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Background Personalized genomic classifiers have transformed the management of prostate cancer (PCa) by identifying the most aggressive subsets of PCa. Nevertheless, the performance of genomic classifiers to risk classify African American men is thus far lacking in a prospective setting. Methods This is a prospective study of the Decipher genomic classifier for National Comprehensive Cancer Network low- and intermediate-risk PCa. Study-eligible non–African American men were matched to African American men. Diagnostic biopsy specimens were processed to estimate Decipher scores. Samples accrued in NCT02723734, a prospective study, were interrogated to determine the genomic risk of reclassification (GrR) between conventional clinical risk classifiers and the Decipher score. Results The final analysis included a clinically balanced cohort of 226 patients with complete genomic information (113 African American men and 113 non–African American men). A higher proportion of African American men with National Comprehensive Cancer Network–classified low-risk (18.2%) and favorable intermediate-risk (37.8%) PCa had a higher Decipher score than non–African American men. Self-identified African American men were twice more likely than non–African American men to experience GrR (relative risk [RR] = 2.23, 95% confidence interval [CI] = 1.02 to 4.90; P = .04). In an ancestry-determined race model, we consistently validated a higher risk of reclassification in African American men (RR = 5.26, 95% CI = 1.66 to 16.63; P = .004). Race-stratified analysis of GrR vs non-GrR tumors also revealed molecular differences in these tumor subtypes. Conclusions Integration of genomic classifiers with clinically based risk classification can help identify the subset of African American men with localized PCa who harbor high genomic risk of early metastatic disease. It is vital to identify and appropriately risk stratify the subset of African American men with aggressive disease who may benefit from more targeted interventions.

Risk factors for meningioma include female gender, African American race, high body mass index (BMI), and exposure to ionizing radiation. Although genome-wide association studies (GWAS) have identified two nuclear genome risk loci for meningioma (rs12770228 and rs2686876), the relation between mitochondrial DNA (mtDNA) sequence variants and meningioma is unknown. We examined the association of 42 common germline mtDNA variants (minor allele frequency ≥ 5%), haplogroups, and genes with meningioma in 1080 controls and 478 meningioma cases from a case–control study conducted at medical centers in the southeastern United States. Associations were examined separately for meningioma overall and by WHO grade (n = 409 grade I and n = 69 grade II/III). Overall, meningioma was significantly associated with being female (OR 2.85; 95% CI 2.21–3.69), self-reported African American race (OR 2.38, 95% CI 1.41–3.99), and being overweight (OR 1.48; 95% CI 1.11–1.97) or obese (OR 1.70; 95% CI 1.25–2.31). The variant m.16362T > C (rs62581341) in the mitochondrial control region was positively associated with grade II/III meningiomas (OR 2.33; 95% CI 1.14–4.77), but not grade I tumors (OR 0.99; 95% CI 0.64–1.53). Haplogroup L, a marker for African ancestry, was associated with meningioma overall (OR 2.92; 95% CI 1.01–8.44). However, after stratifying by self-reported race, this association was only apparent among the few self-reported Caucasians with this haplogroup (OR 6.35; 95% CI 1.56–25.9). No other mtDNA variant, haplogroup, or gene was associated with meningioma. Common mtDNA variants and major mtDNA haplogroups do not appear to have associations with the odds of developing meningioma.

Summary Multiplex immunofluorescence (mIF) staining combined with quantitative digital image analysis is a novel and increasingly used technique that allows for the characterization of the tumor immune microenvironment (TIME). Generally, mIF data is used to examine the abundance of immune cells in the TIME; however, this does not capture spatial patterns of immune cells throughout the TIME, a metric increasingly recognized as important for prognosis. To address this gap, we developed an R package spatialTIME that enables spatial analysis of mIF data, as well as the iTIME web application that provides a robust but simplified user interface for describing both abundance and spatial architecture of the TIME. The spatialTIME package calculates univariate and bivariate spatial statistics (e.g. Ripley’s K, Besag’s L, Macron’s M and G or nearest neighbor distance) and creates publication quality plots for spatial organization of the cells in each tissue sample. The iTIME web application allows users to statistically compare the abundance measures with patient clinical features along with visualization of the TIME for one tissue sample at a time. Availability and implementation spatialTIME is implemented in R and can be downloaded from GitHub (https://github.com/FridleyLab/spatialTIME) or CRAN. An extensive vignette for using spatialTIME can also be found at https://cran.r-project.org/web/packages/spatialTIME/index.html. iTIME is implemented within a R Shiny application and can be accessed online (http://itime.moffitt.org/), with code available on GitHub (https://github.com/FridleyLab/iTIME). Supplementary information Supplementary data are available at Bioinformatics online.

BACKGROUND: Malignant gliomas are the most common primary adult brain tumors, with a poor prognosis and ill-defined etiology. Mitochondrial DNA (mtDNA) sequence variation has been linked with certain cancers; however, research on glioma is lacking. METHODS: We examined the association of common (minor allele frequency ≥ 5%) germline mtDNA variants and haplogroups with glioma risk in 1,653 glioma cases and 1,065 controls from a US case-control study, and 432 glioma cases and 1,556 matched controls from the UK Biobank cohort (UKB). DNA samples were genotyped using the UK Biobank array that included a set of common and rare mtDNA variants. Risk associations were examined separately for glioblastoma (GBM) and lower grade tumors (non-GBM). RESULTS: In the US study, haplogroup W was inversely associated with glioma when compared with haplogroup H (OR=0.43, 95%CI: 0.23–0.79); this association was not demonstrated in the UKB (OR=1.07, 95%CI: 0.47–2.43). In the UKB, the variant m.3010G>A was significantly associated with GBM (OR=1.32; 95%CI: 1.01–1.73; p=0.04), but not non-GBM (1.23; 95%CI: 0.78–1.95; p=0.38); no similar association was observed in the US study. In the US study, the variant m.14798T > C, was significantly associated with non-GBM (OR=0.72; 95%CI: 0.53–0.99), but not GBM (OR=0.86; 95%CI: 0.66–1.11), whereas in the UKB, a positive association was observed between this variant and GBM (OR=1.46; 95%CI: 1.06–2.02) but not non-GBM (OR=0.92; 95%CI: 0.52–1.63). None of these associations were significant after adjustment for multiple testing. CONCLUSION: The association of inherited mtDNA variation, including rare and singleton variants, with glioma risk merits further study.

BACKGROUND: Emerging evidence suggests that a subset of Black men with National Comprehensive Cancer Network (NCCN) low-risk prostate cancer (PCa) may harbor high volume and genomically aggressive disease. However, limited, and ambiguous research exist to evaluate the risk of extreme Gleason reclassification in Black men with low-risk PCa. METHODS: This retrospective cohort study included 45,674 low-risk PCa patients who underwent prostatectomy and were not on active surveillance, from National Cancer Database (NCDB). A propensity score matched-pair design was employed, and the final cohort was limited to 1:1 matched 12,340 patients. Gleason score reclassification was used as primary endpoint. As such, any migration to pathologic Gleason score ≥7(3 + 4) was identified as overall, whereas migration to ≥7(4 + 3) was defined as extreme reclassification. A conditional Poisson regression model was used to estimate the risk of reclassification. Whereas spline model was used to estimate the impact of increasing time to treatment as a non-linear function on Gleason reclassification between race group. RESULTS: Upon matching there were no differences in the baseline characteristics between race groups. In a matched cohort, higher proportion of low-risk Black men (6.6%) reported extreme reclassification to pathologic Gleason score than White men (5.0%), p < 0.001. In a conditional Poisson regression model adjusted for time to treatment, the risk of overall (RR = 1.09, 95% CI, 1.05–1.13, p < 0.001) and extreme (RR = 1.30, 95% CI, 1.12–1.50, p = 0.004) reclassification was significantly higher in Black men as compared to their White counterpart. In spline model, the probability of Gleason reclassification in Black men was elevated with increasing time to treatment, especially after 180 days (53% vs. 43% between Black and White men). CONCLUSION: Risk of Gleason score reclassification is disparately elevated in Black men with low-risk PCa. Furthermore, time to treatment can non-linearly impact Gleason reclassification in Black men.

Purpose The role of growth factors and inflammation in the onset of glioma is poorly understood, and conflicting reports of associations of circulating IGF-1 and inflammatory biomarkers with glioma risk exist in the literature. We examined associations between C-reactive protein (CRP), white blood cell count (WBC), neutrophil-to-lymphocyte ratio (NLR), and insulin-like growth factor-1 (IGF-1) and glioma risk in the UK Biobank cohort. Methods Hazard ratios (HR) and 95% confidence intervals (CI) for glioma according to circulating biomarkers concentrations were calculated using Cox proportional hazards regression, adjusted for age, sex, race, and education. Analyses were conducted separately for glioma overall and by glioma subtype. Results We identified 417 incident glioma cases among 428,537 participants with 3,255,815 person-years of follow up. Weak, non-significant associations were observed with increasing levels of these biomarkers for risk of glioma overall or by glioma subtype. Among women only, IGF-1 in the highest quartile was positively associated with glioma risk compared to the lowest quartile (HR=1.64, 95%CI: 1.03–2.60, p-trend=0.08), as was NLR (HR=1.54, 95%CI: 1.00–2.39, p-trend=0.05). Conclusion In this prospective cohort, we found no significant associations between the inflammatory biomarkers CRP and WBC and the development of glioma. NLR and IGF-1 were associated with risk in women, but not men. When considered with previous studies, further investigation of NLR and IGF-1 as markers of glioma risk appears warranted, particularly in women.

Background: RAS gene family mutations are the most prevalent in thyroid nodules with indeterminate cytology and are present in a wide spectrum of histological diagnoses. We evaluated differentially expressed genes and signaling pathways across the histological/clinical spectrum of RAS-mutant nodules to determine key molecular determinants associated with a high risk of malignancy. Methods: Sixty-one thyroid nodules with RAS mutations were identified. Based on the histological diagnosis and biological behavior, the nodules were grouped into five categories indicating their degree of malignancy: non-neoplastic appearance, benign neoplasm, indeterminate malignant potential, low-risk cancer, or high-risk cancer. Gene expression profiles of these nodules were determined using the NanoString PanCancer Pathways and IO 360 Panels, and Angiopoietin-2 level was determined by immunohistochemical staining. Results: The analysis of differentially expressed genes using the five categories as supervising parameters unearthed a significant correlation between the degree of malignancy and genes involved in cell cycle and apoptosis (BAX, CCNE2, CDKN2A, CDKN2B, CHEK1, E2F1, GSK3B, NFKB1, and PRKAR2A), PI3K pathway (CCNE2, CSF3, GSKB3, NFKB1, PPP2R2C, and SGK2), and stromal factors (ANGPT2 and DLL4). The expression of Angiopoietin-2 by immunohistochemistry also showed the same trend of increasing expression from non-neoplastic appearance to high-risk cancer (p

Few prospective studies have evaluated the relation between fat-soluble vitamins and glioma risk. Using three cohorts—UK Biobank (UKB), Nurses’ Health Study (NHS), and Health Professionals Follow-Up Study (HPFS), we investigated associations of pre-diagnostic concentrations of fat-soluble vitamins D, A, and E with incident glioma. In 346,785 participants (444 cases) in UKB, associations with vitamin D (25-hydroxyvitamin D [25(OH)D]) were evaluated by Cox proportional hazards regression. In NHS (52 cases, 104 controls) and HPFS (32 cases, 64 controls), associations with 25(OH)D, vitamin A (retinol), and vitamin E (α- and γ-tocopherol) were assessed using conditional logistic regression. Our results suggested plasma concentrations of 25(OH)D and retinol were not associated with glioma risk. Comparing the highest to lowest tertile, the multivariable hazard ratio (MVHR) for 25(OH)D was 0.87 (95% confidence interval [CI] 0.68–1.11) in UKB and the multivariable risk ratio (MVRR) was 0.97 (95% CI 0.51–1.85) in NHS and HPFS. In NHS and HPFS, the MVRR for the same comparison for retinol was 1.16 (95% CI 0.56–2.38). Nonsignificant associations were observed for α-tocopherol (MVRRtertile3vs1 = 0.61, 95% CI 0.29–1.32) and γ-tocopherol (MVRR tertile3vs1 = 1.30, 95% CI 0.63–2.69) that became stronger in 4-year lagged analyses. Further investigation is warranted on a potential association between α- and γ-tocopherol and glioma risk.

Bioinformatic scientists are often asked to do widespread analyses of publicly available datasets in order to identify genetic alterations in cancer for genes of interest; therefore, we sought to create a set of tools to conduct common statistical analyses of The Cancer Genome Atlas (TCGA) data. These tools have been developed in response to requests from our collaborators to ask questions, validate findings, and better understand the function of their gene of interest. We describe here what data we have used, how to obtain it, and what figures we have found useful.

Bioinformatic scientists are often asked to do widespread analyses of publicly available datasets in order to identify genetic alterations in cancer for genes of interest; therefore, we sought to create a set of tools to conduct common statistical analyses of The Cancer Genome Atlas (TCGA) data. These tools have been developed in response to requests from our collaborators to ask questions, validate findings, and better understand the function of their gene of interest. We describe here what data we have used, how to obtain it, and what figures we have found useful.

PURPOSE: Evidence is mixed on whether cholesterol plays a role in the pathogenesis of glioma. We explored the associations between circulating lipids and glioma risk in three prospective cohorts. METHODS: Using prospective data from the UK Biobank, we examined the associations of total cholesterol (TC), high- and low-density lipoprotein cholesterol (HDL-C, LDL-C), and triglycerides (TG) with glioma risk in multivariable (MV)-adjusted Cox proportional hazards models. Within the Nurses’ Health Study (NHS) and the Health Professionals Follow-Up Study (HPFS), we carried out a matched, nested case-control study to examine these same associations. RESULTS: In the UK Biobank, 490 gliomas accrued over 2,358,964 person-years. TC was not significantly associated with glioma risk (MV HR=1.20, 95%CI: 0.89-1.61 for highest quartile vs. lowest, p-trend=0.24). In four-year lagged analyses (n=229), higher TC was associated with significantly higher risk of glioma in men (MV HR=2.26, 95%CI: 1.32-3.89, p-trend=0.002) but not women (MV HR =1.28, 95%CI: 0.61-2.68, p-trend=0.72); similar findings emerged for HDL-C and, to a lesser extent, LDL-C. In the NHS/HPFS, no significant associations were found between cholesterol and glioma risk. No significant associations were identified for TG. CONCLUSION: In the UK Biobank, higher prediagnostic TC and HDL-C levels were associated with higher risk of glioma in four-year lagged analyses, but not in non-lagged analyses, in men only. These findings merit further investigation, given that there are few risk factors and no reliable biomarkers of risk identified for glioma.

Gliomas are the most common type of malignant primary brain tumor and few risk factors have been linked to their development. Handedness has been associated with several pathologic neurological conditions such as schizophrenia, autism, and epilepsy, but few studies have evaluated a connection between handedness and risk of glioma. In this study, we examined the relationship between handedness and glioma risk in a large case-control study (1,849 glioma cases and 1,354 healthy controls) and a prospective cohort study (326,475 subjects with 375 incident gliomas). In the case-control study, we found a significant inverse association between left handedness and glioma risk, with left-handed persons exhibiting a 35% reduction in the risk of developing glioma (Odds Ratio (OR)=0.65, 95% Confidence Interval (CI): 0.51, 0.83) after adjustment for age, gender, race, education, and state of residence; similar inverse associations were observed for GBM (OR=0.69, 95% CI: 0.52, 0.91), and non-GBM (OR=0.59, 95% CI: 0.42, 0.82) subgroups. The association was consistent in both males and females, and across age strata, and was observed in both glioblastoma and in lower grade tumors. In the prospective cohort study, we found no association between handedness and glioma risk (Hazards Ratio=0.92, 95% CI: 0.67, 1.28) adjusting for age, gender, and race. Further studies on this association may help to elucidate mechanisms of pathogenesis in glioma.

Background Coffee and tea have been hypothesised to reduce the risk of some cancers; however, their impact on glioma is less well studied. Methods We examined associations between self-reported intake of tea and coffee in relation to glioma risk in the UK Biobank. We identified 487 incident glioma cases among 379,259 participants. Hazard ratios (HR) and 95% confidence intervals (CI) for glioma according to caffeinated beverage consumption were calculated using Cox proportional hazards regression with adjustment for age, gender, race and education; daily cups of tea or coffee were included in models considering the other beverage. Results Consuming 4 or more cups of tea was associated with reduced risk of glioma when compared to no tea consumption (HR = 0.69; 95% CI, 0.51–0.94). A significant inverse association was observed for glioblastoma (HR = 0.93 per 1 cup/d increment; 95% CI, 0.89–0.98) and among males for all gliomas combined (HR = 0.95 per 1 cup/d increment; 95% CI, 0.90–1.00). A suggestive inverse association was also observed with greater consumption of coffee (HR = 0.71; 95% CI, 0.49–1.05 for >4 versus 0 cups/d). Results were not materially changed with further adjustment for smoking, alcohol and body mass index. Associations were similar in 2-year and 3-year lagged analyses. Conclusions In this prospective study, we found a significant inverse association between tea consumption and the risk of developing glioma, and a suggestive inverse association for the consumption of coffee. Further investigation on the possible preventive role of caffeine in glioma is warranted.

Background: Commercial gene expression signatures of prostate cancer prognosis were developed and validated in cohorts of predominantly European American men (EAM). Limited research exists on the value of such signatures in African American men (AAM), who have poor prostate cancer outcomes. We explored differences in gene expression between EAM and AAM for three commercially available panels recommended by the National Comprehensive Cancer Network for prostate cancer prognosis. Methods: A total of 232 EAM and 95 AAM patients provided radical prostatectomy specimens. Gene expression was quantified using NanoString for 60 genes spanning the Oncotype DX Prostate, Prolaris, and Decipher panels. A continuous expression-based risk score was approximated for each. Differential expression, intrapanel coexpression, and risk by race were assessed. Results: Clinical and pathologic features were similar between AAM and EAM. Differential expression by race was observed for 48% of genes measured, although the magnitudes of expression differences were small. Coexpression patterns were more strongly preserved by race group for Oncotype DX and Decipher than Prolaris. Poorer prognosis was estimated in EAM versus AAM for Oncotype DX (P < 0.001), whereas negligible prognostic differences were predicted between AAM and EAM using Prolaris or Decipher (P > 0.05). Conclusions: Because of observed racial differences across three commercial gene expression panels for prostate cancer prognosis, caution is warranted when applying these panels in clinical decision-making in AAM. Impact: Differences in gene expression by race for three commercial panels for prostate cancer prognosis indicate that further study of their effectiveness in AAM with long-term follow-up is warranted.

Methylmercury (MeHg) is an environmental neurotoxin with human exposure mainly from dietary intake of contaminated fish. Exposure to MeHg has been implicated in neurological damage, but research on its role in cancers, specifically glioma, is limited. In a glioma case-control study, we examined associations between toenail mercury (Hg) and glioma risk. We also examined genetic polymorphisms in 13 genes related to MeHg metabolism for association with glioma risk; genetic associations were also studied in the UK Biobank cohort. Median toenail Hg in cases and controls, respectively, was 0.066 μg/g and 0.069 μg/g (interquartile range (IQR): 0.032–0.161 and 0.031–0.150 μg/g). Toenail Hg was not found to be significantly associated with glioma risk (Odds Ratio: 1.02; 95% Confidence Interval: 0.91, 1.14; p = 0.70 in analysis for ordinal trend with increasing quartile of toenail MeHg). No genetic variant was statistically significant in both of the studies; one variant, rs11859163 (MMP2) had a combined p-value of 0.02 though it was no longer significant after adjustment for multiple testing (Bonferroni corrected p = 1). This study does not support the hypothesis that exposure to MeHg plays a role in the development of glioma at levels of exposure found in this study population.

Background Selenium is an essential trace element obtained through diet that plays a critical role in DNA synthesis and protection from oxidative damage. Selenium intake and polymorphisms in selenoproteins have been linked to the risk of certain cancers though data for glioma are sparse. Methods In a case-control study of glioma, we examined the associations of selenium in toenails and genetic variants in the selenoenzyme pathway with the risk of glioma and patient survival. A total of 423 genetic variants in 29 candidate genes in the selenoenzyme pathway were studied in 1547 glioma cases and 1014 healthy controls. Genetic associations were also examined in the UK Biobank cohort comprised of 313,868 persons with 322 incident glioma cases. Toenail selenium was measured in a subcohort of 300 glioma cases and 300 age-matched controls from the case-control study. Results None of the 423 variants studied were consistently associated with glioma risk in the case-control and cohort studies. Moreover, toenail selenium in the case-control study had no significant association with glioma risk (p trend = 0.70) or patient survival among 254 patients with high grade tumors (p trend = 0.70). Conclusion The present study offers no support for the hypothesis that selenium plays a role in the onset of glioma or patient outcome.

The increasing availability of public data resources coupled with advancements in genomic technology has created greater opportunities for researchers to examine the genome on a large and complex scale. To meet the need for integrative genome wide exploration, we present epiTAD. This web-based tool enables researchers to compare genomic structures and annotations across multiple databases and platforms in an interactive manner in order to facilitate in silico discovery. epiTAD can be accessed at https://apps.gerkelab.com/epiTAD/.

Background: Current National Comprehensive Cancer Network (NCCN) guidelines recommend three gene expression-based tests for prostate cancer (PCa) prognosis in men with low or favorable intermediate risk disease: Decipher, Oncotype DX Prostate, and Prolaris. The three tests feature varying numbers of genes with minimal overlap. Importantly, development and validation efforts for all three panels were undertaken in predominantly European American men (EAM) cohorts, and limited research exists on the value of such signatures in African American men (AAM), who have poorer PCa outcomes. Here, we explored differences in gene expression between EAM and AAM for the three panels recommended by the NCCN for PCa prognosis. Methods: 232 EAM and 95 AAM patients provided radical prostatectomy specimens. Gene expression was quantified using Nanostring for 60 genes spanning the Oncotype DX Prostate, Prolaris, and Decipher panels. Differential expression and intrapanel co-expression by race were assessed using Mann-Whitney tests and Spearman’s correlations, respectively. A continuous expression-based risk score was approximated for each panel with higher scores indicating worse outcomes. Race-specific risks were compared using Mann-Whitney tests and Spearman’s correlations. Results: Clinical and pathologic features were similar between AAM and EAM. Differential expression by race was observed for 48% of genes measured, though the magnitudes of expression differences were small. Co-expression patterns were more strongly preserved by race group for Oncotype DX and Decipher versus Prolaris (integrative correlations of 0.87, 0.73, and 0.62, respectively). Paradoxically, poorer prognosis was estimated in EAM versus AAM for Prolaris and Oncotype DX (p = 0.01 for both), whereas worse prognosis was predicted for AAM versus EAM using Decipher (p < 0.001). Discussion: Due to observed racial differences across three commercial gene expression panels for PCa prognosis, caution is warranted when applying these panels in clinical decision-making in AAM. Replication of our findings directly on the commercial panels with long-term follow-up is warranted. Citation Format: Jordan H. Creed, Anders E. Berglund, Robert J. Rounbehler, Shivanshu Awasthi, John L. Cleveland, Jong Y. Park, Kosj Yamoah, Travis A. Gerke. Commercial gene expression tests for prostate cancer prognosis provide paradoxical estimates of race-specific risk [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4471.

Purpose: To derive a gene expression score of transcriptomic homogeneity in localized prostate tumor specimens, and assess its prognostic utility for metastatic or lethal disease. Background: At the time of prostate cancer diagnosis, improved biomarkers are needed to distinguish tumors with metastatic potential versus those likely to follow an indolent course. Previous evidence suggests that gene expression aberrations are homogeneous in nonaggressive tumors, while transcriptomic profiles are disregulated in widely varying patterns across metastasis-prone tumors. Here, we investigate whether a measure of transcriptomic homogeneity has prognostic utility. Study Population: Gene expression profiles of noncancerous prostate tissue from the Genotype-Tissue Expression (GTEx) project (n = 106) were used to develop the homogeneity measure. Prognostic utility of the score was assessed in a study nested in the Health Professionals Follow-up Study (HPFS) and Physicians’ Health Study (PHS), in which whole-transcriptome gene expression was quantified from archival surgical tumor tissue. Cases (n = 113) were men who died of prostate cancer or developed metastatic disease, and controls (n = 291) had at least 8 years of metastasis-free survival. Men were diagnosed with prostate cancer between 1982 and 2005, and median follow-up time was 14.0 years. TCGA data (n = 333) were further used to investigate associations of the expression score with Gleason. Methods: RNA-seq profiles from GTEx were filtered to retain genes persistently expressed across noncancerous prostate tissue specimens. Remaining genes were placed into decile bins on the basis of median expression across samples. The 25 lowest variance genes within each bin were selected to generate a 250-gene panel. Transcriptome homogeneity scores for patients in HPFS and PHS were calculated by summing the standard deviations over the decile bins, where standard deviations were calculated using patient-specific data across 25 genes in each bin. Associations between the score and lethal disease were assessed through logistic regression and AUC analyses. Associations between the homogeneity score and Gleason score in TCGA samples were evaluated via Pearson correlations. Results: High transcriptomic heterogeneity was strongly associated with lethal or metastatic outcomes. A crude odds ratio of 3.36 (95% CI 2.12-5.41; p Conclusions: Transcriptomic homogeneity, as measured by variation across gene sets that are typically stable in normal prostate tissue, is able to distinguish indolent from lethal prostate cancers. Further investigation and discovery of gene sets using this novel approach is likely to deliver new biologic insights and clinically actionable biomarker sets. Citation Format: Travis Gerke, Svitlana Tyekucheva, Jordan H. Creed, Kathryn L. Penney, Jennifer A. Sinnott, Ericka Ebot, Anders E. Berglund, Massimo Loda, Meir J. Stampfer, Peter Kraft, Giovanni Parmigiani, Lorelei A. Mucci. All happy families are alike: Transcriptomic homogeneity in indolent prostate tumors is a useful prognostic biomarker [abstract]. In: Proceedings of the AACR Special Conference: Prostate Cancer: Advances in Basic, Translational, and Clinical Research; 2017 Dec 2-5; Orlando, Florida. Philadelphia (PA): AACR; Cancer Res 2018;78(16 Suppl):Abstract nr A045.