N7-methylguanosine (m7G), one of the most prevalent RNA modifications, has recently attracted significant attention. The m7G modification actively participates in biological and pathological functions by affecting the metabolism of various RNA molecules, including messenger RNA, ribosomal RNA, microRNA, and transfer RNA. Increasing evidence indicates a critical role for m7G in human disease development, especially cancer, and aberrant m7G levels are closely associated with tumorigenesis and progression via regulation of the expression of multiple oncogenes and tumor suppressor genes. Currently, the underlying molecular mechanisms of m7G modification in cancer are not comprehensively understood. Here, we review the current knowledge regarding the potential function of m7G modifications in cancer and discuss future m7G-related diagnostic and therapeutic strategies.

Background Tumour Necrosis Factor (TNF) family members play important roles in mounting anti-tumour immune responses, and clinical trials targeting these molecules are ongoing. However, the expression patterns and clinical significance of TNF members in lung adenocarcinoma (LUAD) remain unrevealed. This study aimed to explore the gene expression profiles of TNF family members in LUAD and constructed a TNF family-based prognosis signature. Methods In total, 1300 LUAD cases from seven different cohorts were collected. Samples from The Cancer Genome Atlas (TCGA) were used as the training set, and the RNA data from five Gene Expression Omnibus (GEO) datasets and qPCR data from 102 samples were used for validation. The immune profiles and potential immunotherapy response prediction value of the signature were also explored. Findings After univariate Cox proportional hazards regression and stepwise multivariable Cox analysis, a TNF family-based signature was constructed in the TCGA dataset that significantly stratified cases into high- and low-risk groups in terms of OS. This signature remained an independent prognostic factor in multivariate analyses. Moreover, the clinical significance of the signature was well validated in different clinical subgroups and independent validation cohorts. Further analysis revealed that signature high-risk patients were characterized by distinctive immune cell proportions and immune-suppressive states. Additionally, signature scores were positively related to multiple immunotherapy biomarkers. Interpretation This was the first TNF family-based model for predicting outcomes and immune landscapes for patients with LUAD. The capability of this signature for predicting immunotherapy response needs further validation.

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BackgroundThe etiology of birth defects has been widely studied but is not yet fully clarified, previously published data had suggested that maternal age or parity maybe involved, but without consistent conclusions.MethodsA population-based, case-control study was nested in a cohort of perinatal infants born from 2010 to 2012 in Baoan District, Shenzhen. Four categories of isolated birth defects were defined as cases: congenital heart defects (CHD, n = 693), polydactyly (n = 352), cleft lip with or without palate (CL/P, n = 159) and equinovarus (n = 119). Controls were non-malformed infants (n = 11,307) randomly selected from the same area and period. Odds ratios (ORs) and the 95% confidence intervals (CIs) were computed by multivariable unconditional logistic regression analysis.ResultsYoung maternal age (<25 years old) was associated with a reduced risk of CHD (adjusted OR = 0.73, 95% CI 0.59–0.90), while with an elevated risk of polydactyly (adjusted OR = 1.42, 95% CI 1.09-1.84). Increased risk of CL/P-affected pregnancy was observed in mothers older than 35 years old (adjusted OR = 2.12, 95% CI 1.26–3.57). Compared to primipara, those having their second, and third or more delivery were less likely to have infants with equinovarus, with significant adjusted ORs of 0.59 (0.40–0.89) and 0.42 (0.19–0.93), respectively.ConclusionMaternal age was significantly associated with CHD, polydactyly and CL/P relevant pregnancy. Mothers with higher parity might have lower risk of equinovarus occurrence in offsprings.

Background: Costimulatory molecules play significant roles in mounting anti-tumor immune responses, and antibodies targeting these molecules are recognized as promising adjunctive cancer immunotherapies. Here, we aim to conduct a first full-scale exploration of costimulatory molecules from the B7-CD28 and TNF families in patients with lung adenocarcinoma (LUAD) and generated a costimulatory moleculebased signature (CMS) to predict survival and response to immunotherapy. Methods: We enrolled 1549 LUAD cases across 10 different cohorts and included 502 samples from TCGA for discovery. The validation set included 970 cases from eight different Gene Expression Omnibus (GEO) datasets and 77 frozen tumor tissues with qPCR data. The underlying mechanisms and predictive immunotherapy capabilities of the CMS were also explored. Results: A five gene-based CMS (CD40LG, TNFRSF6B, TNFSF13, TNFRSF13C, and TNFRSF19) was initially constructed using the bioinformatics method from TCGA that classifies cases as high-vs. low-risk groups per OS. Multivariable Cox regression analysis confirmed that the CMS was an independent prognostic factor. As expected, CMS exhibited prognostic significance in the stratified cohorts and different validation cohorts. Additionally, the prognostic meta-analysis revealed that CMS was superior to the previous signature. Samples in high-and low-risk groups exhibited significantly different tumor-infiltrating leukocytes and inflammatory activities. Importantly, we found that the CMS scores were closely related to multiple immunotherapy biomarkers. Conclusion: We conducted the first and most comprehensive costimulatory molecule landscape analysis of patients with LUAD and built a clinically feasible CMS for prognosis and immunotherapy response prediction, which will be helpful for further optimize immunotherapies for cancer.

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Background Current strategies are insufficient to predict pathologically complete response (pCR) for esophageal squamous cell carcinomas (ESCCs) before treatment. Here, we aim to develop a novel long noncoding RNA (lncRNA) signature for pCR and outcome prediction of ESCCs through a multicenter analysis for a Chinese population. Methods Differentially expressed lncRNAs (DELs) between pCRs and less than pCR (