Prostate Cancer Research Articles

AR (CAG)n Microsatellite and APEX1 c.444T>G (p.Asp148Glu) Polymorphisms as Independent Prognostic Biomarkers in Prostate Cancer: Insights from an Argentinian Cohort

Background/Objectives: Prostate cancer (PCa) is the leading malignancy and the third most common cause of cancer-related death in Argentinian men. Predicting outcomes in localized PCa remains difficult due to tumor heterogeneity. In this study, we assessed the impact of AR (CAG)n and APEX1 c.444T>G polymorphisms on biochemical relapse in Argentine patients with localized PCa. Methods: We genotyped blood samples from 123 PCa patients for AR (CAG)n and APEX1 p.Asp148Glu (c.444T>G) polymorphisms. Associations with clinicopathological parameters and biochemical relapse-free survival (BRFS) were assessed. Results: AR (CAG)20–23 was associated with a family history of breast/ovarian cancer (p = 0.0469). The combination of AR (CAG)20–23 and APEX1 c.444TT/GG correlated with a 2.89 times higher risk of biochemical relapse (log-rank p = 0.006). Multivariable analysis confirmed AR and APEX1 polymorphisms as independent predictors of biochemical relapse (HR = 3.95, p = 0.002). In patients with PSA levels <10 ng/mL, combined AR (CAG)20–23 and APEX1 c.444TT/GG genotypes were significantly associated with an increased risk of biochemical relapse (HR = 2.61, p = 0.044). Multivariable analysis confirmed the prognostic significance of these genotypes (HR = 3.44, p = 0.02). Conclusions: This study has identified AR (CAG)n and APEX1 c.444T>G polymorphisms as independent predictors of PCa relapse in Argentinian patients, suggesting their potential use in improving prognostic models.

Research progress on the role of lipoxygenase and its inhibitors in prostate cancer.

Prostate cancer (PCa) has become a common disease among middle-aged and elderly men. The lipoxygenase (LOX) pathway plays a crucial role in the occurrence, development, invasion and metastasis of PCa and is therefore considered a new target for the prevention and treatment of PCa. 5-LOX and 12-LOX have a promoting effect on the occurrence, development, invasion and metastasis of PCa. 15-LOX-2 has an inhibitory effect on PCa. LOX inhibitors can effectively inhibit the metabolic activity of LOX. The research aims to review the mechanism of action and inhibitors of LOX in PCa, in order to provide relevant references for the prevention and treatment of PCa.

Are we there yet? Closing the gap of prostate cancer presentation disparities in Ireland.

The Irish Prostate Cancer Outcomes Research (IPCOR) Study collected longitudinal data on men newly diagnosed with Prostate Cancer (PC). Understanding the nuances of disease presentation is essential, considering the high incidence of PC in Ireland. This study aims to characterise disease presentation features, identify factors related to socio demographic disparities in presentation following opportunistic screening, and shed light on potential inequality challenges within Ireland's healthcare structure. Data were collected on demographics, diagnosis, and treatment of 6,816 men newly diagnosed with PC across 16 hospitals in the Republic of Ireland from February 2016 to January 2020. A complete case analysis was carried out, complemented by a sensitivity analysis for addressing sites with high rates of missing values. Multivariable logistic regression was conducted to examine the association between various predictor variables and the initial presentation to the urology clinic subsequent to opportunistic screening. A multivariable logistic regression model revealed that the type of hospital was a key determinant in post-opportunistic screening presentation, with patients in public hospitals 45.7% more likely to be presented following screening compared to those in private hospitals. Urban residents were 34% more likely to present following screening than rural ones. Age negatively influenced presentation following screening likelihood, decreasing by 3.4% yearly. Our research has highlighted the key features of PC presentation in Ireland, revealing potential inequalities affecting mainly urban populations, middle socioeconomic groups, and individuals with inadequate healthcare coverage. While the differences we observed in various groups may appear subtle and may indicate the success of the Rapid Access Prostate Clinics, they are still significant in pinpointing specific populations that require special attention. By addressing these nuanced differences in access to healthcare, socioeconomic status, and urban versus rural residence and implementing tailored strategies, we can work towards closing disparity gaps in PC, ultimately leading to improved health outcomes and equity across all population segments.

Abstract B062: Transcriptomic analysis of whole blood samples from prostate cancer patients: A comparative study of patients from geographically diverse populations

Abstract Introduction: Prostate cancer is the most frequently diagnosed cancer across 112 countries. Among American men, an estimated 299, 010 new cases and 35,250 deaths are projected for 2024. In this study, the transcriptomic profile of prostate cancer patients from geographically and ethnically diverse cohorts (USA-Caucasian, RSA-Black) were compared to identify gene expression patterns associated with prostate cancer. Methods: Whole blood samples were collected from PCa and controls. Controls had the same age-range as PCa with no clinical indication of prostatic disease and serum PSA levels below 1.5 ng/ml. RNA was isolated, sequencing was carried out on Novaseq 6000, and data analyzed using PartekFlow to identify differential gene expression patterns (RSA-PCa: 6, RSA-Control: 6, USA-PCa: 7, USA-Control: 11). qRT-PCR was undertaken on a cohort of 27 biomarkers (PROSTest) related to PCa in whole blood. Results: Differential expression analysis identified distinct patterns in USA and RSA groups. In the USA PCa cohort, 2,193 genes were differentially expressed compared to the controls with fold change (FC) >1, p-value (p) <0.05, while in the RSA PCa cohort, 1,627 genes were differentially expressed compared to the controls. Pathway analyses identified enrichment for immune responsive genes in the RSA cohorts. We identified that 26 of 27 Wren’s PROSTest genes detectable in both groups. RNAseq and normalized PCR gene expression were well- correlated (r=0.44, p=0.0012, n=30 pairs). Conclusion: Based on this RNAseq study, there may be geographic differences related to ethnicity in overall blood RNA gene expression. We specifically identified alterations in immune function gene expression between the USA and RSA. Importantly, PROSTest genes were detected in both populations and exhibited a significant correlation. Development of gene signatures for biomarker discovery should, however, consider specific ethnicities and geographical regions. Citation Format: Srinivas V Koduru, Mark Kidd, Ané Pieters, S E Nagel, Robert P Millar, Abdel B Halim. Transcriptomic analysis of whole blood samples from prostate cancer patients: A comparative study of patients from geographically diverse populations [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B062.

The role of miR-152 in urological tumors: potential biomarkers and therapeutic targets

Urological malignant tumors pose a significant threat to human health, with a high incidence rate each year. Prostate cancer, bladder cancer, and renal cell carcinoma are among the most prevalent and extensively researched urological malignancies. Despite advancements in research, the prognosis for these tumors remains unfavorable due to late detection, postoperative recurrence, and treatment resistance. A thorough investigation into their pathogenesis is crucial for early diagnosis and treatment. Recent studies have highlighted the close association between microRNAs (miRNAs) and cancer progression. miRNAs are small non-coding RNAs composed of 19-23 nucleotides that regulate gene expression by binding to the 3’ untranslated region (3’UTR) of target mRNAs, impacting key cellular processes such as proliferation, differentiation, apoptosis, and migration. Dysregulation of miRNAs can disrupt the expression of oncogenes and tumor suppressor genes, contributing to cancer development. Among the various miRNAs studied, miR-152 has garnered attention for its role in urological malignancies. Several studies have indicated that dysregulation of miR-152 expression is significant in these cancers, warranting a comprehensive review of the evidence. This review focuses on the expression and function of miR-152 in prostate cancer, bladder cancer, and renal cell carcinoma, elucidating its mechanisms in cancer progression and exploring its potential as a therapeutic target and biomarker in urological malignancies.

Abstract IA005: Tumor cell-based liquid biopsy to characterize prostate cancer

Abstract Circulating Tumor Cells (CTCs) hold the promise of comprehensive yet noninvasive molecular characterization of cancer cells during the course of tumor evolution and progression. To dissect the epigenetic profile of prostate CTCs, we undertook paired DNA methylation and RNA sequencing of single CTCs isolated from blood specimens of patients with prostate cancer. Across the genome, our study identified 40 core Partial Methylation Domains (PMDs) that arise early in tumorigenesis and are shared by all individual CTCs across multiple patients. Key among these is a single genomic locus harboring multiple interferon-inducible genes along with all the CD1 gene family members, implicated in innate immunity. Based on mouse models, we propose that early biallelic silencing of multiple genes residing within a single PMD may contribute to the escape from immune surveillance in prostate and potentially other cancers. Studies of CTC heterogeneity within individual patients are limited by the very small number of cells that can be isolated from standard 10ml blood volumes. To enable such analyses, we applied a new high throughput microfluidic platform, capable of processing an entire leukapheresis product, interrogating 2-3 L of blood volume equivalent. Applying this technology to patients with metastatic prostate cancer, we successfully enriched thousands of CTCs from individual cases, enabling the characterization of intra-patient heterogeneity at the level of cell morphology and marker expression, chromosome copy number variation and exome-wide genotyping, and transcriptionally-defined tumor cell subpopulations. Such high-volume microfluidic enrichment of CTCs constitutes a new dimension in liquid biopsies. Citation Format: Daniel A Haber, Shyamala Maheswaran, Hongshan Guo, Joanna Vuille, Shih-Bo Huang, Ben S Wittner, Lecia V Sequist, Richard J Lee, Patricia AR Brunker, David T Miyamoto, Avanish Mishra, Mehmet Toner. Tumor cell-based liquid biopsy to characterize prostate cancer [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr IA005.

Abstract PR012: A novel plasma-based epigenomic assay for comprehensive profiling of cancerous and inflammatory disease states

Abstract Background: We developed a method for comprehensive epigenomic profiling from 1 ml of patient (pt) plasma, targeting histone modifications and DNA methylation. This approach can be applied to plasma from pts with cancer and inflammatory conditions, allowing us to infer expression levels of diagnostic markers and drug targets, measure activity of therapeutically targetable transcription factors, and detect non-genomic mechanisms of resistance. By examining the transcriptional status of therapeutic gene targets and pathways, our method addresses the need for new approaches in liquid biopsy (LBx) assays, providing clinically actionable information that enhances the understanding of cancer and inflammatory biology and therapeutic response. Methods: We developed an innovative multimodal assay capable of revealing genome-wide transcriptional activity of promoters and enhancers from chromatin, as well as surveying the DNA methylome. Utilizing this assay on plasma samples from pts with 5 non- cancer conditions and 15 different tumor types, we generated comprehensive genome-wide transcriptional profiles across 21 conditions. Results: We identified transcriptional activation in cancer pt plasma of cancer-associated biomarkers (e.g., HER2, DLL3) in a tumor-specific manner and in autoimmune disorders such as rheumatoid arthritis and systemic lupus erythematosus/lupus nephritis. Epigenomic profiling simultaneously inferred the expression of multiple pertinent ADC and radio-immune targets (e.g., MET, HER2, HER3, TROP2, B7H4 in breast cancer and PSMA in prostate cancer), and SLFN11, a biomarker for sensitivity to these agents. The multimodal platform assesses transcriptional regulation genome-wide, enabling analysis of select genes as well as related pathways. For example, a multimodal classifier robustly predicted HER2 status across multiple HER2-expressing tumors. HER2 classification of breast cancer pts by epigenomic LBx was concordant with standard tissue-based IHC for 64/72 (89%) breast cancer samples (AUC 0.9). Accurate classification was achieved for 11/14 (79%) gastroesophageal adenocarcinoma and 4/4 (100%) ovarian cancer pts. A multi-modal predictive model trained on FOLH1 plasma epigenomic regulatory signals demonstrated significant accuracy in predicting quantitative readouts from PSMA PET scans (total SUVmean) in metastatic castration resistance prostate cancer pts and was associated with response to pluvicto. Epigenomic signatures also delineated activation of the endocrine signaling pathway in breast cancer and multiple mechanisms of resistance to androgen receptor signaling inhibition in prostate cancer, including reactivation of the androgen receptor, glucocorticoid signaling bypass, and histological transformation to a neuroendocrine subtype. Conclusions: This comprehensive epigenomic LBx assay offers a platform for simultaneous genome-wide transcriptional assessment of disease and therapy-relevant genes and pathways, marking a paradigm shift in our ability to assess the underlying transcriptional states of cancer and inflammatory diseases. Citation Format: Travis Clark, Anthony D'Ippolito, Aparna Gorthi, Jonathon Beagan, Jamey Guess, Amy Donahue, Mandy Greene, Alyssa Lau, Fernando Ramirez, Kristian Cibulskis, Jenna Wurster, Michael Coyne, Mary McGillicuddy, Baovy Tran, Tyrone Tamakloe, Hathairat Sawaengsri, Corrie Painter, Juliann Chmielecki, Geoff Otto, Matthew Eaton, Carl Barrett. A novel plasma-based epigenomic assay for comprehensive profiling of cancerous and inflammatory disease states [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr PR012.

Abstract B068: Inferring enhancer activity from cell-free DNA fragmentation patterns

Abstract We present a framework for inferring enhancer activity from cell-free DNA (cfDNA) fragmentation patterns, offering a novel feature set for cfDNA analysis that reflects gene regulation. Enhancers are promoter-distal regulatory elements that regulate gene expression programs that define cell types and cellular states. Despite advances in inferring gene regulation in cancer using liquid biopsy, it remains challenging to identify signals of enhancer activity from cell-free DNA (cfDNA). Active enhancers are characterized by transcription of short enhancer RNAs (eRNAs). Recent studies demonstrated that cfDNA from promoters of transcribed genes demonstrates high variation in DNA fragment length, or “fragmentation entropy”. We tested whether eRNA transcription can be inferred based on cfDNA fragmentation entropy. We quantified “enhancer fragmentation entropy” (EFE) to profile enhancer activity in plasma by measuring Shannon entropy of cfDNA fragments around enhancer transcription start sites (TSS). Using PRO-cap data from lymphoblastoid cell lines, we analyzed EFE signals at 70,000 transcribed enhancers and observed distinct patterns between active (expressed) and inactive enhancers in cfDNA from healthy individuals. cfDNA from patients with prostate cancer showed elevated EFE at enhancers activated in prostate cancer. EFE at these sites correlated with circulating tumor DNA (ctDNA) levels in a published cfDNA dataset of 41 prostate cancer plasma samples. Lower-dimensional projections of the entropy signals across 300 “modules” of co-regulated enhancers revealed tighter clustering of samples within the same cancer type, suggesting that these entropy patterns capture cell-type specific enhancer activity. Our findings suggest that enhancer fragmentation entropy captures cell-type specific signals and, when measured at cancer-specific enhancers in cfDNA, could serve as a promising biomarker for cancer detection and monitoring. Ongoing work is focused on validating these findings in larger cohorts and applying EFE to cancer monitoring and clinical subtyping. Citation Format: Alexis Yang. Inferring enhancer activity from cell-free DNA fragmentation patterns [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B068.

Abstract IA011: Heterogeneity of cancer-derived extracellular vesicles

Abstract Extracellular vesicles (EVs) are heterogenous in size, biogenesis, cargo and function. Beside small EVs, aggressive tumor cells release a population of particularly large EVs, namely large oncosomes (LO). This study provides the first resource of label-free quantitative proteomics of LO and small EVs obtained from distinct cancer cell types (prostate, breast, and glioma). This dataset was integrated with a SWATH Proteomic assay on LO, rigorously isolated from the plasma of patients with metastatic prostate cancer (PC). Proteins enriched in LO, which were identified also at the RNA level, and found in plasma LO significantly correlated with PC progression. Single EV RNA-Seq of the PC cell-derived LO confirmed some of the main findings from the bulk RNA-Seq, providing first evidence that single cell technologies can be successfully applied to EVs. This multiomics resource of cancer EVs can be leveraged for developing a multi-analyte approach for liquid biopsy. Citation Format: Dolores Di Vizio. Heterogeneity of cancer-derived extracellular vesicles [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr IA011.

Utility of Multiparametric Prostate MRI to Predict Regional or Distant Metastatic Disease Against Conventional Staging Using CT and Bone Scintigraphy or 68Ga-PSMA PET in Intermediate-to-High-Risk Prostate Cancer

Utility of Multiparametric Prostate MRI to Predict Regional or Distant Metastatic Disease Against Conventional Staging Using CT and Bone Scintigraphy or 68Ga-PSMA PET in Intermediate-to-High-Risk Prostate Cancer

CAGn Polymorphic Locus of Androgen Receptor (AR) Gene in Russian Infertile and Fertile Men

The androgen receptor (AR) is critical for mediating the effects of androgens. The polymorphic CAGn locus in exon 1 of the AR gene is associated with several diseases, including spinal and bulbar muscular atrophy (SBMA), prostate cancer, and male infertility. This study evaluated the CAGn locus in 9000 infertile Russian men and 286 fertile men (control group). The CAGn locus was analyzed using the amplified fragment length polymorphism method. In the infertile cohort, the number of CAG repeats ranged from 6 to 46, with a unimodal distribution. The number of CAG repeats in infertile and fertile men was 22.15 ± 0.93 and 22.02 ± 1.36, respectively. In infertile men, variants with 16 to 29 repeats were present in 97% of the alleles. A complete mutation (≥42 CAG repeats) was found in three patients, while three others had 39-41 repeats. The incidence of SBMA was 1:3000 infertile men. Significant differences (p < 0.05) were observed between infertile and fertile men in alleles with 21, 24 and 25 repeats. This study revealed certain differences in the CAGn polymorphic locus of the AR gene in Russian infertile and fertile men and determined the frequency of SBMA in infertile patients.

Abstract A056: Performance of multi-biomarker class reflex testing in a prospectively-collected cohort

Abstract Background: A multi-biomarker blood test has the potential to detect cancers in a broad range of organ types and stages. We previously trained and independently assessed the performance of two biomarker classes (methylation and protein; MP) for multi-cancer early detection (MCED) in a prospectively collected study (Cancer Res,2024;84(7Supp):LB100). Here, we assessed the addition of a somatic mutation reflex approach to samples with initially negative MP-results (MP-reflex; MP-r). Methods: This study included 3,160 samples (739 cancer and 2421 non- cancer) representing 20 organ types and all stages. Samples with negative MP results at a specificity threshold of ≥ 98.5% and detectable MP signals above pre-specified lower thresholds were analyzed for mutations using next generation sequencing. Classifier models and thresholds were developed using an independent training set. Sensitivity of the MP biomarker classifier was determined at a combined specificity of ≥98.5%. We also compared the performance of MP and MP-r configurations with prostate (n=52) and breast (n=88) organ types excluded. Results: At 98.5% specificity, the observed overall sensitivity for MP was 52.9%, with sensitivities of 15.3%, 39.8%, 71.2%, 87.2%, 26.7% and 37.5% for stages I, II, III, IV, I/II and unknown, respectively. At the same specificity of 98.5%, when an MP-r configuration was utilized, overall sensitivity was 55.8%, with sensitivities of 19.1%, 42.2%, 72.3%, 89.9%, 29.9% and 46.9% for stages I, II, III, IV, I/II and unknown, respectively. MP-r demonstrated absolute sensitivity increases of 3.8%, 2.5%, 1.1 %, 2.8%, 3.2%, 9.4%, and 2.8%, for stages I, II, III, IV, I/II, unknown, and overall, respectively. When breast and prostate cancers were excluded, test sensitivity for MP was 59.3%, with sensitivities of 17.2%, 51.9%, 76.4%, 88.3%, 31.9% and 41.4% for stages I, II, III, IV, I/II and unknown, respectively. When an MP-r configuration was utilized, overall sensitivity was 62.3% %, with sensitivities of 22.1%, 54.7%, 76.4%, 91.4%, 35.9% and 51.7% for stages I, II, III, IV, I/II and unknown, respectively. MP-r demonstrated absolute sensitivity increases of 4.8 %, 2.8%, 0.0%, 3.1%, 4.0%, 10.3%, and 3.0% for stages I, II, III, IV, I/II, unknown, and overall, respectively. Conclusions: Compared to MP alone (breast and prostate cancers excluded), an MP-r approach results in a relative sensitivity increase of 28% in Stage I cancers and 12.5% for Stage I/II cancers. MP-r is an efficient strategy to add a third biomarker class and enhance sensitivity of MP for the detection of early-stage cancer. Citation Format: Vladimir Gainullin, Jin Bae, Violeta Beleva Guthrie, Fanglei Zhuang, Chen Ji, Christopher Tyson, Mark Evans, Kevin Arvai, Melissa Gray, Madhav Kumar, Mael Manesse, Xi Chen, Philip Uren, Gustavo C. Cerqueira, Amin Mazloom, Jorge Garces, Tomasz M. Beer, Frank Diehl. Performance of multi-biomarker class reflex testing in a prospectively-collected cohort [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr A056.

Abstract B049: Validation of the PGDx elio™ plasma complete for comprehensive genomic profiling of solid tumors through liquid biopsy with Epic Sciences

Abstract Introduction: To help guide treatment decisions and enable clinical trial matching for cancer patients, tissue-based comprehensive genomic profiling (CGP) is an essential precision oncology tool. Liquid biopsy may be used as a complementary approach to assess tumor-specific DNA alterations circulating in the blood when tissue is limited or unavailable. PGDx’s elio™ plasma complete is a next-generation-sequencing (NGS), cell-free DNA (cfDNA) CGP assay that identifies clinically significant variants from the plasma of patients with advanced and metastatic solid cancers. Methods: The PGDx elio plasma complete is a hybrid-capture, DNA-based kitted solution, optimized for 25 ng of cfDNA input with a targeted panel covering coding exons for 521 genes, and is designed to detect single nucleotide variants (SNVs), small insertions and deletions (indels), copy number amplifications (CNAs), and translocations. It also evaluates blood MSI and tumor mutational burden (bTMB) to guide immunotherapy selection. This study presents the validation of the PGDx elio plasma complete assay to enable the processing of patient blood samples in Epic Sciences' CAP/CLIA-certified laboratory. In the validated configuration, patient plasma will be received and isolated at Epic Sciences and subsequently shipped to PGDx/Labcorp Oncology for cfDNA extraction, library preparation, sequencing, and bioinformatics analysis. Finally, clinical report generation will be carried out by Velsera’s CGW software. Analytical validation was assessed using 105 replicates of SeraCare® (n=21) and Horizon (n=3) reference materials to establish analytical sensitivity, accuracy, and reproducibility and repeatability. Specificity was assessed using 20 non-cancerous plasma samples that were also tested orthogonally. For clinical validation a cohort of >150 cancer patient plasma samples were evaluated, including lung, breast, colorectal, head and neck, pancreatic, and prostate cancers, and compared to Illumina’s TSO500 ctDNA or Labcorp Plasma Focus results. Results: Analytical sensitivity and specificity were evaluated for SNVs, indels, CNAs, fusions, MSI and bTMB. Across all variant types, sensitivity was ≥90%, and specificity was ≥95% at LoDs. The reproducibility and repeatability study resulted in ≥95% agreement for all variant types. Analytical sensitivity was calculated using vendor-verified variants in each control. SeraCare® controls and Horizon reference materials were used to assess variant concordance with an aggregate analytical performance across all control samples with ≥95% PPA and NPA for all variant types. Conclusions: The validation of the PGDx elio plasma complete liquid biopsy assay as part of the Epic Sciences' CAP/CLIA diagnostic workflow for cfDNA-based NGS demonstrates that the liquid biopsy approach is highly sensitive, specific, accurate, reproducible, and robust for comprehensive genomic profiling to complement tissue- based testing and inform clinical decision making. Citation Format: Cynthia Maddox, Kenneth C Valkenburg, Cesar Nalvarte, Amanda Harvey, Amy Greer, Ellen L Verner, Renee L Sears, Martin Blankford, Eric A Severson, Taylor J Jensen, Marcia Eisenberg, Shakti Ramkissoon. Validation of the PGDx elio™ plasma complete for comprehensive genomic profiling of solid tumors through liquid biopsy with Epic Sciences [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B049.

Intrahepatic Cholangiocarcinoma Presenting as an Incidentaloma on F-18 PYL PSMA PET/CT

AbstractCholangiocarcinoma is an aggressive malignancy arising from the biliary tract epithelium with rising incidence and mortality. Imaging commonly used for diagnostic workup includes computed tomography (CT) scan and magnetic resonance imaging (MRI). Fluorine-18 fluorodeoxyglucose positron emission tomography (FDG PET) scans can be used for investigating equivocal findings on radiographic imaging. Prostate-specific membrane antigen (PSMA) is known to be highly expressed in prostate adenocarcinoma, allowing it to be leveraged as a target for both imaging and radioligand therapy in prostate cancer. However, PSMA is also commonly expressed in other malignancies such as breast cancer, thyroid carcinomas, and head and neck malignancies, which increase the chances of their incidental diagnosis on PSMA PET scans. Biliary tract cancers, including cholangiocarcinoma, are not commonly expected to be incidentally diagnosed on PSMA PET imaging. Here, we describe the case of a patient with known prostate adenocarcinoma who was later incidentally diagnosed with advanced intrahepatic cholangiocarcinoma on PSMA PET/computed tomography (CT). This case highlights the unexpected finding of cholangiocarcinoma on PSMA PET/CT and suggests further investigation into the role of PSMA PET in diagnosing ambiguous cases of cholangiocarcinoma and its potential theranostic applications.

Periodontitis promotes tumor growth and immune evasion via PD-1/PD-L1.

Our study investigated the role of experimental periodontitis on tumor growth, local and systemic immunosuppressive status, and programmed death receptor 1 (PD-1) / programmed death ligand 1 (PD-L1) expression in oral squamous cell carcinoma (OSCC) and prostate cancer. Mouse oral or prostate cancer xenograft models were divided into control, periodontitis and periodontitis + anti-PD-1 groups. Tumor volume and weight were recorded and the levels of relevant immune-suppressive cells and T cells were detected by flow cytometry or immunofluorescence. THP-1 cells were stimulated using conditioned media of LPS-stimulated Cal-27 cells and PD-L1 expression was measured by quantitative real-time PCR, western blotting and immunofluorescence. Tumor specimens from OSCC patients with or without periodontitis were also collected for immunofluorescence. Periodontitis significantly promoted tumor volume and weight. Compared to the control, the proportions of tumor-associated macrophages (TAMs), regulatory T cells (Tregs), PD-L1+TAMs and PD-1+CD8+T cells increased, while CD8+T cells decreased in the periodontitis group. Immunofluorescence demonstrated that there was an increase in PD-L1+TAMs and PD-1+CD8+T cells, but a decrease in IFN-γ+CD8+T cells in both xenografts and clinical OSCC samples with periodontitis. In vitro, LPS-stimulated Cal-27 cells had a stronger potential to induce PD-L1 expression in macrophages compared with unstimulated Cal-27 cells. And the promoting effect of periodontitis on tumor growth and immune evasion was significantly attenuated after anti-PD-1 therapy. Periodontitis may facilitate tumor growth and immune escape evidenced by the increased immune-suppressive cells and the decreased functional T cells, via enhancing PD-1/PD-L1 expression in the tumor microenvironment.

Abstract A031: Harnessing the potential of circulating tumour cells for precision diagnostics via multiplexed imaging of the levels and subcellular localizations of over 50 cell identity, state and signaling markers per cell

Abstract Due to their longitudinal accessibility through liquid biopsy, circulating tumour cells (CTCs) hold huge potential as sources of molecular information capable of underpinning precision diagnostics in cancer. Yet key methodological limitations have thus far constrained the practical utility of CTCs as diagnostic analytes, including: a) reliance on positive CTC selection strategies that can bias against distinctive CTC subpopulations (e.g. low EpCAM, low size, low density), and; b) standard fluorescence imaging methods that capture only 4-6 molecular markers per cell. Since 3-4 markers are required to identify CTCs with even moderate confidence, such low marker plexity acutely restricts derivation of additional molecular insights about the cellular states and molecular signals that may be driving disease. Yet these insights are essential to guide selection of optimal therapies, to adapt therapeutic strategies as cycles of resistance arise, and even to stratify patients to the trials needed to expand the therapeutic arsenal. To overcome these challenges and harness the potential of CTCs for precision diagnostics, we have developed a comprehensive pipeline for CTC isolation, storage and batch processing via multiplexed immunofluorescence imaging of 50+ molecular markers per cell. These markers illuminate CTC identity, state (epithelial vs mesenchymal vs stemness), fate (proliferation, death, senescence) and signalling (spanning ∼10 alternate ‘driver’ signalling pathways), providing truly unprecedented molecular insights per CTC, across heterogeneous CTC populations, and regarding potential therapeutic targets. Downstream single-cell quantitative image analyses enable robust but adaptable computational parsing of CTC identity, removing false-positive and false-negative instances otherwise resulting from standard 4-plex CTC definitions (e.g. DAPI, CD45, EpCAM, pan-Cytokeratin) and complementing our upstream use of negative selection methods that capture the full, unbiased diversity of CTCs. The remaining 40+ markers facilitate integrated analyses of relationships between CTC state, fate and signalling pathways, capturing not only protein and phospho-protein expression levels per cell, but also variations in subcellular localisation that constitute additional layers of functional regulation not captured by most omics methods. Excitingly, when combined with machine learning, our approach can discern therapy- resistant cell subpopulations with over 98% accuracy in models of prostate cancer therapy resistance. We are now assessing CTC diversity across patients ranging from treatment naïve to advanced castrate-resistance prostate cancers. Overall, our unique high-plexity analysis now enables interrogation of detailed states, signals and dependencies in each patient CTC, providing the foundations for next-generation precision diagnostics to continuously match individual patients to optimal therapies at each stage of their disease journey. We believe this marks a significant step towards harnessing the true potential of CTCs for precision diagnostics. Citation Format: John G Lock, Tim J Mann, Ye Zheng, Tanzila Khan, Daniel Neumann, Alexander James, Therese Becker, Tara Roberts. Harnessing the potential of circulating tumour cells for precision diagnostics via multiplexed imaging of the levels and subcellular localizations of over 50 cell identity, state and signaling markers per cell [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr A031.

Prostate Cancer Risk Prediction Model Using Clinical and Magnetic Resonance Imaging–Related Findings: Impact of Combining Lesions' Locations and Apparent Diffusion Coefficient Values

Objectives The aims of the study are to develop a prostate cancer risk prediction model that combines clinical and magnetic resonance imaging (MRI)–related findings and to assess the impact of adding Prostate Imaging-Reporting and Data System (PI-RADS) ≥3 lesions-level findings on its diagnostic performance. Methods This 3-center retrospective study included prostate MRI examinations performed with clinical suspicion of clinically significant prostate cancer (csPCa) between 2018 and 2022. Pathological diagnosis within 1 year after the MRI was used to diagnose csPCa. Seven clinical, 3 patient-level MRI-related, and 4 lesion-level MRI-related findings were extracted. After feature selection, 2 logistic regression models with and without lesions-level findings were created using data from facility I and II (development cohort). The area under the receiver operating characteristic curve (AUC) between the 2 models was compared in the PI-RADS ≥3 population in the development cohort and Facility III (validation cohort) using the Delong test. Interfacility differences of the selected predictive variables were evaluated using the Kruskal-Wallis test or chi-squared test. Results Selected lesion-level features included the peripheral zone involvement and apparent diffusion coefficient (ADC) values. The model with lesions-level findings had significantly higher AUC than the model without in 655 examinations in the development cohort (0.81 vs 0.79, respectively, P = 0.005), but not in 553 examinations in the validation cohort (0.77 vs 0.76, respectively). Large interfacility differences were seen in the ADC distribution (P < 0.001) and csPCa proportion in PI-RADS 3–5 (P < 0.001). Conclusions Adding lesions-level findings improved the csPCa discrimination in the development but not the validation cohort. Interfacility differences impeded model generalization, including the distribution of reported ADC values and PI-RADS score-level csPCa proportion.

Abstract PR019: Transfer learning for accurate tissue of origin classification from cfDNA methylation

Abstract Accurately predicting the tissue of origin (TOO) is required for blood-based multi-cancer screening to guide follow-up imaging and care when cancer is detected. However, precisely determining the TOO using cell-free DNA (cfDNA) methylation remains challenging due to low and variable concentrations of circulating tumor DNA and cfDNA and the complex, poorly characterized nature of tissue-specific methylation patterns. To address these challenges, we developed a transfer learning approach that leverages methylation profiles learned from tissue biopsy samples to predict the TOO of cfDNA cancer samples. Our model achieved 89% balanced accuracy (BA) in classifying the TOO across 10 cancer groups and outperformed models trained solely on plasma cfDNA data. Unmatched tissue biopsy (N=517) and blood (N=1,155, NCT05435066) samples were collected from treatment-naïve cancer patients across 21 tumor types consolidated into 17 cancer groups. All samples were analyzed using a custom targeted bisulfite sequencing hybrid capture assay. Five unique metrics were used to quantify informative methylation signal at each TOO region of interest. A feed-forward neural network was first trained on biopsy methylation features, where the cancer signal is strongest. Subsequently, the model was fine-tuned using plasma cfDNA methylation features, which have significantly lower signal-to-noise ratio, allowing the model to adapt its predictions to the noisier data. The Adam optimizer was employed for both training and fine-tuning, with early stopping implemented to prevent overfitting. Dropout layers were incorporated to enhance model generalization and performance was evaluated using 10-fold cross validation on plasma cfDNA samples across 10 cancer groups for which at least 25 plasma samples were available (N=1,041). The same architecture was trained exclusively on plasma cfDNA samples for comparison. Results are reported for samples with tumor content greater than 0.1% (N=415). Our TOO prediction achieved 73% BA in top-one predictions, where the true label matched the highest probability prediction, and 89% BA in top-two predictions, where the true label matched the highest or the second-highest probability prediction. Multi-class classification revealed our method significantly outperforms a model trained only on plasma cfDNA data. The plasma only model achieved 69% and 82% BA in top-one and top-two predictions, respectively. Accuracy per indication revealed that training on biopsy data significantly improves the detection of tumor types that shed DNA at low rates compared to training on plasma data alone (breast cancer +14%, prostate cancer +12%, and uterine cancer +20% points). In conclusion, our transfer learning approach, utilizing tissue biopsy methylation data, significantly improves cfDNA-based TOO detection accuracy. This approach highlights the capability of transfer learning to enable automated feature extraction from signal-rich data to enhance the analysis of more challenging, heterogeneous cfDNA samples, advancing non-invasive cancer diagnostics. Citation Format: Shiva Farashahi, Amirali Kia, Dorna Kashef, Esther Brown, Feras Hantash, Kieran I Chacko. Transfer learning for accurate tissue of origin classification from cfDNA methylation [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr PR019.

Abstract IA026: Methods for tumor subtype classification using cell-free DNA

Abstract Accurately diagnosing the tumor histological subtype is crucial for clinical care. Changes in subtype can emerge during treatment resistance. However, obtaining a biopsy to determine the tumor histology presents challenges for patients with advanced cancers. Circulating tumor DNA (ctDNA) is a non-invasive 'liquid biopsy' solution that overcomes this limitation of tissue accessibility. Current ctDNA approaches primarily focuses on detecting genetic mutations, but these alterations alone may not fully delineate tumor histological subtypes or explain treatment resistance. Recent advancements highlight the value of epigenetic information obtained from profiling nucleosome positioning and accessibility in ctDNA. I will discuss how we applied these concepts to develop computational methods for predicting transcriptional activity and classifying tumor subtypes and phenotypes in breast, prostate, and lung cancers. These tools have applications in monitoring treatment-induced phenotype changes and expand on the utility of ctDNA for precision oncology. Citation Format: Gavin Ha. Methods for tumor subtype classification using cell-free DNA [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr IA026.

Trop2-Targeted Molecular Imaging in Solid Tumors: Current Advances and Future Outlook.

Trophoblast cell surface antigen 2 (Trop2), a transmembrane glycoprotein, plays a dual role in physiological and pathological processes. In healthy tissues, Trop2 facilitates development and orchestrates intracellular calcium signaling. However, its overexpression in numerous solid tumors shifts its function toward driving cell proliferation and metastasis, thus leading to a poor prognosis. The clinical relevance of Trop2 is underscored by its utility as both a biomarker for diagnostic imaging and a target for therapy. Notably, the U.S. Food and Drug Administration (FDA) has approved sacituzumab govitecan (SG), a novel Trop2-targeted agent, for treating triple-negative breast cancer (TNBC) and refractory urothelial cancer, highlighting the significance of Trop2 in clinical oncology. Molecular imaging, a powerful tool for visualizing and quantifying biological phenomena at the molecular and cellular levels, has emerged as a critical technique for studying Trop2. This approach encompasses various modalities, including optical imaging, positron emission tomography (PET), single photon emission computed tomography (SPECT), and targeted antibodies labeled with radioactive isotopes. Incorporating Trop2-targeted molecular imaging into clinical practice is vital for the early detection, prognostic assessment, and treatment planning of a broad spectrum of solid tumors. Our review captures the latest progress in Trop2-targeted molecular imaging, focusing on both diagnostic and therapeutic applications across diverse tumor types, including lung, breast, gastric, pancreatic, prostate, and cervical cancers, as well as salivary gland carcinomas. We critically evaluate the current state by examining the relevant applications, diagnostic accuracy, therapeutic efficacy, and inherent limitations. Finally, we analyze the challenges impeding widespread clinical application and offer insights into strategies for advancing the field, thereby guiding future research endeavors.