Prostate, Lung, Colorectal And Ovarian Research Articles

Ultra-processed food consumption and risk of chronic respiratory diseases mortality

Chronic respiratory diseases (CRDs) are diseases of the respiratory tract and are among the most prominent causes of disability and mortality globally(1). Chronic obstructive pulmonary disease (COPD) and lung cancer are among the leading cause of death among all CRDs(2). Evidence showed that diet, particularly ultra-processed foods (UPFs) are strongly associated with cardiovascular disease, diabetes, cancer, and depression(3). However, the link between UPFs intake and CRDs has rarely been investigated. we aimed to examine the association between UPF consumption and risk of mortality due to CRDs overall, COPD and lung cancer among adults in the USA. A total of 96,607 participants aged 55 years and over were obtained from Prostate, Lung, Colorectal and Ovarian (PLCO) cancer study, a randomised trial designed to investigate the effects of screening on cancer-related mortality. However, data collected also afforded the opportunity to examine the relationships between UPF intake and mortality caused by respiratory diseases. Dietary history of participants was collected at baseline using a validated food frequency questionnaire as was the presence of respiratory diseases. Food items were grouped into one of the four NOVA food classification system(4). Cox regression was fitted to estimate the risk of all-cause mortality and cause-specific mortality due to increased consumption of UPFs over time. Competing risk regression was used to account for the competing risks events and effect of participant loss. During the follow-up period of 1,379,655.5 person-years (median 16.8 years), 28700 all-cause, 4,901 all respiratory, 2,015 lung cancer and 1,536 COPD mortalities occurred. A dose-response association was found between higher UPF intake and mortality from all respiratory diseases and COPD, but not lung cancer. After considering competing events, higher intake of UPF increased the risk of mortality from all respiratory diseases by 10% (HR: 1.10; 95% CI: 1.01, 1.21) and COPD by 20% (HR: 1.20; 95% CI: 1.02, 1.42). After imputation for missing data, the risk of lung cancer increased by 25% among participants in the highest quintile of UPF intake. The PLCO trial data highlighted that consumption of UPF increased respiratory mortality, among those with COPD, however further mechanistic studies are recommended to further clarify the link between UPF and lung cancer. This study also indicated that a high intake of UPF generally increases the risk of mortality of those with respiratory diseases and contributes to a large body of evidence indicating that higher UPF consumption increases the overall risk of mortality.

Abstract 3464: Development and prospective validation of an estrogen receptor positive breast cancer risk model to identify women who could benefit for risk-reducing therapies

Abstract Background: Breast cancer risk-reducing therapies such as tamoxifen and aromatase inhibitors are effective for ER-positive (ER+) but not for ER-negative disease. As these therapies have side effects it is important to identify women at risk of ER+ disease. We developed and validated ER-specific risk prediction models in a prospective cohort and evaluated the expected gains of predicting ER+ vs overall disease. Methods: The iCARE-Lit model integrates established questionnaire-based risk factors and a 313 variant polygenic risk score. We reparametrized the iCARE-Lit model to estimate risk of ER+ and ER- disease separately by obtaining relative risks from published literature for ages at menarche, menopause, first childbirth, and parity to account for their heterogeneous associations with risk of ER-defined subtypes. We estimated 5-year (yr) absolute risk (AR) for ER+ disease using an overall and ER+ model. We evaluated model performance in the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial prospective cohort. This included evaluation of calibration (expected-to-observed (E/O) ratio) and discrimination (area under the receiver operating characteristic curve (AUC)), among 46,571 self-reported non-Hispanic White women aged 50-75 yrs (1,052 ER+ cases with 5 yrs of follow-up from enrollment). We compared projected risk stratification of the overall and ER+ models among eligible US women in terms of proportions of women and future ER+ cases identified above the 3% 5-yr AR threshold recommended for risk-reducing interventions in the US. Results: In predicting ER+ disease in PLCO, on average the overall and ER+ AR were well calibrated; however, models overpredicted risk at the ≥3% 5-yr AR threshold, (E/O = 1.31 (1.20, 1. 42) and 1.23 (1.13, 1.34), respectively. Risk discrimination was similar from the overall and ER+ models (AUC=0.65 (0.64-0.67) and 0.66 (0.64-0.67), respectively. The overall model projected that 16% of women in the US could be eligible for risk-reducing therapies, compared to 11% when using ER+ model, resulting in ~1.4 million less women crossing the risk threshold when using the ER+ score. However, the percentage of ER+ cases in the US population projected to occur within 5-yrs among eligible women was larger for the overall (38%) than ER+ (32%) risk score. Conclusion: Findings suggest that ER-specific risk scores might not offer a substantial advantage compared to overall risk scores to identify women eligible for risk-reducing therapies. Further risk-benefit analyses are needed to quantify the potential gains of predicting ER+ vs overall breast cancer. Citation Format: Thomas U. Ahearn, Srijon Mukhopadhyay, Jeya Balasubramanian, Nilanjan Chatterjee, Montserrat García-Closas, Parichoy Pal Choudhury. Development and prospective validation of an estrogen receptor positive breast cancer risk model to identify women who could benefit for risk-reducing therapies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3464.

Abstract 6147: Genome-wide association study identifies new genetic susceptibility loci for multiple primary cancers

Abstract Objectives: Genetic susceptibility is thought to contribute to the development of multiple primary cancers (MPC), often called secondary cancers. Although rare variants contribute to risk, these only account for a small fraction of MPC cases. The contribution of common variants to risk is unknown. Methods: To identify common genetic variants associated with the risk of MPC, we conducted a trans-ancestry meta-analysis of genome-wide association studies (GWAS), including 7,360 MPC cases and 138,684 controls from the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial and UK Biobank (UKBB). Association analyses were performed separately by genetic ancestry, genotype platform, and study, adjusting for age, sex, and principal components, and the results were meta-analyzed together using a fixed effects model. Genome-wide SNP heritability was estimated using GCTA. Pathway and functional enrichment analyses were conducted to gain insights into potential biological mechanisms underlying discovered loci. Results: We identified one novel locus at chromosome 3q26.2 (LRRC34, rs7621631) that was associated with MPC risk (P=1.16x10-8). Variants in this region have been previously associated with telomere length, suggesting a possible underlying mechanism. In sex-stratified analyses, we identified an additional locus at chromosome 12q24.33 (intergenic, rs10466868) associated with MPC in men (P= 7.76x10-8), but not women. Although the risk associated with these two discovered loci was small, the genome-wide SNP heritability was estimated to be 12%, suggesting that there are likely more common variants to be discovered for MPC risk. Conclusions: Our study demonstrates that common genetic variation contributes to the risk of multiple primary cancers and suggests additional loci are likely to be identified with larger studies. Citation Format: Shisi He, James Perry, Shengchao Li, Braxton D. Mitchell, Yuji Zhang, Shuo Chen, Laura Beane-Freeman, Kathryn Hughes Barry, Sonja I. Berndt. Genome-wide association study identifies new genetic susceptibility loci for multiple primary cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6147.

Ultra-processed food consumption and risk of chronic respiratory diseases mortality among adults: evidence from a prospective cohort study.

The purpose of the study was to determine the relationships between ultra-processed food (UPF) consumption and risk of mortality due to chronic respiratory diseases (CRDs) overall, chronic obstructive pulmonary disease (COPD), and lung cancer. A total of 96,607 participants aged 55years and over were included from the Prostate, Lung, Colorectal and Ovarian (PLCO) cancer trial. Dietary intake was measured using food frequency questionnaire. Cox regression was fitted to estimate the risk of all-cause mortality and mortality due to CRDs overall, COPD and lung cancer associated with UPF intake. Competing risk regression was used to account for deaths from other causes and censoring. During the follow-up of 1,379,655.5 person-years (median 16.8years), 28,700 all-cause, 4092 CRDs, 2015 lung cancer and 1,536 COPD mortality occurred. A higher intake of UPF increased the risk of mortality from CRDs overall by 10% (HR 1.10; 95% CI 1.01, 1.22) and COPD by 26% (HR 1.26; 95% CI 1.06, 1.49) but not associated with lung cancer mortality risk (HR 0.97; 95% CI 0.84, 1.12). However, the risk of lung cancer increased by 16% (HR 1.16; 95% CI 1.01, 1.34) in the highest UPF intake after multiple imputation. Dose-response relationships existed for CRDs and COPD mortality but not lung cancer. UPF consumption was associated with an increased risk of CRD mortality. The association between UPF consumption and lung cancer mortality is inconclusive and only significant when multiple imputation was applied.

Dietary phytoestrogen intake and ovarian cancer risk: a prospective study in the Prostate, Lung, Colorectal and Ovarian (PLCO) cohort.

Estrogen plays crucial roles in ovarian tumorigenesis. Phytoestrogens (PEs) are a type of daily dietary nutrients for humans and possess a mild estrogenic characteristic. This study aimed to assess the correlation of the consumption of dietary PEs with ovarian cancer risk using data in the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial. Participants were enrolled in PLCO from 1993 to 2001. Hazard ratios (HRs) and 95% confidence intervals (CIs) were utilized to determine the association between the intake of PEs and ovarian cancer occurrence, which were calculated by the Cox proportional hazards regression analysis. Totally, 24,875 participants were identified upon completion of the initial dietary questionnaire (DQX). Furthermore, the analysis also included a total of 45,472 women who filled out the diet history questionnaire (DHQ). Overall, after adjustment for confounders, the dietary intake of total PEs was significantly associated with the risk of ovarian cancer in the DHQ group (HRQ4vsQ1 = 0.69, 95% CI: 0.50-0.95; P for trend = 0.066). Especially, individuals who consumed the highest quartile of isoflavones were found to have a decreased risk of ovarian cancer in the DHQ group (HRQ4vsQ1 = 0.68, 95% CI: 0.50-0.94; P for trend = 0.032). However, no such significant associations were observed for the DQX group. In summary, this study suggests that increased dietary intake of total PEs especially isoflavones was linked with a lower risk for developing ovarian cancer. More researches are necessary to validate the findings and explore the potential mechanisms.

Variation in harms and benefits of prostate‐specific antigen screening for prostate cancer by socio‐clinical risk factors: A rapid review

AbstractObjectiveTo analyse the latest evidence on the relative harms and benefits of screening and diagnostic pathways with close examination of (i) men aged 50 years or older, (ii) men whose ethnicity places them at higher risk and (iii) men with a family history.MethodsWe conducted a literature search using PubMed and Cochrane Central Register of Controlled Trials (CENTRAL) databases and other sources, from January 1990 to 25 January 2023. Two independent reviewers selected for randomised controlled trials (RCTs) and cohort studies which met our inclusion criteria.ResultsTwenty‐eight articles were selected, from six trials, including the Göteborg trial—reported separately from European Randomised Study of Screening for Prostate Cancer (ERSPC). Prostate‐specific antigen (PSA)‐based screening led to the increased detection of low‐grade cancer and reduction of advanced/metastatic disease but had contradictory effects on prostate cancer (PCa)‐specific mortality (no difference or reduced), possibly due to issues of contamination or compliance. Screening men from a relatively young age (50–55) reduced risk of PCa‐specific mortality in a subanalysis of an 18‐year follow‐up study and in a 17‐year cohort study from the main Göteborg trial. Moreover, one Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial analysis reported a trend of reduced risk of PCa‐specific mortality for men with a family history who were screened. [Correction added on 05 March 2024, after first online publication: “Cancer Screening Trial” has been added to the preceding sentence.] However, we did not find relevant studies for ethnicity.ConclusionUnder current UK practice, the choice to conduct a PSA test relies on a shared decision‐making approach guided by known risk factors. However, we found there was a lack of strong evidence on the harms and benefits of PSA screening by socio‐clinical risk factors and suggest further research is required to understand the long‐term impact of screening on high‐risk populations in the current diagnostic setting.

Associations between Two Dietary Quality Scores and Pancreatic Cancer Risk in a US National Prospective Cohort Study

Objective Most previous studies investigated the associations between intake of individual nutrients and risk of disease, which failed to consider the potential interactions and correlations between various nutrients contained in food. Although dietary quality scores provide a comprehensive evaluation of the entire diet, it remains elusive whether they are associated with the risk of pancreatic cancer. Methods Dietary intake data collected with the Dietary Questionnaire (DQX) and Diet History Questionnaire (DHQ) were used to calculate HEI-2015 and DQI-R scores for participants in the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial. A high score indicates an increased intake of adequacy components and a decreased intake of moderation components. This study included 252 cases of pancreatic cancer documented from 58,477 persons during a median follow-up of 12.2 years in the DQX cohort and 372 cases of pancreatic cancer ascertained from 101,721 persons during a median follow-up of 8.9 years in the DHQ cohort. Cox proportional hazards regression analysis was performed to calculate hazard ratios (HR) and 95% confidence intervals (CI) for the associations between the two dietary quality scores and pancreatic cancer risk. Results After adjustment for confounders, HEI-2015 and DQI-R scores were not significantly associated with pancreatic cancer risk. However, a significantly lower risk was observed for overweight persons with a higher HEI-2015 score in the DQX cohort (HR [95% CI] comparing the highest with lowest tertile: 0.52 [0.32, 0.85], p for trend = 0.009) and those with higher scores of some individual components. Conclusion Collectively, overall dietary quality is not associated with an altered risk of pancreatic cancer in this US population.

Navigating through the Controversies and Emerging Paradigms in Early Detection of Prostate Cancer: Bridging the Gap from Classic RCTs to Modern Population-Based Pilot Programs.

Over the last three decades, the European Randomized Study of Screening for Prostate Cancer (ERSPC) and the US-based Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening have steered the conversation around the early detection of prostate cancer. These two randomized trials assessed the effect of screening on prostate cancer disease-specific mortality. Elevated PSA levels were followed by a systematic sextant prostate biopsy. Standard repeat testing intervals were applied. After controversies from 2009 to 2016 due to contradicting results of the two trials, the results aligned in 2016 and showed that early PSA detection reduces prostate cancer-specific mortality. However, overdiagnosis rates of up to 50% were reported, and this sparked an intense debate on harms and benefits for almost 20 years. The balance between harms and benefits is highly debated and has initiated further research to investigate new ways of early detection. In the meantime, the knowledge and tools for the diagnostic algorithm improved. This is a continuously ongoing effort which focuses on individual risk-based screening algorithms that preserve the benefits of the purely PSA-based screening algorithms, while reducing the side effects. An important push towards investigating new techniques for early detection came from the European Commission on the 20th of September 2022. The European Commission published its updated recommendation to investigate prostate, lung, and gastric cancer early detection programs. This opened a new window of opportunity to move away from the trial setting to population-based early detection settings. With this review, we aim to review 30 years of historical evidence of prostate cancer screening, which led to the initiation of the 'The Prostate Cancer Awareness and Initiative for Screening in the European Union' (PRAISE-U) project, which aims to encourage the early detection and diagnosis of PCa through customized and risk-based screening programs.

Assessing eligibility for lung cancer screening using parsimonious ensemble machine learning models: A development and validation study.

Risk-based screening for lung cancer is currently being considered in several countries; however, the optimal approach to determine eligibility remains unclear. Ensemble machine learning could support the development of highly parsimonious prediction models that maintain the performance of more complex models while maximising simplicity and generalisability, supporting the widespread adoption of personalised screening. In this work, we aimed to develop and validate ensemble machine learning models to determine eligibility for risk-based lung cancer screening. For model development, we used data from 216,714 ever-smokers recruited between 2006 and 2010 to the UK Biobank prospective cohort and 26,616 high-risk ever-smokers recruited between 2002 and 2004 to the control arm of the US National Lung Screening (NLST) randomised controlled trial. The NLST trial randomised high-risk smokers from 33 US centres with at least a 30 pack-year smoking history and fewer than 15 quit-years to annual CT or chest radiography screening for lung cancer. We externally validated our models among 49,593 participants in the chest radiography arm and all 80,659 ever-smoking participants in the US Prostate, Lung, Colorectal and Ovarian (PLCO) Screening Trial. The PLCO trial, recruiting from 1993 to 2001, analysed the impact of chest radiography or no chest radiography for lung cancer screening. We primarily validated in the PLCO chest radiography arm such that we could benchmark against comparator models developed within the PLCO control arm. Models were developed to predict the risk of 2 outcomes within 5 years from baseline: diagnosis of lung cancer and death from lung cancer. We assessed model discrimination (area under the receiver operating curve, AUC), calibration (calibration curves and expected/observed ratio), overall performance (Brier scores), and net benefit with decision curve analysis. Models predicting lung cancer death (UCL-D) and incidence (UCL-I) using 3 variables-age, smoking duration, and pack-years-achieved or exceeded parity in discrimination, overall performance, and net benefit with comparators currently in use, despite requiring only one-quarter of the predictors. In external validation in the PLCO trial, UCL-D had an AUC of 0.803 (95% CI: 0.783, 0.824) and was well calibrated with an expected/observed (E/O) ratio of 1.05 (95% CI: 0.95, 1.19). UCL-I had an AUC of 0.787 (95% CI: 0.771, 0.802), an E/O ratio of 1.0 (95% CI: 0.92, 1.07). The sensitivity of UCL-D was 85.5% and UCL-I was 83.9%, at 5-year risk thresholds of 0.68% and 1.17%, respectively, 7.9% and 6.2% higher than the USPSTF-2021 criteria at the same specificity. The main limitation of this study is that the models have not been validated outside of UK and US cohorts. We present parsimonious ensemble machine learning models to predict the risk of lung cancer in ever-smokers, demonstrating a novel approach that could simplify the implementation of risk-based lung cancer screening in multiple settings.

Serum concentrations of per- and polyfluoroalkyl substances and risk of renal cell carcinoma in the Multiethnic Cohort Study

Per- and polyfluoroalkyl substances (PFAS) are environmentally persistent organic pollutants detectable in the serum of most U.S. adults. We previously reported a positive association between serum perfluorooctanoate (PFOA) concentrations and risk of renal cell carcinoma (RCC) within the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial, comprising predominantly White individuals enrolled in 1993–2001. To extend our investigations to a larger and more racially and ethnically diverse population, we conducted a nested case-control study of serum PFAS concentrations and RCC within the Multiethnic Cohort Study. We measured pre-diagnostic serum concentrations of nine PFAS among 428 RCC cases and 428 individually matched controls. We estimated odds ratios (ORs) and 95 % confidence intervals (CIs) for risk of RCC in relation to each PFAS using conditional logistic regression, adjusting for RCC risk factors and other PFAS. PFOA was not associated with RCC risk overall [doubling in serum concentration, ORcontinuous = 0.89 (95 %CI = 0.67, 1.18)]. However, we observed suggestive positive associations among White participants [2.12 (0.87, 5.18)] and among participants who had blood drawn before 2002 [1.49 (0.77, 2.87)]. Furthermore, higher perfluorononanoate (PFNA) concentration was associated with increased risk of RCC overall [fourth vs. first quartile, OR = 1.84 (0.97, 3.50), Ptrend = 0.04; ORcontinuous = 1.29 (0.97, 1.71)], with the strongest association observed among African American participants [ORcontinuous = 3.69 (1.33, 10.25)], followed by Native Hawaiian [2.24 (0.70, 7.19)] and White [1.98 (0.92, 4.25)] participants. Most other PFAS were not associated with RCC. While PFOA was not associated with RCC risk overall in this racially and ethnically diverse population, the positive associations observed among White participants and those with sera collected before 2002 are consistent with previous PLCO findings. Our study also provided new evidence of a positive association between PFNA and RCC risk that was strongest in African American participants. These findings highlight the need for additional epidemiologic research investigating PFAS exposures and RCC in large racially and ethnically diverse populations.

Mortality benefit of a blood-based biomarker panel for lung cancer and the PLCO cohort.

8560 Background: A 4-protein biomarker panel (4MP) combined with the validated PLCOm2012 clinical risk model has been shown to improve lung cancer risk estimation over either metric alone. We investigated whether these panels in combination could also identify individuals at high risk of harboring a lethal lung cancer. Methods: We used data from an established logistic regression combining the 4MP and the PLCOm2012 risk model, which were assessed in pre-diagnostic sera from 552 lung cancer cases and 2,193 non-cases from the Prostate Lung Colorectal and Ovarian (PLCO) cohort. Of the 552 lung cancer cases, 387 (70%) died from lung cancer. Cumulative incidence of lung cancer death as well as sub-distributional and cause-specific hazard ratios were calculated based on 4MP+PLCOm2012 risk scores at a pre-defined 1.0% and 1.7% 6-year risk thresholds, which correspond to the 2013 and 2021 US Preventive Services Task Force lung cancer screening criteria, respectively. Results: When considering cases diagnosed within 1 year of blood draw and all non-cases, the AUC estimate of the 4MP+PLCOm2012 model for risk prediction of lung cancer death was 0.88 (95% CI: 0.86-0.90). Among cases, the cumulative incidence of lung cancer death was statistically significantly higher in individuals with 4MP+PLCOm2012 scores above the 1.0% 6-year risk threshold (modified χ2: 5.42, P: 0.02). Corresponding sub-distributional and lung cancer death-specific hazard ratios for test-positive cases were 1.69 (95% CI: 1.07-2.66) and 1.80 (95% CI: 1.15-2.82), respectively. Conclusions: The blood-based biomarker panel in combination with PLCOm2012 identifies individuals at high risk of a lethal lung cancer.

Abstract 6465: Associations of early menopause and hormone therapy with lung health and mortality among female never and ever smokers from the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial

Abstract Our previous study using the Lovelace Smokers cohort identified early natural menopause (i.e., age at menopause<45 yr), which is a biomarker of ovarian aging, as a risk factor for lung disease and mortality among female smokers. However, most of the associations reported in female smokers with natural menopause were not observed in those with surgical menopause, (a mixed group of subjects with bilateral oophorectomy or hysterectomy without bilateral oophorectomy). Females with bilateral oophorectomy lose ovarian estrogen and progesterone production, while females with hysterectomy, +/- unilateral oophorectomy, maintain some of this hormone production. We hypothesize that associations between early menopause, lung health and mortality will vary based on type of menopause. Among 69,071 females from the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial, early menopause rates were 8.7%, 44.1%, and 72.8% in never smokers versus 12.1%, 51.6%, and 78.0% in ever smokers with natural, bilateral oophorectomy, or hysterectomy without bilateral oophorectomy, respectively. We analyzed the associations of early menopause and hormone therapy with lung health (physician diagnosed emphysema and chronic bronchitis and lung cancer incidence) and mortality (all-cause and cause-specific) outcomes by smoking status and menopause types. The most consistent associations were observed for all-cause mortality: 1) Except in never smokers who received hysterectomy only, early menopause was associated with higher all-cause mortality regardless of smoking status 2) hormone therapy was associated with lower all-cause mortality in all groups and the longer the use, the more beneficial the outcome; 3) the magnitude of this association was strongest in those who underwent bilateral oophorectomy. Furthermore, in ethnic disparity analysis, all-cause mortality was affected by early menopause to a lesser degree in non-Hispanic black ever smokers and there was increased benefit from hormone therapy in non-Hispanic black never smokers. Overall, we identified further evidence supporting early menopause as a risk factor for lung health and mortality and hormone therapy as being beneficial regardless of smoking status or menopause type. Our results support the “shorter lifetime estrogen exposure in early menopause” hypothesis and the clinical importance of hormone therapy beyond withdrawal symptom coping. Supported by National Cancer Institute (NCI) grant P30 CA118100. The authors thank the NCI for access to NCI's data collected by the PLCO Cancer Screening Trial (the Cancer Data Access System Project Number PLCO-981). Citation Format: Tessa Flores, Xiaochun Gai, Yiliang Zhu, Kimberly Leslie, Shuguang Leng. Associations of early menopause and hormone therapy with lung health and mortality among female never and ever smokers from the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6465.

Risk prediction models for endometrial cancer: development and validation in an international consortium.

Endometrial cancer risk stratification may help target interventions, screening, or prophylactic hysterectomy to mitigate the rising burden of this cancer. However, existing prediction models have been developed in select cohorts and have not considered genetic factors. We developed endometrial cancer risk prediction models using data on postmenopausal White women aged 45-85 years from 19 case-control studies in the Epidemiology of Endometrial Cancer Consortium (E2C2). Relative risk estimates for predictors were combined with age-specific endometrial cancer incidence rates and estimates for the underlying risk factor distribution. We externally validated the models in 3 cohorts: Nurses' Health Study (NHS), NHS II, and the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial. Area under the receiver operating characteristic curves for the epidemiologic model ranged from 0.64 (95% confidence interval [CI] = 0.62 to 0.67) to 0.69 (95% CI = 0.66 to 0.72). Improvements in discrimination from the addition of genetic factors were modest (no change in area under the receiver operating characteristic curves in NHS; PLCO = 0.64 to 0.66). The epidemiologic model was well calibrated in NHS II (overall expected-to-observed ratio [E/O] = 1.09, 95% CI = 0.98 to 1.22) and PLCO (overall E/O = 1.04, 95% CI = 0.95 to 1.13) but poorly calibrated in NHS (overall E/O = 0.55, 95% CI = 0.51 to 0.59). Using data from the largest, most heterogeneous study population to date (to our knowledge), prediction models based on epidemiologic factors alone successfully identified women at high risk of endometrial cancer. Genetic factors offered limited improvements in discrimination. Further work is needed to refine this tool for clinical or public health practice and expand these models to multiethnic populations.

GWAS Explorer: an open-source tool to explore, visualize, and access GWAS summary statistics in the PLCO Atlas

The Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial is a prospective cohort study of nearly 155,000 U.S. volunteers aged 55–74 at enrollment in 1993–2001. We developed the PLCO Atlas Project, a large resource for multi-trait genome-wide association studies (GWAS), by genotyping participants with available DNA and genomic consent. Genotyping on high-density arrays and imputation was performed, and GWAS were conducted using a custom semi-automated pipeline. Association summary statistics were generated from a total of 110,562 participants of European, African and Asian ancestry. Application programming interfaces (APIs) and open-source software development kits (SKDs) enable exploring, visualizing and open data access through the PLCO Atlas GWAS Explorer website, promoting Findable, Accessible, Interoperable, and Re-usable (FAIR) principles. Currently the GWAS Explorer hosts association data for 90 traits and >78,000,000 genomic markers, focusing on cancer and cancer-related phenotypes. New traits will be posted as association data becomes available. The PLCO Atlas is a FAIR resource of high-quality genetic and phenotypic data with many potential reuse opportunities for cancer research and genetic epidemiology.

Abstract P076: Contribution of the microbiome to a metabolomic signature predictive of risk for pancreatic cancer

Abstract Purpose: Emerging evidence implicates the microbiome in the development of pancreatic cancer. We investigated whether increased levels of microbial-related metabolites in circulation are associated with pancreatic cancer risk. Methods: We applied metabolomics profiling to sera from the Prostate, Lung, Colorectal and Ovarian (PLCO) Cohort to quantify and build a model based on 14 microbial-related metabolites. The study involved samples collected from 172 subjects within five years prior to diagnosis and 863 matched controls. Data from five PLCO centers were used for training and from two centers for validation and model selection. The model was subsequently tested using samples from three independent centers. The contributions of non-microbial-associated metabolites as well as CA19-9 was also assessed. Results: A 3-marker microbial-related metabolite panel yielded in the PLCO testing set an AUC of 0.64 (95% CI: 0.53-0.76) for 5-year probability of pancreatic cancer. Five additional non-microbial metabolites were identified that when combined with the microbiome panel yielded an AUC of 0.79 (95% CI: 0.71-0.88) for 5-year probability of pancreatic cancer in the PLCO testing set. The combined metabolite panel and CA19-9 yielded an AUC of 0.86 (95% CI: 0.77-0.95) for 2-year probability of pancreatic cancer in the PLCO testing set, which was improved compared to CA19-9 alone (AUC: 0.70 (95% CI: 0.57-0.82), p< 0.001). Conclusion: We developed a metabolite panel derived in part from the microbiome for risk assessment of pancreatic cancer, which has relevance to prevention and early detection. Citation Format: Johannes F. Fahrmann, Ehsan Irajizad, Ana Kenney, Tiffany Tang, Jody Vykoukal, Ranran Wu, Jennifer B. Dennison, Marta Sans Escofet, James P. Long, Maureen Loftus, John A. Chabot, Michael D. Kluger, Fay Kastrinos, Lauren Brais, Ana Babic, Kunal Jajoo, Linda S. Lee, Thomas E. Clancy, Kimmie Ng, Andrea Bullock, Jeanine M. Genkinger, Anirban Maitra, Kim-Anh Do, Bin Yu, Brian M. Wolpin, Samir Hanash. Contribution of the microbiome to a metabolomic signature predictive of risk for pancreatic cancer. [abstract]. In: Proceedings of the AACR Special Conference: Precision Prevention, Early Detection, and Interception of Cancer; 2022 Nov 17-19; Austin, TX. Philadelphia (PA): AACR; Can Prev Res 2023;16(1 Suppl): Abstract nr P076.

Abstract P013: Impact of blood-based biomarkers for predicting lung cancer mortality in the PLCO cohort

Abstract Purpose: To investigate the utility of integrating a panel of circulating protein biomarkers in combination with a risk model based on subject characteristics for identifying individuals at high risk of harboring a lethal lung cancer. Methods: Data for a 4-marker protein panel (4MP) (consisting of the precursor form of surfactant protein B, cancer antigen 125, carcinoembryonic antigen, and cytokeratin-19 fragment) previously assayed in pre-diagnostic sera from 552 lung cancer cases and 2,193 non-cases from the Prostate Lung Colorectal and Ovarian (PLCO) cohort as well as a scores from a logistic regression model that combined the 4MP with the PLCOm2012 risk model were used for this study. Of the 552 lung cancer cases, 387 (70%) died from lung cancer. Cumulative incidence of lung cancer death as well as sub-distributional and cause-specific hazard ratios were calculated based on 4MP+PLCOm2012 risk scores at a pre-defined 1.0%/6-year risk threshold, which corresponds to current US Preventive Services Task Force screening criteria. For hazard modeling, stage at the time of clinical diagnosis and treatment modality were considered as co-variables. Results: When considering cases diagnosed within 1 year of blood draw and all non-cases, the performance estimate of the 4MP+PLCOm2012 model for risk prediction of lung cancer death was 0.88 (95% CI: 0.86-0.90). Among cases only, at the 1.0%/6-year risk threshold the cumulative incidence of lung cancer death was statistically significantly higher in ‘test positive’ cases compared to ‘test negative’ cases (Chi-square test: 5.42, P: 0.02). The adjusted sub distributional hazard ratio for ‘test positive’ cases was 1.67 (95% CI: 1.02-2.74). The adjusted lung-cancer death-specific hazard ratio for ‘test positive’ cases was 2.02 (95% CI: 1.28-3.17). Conclusions and Relevance: The blood-based biomarker panel in combination with PLCOm2012 identifies individuals at high risk of a lethal lung cancer. Citation Format: Ehsan Irajizad, Johannes F. Fahrmann, Jody V. Vykoukal, Jennifer B. Dennison, James P. Long, Kim-Anh Do, Edwin J. Ostrin, Sam Hanash. Impact of blood-based biomarkers for predicting lung cancer mortality in the PLCO cohort. [abstract]. In: Proceedings of the AACR Special Conference: Precision Prevention, Early Detection, and Interception of Cancer; 2022 Nov 17-19; Austin, TX. Philadelphia (PA): AACR; Can Prev Res 2023;16(1 Suppl): Abstract nr P013.

Dietary Inflammatory Index and Mortality from All Causes, Cardiovascular Disease, and Cancer: A Prospective Study.

Simple SummaryOur study investigated the association between the inflammatory potential of the diet, as calculated by the Energy-adjusted Dietary Inflammatory Index (E-DIITM), and total and cause-specific mortality. We analyzed the data of 101,832 participants from the Prostate, Lung, Colorectal and Ovarian (PLCO) trial with 17 years of follow-up. We found that the E-DII was significantly associated with all-cause mortality. The HR (95% CI) in the highest E-DII quintile compared to the lowest quintile was 1.23 (1.18–1.29) (p for trend <0.001). Based on the fully adjusted model, the E-DII was also statistically significantly associated with CVD and cancer mortality. The findings of our study provide more evidence to help guide recommendations regarding anti-inflammatory food intake.The Energy-adjusted Dietary Inflammatory Index (E-DIITM) is a comprehensive, literature-derived index for assessing the effect of dietary constituents on inflammatory biomarkers and inflammation-related chronic diseases. Several studies have examined the association between E-DII scores and mortality, with results that vary across populations. Therefore, in the present study, we aimed to investigate the potential association between E-DII scores and all-cause, cardiovascular disease (CVD), and cancer mortality using data from the Prostate, Lung, Colorectal and Ovarian (PLCO) Screening Trial. E-DII scores, calculated based on a food-frequency questionnaire, were analyzed both as a continuous variable and after categorization into quintiles. A multivariate Cox proportional hazards model was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). A total of 101,832 individuals were included, with 24,141 deaths recorded after a median of 17.0 years of follow-up. In multivariable-adjusted analyses, the E-DII score was significantly associated with all-cause mortality. The HR (95% CI) in the highest E-DII quintile compared to the lowest quintile was 1.23 (1.18–1.29). The E-DII was also statistically related to CVD mortality (Q5 vs. Q1; HR, 1.30 [95% CI, 1.20–1.41]) and cancer mortality (Q5 vs. Q1; HR, 1.14 [95% CI, 1.06–1.24]). Similar results were obtained from sensitivity analyses and subgroup analyses. In conclusion, the inflammatory potential of the diet, as calculated by the E-DII, was significantly associated with overall and CVD- and cancer-specific mortality risk in the PLCO study.

Variability of body mass index and risks of prostate, lung, colon, and ovarian cancers.

ObjectiveWe investigated the association between cancer incidence and body mass index (BMI) variability calculated from the recall of weight at decades of age by participants in the USA Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial.MethodsA total of 89,822 individuals' BMI were recorded as recalled the participant's aged 30, 40, 50, 60, 70 years, and baseline. BMI variability was assessed using four indices: SD, coefficient of variation (CV), variability independent of the mean (VIM), and average real variability (ARV). The multivariate Cox regression analysis was performed to calculate hazard ratios (HRs) of these measures for incident cancers and corresponding 95% CIs.ResultsDuring the median follow-up of 11.8 years, there were newly diagnosed 5,012 cases of prostate cancer, 792 cases of lung cancer, 994 cases of colon cancer, and 132 cases of ovarian cancer. Compared with the lowest quartile (Q1) group, the highest quartile (Q4) group of BMI variability indices was associated with increased lung cancer risk, including BMI_SD (HR, 1.58; 95% CI, 1.17–2.12), BMI_CV (HR, 1.46; 95% CI, 1.10–1.94), BMI_VIM (HR, 1.73; 95% CI, 1.33–2.25), and BMI_ARV (HR, 2.17; 95% CI, 1.62–2.91). Associations between BMI variability and prostate, colon, and ovarian cancer incidences were of limited significance.ConclusionThe findings imply that maintaining a stable weight across adulthood is associated with a decreased incidence of lung cancer.

Serum Pepsinogen as a Biomarker for Gastric Cancer in the United States: A Nested Case-Control Study Using the PLCO Cancer Screening Trial Data.

Gastric cancer lacks specific symptoms, resulting in diagnosis at later stages and high mortality. Serum pepsinogen is a biomarker for atrophic gastritis, a gastric cancer precursor, and may be useful to detect persons at increased risk of gastric cancer. The Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial was conducted in the United States between 1993 and 2001. ELISA-based pepsinogen tests were conducted on prediagnostic serum samples of 105 PLCO participants who developed gastric cancer and 209 age, sex, and race-matched controls. Pepsinogen positive (PG+) was defined as pepsinogen I ≤ 70 μg/L and pepsinogen I/II ratio ≤3.0. Results of conditional logistic regression models, and sensitivity and specificity, of PG+ for gastric cancer are reported. Gastric cancer cases were more likely to be PG+ (31.4% vs. 5.5%, P < 0.001) at baseline than controls. Compared to PG-, PG+ was associated with an 8.5-fold increased risk for gastric cancer [95% confidence interval (CI) = 3.8-19.4]. This risk remained significant after adjusting for Helicobacter pylori, family history of gastric cancer, education, smoking, and BMI (aOR, 10.6; 95% CI, 4.3-26.2). In subgroup analysis, PG+ individuals were 11-fold more like to develop non-cardia gastric cancer (OR, 11.1; 95% CI, 4.3-28.8); conversely, they were not significantly more likely to develop cardia gastric cancer (OR, 2.0; 95% CI = 0.3-14.2). PG+ status yielded low sensitivity but high specificity for both noncardia (44.3%; 93.6%) and cardia gastric cancer (5.7%; 97.2%). Prediagnostic serum pepsinogen levels from a large, prospective cohort study were associated with risk of gastric cancer, particularly noncardia gastric cancer. PG status may identify individuals at higher risk of noncardia gastric cancer for targeted screening or interventions. See related commentary by Zhou and Huang, p. 1257.

Single nucleotide polymorphisms in FOXP1 and RORA of the lymphocyte activation-related pathway affect survival of lung cancer patients.

BackgroundLymphocyte activation is part of a complex microenvironment that affects the development and progression of solid tumors. The present study analyzed the associations between genetic variants in lymphocyte activation-related genes and survival of patients with non-small cell lung cancer (NSCLC).MethodsOur study evaluated the associations of 14,400 (1,599 genotyped and 12,801 imputed) single-nucleotide polymorphisms (SNPs) in 176 lymphocyte activation pathway-related genes with survival of 1,185 NSCLC patients in the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial and validated the results in another independent dataset of 984 NSCLC patients from the Harvard Lung Cancer Susceptibility (HLCS) trial.ResultsMultivariable Cox proportional hazards regression analyses identified two distinct and possibly functional variants in forkhead box P1 (FOXP1; rs2568847 G>C) and RAR-related orphan receptor A (RORA; rs922782 T>G) that were significantly and independently associated with overall survival (OS) [adjusted hazards ratios (HRs) of 1.21 and 0.82, respectively; 95% confidence intervals (CI), 1.11 to 1.32 and 0.76 to 0.88, respectively; P=5.38×10−6 and 2.68×10−2, respectively]. Combined analysis of the unfavorable genotypes showed a significant correlation with both OS and disease-specific survival (DSS) in patients with NSCLC patients from PLCO trial (both Ptrend<0.0001). Further expression quantitative trait loci (eQTL) analysis using RORA mRNA expression and genotype data in the 1000 Genomes Project demonstrated that the RORA rs922782 G allele predicted mRNA expression levels.ConclusionsGenetic variants in FOXP1 and RORA of the lymphocyte activation pathway may be promising predictors of NSCLC survival. The RORA rs922782 G allele may predict NSCLC survival, possibly by controlling RORA mRNA expression.