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PURPOSE To investigate whether postdiagnosis smoking cessation may affect the risk of death and disease progression in patients with renal cell carcinoma (RCC) who smoked at the time of diagnosis. METHODS Two hundred twelve patients with primary RCC were recruited between 2007 and 2016 from the Urological Department in N.N. Blokhin National Medical Research Center of Oncology, Moscow, Russia. Upon enrollment, a structured questionnaire was completed, and the patients were followed annually through 2020 to repeatedly assess their smoking status and disease progression. Survival probabilities and hazards for all-cause and cancer-specific mortality and disease progression were investigated using extended the Kaplan-Meier method, time-dependent Cox proportional hazards regression, and Fine-Gray competing-risk models. RESULTS Patients were followed for a median of 8.2 years. During this time, 110 cases of disease progression, 100 total deaths, and 77 cancer-specific deaths were recorded. Eighty-four patients (40%) quit smoking after diagnosis. The total person-years at risk for this analysis were 748.2 for continuing smoking and 611.2 for quitting smoking periods. At 5 years of follow-up, both overall survival (85% v 61%) and progression-free survival (80% v 57%) rates were higher during the quitting than continuing smoking periods (both P < .001). In the multivariable time-dependent models, quitting smoking was associated with lower risk of all-cause mortality (hazard ratio [HR], 0.51; 95% CI, 0.31 to 0.85), disease progression (HR, 0.45; 95% CI, 0.29 to 0.71), and cancer-specific mortality (HR, 0.54; 95% CI, 0.31 to 0.93). The beneficial effect of quitting smoking was evident across all subgroups, including light smokers versus moderate-heavy smokers and those with early-stage versus late-stage tumors. CONCLUSION Quitting smoking after RCC diagnosis may significantly improve survival and reduce the risk of disease progression and cancer mortality among patients who smoke.

Background Germline genetic variation contributes to lung cancer (LC) susceptibility. Previous genome-wide association studies (GWAS) have implicated susceptibility loci involved in smoking behaviors and DNA repair genes, but further work is required to identify susceptibility variants. Methods To identify LC susceptibility loci, a family history-based genome-wide association by proxy (GWAx) of LC (48 843 European proxy LC patients, 195 387 controls) was combined with a previous LC GWAS (29 266 patients, 56 450 controls) by meta-analysis. Colocalization was used to explore candidate genes and overlap with existing traits at discovered susceptibility loci. Polygenic risk scores (PRS) were tested within an independent validation cohort (1 666 LC patients vs 6 664 controls) using variants selected from the LC susceptibility loci and a novel selection approach using published GWAS summary statistics. Finally, the effects of the LC PRS on somatic mutational burden were explored in patients whose tumor resections have been profiled by exome (n = 685) and genome sequencing (n = 61). Statistical tests were 2-sided. Results The GWAx–GWAS meta-analysis identified 8 novel LC loci. Colocalization implicated DNA repair genes (CHEK1), metabolic genes (CYP1A1), and smoking propensity genes (CHRNA4 and CHRNB2). PRS analysis demonstrated that these variants, as well as subgenome-wide significant variants related to expression quantitative trait loci and/or smoking propensity, assisted in LC genetic risk prediction (odds ratio = 1.37, 95% confidence interval = 1.29 to 1.45; P Conclusions This study has expanded the number of LC susceptibility loci and provided insights into the molecular mechanisms by which these susceptibility variants contribute to LC development.

L.K. is a fellow in the Canadian Institutes of Health Research (CIHR) Strategic Training in Advanced Genetic Epidemiology (STAGE) programme and is supported by the CIHR Doctoral Research Award from the Frederick Banting and Charles Best Canada Graduate Scholarships (GSD-137441). Transdisciplinary Research for Cancer in Lung (TRICL) of the International Lung Cancer Consortium (ILCCO) was supported by the National Institutes of Health (U19-CA148127, CA148127S1). Genotyping for the TRICL-ILCCO OncoArray was supported by in-kind genotyping at Centre for Inherited Disease Research (CIDR) (26820120008i-0–6800068-1). Genotyping for the Head and Neck Cancer OncoArray performed at CIDR was funded by the US National Institute of Dental and Craniofacial Research (NIDCR) grant 1X01HG007780–0. CAPUA study was supported by FIS-FEDER/Spain grant numbers FIS-01/310, FIS-PI03–0365 and FIS-07-BI060604, FICYT/Asturias grant numbers FICYT PB02–67 and FICYT IB09–133, and the University Institute of Oncology (IUOPA), of the University of Oviedo and the Ciber de Epidemiologia y Salud Publica. CIBERESP, SPAIN. The work performed in the CARET study was supported by the National Institute of Health (NIH)/National Cancer Institute (NCI): UM1 CA167462 (PI: Goodman), National Institute of Health UO1-CA6367307 (PIs Omen, Goodman); National Institute of Health R01 CA111703 (PI Chen), National Institute of Health 5R01 CA151989 (PI Doherty). The Liverpool Lung Project is supported by the Roy Castle Lung Cancer Foundation. The Harvard Lung Cancer Study was supported by the NIH (National Cancer Institute) grants CA092824, CA090578 and CA074386. The Multiethnic Cohort Study was partially supported by NIH Grants CA164973, CA033619, CA63464 and CA148127. The work performed in MSH-PMH study was supported by the Canadian Cancer Society Research Institute (020214), Ontario Institute of Cancer and Cancer Care Ontario Chair Award to R.J.H. and G.L. and the Alan Brown Chair and Lusi Wong Programs at the Princess Margaret Hospital Foundation. The Norway study was supported by Norwegian Cancer Society, Norwegian Research Council. The work in TLC study has been supported in part the James & Esther King Biomedical Research Program (09KN-15), National Institutes of Health Specialized Programs of Research Excellence (SPORE) Grant (P50 CA119997) and by a Cancer Center Support Grant (CCSG) at the H. Lee Moffitt Cancer Center and Research Institute, an NCI designated Comprehensive Cancer Center (grant number P30-CA76292). The dataset(s) used for the analyses described were obtained from Vanderbilt University Medical Center’s BioVU, which is supported by institutional funding and by the Vanderbilt CTSA grant UL1 TR000445 from NCATS/NIH. Dr Melinda Aldrich is supported by the by NIH/National Cancer Institute 5K07CA172294. The Copenhagen General Population Study (CGPS) was supported by the Chief Physician Johan Boserup and Lise Boserup Fund, the Danish Medical Research Council and Herlev Hospital. The NELCS study: Grant Number P20RR018787 from the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH). Kentucky Lung Cancer Research Initiative (KLCRI) was supported by the Department of Defense (Congressionally Directed Medical Research Program, U.S. Army Medical Research and Materiel Command Program) under award number: 10153006 (W81XWH-11–1-0781). Views and opinions of, and endorsements by the author(s) do not reflect those of the US Army or the Department of Defense. This research was also supported by unrestricted infrastructure funds from the UK Center for Clinical and Translational Science, NIH grant UL1TR000117 and Markey Cancer Center NCI Cancer Center Support Grant (P30 CA177558) Shared Resource Facilities: Cancer Research Informatics, Biospecimen and Tissue Procurement, and Biostatistics and Bioinformatics. The research undertaken by M.D.T., L.V.W. and M.S.A. was partly funded by the National Institute for Health Research (NIHR). The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. M.D.T. holds a Medical Research Council Senior Clinical Fellowship (G0902313). The Tampa study was funded by Public Health Service grants P01-CA68384 and R01-DE13158 from the National Institutes of Health. The University of Pittsburgh head and neck cancer case–control study is supported by US National Institutes of Health grants P50 CA097190 and P30 CA047904. The Carolina Head and Neck Cancer Study (CHANCE) was supported by the National Cancer Institute (R01CA90731). The Head and Neck Genome Project (GENCAPO) was supported by the Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP; grants 04/12054–9 and 10/51168–0). The authors thank all the members of the GENCAPO team. This publication presents data from the Head and Neck 5000 study. The study was a component of independent research funded by the National Institute for Health Research (NIHR) under its Programme Grants for Applied Research scheme (RP-PG-0707–10034). The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. Human papillomavirus (HPV) serology was supported by a Cancer Research UK Programme Grant, the Integrative Cancer Epidemiology Programme (grant number: C18281/A19169). The Alcohol-Related Cancers and Genetic Susceptibility Study in Europe (ARCAGE) was funded by the European Commission’s fifth framework programme (QLK1– 2001-00182), the Italian Association for Cancer Research, Compagnia di San Paolo/FIRMS, Region Piemonte and Padova University (CPDA057222). The Rome Study was supported by the Associazione Italiana per la Ricerca sul Cancro (AIRC) awards IG 2011 10491 and IG 2013 14220 to S.B. and by Fondazione Veronesi to S.B. The IARC Latin American study was funded by the European Commission INCO-DC programme (IC18-CT97–0222), with additional funding from Fondo para la Investigacion Cientifica y Tecnologica (Argentina) and the Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (01/01768–2). The IARC Central Europe study was supported by the European Commission’s INCO-COPERNICUS Program (IC15-CT98–0332), US NIH/National Cancer Institute grant CA92039 and World Cancer Research Foundation grant WCRF 99A28. The IARC Oral Cancer Multicenter study was funded by grant S06 96 202489 05F02 from Europe against Cancer; grants FIS 97/0024, FIS 97/0662 and BAE 01/5013 from Fondo de Investigaciones Sanitarias, Spain; the UICC Yamagiwa-Yoshida Memorial International Cancer Study; the National Cancer Institute of Canada; Associazione Italiana per la Ricerca sul Cancro; and the Pan-American Health Organization. Coordination of the EPIC study is financially supported by the European Commission (DG SANCO) and the International Agency for Research on Cancer.

Smoking not only increases the risk of the development of malignant tumors (MT), but affects the disease prognosis, mortality and survivability of cancer patients. The link between the smoking of cancer patients and increased risk of death by all diseases and oncological causes has been established. Mortality increases with the growth of the smoking intensity, i.e. the number of cigarettes, smoked per day. Smoking is associated with the worst general and oncological survivability. The statistically trend-line between the smoking intensity and survivability was observed: each additional unit of cigarette consumption (pack/year) leads to the Overall Survival Reduction by 1% (p = 0.002). The link between smoking and the risk of developing second primary tumors has been confirmed. Smoking increases the likelihood of side effects of the antitumor therapy both drug therapy and radiation therapy and reduces the treatment efficacy. The smoking cessation leads to a significant improvement in the prognosis of a cancer patient. Scientific data on the negative effect of smoking on the prognosis of cancer patients have a major clinical importance. The treatment program for cancer patients should include science-based methods for the smoking cessation. The latter is fundamentally important, taking into account that the smoking frequency among cancer patients is much higher than in the population.

Background Lung cancer is the leading cause of cancer death worldwide, and about one half of patients with lung cancer are active smokers at diagnosis. Objective To determine whether quitting smoking after diagnosis of lung cancer affects the risk for disease progression and mortality. Design Prospective study of patients with non-small cell lung cancer (NSCLC) who were recruited between 2007 and 2016 and followed annually through 2020. Setting N.N. Blokhin National Medical Research Center of Oncology and City Clinical Oncological Hospital No. 1, Moscow, Russia. Patients 517 current smokers who were diagnosed with early-stage (IA-IIIA) NSCLC. Measurements Probabilities of overall survival, progression-free survival, and lung cancer-specific mortality and hazard ratios (HRs) for all-cause and cancer-specific mortality. Results During an average of 7 years of follow-up, 327 (63.2%) deaths, 273 (52.8%) cancer-specific deaths, and 172 (33.7%) cases of tumor progression (local recurrence or metastasis) were recorded. The adjusted median overall survival time was 21.6 months higher among patients who had quit smoking than those who continued smoking (6.6 vs. 4.8 years, respectively; P = 0.001). Higher 5-year overall survival (60.6% vs. 48.6%; P = 0.001) and progression-free survival (54.4% vs. 43.8%; P = 0.004) were observed among patients who quit than those who continued smoking. After adjustments, smoking cessation remained associated with decreased risk for all-cause mortality (HR, 0.67 [95% CI, 0.53 to 0.85]), cancer-specific mortality (HR, 0.75 [CI, 0.58 to 0.98]), and disease progression (HR, 0.70 [CI, 0.56 to 0.89]). Similar effects were observed among mild to moderate and heavy smokers and patients with earlier and later cancer stages. Limitation Exposure measurements were based on self-reported questionnaires. Conclusion Smoking cessation after diagnosis materially improved overall and progression-free survival among current smokers with early-stage lung cancer. Primary funding source International Agency for Research on Cancer.

Germline genetic variants are involved in lung cancer (LC) susceptibility. Previous genome-wide association studies (GWAS) have implicated genes involved in smoking propensity and DNA repair but further work is required to identify additional LC susceptibility variants and to investigate LC disease development dynamics.We have undertaken a family history-based genome-wide association (GWAx) study of LC, analysing 48,843 European cases with a parent/sibling with LC compared to 195,387 controls from the UK Biobank. This was meta-analysed with previously described LC GWAS results. We performed Polygenic Risk Scores (PRS) analyses and further evaluated the PRS influence on the somatic environment in exome (N=736) and genome sequencing (N=61) profiled cohorts.Eight novel loci were identified including DNA repair genes (CHEK1, MDM4), metabolic genes (CYP1A1) and variants that were also associated with smoking propensity, such as both subunits of the neuronal α4β2 nicotinic acetylcholine receptor (CHRNA4 and CHRNB2). PRS analysis demonstrated that variants related to eQTLs and/or smoking propensity are enriched for susceptibility variants, including variants below genome-wide significant threshold. PRS of LC variants related to smoking propensity were associated with somatic mutation burden in two case cohorts, with individuals with higher polygenic genetic risk having increased numbers of somatic mutations in their lung tumours.This study has expanded the number of susceptibility loci linked with LC and provided insights into the molecular mechanisms by which these susceptibility variants contribute to the development of lung cancer.

Kidney cancer consists of renal cell cancer (RCC) accounting for over 90 % of all kidney carcinomas and the transitional cell cancer. Clear cell cancer is a predominant type (80–85 %) of RCC. Smoking, overweight, obesity, hypertension, occupational exposures to pesticides, specifically to trichloroethylene are considered causal risk factors for sporadic i.e. non-hereditary RCC. The majority of sporadic RCC have polygenic etiology. They develop as a result of combined effect of large number of low penetrance genetic susceptibility genes (genetic polymorphism). The interplay of exposures to environmental risk factors and genetic susceptibility of exposed individuals is believed to influence the risk of developing sporadic RCC. Inheritance of high penetrance genes is associated with very high risk of the RCC. To these genes belongs, for example, VHL (von Hippel–Lindau). Germline mutations in VHL are causing VHL syndrome and hereditary type of RCC. Risk of RCC in individuals with germ-line mutations is very high however the proportion RCC associated with these events is very low (>5–7 %). Environmental factors virtually do not influence the risk of these cancers.The studies in molecular epidemiology based on candidate gene approach have shown that certain types (variants) of polymorphisms of GST, MTHFR, TYMS, VHL genes are associated with RCC. The genome wide association studies identified over twenty locus with single nucleotide polymorphism affecting the risk of RCC. The risk loci so far identified for RCC account for only about 10 % of the familial risk of RCC. Thus more studies with larger sample size are needed. As more RCC susceptibility alleles are discovered, deciphering the biological basis of risk variants should provide new insights into the biology of RCC that may lead to new approaches to prevention, early detection and therapeutic intervention.

Circulating miRNAs have shown great promises as noninvasive diagnostic and predictive biomarkers in several solid tumors. While the miRNA profiles of renal tumors have been extensively explored, knowledge of their circulating counterparts is limited. Our study aimed to provide a large-scale genome-wide profiling of plasma circulating miRNA in clear-cell renal cell carcinoma (ccRCC). Plasma samples from 94 ccRCC cases and 100 controls were screened for 754 circulating micro-RNAs (miRNA) by TaqMan arrays. Analyses including known risk factors for renal cancer-namely, age, sex, hypertension, obesity, diabetes, tobacco smoking and alcohol consumption-highlighted that circulating miRNA profiles were tightly correlated with the stage of the disease. Advanced tumors, characterized as stage III and IV, were associated with specific miRNA signatures that significantly differ from both controls and earlier stage ccRCC cases. Molecular pathway enrichment analyses of their gene targets showed high similarities with alterations observed in renal tumors. Plasma circulating levels of miR-150 were significantly associated with RCC-specific survival and could marginally improve the predictive accuracy of clinical parameters in our series, including age at diagnosis, sex and conventional staging. In summary, our results suggest that circulating miRNAs may provide insights into renal cell carcinoma progression.

The emergence of Next-Generation Sequencing (NGS) has revolutionized the way of reaching a genome sequence, with the promise of potentially providing a comprehensive characterization of DNA variations. Nevertheless, detecting somatic mutations is still a difficult problem, in particular when trying to identify low abundance mutations such as subclonal mutations, tumour-derived alterations in body fluids or somatic mutations from histological normal tissue. The main challenge is to precisely distinguish between sequencing artefacts and true mutations, particularly when the latter are so rare they reach similar abundance levels as artefacts. Here, we present needlestack, a highly sensitive variant caller, which directly learns from the data the level of systematic sequencing errors to accurately call mutations. Needlestack is based on the idea that the sequencing error rate can be dynamically estimated from analyzing multiple samples together. We show that the sequencing error rate varies across alterations, illustrating the need to precisely estimate it. We evaluate the performance of needlestack for various types of variations, and we show that needlestack is robust among positions and outperforms existing state-of-the-art method for low abundance mutations. Needlestack, along with its source code is freely available on the GitHub plateform: https://github.com/IARCbioinfo/needlestack.

Background: Evidence from observational studies of telomere length (TL) has been conflicting regarding its direction of association with cancer risk. We investigated the causal relevance of TL for lung and head and neck cancers using Mendelian Randomization (MR) and mediation analyses. Methods: We developed a novel genetic instrument for TL in chromosome 5p15.33, using variants identified through deep-sequencing, that were genotyped in 2051 cancer-free subjects. Next, we conducted an MR analysis of lung (16 396 cases, 13 013 controls) and head and neck cancer (4415 cases, 5013 controls) using eight genetic instruments for TL. Lastly, the 5p15.33 instrument and distinct 5p15.33 lung cancer risk loci were evaluated using two-sample mediation analysis, to quantify their direct and indirect, telomere-mediated, effects. Results: The multi-allelic 5p15.33 instrument explained 1.49-2.00% of TL variation in our data (p = 2.6 × 10-9). The MR analysis estimated that a 1000 base-pair increase in TL increases risk of lung cancer [odds ratio (OR) = 1.41, 95% confidence interval (CI): 1.20-1.65] and lung adenocarcinoma (OR = 1.92, 95% CI: 1.51-2.22), but not squamous lung carcinoma (OR = 1.04, 95% CI: 0.83-1.29) or head and neck cancers (OR = 0.90, 95% CI: 0.70-1.05). Mediation analysis of the 5p15.33 instrument indicated an absence of direct effects on lung cancer risk (OR = 1.00, 95% CI: 0.95-1.04). Analysis of distinct 5p15.33 susceptibility variants estimated that TL mediates up to 40% of the observed associations with lung cancer risk. Conclusions: Our findings support a causal role for long telomeres in lung cancer aetiology, particularly for adenocarcinoma, and demonstrate that telomere maintenance partially mediates the lung cancer susceptibility conferred by 5p15.33 loci. © 2018 The Author(s) 2018; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.

BACKGROUND: Relative telomere length in peripheral blood leukocytes has been evaluated as a potential biomarker for renal cell carcinoma (RCC) risk in several studies, with conflicting findings. OBJECTIVE: We performed an analysis of genetic variants associated with leukocyte telomere length to assess the relationship between telomere length and RCC risk using Mendelian randomization, an approach unaffected by biases from temporal variability and reverse causation that might have affected earlier investigations. DESIGN, SETTING, AND PARTICIPANTS: Genotypes from nine telomere length-associated variants for 10 784 cases and 20 406 cancer-free controls from six genome-wide association studies (GWAS) of RCC were aggregated into a weighted genetic risk score (GRS) predictive of leukocyte telomere length. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Odds ratios (ORs) relating the GRS and RCC risk were computed in individual GWAS datasets and combined by meta-analysis. RESULTS AND LIMITATIONS: Longer genetically inferred telomere length was associated with an increased risk of RCC (OR=2.07 per predicted kilobase increase, 95% confidence interval [CI]:=1.70-2.53, p0.5) with GWAS-identified RCC risk variants (rs10936599 and rs9420907) from the telomere length GRS; despite this exclusion, a statistically significant association between the GRS and RCC risk persisted (OR=1.73, 95% CI=1.36-2.21, p

It has come to our attention that authors Lenka Foretova, Ivana Holcatova, Vladimir Janout, Dana Mates, Anush Mukeriya, Stefan Rascu, David Zaridze, Vladimir Bencko, and Cezary Cybulski were not assigned to the correct affiliations. Their correct affiliations are as in the list above. Conflicts of interest: The authors have nothing to disclose.

Background Several obesity-related factors have been associated with renal cell carcinoma (RCC), but it is unclear which individual factors directly influence risk. We addressed this question using genetic markers as proxies for putative risk factors and evaluated their relation to RCC risk in a mendelian randomization (MR) framework. This methodology limits bias due to confounding and is not affected by reverse causation. Methods and findings Genetic markers associated with obesity measures, blood pressure, lipids, type 2 diabetes, insulin, and glucose were initially identified as instrumental variables, and their association with RCC risk was subsequently evaluated in a genome-wide association study (GWAS) of 10,784 RCC patients and 20,406 control participants in a 2-sample MR framework. The effect on RCC risk was estimated by calculating odds ratios (ORSD) for a standard deviation (SD) increment in each risk factor. The MR analysis indicated that higher body mass index increases the risk of RCC (ORSD: 1.56, 95% confidence interval [CI] 1.44–1.70), with comparable results for waist-to-hip ratio (ORSD: 1.63, 95% CI 1.40–1.90) and body fat percentage (ORSD: 1.66, 95% CI 1.44–1.90). This analysis further indicated that higher fasting insulin (ORSD: 1.82, 95% CI 1.30–2.55) and diastolic blood pressure (DBP; ORSD: 1.28, 95% CI 1.11–1.47), but not systolic blood pressure (ORSD: 0.98, 95% CI 0.84–1.14), increase the risk for RCC. No association with RCC risk was seen for lipids, overall type 2 diabetes, or fasting glucose. Conclusions This study provides novel evidence for an etiological role of insulin in RCC, as well as confirmatory evidence that obesity and DBP influence RCC risk., Using mendelian randomization approaches, Paul Brennan and colleagues reveal an association between 12 obesity-related factors, including insulin and the development of renal cell carcinoma., Author summary Why was this study done? Traditional observational studies wherein putative risk factors are measured directly have found several obesity-related factors associated with increased risk of renal cell carcinoma (RCC). Traditional observational studies are subject to confounding and reverse causation and have not been able to disentangle which obesity-related risk factors directly influence RCC risk. This study used an alternative methodology commonly referred to as mendelian randomization (MR). MR circumvents many of the inherent limitations of traditional observational study by use of genetic proxies of putative risk factors when evaluating their associations with disease risk, as they are not subject to reverse causation and are less likely to be confounded by other risk factors. What did the researchers do and find? First, we used large-scale genome-wide association studies (GWAS) to identify genetic variants associated with obesity measures, blood pressure, lipids, type 2 diabetes, insulin, and glucose. Second, these genetic variants were used as proxies for the above-mentioned risk factors and evaluated in relation RCC risk using GWAS data from 10,000 RCC patients and 20,000 control participants. Based on these genetic data, we found that multiple measures of obesity, as well as diastolic blood pressure (DBP) and fasting insulin, are associated with RCC risk. In contrast, we found little evidence for an association with RCC risk for systolic blood pressure (SBP), circulating lipids, overall diabetes, or fasting glucose. What do these findings mean? This study provided robust and confirmatory evidence of an important role of obesity as an important risk factor of RCC. Further confirmatory evidence was found for elevated DBP as a risk factor of RCC, but it is not clear why DBP rather than SBP is important in RCC. The study, to our knowledge, provided novel evidence of an important role of circulating insulin in RCC etiology. This study provided some novel insights into the pathways involved in mediating the risk increase in RCC that is caused by obesity, most notably through insulin and DBP, but further research is needed to fully elucidate the important relationship between obesity and RCC.

CAPUA study was supported by FIS-FEDER/Spain grant numbers FIS-01/310, FIS-PI03-0365, and FIS-07-BI060604, FICYT/Asturias grant numbers FICYT PB02-67 and FICYT IB09-133, and the University Institute of Oncology (IUOPA), of the University of Oviedo and the Ciber de Epidemiología y Salud Pública. CIBERESP, SPAIN (...), Ferreiro-Iglesias, A., Lesseur, C., McKay, J., Hung, R.J., Han, Y., Zong, X., Christiani, D., Johansson, M., Xiao, X., Li, Y., Qian, D.C., Ji, X., Liu, G., Caporaso, N., Scelo, G., Zaridze, D., Mukeriya, A., Kontic, M., Ognjanovic, S., Lissowska, J., Szołkowska, M., Swiatkowska, B., Janout, V., Holcatova, I., Bolca, C., Savic, M., Ognjanovic, M., Bojesen, S.E., Wu, X., Albanes, D., Aldrich, M.C., Tardon, A., Fernandez-Somoano, A., Fernandez-Tardon, G., Le Marchand, L., Rennert, G., Chen, C., Doherty, J., Goodman, G., Bickeböller, H., Wichmann, H.-E., Risch, A., Rosenberger, A., Shen, H., Dai, J., Field, J.K., Davies, M., Woll, P., Teare, M.D., Kiemeney, L.A., van der Heijden, E.H.F.M., Yuan, J.-M., Hong, Y.-C., Haugen, A., Zienolddiny, S., Lam, S., Tsao, M.-S., Johansson, M., Grankvist, K., Schabath, M.B., Andrew, A., Duell, E., Melander, O., Brunnström, H., Lazarus, P., Arnold, S., Slone, S., Byun, J., Kamal, A., Zhu, D., Landi, M.T., Amos, C.I., Brennan, P.

Lung cancer has several genetic associations identified within the major histocompatibility complex (MHC); although the basis for these associations remains elusive. Here, we analyze MHC genetic variation among 26,044 lung cancer patients and 20,836 controls densely genotyped across the MHC, using the Illumina Illumina OncoArray or Illumina 660W SNP microarray. We impute sequence variation in classical HLA genes, fine-map MHC associations for lung cancer risk with major histologies and compare results between ethnicities. Independent and novel associations within HLA genes are identified in Europeans including amino acids in the HLA-B*0801 peptide binding groove and an independent HLA-DQB1*06 loci group. In Asians, associations are driven by two independent HLA allele sets that both increase risk in HLA-DQB1*0401 and HLA-DRB1*0701; the latter better represented by the amino acid Ala-104. These results implicate several HLAtumor peptide interactions as the major MHC factor modulating lung cancer susceptibility. (VLID)2956679

Previous genome-wide association studies (GWAS) have identified six risk loci for renal cell carcinoma (RCC). We conducted a meta-analysis of two new scans of 5,198 cases and 7,331 controls together with four existing scans, totalling 10,784 cases and 20,406 controls of European ancestry. Twenty-four loci were tested in an additional 3,182 cases and 6,301 controls. We confirm the six known RCC risk loci and identify seven new loci at 1p32.3 (rs4381241, P=3.1 × 10−10), 3p22.1 (rs67311347, P=2.5 × 10−8), 3q26.2 (rs10936602, P=8.8 × 10−9), 8p21.3 (rs2241261, P=5.8 × 10−9), 10q24.33-q25.1 (rs11813268, P=3.9 × 10−8), 11q22.3 (rs74911261, P=2.1 × 10−10) and 14q24.2 (rs4903064, P=2.2 × 10−24). Expression quantitative trait analyses suggest plausible candidate genes at these regions that may contribute to RCC susceptibility.

NCI, National Cancer Institute; NIHR, National Institute for Health Research, Carreras-Torres, R., Johansson, M., Haycock, P.C., Wade, K.H., Relton, C.L., Martin, R.M., Smith, G.D., Albanes, D., Aldrich, M.C., Andrew, A., Arnold, S.M., Bickeböller, H., Bojesen, S.E., Brunnström, H., Manjer, J., Brüske, I., Caporaso, N.E., Chen, C., Christiani, D.C., Christian, W.J., Doherty, J.A., Duell, E.J., Field, J.K., Davies, M.P.A., Marcus, M.W., Goodman, G.E., Grankvist, K., Haugen, A., Hong, Y.-C., Kiemeney, L.A., Van Der Heijden, E.H.F.M., Kraft, P., Johansson, M.B., Lam, S., Landi, M.T., Lazarus, P., Le Marchand, L., Liu, G., Melander, O., Park, S.L., Rennert, G., Risch, A., Haura, E.B., Scelo, G., Zaridze, D., Mukeriya, A., Savić, M., Lissowska, J., Swiatkowska, B., Janout, V., Holcatova, I., Mates, D., Schabath, M.B., Shen, H., Tardon, A., Teare, M.D., Woll, P., Tsao, M.-S., Wu, X., Yuan, J.-M., Hung, R.J., Amos, C.I., McKay, J., Brennan, P.

Circulating miRNAs have shown great promises as noninvasive diagnostic and predictive biomarkers in several solid tumors. While the miRNA profiles of renal tumors have been extensively explored, knowledge of their circulating counterparts is limited. Our study aimed to provide a large-scale genome-wide profiling of plasma circulating miRNA in clear-cell renal cell carcinoma (ccRCC). Plasma samples from 94 ccRCC cases and 100 controls were screened for 754 circulating micro-RNAs (miRNA) by TaqMan arrays. Analyses including known risk factors for renal cancer—namely, age, sex, hypertension, obesity, diabetes, tobacco smoking and alcohol consumption—highlighted that circulating miRNA profiles were tightly correlated with the stage of the disease. Advanced tumors, characterized as stage III and IV, were associated with specific miRNA signatures that significantly differ from both controls and earlier stage ccRCC cases. Molecular pathway enrichment analyses of their gene targets showed high similarities with alterations observed in renal tumors. Plasma circulating levels of miR-150 were significantly associated with RCC-specific survival and could marginally improve the predictive accuracy of clinical parameters in our series, including age at diagnosis, sex and conventional staging. In summary, our results suggest that circulating miRNAs may provide insights into renal cell carcinoma progression.