PLCO: Evolution of an Epidemiologic Resource and Opportunities for Future Studies

Early menopause and hormone therapy as determinants for lung health outcomes: a secondary analysis using the PLCO trial

RATIONALE

Early natural menopause (early-M; <45 years of age) increases the risk of lung morbidities and mortalities in smokers. However, it is largely unknown whether early-M due to surgery demonstrates similar effects and whether menopausal hormone therapy (MHT) is protective against lung diseases.

OBJECTIVES

To assess the associations of early-M and MHT with lung morbidities and mortalities using the prospective Prostate, Lung, Colorectal and Ovarian (PLCO) trial.

METHODS

We estimated the risk among 69 706 postmenopausal women in the PLCO trial, stratified by menopausal types and smoking status.

RESULTS

Early-M was associated with an increased risk of most lung disease and mortality outcomes in ever smokers with the highest risk seen for respiratory mortality (HR 1.98, 95% CI 1.34 to 2.92) in those with bilateral oophorectomy (BO). Early-M was positively associated with chronic bronchitis, and all-cause, non-cancer and respiratory mortality in never smokers with natural menopause or BO, with the highest risk seen for BO- respiratory mortality (HR 1.91, 95% CI 1.16 to 3.12). Ever MHT was associated with reduced all-cause, non-cancer and cardiovascular mortality across menopause types regardless of smoking status and was additionally associated with reduced risk of non-ovarian cancer, lung cancer (LC) and respiratory mortality in ever smokers. Among smokers, ever MHT use was associated with a reduction in HR for all-cause, non-cancer and cardiovascular mortality in a duration-dependent manner.

CONCLUSIONS

Smokers with early-M should be targeted for smoking cessation and LC screening regardless of menopause types. MHT users had a lower likelihood of dying from LC and respiratory diseases in ever smokers.

Associations of serum trimethylamine N-oxide and its precursors with colorectal cancer risk in the Prostate, Lung, Colorectal, Ovarian Cancer Screening Trial Cohort

BACKGROUND

Dietary intake influences gut microbiome composition, which in turn may be associated with colorectal cancer (CRC). Associations of the gut microbiome with colorectal carcinogenesis may be mediated through bacterially regulated, metabolically active metabolites, including trimethylamine N-oxide (TMAO) and its precursors, choline, L-carnitine, and betaine.

METHODS

Prospective associations of circulating TMAO and its precursors with CRC risk were investigated. TMAO, choline, betaine, and L-carnitine were measured in baseline serum samples from 761 incident CRC cases and 1:1 individually matched controls in the prospective Prostate, Lung, Colorectal, Ovarian Cancer Screening Trial Cohort using targeted fully quantitative liquid chromatography tandem mass spectrometry panels. Prospective associations of the metabolites with CRC risk, using multivariable conditional logistic regression, were measured. Associations of a priori-selected dietary exposures with the four metabolites were also investigated.

RESULTS

TMAO and its precursors were not associated with CRC risk overall, but TMAO and choline were positively associated with higher risk for distal CRC (continuous ORQ90 vs. Q10 [95% CI] = 1.90 [CI, 1.24-2.92; p = .003] and 1.26 [1.17-1.36; p < .0001], respectively). Conversely, choline was inversely associated with rectal cancer (ORQ90 vs. Q10 [95% CI] = 0.77 [0.76-0.79; p < .001]). Red meat, which was previously associated with CRC risk in the Prostate, Lung, Colorectal, Ovarian Cancer Screening Trial Cohort , was positively associated with TMAO (Spearman rho = 0.10; p = .0003).

CONCLUSIONS

Serum TMAO and choline may be associated with higher risk of distal CRC, and red meat may be positively associated with serum TMAO. These findings provide insight into a potential microbially mediated mechanism underlying CRC etiology.

Model-agnostic explanations for survival prediction models

Advanced machine learning methods capable of capturing complex and nonlinear relationships can be used in biomedical research to accurately predict time-to-event outcomes. However, these methods have been criticized as "black boxes" that are not interpretable and thus are difficult to trust in making important clinical decisions. Explainable machine learning proposes the use of model-agnostic explainers that can be applied to predictions from any complex model. These explainers describe how a patient's characteristics are contributing to their prediction, and thus provide insight into how the model is arriving at that prediction. The specific application of these explainers to survival prediction models can be used to obtain explanations for (i) survival predictions at particular follow-up times, and (ii) a patient's overall predicted survival curve. Here, we present a model-agnostic approach for obtaining these explanations from any survival prediction model. We extend the local interpretable model-agnostic explainer framework for classification outcomes to survival prediction models. Using simulated data, we assess the performance of the proposed approaches under various settings. We illustrate application of the new methodology using prostate cancer data.

Prediction of prognosis and treatment response in ovarian cancer patients from histopathology images using graph deep learning: a multicenter retrospective study

BACKGROUND

Ovarian cancer (OV) is a prevalent and deadly disease with high mortality rates. The development of accurate prognostic tools and personalized therapeutic strategies is crucial for improving patient outcomes.

METHODS

A graph-based deep learning model, the Ovarian Cancer Digital Pathology Index (OCDPI), was introduced to predict prognosis and response to adjuvant therapy using hematoxylin and eosin (H&E)-stained whole-slide images (WSIs). The OCDPI was developed using formalin-fixed, paraffin-embedded (FFPE) WSIs from the TCGA-OV cohort, and was externally validated in two independent cohorts from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO) and Harbin Medical University Cancer Hospital (HMUCH).

RESULTS

The OCDPI showed prognostic ability for overall survival prediction in the PLCO (HR, 1.916; 95% CI, 1.380-2.660; log-rank test, P < 0.001) and HMUCH (HR, 2.796; 95% CI, 1.404-5.568; log-rank test, P = 0.0022) cohorts. Patients with low OCDPI experienced better survival benefits and lower recurrence rates following adjuvant therapy compared to those with high OCDPI. Multivariable analyses, adjusting for clinicopathological factors, consistently identified OCDPI as an independent prognostic factor across all cohorts (all P < 0.05). Furthermore, OCDPI performed well in patients with low-grade tumors or fresh-frozen slides, and could differentiate between HRD-deficient or HRD-intact patients with and without sensitivity to adjuvant therapy.

CONCLUSION

The results from this multicenter cohort study indicate that the OCDPI may serve as a valuable and labor-saving tool to improve prognostic and predictive clinical decision-making in patients with OV.

Lifetime Body Weight Trajectories and Risk of Renal Cell Cancer: A Large U.S. Prospective Cohort Study

BACKGROUND

Body mass index (BMI) is a known risk factor for renal cell cancer (RCC), but data are limited as to the effect of lifetime exposure to excess body weight.

METHODS

Using the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (N = 138,614, 527 incident RCCs), we identified several anthropometric measures to capture the lifetime BMI patterns: (i) BMI at specific ages; (ii) adulthood BMI trajectories; (iii) cumulative exposure to overweight/obesity denoted as weighted years of living overweight/obese (WYO); and (iv) weight change during each age span. We conducted multivariable Cox model to quantify the association between each anthropometric metric and incident RCC.

RESULTS

A higher BMI at ages 20 and 50 and at baseline was associated with a greater hazard of RCC. Compared with individuals who retained normal BMI throughout adulthood, we observed an increased hazard of RCC for BMI trajectory of progressing from normal BMI to overweight [HR, 1.49; 95% confidence interval (CI), 1.19-1.87], from normal BMI to obesity (HR, 2.22; 95% CI, 1.70-2.90), and from overweight to obesity (HR, 2.78; 95% CI, 1.81-4.27). Compared with individuals who were never overweight (WYO = 0), elevated HRs were observed among individuals who experienced low (HR, 1.31; 95% CI, 0.99-1.74), medium (HR, 1.57; 95% CI, 1.20-2.05), and high (HR, 2.10; 95% CI, 1.62-2.72) WYO tertile. Weight gain of ≥10 kg was associated with increased RCC incidence for each age span.

CONCLUSIONS

Across the lifespan, being overweight/obese, weight gain, and higher cumulative exposure to excess weight were all associated with increased RCC risk.

IMPACT

It is important to avoid weight gain and assess BMI from a life-course perspective to reduce RCC risk.

Histopathology images predict multi-omics aberrations and prognoses in colorectal cancer patients

Histopathologic assessment is indispensable for diagnosing colorectal cancer (CRC). However, manual evaluation of the diseased tissues under the microscope cannot reliably inform patient prognosis or genomic variations crucial for treatment selections. To address these challenges, we develop the Multi-omics Multi-cohort Assessment (MOMA) platform, an explainable machine learning approach, to systematically identify and interpret the relationship between patients' histologic patterns, multi-omics, and clinical profiles in three large patient cohorts (n = 1888). MOMA successfully predicts the overall survival, disease-free survival (log-rank test P-value<0.05), and copy number alterations of CRC patients. In addition, our approaches identify interpretable pathology patterns predictive of gene expression profiles, microsatellite instability status, and clinically actionable genetic alterations. We show that MOMA models are generalizable to multiple patient populations with different demographic compositions and pathology images collected from distinctive digitization methods. Our machine learning approaches provide clinically actionable predictions that could inform treatments for colorectal cancer patients.

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.

Risk assessment for PFOA and kidney cancer based on a pooled analysis of two studies

INTRODUCTION

Perfluorooctanoic acid (PFOA) has been associated with kidney cancer in human studies.

METHODS

We conducted a pooled analysis of two large studies of PFOA and renal cell carcinoma (RCC, the most common type of kidney cancer); one from the National Cancer Institute (NCI) (324 cases and controls), and a second from the C8 Science Panel (103 cases and 511 controls). Serum PFOA levels were estimated a median of 8 years before diagnosis. Analyses were conducted via conditional logistic regression. Lifetime risk of kidney cancer per unit serum PFOA concentration and per unit dose were calculated.

RESULTS

The 25th, 50th and 75th percentiles of serum PFOA levels were 4.8, 7.3, and 23.9 ng/ml for the pooled analysis. The preferred model for the pooled datawas a two-piece linear spline model (knot at 12.5 ng/ml serum PFOA); the log odds of RCC increased 0.1349 per 1 ng/ml increase in serum PFOA up to the knot (eg, an OR of 2.02 (1.45-2.80) from the median to the knot), and was flat thereafter. The estimated lifetime excess risk (cancer slope factor) with an exposure of 1 ng/ml was 0.0018, similar to the excess risk of 0.0026 recently reported by CalEPA based on different methods. Assuming a serum half-life of 2.3 years and a distribution volume of 170 ml/kg for PFOA, our results are equivalent to 0.0128 per ng/kg/d of PFOA intake. To limit excess lifetime kidney cancer risk to 1/1,000,000, our data suggest a limit of 0.0015 ng/L (0.0015 ppt) for PFOA in drinking water, similar to CalEPA's proposed Public Health Goal and the new US EPA Drinking Water Health Advisory.

CONCLUSIONS

Our results correspond reasonably well with cancer slope factors developed by other investigators using published summary data, and suggest drinking water limits similar to new recommendations by the US EPA.

Relative impact of genetic ancestry and neighborhood socioeconomic status on all-cause mortality in self-identified African Americans

Self-identified race/ethnicity is a correlate of both genetic ancestry and socioeconomic factors, both of which may contribute to racial disparities in mortality. Investigators often hold a priori assumptions, rarely made explicit, regarding the relative importance of these factors. We studied 2,239 self-identified African Americans (SIAA) from the Prostate, Lung, Colorectal and Ovarian screening trial enrolled from 1993–1998 and followed prospectively until 2019 or until death, whichever came first. Percent African genetic ancestry was estimated using the GRAF-Pop distance-based method. A neighborhood socioeconomic status (nSES) index was estimated using census tract measures of income, housing, and employment and linked to participant residence in 2012. We used Directed Acyclic Graphs (DAGs) to represent causal models favoring (1) biomedical and (2) social causes of mortality. Hazard ratios were estimated using Cox models adjusted for sociodemographic, behavioral, and neighborhood covariates guided by each DAG. 901 deaths occurred over 40,767 person-years of follow-up. In unadjusted (biomedical) models, a 10% increase in percent African ancestry was associated with a 7% higher rate of all-cause mortality (HR: 1.07, 95% CI: 1.02, 1.12). This effect was attenuated in covariate adjusted (social) models (aHR: 1.01, 95% CI: 0.96, 1.06). Mortality was lower comparing participants in the highest to lowest nSES quintile following adjustment for covariates and ancestry (aHR: 0.74, 95% CI: 0.57, 0.98, Ptrend = 0.017). Higher African ancestry and lower nSES were associated with higher mortality, but African ancestry was not associated with mortality following covariate adjustment. Socioeconomic factors may be more important drivers of mortality in African Americans.

PLCOjs, a FAIR GWAS web SDK for the NCI Prostate, Lung, Colorectal and Ovarian Cancer Genetic Atlas project

MOTIVATION

The Division of Cancer Epidemiology and Genetics (DCEG) and the Division of Cancer Prevention (DCP) at the National Cancer Institute (NCI) have recently generated genome-wide association study (GWAS) data for multiple traits in the Prostate, Lung, Colorectal, and Ovarian (PLCO) Genomic Atlas project. The GWAS included 110 000 participants. The dissemination of the genetic association data through a data portal called GWAS Explorer, in a manner that addresses the modern expectations of FAIR reusability by data scientists and engineers, is the main motivation for the development of the open-source JavaScript software development kit (SDK) reported here.

RESULTS

The PLCO GWAS Explorer resource relies on a public stateless HTTP application programming interface (API) deployed as the sole backend service for both the landing page's web application and third-party analytical workflows. The core PLCOjs SDK is mapped to each of the API methods, and also to each of the reference graphic visualizations in the GWAS Explorer. A few additional visualization methods extend it. As is the norm with web SDKs, no download or installation is needed and modularization supports targeted code injection for web applications, reactive notebooks (Observable) and node-based web services.

AVAILABILITY AND IMPLEMENTATION

code at https://github.com/episphere/plco; project page at https://episphere.github.io/plco.

Type 2 diabetes prevention diet and the risk of pancreatic cancer: A large prospective multicenter study

BACKGROUND & AIMS

Type 2 diabetes prevention diet confers a lower risk of type 2 diabetes, which exhibits overlapping mechanisms with pancreatic cancer. We performed a prospective study to examine whether adherence to this dietary pattern is associated with a reduced risk of pancreatic cancer.

METHODS

A population-based cohort of 101,729 American adults was identified. A dietary diabetes risk reduction score was computed to reflect adherence to this dietary pattern, with higher scores representing greater adherence. Cox regression was used to compute hazard ratios (HRs) for pancreatic cancer incidence. Prespecified subgroup analyses were used to identify the potential effect modifiers.

RESULTS

After an average follow-up of 8.86 years (900,871.67 person-years), a total of 402 pancreatic cancer cases were observed. In the fully adjusted model, participants in the highest quartile of dietary diabetes risk reduction score were found to have a reduced risk of pancreatic cancer compared with those in the lowest quartile [HR_{quartiles 4versus1}: 0.62; 95% confidence interval (CI): 0.44, 0.86; P_trend = 0.004], which remained in a series of sensitivity analyses. Subgroup analyses further found that this favorable association was more pronounced in current or former smokers (HR_{quartiles 4versus1}: 0.48; 95% CI: 0.30, 0.77) than in never smokers (HR_{quartiles 4versus1}: 0.71; 95% CI: 0.44, 1.15), although the interaction test did not reach statistical significance (P_interaction = 0.095).

CONCLUSIONS

Greater adherence to type 2 diabetes prevention diet is associated with a lower risk of pancreatic cancer in this US population. More studies are needed to confirm our findings.

Associations of specific-age and decade recall body mass index trajectories with obesity-related cancer

Background

Excess body fatness, commonly approximated by a one-off determination of body mass index (BMI), is associated with increased risk of at least 13 cancers. Modelling of longitudinal BMI data may be more informative for incident cancer associations, e.g. using latent class trajectory modelling (LCTM) may offer advantages in capturing changes in patterns with time. Here, we evaluated the variation in cancer risk with LCTMs using specific age recall versus decade recall BMI.

Methods

We obtained BMI profiles for participants from the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. We developed gender-specific LCTMs using recall data from specific ages 20 and 50 years (72,513 M; 74,837 W); decade data from 30s to 70s (42,113 M; 47,352 W) and a combination of both (74,106 M, 76,245 W). Using an established methodological framework, we tested 1:7 classes for linear, quadratic, cubic and natural spline shapes, and modelled associations for obesity-related cancer (ORC) incidence using LCTM class membership.

Results

Different models were selected depending on the data type used. In specific age recall trajectories, only the two heaviest classes were associated with increased risk of ORC. For the decade recall data, the shapes appeared skewed by outliers in the heavier classes but an increase in ORC risk was observed. In the combined models, at older ages the BMI values were more extreme.

Conclusions

Specific age recall models supported the existing literature changes in BMI over time are associated with increased ORC risk. Modelling of decade recall data might yield spurious associations.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08226-4.

Potential Disparities by Sex and Race or Ethnicity in Lung Cancer Screening Eligibility Rates

BACKGROUND

Criteria for low-dose CT scan lung cancer screening vary across guidelines. Knowledge of the eligible pool across demographic groups can enable policy and programmatic decision-making, particularly for disproportionately affected populations.

RESEARCH QUESTION

What are the eligibility rates for low-dose CT scan screening according to sex and race or ethnicity and how do these rates relate to corresponding lung cancer incidence rates?

STUDY DESIGN AND METHODS

This was a cross-sectional study using data from the 2015 National Health Interview Survey adult and cancer control supplement files. In addition to eligibility rates, the ratio of the eligibility rate to the lung cancer incidence rate in a given population group (eligibility to incidence [E-I] ratio) also was determined. Guidelines assessed were: Centers for Medicare and Medicaid Services, National Comprehensive Cancer Network, and US Preventive Services Task Force current or with expansion of age and smoking or quit thresholds. We also assessed a risk model (PLCO_M2012 risk model).

RESULTS

Total numbers eligible based on current guidelines ranged from 8.3 to 13.3 million, representing 8.3% to 13.4% of the US population 50 to 80 years of age, and up to 17.5 million with expanded criteria. Overall eligibility rates on average were about 10 percentage points higher for men than women. For both men and women, and both overall and among ever smokers, non-Hispanic Whites had the highest eligibility rates across all guidelines, followed generally by non-Hispanic Blacks, and then Asians and Hispanics. Among both men and women, non-Hispanic Whites had the highest E-I ratios across all guidelines; non-Hispanic Black men had higher lung cancer incidence, but 30% to 50% lower E-I ratios, than non-Hispanic White men.

INTERPRETATION

Screening eligibility rates vary widely across guidelines, with disparities evident in E-I ratios, including among non-Hispanic Black men, despite higher lung cancer burden. Consideration of smoking duration in risk assessment criteria may address current disparities.

A prospective study of the associations among fine particulate matter, genetic variants, and the risk of colorectal cancer

BACKGROUND

Fine particulate matter (PM_2.5) is suspected to increase the risk of colorectal cancer, but the mechanism remains unknown. We aimed to investigate the association between PM_2.5 exposure, genetic variants and colorectal cancer risk in the Prostate, Lung, Colon and Ovarian (PLCO) Cancer Screening trial.

METHODS

We included a prospective cohort of 139,534 cancer-free individuals from 10 United States research centers with over ten years of follow-up. We used a Cox regression model to assess the association between PM_2.5 exposure and colorectal cancer incidence by calculating the hazard ratio (HR) and 95% confidence interval (CI) with adjustment for potential confounders. The polygenic risk score (PRS) and genome-wide interaction analysis (GWIA) were used to evaluate the multiplicative interaction between PM_2.5 exposure and genetic variants in regard to colorectal cancer risk.

RESULTS

After a median of 10.43 years of follow-up, 1,666 participants had been diagnosed with colorectal cancer. PM_2.5 exposure was significantly associated with an increased risk of colorectal cancer (HR = 1.27; 95% CI = 1.17-1.37 per 5 μg/m³ increase). Five independent susceptibility loci reached statistical significance at P < 1.22 × 10^-8 in the interaction analysis. Furthermore, a joint interaction was observed between PM_2.5 exposure and the PRS based on these five loci with colorectal cancer risk (P = 3.11 × 10^-29). The Gene Ontology analysis showed that the vascular endothelial growth factor (VEGF) receptor signaling pathway was involved in the biological process of colorectal cancer.

CONCLUSIONS

Our large-scale analysis has shown for the first time that long-term PM_2.5 exposure potential increases colorectal cancer risk, which might be modified by genetic variants.

Immune factors preceding diagnosis of glioma: a Prostate Lung Colorectal Ovarian Cancer Screening Trial nested case-control study

Background

Epidemiological studies of adult glioma have identified genetic and environmental risk factors, but much remains unclear. The aim of the current study was to evaluate anthropometric, disease-related, and prediagnostic immune-related factors for relationship with glioma risk.

Methods

We conducted a nested case–control study among the intervention arm of the Prostate, Lung, Colorectal, and Ovarian Cancer (PLCO) Screening Trial. One hundred and twenty-four glioma cases were identified and each matched to four controls. Baseline characteristics were collected at enrollment and were evaluated for association with glioma status. Serum specimens were collected at yearly intervals and were analyzed for immune-related factors including TGF-β1, TNF-α, total IgE, and allergen-specific IgE. Immune factors were evaluated at baseline in a multivariate conditional logistic regression model, along with one additional model that incorporated the latest available measurement.

Results

A family history of glioma among first-degree relatives was associated with increased glioma risk (OR = 4.41, P = .002). In multivariate modeling of immune factors at baseline, increased respiratory allergen-specific IgE was inversely associated with glioma risk (OR for allergen-specific IgE > 0.35 PAU/L: 0.59, P = .03). A logistic regression model that incorporated the latest available measurements found a similar association for allergen-specific IgE (P = .005) and showed that elevated TGF-β1 was associated with increased glioma risk (P-value for trend <.0001).

Conclusion

The results from this prospective prediagnostic study suggest that several immune-related factors are associated with glioma risk. The association observed for TGF-β1 when sampling closer to the time of diagnosis may reflect the nascent brain tumor’s feedback on immune function.

Simultaneous Measurement of 92 Serum Protein Biomarkers for the Development of a Multiprotein Classifier for Ovarian Cancer Detection

The best known ovarian cancer biomarker, CA125, is neither adequately sensitive nor specific for screening the general population. By using a combination of proteins for screening, it may be possible to increase the sensitivity and specificity over CA125 alone. In this study, we used Proseek Multiplex Oncology II plates to simultaneously measure the expression of 92 cancer-related proteins in serum using proximity extension assays. This technology combines the sensitivity of the PCR with the specificity of antibody-based detection methods, allowing multiplex biomarker detection and high-throughput quantification. We analyzed 1 μL of sera from each of 61 women with ovarian cancer and compared the values obtained with those from 88 age-matched healthy women. Principle component analysis and unsupervised hierarchical clustering separated the ovarian cancer patients from the healthy, with minimal misclassification. Data from the Proseek plates for CA125 levels exhibited a strong correlation with clinical values for CA125. We identified 52 proteins that differed significantly (P < 0.006) between ovarian cancer and healthy samples, several of which are novel serum biomarkers for ovarian cancer. In total, 40 proteins had an estimated area under the ROC curve of 0.70 or greater, suggesting their potential to serve as biomarkers for ovarian cancer. CA125 alone achieved a sensitivity of 93.4% at a specificity of 98%. By adding the Oncology II values for five proteins to CA125 in a multiprotein classifier, we increased the assay sensitivity to 98.4% at a specificity of 98%, thereby improving the sensitivity and specificity of CA125 alone.

A multiplex platform for the identification of ovarian cancer biomarkers

Background

Currently, there are no FDA approved screening tools for detecting early stage ovarian cancer in the general population. Development of a biomarker-based assay for early detection would significantly improve the survival of ovarian cancer patients.

Methods

We used a multiplex approach to identify protein biomarkers for detecting early stage ovarian cancer. This new technology (Proseek^® Multiplex Oncology Plates) can simultaneously measure the expression of 92 proteins in serum based on a proximity extension assay. We analyzed serum samples from 81 women representing healthy, benign pathology, early, and advanced stage serous ovarian cancer patients.

Results

Principle component analysis and unsupervised hierarchical clustering separated patients into cancer versus non-cancer subgroups. Data from the Proseek^® plate for CA125 levels exhibited a strong correlation with current clinical assays for CA125 (correlation coefficient of 0.89, 95% CI 0.83, 0.93). CA125 and HE4 were present at very low levels in healthy controls and benign cases, while higher levels were found in early stage cases, with highest levels found in the advanced stage cases. Overall, significant trends were observed for 38 of the 92 proteins (p < 0.001), many of which are novel candidate serum biomarkers for ovarian cancer. The area under the ROC curve (AUC) for CA125 was 0.98 and the AUC for HE4 was 0.85 when comparing early stage ovarian cancer versus healthy controls. In total, 23 proteins had an estimated AUC of 0.7 or greater. Using a naïve Bayes classifier that combined 12 proteins, we improved the sensitivity corresponding to 95% specificity from 93 to 95% when compared to CA125 alone. Although small, a 2% increase would have a significant effect on the number of women correctly identified when screening a large population.

Conclusions

These data demonstrate that the Proseek^® technology can replicate the results established by conventional clinical assays for known biomarkers, identify new candidate biomarkers, and improve the sensitivity and specificity of CA125 alone. Additional studies using a larger cohort of patients will allow for validation of these biomarkers and lead to the development of a screening tool for detecting early stage ovarian cancer in the general population.

Electronic supplementary material

The online version of this article (doi:10.1186/s12014-017-9169-6) contains supplementary material, which is available to authorized users.

Serum 25-hydroxyvitamin D, vitamin D binding protein, and prostate cancer risk in black men

BACKGROUND

Few studies have prospectively examined the relationship between vitamin D status and prostate cancer risk in black men, a group at high risk for both low vitamin D status and prostate cancer.

METHODS

Among black men in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial, we identified 226 prostate cancer cases and 452 controls matched on age at randomization (±5 years), date of blood draw (±30 days), calendar year of cohort entry, and time since baseline prostate cancer screening (±1 year). Conditional logistic regression was used to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) for the associations between serum 25-hydroxyvitamin D [25(OH)D], vitamin D binding protein (DBP), the 25(OH)D:DBP molar ratio, and prostate cancer risk.

RESULTS

Serum 25(OH)D was not associated with overall prostate cancer (Q4 vs Q1: OR, 0.73; 95% CI, 0.40-1.33; P for trend = .25), although there were apparent inverse associations for nonaggressive disease (global P = .03, clinical stage I/II, and Gleason score <7) and among men ≥62 years old (P for interaction = .04) that were restricted to Q3. Interestingly, serum DBP was significantly inversely associated with prostate cancer risk (Q4 vs Q1: OR, 0.45; 95% CI, 0.20-1.00; P for trend = .03), whereas the 25(OH)D:DBP molar ratio was not. Results were similar when we mutually adjusted for 25(OH)D and DBP, and we found no evidence of interaction between the two.

CONCLUSION

Our study suggests higher (versus lower) circulating DBP may be independently associated with a decreased prostate cancer risk in black men independent of 25(OH)D status. Cancer 2017;123:2698-704. © 2017 American Cancer Society.

Extended mortality results for prostate cancer screening in the PLCO trial with median follow-up of 15 years

BACKGROUND

Two large-scale prostate cancer screening trials using prostate-specific antigen (PSA) have given conflicting results in terms of the efficacy of such screening. One of those trials, the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial, previously reported outcomes with 13 years of follow-up. This study presents updated findings from the PLCO trial.

METHODS

The PLCO trial randomized subjects from 1993 to 2001 to an intervention or control arm. Intervention-arm men received annual PSA tests for 6 years and digital rectal examinations for 4 years. This study used a linkage with the National Death Index to extend mortality follow-up to a maximum of 19 years after randomization.

RESULTS

Men were randomized to the intervention arm (n = 38,340) or the control arm (n = 38,343). The median follow-up time was 14.8 years (25th/75th, 12.7/16.5 years) in the intervention arm and 14.7 years (25th/75th, 12.6/16.4 years) in the control arm. There were 255 deaths from prostate cancer in the intervention arm and 244 deaths from prostate cancer in the control arm; this meant a rate ratio (RR) of 1.04 (95% confidence interval [CI], 0.87-1.24). The RR for all-cause mortality was 0.977 (95% CI, 0.950-1.004). It was estimated that 86% of the men in the control arm and 99% of the men in the intervention arm received any PSA testing during the trial, and the estimated yearly screening-phase PSA testing rates were 46% and 84%, respectively.

CONCLUSIONS

Extended follow-up of the PLCO trial over a median of 15 years continues to indicate no reduction in prostate cancer mortality for the intervention arm versus the control arm. Because of the high rate of control-arm PSA testing, this finding can be viewed as showing no benefit of organized screening versus opportunistic screening. Cancer 2017;123:592-599. © 2016 American Cancer Society.