The effect of sleep duration on cancer risk remains controversial. We aimed to quantify the available evidence on this relationship using categorical and dose–response meta-analyses. Population-based cohort studies and case-control studies with at least three categories of sleep duration were identified by searching PubMed, EMBASE, and the Cochrane Library database up to July 2017. Sixty-five studies from 25 articles were included, involving 1,550,524 participants and 86,201 cancer cases. The categorical meta-analysis revealed that neither short nor long sleep duration was associated with increased cancer risk (short: odds ratio [OR] = 1.01, 95% confidence intervals [CI] = 0.97–1.05; long: OR = 1.02, 95% CI = 0.97–1.07). Subgroup analysis revealed that short sleep duration was associated with cancer risk among Asians (OR = 1.36; 95% CI: 1.02–1.80) and long sleep duration significantly increased the risk of colorectal cancer (OR = 1.21; 95% CI: 1.08–1.34). The dose–response meta-analysis showed no significant relationship between sleep duration and cancer risk. When treated as two linear piecewise functions with a cut point of 7 h, similar nonsignificant associations were found (per 1-h reduction: OR = 1.02, 95% CI = 0.98–1.07; per 1-h increment: OR = 1.003, 95% CI = 0.97–1.03). Categorical meta-analysis indicated that short sleep duration increased cancer risk in Asians and long sleep duration increased the risk of colorectal cancer, but these findings were not consistent in the dose–response meta-analysis. Long-term randomized controlled trials and well-designed prospective studies are needed to establish causality and to elucidate the mechanism underlying the association between sleep duration and cancer risk.

Human papillomavirus (HPV) is one of the most prevalent sexually transmitted viruses. Despite the increasing evidence of HPV prevalence in semen, the worldwide distribution of HPV types in semen and risk for male infertility remain inconclusive. Four electronic databases were searched for English language studies conducted between January 1990 and December 2016 that reported HPV DNA prevalence in semen. Based on the PRISMA guidelines, HPV prevalence was estimated among general population and fertility clinic attendees, respectively, and heterogeneity testing was performed using Cochran’s Q and I 2 statistics. The association between HPV positivity and male infertility was evaluated by a meta-analysis of case-control studies. A total of 31 eligible studies comprising 5194 males were included. The overall prevalence of HPV DNA in semen was 11.4% (95% CI = 7.8-15.0%) in general population (n = 2122) and 20.4% (95% CI = 16.2-24.6%) in fertility clinic attendees (n = 3072). High-risk type prevalence was 10.0% (95% CI = 5.9-14.0%) and 15.5% (95% CI = 11.4-19.7%), respectively. HPV16 was the most common type, with a prevalence of 4.8% (95% CI = 1.7-7.8%) in general population and 6.0% (95% CI = 3.8-8.2%) in fertility clinic attendees. A significantly increased risk of infertility was found for males with HPV positivity in semen (OR = 2.93, 95% CI = 2.03-4.24). Seminal HPV infection is common worldwide, which may contribute to the risk of male infertility.

Background: Circular RNAs (circRNAs) are involved in regulatory processes of ubiquitination and deubiquitination in various tumors at post-transcriptional epigenetic modification level. However, the underlying mechanism and its biological functions of circRNAs in the advanced laryngeal squamous cell carcinoma (LSCC) remain obscure. Methods: RNA sequencing and quantitative real-time PCR (qRT-PCR) assays were applied to screen for circRNAs differentially expressed in LSCC tissues and cell lines. The candidate RNA-binding proteins and target signalling pathway were detected by RNA pull-down and mass spectrometry, in situ hybridization (ISH), immunohistochemistry (IHC), qRT-PCR assays, and bioinformatics analysis. The functional roles of these molecules were investigated using in vitro and in vivo experiments including EdU, transwell, wound healing, western blot assays, and the xenograft mice models. The molecular mechanisms were identified using RNA pull-down assays, RNA immunoprecipitation (RIP), Co-IP, ISH, Ubiquitination assay, bioinformatics analysis, and the rescue experiments. Results: Here, we unveil that microtubule cross-linking factor 1 circRNA (circMTCL1, circ0000825) exerts its critical oncogenic functions by promoting complement C1q-binding protein (C1QBP)-dependent ubiquitin degradation and subsequently activating Wnt/β-catenin signalling in laryngeal carcinoma initiation and development. Specifically, circMTCL1 was remarkably up-regulated in the paired tissues of patients with LSCC (n = 67), which predicted a worse clinical outcome. Functionally, circMTCL1 exerted oncogenic biological charactersistics by promoting cell proliferative capability and invasive and migrative abilities. Ectopic circMTCL1 augumented cell proliferation, migration, and invasion of LSCC cells, and this effect could be reversed by C1QBP knocking down in vitro and in vivo. Mechanistically, circMTCL1 directly recruited C1QBP protein by harboring the specific recognized sequence (+ 159 − + 210), thereby accelerating the translation of C1QBP expression by inhibiting its ubiquitin–proteasome-mediated degradation. Importantly, the direct interaction of C1QBP with β-catenin protein was enhanced via suppressing the β-catenin phosphorylation and accelerating its accumulation in cytoplasm and nucleus. Conclusion: Our findings manifested a novel circMTCL1-C1QBP-β-catenin signaling axis involving in LSCC tumorigenesis and progression, which shed new light on circRNAs-ubiquitous acidic glycoprotein mediated ubiquitin degradation and provided strategies and targets in the therapeutic intervention of LSCC.

Rationale: Over 40% of lung cancer cases occurred in never-smokers in China. However, high-risk never-smokers were precluded from benefiting from lung cancer screening as most screening guidelines did not consider them. Objectives: We sought to develop and validate prediction models for 3-year lung cancer risks for never- and ever-smokers, named the China National Cancer Center Lung Cancer models (China NCC-LCm2021 models). Methods: 425,626 never-smokers and 128,952 ever-smokers from the National Lung Cancer Screening program were used as the training cohort and analyzed using multivariable Cox models. Models were validated in two independent prospective cohorts: one included 369,650 never-smokers and 107,678 ever-smokers (841 and 421 lung cancers), and the other included 286,327 never-smokers and 78,469 ever-smokers (503 and 127 lung cancers). Measurements and Main Results: The areas under the receiver operating characteristic curves in the two validation cohorts were 0.698 and 0.673 for never-smokers and 0.728 and 0.752 for ever-smokers. Our models had higher areas under the receiver operating characteristic curves than other existing models and were well calibrated in the validation cohort. The China NCC-LCm2021 ≥0.47% threshold was suggested for never-smokers and ≥0.51% for ever-smokers. Moreover, we provided a range of threshold options with corresponding expected screening outcomes, screening targets, and screening efficiency. Conclusion: The construction of the China NCC-LCm2021 models can accurately reflect individual risk of lung cancer, regardless of smoking status. Our models can significantly increase the feasibility of conducting centralized lung cancer screening programs because we provide justified thresholds to define the high-risk population of lung cancer and threshold options to adapt different configurations of medical resources.

Background: Screening with low‐dose computed tomography (LDCT) is an efficient way to detect lung cancer at an earlier stage, but has a high false‐positive rate. Several pulmonary nodules risk prediction models were developed to solve the problem. This systematic review aimed to compare the quality and accuracy of these models.Methods: The keywords “lung cancer,” “lung neoplasms,” “lung tumor,” “risk,” “lung carcinoma” “risk,” “predict,” “assessment,” and “nodule” were used to identify relevant articles published before February 2021. All studies with multivariate risk models developed and validated on human LDCT data were included. Informal publications or studies with incomplete procedures were excluded. Information was extracted from each publication and assessed.Results: A total of 41 articles and 43 models were included. External validation was performed for 23.2% (10/43) models. Deep learning algorithms were applied in 62.8% (27/43) models; 60.0% (15/25) deep learning based researches compared their algorithms with traditional methods, and received better discrimination. Models based on Asian and Chinese populations were usually built on single‐center or small sample retrospective studies, and the majority of the Asian models (12/15, 80.0%) were not validated using external datasets.Conclusion: The existing models showed good discrimination for identifying high‐risk pulmonary nodules, but lacked external validation. Deep learning algorithms are increasingly being used with good performance. More researches are required to improve the quality of deep learning models, particularly for the Asian population.

Background: Albumin is supposed to be associated with cancer risk. However, evidence on serum albumin and cancer risk among the Chinese population is sparse. This study was conducted to evaluate the association between pre‐diagnostic serum albumin and cancer risk among Chinese.Methods: A total of 82,061 participants with baseline information on serum albumin concentration in the Kailuan cohort were recruited. Cox proportional hazards models and restricted cubic spline (RCS) analyses were used to evaluate the association between pre‐diagnostic serum albumin and cancer risk.Results: Albumin levels were inversely associated with overall cancer risk (HR [95% CI]: Q2, Q3, Q4 vs. Q1: 0.91 [0.78–1.07], 0.80 [0.70–0.92], 0.73 [0.63–0.85]), and the risk of lung, colorectal, and liver cancer (HR [95% CI]: Q4 vs. Q1: lung: 0.70 [0.52–0.95], colorectal: 0.43 [0.26–0.72], liver: 0.59 [0.36–0.95]). After excluding new cancer cases within 2 years since enrollment, a more significant association was observed for liver cancer (HR [95% CI]: Q4 vs. Q1: 0.41 [0.21–0.78]), while associations converted to nonsignificant for lung and colorectal cancer. The RCS model suggested an inverse linear association between albumin and the risk of overall cancer (p‐overall < 0.0001, p‐nonlinear = 0.3716) and liver cancer (p‐overall = 0.0002, p‐nonlinear = 0.1807).Conclusions: Our findings suggest that pre‐diagnostic serum albumin is inversely and linearly associated with cancer risk among the Chinese population. This study provides evidence that albumin may be valuable to the prediction and stratification of cancer risk in the general population. However, the biological mechanism and clinical significance remain to be elucidated. Population studies with longer follow‐up time as well as experimental studies are further required.