A novel prognostic signature of coagulation-related genes leveraged by machine learning algorithms for lung squamous cell carcinoma.

Coagulation-related genes (CRGs) have been demonstrated to be essential for the development of certain tumors; however, little is known about CRGs in lung squamous cell carcinoma (LUSC). In this study, we adopted CRGs to construct a coagulation-related gene prognostic signature (CRGPS) using machine learning algorithms. Using a set of 92 machine learning integrated algorithms, the CRGPS was determined to be the optimal prognostic signature (median C-index = 0.600) for predicting the prognosis of an LUSC patient. The CRGPS was not only superior to traditional clinical parameters (e.g., T stage, age, and gender) and its commutative genes but also outperformed 19 preexisting prognostic signatures for LUSC on predictive accuracy. The CRGPS score was positively correlated with poor prognoses in patients with LUSC (hazard ratio > 1, p < 0.05), indicating its suitability as a prognostic marker for this disease. The CRGPS was observed to be inversely correlated with the degree of infiltration of natural killer cells. For some tumors, patients with lower CRGPS scores are more likely to experience enhanced immunotherapy effects (area under the curve = 0.70), which implies that the CRGPS can potentially predict immunotherapy efficacy. A high CRGPS score is predictive of an LUSC patient being sensitive to several drugs. Collectively, these findings indicate that the CRGPS may be a reliable indicator of the prognoses of patients with LUSC and may be useful for the clinical management of such patients.

MMP12 is a Potential Predictive and Prognostic Biomarker of Various Cancers Including Lung Adenocarcinoma.

OBJECTIVE: This study sought to explore the clinical value of matrix metalloproteinases 12 (MMP12) in multiple cancers, including lung adenocarcinoma (LUAD). METHODS: Using >10,000 samples, this retrospective study demonstrated the first pan-cancer analysis of MMP12. The expression of MMP12 between cancer groups and their control groups was analyzed using Wilcoxon rank-sum tests. The clinical significance of MMP12 expression in multiple cancers was assessed using receiver operating characteristic curves, Kaplan-Meier curves, and univariate Cox analysis. A further LUAD-related analysis based on 4565 multi-center and in-house samples was performed to verify the findings regarding MMP12 in pan-cancer analysis partly. RESULTS: MMP12 mRNA is highly expressed in 13 cancers compared to their controls, and the MMP12 protein level is elevated in some of these cancers (e.g., colon adenocarcinoma) (P < .05). MMP12 expression makes it feasible to distinguish 21 cancer tissues from normal tissues (AUC = 0.86). A high MMP12 expression is a prognosis risk factor in eight cancers, such as adrenocortical carcinoma (hazard ratio >1, P < .05). The elevated MMP12 expression is also a prognosis protective factor in breast-invasive carcinoma and colon adenocarcinoma (hazard ratio <1, P < .05). Some pan-cancer findings regarding MMP12 are verified in LUAD-MMP12 expression is upregulated in LUAD at both the mRNA and protein levels (P < .05), has the potential to distinguish LUAD with considerable accuracy (AUC = .91), and plays a risk prognosis factor for patients with the disease (P < .05). CONCLUSIONS: MMP12 is highly expressed in most cancers and may serve as a novel biomarker for the prediction and prognosis of numerous cancers.

Prognostic Signature and Discrimination Signature of Lung Adenocarcinoma based on Pyroptosis-Related Genes.

BACKGROUND: The clinical value of pyroptosis-related genes (PRGs) in lung adenocarcinoma (LUAD) remains obscure. OBJECTIVE: The study attempts to explore PRGs in LUAD, which will enable an understanding of LUAD from the perspective of PRGs. METHODS: Lung adenocarcinoma patients were diagnosed using pathology, and their clinical information was collected from several public databases. A PRGs prognostic signature (PPS) for LUAD patients was established based on a multivariate Cox regression analysis. The differential expression of PRGs was identified using standardized mean differences in 6,958 samples. The area under the curve (AUC) was used to evaluate the predictive effects of the PPS to determine the survival rate of LUAD patients. Decision curve analysis was utilized to assess the clinical significance of the PPS in LUAD. RESULTS: The PPS consists of five PRGs, namely CASP3, CASP9, GSDMB, NLRP1, and TNF. The prognostic effect of the PPS is evident in all the predicted one-, three-, and five-year survival rates (AUCs ≥ 0.58). The PPS represents an independent risk factor for the prognosis of LUAD patients (hazard ratio > 1; 95% confidence interval excluding 1). The PPS risk score can predict the prognosis of LUAD patients more accurately than PRGs of the PPS and multiple clinical parameters, such as age, tumor stage, and clinical stage. The decision curve analysis revealed that the nomogram based on the PPS and clinical parameters might result in better clinical decisions. CONCLUSION: The PPS makes it feasible to distinguish LUAD from non-LUAD. Thus, the underlying significance of the PPS in distinguishing LUAD from non-LUAD is promising.

Prognostic signature of esophageal adenocarcinoma based on pyroptosis-related genes.

BACKGROUND: The role of pyroptosis-related genes (PRGs) in esophageal adenocarcinoma (EAC) remains unknown. METHODS: In this study, the first PRGs prognostic signature (PPS) of EAC was constructed based on the results of multivariate stepwise Cox regression analysis. Based on 1,047 samples of EAC and normal esophagus (NE), differentially expressed PRGs were selected for the establishment of the PPS. The discrimination effect of this PPS was detected by receiver operating characteristic curves, and the prognosis value of this PPS was determined through Cox regression analysis and Kaplan-Meier curves. Net benefits of the EAC patients from the nomogram (constructed based on the PPS and some clinical parameters) were assessed via decision curve analysis. The potential molecular mechanism of the PPS in EAC was explored via gene set enrichment analysis. The ability of PPS to distinguish EAC and NE was evaluated based on the results of summary receiver operating characteristic curves. RESULTS: The significant prognostic value of PPS can be observed at all of the training cohort, test cohort, and validation cohort, such as its independent risk role in the prognosis of the EAC patients (hazard ratio > 0; 95% CI not including 0). The positive net benefits of the nomogram for the EAC patients can be detected via decision curve analysis, and the potential molecular mechanism of the PPS in EAC is likely related to cell pyroptosis. Last, some of the PRGs (particularly CASP5) included in this PPS specifically support its feasibility for identifying EAC (area under the curves > 0.7). CONCLUSIONS: The construction of this PPS in EAC enhances the present understanding of the relationship between PRGs and EAC, thus representing a novel approach to the clinical identification and management of EAC based on PRGs.

Overexpression of cyclin-dependent kinase 1 in esophageal squamous cell carcinoma and its clinical significance.

Cyclin-dependent kinase 1 (CDK1) plays a significant role in certain malignancies. However, it remains unclear whether CDK1 plays a role in esophageal squamous cell carcinoma (ESCC). The aim of this study was to analyze the expression and clinical value of CDK1 in ESCC. CDK1 protein in 151 ESCC tissues and 138 normal esophageal tissues was detected by immunohistochemistry. RNA-seq of eight pairs of ESCC and adjacent esophageal specimens was performed to evaluate the levels of CDK1 mRNA. Microarray and external RNA-seq data from 664 cases of ESCC and 1733 cases of control tissues were used to verify the difference in CDK1 expression between the two groups. A comprehensive analysis of all data was performed to evaluate the difference in CDK1 between ESCC tissues and control tissues. Further, functional enrichment analyses were performed based on differentially expressed genes (DEGs) of ESCC and co-expressed genes (CEGs) of CDK1. In addition, a lncRNA-miRNA-CDK1 network was constructed. The expression of CDK1 protein was obviously increased in ESCC tissues (3.540 ± 2.923 vs. 1.040 ± 1.632, P < 0.001). RNA-seq indicated that the mRNA level of CDK1 was also highly expressed in ESCC tissues (5.261 ± 0.703 vs. 2.229 ± 1.161, P < 0.0001). Comprehensive analysis revealed consistent up-regulation of CDK1 (SMD = 1.41; 95% CI 1.00-1.83). Further, functional enrichment analyses revealed that the functions of these genes were mainly concentrated in the cell cycle. A triple regulatory network of PVT1-hsa-miR-145-5p/hsa-miR-30c-5p-CDK1 was constructed using in silico analysis. In summary, overexpression of CDK1 is closely related to ESCC tumorigenesis.

Downregulation of miRNA-126-3p is associated with progression of and poor prognosis for lung squamous cell carcinoma.

Lung squamous cell carcinoma (LUSC) is the main pathological type of pulmonary malignant tumors; at present, less than 10% of patients with advanced metastatic LUSC live for more than 5 years. We previously reported that low expression of miRNA-126-3p is associated with the occurrence and progression of lung adenocarcinoma (LUAD). Here, we examined expression of miRNA-126-3p in 23 samples from patients with LUSCs and 23 normal control specimens by quantitative real-time PCR (RT-qPCR). Associations between miRNA-126-3p expression and clinical features were studied from materials derived from Gene Expression Omnibus (GEO) chips and The Cancer Genome Atlas (TCGA) database. Twelve online platforms were used to identify candidate target genes of miRNA-126-3p. Further analyses of the Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and protein-protein interaction (PPI) network were performed on the target genes. GEO microarray analysis, TCGA data mining, RT-qPCR, and integration analysis consistently reported low expression of miRNA-126-3p in LUSC. A total of 42 genes were identified as potential target genes of miRNA-126-3p from online platforms, GEO microarrays, and the TCGA database. GO and KEGG analyses demonstrated that the target genes are involved in several biological processes that promote the progression of LUSC. SOX2, E2F2, and E2F3 were selected as hub genes from the PPI network for further analysis. In summary, our results suggest that the low expression of miRNA-126-3p may play a role in promoting the development of LUSC and miRNA-126-3p may be a biomarker for LUSC early diagnosis and prognosis.

The Clinical Significance and Potential Molecular Mechanism of PTTG1 in Esophageal Squamous Cell Carcinoma.

Esophageal squamous cell carcinoma (ESCC) is the major histological type of esophageal cancers worldwide. Transcription factor PTTG1 was seen highly expressed in a variety of tumors and was related to the degree of tumor differentiation, invasion, and metastasis. However, the clinical significance of PTTG1 had yet to be verified, and the mechanism of abnormal PTTG1 expression in ESCC was not clear. In this study, the comprehensive analysis and evaluation of PTTG1 expression in ESCC were completed by synthesizing in-house immunohistochemistry (IHC), clinical sample tissue RNA-seq (in-house RNA-seq), public high-throughput data, and literature data. We also explored the possible signaling pathways and target genes of PTTG1 in ESCC by combining the target genes of PTTG1 (displayed by ChIP-seq), differentially expressed genes (DEGs) of ESCC, and PTTG1-related genes, revealing the potential molecular mechanism of PTTG1 in ESCC. In the present study, PTTG1 protein and mRNA expression levels in ESCC tissues were all significantly higher than in non-cancerous tissues. The pool standard mean difference (SMD) of the overall PTTG1 expression was 1.17 (95% CI: 0.72-1.62, P < 0.01), and the area under curve (AUC) of the summary receiver operating characteristic (SROC) was 0.86 (95% CI: 0.83-0.89). By combining the target genes displayed by ChIP-seq of PTTG1, DEGs of ESCC, and PTTG1-related genes, it was observed that PTTG1 may interact with these genes through chemokines and cytokine signaling pathways. By constructing a protein-protein interaction (PPI) network and combining ChIP-seq data, we obtained four PTTG1 potential target genes, SPTAN1, SLC25A17, IKBKB, and ERH. The gene expression of PTTG1 had a strong positive correlation with SLC25A17 and ERH, which suggested that PTTG1 might positively regulate the expression of these two genes. In summary, the high expression of PTTG1 may play an important role in the formation of ESCC. These roles may be completed by PTTG1 regulating the downstream target genes SLC25A17 and ERH.