Additionally, HCC patients with low LRRS were more sensitive to immunotherapy, while patients in the high LRRS group responded better to chemotherapy. Upon single-cell RNA sequencing, CLN3, GBA, and LAPTM4B were found to be specially expressed in hepatocytes, where they promoted cell progression. Finally, RT-qPCR and external datasets confirmed the mRNA expression levels of model genes. This study provided a direct links between LRRS signature and clinical characteristics, tumor microenvironment, and clinical drug-response, highlighting the critical role of lysosome in the development and treatment resistance of liver cancer, providing valuable insights into the prognosis prediction and treatment response of HCC, thereby providing valuable insights into prognostic prediction, early diagnosis, and therapeutic response of HCC.

Expression of long noncoding RNA MEG3 and microRNA-302b-3p in colon cancer: Correlation with clinical stage and value in predicing prognosis after surgical treatment

BACKGROUND

More and more long non-coding RNAs and microRNAs have been found to have significant changes in expression levels during the occurrence and development of tumors, which can affect the expression of tumor suppressor genes or oncogenes and play an important role in the proliferation and metastasis of cancer cells.

AIM

To investigate the correlation between the expression of long non-coding RNA maternal imprinted gene 3 (LncRNA MEG3) and microRNA (miR)-302b-3p in colon cancer and clinical stage and analyze their value in predicting the prognosis after surgical treatment.

METHODS

A total of 97 patients with colon cancer treated at Jinhua Hospital of TCM from January 2017 to March 2022 were selected to compare the expression of LncRNA MEG3 and miR-302b-3p in different tissues, analyze the correlation between the expression of LncRNA MEG3 and miR-302b-3p and clinical pathological characteristics, compare the recurrence in patients with different LncRNA MEG3 and miR-302b-3p expression, analyze the factors affecting the recurrence of colon cancer after surgery, and analyze the impact of the interaction between LncRNA MEG3 and miR-302b-3p on the recurrence of colon cancer. The predictive value of LncRNA MEG3 and miR-302b-3p expression for the recurrence of colon cancer after surgery was evaluated.

RESULTS

The expression of LncRNA MEG3 and miR-302b-3p in colon cancer tissues was lower than that in tumor-adjacent tissues (P < 0.05). The expression of LncRNA MEG3 and miR-302b-3p in colon cancer tissues was not correlated with sex, age, or tumor size (P > 0.05), but was correlated with tumor differentiation, clinical stage, and lymph node metastasis (P < 0.05). In colon cancer tissues, the recurrence rate in patients with high LncRNA MEG3 and miR-302b-3p expression was lower than that of patients with lower LncRNA MEG3 and miR-302b-3p expression (P < 0.05). Tumor differentiation degree, clinical stage, and lymph node metastasis were all identified to be risk factors for colon cancer recurrence, and LncRNA MEG3 and miR-302b-3p expression were protective factors for colon cancer recurrence (P < 0.05). The interaction analysis showed that the synergistic effect of simultaneous exposure to LncRNA MEG3 and miR-302b-3p was 15.888 times greater than the effect of exposure to either LncRNA MEG3 or miR-302b-3p alone, and when simultaneously exposing to both, 56.98% of the risk of colon cancer recurrence was attributed to their synergistic effect. The area under the curve (AUC) (95% confidence interval [CI]) of LncRNA MEG3 and miR-302b-3p in predicting the prognosis of colon cancer patients was 0.720 (0.620-0.807) and 0.767 (0.670-0.847), respectively, and that of the combined prediction was 0.892 (0.813-0.946), with a sensitivity and specificity of 92.31% and 83.33%, respectively, which were significantly higher than those of either LncRNA MEG3 or miR-302b-3p alone.

CONCLUSION

The down-regulated expression of LncRNA MEG3 and miR-302b-3p in colon cancer is related to clinical stage. Clinical detection of their expression can be used to determine the malignant degree of tumor and predict the prognosis of surgical treatment, thus providing reference for adjustment of clinical treatment plan.

Cuproptosis: mechanisms and links with cancers

Cuproptosis was a copper-dependent and unique kind of cell death that was separate from existing other forms of cell death. The last decade has witnessed a considerable increase in investigations of programmed cell death, and whether copper induced cell death was an independent form of cell death has long been argued until mechanism of cuproptosis has been revealed. After that, increasing number of researchers attempted to identify the relationship between cuproptosis and the process of cancer. Thus, in this review, we systematically detailed the systemic and cellular metabolic processes of copper and the copper-related tumor signaling pathways. Moreover, we not only focus on the discovery process of cuproptosis and its mechanism, but also outline the association between cuproptosis and cancers. Finally, we further highlight the possible therapeutic direction of employing copper ion ionophores with cuproptosis-inducing functions in combination with small molecule drugs for targeted therapy to treat specific cancers.

Identification and validation of a new pyroptosis-associated lncRNA signature to predict survival outcomes, immunological responses and drug sensitivity in patients with gastric cancer

BACKGROUND

Gastric cancer (GC) ranks fifth in prevalence among carcinomas worldwide. Both pyroptosis and long noncoding RNAs (lncRNAs) play crucial roles in the occurrence and development of gastric cancer. Therefore, we aimed to construct a pyroptosis-associated lncRNA model to predict the outcomes of patients with gastric cancer.

METHODS

Pyroptosis-associated lncRNAs were identified through co-expression analysis. Univariate and multivariate Cox regression analyses were performed using the least absolute shrinkage and selection operator (LASSO). Prognostic values were tested through principal component analysis, a predictive nomogram, functional analysis and Kaplan‒Meier analysis. Finally, immunotherapy and drug susceptibility predictions and hub lncRNA validation were performed.

RESULTS

Using the risk model, GC individuals were classified into two groups: low-risk and high-risk groups. The prognostic signature could distinguish the different risk groups based on principal component analysis. The area under the curve and the conformance index suggested that this risk model was capable of correctly predicting GC patient outcomes. The predicted incidences of the one-, three-, and five-year overall survivals exhibited perfect conformance. Distinct changes in immunological markers were noted between the two risk groups. Finally, greater levels of appropriate chemotherapies were required in the high-risk group. AC005332.1, AC009812.4 and AP000695.1 levels were significantly increased in gastric tumor tissue compared with normal tissue.

CONCLUSIONS

We created a predictive model based on 10 pyroptosis-associated lncRNAs that could accurately predict the outcomes of GC patients and provide a promising treatment option in the future.

Machine learning and bioinformatics-based insights into the potential targets of saponins in Paris polyphylla smith against non-small cell lung cancer

Background: Lung cancer has the highest mortality rate among cancers worldwide, and non-small cell lung cancer (NSCLC) is the major lethal factor. Saponins in Paris polyphylla smith exhibit antitumor activity against non-small cell lung cancer, but their targets are not fully understood.

Methods: In this study, we used differential gene analysis, lasso regression analysis and support vector machine recursive feature elimination (SVM-RFE) to screen potential key genes for NSCLC by using relevant datasets from the GEO database. The accuracy of the signature genes was verified by using ROC curves and gene expression values. Screening of potential active ingredients for the treatment of NSCLC by molecular docking of the reported active ingredients of saponins in Paris polyphylla Smith with the screened signature genes. The activity of the screened components and their effects on key genes expression were further validated by CCK-8, flow cytometry (apoptosis and cycling) and qPCR.

Results: 204 differential genes and two key genes (RHEBL1, RNPC3) stood out in the bioinformatics analysis. Overall survival (OS), First-progression survival (FP) and post-progression survival (PPS) analysis revealed that low expression of RHEBL1 and high expression of RNPC3 indicated good prognosis. In addition, Polyphyllin VI(PPVI) and Protodioscin (Prot) effectively inhibited the proliferation of non-small cell lung cancer cell line with IC50 of 4.46 μM ± 0.69 μM and 8.09 μM ± 0.67μM, respectively. The number of apoptotic cells increased significantly with increasing concentrations of PPVI and Prot. Prot induces G1/G0 phase cell cycle arrest and PPVI induces G2/M phase cell cycle arrest. After PPVI and Prot acted on this cell line for 48 h, the expression of RHEBL1 and RNPC3 was found to be consistent with the results of bioinformatics analysis.

Conclusion: This study identified two potential key genes (RHEBL1 and RNPC3) in NSCLC. Additionally, PPVI and Prot may act on RHEBL1 and RNPC3 to affect NSCLC. Our findings provide a reference for clinical treatment of NSCLC.