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Additional file 1: Table S1. Characteristics of the study populations. Table S2. Replication of the SNPs reported as associated with pancreatic cancer risk in European population and published in GWAS Catalog. Table S3. Validated variants (at the nominal p-value), in PanScan and PanC4 populations, among the top 20 SNPs identified in the PanGenEU GWAS study. Figure S1. Functional in-silico analysis strategy followed to identify novel genomic regions previously prioritized using the 1D, 2D and 3D approaches. Figure S2. GWAS Manhattan plot for the PanGenEU study. The x-axis is the genomic position of each variant and the y-axis is the −log10 p-value obtained in the 1D analysis. Figure S3. Q-Q plots for pancreatic cancer risk of the association results using the PanGenEU case-control study (S2a) and PanGenEU&EPICURO study populations (S2b). Figure S4. Scatterplot of the local Moran’s index (LMI) obtained in the 2D approach and the –log10 p-value obtained in the GWAS analysis (1D approach). Figure S5. Results of the benchmarking test showing that the median rank position of the LMI values for the 22 pancreatic cancer signals from the GWAS Catalog is significantly higher than 10,000 randomly selected sets of the same size. Figure S6. Minor allele frequency (MAF) distributions for the top 97 SNPs identified by LMI (in pink) and by GWAS (in blue). Figure S7. LMI Manhattan plot for the PanGenEU study. The x-axis is the genomic position of each variant and the y-axis is the LMI value obtained in the 2D analysis. Figure S8. Q-Q plots show significant enrichment of SNPs with low p-values in the variants prioritized in the 2D-approach (S8a), and in the credible sets derived from them (S8b). Figure S9. Complementary NETWORK (in blue our input KEGG pathways; in green, the complementary pathways interconnected with them) obtained with Pathway-connector webtool.

The role of PD-L1 as a prognostic and predictive biomarker is an area of great interest. However, there is a lack of consensus on how to deliver PD-L1 as a clinical biomarker. At the heart of this conundrum is the subjective scoring of PD-L1 IHC in most studies to date. Current standard scoring systems involve separation of epithelial and inflammatory cells and find clinical significance in different percentages of expression, e.g., above or below 1%. Clearly, an objective, reproducible and accurate approach to PD-L1 scoring would bring a degree of necessary consistency to this landscape. Using a systematic comparison of technologies and the application of QuPath, a digital pathology platform, we show that high PD-L1 expression is associated with improved clinical outcome in Triple Negative breast cancer in the context of standard of care (SoC) chemotherapy, consistent with previous findings. In addition, we demonstrate for the first time that high PD-L1 expression is also associated with better outcome in ER- disease as a whole including HER2+ breast cancer. We demonstrate the influence of antibody choice on quantification and clinical impact with the Ventana antibody (SP142) providing the most robust assay in our hands. Through sampling different regions of the tumour, we show that tumour rich regions display the greatest range of PD-L1 expression and this has the most clinical significance compared to stroma and lymphoid rich areas. Furthermore, we observe that both inflammatory and epithelial PD-L1 expression are associated with improved survival in the context of chemotherapy. Moreover, as seen with PD-L1 inhibitor studies, a low threshold of PD-L1 expression stratifies patient outcome. This emphasises the importance of using digital pathology and precise biomarker quantitation to achieve accurate and reproducible scores that can discriminate low PD-L1 expression.

Background: Despite smoking being a well-established risk factor for pancreatic cancer, there is a need to further characterize pancreatic cancer risk according to lifespan smoking patterns and other smoking features, such as tobacco type. Our aim was to deeply investigate them within a large European case–control study. Methods: Tobacco smoking habits and other relevant information were obtained from 2,009 cases and 1,532 controls recruited in the PanGenEU study using standardized tools. Multivariate logistic regression analysis was performed to evaluate pancreatic cancer risk by smoking characteristics and interactions with other pancreatic cancer risk factors. Fractional polynomials and restricted cubic splines were used to test for nonlinearity of the dose–response relationships and to analyze their shape. Results: Relative to never-smokers, current smokers [OR = 1.72; 95% confidence interval (95% CI), 1.39–2.12], those inhaling into the throat (OR = 1.48; 95% CI, 1.11–1.99) or chest (OR = 1.33; 95% CI, 1.12–1.58), and those using nonfiltered cigarettes (OR = 1.69; 95% CI, 1.10–2.61), were all at an increased pancreatic cancer risk. Pancreatic cancer risk was highest in current black tobacco smokers (OR = 2.09; 95% CI, 1.31–3.41), followed by blond tobacco smokers (OR = 1.43; 95% CI, 1.01–2.04). Childhood exposure to tobacco smoke relative to parental smoking was also associated with increased pancreatic cancer risk (OR = 1.24; 95% CI, 1.03–1.49). Dose–response relationships for smoking duration, intensity, cumulative dose, and smoking cessation were nonlinear and showed different shapes by tobacco type. Effect modification by family history of pancreatic cancer and diabetes was likely. Conclusions: This study reveals differences in pancreatic cancer risk by tobacco type and other habit characteristics, as well as nonlinear risk associations. Impact: This characterization of smoking-related pancreatic cancer risk profiles may help in defining pancreatic cancer high-risk populations.

Excessive lower oesophageal sphincter relaxation increases gastro-oesophageal acid reflux, an oesophageal adenocarcinoma risk factor. Medications that relax this sphincter (benzodiazepines, calcium channel blockers, nitrates, β2 agonists and xanthines) could promote cancer. These medications were investigated in two independent datasets. In the Scottish Primary Care Clinical Informatics Unit (PCCIU) database, a nested case-control study of oesophageal cancer was performed using GP prescription records. Conditional logistic regression was used to calculate odds ratios (OR) and 95% confidence intervals (CIs) for medication use and oesophageal cancer. In UK Biobank, a cohort study was conducted using self-reported medication use. Cox regression was used to calculate hazard ratios (HRs) and 95% CIs for medication use and oesophageal cancer, and by tumour subtype. Overall, 1,979 oesophageal cancer patients were matched to 9,543 controls in PCCIU, and 355 of 475,768 participants developed oesophageal cancer in UK Biobank. None of the medications investigated were significantly associated with oesophageal cancer risk apart from β2 agonists, which were associated with increased oesophageal cancer risk in PCCIU (adjusted OR 1.38, 95% CI 1.12, 1.70) but not in UK Biobank (adjusted HR 1.21, 95% CI 0.70, 2.08). Medications that relax the lower oesophageal sphincter were not associated with oesophageal cancer, apart from β2 agonists. This increased cancer risk in β2 agonist users merits further investigation.

BACKGROUND: Preclinical studies have demonstrated that propranolol inhibits several pathways involved in breast cancer progression and metastasis. We investigated whether breast cancer patients who used propranolol, or other non-selective beta-blockers, had reduced breast cancer-specific or all-cause mortality in eight European cohorts.METHODS: Incident breast cancer patients were identified from eight cancer registries and compiled through the European Cancer Pharmacoepidemiology Network. Propranolol and non-selective beta-blocker use was ascertained for each patient. Breast cancer-specific and all-cause mortality were available for five and eight cohorts, respectively. Cox regression models were used to calculate hazard ratios (HR) and 95% confidence intervals (CIs) for cancer-specific and all-cause mortality by propranolol and non-selective beta-blocker use. HRs were pooled across cohorts using meta-analysis techniques. Dose-response analyses by number of prescriptions were also performed. Analyses were repeated investigating propranolol use before cancer diagnosis.RESULTS: The combined study population included 55,252 and 133,251 breast cancer patients in the analysis of breast cancer-specific and all-cause mortality respectively. Overall, there was no association between propranolol use after diagnosis of breast cancer and breast cancer-specific or all-cause mortality (fully adjusted HR = 0.94, 95% CI, 0.77, 1.16 and HR = 1.09, 95% CI, 0.93, 1.28, respectively). There was little evidence of a dose-response relationship. There was also no association between propranolol use before breast cancer diagnosis and breast cancer-specific or all-cause mortality (fully adjusted HR = 1.03, 95% CI, 0.86, 1.22 and HR = 1.02, 95% CI, 0.94, 1.10, respectively). Similar null associations were observed for non-selective beta-blockers.CONCLUSIONS: In this large pooled analysis of breast cancer patients, use of propranolol or non-selective beta-blockers was not associated with improved survival.

Assessment of Human papillomavirus (HPV) prevalence and genotype distribution is important for monitoring the impact of prophylactic HPV vaccination. This study aimed to demonstrate the HPV genotypes predominating in pre-malignant and cervical cancers in Northern Ireland (NI) before the vaccination campaign has effect. Formalin fixed paraffin embedded tissue blocks from 2,303 women aged 16-93 years throughout NI were collated between April 2011 and February 2013. HPV DNA was amplified by PCR and HPV genotyping undertaken using the Roche® linear array detection kit. In total, 1,241 out of 1,830 eligible samples (68.0%) tested positive for HPV, with the majority of these [1,181/1,830 (64.5%)] having high-risk (HR) HPV infection; 37.4% were positive for HPV-16 (n=684) and 5.1% for HPV-18 (n=93). HPV type-specific prevalence was 48.1%, 65.9%, 81.3%, 92.2%, and 64.3% among cervical intraepithelial neoplasias (CIN) Grades I-III, squamous cell carcinomas (SCC) and adenocarcinoma (AC) cases, respectively. Most SCC cases (81.3%) had only one HPV genotype detected and almost a third (32.0%) of all cervical pathologies were HPV negative including 51.9% of CIN I (n=283), 34.1% CIN II (n=145), 18.7% of CIN III (n=146), 7.8% of SCC (n=5), and 35.7% of AC (n=5) cases. This study provides important baseline data for monitoring the effect of HPV vaccination in NI and for comparison with other UK regions. The coverage of other HR-HPV genotypes apart from 16 and 18, including HPV-45, 31, 39, and 52, and the potential for cross protection, should be considered when considering future polyvalent vaccines.