Lilja, Hans

Abstract Inherited susceptibility plays a critical role in prostate cancer (PCa) risk. Using large biobank and case-control datasets, we evaluated the contribution of both common variants and rare germline pathogenic variants (PVs) to overall PCa risk. The Prostate Cancer Exome Sequencing Consortium currently includes 427,388 male participants (51,452 PCa cases and 375,936 controls) with whole-exome sequencing data from ten biobanks and studies: UK Biobank (14,669 cases/195,600 controls), All of Us Research Program (7,577/75,226), African Ancestry Prostate Cancer Consortium (7,176/4,675), Mayo Clinic Biobank (6,031/15,084), Mass General Brigham Biobank (3,393/14,095), Geisinger’s MyCode Community Health Initiative (3,026/15,130), UCLA ATLAS Precision Medicine Biobank (2,850/16,904), Penn Medicine Biobank (2,598/16,255), Colorado Center for Personalized Medicine (2,269/13,399), and Malmo Diet and Cancer (1,863/9,568). Based on self-reported race/ethnicity and estimated genetic ancestry, the cases comprise approximately 79% European, 18% African, and 3% other ancestry populations. Single-variant association analyses tested all variants on chromosomes 1-22 and X with a minor allele count ≥ 5. In gene-based analyses, PVs were defined as rare variants (minor allele frequency [MAF] < 1% in controls) that had either a Variant Effect Predictor (VEP) impact score of “high” or a pathogenic or likely pathogenic ClinVar classification. Associations were estimated using Firth logistic regression, adjusting for age and the top ten genetic principal components. Results from individual studies were combined using fixed-effect meta-analysis. In single-variant association analyses, 496 variants reached genome-wide significance (p<5×10-8; MAF>0.02%). Among these, 458 (92%) variants mapped to previously known risk regions, including three rare PVs in HOXB13 (rs138213197), CHEK2 (rs555607708), and FAM111A (rs533676902). Characterization of the remaining 38 variants is ongoing. Gene-based analyses identified significant associations (p<2.4×10-6) for eight genes: HOXB13 (OR=3.7, 95% CI=3.3-4.2), BRCA2 (OR=2.0, 95% CI=1.7-2.3), CHEK2 (OR=1.6, 95% CI=1.5-1.8), ATM (OR=1.6, 95% CI=1.4-1.9), FAM111A (OR=1.4, 95% CI=1.3-1.5), BIK (OR=1.4, 95% CI=1.2-1.6), SAMHD1 (OR=2.1, 95% CI=1.6-2.7), and SMOC2 (OR=3.2, 95% CI=2.0-5.1). All genes except SMOC2 have been previously implicated in PCa susceptibility. Among cancer predisposition and DNA repair genes, nominal associations were also observed for XRCC2 (OR=1.6, 95% CIs=1.2-2.3) and BRCA1 (OR=1.2, 95% CI=1.0-1.4), whereas the association was not significant for PALB2 (OR=1.2, 95% CI=0.9-1.5). These findings reinforce the role of rare germline PVs, particularly in cancer predisposition and DNA repair genes, in PCa susceptibility. As additional studies are incorporated into the Consortium, we expect this work to provide a more comprehensive characterization of the genetic architecture of PCa. Citation Format: Yifan Zhang, Shuyan Cheng, Nicholas Boddicker, Matthew Lebo, Alexander S. Berry, Roni Haas, Ryan Hausler, Tokhir Dadaev, Heena Desai, Alex A. Rodriguez, Ravi K. Madduri, Andrew Hill, Xin Sheng, Susan M. Gundell, Mine Cicek, Penn Medicine Biobank, Olle Melander, Chris R. Gignoux, Isla P. Garraway, Bogdan Pasaniuc, Paul C. Boutros, Matt Oetjens, Adam S. Kibel, Robert J. Klein, Zsofia Kote-Jarai, Fergus J. Couch, Kara N. Maxwell, Burcu F. Darst, David V. Conti, Christopher A. Haiman, Fei Chen. Genetic risk of prostate cancer: Insights from the Prostate Cancer Sequencing Consortium [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(8_Suppl):Abstract nr LB390.

Objectives To prospectively evaluate the performance of a pre‐specified statistical model based on four kallikrein markers in blood (total prostate‐specific antigen [PSA], free PSA, intact PSA, and human kallikrein‐related peptidase 2), commercially available as the 4Kscore, in predicting Gleason Grade Group (GG) ≥2 prostate cancer at biopsy in an international multicentre study at three academic medical centres, and whether microseminoprotein‐β (MSP) adds predictive value. Patients and Methods A total of 984 men were prospectively enrolled at three academic centres. The primary outcome was GG ≥2 on prostate biopsy. Three pre‐specified statistical models were used: a base model including PSA, age, digital rectal examination and prior negative biopsy; a model that added free PSA to the base model; and the 4Kscore. Results A total of 947 men were included in the final analysis and 273 (29%) had GG ≥2 on prostate biopsy. The base model area under the receiver operating characteristic curve of 0.775 increased to 0.802 with the addition of free PSA, and to 0.824 for the 4Kscore. Adding MSP to the 4Kscore model yielded an increase (0.014–0.019) in discrimination. In decision‐curve analysis of clinical utility, the 4Kscore showed a benefit starting at a 7.5% threshold. Conclusion A prospective multicentre evaluation of a pre‐specified model based on four kallikrein markers (4Kscore) with the addition of MSP improves the predictive discrimination for GG ≥2 prostate cancer on biopsy and could be used to inform biopsy decision‐making.

AbstractBackgroundTo assess whether a prespecified statistical model based on the four kallikrein markers measured in blood—total, free, and intact prostate‐specific antigen (PSA), together with human kallikrein‐related peptidase 2 (hK2)—or any individual marker measured in pretreatment serum were associated with biochemical recurrence‐free (BCR) or metastasis‐free survival after radical prostatectomy (RP) in a subgroup of men with very high‐risk disease.MethodsWe identified 106 men treated at Mayo Clinic from 2004 to 2008 with pathological Gleason grade group 4 to 5 or seminal vesicle invasion at RP. Univariable and multivariable Cox models were used to test the association between standard predictors (Kattan nomogram and GPSM [Gleason, PSA, seminal vesicle and margin status] score), kallikrein panel, and individual kallikrein markers with the outcomes.ResultsBCR and metastasis occurred in 67 and 30 patients, respectively. The median follow‐up for patients who did not develop a BCR was 10.3 years (interquartile range = 8.2‐11.8). In this high‐risk group, neither Kattan risk, GPSM score, or the kallikrein panel model was associated with either outcome. However, after adjusting for Kattan risk and GPSM score, separately, preoperative intact PSA was associated with both outcomes while hK2 was associated with metastasis‐free survival.ConclusionsConventional risk prediction tools were poor discriminators for risk of adverse outcomes after RP (Kattan risk and GPSM risk) in patients with very high‐risk disease. Further studies are needed to define the role of individual kallikrein marker forms in the blood to predict adverse prostate cancer outcomes after RP in this high‐risk setting.

AbstractBackground: Updated National Academy of Clinical Biochemistry (NACB) Laboratory Medicine Practice Guidelines for the use of tumor markers in the clinic have been developed.Methods: Published reports relevant to use of tumor markers for 5 cancer sites—testicular, prostate, colorectal, breast, and ovarian—were critically reviewed.Results: For testicular cancer, α-fetoprotein, human chorionic gonadotropin, and lactate dehydrogenase are recommended for diagnosis/case finding, staging, prognosis determination, recurrence detection, and therapy monitoring. α-Fetoprotein is also recommended for differential diagnosis of nonseminomatous and seminomatous germ cell tumors. Prostate-specific antigen (PSA) is not recommended for prostate cancer screening, but may be used for detecting disease recurrence and monitoring therapy. Free PSA measurement data are useful for distinguishing malignant from benign prostatic disease when total PSA is <10 μg/L. In colorectal cancer, carcinoembryonic antigen is recommended (with some caveats) for prognosis determination, postoperative surveillance, and therapy monitoring in advanced disease. Fecal occult blood testing may be used for screening asymptomatic adults 50 years or older. For breast cancer, estrogen and progesterone receptors are mandatory for predicting response to hormone therapy, human epidermal growth factor receptor-2 measurement is mandatory for predicting response to trastuzumab, and urokinase plasminogen activator/plasminogen activator inhibitor 1 may be used for determining prognosis in lymph node–negative patients. CA15-3/BR27–29 or carcinoembryonic antigen may be used for therapy monitoring in advanced disease. CA125 is recommended (with transvaginal ultrasound) for early detection of ovarian cancer in women at high risk for this disease. CA125 is also recommended for differential diagnosis of suspicious pelvic masses in postmenopausal women, as well as for detection of recurrence, monitoring of therapy, and determination of prognosis in women with ovarian cancer.Conclusions: Implementation of these recommendations should encourage optimal use of tumor markers.

Abstract A group of investigators met at a Specialized Programs of Research Excellence Workshop to discuss key issues in the translation of biomarker discovery to the development of useful laboratory tests for cancer care. Development and approval of several new markers and technologies have provided informative examples that include more specific markers for prostate cancer, more sensitive tests for ovarian cancer, more objective analysis of tissue architecture and an earlier indication of response to treatment in breast cancer. Although there is no clear paradigm for biomarker development, several principles are clear. Marker development should be driven by clinical needs, including early cancer detection, accurate pretreatment staging, and prediction of response to treatment, as well as monitoring disease progression and response to therapy. Development of a national repository that uses carefully preserved, well-annotated tissue specimens will facilitate new marker development. Reference standards will be an essential component of this process. Both hospital-based and commercial laboratories can play a role in developing biomarkers from discovery to test validation. Partnering of academe and industry should occur throughout the process of biomarker development. The National Cancer Institute is in a unique position to bring together academe, industry, and the Food and Drug Administration to (a) define clinical needs for biomarkers by tumor type, (b) establish analytic and clinical paradigms for biomarker development, (c) discuss ways in which markers from different companies might be evaluated in combination, (d) establish computational methods to combine data from multiple biomarkers, (e) share information regarding promising markers developed in National Cancer Institute–supported programs, and (f) exchange data regarding new platforms and techniques that can accelerate marker development.