BACKGROUND:The associations between different types of diabetes, characterized by distinct pathophysiology and genetic architecture, and pancreatic ductal adenocarcinoma (PDAC) risk are not understood. METHODS:We investigated associations of genetic susceptibility to type 2 diabetes (T2D), 8 T2D mechanistic clusters, type 1 diabetes (T1D), and maturity-onset diabetes of the young (MODY) with PDAC risk. We used genome-wide association study (GWAS) summary-level statistics for T2D (242 283 cases, 1 569 734 controls), T1D (18 942 cases, 501 638 controls), and PDAC (10 244 cases and 360 535 controls) in individuals of European ancestry. RESULTS:Two-sample Mendelian randomization (MR) using the Robust Adjusted Profile Score (MR-RAPS) method indicated that genetically predicted T2D was associated with PDAC risk (OR = 1.10; 95% CI = 1.05 to 1.15), particularly the T2D obesity (OR = 1.28; 95% CI = 1.15 to 1.42) and lipodystrophy (OR = 1.25; 95% CI = 1.03 to 1.51) clusters. No association was observed for T1D with PDAC risk (OR = 1.01; 95% CI = 0.99 to 1.02). Pathway/gene-set analysis using the summary-based Adaptive Rank Truncated Product (sARTP) method revealed a significant association between the MODY gene-sets and PDAC risk (P = 1.5 × 10-8), which remained after excluding 20 known PDAC GWAS loci (P = 7.6 × 10-4). HNF1A, FOXA3, and HNF4A were the top contributing genes after excluding the previously identified GWAS loci regions. CONCLUSIONS:Our results from this genetic association study support that T2D, particularly the obesity and lipodystrophy mechanistic clusters, and MODY genomic susceptibility regions play a role in the etiology of PDAC.

Supplementary Table S3 shows results of univariate analysis for 36 biopsy-confirmed nonalcoholic fatty liver disease SNPs in the PanScan sample

Hepatocellular carcinoma (HCC) is a leading cause of cancer deaths worldwide, which is mostly diagnosed at advanced and incurable stages. The suboptimal performance of current screening approaches including serum alpha-fetoprotein testing and ultrasound, highlights the urgent need for novel biomarkers to enable risk stratification and early detection of HCC. Based on our previous mechanistic insights with data from human genomic studies available in The Cancer Genome Atlas (TCGA) and from animal models (Cell Rep. 2024.43(9):114676 and Sci Transl Med. 2021.13(624): eabk2267), we have identified functional protein markers associated with HCC such as TGFBR2, MSTN, and PKM2. In this study, we present a model based on the TGF-β and associated immune pathways for the HCC stratification in cirrhotic patients that incorporates biologically relevant proteins to capture ongoing pathophysiological changes that drive hepatocarcinogenesis. A proteomic analysis of 7, 000 proteins (SomaScan) utilizing serum samples (55 uL/each) from 311 individuals with cirrhosis, 18 of whom developed HCC by imaging criteria during the median 5-year follow-up. Using a multivariable logistic regression method, we conducted an unsupervised clustering analysis of TGF-β and the corresponding immune pathway and combined with well-described serum biomarkers to create a risk prediction model. We followed this with ELISA validation of the most promising biomarkers. In our prospective cirrhosis cohort (n=311), 18 HCC cases (5.8%) developed over a median follow-up of 5 years. Using unsupervised hierarchical clustering, we analyzed TGF-β pathway (n=28) and inflammatory/immune response proteins (n=36), grouping patients into two subgroups based on serum protein expression. Among HCC cases, 77.8% showed higher SMAD3 and 66.7% showed higher TGFBR2 expression. Cirrhotic patients with elevated expression of serum HMGB1/IL34/CCL3L1/IL37/SMAD3/TGFBR2 had a six-fold higher HCC risk (10.64% vs. 1.76%). A TGF-β model combining TGFBR2, GPC3, ANGPTL8, and GZMK outperformed the AFP model, with AUCs of 0.88 vs. 0.60 and better sensitivity (0.61 vs. 0.11) at 0.90 specificity. ELISA validation confirmed that MSTN, TGFBR2, and HMGB2 levels were significantly elevated in HCC (p<0.05). This study successfully demonstrates the high performance of our TGF-β and corresponding immune pathway biologically related biomarkers for HCC risk stratification in cirrhotic patients. The next steps will be large-scale validations of this biomarker panel in cirrhotic patients across all racial and ethnic subgroups in Phase II/III studies. Xiyan Xiang, Richard L. Amdur, Kirti Shetty, Herbert Yu, Linda L. Wong, Nyasha Chambwe, Sanjaya K. Satapathy, James M. Crawford, Lopa Mishra. Biomarkers in TGF-β and corresponding Immune pathway stratify HCC-risk in cirrhotic patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 7061.

Supplementary Table S10 shows descriptive Statistics for PanC4 sample

BACKGROUND:Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths, primarily due to late-stage diagnosis. In this multicenter study, our goal is to identify functional biomarkers that stratify the risk of HCC in patients with cirrhosis (CP) for early diagnosis. METHODS:Five thousand and eight serum proteins (Somascan) were analysed in Cohort A (477 CP, including 125 HCC). Clustering analysis of the TGF-β pathway-associated protein signature was performed in a longitudinal, prospective Cohort B (312 CP, in which 18 cases developed HCC over a 5-year follow-up period). Next, a multivariable prediction model was built using logistic regression analysis of cross-sectional data from a matched subgroup (n = 328, Cohort C). Model performance was 10-fold cross-validated across the entire Cohort A (n = 477). RESULTS:Longitudinal follow-up analysis revealed that patients with elevated TGF-β-related protein signature displayed a five-fold increased risk of developing HCC (9.68% vs. 1.91%). Compared to cirrhosis, serum MSTN, TGFBR2, and AFP levels raised in HCC were validated by ELISA (n = 200, odds ratio = 1.4-2.9, p < 0.05). In Cohort C, 88 proteins were significantly altered in HCC compared to cirrhosis (p < 0.05). The six-protein panel (TGFBR2, MSTN, AFP, COL18A1, GLUL, TP63) displayed a strong performance in the matched cohort C (AUC 0.87, sensitivity 0.88, specificity 0.72), alongside four clinical factors (Age, Sex, BMI, Bilirubin). A 10-fold cross-validation demonstrated a mean AUC of 0.86 in cohort A, with strong predictive power in obese/MASLD/ALD-related patients (AUCs: 0.862-0.921). CONCLUSIONS:The mechanism-based panel effectively stratifies HCC risk in cirrhotic patients, underscoring the need for Phase II/III validation.

Supplementary Table S2 shows results of univariate analysis for 22 imaging-defined nonalcoholic fatty liver disease SNPs in the PanScan sample

Supplementary Table S6 shows results of univariate analysis for 22 imaging defined nonalcoholic fatty liver disease SNPs in the PanC4 sample

Supplementary Table S1 shows results of univariate analysis for 77 chronically elevated serum alanine aminotransferase (cALT)-defined nonalcoholic fatty liver disease SNPs in the Pancreatic Cancer Cohort Consortium (PanScan) data

Supplementary Table S7 shows results of univariate analysis for 36 biopsy-confirmed nonalcoholic fatty liver disease SNPs in the PanC4 sample

Supplementary Table S8 shows results of univariate analysis for 17 imaging and biopsy validated SNPs in the PanC4 sample

Supplementary Figure S1 shows forest plot for minimally adjusted model for the PanScan sample.

Supplemental Table 8. Enrichment in regulatory regions for rs842357 and related SNPs

Host immunity involves various immune cells working in concert to achieve balanced immune response. Host immunity interacts with tumorigenic process impacting disease outcome. Clusters of different immune cells may reveal unique host immunity in relation to breast cancer progression. CIBERSORT algorithm was used to estimate relative abundances of 22 immune cell types in 3 datasets, METABRIC, TCGA, and our study. The cell type data in METABRIC were analyzed for cluster using unsupervised hierarchical clustering (UHC). The UHC results were employed to train machine learning models. Kaplan–Meier and Cox regression survival analyses were performed to assess cell clusters in association with relapse-free and overall survival. Differentially expressed genes by clusters were interrogated with IPA for molecular signatures. UHC analysis identified two distinct immune cell clusters, clusters A (83.2%) and B (16.8%). Memory B cells, plasma cells, CD8 positive T cells, resting memory CD4 T cells, activated NK cells, monocytes, M1 macrophages, and resting mast cells were more abundant in clusters A than B, whereas regulatory T cells and M0 and M2 macrophages were more in clusters B than A. Patients in cluster A had favorable survival. Similar survival associations were also observed in other independent studies. IPA analysis showed that pathogen-induced cytokine storm signaling pathway, phagosome formation, and T cell receptor signaling were related to the cell type clusters. Our finding suggests that different immune cell clusters may indicate distinct immune responses to tumor growth, suggesting their potential for disease management.

A full-term pregnancy is associated with reduced endometrial cancer risk; however, whether the effect of additional pregnancies is independent of age at last pregnancy is unknown. The associations between other pregnancy-related factors and endometrial cancer risk are less clear. We pooled individual participant data from 11 cohort and 19 case-control studies participating in the Epidemiology of Endometrial Cancer Consortium (E2C2) including 16 986 women with endometrial cancer and 39 538 control women. We used one- and two-stage meta-analytic approaches to estimate pooled odds ratios (ORs) for the association between exposures and endometrial cancer risk. Ever having a full-term pregnancy was associated with a 41% reduction in risk of endometrial cancer compared to never having a full-term pregnancy (OR = 0.59, 95% confidence interval [CI] 0.56-0.63). The risk reduction appeared the greatest for the first full-term pregnancy (OR = 0.78, 95% CI 0.72-0.84), with a further ~15% reduction per pregnancy up to eight pregnancies (OR = 0.20, 95% CI 0.14-0.28) that was independent of age at last full-term pregnancy. Incomplete pregnancy was also associated with decreased endometrial cancer risk (7%-9% reduction per pregnancy). Twin births appeared to have the same effect as singleton pregnancies. Our pooled analysis shows that, while the magnitude of the risk reduction is greater for a full-term pregnancy than an incomplete pregnancy, each additional pregnancy is associated with further reduction in endometrial cancer risk, independent of age at last full-term pregnancy. These results suggest that the very high progesterone level in the last trimester of pregnancy is not the sole explanation for the protective effect of pregnancy.

This study aimed to assess the relationship between specific nighttime-daytime sleep patterns and prevalence of different chronic diseases in an elderly population. We conducted a community-based cross-sectional study in 4150 elderly Chinese, with an average age of 74 years. Sleep-related variables (nighttime sleep duration, daytime napping and duration) and chronic disease status, including diabetes, cardiovascular diseases (CVD), dyslipidemia cancer and arthritis were collected for the study. Multivariable logistic regression models were used to analyze the relationship between nighttime-daytime sleep patterns and prevalence of chronic diseases. Overall prevalence of any of chronic diseases was 83.8%. Nighttime-daytime sleep patterns were defined according to nighttime sleep duration and habitual nappers/non-nappers. Taking the nighttime-daytime sleep pattern “short nighttime sleep with daytime napping” as reference, those with “long nighttime sleep without daytime napping” had higher prevalence of diabetes [OR and 95% CI, 1.35 (1.01–1.80)] and lower prevalence of arthritis [OR and 95% CI, 0.46 (0.33–0.63)]. And those with “long nighttime sleep with daytime napping” had higher prevalence of diabetes [OR and 95% CI, 1.36 (1.05–1.78)] while lower prevalence of cancer [OR and 95% CI, 0.48 (0.26–0.85)] and arthritis [OR and 95% CI, 0.67 (0.51–0.86)]. Further, in habitual nappers, subjects were classified according to duration of nighttime sleep and daytime naps. Compared to “short nighttime sleep with long daytime napping”, individuals with “long nighttime sleep with short daytime napping” had significantly positive association with diabetes prevalence [OR and 95% CI, 1.73 (1.15–2.68)] while border-significantly and significantly negative association with cancer [OR and 95% CI, 0.49 (0.23–1.07)] and arthritis [OR and 95% CI, 0.64 (0.44–0.94)], respectively. Elderly individuals with chronic diseases had different nighttime-daytime sleep patterns, and understanding these relationships may help to guide the management of chronic diseases.

In 2020, 146,063 deaths due to pancreatic cancer are estimated to occur in Europe and the United States combined. To identify common susceptibility alleles, we performed the largest pancreatic cancer GWAS to date, including 9040 patients and 12,496 controls of European ancestry from the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4). Here, we find significant evidence of a novel association at rs78417682 (7p12/ TNS3 , P = 4.35 × 10 −8 ). Replication of 10 promising signals in up to 2737 patients and 4752 controls from the PANcreatic Disease ReseArch (PANDoRA) consortium yields new genome-wide significant loci: rs13303010 at 1p36.33 ( NOC2L , P = 8.36 × 10 −14 ), rs2941471 at 8q21.11 ( HNF4G , P = 6.60 × 10 −10 ), rs4795218 at 17q12 ( HNF1B , P = 1.32 × 10 −8 ), and rs1517037 at 18q21.32 ( GRP , P = 3.28 × 10 −8 ). rs78417682 is not statistically significantly associated with pancreatic cancer in PANDoRA. Expression quantitative trait locus analysis in three independent pancreatic data sets provides molecular support of NOC2L as a pancreatic cancer susceptibility gene.

Prolonged estrogen exposure is believed to be the major cause of endometrial cancer. As possible markers of estrogen exposure, various menstrual and reproductive features, e.g., ages at menarche and menopause, are found to be associated with endometrial cancer risk. In order to assess their combined effects on endometrial cancer, we created the total number of menstrual cycles (TNMC) that a woman experienced during her life or up to the time of study and two genetic risk scores, GRS1 for age at menarche and GRS2 for age at menopause. Comparing 482 endometrial cancer patients with 571 population controls, we found TNMC was associated with endometrial cancer risk and that the association remained statistically significant after adjustment for obesity and other potential confounders. Risk increased by about 2.5% for every additional 10 menstrual-cycles. The study also showed that high GRS1 was associated with increased risk. This relationship, however, was attenuated after adjustment for obesity. Our study further indicated women with high TNMC and GRS1 had twice the risk of endometrial cancer compared to those low in both indices. Our results provided additional support to the involvement of estrogen exposure in endometrial cancer risk with regard to genetic background and lifestyle features.

Objectives While pancreatic cancer (PC) most often affects older adults, to date, there has been no comprehensive assessment of risk factors among PC patients younger than 60 years. Methods We defined early-onset PC (EOPC) and very-early-onset PC (VEOPC) as diagnosis of PC in patients younger than 60 and 45 years, respectively. We pooled data from 8 case-control studies, including 1954 patients with EOPC and 3278 age- and sex-matched control subjects. Logistic regression analysis was performed to identify associations with EOPC and VEOPC. Results Family history of PC, diabetes mellitus, smoking, obesity, and pancreatitis were associated with EOPC. Alcohol use equal to or greater than 26 g daily also was associated with increased risk of EOPC (odds ratio, 1.49; 95% confidence interval, 1.21–1.84), and there appeared to be a dose- and age-dependent effect of alcohol on risk. The point estimate for risk of VEOPC was an odds ratio of 2.18 (95% confidence interval, 1.17–4.09). Conclusions The established risk factors for PC, including smoking, diabetes, family history of PC, and obesity, also apply to EOPC. Alcohol intake appeared to have an age-dependent effect; the strongest association was with VEOPC.

Endometrial cancer (EC), a neoplasm of the uterine epithelial lining, is the most common gynecological malignancy in developed countries and the fourth most common cancer among US women. Women with a family history of EC have an increased risk for the disease, suggesting that inherited genetic factors play a role. We conducted a two-stage genome-wide association study of Type I EC. Stage 1 included 5,472 women (2,695 cases and 2,777 controls) of European ancestry from seven studies. We selected independent single-nucleotide polymorphisms (SNPs) that displayed the most significant associations with EC in Stage 1 for replication among 17,948 women (4,382 cases and 13,566 controls) in a multiethnic population (African America, Asian, Latina, Hawaiian and European ancestry), from nine studies. Although no novel variants reached genome-wide significance, we replicated previously identified associations with genetic markers near the HNF1B locus. Our findings suggest that larger studies with specific tumor classification are necessary to identify novel genetic polymorphisms associated with EC susceptibility.