Gallstones is common and associated with substantial health and economic burden. We aimed to comprehensively evaluate the prevalence and incidence of gallstones in the 21^st century. We systematically searched PubMed and Embase to identify studies reporting the prevalence and/or incidence of gallstones between Jan 1, 2000 and Nov 18, 2023. Pooled prevalence and incidence were calculated using DerSimonian and Laird's random-effects model. We performed subgroup analyses and meta-regression based on age, sex, geographic location, population setting, and modality of detection to examine sources of heterogeneity. Based on 115 studies with 32,610,568 participants, pooled prevalence of gallstones was 6.1% (95% CI, 5.6-6.5) Prevalence was higher in females vs. males (7.6% vs. 5.4%), in South America vs. Asia (11.2% vs. 5.1%), in upper-middle income country vs. high-income country (8.9% vs. 4.0%) and with advancing age. On sensitivity analysis of population-based studies, prevalence of gallstones was 5.5% (95% CI, 4.1-7.4; n=44 studies), and on limiting to imaging-based detection modalities, prevalence was 6.7% (95% CI, 6.1-7.3; n=101 studies). Prevalence was stable over the last 20 years. Based on 12 studies, incidence of gallstones was 0.47 per 100 person-years (95% CI, 0.37-0.51), without differences between males and females, and with rising incidence in more recent studies. Globally, 6% of the population have gallstones, with higher rates in females and in South America. The incidence of gallstones may be rising. Our findings call for prioritizing research on prevention of gallstones.

Background: Tumor mutation burden (TMB) have been served as the most prevalent biomarkers to predict immunotherapy response. LRP1B (low-density lipoprotein receptor-related protein 1B) is frequently mutated in melanoma, non-small cell lung cancer (NSCLC) and other tumors; however, its association with TMB and survival in patients with immunotherapy remains unknown. Methods: We curated somatic mutation data and clinicopathologic information from 332 melanoma immunotherapy samples for discovery and 113 NSCLC samples for further corroboration. Bayesian variants non-negative matrix factorization was used to extract tumor mutational signatures. Multivariate Cox and logistic regression models were applied to adjust confounding factors. The CIBERSORT and GSEA algorithm were separately used to infer leukocyte relative abundance and significantly enriched pathways. Results: Patients with LRP1B mutation were identified to be associated with prolonged survival in both immunotherapy cohort. Higher tumor mutation burden was found in LRP1B mutated patients, and the association remained significant after controlling for age, gender, stage, mutations in TP53 and ATR, and mutational signatures. Immune response and cell cycle regulation circuits were among the top enriched pathways in samples with LRP1B mutations. Conclusion: Our studies suggested sequencing even a single, frequently mutated gene may provide insight into genome-wide mutational burden, and may serve as a biomarker to predict immune response.

Esophageal squamous cell carcinoma (ESCC) is often diagnosed at an advanced and incurable stage. Information on driver genes and prognosticators in ESCC remains incomplete. The objective was to elucidate significantly mutated genes (SMGs), mutational signatures, and prognosticators in ESCC. Three MutSig algorithms (i.e. MutSigCV, MutSigCL and MutSigFN) and ‘20/20+’ ratio-metric were employed to identify SMGs. Nonnegative matrix factorization was used to decipher mutational signatures. Kaplan–Meier survival analysis, multivariate Cox and logistic regression models were applied to analyze association between mutational features and clinical parameters. We identified 26 SMGs, including 8 novel (NAV3, TENM3, PTCH1, TGFBR2, RIPK4, PBRM1, USP8 and BAP1) and 18 that have been previously reported. Three mutational signatures were identified to be prevalent in ESCC including clocklike C>T at CpG, APOBEC overactive C>T at TpCp[A/T], and a signature featured by T>C substitution. The T>C mutational signature was significantly correlated with alcohol consumption (OR: 3.59; 95% CI: 2.30–5.67; P < 0.001). This alcohol consumption signature was also observed in liver cancer and head and neck squamous cell carcinoma, and its mutational activity was substantially higher in samples with mutations in TP53. Survival analysis revealed that TENM3 mutations (HR: 5.54; CI: 2.68–11.45; P < 0.001) and TP53 hotspot mutation p.R213* (HR: 3.37; CI: 1.73–8.06; P < 0.001) were significantly associated with shortened survival outcome. The association remained statistically significant after controlling for age, gender, TNM stage and tumor grade. We have uncovered several new SMGs in ESCC and defined an alcohol consumption related mutational signature. TENM3 mutations and the TP53 hotspot mutation p.R213* are independent prognosticators for poor survival in ESCC.

The Gail model has been widely used and validated with conflicting results. The current study aims to evaluate the performance of different versions of the Gail model by means of systematic review and meta-analysis with trial sequential analysis (TSA). Three systematic review and meta-analyses were conducted. Pooled expected-to-observed (E/O) ratio and pooled area under the curve (AUC) were calculated using the DerSimonian and Laird random-effects model. Pooled sensitivity, specificity and diagnostic odds ratio were evaluated by bivariate mixed-effects model. TSA was also conducted to determine whether the evidence was sufficient and conclusive. Gail model 1 accurately predicted breast cancer risk in American women (pooled E/O = 1.03; 95% CI 0.76–1.40). The pooled E/O ratios of Caucasian-American Gail model 2 in American, European and Asian women were 0.98 (95% CI 0.91–1.06), 1.07 (95% CI 0.66–1.74) and 2.29 (95% CI 1.95–2.68), respectively. Additionally, Asian-American Gail model 2 overestimated the risk for Asian women about two times (pooled E/O = 1.82; 95% CI 1.31–2.51). TSA showed that evidence in Asian women was sufficient; nonetheless, the results in American and European women need further verification. The pooled AUCs for Gail model 1 in American and European women and Asian females were 0.55 (95% CI 0.53–0.56) and 0.75 (95% CI 0.63–0.88), respectively, and the pooled AUCs of Caucasian-American Gail model 2 for American, Asian and European females were 0.61 (95% CI 0.59–0.63), 0.55 (95% CI 0.52–0.58) and 0.58 (95% CI 0.55–0.62), respectively. The pooled sensitivity, specificity and diagnostic odds ratio of Gail model 1 were 0.63 (95% CI 0.27–0.89), 0.91 (95% CI 0.87–0.94) and 17.38 (95% CI 2.66–113.70), respectively, and the corresponding indexes of Gail model 2 were 0.35 (95% CI 0.17–0.59), 0.86 (95% CI 0.76–0.92) and 3.38 (95% CI 1.40–8.17), respectively. The Gail model was more accurate in predicting the incidence of breast cancer in American and European females, while far less useful for individual-level risk prediction. Moreover, the Gail model may overestimate the risk in Asian women and the results were further validated by TSA, which is an addition to the three previous systematic review and meta-analyses. PROSPERO CRD42016047215 .

Immune checkpoint blockade (ICB) therapy has achieved remarkable clinical benefit in non‐small‐cell lung cancer (NSCLC), but our understanding of biomarkers that predict the response to ICB remain obscure. Here we integrated somatic mutational profile and clinicopathologic information from 113 NSCLC patients treated by ICB (CTLA‐4/PD‐1). High tumor mutation burden (TMB) and neoantigen burden were identified significantly associated with improved efficacy in NSCLC immunotherapy. Furthermore, we identified apolipoprotein B mRNA editing enzyme, catalytic polypeptide‐like (APOBEC) mutational signature was markedly associated with responding of ICB therapy (log‐rank test, P = .001; odds ratio (OR), 0.18 [95% CI, 0.06‐0.50], P < .001). The association with progression‐free survival remained statistically significant after controlling for age, sex, histological type, smoking, PD‐L1 expression, hypermutation, smoking signature and mismatch repair (MMR) (HR, 0.30 [95% CI, 0.12‐0.75], P = .010). Combined high TMB with APOBEC signature preferably predict immunotherapy responders in NSCLC cohort. The CIBERSORT algorithm revealed that high APOBEC mutational activity samples were associated with increased infiltration of CD4 memory activated T cells, CD8⁺ T cells and natural killer (NK) cells, but reduced infiltration of regulatory T cells. Besides, individual genes mutation of IFNGR1 or VTCN1 were only found in responders; however, the PTEN mutation was only found in non‐responders (Fisher's exact test, all P < .05). These findings may be applicable for guiding immunotherapy for patients with NSCLC.

The present systematic review and meta-analysis was conducted to assess any association between breastfeeding and the risk of ovarian cancer. A systematic search of published studies was performed in PUBMED and EMBASE and by reviewing reference lists from retrieved articles through March 2013. Data extraction was conducted independently by two authors. Pooled relative risk ratios were calculated using random-effect models. Totals of 5 cohort studies and 35 case-control studies including 17,139 women with ovarian cancer showed a 30% reduced risk of ovarian cancer when comparing the women who had breastfed with those who had never breastfed (pooled RR = 0.70, 95% CI: 0.64-0.76; p = 0.00), with significant heterogeneity in the studies (p = 0.00; I2 = 76.29%). A significant decreasd in risk of epithelial ovarian cancer was also observed (pooled RR = 0.68, 95% CI: 0.61-0.76). When the participants were restricted to only parous women, there was a slightly attenuated but still significant risk reduction of ovarian cancer (pooled RR = 0.76, 95% CI: 0.69-0.83). For total breastfeeding duration, the pooled RRs in the < 6 months, 6-12 months and > 12 months of breastfeeding subgroups were 0.85 (95% CI: 0.77-0.93), 0.73 (95% CI: 0.65-0.82) and 0.64 (95%CI: 0.56-0.73), respectively. Meta-regression of total breastfeeding duration indicated an increasing linear trend of risk reduction of ovarian cancer with the increasing total breastfeeding duration (p = 0.00). Breastfeeding was inversely associated with the risk of ovarian cancer, especially long-term breastfeeding duration that demonstrated a stronger protective effect.