The role of extreme phenotype selection studies in the identification of clinically relevant genotypes in cancer research

Whole exome sequencing and machine learning germline analysis of individuals presenting with extreme phenotypes of high and low risk of developing tobacco-associated lung adenocarcinoma

BACKGROUND

Tobacco is the main risk factor for developing lung cancer. Yet, while some heavy smokers develop lung cancer at a young age, other heavy smokers never develop it, even at an advanced age, suggesting a remarkable variability in the individual susceptibility to the carcinogenic effects of tobacco. We characterized the germline profile of subjects presenting these extreme phenotypes with Whole Exome Sequencing (WES) and Machine Learning (ML).

METHODS

We sequenced germline DNA from heavy smokers who either developed lung adenocarcinoma at an early age (extreme cases) or who did not develop lung cancer at an advanced age (extreme controls), selected from databases including over 6600 subjects. We selected individual coding genetic variants and variant-rich genes showing a significantly different distribution between extreme cases and controls. We validated the results from our discovery cohort, in which we analysed by WES extreme cases and controls presenting similar phenotypes. We developed ML models using both cohorts.

FINDINGS

Mean age for extreme cases and controls was 50.7 and 79.1 years respectively, and mean tobacco consumption was 34.6 and 62.3 pack-years. We validated 16 individual variants and 33 variant-rich genes. The gene harbouring the most validated variants was HLA-A in extreme controls (4 variants in the discovery cohort, p = 3.46E-07; and 4 in the validation cohort, p = 1.67E-06). We trained ML models using as input the 16 individual variants in the discovery cohort and tested them on the validation cohort, obtaining an accuracy of 76.5% and an AUC-ROC of 83.6%. Functions of validated genes included candidate oncogenes, tumour-suppressors, DNA repair, HLA-mediated antigen presentation and regulation of proliferation, apoptosis, inflammation and immune response.

INTERPRETATION

Individuals presenting extreme phenotypes of high and low risk of developing tobacco-associated lung adenocarcinoma show different germline profiles. Our strategy may allow the identification of high-risk subjects and the development of new therapeutic approaches.

FUNDING

See a detailed list of funding bodies in the Acknowledgements section at the end of the manuscript.

Genomic architecture of phenotypic extremes in a wild cervid

Identifying the genes underlying fitness-related traits such as body size and male ornamentation can provide tools for conservation and management and are often subject to various selective pressures. Here we performed high-depth whole genome re-sequencing of pools of individuals representing the phenotypic extremes for antler and body size in white-tailed deer (Odocoileus virginianus). Samples were selected from a tissue repository containing phenotypic data for 4,466 male white-tailed deer from Anticosti Island, Quebec, with four pools representing the extreme phenotypes for antler and body size after controlling for age. Our results revealed a largely homogenous population but detected highly divergent windows between pools for both traits, with the mean allele frequency difference of 14% for and 13% for antler and body SNPs in outlier windows, respectively. Genes in outlier antler windows were enriched for pathways associated with cell death and protein metabolism and some of the most differentiated windows included genes associated with oncogenic pathways and reproduction, processes consistent with antler evolution and growth. Genes associated with body size were more nuanced, suggestive of a highly complex trait. Overall, this study revealed the complex genomic make-up of both antler morphology and body size in free-ranging white-tailed deer and identified target loci for additional analyses.

Burden of rare variants in synaptic genes in patients with severe tinnitus: An exome based extreme phenotype study

BACKGROUND

tinnitus is a heterogeneous condition associated with audiological and/or mental disorders. Chronic, severe tinnitus is reported in 1% of the population and it shows a relevant heritability, according to twins, adoptees and familial aggregation studies. The genetic contribution to severe tinnitus is unknown since large genomic studies include individuals with self-reported tinnitus and large heterogeneity in the phenotype. The aim of this study was to identify genes for severe tinnitus in patients with extreme phenotype.

METHODS

for this extreme phenotype study, we used three different cohorts with European ancestry (Spanish with Meniere disease (MD), Swedes tinnitus and European generalized epilepsy). In addition, four independent control datasets were also used for comparisons. Whole-exome sequencing was performed for the MD and epilepsy cohorts and whole-genome sequencing was carried out in Swedes with tinnitus.

FINDINGS

we found an enrichment of rare missense variants in 24 synaptic genes in a Spanish cohort, the most significant being PRUNE2, AKAP9, SORBS1, ITGAX, ANK2, KIF20B and TSC2 (p < 2E-04), when they were compared with reference datasets. This burden was replicated for ANK2 gene in a Swedish cohort with 97 tinnitus individuals, and in a subset of 34 Swedish patients with severe tinnitus for ANK2, AKAP9 and TSC2 genes (p < 2E-02). However, these associations were not significant in a third cohort of 701 generalized epilepsy individuals without tinnitus. Gene ontology (GO) and gene-set enrichment analyses revealed several pathways and biological processes involved in severe tinnitus, including membrane trafficking and cytoskeletal protein binding in neurons.

INTERPRETATION

a burden of rare variants in ANK2, AKAP9 and TSC2 is associated with severe tinnitus. ANK2, encodes a cytoskeleton scaffolding protein that coordinates the assembly of several proteins, drives axonal branching and influences connectivity in neurons.

Whole exome sequencing characterization of individuals presenting extreme phenotypes of high and low risk of developing tobacco-induced lung adenocarcinoma

Background

Tobacco is the main risk factor for developing lung cancer. Yet, some heavy smokers do not develop lung cancer at advanced ages while others develop it at young ages. Here, we assess for the first time the genetic background of these clinically relevant extreme phenotypes using whole exome sequencing (WES).

Methods

We performed WES of germline DNA from heavy smokers who either developed lung adenocarcinoma at an early age (extreme cases, n=50) or did not present lung adenocarcinoma or other tumors at an advanced age (extreme controls, n=50). We selected non-synonymous variants located in exonic regions and consensus splice sites of the genes that showed significantly different allelic frequencies between both cohorts. We validated our results in all the additional extreme cases (i.e., heavy smokers who developed lung adenocarcinoma at an early age) available from The Cancer Genome Atlas (TCGA).

Results

The mean age for the extreme cases and controls was respectively 49.7 and 77.5 years. Mean tobacco consumption was 43.6 and 56.8 pack-years. We identified 619 significantly different variants between both cohorts, and we validated 108 of these in extreme cases selected from TCGA. Nine validated variants, located in relevant cancer related genes, such as PARP4, HLA-A or NQO1, among others, achieved statistical significance in the False Discovery Rate test. The most significant validated variant (P=4.48×10⁻⁵) was located in the tumor-suppressor gene ALPK2.

Conclusions

We describe genetic variants associated with extreme phenotypes of high and low risk for the development of tobacco-induced lung adenocarcinoma. Our results and our strategy may help to identify high-risk subjects and to develop new therapeutic approaches.

Variants in immune-related genes and genital HPV 16 persistence in men

OBJECTIVES

While most human papillomavirus (HPV) infection clears on its own, persistent HPV infection can cause genital warts and anal, penile and oropharyngeal cancers in men. We conducted genetic analysis in a sub-cohort of the HPV infection in men (HIM) study to test the hypothesis that differences in host genes influence HPV persistence in men.

METHODS

Baseline and longitudinal genital HPV status at the genitals was measured every 6-months using the Linear Array assay amplified HPV L1 gene fragment using the PGMY09/11 L1 consensus primer system. DNA was extracted from peripheral blood and single nucleotide polymorphisms (SNPs) in the customized genome-wide genotyping array, the "TxArray," were examined using logistic regression in a case-control study design to assess the association with HPV16 persistence/clearance.

RESULTS

Of the total of 737,742 autosomal SNPs in the array, 605,885 passed basic quality control and were examined between 40 men (cases) with > 18 months persistent genital HPV 16 infection vs. 151 controls who were HPV 16-positive, but whose infections cleared in < 18 months. The logistic regression analysis from this case-control study showed variants in several gene regions associated with genital HPV 16 persistence, with the strongest association detected with SNPs on chromosomes 20 (p < 5.72 × 10^-6) and 15 (p < 5.89 × 10^-6), after adjusting for age, smoking status, number of sex partners and four principal components (ancestral background).

CONCLUSIONS

Our results provide a preliminary basis for understanding the biological mechanism of oncogenic HPV 16 pathogenesis at the genitals in men. Some of the genes flanking the top hit SNPs are consistent with previous findings in both HPV related and non-related cancers but further genetic studies in larger cohorts are warranted to confirm these and identify novel major susceptibility genes involved in the pathogenesis of genital HPV persistence in men.

Genomic characterization of individuals presenting extreme phenotypes of high and low risk to develop tobacco-induced lung cancer

Single nucleotide polymorphisms (SNPs) may modulate individual susceptibility to carcinogens. We designed a genome-wide association study to characterize individuals presenting extreme phenotypes of high and low risk to develop tobacco-induced non-small cell lung cancer (NSCLC), and we validated our results. We hypothesized that this strategy would enrich the frequencies of the alleles that contribute to the observed traits. We genotyped 2.37 million SNPs in 95 extreme phenotype individuals, that is: heavy smokers that either developed NSCLC at an early age (extreme cases); or did not present NSCLC at an advanced age (extreme controls), selected from a discovery set (n = 3631). We validated significant SNPs in 133 additional subjects with extreme phenotypes selected from databases including >39,000 individuals. Two SNPs were validated: rs12660420 (pcombined  = 5.66 × 10-5 ; ORcombined  = 2.80), mapping to a noncoding transcript exon of PDE10A; and rs6835978 (pcombined  = 1.02 × 10-4 ; ORcombined  = 2.57), an intronic variant in ATP10D. We assessed the relevance of both proteins in early-stage NSCLC. PDE10A and ATP10DmRNA expressions correlated with survival in 821 stage I-II NSCLC patients (p = 0.01 and p < 0.0001). PDE10A protein expression correlated with survival in 149 patients with stage I-II NSCLC (p = 0.002). In conclusion, we validated two variants associated with extreme phenotypes of high and low risk of developing tobacco-induced NSCLC. Our findings may allow to identify individuals presenting high and low risk to develop tobacco-induced NSCLC and to characterize molecular mechanisms of carcinogenesis and resistance to develop NSCLC.

Selecting cases and controls for DNA sequencing studies using family histories of disease

Recent improvements in sequencing technology have enabled the investigation of so-called missing heritability, and a large number of affected subjects have been sequenced in order to detect significant associations between human diseases and rare variants. However, the cost of genome sequencing is still high, and a statistically powerful strategy for selecting informative subjects would be useful. Therefore, in this report, we propose a new statistical method for selecting cases and controls for sequencing studies based on family history. We assume that disease status is determined by unobserved liability scores. Our method consists of two steps: first, the conditional means of liability are estimated with the liability threshold model given the individual's disease status and those of their relatives. Second, the informative subjects are selected with the estimated conditional means. Our simulation studies showed that statistical power is substantially affected by the subject selection strategy chosen, and power is maximized when affected (unaffected) subjects with high (low) risks are selected as cases (controls). The proposed method was successfully applied to genome-wide association studies for type 2 diabetes, and our analysis results reveal the practical value of the proposed methods. Copyright © 2017 John Wiley & Sons, Ltd.

Knowledge of Prostate Cancer and Screening Among Young Multiethnic Black Men

The purpose of this study was to assess the knowledge of prostate cancer and screening and its associated factors in young Black men aged 18 to 40 years. This was a cross-sectional study conducted in a convenience sample of 267 young Black men in Austin, Texas. Knowledge about prostate cancer and screening was operationalized through 14 items, including 12 items from the Knowledge about Prostate Cancer Screening Questionnaire (PC knowledge), and two items assessing dietary knowledge and prostate cancer screening controversy. PC knowledge scores were regressed on age, cues to action, health screening experience, and demographic/personal factors. Most participants were African American men of American origin (65.3%) and were college freshmen (18.9%). PC knowledge scores were low, with mean correct responses of 28.5%, mean knowledge score of 5.25 ± 3.81 (possible score range of 0 to 14, with higher scores indicating higher PC knowledge) and a median score of 5.00. On average, 47% of the respondents replied “Don’t Know” to the questions. Overall, PC knowledge scores were low among these young Black men, especially in domains related to risk factors, screening age guidelines, limitations, and diet. It is thus important that these men be educated more on these important domains of prostate cancer and screening so that the decision to screen or not will be an informed one. Health screening experience, residence area, major field of study, and academic classification were significant predictors of knowledge.

Strategies to design clinical studies to identify predictive biomarkers in cancer research

The discovery of reliable biomarkers to predict efficacy and toxicity of anticancer drugs remains one of the key challenges in cancer research. Despite its relevance, no efficient study designs to identify promising candidate biomarkers have been established. This has led to the proliferation of a myriad of exploratory studies using dissimilar strategies, most of which fail to identify any promising targets and are seldom validated. The lack of a proper methodology also determines that many anti-cancer drugs are developed below their potential, due to failure to identify predictive biomarkers. While some drugs will be systematically administered to many patients who will not benefit from them, leading to unnecessary toxicities and costs, others will never reach registration due to our inability to identify the specific patient population in which they are active. Despite these drawbacks, a limited number of outstanding predictive biomarkers have been successfully identified and validated, and have changed the standard practice of oncology. In this manuscript, a multidisciplinary panel reviews how those key biomarkers were identified and, based on those experiences, proposes a methodological framework-the DESIGN guidelines-to standardize the clinical design of biomarker identification studies and to develop future research in this pivotal field.

MiR-99b-5p expression and response to tyrosine kinase inhibitor treatment in clear cell renal cell carcinoma patients

A number of treatments targeting VEGF or mTOR pathways have been approved for metastatic clear cell Renal Cell Carcinoma (ccRCC), but the majority of patients show disease progression after first line therapy with a very low rate of complete or long-term responders. It has been shown that miRs may play a role in prediction of treatment response in various cancer types. The aim of our study was to identify a miR signature predictive for RCC patients' response to antiangiogenic tyrosine kinase inhibitor (TKI) treatment in the first line therapy. Sequencing of 40 paired normal/tumor formalin fixed and paraffin embedded ccRCC tissues revealed separate clustering via unsupervised dendrograms. With supervised analysis, the strongest differential expression was obtained with miR-99b-5p, which was significantly lower in patients with short progression free survival (<8 months) and TKI non-responders (progressive disease patients according to RECIST) (p<0.0001, each). Validation using RTqPCR and a second patient cohort compiled from three different hospitals (n=65) showed higher expression of miR-99b-5p in complete responders, but this trend did not reach statistical significance. It is concluded that low miR-99b-5p expression analyzed with sequencing methodology may correlate with tumor progression in TKI-treated ccRCC patients.

Determinants of Prostate Cancer Screening Intentions of Young Black Men Aged 18 to 40 Years

INTRODUCTION

Black men are more likely to be diagnosed with prostate cancer, with higher stage and higher grade at presentation. Evidence suggests that for education in health promotion behaviors (such as screenings) in early adult years, young Black men can be better equipped to make informed decisions in later years.

OBJECTIVE

Using the theory of reasoned action (TRA), we assessed the intention of young Black men to screen for prostate cancer when it is recommended and determined its correlates.

METHODS

This was a cross-sectional study of 267 Black men aged 18 to 40 years. A 47-item questionnaire collected information on demographics/personal factors, attitudes toward prostate cancer screening, social influence, comfortability with prostate examinations, cues to action, health screening experiences, knowledge of prostate cancer and screening, and intention. Descriptive statistics were calculated for all variables and hierarchical logistic regression was employed to determine significant predictors of prostate cancer screening intentions.

RESULTS

The regression model accounted for 46% of the variance in intention (p < 0.01), with excellent perception of health, having private or public health insurance, longer regular source of care, positive attitude, positive social influence, positive cues to action, and higher knowledge levels being significant predictors of intentions.

CONCLUSION

This study provides support for the use of TRA in predicting prostate cancer screening intentions among young Black men when it is recommended by a physician. Findings may inform the development of empirical-based interventions to educate and inform at-risk young Black men about the pros and cons of prostate cancer screening so that they can make informed decision on screening when recommended later in life.

Whole-genome resequencing of extreme phenotypes in collared flycatchers highlights the difficulty of detecting quantitative trait loci in natural populations

Dissecting the genetic basis of phenotypic variation in natural populations is a long-standing goal in evolutionary biology. One open question is whether quantitative traits are determined only by large numbers of genes with small effects, or whether variation also exists in large-effect loci. We conducted genomewide association analyses of forehead patch size (a sexually selected trait) on 81 whole-genome-resequenced male collared flycatchers with extreme phenotypes, and on 415 males sampled independent of patch size and genotyped with a 50K SNP chip. No SNPs were genomewide statistically significantly associated with patch size. Simulation-based power analyses suggest that the power to detect large-effect loci responsible for 10% of phenotypic variance was <0.5 in the genome resequencing analysis, and <0.1 in the SNP chip analysis. Reducing the recombination by two-thirds relative to collared flycatchers modestly increased power. Tripling sample size increased power to >0.8 for resequencing of extreme phenotypes (N = 243), but power remained <0.2 for the 50K SNP chip analysis (N = 1245). At least 1 million SNPs were necessary to achieve power >0.8 when analysing 415 randomly sampled phenotypes. However, power of the 50K SNP chip to detect large-effect loci was nearly 0.8 in simulations with a small effective population size of 1500. These results suggest that reliably detecting large-effect trait loci in large natural populations will often require thousands of individuals and near complete sampling of the genome. Encouragingly, far fewer individuals and loci will often be sufficient to reliably detect large-effect loci in small populations with widespread strong linkage disequilibrium.

Power in the phenotypic extremes: a simulation study of power in discovery and replication of rare variants

Next-generation sequencing technologies are making it possible to study the role of rare variants in human disease. Many studies balance statistical power with cost-effectiveness by (a) sampling from phenotypic extremes and (b) utilizing a two-stage design. Two-stage designs include a broad-based discovery phase and selection of a subset of potential causal genes/variants to be further examined in independent samples. We evaluate three parameters: first, the gain in statistical power due to extreme sampling to discover causal variants; second, the informativeness of initial (Phase I) association statistics to select genes/variants for follow-up; third, the impact of extreme and random sampling in (Phase 2) replication. We present a quantitative method to select individuals from the phenotypic extremes of a binary trait, and simulate disease association studies under a variety of sample sizes and sampling schemes. First, we find that while studies sampling from extremes have excellent power to discover rare variants, they have limited power to associate them to phenotype—suggesting high false-negative rates for upcoming studies. Second, consistent with previous studies, we find that the effect sizes estimated in these studies are expected to be systematically larger compared with the overall population effect size; in a well-cited lipids study, we estimate the reported effect to be twofold larger. Third, replication studies require large samples from the general population to have sufficient power; extreme sampling could reduce the required sample size as much as fourfold. Our observations offer practical guidance for the design and interpretation of studies that utilize extreme sampling.

Identification of tissue microRNAs predictive of sunitinib activity in patients with metastatic renal cell carcinoma

Purpose

To identify tissue microRNAs predictive of sunitinib activity in patients with metastatic renal-cell-carcinoma (MRCC) and to evaluate in vitro their mechanism of action in sunitinib resistance.

Methods

We screened 673 microRNAs using TaqMan Low-density-Arrays (TLDAs) in tumors from MRCC patients with extreme phenotypes of marked efficacy and resistance to sunitinib, selected from an identification cohort (n = 41). The most relevant differentially expressed microRNAs were selected using bioinformatics-based target prediction analysis and quantified by qRT-PCR in tumors from patients presenting similar phenotypes selected from an independent cohort (n = 101). In vitro experiments were conducted to study the role of miR-942 in sunitinib resistance.

Results

TLDAs identified 64 microRNAs differentially expressed in the identification cohort. Seven candidates were quantified by qRT-PCR in the independent series. MiR-942 was the most accurate predictor of sunitinib efficacy (p = 0.0074). High expression of miR-942, miR-628-5p, miR-133a, and miR-484 was significantly associated with decreased time to progression and overall survival. These microRNAs were also overexpressed in the sunitinib resistant cell line Caki-2 in comparison with the sensitive cell line. MiR-942 overexpression in Caki-2 up-regulates MMP-9 and VEGF secretion which, in turn, promote HBMEC endothelial migration and sunitinib resistance.

Conclusions

We identified differentially expressed microRNAs in MRCC patients presenting marked sensitivity or resistance to sunitinib. MiR-942 was the best predictor of efficacy. We describe a novel paracrine mechanism through which high miR-942 levels in MRCC cells up-regulates MMP-9 and VEGF secretion to enhance endothelial migration and sunitinib resistance. Our results support further validation of these miRNA in clinical confirmatory studies.

The tissue microlocalisation and cellular expression of CD163, VEGF, HLA-DR, iNOS, and MRP 8/14 is correlated to clinical outcome in NSCLC

Background

We have previously investigated the microlocalisation of M1 and M2 macrophages in NSCLC. This study investigated the non-macrophage (NM) expression of proteins associated with M1 and M2 macrophages in NSCLC.

Methods

Using immunohistochemistry, CD68⁺ macrophages and proteins associated with either a cytotoxic M1 phenotype (HLA-DR, iNOS, and MRP 8/14), or a non-cytotoxic M2 phenotype (CD163 and VEGF) were identified. NM expression of the markers was analysed in the islets and stroma of surgically resected tumours from 20 patients with extended survival (ES) (median 92.7 months) and 20 patients with poor survival (PS) (median 7.7 months).

Results

The NM expression of NM-HLA-DR (p<0.001), NM-iNOS (p = 0.02) and NM-MRP 8/14 (p = 0.02) was increased in ES compared to PS patients in the tumour islets. The tumour islet expression of NM-VEGF, was decreased in ES compared to PS patients (p<0.001). There was more NM-CD163 expression (p = 0.04) but less NM-iNOS (p = 0.002) and MRP 8/14 (p = 0.01) expression in the stroma of ES patients compared with PS patients. The 5-year survival for patients with above and below median NM expression of the markers in the islets was 74.9% versus 4.7% (NM-HLA-DR p<0.001), 65.0% versus 14.6% (NM-iNOS p = 0.003), and 54.3% versus 22.2% (NM-MRP 8/14 p = 0.04), as opposed to 34.1% versus 44.4% (NM-CD163 p = 0.41) and 19.4% versus 59.0% (NM-VEGF p = 0.001).

Conclusions

Cell proteins associated with M1 and M2 macrophages are also expressed by other cell types in the tumour islets and stroma of patients with NSCLC. Their tissue and cellular microlocalisation is associated with important differences in clinical outcome.

Selection of extreme phenotypes: the role of clinical observation in translational research

Systematic collection of phenotypes and their correlation with molecular data has been proposed as a useful method to advance in the study of disease. Although some databases for animal species are being developed, progress in humans is slow, probably due to the multifactorial origin of many human diseases and to the intricacy of accurately classifying phenotypes, among other factors. An alternative approach has been to identify and to study individuals or families with very characteristic, clinically relevant phenotypes. This strategy has shown increased efficiency to identify the molecular features underlying such phenotypes. While on most occasions the subjects selected for these studies presented harmful phenotypes, a few studies have been performed in individuals with very favourable phenotypes. The consistent results achieved suggest that it seems logical to further develop this strategy as a methodology to study human disease, including cancer. The identification and the study with high-throughput techniques of individuals showing a markedly decreased risk of developing cancer or of cancer patients presenting either an unusually favourable prognosis or striking responses following a specific treatment, might be promising ways to maximize the yield of this approach and to reveal the molecular causes that explain those phenotypes and thus highlight useful therapeutic targets. This manuscript reviews the current status of selection of extreme phenotypes in cancer research and provides directions for future development of this methodology.

Identification of TNF-alpha and MMP-9 as potential baseline predictive serum markers of sunitinib activity in patients with renal cell carcinoma using a human cytokine array

Background:

Several drugs are available to treat metastatic renal-cell carcinoma (MRCC), and predictive markers to identify the most adequate treatment for each patient are needed. Our objective was to identify potential predictive markers of sunitinib activity in MRCC.

Methods:

We collected sequential serum samples from 31 patients treated with sunitinib. Sera of six patients with extreme phenotypes of either marked responses or clear progressions were analysed with a Human Cytokine Array which evaluates 174 cytokines before and after treatment. Variations in cytokine signal intensity were compared between both groups and the most relevant cytokines were assessed by ELISA in all the patients.

Results:

Twenty-seven of the 174 cytokines varied significantly between both groups. Five of them (TNF-α, MMP-9, ICAM-1, BDNF and SDF-1) were assessed by ELISA in 21 evaluable patients. TNF-α and MMP-9 baseline levels were significantly increased in non-responders and significantly associated with reduced overall survival and time-to-progression, respectively. The area under the ROC curves for TNF-α and MMP-9 as predictive markers of sunitinib activity were 0.83 and 0.77.

Conclusion:

Baseline levels of TNF-α and MMP-9 warrant further study as predictive markers of sunitinib activity in MRCC. Selection of patients with extreme phenotypes seems a valid method to identify potential predictive factors of response.

Treatment and survival outcomes in young men diagnosed with prostate cancer: a Population-based Cohort Study

BACKGROUND

Outcomes of treatment for young men compared with older men with prostate cancer are poorly defined outside of limited institutional series. In this study, the authors examined the association between age at diagnosis and grade, stage, treatment, and survival outcomes in men who were diagnosed during the era of prostate-specific antigen testing.

METHODS

The National Cancer Institute's Surveillance, Epidemiology, and End Results database was used to identify men who were diagnosed with prostate cancer between 1988 and 2003. Men ages 35 years to 74 years were stratified by age at diagnosis to examine differences in tumor characteristics, treatment, and survival within each age group.

RESULTS

In total, 318,774 men ages 35 years to 74 years were identified who had been diagnosed with adenocarcinoma of the prostate between 1988 and 2003. The proportion of men aged < or =55 years at diagnosis increased over the study period from 2.3% between the years 1988 and 1991 to 9% between the years 2000 and 2003, and the median age at diagnosis decreased from 72 years in 1988 to 68 years in 2003. Younger men were diagnosed less frequently with organ-confined tumors (P < .001) but were less likely to be diagnosed with high-grade cancer (P < .001). Older men were more likely to receive no local therapy or external beam radiation than young men (P < .001 for trend). Among men who had tumors with a Gleason score between 5 and 7, overall survival was worse with advancing age. However, among all age groups with high grade and stage, the youngest men (ages 35-44 years) were at the highest risk of all-cause and cancer-specific death.

CONCLUSIONS

Age at diagnosis among men with prostate cancer continued to decline. Younger men were more likely to undergo prostatectomy, have lower grade cancer, and, as a group, to have better overall and equivalent cancer-specific survival at 10 years compared with older men. Among men with high grade and locally advanced prostate cancer, the youngest men had a particularly poor prognosis compared with older men.