Although accumulating data have suggested the development of cancer in systemic lupus erythematosus (SLE) patients, these results remain inconsistent. To examine such a putative association, this analysis reports the association between SLE and the risks of 24 cancer types. Online databases PubMed, EMBASE, and Web of Science were searched comprehensively for eligible studies, published up to 15 May 2018. Pooled standardized incidence rates (SIRs) with 95% confidence intervals (CIs) were utilized to reveal their associations. A total of 24 eligible studies were ultimately enrolled. Our results indicated that SLE was associated with increased risk of overall cancers, cancer risk in both genders, non-Hodgkin’s lymphoma, Hodgkin’s lymphoma, leukemia, multiple myeloma, cervix, vagina/vulva, renal, bladder, esophagus, gastric, hepatobiliary, lung, oropharynx, larynx, non-melanoma skin, and thyroid cancers. Additionally, SLE could reduce the risk of prostate cancer and cutaneous melanoma; however, it was not significantly associated with breast, uterus, ovarian, pancreatic, colorectal, or brain cancers. Our results shed light SLE being correlated with increased risk for 16 involved cancers and decreased risk for prostate cancer and cutaneous melanoma. This comprehensive meta-analysis provides epidemiological evidence supporting the associations between SLE and cancer risk. This evidence could be utilized to drive public policies and to help guide personalized medicine to better manage SLE and reduce associated cancer morbidity and mortality.

To evaluate the validity of CHAC1 for predicting the prognosis of kidney renal clear cell carcinoma (KIRC) and to explore its therapeutic potential for KIRC, we conducted several bioinformatic analyses using the sequencing data and clinical information derived from online databases. We found CHAC1 is down‐regulated in KIRC samples when compared with normal samples but up‐regulated in KIRC samples with relatively higher malignancy and later stages. Univariate cox analysis and multivariate cox regression analysis were conducted and the results revealed up‐regulated CHAC1 is an independent risk factor for poor prognosis of KIRC. Further, the nomogram model based on the result of multivariate cox regression analysis was constructed and effectively predicted patients' 1‐year, 3‐year and 5‐year survival respectively. The correlation analyses showed CHAC1 is associated with the immune pathway markers of memory B cell, natural killer cell and type1 T helper cell as well as the checkpoint genes like ADORA2A, CD200, CD44, CD70, HHLA2, NRP1, PDCD1LG2 and TNFRSF18. Furthermore, experiments in vitro indicated CHAC1 could induce cell death in KIRC cell lines but had limited influence on cell migration and cell invasion. In conclusion, CHAC1 is found a valid indicator for poor prognosis of kidney renal clear cell carcinoma.

Galectin-3 as a β-galactoside-binding protein, has been found to be involved in tumor cell growth, anti-apoptosis, adhesion, angiogenesis, invasion, and distant metastases, indicating that it may play a pivotal role in cancer development and progression. However, their results remain debatable and inconclusive. Hence, this meta-analysis was performed to clarify the precise predictive value of galectin-3 in various cancers. PubMed, Web of Science, Embase, Cochrane Library, CNKI and Wanfang databases were searched comprehensively for eligible studies up to July 15, 2018. Pooled hazard ratios (HRs) with 95% confidence intervals (CIs) of OS or DFS/PFS/RFS were calculated to demonstrate their associations. A total of 36 relevant studies were ultimately enrolled in this meta-analysis. Our results shed light on the significant association of elevated galectin-3 expression with reduced OS or DFS/RFS/PFS in overall cancer patients (pooled HR = 1.79, 95% CI 1.42–2.27, I²= 67.3%, p < 0.01; pooled HR = 1.57, 95% CI 1.04–2.37, I²= 67.1%, p = 0.001). In tumor type subgroup analysis, we found high expression of galectin-3 was correlated with shorter OS or DFS/RFS/PFS in colorectal cancer (pooled HR = 3.05, 95% CI 2.13–4.35, I²= 0.0%, p = 0.734; pooled HR = 2.49, 95% CI 1.82–3.41, I² = 0.0%, p = 0.738; respectively) and meanwhile it merely associated with reduced OS in ovarian cancer or non-small cell lung cancer (pooled HR = 2.24, 95% CI 1.38–3.64, I²= 0.0%, p = 0.910; pooled HR = 2.07, 95% CI 1.48–2.88, I²= 0.0%, p = 0.563; separately). Taken together, our results suggested that galectin-3 played an oncogenic role in colorectal cancer, ovarian cancer and non-small cell lung cancer, indicating it could be a promising biomarker and a novel therapeutic target for them. Further studies were warranted to validate our findings.

Background: The role of glycolysis in tumorigenesis has received increasing attention and multiple glycolysis-related genes (GRGs) have been proven to be associated with tumor metastasis. Hence, we aimed to construct a prognostic signature based on GRGs for clear cell renal cell carcinoma (ccRCC) and to explore its relationships with immune infiltration. Methods: Clinical information and RNA-sequencing data of ccRCC were obtained from The Cancer Genome Atlas (TCGA) and ArrayExpress datasets. Key GRGs were finally selected through univariate COX, LASSO and multivariate COX regression analyses. External and internal verifications were further carried out to verify our established signature. Results: Finally, 10 GRGs including ANKZF1, CD44, CHST6, HS6ST2, IDUA, KIF20A, NDST3, PLOD2, VCAN, FBP1 were selected out and utilized to establish a novel signature. Compared with the low-risk group, ccRCC patients in high-risk groups showed a lower overall survival (OS) rate (P = 5.548Ee-13) and its AUCs based on our established signature were all above 0.70. Univariate/multivariate Cox regression analyses further proved that this signature could serve as an independent prognostic factor (all P < 0.05). Moreover, prognostic nomograms were also created to find out the associations between the established signature, clinical factors and OS for ccRCC in both the TCGA and ArrayExpress cohorts. All results remained consistent after external and internal verification. Besides, nine out of 21 tumor-infiltrating immune cells (TIICs) were highly related to high- and low- risk ccRCC patients stratified by our established signature. Conclusions: A novel signature based on 10 prognostic GRGs was successfully established and verified externally and internally for predicting OS of ccRCC, helping clinicians better and more intuitively predict patients’ survival.

To investigate the potential prognostic role of pre-treatment prognostic nutritional index (PNI) in urinary cancers. Relevant articles were searched comprehensively from PubMed, Embase and Web of Science, up to November 2018. The pooled hazard ratios (HRs) with 95% confidence intervals (CIs) were extracted to evaluate their associations. A total of 12 related articles including 6561 patients were ultimately enrolled. Our results indicated that a relatively lower level of pre-treatment PNI was associated with decreased OS, CSS/DSS and DFS/RFS/PFS (pooled HR = 1.68, 95% CI 1.45–1.95; pooled HR = 1.57, 95% CI 1.33–1.86; pooled HR = 1.75, 95% CI 1.53–1.99, respectively). Subsequent stratified analysis by cancer type for OS showed that PNI could also be a predictor no matter in renal cell cancer (RCC) or bladder cancer (BC) (pooled HR = 1.65, 95% CI 1.37–1.97 and pooled HR = 1.67, 95% CI 1.20–2.33). Similar results could be found in DFS/RFS/PFS (RCC: HR = 1.81, 95% CI 1.54–2.13 and BC: HR = 1.68, 95% CI 1.32–2.12) and in CSS/DSS (RCC: HR = 1.50, 95% CI 1.23–1.82 and upper tract urothelial carcinoma: HR = 1.61, 95% CI 1.13–2.28). As for the treatment subgroup, a relatively lower level of PNI could also be a positive predictor for OS (surgery: HR = 1.64, 95% CI 1.40–1.93; target therapy: HR = 1.88, 95% CI 1.34–2.63) and DFS/RFS/PFS (surgery: HR = 1.69, 95% CI 1.47–1.95; target therapy: HR = 2.14, 95% CI 1.50–3.05). The outcomes of us shed light on that elevated pre-treatment PNI was positively associated with OS, CSS/DSS and DFS/RFS/PFS, indicating that it could be an independent prognostic factor in urinary cancers.

Background: METTL14, as one of N6-methyladenosine (m6A) related genes, has been found to be associated with promoting tumorigenesis in different types of cancers. This study was aimed to investigate the prognostic value of METTL14 in clear cell renal cell carcinoma (ccRCC).Methods: We collected ccRCC patients’ clinicopathological parameters information and 13 m6A related genes expression from The Cancer Genome Atlas (TCGA) database. Univariate and multivariate Cox regression analyses were conducted to investigate whether METTL14 could serve as an independent factor correlated with overall survival (OS). Gene Set Enrichment Analysis (GSEA) was carried out to identify METTL14-related signaling pathways. Moreover, a risk score (RS) was calculated to predict the prognosis of ccRCC. Quantitative real-time PCR (qRT-PCR) was also utilized to verify the expression of METTL14 in clinical specimens.Results: Differently expressed m6A related genes were identified between ccRCC tissues and normal tissues. Therein, METTL14 was lowly expressed in ccRCC tissues and verified by qRT-PCR (all p < 0.01). Survival analysis indicated that high expression of METTL14 was associated with better OS (p = 1e−05). GSEA results revealed that high METTL14 expression was enriched in ERBB pathway, MAPK pathway, mTOR pathway, TGF-β pathway and Wnt pathway. Moreover, METTL14 was proved to be an independent prognostic factor by means of univariate and multivariate Cox regression analyses. Nomogram integrating both the METTL14 expression and clinicopathologic variables was also established to provide clinicians with a quantitative approach for predicting survival probabilities of ccRCC. Furthermore, a METTL14-based riskscore (RS) was developed with significant OS (p = 6.661e−16) and increased AUC of 0.856. Besides, significant correlated genes with METTL14 were also provided.Conclusions: Our results indicated that METTL14 could serve as a favorable prognostic factor for ccRCC. Moreover, this study also provided a prognostic signature to predict prognosis of ccRCC and identified METTL14-related signaling pathways.