A pan-cancer analysis of the prognostic and immunological roles of matrix metalloprotease-1 (MMP1) in human tumors.

Objective: Cancer remains the leading killer of human health worldwide. It has been shown that matrix metalloproteinase-1(MMP1) is related to poor prognosis in cancers such as BRCA, CESC and COAD. However, systematic pan-cancer analysis about the prognostic and immunological roles of MMP1 has not been explored. Here, the purpose of this study was to investigate the prognostic and immunological roles of MMP1 in pan-cancer and confirm cancer-promoting effect in pancreatic cancer. Methods: In our study, bioinformatics were first used to analyze data from multiple databases. Then, several bioinformatics tools were utilized to investigate the role of MMP1 in 33 tumor types. Finally, molecular biology experiments were carried out to prove the cancer-promoting effect of MMP1 in pancreatic cancer. Results: MMP1 expression was higher in tumor tissues than in control tissues in most tumor types. High expression of MMP1 was associated with poor overall survival (OS) and disease-free survival (DFS) in some tumor types. Further analysis of MMP1 gene mutation data showed that MMP1 mutations significantly influenced the prognosis of STAD. In addition, MMP1 expression was closely related to cancer-associated fibroblast (CAFs) infiltration in a variety of cancers and played an important role on immune infiltration score, tumor mutational burden (TMB) and microsatellite instability (MSI). Gene Ontology enrichment analysis indicated that these 20 genes were mainly related to extracellular structure organization/extracellular matrix organization/extracellular matrix disassembly/collagen metabolic process in the enriched biological processes. Finally, molecular biology experiments confirmed the cancer-promoting effect of MMP1 in pancreatic cancer. Conclusions: Our pan-cancer analysis comprehensively proved that MMP1 expression is related with clinical prognosis and tumor immune infiltration, and MMP1 can become a prognostic and immunological biomarker.

A New Clinical Nomogram From the TCGA Database to Predict the Prognosis of Hepatocellular Carcinoma.

BACKGROUND AND AIM: Hepatocellular carcinoma is a common malignant tumor of the digestive system with a poor prognosis. The high recurrence rate and metastasis after surgery reduce the survival time of patients. Therefore, assessing the overall survival of patients with hepatocellular carcinoma after hepatectomy is critical to clinicians' clinical decision-making. Conventional hepatocellular carcinoma assessment systems (such as tumor lymph node metastasis and Barcelona clinical hepatocellular carcinoma) are obviously insufficient in assessing the overall survival rate of patients. This research is devoted to the development of nomogram assessment tools to assess the overall survival probability of patients undergoing liver resection. METHODS: We collected the clinical and pathological information of 438 hepatocellular carcinoma patients undergoing surgery from The Cancer Genome Atlas (TCGA) database, then excluded 87 patients who did not meet inclusion criteria. Univariate and multivariate analyses were performed on patient characteristics and related pathological factors. Finally, we developed a nomogram model to predict patient's prognosis. RESULTS: A retrospective analysis of 438 consecutive samples from the TCGA database of patients with hepatocellular carcinoma who underwent potentially curative liver resections. Six risk factors were included in the final model. In the training set, the discriminative ability of the nomogram was very good (concordance index = 0.944), and the external verification method (concordance index = 0.962) was used for verification. At the same time, the internal and external calibration of the model was verified, showing that the model was well calibrated. The calibration between the evaluation of the nomogram and the actual observations was good. According to the patient's risk factors, we determined the patient's Kaplan-Meyer survival analysis curve. Finally, the clinical decision curve was used to compare the benefits of two different models in evaluating patients' clinical outcomes. CONCLUSIONS: The nomogram can be used to evaluate the post-hepatectomy 1-, 3-, and 5-year survival rates of patients with hepatocellular carcinoma. The Kaplan-Meyer curve can intuitively display the survival differences among patients with various risk factors. The clinical decision curve is a good reference guide for clinical application.

Prognostic and predictive role of a metabolic rate-limiting enzyme signature in hepatocellular carcinoma.

OBJECTIVES: Abnormal expression of metabolic rate-limiting enzymes drives the occurrence and progression of hepatocellular carcinoma (HCC). This study aimed to elucidate the comprehensive model of metabolic rate-limiting enzymes associated with the prognosis of HCC. MATERIALS AND METHODS: HCC animal model and TCGA project were used to screen out differentially expressed metabolic rate-limiting enzyme. Cox regression, least absolute shrinkage and selection operation (LASSO) and experimentally verification were performed to identify metabolic rate-limiting enzyme signature. The area under the receiver operating characteristic curve (AUC) and prognostic nomogram were used to assess the efficacy of the signature in the three HCC cohorts (TCGA training cohort, internal cohort and an independent validation cohort). RESULTS: A classifier based on three rate-limiting enzymes (RRM1, UCK2 and G6PD) was conducted and serves as independent prognostic factor. This effect was further confirmed in an independent cohort, which indicated that the AUC at year 5 was 0.715 (95% CI: 0.653-0.777) for clinical risk score, whereas it was significantly increased to 0.852 (95% CI: 0.798-0.906) when combination of the clinical with signature risk score. Moreover, a comprehensive nomogram including the signature and clinicopathological aspects resulted in significantly predict the individual outcomes. CONCLUSIONS: Our results highlighted the prognostic value of rate-limiting enzymes in HCC, which may be useful for accurate risk assessment in guiding clinical management and treatment decisions.

Downregulation of lncRNA HCP5 has inhibitory effects on gastric cancer cells by regulating DDX21 expression.

LncRNA HCP5 has been confirmed to play crucial roles in many types of cancers. However, the role of lncRNA HCP5 in regulating the occurrence and development of gastric cancer (GC) remains unknown. In the current study, we aimed to investigate the precise effects of lncRNA HCP5 on cell proliferation, migration and invasion and molecular mechanisms in gastric cancer. Using RT-qPCR analysis, we found that lncRNA HCP5 was differentially expressed in GC cell lines. CCK-8, wound healing and transwell assay indicated that the proliferation, migration and invasion of gastric cancer cells were inhibited by downregulation of lncRNA HCP5 and lncRNA HCP5 overexpression exhibited the opposite effects in gastric cancer cells. Mechanistically, RNA binding protein immunoprecipitation and dual luciferase reporter assay confirmed the interaction between lncRNA HCP5 and DDX21. The effects of lncRNA HCP5 overexpression the proliferation, migration and invasion of GC cells were partly rescued by DDX21 silencing. Taken together, downregulation of lncRNA HCP5 exerted inhibitory effects on GC cell proliferation, migration and invasion through modulation of DDX21 expression, demonstrating the function of lncRNA HCP5 and DDX21 in GC progression.