Cholangiocarcinoma (CCA) represents a heterogenous set of malignancies arising from the biliary tract. Classification of CCA subdivides tumours into intrahepatic (iCCA) and extrahepatic (eCCA), with eCCA further categorised as perihilar (pCCA) and distal (dCCA) lesions. Tumour subtypes show distinct epidemiological, genetic and clinical characteristics. Global incidence and mortality are rising, with the highest rates seen in Asian populations compared to the West. There has been a divergence in recent mortality trends observed between CCA subtypes, with rising rates of iCCA seen compared with eCCA. There are several drivers for these differing trends, including specific risk factors, misclassification of CCA subtypes and variation in diagnosis and surveillance. Risk factors for CCA can be divided into hepatobiliary, extra-hepatic and environmental, with hepatobiliary diseases conferring the largest risk. Surgery represents the only curative treatment for CCA, but can only be offered to early-stage candidates who are otherwise fit; the majority of patients are therefore treated with chemotherapy and, recently, immunotherapy. Due to late-stage presentation of disease, prognosis is poor, with 5-year survival <20%.

Smoking is a well-established cause of lung cancer and there is strong evidence that smoking also increases the risk of several other cancers. Alcohol consumption has been inconsistently associated with cancer risk in observational studies. This mendelian randomisation (MR) study sought to investigate associations in support of a causal relationship between smoking and alcohol consumption and 19 site-specific cancers. We used summary-level data for genetic variants associated with smoking initiation (ever smoked regularly) and alcohol consumption, and the corresponding associations with lung, breast, ovarian, and prostate cancer from genome-wide association studies consortia, including participants of European ancestry. We additionally estimated genetic associations with 19 site-specific cancers among 367,643 individuals of European descent in UK Biobank who were 37 to 73 years of age when recruited from 2006 to 2010. Associations were considered statistically significant at a Bonferroni corrected p-value below 0.0013. Genetic predisposition to smoking initiation was associated with statistically significant higher odds of lung cancer in the International Lung Cancer Consortium (odds ratio [OR] 1.80; 95% confidence interval [CI] 1.59–2.03; p = 2.26 × 10⁻²¹) and UK Biobank (OR 2.26; 95% CI 1.92–2.65; p = 1.17 × 10⁻²²). Additionally, genetic predisposition to smoking was associated with statistically significant higher odds of cancer of the oesophagus (OR 1.83; 95% CI 1.34–2.49; p = 1.31 × 10⁻⁴), cervix (OR 1.55; 95% CI 1.27–1.88; p = 1.24 × 10⁻⁵), and bladder (OR 1.40; 95% CI 1.92–2.65; p = 9.40 × 10⁻⁵) and with statistically nonsignificant higher odds of head and neck (OR 1.40; 95% CI 1.13–1.74; p = 0.002) and stomach cancer (OR 1.46; 95% CI 1.05–2.03; p = 0.024). In contrast, there was an inverse association between genetic predisposition to smoking and prostate cancer in the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome consortium (OR 0.90; 95% CI 0.83–0.98; p = 0.011) and in UK Biobank (OR 0.90; 95% CI 0.80–1.02; p = 0.104), but the associations did not reach statistical significance. We found no statistically significant association between genetically predicted alcohol consumption and overall cancer (n = 75,037 cases; OR 0.95; 95% CI 0.84–1.07; p = 0.376). Genetically predicted alcohol consumption was statistically significantly associated with lung cancer in the International Lung Cancer Consortium (OR 1.94; 95% CI 1.41–2.68; p = 4.68 × 10⁻⁵) but not in UK Biobank (OR 1.12; 95% CI 0.65–1.93; p = 0.686). There was no statistically significant association between alcohol consumption and any other site-specific cancer. The main limitation of this study is that precision was low in some analyses, particularly for analyses of alcohol consumption and site-specific cancers. Our findings support the well-established relationship between smoking and lung cancer and suggest that smoking may also be a risk factor for cancer of the head and neck, oesophagus, stomach, cervix, and bladder. We found no evidence supporting a relationship between alcohol consumption and overall or site-specific cancer risk.

Cholangiocarcinoma (CCA) is a cancer that originates within the bile ducts. Traditionally considered to be a rare neoplasm, increased awareness of CCA alongside advancements in diagnosis and the rising prevalence of certain risk factors have contributed to a global increase in incidence and mortality. CCAs are highly heterogeneous from the clinical, histomorphological and molecular perspectives but commonly share a poor prognosis. These tumours usually develop and progress silently; by the time they are detected, it is often too late for curative surgical intervention. In such cases, current therapeutic approaches offer modest survival improvements and are generally considered palliative. Although well-known risk factors predispose individuals to developing CCA, the majority of cases are considered sporadic, occurring without any identifiable underlying condition. Over the past decade, substantial collaborative efforts have been made to improve our understanding of the aetiopathogenesis of these tumours, aiming to identify novel biomarkers and therapeutic targets to develop more effective treatments. The ultimate goal is to improve patient outcomes and overall well-being. However, there are significant gaps in our understanding of the molecular mechanisms that drive cholangiocarcinogenesis. In this international Consensus Statement, which is endorsed by the European Network for the Study of Cholangiocarcinoma, we provide a critical overview of the latest advancements in the field of CCA. We highlight the key aspects of CCA aetiopathogenesis and clinical management and provide insights into promising new treatments. Finally, we provide a set of consensus recommendations and future research priorities for CCA based on a Delphi panel questionnaire involving international experts.

Background: Evidence for the impact of body size and composition on cancer risk is limited. This mendelian randomisation (MR) study investigates evidence supporting causal relationships of body mass index (BMI), fat mass index (FMI), fat-free mass index (FFMI), and height with cancer risk. Methods and findings: Single nucleotide polymorphisms (SNPs) were used as instrumental variables for BMI (312 SNPs), FMI (577 SNPs), FFMI (577 SNPs), and height (293 SNPs). Associations of the genetic variants with 22 site-specific cancers and overall cancer were estimated in 367,561 individuals from the UK Biobank (UKBB) and with lung, breast, ovarian, uterine, and prostate cancer in large international consortia. In the UKBB, genetically predicted BMI was positively associated with overall cancer (odds ratio [OR] per 1 kg/m² increase 1.01, 95% confidence interval [CI] 1.00–1.02; p = 0.043); several digestive system cancers: stomach (OR 1.13, 95% CI 1.06–1.21; p < 0.001), esophagus (OR 1.10, 95% CI 1.03, 1.17; p = 0.003), liver (OR 1.13, 95% CI 1.03–1.25; p = 0.012), and pancreas (OR 1.06, 95% CI 1.01–1.12; p = 0.016); and lung cancer (OR 1.08, 95% CI 1.04–1.12; p < 0.001). For sex-specific cancers, genetically predicted elevated BMI was associated with an increased risk of uterine cancer (OR 1.10, 95% CI 1.05–1.15; p < 0.001) and with a lower risk of prostate cancer (OR 0.97, 95% CI 0.94–0.99; p = 0.009). When dividing cancers into digestive system versus non-digestive system, genetically predicted BMI was positively associated with digestive system cancers (OR 1.04, 95% CI 1.02–1.06; p < 0.001) but not with non-digestive system cancers (OR 1.01, 95% CI 0.99–1.02; p = 0.369). Genetically predicted FMI was positively associated with liver, pancreatic, and lung cancer and inversely associated with melanoma and prostate cancer. Genetically predicted FFMI was positively associated with non-Hodgkin lymphoma and melanoma. Genetically predicted height was associated with increased risk of overall cancer (OR per 1 standard deviation increase 1.09; 95% CI 1.05–1.12; p < 0.001) and multiple site-specific cancers. Similar results were observed in analyses using the weighted median and MR–Egger methods. Results based on consortium data confirmed the positive associations between BMI and lung and uterine cancer risk as well as the inverse association between BMI and prostate cancer, and, additionally, showed an inverse association between genetically predicted BMI and breast cancer. The main limitations are the assumption that genetic associations with cancer outcomes are mediated via the proposed risk factors and that estimates for some lower frequency cancer types are subject to low precision. Conclusions: Our results show that the evidence for BMI as a causal risk factor for cancer is mixed. We find that BMI has a consistent causal role in increasing risk of digestive system cancers and a role for sex-specific cancers with inconsistent directions of effect. In contrast, increased height appears to have a consistent risk-increasing effect on overall and site-specific cancers.

Atezolizumab plus bevacizumab (A/B) is a first-line therapy for unresectable hepatocellular carcinoma (HCC). Only a small proportion of patients respond to treatment. This study integrated radiomic and clinical data derived from routine pre-treatment imaging to predict outcomes after immunotherapy. A total of 152 patients from two international centres receiving A/B were retrospectively reviewed. Deep learning autosegmentation generated whole liver masks from pre-treatment CTs. Radiomic features combined with clinical variables were used to predict 12-month mortality post A/B. Radiomic and integrated radiomic-clinical models were developed using seven machine learning models in combination with 13 feature selection techniques in the Imperial College London (ICL) cohort. K-means clustering identified high- and low-risk groups and predicted overall survival (OS), progression-free survival (PFS) and response. Model performance was assessed in the independent Assistance Publique-Hôpitaux de Paris (AP-HP) cohort. The integrated radiomic-clinical model outperformed BCLC stage (AUC 0.61, p <0.001) and ALBI grade (AUC 0.48, p <0.001) in the ICL (AUC 0.89, 95% CI 0.75-0.99) and AP-HP (AUC 0.75, 95% CI 0.64-0.85) cohorts. Integrated model-stratified high-risk patients had significantly shorter median OS (ICL: 5.6 months vs. 28.2 months; p <0.001; AP-HP: 5.8 months vs. 15.7 months; p <0.001) and PFS (ICL: 2.4 months vs. 14.6 months; p <0.001; AP-HP: 2.1 months vs. 6.1 months; p = 0.046). Low-risk patients had significantly higher immune checkpoint inhibitor response rates compared to high-risk patients (35.6% vs. 21.4%; p = 0.038). In multivariable analysis, radiomic group was the strongest predictor of OS (hazard ratio 3.22, 95% CI 1.99-5.20; p <0.001) and PFS (hazard ratio 1.82, 95% CI 1.18-2.80; p = 0.010). Radiomic-based models predict survival outcomes and response to immunotherapy in patients with advanced HCC. Deep learning in combination with machine learning can stratify patients and allows for precision treatment strategies. Prognostic markers predicting survival and response to immunotherapy in hepatocellular carcinoma are lacking. This study used deep learning and machine learning to develop and validate an integrated radiomic-clinical model which can predict survival and response to atezolizumab plus bevacizumab from pre-treatment imaging. Radiomic-based machine learning models can risk-stratify patients with advanced HCC receiving atezolizumab plus bevacizumab.

Context The causal role of endogenous estradiol in cancers other than breast and endometrial cancer remains unclear. Objective This Mendelian randomization study assessed the causal associations of endogenous 17β-estradiol (E2), the most potent estrogen, with cancer risk in women. Methods As primary genetic instrument, we used a genetic variant in the CYP19A1 gene that is strongly associated with serum E2 levels. Summary statistics genetic data for the association of the E2 variant with breast, endometrial, and ovarian cancer were obtained from large-scale consortia. We additionally estimated the associations of the E2 variant with any and 20 site-specific cancers in 198 825 women of European descent in UK Biobank. Odds ratios (OR) of cancer per 0.01 unit increase in log-transformed serum E2 levels in pmol/L were estimated using the Wald ratio. Results Genetic predisposition to higher serum E2 levels was associated with increased risk of estrogen receptor (ER)-positive breast cancer (OR 1.02; 95% CI, 1.01-1.03; P = 2.5 × 10⁻³), endometrial cancer overall (OR 1.09; 95% CI, 1.06-1.11; P = 7.3 × 10⁻¹³), and endometrial cancer of the endometrioid histology subtype (OR 1.10; 95% CI, 1.07-1.13; P = 2.1 × 10⁻¹¹). There were suggestive associations with breast cancer overall (OR 1.01; 95% CI, 1.00-1.02; P = 0.02), ovarian cancer of the endometrioid subtype (OR 1.05; 95% CI, 1.01-1.10; P = 0.02), and stomach cancer (OR 1.12; 95% CI, 1.00-1.26; P = 0.05), but no significant association with other cancers. Conclusion This study supports a role of E2 in the development of ER-positive breast cancer and endometrioid endometrial cancer but found no strong association with other cancers in women.