The roles of MASPIN expression and subcellular localization in non-small cell lung cancer

Split Gp41-1 intein splicing as a model to evaluate the cellular location of the oncosuppressor Maspin in an in vitro model of osteosarcoma

Inteins are proteins involved in the protein splicing mechanism, an autoprocessing event, where sequences (exteins) separated by inteins become ligated each other after recombination. Two kinds of inteins have been described, contiguous inteins and split inteins. The former ones are transcribed and translated as a single peptide along with their exteins, while the latter are fragmented between two different genes and are transcribed and translated separately. The aim of this study is to establish a method to obtain a fluorescent eukaryotic protein to analyze its cellular localization, using the natural split gp41-1 inteins. We chose natural split inteins due to their distribution in all three domains of life. Two constructs were prepared, one containing the N-terminal split intein along with the N-moiety of the Red Fluorescent Protein (RFP) and a second construct containing the C-terminal of split intein, the C-moiety of RFP and the gene coding for Maspin, a tumor suppressor protein. The trans-splicing was verified by transfecting both N-terminal and C-terminal constructs into mammalian cells. The success of the recombination event was highlighted through the fluorescence produced by reconstituted RFP after recombination, along with the overlap of the red fluorescence produced by recombined RFP and the green fluorescence produced by the hybridization of the recombinant Maspin with a specific antibody. In conclusion, we opted to use this mechanism of recombination to obtain a fluorescent Maspin instead to express a large fusion protein, considering that it could interfere with Maspin's structure and function.

SERPINB5 is a prognostic biomarker and promotes proliferation, metastasis and epithelial-mesenchymal transition (EMT) in lung adenocarcinoma

BACKGROUND

Serine protease inhibitors clade B serpins (SERPINBs) are the largest subclass of protease inhibitors, once thought of as a tumor suppressor gene family. However, some SERPINBs exhibit functions unrelated to the inhibition of catalytic activity.

METHODS

The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), Gene Set Cancer Analysis (GSCA), and cBioPortal databases were utilized to investigate SERPINBs expression, prognostic correlation, and genomic variation in 33 cancer types. We also conducted a comprehensive transcriptome analysis in multiple lung adenocarcinoma (LUAD) cohorts to reveal the molecular mechanism of SERPINB5 in LUAD. Then, qPCR and immunohistochemistry were used to verify the expression and prognostic value of SERPINB5 in LUAD patients. Furthermore, knockdown and overexpression of SERPINB5 in LUAD cell lines were performed to evaluate cell proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT).

RESULTS

The expression of SERPINB5 was upregulated and demethylated in LUAD, and its abnormally high expression was significantly correlated with poor overall survival (OS). In addition, the expression of SERPINB5 was analyzed to determine its prognostic value in LUAD and confirmed that SERPINB5 was an independent predictor of LUAD in TCGA and GEO cohorts and qPCR validation with 106 clinical samples. At last, A knockdown of SERPINB5 in LUAD cells reduced proliferation, migration, and EMT. Proliferation, migration, and invasion are promoted by the overexpression of SERPINB5.

CONCLUSION

Therefore, SERPINB5 has shown potential as a prognostic biomarker for LUAD, and it may become a potential therapeutic target for lung adenocarcinoma.

Association and functional significance of genetic variants present in regulatory elements of SERPINB5 gene in gallbladder cancer

SERPINB5 is a mammary serine protease inhibitor, which is involved in various cellular functions. The aberrant expression of SERPINB5 is reported in many cancers along with GBC but limited information is available about its role in genetic predisposition for GBC. We carried out case-control study in 206 cases and 219 controls. Promoter SNPs were genotyped by Sanger's sequencing. In-silico promoter analysis and luciferase reporter assay were done to elucidate the role of promoter variants in regulation of SERPINB5 expression. Out of four SNPs, three SERPINB5 promoter variants showed association with GBC in different models. The 'C' allele of variant rs17071138 was found to be significantly associated with GBC (p = 0.017). The 'T' allele of rs3744940 significantly increased the risk for GBC in dominant (p = 0.035) and additive models (p = 0.005). Also, rs3744941 'T' allele increased the risk for GBC by dominant (p = 0.042) as well as additive models (p = 0.016). In-silico promoter analysis and luciferase reporter assay revealed the probable regulatory role of the SERPINB5 promoter variant rs17071138 on the expression. Overall, our study reveals the genetic association of SERPINB5 promoter variants with GBC and possible role of rs17071138 in the regulation of expression.

A novel 14-gene signature for overall survival in lung adenocarcinoma based on the Bayesian hierarchical Cox proportional hazards model

There have been few investigations of cancer prognosis models based on Bayesian hierarchical models. In this study, we used a novel Bayesian method to screen mRNAs and estimate the effects of mRNAs on the prognosis of patients with lung adenocarcinoma. Based on the identified mRNAs, we can build a prognostic model combining mRNAs and clinical features, allowing us to explore new molecules with the potential to predict the prognosis of lung adenocarcinoma. The mRNA data (n = 594) and clinical data (n = 470) for lung adenocarcinoma were obtained from the TCGA database. Gene set enrichment analysis (GSEA), univariate Cox proportional hazards regression, and the Bayesian hierarchical Cox proportional hazards model were used to explore the mRNAs related to the prognosis of lung adenocarcinoma. Multivariate Cox proportional hazard regression was used to identify independent markers. The prediction performance of the prognostic model was evaluated not only by the internal cross-validation but also by the external validation based on the GEO dataset (n = 437). With the Bayesian hierarchical Cox proportional hazards model, a 14-gene signature that included CPS1, CTPS2, DARS2, IGFBP3, MCM5, MCM7, NME4, NT5E, PLK1, POLR3G, PTTG1, SERPINB5, TXNRD1, and TYMS was established to predict overall survival in lung adenocarcinoma. Multivariate analysis demonstrated that the 14-gene signature (HR 3.960, 95% CI 2.710–5.786), T classification (T₁, reference; T₃, HR 1.925, 95% CI 1.104–3.355) and N classification (N₀, reference; N₁, HR 2.212, 95% CI 1.520–3.220; N₂, HR 2.260, 95% CI 1.499–3.409) were independent predictors. The C-index of the model was 0.733 and 0.735, respectively, after performing cross-validation and external validation, a nomogram was provided for better prediction in clinical application. Bayesian hierarchical Cox proportional hazards models can be used to integrate high-dimensional omics information into a prediction model for lung adenocarcinoma to improve the prognostic prediction and discover potential targets. This approach may be a powerful predictive tool for clinicians treating malignant tumours.

Identification of a novel tumour microenvironment-based prognostic biomarker in skin cutaneous melanoma

Skin cutaneous melanoma (SKCM) is one of the most destructive skin malignancies and has attracted worldwide attention. However, there is a lack of prognostic biomarkers, especially tumour microenvironment (TME)-based prognostic biomarkers. Therefore, there is an urgent need to investigate the TME in SKCM, as well as to identify efficient biomarkers for the diagnosis and treatment of SKCM patients. A comprehensive analysis was performed using SKCM samples from The Cancer Genome Atlas and normal samples from Genotype-Tissue Expression. TME scores were calculated using the ESTIMATE algorithm, and differential TME scores and differentially expressed prognostic genes were successively identified. We further identified more reliable prognostic genes via least absolute shrinkage and selection operator regression analysis and constructed a prognostic prediction model to predict overall survival. Receiver operating characteristic analysis was used to evaluate the diagnostic efficacy, and Cox regression analysis was applied to explore the relationship with clinicopathological characteristics. Finally, we identified a novel prognostic biomarker and conducted a functional enrichment analysis. After considering ESTIMATEScore and tumour purity as differential TME scores, we identified 34 differentially expressed prognostic genes. Using least absolute shrinkage and selection operator regression, we identified seven potential prognostic biomarkers (SLC13A5, RBM24, IGHV3OR16-15, PRSS35, SLC7A10, IGHV1-69D and IGHV2-26). Combined with receiver operating characteristic and regression analyses, we determined PRSS35 as a novel TME-based prognostic biomarker in SKCM, and functional analysis enriched immune-related cells, functions and signalling pathways. Our study indicated that PRSS35 could act as a potential prognostic biomarker in SKCM by investigating the TME, so as to provide new ideas and insights for the clinical diagnosis and treatment of SKCM.

Reassessing Revascularization Strategies in Coronary Artery Disease and Type 2 Diabetes Mellitus

Percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG) is still controversial in patients with coronary artery disease (CAD) and type 2 diabetes mellitus (T2DM). Here, we aimed to evaluate the long-term follow-up events of PCI and CABG in these populations. Relevant randomized controlled trials were retrieved from PubMed, Embase, and the Cochrane databases. The pooled results were represented as risk ratios (RRs) with 95% confidence intervals (CIs) with STATA software. A total of six trials with 1,766 patients who received CABG and 2,262 patients who received PCI were included in our study. Patients in the CABG group were significantly associated with a lower all-cause mortality compared with those in the PCI group (RR = 0.74, 95% CI = 0.56–0.98, P = 0.037). Cardiac mortality, recurrent myocardial infarction, and repeat revascularization were also significantly lower in the CABG group (RR = 0.79, 95% CI = 0.40–1.53, P = 0.479; RR = 0.70, 95% CI = 0.32–1.56, P = 0.387; and RR = 0.36, 95% CI = 0.28–0.46, P < 0.0001; respectively). However, compared with the PCI group, the cerebral vascular accident was higher in the CABG group (RR = 2.18, 95% CI = 1.43–3.33, P < 0.0001). There was no publication bias in our study. CABG revascularization was associated with significantly lower long-term adverse clinical outcomes, except cerebral vascular accident, compared with PCI in patients with CAD and T2DM.

Systematic Review Registration: PROSPERO, identifier: CRD42020216014.

Rivaroxaban for cancer-associated venous thromboembolism

All cancers can increase the risk of developing venous thromboembolism (VTE), and anticoagulants should be considered as an optimal treatment for patients suffering from cancer-associated VTE. However, there is still a debate about whether the new oral anticoagulant, rivaroxaban, can bring better efficacy and safety outcomes globally. Thus, this systematic review and meta-analysis was conducted to evaluate the efficacy and safety of rivaroxaban. We searched PubMed, Cochrane Central Register of Controlled Trials, Web of Science, and China National Knowledge Infrastructure for relevant published papers before 1 September 2019, with no language restrictions. The primary outcomes are defined as the recurrence of VTE. The secondary outcomes are defined as clinically relevant non-major bleeding, adverse major bleeding events, and all-cause of death. The data were analyzed by Stata with risk ratio (RR) and 95% confidence interval (CI). Four trials encompassing 1996 patients were included. Rivaroxaban reduced recurrent VTE with no significant difference (RR = 0.68, 95% CI = 0.43-1.07). Similarly, there were no significant differences in adverse major bleeding events (RR = 0.86, 95% CI = 0.37-2.00), clinically relevant non-major bleeding (RR = 1.24, 95% CI = 0.73-2.12) and all-cause mortality (RR = 0.76, 95% CI = 0.40-1.44). In a selected study population of cancer patients with VTE, rivaroxaban is as good as other anticoagulants. Further, carefully designed randomized controlled trials should be performed to confirm these results.

Clinicopathological and Prognostic Roles of STAT3 and Its Phosphorylation in Glioma

Glioma is defined as a common brain tumor which causes severe disability or death. As many genes are reported to relate with glioma's occurrence and development, their prognostic and therapeutic value still remains uncertain. This study aimed at investigating the association between STAT3/p-STAT3 and glioma prognosis. Nine studies (12 trials) scored ≥5 on the Newcastle-Ottawa scale were meta-analysed from the Medline, Embase, and Web of Science databases. We found that STAT3/p-STAT3 overexpression in glioma patients was associated with worse overall survival (hazard  ratio  (HR) = 1.40, 95%confidence  interval  (CI) = 1.05 ~ 1.86, P = 0.020), progression-free survival (HR = 2.05, 95%CI = 1.63 ~ 2.58, P < 0.001), and better recurrence-free survival (HR = 0.37, 95%CI = 0.15 ~ 0.95, P < 0.039). Subgroup analysis implied that STAT3/p-STAT3 overexpression was associated with worse OS in standard treatment (HR = 1.80, 95%CI = 1.06 ~ 3.04, P = 0.030), and in China (HR = 2.18, 95%CI = 1.77 ~ 2.70, P < 0.001), and metaregression analysis indicated countries (P = 0.001) may be the source of heterogeneity in our study. In conclusion, we suggested STAT3/p-STAT3 was associated with poor prognosis in patients with glioma, which indicated that STAT3/p-STAT3 might be a valuable prognostic biomarker and a promising therapeutic target for glioma.

Long Intergenic Non-protein Coding RNA 511 in Cancers

Background: Long intergenic non-protein coding RNA 511 (LINC00511) is upregulated in diverse cancers and involved in prognosis. This study aimed to evaluate the prognostic profile of LINC00511 in cancer patients.

Methods: Published studies evaluating the prognosis of LINC00511 in patients with different cancers were identified from Medline, Embase, and Web of Science. Analysis of the association between LINC00511 and clinicopathological characteristics was conducted. GEPIA was used to validation and functional analysis and LnCeVar was used to get genomic variations.

Results: We eventually included 9 studies, and the combined results showed LINC00511 was significantly associated with decreased OS (HR = 3.18, 95% CI = 2.29 ~ 4.42, P < 0.001) albeit with mild heterogeneity (I² = 58.1%, P_h = 0.014), similarly in cancer type subgroups: breast cancer, digestive system cancer, and cervical cancer (all P < 0.001). There is no publication bias and meta-regression indicated follow-up time maybe heterogeneity of the results (P = 0.008). Additionally, LINC00511 appeared to be correlated with age, clinical stage, tumor size, and lymph node metastasis. Those findings were confirmed in GEPIA. Through LnCeVars, gene ontology and functional pathways were enriched, and dysregulated hallmarks and related ceRNA network of LINC00511 were disturbed.

Conclusions: LINC00511 could be predictive of poor OS and lymph node metastasis in multiple cancers, in another word, LINC00511 serves as an unfavorable prognostic factor, and its mechanism is related to ceRNA.