Table S3. List of Hyper-fucosylated glycans for prostate cancer analysis

Figure S3. Ley expression in small cell prostate cancer.

Figure S5. Heat map of selected glycans of a metastatic small cell carcinoma to a lymph node.

Figure S8. Fucosylated glycan expression in tumors from prostatectomy specimens do not associate with PSA, grade, or stage.

Table S2. Patient data from the University of Texas Health San Antonio Tissue Microarray.

Background:Risk stratification for prostate cancer (PCa) progression or aggressiveness is often based on clinicopathologic features, some of which may be influenced by genetic factors. We developed a novel, germline polygenic risk score (PRSagg) to predict likelihood of developing aggressive PCa. Methods:PRSagg was developed using data from 38,688 patients with PCa (case-only analysis) from the Million Veteran Program (MVP) through a genome-wide search for variants associated with PCa grade group at diagnosis. We tested associations of PRSagg with grade group using the entire MVP dataset using the .632 bootstrap method. In an MVP cohort with localized PCa that was initially monitored without treatment, we tested PRSagg for association with unfavorable outcomes (subsequent development of grade group 4-5, metastasis, and/or biochemical recurrence after definitive treatment). We performed external validation in data from patients in the PRACTICAL Consortium (n=45,214) and from participants in the ProtecT randomized trial who underwent active monitoring (n=316). Odds ratios (ORs) were calculated per standard deviation (SD) increase with 95% confidence intervals, while adjusting for age, genetic ancestry, a previously developed polygenic score for risk of PCa (PHS601), and a polygenic score for benign elevated prostate-specific antigen (PRSPSA). For the outcome of metastasis, we additionally adjusted for PSA at diagnosis. Results:In the MVP training dataset, PRSagg (172 variants) was associated with higher grade group at diagnosis (OR = 1.53 [1.51-1.56]) and with increased risk of unfavorable outcomes during monitoring (OR = 1.13 [1.09-1.18]). These findings were confirmed in the external datasets. PRSagg was associated with greater odds of higher grade group at diagnosis (OR = 1.09 [1.061.11]). Among ProtecT participants undergoing active monitoring, PRSagg was associated with higher risk of metastasis (OR = 2.15 [1.02-3.88]). Among MVP participants with high polygenic risk of developing any PCa, the risk of aggressive disease was highest in men with high PRSagg and low genetic risk of PSA elevation. Conclusions:Among men who develop PCa, a weighted sum of common germline variants (PRSagg) is independently associated with PCa aggressiveness. These findings may inform future study of germline influence on tumor evolution and risk-stratified intensity of active surveillance.

Table S1. Patient data from the Washington University cohort.

Figure S1. Schematic of fucosylated glycan architecture.

Figure S7. Example of adenocarcinoma with NE features.

Background Gene polymorphisms can lead to differential production of inflammatory proteins associated with cancer development. Prior explorations of the association of single nucleotide polymorphisms (SNPs) of monocyte chemoattractant protein (MCP-1/CCL2) and its receptor, CCR2, to bladder cancer, yielded conflicting findings.Objective To analyze the distributions of the polymorphisms CCL2 rs1024611 and CCR2 rs1799864 between healthy controls and bladder cancer patients to determine if they are associated with bladder cancer risk in a cohort of Hispanic White and non-Hispanic White men.Methods DNA was isolated from blood obtained from healthy male controls (CCL2 n = 447; CCR2 n = 612) and from male bladder cancer patients (CCL2 n = 233; CCR2 n = 227). The CCL2 rs1024611 SNP and CCR2 rs1799864 SNP were genotyped using the TaqMan methodology. Multivariable logistic regression was used to determine associations between SNP genotypes and bladder cancer in Hispanic and non-Hispanic White men.Results There were no significant differences in the genotype frequencies for either the CCL2 or CCR2 SNP and bladder cancer risk was equivalent regardless of CCL2 (NHW AA vs AG/GG, p = 0.7232; H AA vs. AG/GG, p = 0.5187) or CCR2 genotype (NHW AA vs GG/GG, p = 0.6826; H GG vs. AA/AG, p = 0.2425).Conclusion Prior studies have shown conflicting results regarding the association between bladder cancer risk and the CCL2 rs1024611 and CCR2 rs1799864 polymorphisms. We were unable to validate significant findings regarding any relationship between these polymorphism distributions across individuals with or without bladder cancer in a cohort of non-Hispanic White and Hispanic White men, suggesting no role of CCL2/CCR2 polymorphisms in bladder cancer.

Figure S2. Enrichment of glycans in specimens with small cell versus adenocarcinoma histology.

Table of all detected ECM peptides following LCMS analysis

Figure S4. Heat map of selected glycans of a GG5 adenocarcinoma.

Annotated LCMS spectra for COL1A1;COL1A2

BACKGROUND AND OBJECTIVE:Most prostate cancer prevention strategies suggest lifestyle modifications, which lack personalization. Gut microbiome is increasingly recognized as an influencing factor in nongastrointestinal cancers, including prostate cancer. The use of gut microbiome as a lifestyle biomarker could help identify individuals with lifestyle more prone to prostate cancer and allow for modification. We aimed to develop a gut microbiome-based biomarker derived from patients undergoing prostate cancer screening. METHODS:We assessed whether the future cancer risk can be evaluated based on a microbiome risk analysis. After extracting DNA, sequencing, and performing a bioinformatics analysis, we identified 39 unique microbial genera of importance. We utilized an artificial intelligence model to calculate their presence, abundance, and weighted significance, generating a microbiome score (Prostate Cancer Risk Insight using Microbiome UnderStanding [PRIMUS]) that ranges from 0 to 1. KEY FINDINGS AND LIMITATIONS:Men with an increasing PRIMUS signature showed a sequential increase in prostate cancer risk. The prostate cancer risk persisted after a median follow-up of 4.5 yr. As a risk-assessment tool, the microbiome score compared favorably with prostate cancer risk calculators. Study limitations include the use of two patient groups to diversify the population for both a screening and a prebiopsy scenario; however, the cohorts used different collection methods, including stool, rectal swabs, and glove tip samples, but the same DNA isolation and sequencing. We relied on the longitudinal approach to help reduce these initial differences. CONCLUSIONS AND CLINICAL IMPLICATIONS:The gut microbiome may serve as a lifestyle risk factor for prostate cancer, but it is not intended to guide biopsy decisions. The implications of this study hinge on the potential for modifiability of the microbiome that could be tested in future clinical trials on prostate cancer risk reduction.

Figure S6. Heat map of selected glycans of a mixed GG5 adenocarcinoma and small cell tumor.

Prostate cancer (PCa) remains a significant public health challenge, ranking as the second leading cause of cancer-related deaths among men in the United States. Current diagnostic approaches, predominantly centered on prostate-specific antigen (PSA) testing, often lead to overdiagnosis and unnecessary biopsies. The long nonprotein coding gene, PVT1 (plasmacytoma variant translocation 1), has shown promise as a biomarker, being upregulated in PCa and associated with disease progression and metastasis. This study investigates the potential of incorporating PVT1 biomarkers to improve diagnostic accuracy for PCa detection, focusing on both the general population and men of African ancestry, who are disproportionately impacted by PCa incidence and mortality.A total of 144 serum samples were analyzed, with 72 samples from men diagnosed with PCa and 72 from men without cancer. Serum levels of PVT1 Exons 4A, 4B, and 9 were quantified using digital PCR. Multiple logistic regression models were developed to predict cancer status based on PSA alone, PVT1 biomarkers alone, and combinations of PSA with PVT1 biomarkers. Model performance was assessed using stratified k-fold cross-validation, with comparisons made using likelihood ratio tests, and z-tests for statistical significance.The results show that combining PSA with PVT1 Exon 4A improves specificity in predicting cancer status in the general population from 0.45 to 0.54 while maintaining sensitivity at 0.81. Within the subpopulation of men of African Ancestry, PVT1 Exon 4A alone achieves an accuracy of 0.75 with a sensitivity of 1.0 and specificity of 0.5 compared to PSA alone which had an accuracy of 0.38, sensitivity of 0.5 and specificity of 0.25.This study underscores the potential clinical utility of integrating PVT1 biomarkers into prostate cancer screening programs. The inclusion of Exon 4A enhanced PSA-based prediction by addressing its limitations in overdiagnosis and unnecessary biopsies, providing a balanced improvement in diagnostic performance. By improving the accuracy of PCa detection while reducing the burden of overdiagnosis, this approach provides significant value for healthcare providers, diagnostic laboratories, and insurers aiming to enhance early detection and equitable screening outcomes. Tinovimba L. Hove, Rachel E. Sexton, Michael Liss, Robin Leach, Emmanuel Asante-Asamani, Olorunseun O. Ogunwobi. The prediction of positive prostate biopsies in men is significantly enhanced when PVT1 Exon 4A is combined with serum Prostate Specific Antigen (PSA) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 1058.