The renal lineage factor PAX8 controls oncogenic signalling in kidney cancer.

Large-scale human genetic data1-3 have shown that cancer mutations display strong tissue-selectivity, but how this selectivity arises remains unclear. Here, using experimental models, functional genomics and analyses of patient samples, we demonstrate that the lineage transcription factor paired box 8 (PAX8) is required for oncogenic signalling by two common genetic alterations that cause clear cell renal cell carcinoma (ccRCC) in humans: the germline variant rs7948643 at 11q13.3 and somatic inactivation of the von Hippel-Lindau tumour suppressor (VHL)4-6. VHL loss, which is observed in about 90% of ccRCCs, can lead to hypoxia-inducible factor 2α (HIF2A) stabilization6,7. We show that HIF2A is preferentially recruited to PAX8-bound transcriptional enhancers, including a pro-tumorigenic cyclin D1 (CCND1) enhancer that is controlled by PAX8 and HIF2A. The ccRCC-protective allele C at rs7948643 inhibits PAX8 binding at this enhancer and downstream activation of CCND1 expression. Co-option of a PAX8-dependent physiological programme that supports the proliferation of normal renal epithelial cells is also required for MYC expression from the ccRCC metastasis-associated amplicons at 8q21.3-q24.3 (ref. 8). These results demonstrate that transcriptional lineage factors are essential for oncogenic signalling and that they mediate tissue-specific cancer risk associated with somatic and inherited genetic variants.

Transcriptome- and proteome-wide association studies identify genes associated with renal cell carcinoma.

We performed a series of integrative analyses including transcriptome-wide association studies (TWASs) and proteome-wide association studies (PWASs) of renal cell carcinoma (RCC) to nominate and prioritize molecular targets for laboratory investigation. On the basis of a genome-wide association study (GWAS) of 29,020 affected individuals and 835,670 control individuals and prediction models trained in transcriptomic reference models, our TWAS across four kidney transcriptomes (GTEx kidney cortex, kidney tubules, TCGA-KIRC [The Cancer Genome Atlas kidney renal clear-cell carcinoma], and TCGA-KIRP [TCGA kidney renal papillary cell carcinoma]) identified 38 gene associations (false-discovery rate <5%) in at least two of four transcriptomic panels and identified 12 genes that were independent of GWAS susceptibility regions. Analyses combining TWAS associations across 48 tissues from GTEx identified associations that were replicable in tumor transcriptomes for 23 additional genes. Analyses by the two major histologic types (clear-cell RCC and papillary RCC) revealed subtype-specific associations, although at least three gene associations were common to both subtypes. PWAS identified 13 associated proteins, all mapping to GWAS-significant loci. TWAS-identified genes were enriched for active enhancer or promoter regions in RCC tumors and hypoxia-inducible factor binding sites in relevant cell lines. Using gene expression correlation, common cancers (breast and prostate) and RCC risk factors (e.g., hypertension and BMI) display genetic contributions shared with RCC. Our work identifies potential molecular targets for RCC susceptibility for downstream functional investigation.

Association of tea and coffee consumption and biliary tract cancer risk: The Biliary Tract Cancers Pooling Project.

BACKGROUND AND AIMS: Tea and coffee are widely consumed beverages worldwide. We evaluated their association with biliary tract cancer (BTC) incidence. APPROACH AND RESULTS: We pooled data from 15 studies in the Biliary Tract Cancers Pooling Project to evaluate associations between tea and coffee consumption and biliary tract cancer development. We categorized participants as nondrinkers (0 cup/day), moderate drinkers (>0 and <3 cups/day), and heavy drinkers (≥3 cups/day). We estimated multivariable HRs and 95% CIs using Cox models. During 29,911,744 person-years of follow-up, 851 gallbladder, 588 intrahepatic bile duct, 753 extrahepatic bile duct, and 458 ampulla of Vater cancer cases were diagnosed. Individuals who drank tea showed a statistically significantly lower incidence rate of gallbladder cancer (GBC) relative to tea nondrinkers (HR=0.77; 95% CI, 0.64-0.91), and intrahepatic bile duct cancer (IHBDC) had an inverse association (HR=0.81; 95% CI, 0.66-1.00). However, no associations were observed for extrahepatic bile duct cancer (EHBDC) or ampulla of Vater cancer (AVC). In contrast, coffee consumption was positively associated with GBC, with a higher incidence rate for individuals consuming more coffee (HR<3 cups/day =1.29; 95% CI, 1.01-1.66; HR≥3 cups/day =1.49; 95% CI, 1.11-1.99, Ptrend=0.01) relative to coffee nondrinkers. However, there was no association between coffee consumption and GBC when restricted to coffee drinkers. There was little evidence of associations between coffee consumption and other biliary tract cancers. CONCLUSIONS: Tea consumption was associated with a lower incidence of GBC and possibly IHBDC. Further research is warranted to replicate the observed positive association between coffee and GBC.

Occupational exposure to benzene and risk of non-Hodgkin lymphoma in an extended follow-up of two population-based prospective cohorts of Chinese men and women.

The carcinogenicity of benzene was reevaluated by the International Agency for Research on Cancer in 2017, with the Working Group reaffirming positive yet inconclusive associations with non-Hodgkin lymphoma (NHL). To extend our previous observation of a significant exposure-response for cumulative occupational benzene exposure and NHL risk among Chinese women in a population-based cohort in Shanghai, we extended follow-up of this cohort and pooled the data with a similarly designed population-based cohort of men in Shanghai. Cumulative exposure estimates were derived for 134,449 participants in the pooled analysis by combining ordinal job-exposure matrix intensity ratings with quantitative benzene measurements from an inspection database of Shanghai factories. Associations between benzene exposure metrics and NHL (n = 363 cases including multiple myeloma [MM]) were assessed using Cox proportional hazard models. Ever occupational exposure to benzene in the pooled population was associated with NHL risk (HR = 1.5, 95% CI = 1.2-2.0), and exposure-response relationships were observed for increasing duration (ptrend = .003) and cumulative exposure (ptrend = .003). Associations with ever exposure, duration, and cumulative exposure were similar for NHL with and without MM in the case definition, including lifetime cumulative exposures in the highest quartile (HR = 1.6, 95% CI = 1.1-2.4 with MM included; HR = 1.7, 95% CI = 1.1-2.7 with MM excluded). An elevated risk of the chronic lymphocytic leukemia subtype was suggested in the pooled analyses (HR for ever vs. never exposure = 2.3, 95% CI = 0.9-5.6). These observations provide additional support for a plausible association between occupational benzene exposure and risk of NHL.

Observational and genetic associations between cardiorespiratory fitness and cancer: a UK Biobank and international consortia study.

BACKGROUND: The association of fitness with cancer risk is not clear. METHODS: We used Cox proportional hazards models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for risk of lung, colorectal, endometrial, breast, and prostate cancer in a subset of UK Biobank participants who completed a submaximal fitness test in 2009-12 (N = 72,572). We also investigated relationships using two-sample Mendelian randomisation (MR), odds ratios (ORs) were estimated using the inverse-variance weighted method. RESULTS: After a median of 11 years of follow-up, 4290 cancers of interest were diagnosed. A 3.5 ml O2⋅min-1⋅kg-1 total-body mass increase in fitness (equivalent to 1 metabolic equivalent of task (MET), approximately 0.5 standard deviation (SD)) was associated with lower risks of endometrial (HR = 0.81, 95% CI: 0.73-0.89), colorectal (0.94, 0.90-0.99), and breast cancer (0.96, 0.92-0.99). In MR analyses, a 0.5 SD increase in genetically predicted O2⋅min-1⋅kg-1 fat-free mass was associated with a lower risk of breast cancer (OR = 0.92, 95% CI: 0.86-0.98). After adjusting for adiposity, both the observational and genetic associations were attenuated. DISCUSSION: Higher fitness levels may reduce risks of endometrial, colorectal, and breast cancer, though relationships with adiposity are complex and may mediate these relationships. Increasing fitness, including via changes in body composition, may be an effective strategy for cancer prevention.

Altered regulation of DPF3, a member of the SWI/SNF complexes, underlies the 14q24 renal cancer susceptibility locus.

Our study investigated the underlying mechanism for the 14q24 renal cell carcinoma (RCC) susceptibility risk locus identified by a genome-wide association study (GWAS). The sentinel single-nucleotide polymorphism (SNP), rs4903064, at 14q24 confers an allele-specific effect on expression of the double PHD fingers 3 (DPF3) of the BAF SWI/SNF complex as assessed by massively parallel reporter assay, confirmatory luciferase assays, and eQTL analyses. Overexpression of DPF3 in renal cell lines increases growth rates and alters chromatin accessibility and gene expression, leading to inhibition of apoptosis and activation of oncogenic pathways. siRNA interference of multiple DPF3-deregulated genes reduces growth. Our results indicate that germline variation in DPF3, a component of the BAF complex, part of the SWI/SNF complexes, can lead to reduced apoptosis and activation of the STAT3 pathway, both critical in RCC carcinogenesis. In addition, we show that altered DPF3 expression in the 14q24 RCC locus could influence the effectiveness of immunotherapy treatment for RCC by regulating tumor cytokine secretion and immune cell activation.

Improve the model of disease subtype heterogeneity by leveraging external summary data.

Researchers are often interested in understanding the disease subtype heterogeneity by testing whether a risk exposure has the same level of effect on different disease subtypes. The polytomous logistic regression (PLR) model provides a flexible tool for such an evaluation. Disease subtype heterogeneity can also be investigated with a case-only study that uses a case-case comparison procedure to directly assess the difference between risk effects on two disease subtypes. Motivated by a large consortium project on the genetic basis of non-Hodgkin lymphoma (NHL) subtypes, we develop PolyGIM, a procedure to fit the PLR model by integrating individual-level data with summary data extracted from multiple studies under different designs. The summary data consist of coefficient estimates from working logistic regression models established by external studies. Examples of the working model include the case-case comparison model and the case-control comparison model, which compares the control group with a subtype group or a broad disease group formed by merging several subtypes. PolyGIM efficiently evaluates risk effects and provides a powerful test for disease subtype heterogeneity in situations when only summary data, instead of individual-level data, is available from external studies due to various informatics and privacy constraints. We investigate the theoretic properties of PolyGIM and use simulation studies to demonstrate its advantages. Using data from eight genome-wide association studies within the NHL consortium, we apply it to study the effect of the polygenic risk score defined by a lymphoid malignancy on the risks of four NHL subtypes. These results show that PolyGIM can be a valuable tool for pooling data from multiple sources for a more coherent evaluation of disease subtype heterogeneity.

Serum perfluorooctane sulfonate and perfluorooctanoate and risk of postmenopausal breast cancer according to hormone receptor status: An analysis in the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial.

Per- and polyfluoroalkyl substances (PFAS) are highly persistent endocrine-disrupting chemicals that may contribute to breast cancer development; however, epidemiologic evidence is limited. We investigated associations between prediagnostic serum levels of perfluorooctane sulfonate (PFOS) and perfluorooctanoate (PFOA) and postmenopausal breast cancer risk, overall and by hormone receptor status, in a nested case-control study of 621 cases and 621 matched controls in the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. PFOS and PFOA levels were determined based on serum metabolomic profiling performed using ultraperformance liquid chromatography-tandem mass spectrometry. We used multivariable conditional logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the association between each PFAS and breast cancer risk, overall, by estrogen receptor (ER) or progesterone receptor (PR) status, and by joint ER/PR status. We found little evidence of association between PFOS or PFOA and breast cancer risk overall. However, in subtype-specific analyses, we observed statistically significant increased risks of ER+, PR+, and ER+/PR+ tumors for the third vs lowest quartile of serum PFOS (ORs [95% CIs] = 1.59 [1.01-2.50], 2.34 [1.29-4.23], and 2.19 [1.21-3.98], respectively) and elevated but nonstatistically significant ORs for the fourth quartile. Conversely, for PFOA, modest positive associations with ER-, PR-, ER+/PR-, and ER-/PR- tumors were generally seen in the upper quartiles. Our findings contribute evidence supporting positive associations between serum PFOS and hormone receptor-positive tumors, and possibly between PFOA and receptor-negative tumors. Future prospective studies incorporating tumor hormone receptor status are needed to better understand the role of PFAS in breast cancer etiology.

Circulating immune markers and risks of non-Hodgkin lymphoma subtypes: A pooled analysis.

Although prediagnostic circulating concentrations of the immune activation markers soluble CD27 (sCD27), sCD30 and chemokine ligand-13 (CXCL13) have been associated with non-Hodgkin lymphoma (NHL) risk, studies have been limited by sample size in associations with NHL subtypes. We pooled data from eight nested case-control studies to investigate subtype-specific relationships for these analytes. Using polytomous regression, we calculated odds ratios (ORs) with 95% confidence intervals (CIs) relating study-specific analyte tertiles to selected subtypes vs controls (n = 3310): chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL; n = 623), diffuse large B cell lymphoma (DLBCL; n = 621), follicular lymphoma (FL; n = 398), marginal zone lymphoma (MZL; n = 138), mantle cell lymphoma (MCL; n = 82) and T cell lymphoma (TCL; n = 92). We observed associations with DLBCL for elevated sCD27 [OR for third vs first tertile (ORT3 ) = 2.2, 95% CI = 1.6-3.1], sCD30 (ORT3  = 2.0, 95% CI = 1.6-2.5) and CXCL13 (ORT3  = 2.3, 95% CI = 1.8-3.0). We also observed associations with sCD27 for CLL/SLL (ORT3  = 3.3, 95% CI = 2.4-4.6), MZL (ORT3  = 7.7, 95% CI = 3.0-20.1) and TCL (ORT3  = 3.4, 95% CI = 1.5-7.7), and between sCD30 and FL (ORT3  = 2.7, 95% CI = 2.0-3.5). In analyses stratified by time from phlebotomy to case diagnosis, the sCD27-TCL and all three DLBCL associations were equivalent across both follow-up periods (<7.5, ≥7.5 years). For other analyte-subtype comparisons, associations were stronger for the follow-up period closer to phlebotomy, particularly for indolent subtypes. In conclusion, we found robust evidence of an association between these immune markers and DLBCL, consistent with hypotheses that mechanisms related to immune activation are important in its pathogenesis. Our other findings, particularly for the rarer subtypes MZL and TCL, require further investigation.

An approach for normalization and quality control for NanoString RNA expression data.

The NanoString RNA counting assay for formalin-fixed paraffin embedded samples is unique in its sensitivity, technical reproducibility and robustness for analysis of clinical and archival samples. While commercial normalization methods are provided by NanoString, they are not optimal for all settings, particularly when samples exhibit strong technical or biological variation or where housekeeping genes have variable performance across the cohort. Here, we develop and evaluate a more comprehensive normalization procedure for NanoString data with steps for quality control, selection of housekeeping targets, normalization and iterative data visualization and biological validation. The approach was evaluated using a large cohort ($N=\kern0.5em 1649$) from the Carolina Breast Cancer Study, two cohorts of moderate sample size ($N=359$ and$130$) and a small published dataset ($N=12$). The iterative process developed here eliminates technical variation (e.g. from different study phases or sites) more reliably than the three other methods, including NanoString's commercial package, without diminishing biological variation, especially in long-term longitudinal multiphase or multisite cohorts. We also find that probe sets validated for nCounter, such as the PAM50 gene signature, are impervious to batch issues. This work emphasizes that systematic quality control, normalization and visualization of NanoString nCounter data are an imperative component of study design that influences results in downstream analyses.