tbuckley/cabot-search huggingface dataset:
Impact of liquid biopsies on early detection, monitoring, and prognostication in prostate cancer: A meta-analysis of emerging evidence.
Authors: Muhammad Nabeel Saddique, Atif Hussain Sarwar, Hashim Talib Hashim, Ahmed Qasim Mohammed Alhatemi, Sheena Shamoon
Journal: Journal of Clinical Oncology (2025)

32 Background: Prostate cancer remains a leading cause of cancer-related morbidity and mortality among men worldwide. Traditional diagnostic and monitoring techniques often lack sensitivity and specificity, particularly in early stages. Liquid biopsies, which analyze circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA) from blood samples, have emerged as a promising non-invasive alternative for early detection, monitoring disease progression, and prognostication in prostate cancer. Methods: The PubMed, Embase, Scopus and Cochrane databases were systematically searched from inception until June 2024 using relevant keywords. We analyzed the pooled data as untransformed proportions with 95% confidence intervals (CI) using Random Effects model in OpenMeta (version 5.3). The I 2 and X 2 statistics were used to evaluate inter-study heterogeneity. An I 2 value of &gt;50% was considered significant heterogeneity. Subgroup analyses were performed to assess the diagnostic accuracy, prognostic value, and clinical utility of CTCs and ctDNA. Results: A total of 30 studies involving 5,200 prostate cancer patients were included in the meta-analysis. Liquid biopsies demonstrated a pooled sensitivity of 85% (95% CI: 80%-90%) and a specificity of 88% (95% CI: 83%-92%) for early detection of prostate cancer. CTCs and ctDNA levels were significantly correlated with tumor burden, Gleason score, and metastatic potential. Furthermore, elevated levels of CTCs and ctDNA were associated with poorer overall survival and progression-free survival, underscoring their prognostic value. Conclusions: Liquid biopsies offer a robust, non-invasive method for the early detection, monitoring, and prognostication of prostate cancer. This meta-analysis highlights their potential to improve clinical outcomes through timely and accurate disease management. Future research should focus on standardizing methodologies and integrating liquid biopsies into routine clinical practice.
Utilizing ChatGPT for assessing disease volume in patients (pts) with metastatic prostate cancer (mPC).
Authors: Diya Garg, Micah Ostrowski, Ayana Srivastava, Beverly Chigarira, Yeonjung Jo, Zeynep Irem Ozay, Chadi Hage Chehade, Georges Gebrael, Nicolas Sayegh, Gliceida Galarza Fortuna, Vinay Mathew Thomas, Benjamin L. Maughan, Umang Swami, Neeraj Agarwal, Haoran Li
Journal: Journal of Clinical Oncology (2025)

42 Background: Artificial intelligence (AI) has transformed many aspects of healthcare, particularly in medical imaging analysis. In mPC, accurate identification of bone metastases is crucial in guiding pt management. This proof-of-concept study explores the application of ChatGPT-4o, a multimodal, generative pre-trained transformer (large language model) with emerging image recognition capabilities, in diagnosing bone metastases from bone scans and determining disease volume in pts with mPC. Methods: In this IRB-approved, retrospective study, pts with newly diagnosed mPC and bone-predominant disease were randomly selected. Those who had previously received bone-protecting agents, chemotherapy, hormone therapy, or radiation therapy prior to the bone scan were excluded. Using CHAARTED criteria, high-volume versus low-volume bone disease was classified based on radiologist reports. The bone scan images were then uploaded to ChatGPT, which was instructed to act as a radiologist and asked to classify the disease volume. ChatGPT's classifications were compared to the radiologists’ findings by using Cohen’s Kappa test. Confusion’s matrix was used to represent the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of ChatGPT. Results: A total of 110 pts were selected, with a median age of 67 years (range: 44 to 89). The majority were Caucasian (98.2%). The median Gleason score was 9, and 77.3% of pts had de novo metastatic disease. The median PSA value at diagnosis was 35.2 ng/ml (range: 1-5843). High-volume disease was present in 52% of pts. ChatGPT's overall concordance with radiologists was 74% (Cohen's Kappa = 0.65). For high-volume disease, ChatGPT demonstrated a high sensitivity of 92.3% (48/52). However, it misclassified 45.8% of low-volume cases as high-volume (specificity: 54.2%). The PPV and NPV of ChatGPT were 68.6% and 86.7%, respectively. Interestingly, ChatGPT’s accuracy was significantly higher when each case was analyzed individually (77.7%) compared to when cases were grouped in a single conversation (43.5%, p&lt;0.001). Conclusions: This hypothesis-driven research demonstrated that ChatGPT-4o has the potential to read medical images independently and apply existing knowledge, such as the CHAARTED criteria, to assist in content generation. However, its reliability remains a significant challenge for broader use in healthcare. Notably, it exhibited "information fatigue," where accuracy significantly declined when similar or repetitive information accumulated within a single conversation.
Decipher genomic classifier (DGC) of early prostate cancer (EPC), and underlying transcriptomic profile (TP): American (Am) versus non-American (NA).
Authors: Daniel Keizman, Elai Davicioni, Avivit Peer, David Sarid, Keren Rouvinov, Avishay Sella, Hadas Dresler, Yoav Manaster
Journal: Journal of Clinical Oncology (2025)

414 Background: Data on DGC in EPC, come predominantly from US patients (pts), revealing significant reclassification of NCCN risk Despite its global use, data among NA is scant. We aimed to analyze DGC results and TP among NA versus (vs) Am with EPC Methods: From the DGC database (Decipher Biosciences Inc), we identified and analyzed the results (risk and TP) of Israeli (Is) vs matched Am pts with EPC. Matching was according to common NCCN clinicopathologic features (T and N stage, Gleason grade, number of adverse pathologic features). Results: Among Is pts, 692 (median age, ma, 69) had a biopsy (bx) DGC, and 115 (ma 67) a post prostatectomy (PP) DGC. Their median DGC in bx was 0.47, and PP 0.78. DGC risk was 45% low, 24% intermediate, 31% high, in bx, and 13% low, 16% intermediate, 71% high, PP. Bx DGC led to reclassification of risk in 33% of pts with clinical NCCN low-favorable intermediate risk, and 48% of pts with clinical NCCN unfavorable intermediate-high risk. Among matched Am, 103,108 (ma 68) had a bx DGC, and 40,906 (ma 65) a PP DGC. Am median DGC was 0.43 in bx, and 0.65 PP. Am DGC risk was 52% low, 20% intermediate, 28% high, in bx, and 28% low, 17% intermediate, 55% high, PP. While NCCN risk grouping was similar between Is vs matched Am (p=1.0), median DGC risk was significantly higher among Is (p&lt;0.001), and the distribution of DGC risk groups significantly different (p=0.004 for bx, p&lt;0.001 PP). A correlative TP analysis revealed greater overall differences of Isi vs matched Am. Significant (p&lt;0.001) differences in bx DGC, included AR status (intact vs deficient), prostate subtype classifier (PSC, luminal differentiated, luminal proliferating, basal immune, basal neuroendocrine), PAM50 (Luminal A, Luminal B, Basal), RSI (1), Cell cycle progression (2), activated CD8, T regulatory cells, angiogenesis (Uhlik), Myeloid derived suppressor cells, Interferon response alpha hallmark, and immune 190. Significant (p&lt;0.001) differences in PP DGC, included AR activity, p53 mutation, PSC, PAM50, SC/NE (adenocarcinoma, neuroendocrine carcinoma (3), RSI, activated CD4 and CD8, T regulatory cells, angiogenesis (Uhlik), tertiary lymphoid structure, PDL2 signature, Myeloid derived suppressor cells, and Interferon response alpha hallmark. Conclusions: In early prostate cancer, as previously reported among American pts, DGC may be an important tool for accurate patients risk assessment, leading to NCCN risk reclassification in a significant proportion, Furthermore, the present study preliminary results suggest that geographic variation DGC may exist, and correlate with differences in transcriptomic profile. 1. Torres-Roca 2009. 2. Cuzick 2011. 3. Beltran 2016.
Novel urine-enriched RNA panel (EPCAM, TTC3, H4C5) to detect prostate cancer and differentiate it from benign prostatic disease.
Authors: Ranjan Joseph Perera, Menglang Yuan, Marcio Moschovas, Roshane Perera, Ernest Amankwah, Bongyong Lee, Guru P. Sonpavde, Vipul Patel, Christian P. Pavlovich, Kandarp Joshi
Journal: Journal of Clinical Oncology (2025)

31 Background: Prostate Cancer (PCa) is one of the leading causes of cancer deaths among men worldwide. Although the Prostate-Specific Antigen (PSA) test is widely used for screening, several advisory groups recommend against PSA because of its non-specific and suboptimal performance. Hence, there is an urgent unmet need for novel and more accurate biomarker panels for PCa detection. Methods: To develop an alternate assay, we collected voided urine (50 ml) from 236 pre- and 198 matched post-prostatectomy men with PCa, 76 benign prostatic hyperplasia (BPH), 21 prostatitis and 107 normal healthy men between the years 40-80. We isolated RNA from exfoliated cells and debris shed into urine, subjected to deep-sequencing of 50 selected genes (adj P value &lt; 0.05 and log FC &gt; 2), and performed advanced machine-learning approaches to discover potential biomarkers in men with PCa. Results: From 50 RNAs initially tested in 20 pooled urine samples, 3 RNAs (EPCAM, TTC3, H4C5) were identified to detect men with PCa robustly (with higher specificity and sensitivity) and distinguished them between pre- and post-prostatectomy in PCa patients. The biomarkers, in combination, outperformed a known urinary RNA marker, PCA3 (area under the curve, 0.96, Figure 1 left). Immunohistochemistry and qPCR analysis in prostate FFPE tissues further confirmed that the origin of these three biomarkers is prostate-specific. In addition, the biomarker panel could separate PCa from benign prostatic disease (area under the curve, 0.89), where both diseases show a higher elevation of PSA. TTC3 and EpCAM gene silencing in PCa cells showed a tumor suppression in vitro and in vivo , suggesting its relevance to PCa development. Conclusions: The urine-based RNA biomarker panel (EPCAM, TTC3, H4C5) is a promising noninvasive diagnostic tool to separate PCa from BPH/prostatitis and healthy individuals; further prospective validation is warranted.
Optyx study: Clinical characteristics and preferences for initiating relugolix in a cohort of US patients in real-world care settings.
Authors: Daniel Eidelberg Spratt, Rana R. McKay, Ashley Ross, Benjamin H Lowentritt, Scott C Flanders, Yi Zhong, Agnes Hong, Michael Ryan, Tanya B. Dorff
Journal: Journal of Clinical Oncology (2025)

67 Background: Relugolix is the only oral androgen deprivation therapy indicated for advanced prostate cancer (PC). The OPTYX study is the first prospective study to collect evidence on the long-term safety, effectiveness, treatment patterns, disease course, and patient outcomes with relugolix in real-world care. Enrollment is completed and this analysis assessed key baseline variables, reasons for starting relugolix, and treatment patterns. Methods: The multi-center observational OPTYX study enrolled men with PC starting relugolix across various disease stages and treatment regimens (e.g., mono or combination therapy). Enrollment occurred in diverse clinical settings including urology, oncology, and radiation oncology. Eligibility required intent to treat with relugolix for more than 4 months. Data collected included baseline demographics, clinical characteristics, reasons for initiating treatment, treatment patterns, and quality of life (FACT-P) questionnaires from Oct 2022 to Sept 2024. Results: By September 2024, 999 men were enrolled and received relugolix with a median treatment duration of 242 days. The median age was 71 years; 77.4% self-identified as White, 16.4% as Black. Over 80% submitted FACT-P questionnaires at baseline. Disease states included localized (42.0%), locally advanced (16.7%), biochemical recurrence (11.2%), metastatic castration sensitive PC (18.7%), non-metastatic (1.5%), metastatic castration resistant PC (4.8%), and unknown (5.0%). Of these, 476 men (47.7%) received relugolix in combination with other PC therapies including radiation and systemic therapies. Prior ADT was reported in 21.0% of patients. Mean (SD) baseline testosterone and PSA were 293.1 (227.8) ng/dL and 61.3 (342.4) ng/mL, respectively. The top reasons physicians prescribed relugolix were preference for oral over injection administration (41.5%), rapid testosterone suppression (34.6%), and safety (29.0%), while patients reported physician recommendation (72.3%), oral over injection (36.4%), and rapid testosterone recovery (10.2%). Conclusions: The OPTYX study enrolled 999 patients to assess real-world experience with relugolix. Nearly half started relugolix with other therapies. Many patients and physicians preferred the oral formulation, and other top reasons for initiation included safety and rapid testosterone suppression and recovery. Clinical trial information: NCT05467176 . Relugolix Initiation Preference n (%) By Physician By Patient Oral Instead of Injection 415 (41.5) 364 (36.4) Rapid Testosterone Suppression 346 (34.6) 98 (9.8) Safety Profile 290 (29.0) 95 (9.5) Efficacy Data 255 (25.5) 66 (6.6) Rapid Testosterone Recovery 209 (20.9) 102 (10.2) Tolerability 119 (11.9) 55 (5.5) Co-morbid Disease 76 (7.6) 17 (1.7) Physician Recommended 60 (6.0) 722 (72.3) Other/Unknown 45 (4.5) 22 (2.2)
Pathological subclassification of T3 upper tract urothelial carcinoma: Complementary evidence for existing guidelines.
Authors: Lei Zheng, Jianjun Ye, Qihao Wang, Qiang Wei, Yige Bao
Journal: Journal of Clinical Oncology (2025)

841 Background: According to the current guidelines, upper tract urothelial carcinoma (UTUC), which encroaches beyond the muscularis propria but does not invade peripheral organs or perirenal fat, is classified as pathological T3 (pT3). However, the current classification definition of pT3 fails to meet clinical needs due to the significant heterogeneity of pT3 UTUC in terms of biological features and oncological outcomes. Therefore, the aim of this study was to explore the effect of subclassifying pT3 UTUC on oncological outcomes based on a large UTUC cohort from Southwest China. Methods: Data of pathologically confirmed UTUC patients treated with radical nephroureterectomy (RNU) treatment at West China Hospital of Sichuan University from May 2003 to June 2019 were retrospectively collected. Only patients with a diagnosis of initial pT3 and complete follow-up information were included in the study. pT3 was subclassified into pT3a (defined as tumor invasion of the ureteral adventitia or renal parenchyma) and pT3b (defined as tumor invasion of the ureter or peri-pelvic fat). The primary endpoints included cancer-specific survival (CSS), overall survival (OS) and recurrence-free survival (RFS). Results: A total of 326 patients with initial pT3 UTUC were finally included. According to our proposed subclassification, 232 cases were in pT3a group and 94 cases were in pT3b group. K-M analysis showed that the patients in pT3b group had significantly worse OS, CSS and RFS than those in pT3a group. Multifactorial Cox regression analysis demonstrated that patients in pT3b group had a 1.86-fold (95% CI, 1.19-2.91) risk of death, a 1.95-fold (95% CI, 1.21-3.17) risk of disease-related death and a 1.78-fold (95% CI, 1.21-3.17) risk of disease recurrence than those in the pT3a group. After adjustment for tumor size, tumor grade and lymph node metastasis the above findings remained statistically significant. Conclusions: Based on the presence or absence of invasion of the ureter and peri-pelvic fat, our study proposes a novel pT3 subclassification, which provide physicians with invaluable insight into better stratification of pT3 UTUC patients and provide a basis for individualized treatment.
Development of an miRNA signature for individual prognostic assessment in seminoma patients.
Authors: Julia Heinzelbecker, Farzaneh Zohari, Lea Eckhart, Hiresh Ayoubyan, Hans-Peter Lenhof, Rainer Maria Bohle, Felix Bremmer, Fabian Alexander Gayer, Yue Che, Peter Albers, Michael Stöckle, Kerstin Junker
Journal: Journal of Clinical Oncology (2025)

645 Background: Due to the risk of long-term toxicities in young non-metastatic seminoma patients, surveillance regimens nowadays are the standard of care. However, up to 20% of patients will relapse and undergo further treatment, requiring even greater efforts in terms of adjuvant therapy. miRNAs are known to be very stable and robust biomarkers. This study aims to establish a prognostic miRNA profile utilizing bioinformatics tools to differentiate between metastatic (met) and non-metastatic (nmet) seminomas. Methods: MiRNA was extracted from formalin-fixed paraffin-embedded sections. Using microarray analysis (Agilent Technology), two cohorts of patients with seminoma (24 patients each, 12 nmet and 12 met) were examined. The following criteria were used to preselect relevant miRNAs: absolute median log2 fold change &gt;0.5, distance correlation &gt;0.5, accuracy in single-miRNA classifier trained with leave-one-out cross-validation (met vs. nmet) &gt;0.7. Validation was performed in 88 patients (47 nmet and 41 met) through qPCR using the TaqMan assay, with RNU48, miR-191-5p, and miR-361-5p serving as references. Statistical and bioinformatics analyses were performed using the Mann-Whitney U test and machine learning algorithms. Results: The bioinformatics analysis of microarrays identified 16 miRNAs exhibiting an accuracy &gt;70% in differentiating met tumors from nmet ones. The validation of 6 miRNAs by qPCR revealed significant expression differences between met and nmet tumors for miRNAs miR-371a-5p, miR-512-3p, miR−509−3−5p, miR-517a-3p (p&lt;0.05), dependent on the reference used. All 4 miRNAs are higher expressed in met tumors. Synchronous met tumors exhibit stronger differences in the expression of the above-mentioned miRNAs compared to metachronous met tumors, except for miR-509-3-5p. miR-371a-5p was found to be the most robust miRNA to distinguish both synchronous and metachronous met from nmet seminomas. Classifiers trained on the PCR data for different combinations of the 6 investigated miRNAs using leave-one-out cross-validation show a medium performance (average accuracy of 0.59) including one model based on 4 miRNAs with high accuracy of 0.99. Conclusions: By using machine-learning algorithms on microarray data, we have established a miRNA signature that can differentiate metastatic from non-metastatic seminomas with high reliability. Validation of 4 miRNAs by qPCR confirms the high prognostic value of miRNAs in seminoma patients. Currently, we examine the suitability of this miRNA panel in liquid biopsy.
The impact of neoadjuvant therapy on the formation of tertiary lymphatic structures and the distinct prognosis in prostate cancer.
Authors: Shengzhuo Liu, Jing Zhou, Xin Yan, Yunfei Yu, Xiaoyang Liu, Qiang Dong
Journal: Journal of Clinical Oncology (2025)

411 Background: This study aims to investigate the characteristics and prognostic predictive efficiency of tertiary lymphoid structures (TLS) in prostate cancer (PCA). We also perform experiments to explore the effects of neoadjuvant hormone therapy (NHT) on TLS formation and immune infiltration in PCA. Methods: We retrospectively collected paraffin-embedded tumor tissue samples from 27 patients who didn`t receive NHT and underwent radical prostatectomy for PCa, and these patients were categorized as Cohort 1. We Additionally retrospectively collected 28 PCa tumor samples, from 14 NHT treated and 14 NHT naive patients, which are categorized as Cohort 2. We prospectively collected prostate biopsy tissue samples, as well as corresponding radical prostatectomy tumor specimens, from 21 patients who all received NHT and are categorized as Cohort 3. We performed HE staining and Multiplex immunohistochemical (mIHC) staining for ki67, panCK, CD21, CD4, CD8, and CD20 to evaluate TLS characteristics and immune infiltration level in different cohorts. We enrolled two GEO cohorts to evaluate the difference of TLS signature between NHT treated PCA and NHT-Naive PCA patients, and between pre-NHT and post-NHT tumor paired samples. We developed an immunocompetent orthotopic prostate cancer mouse model based on CRISPR-Cas9 gene editing technology. In in vivo experiments, we utilized flow cytometry to investigate the difference of CD4 and CD8 immune cell infiltration level in tumor tissues of mice treated or not with androgen deprivation treatment. Results: We found most of the NHT-naive PCa tissues were TLS positive (93%), and the majority of TLSs are located within the tumor region. Patients with positive mature TLSs, SFL-TLSs and higher intra-tumor TLSs density had significantly longer PFS duration. Compared with that in patients received no NHT, TLSs maturity grade and density were higher in NHT treated patients. A matched analysis using biopsy and paired post-NHT tumor samples revealed that NHT significantly increased the positive detection rate of tertiary lymphoid structures (TLSs) within the tumor, the maturity grade of TLSs, and the level of CD8+ T cell infiltration within the TLSs. Transcriptome analysis revealed elevated TLSs signature expression and CD8+ T cell infiltration in NHT treated tumor samples. In vivo experiments also show elevated CD3+ and CD8+ T cells infiltration level after NHT treatment. Conclusions: This study comprehensively characterizes TLSs in PCa and highlights the heterogeneity among patients. Our clinical cohort data, transcriptome sequencing analysis, and in-vivo experiment data confirm that neoadjuvant hormone therapy promotes immune cell infiltration, as well as the formation and maturation of TLSs within PCa tissues. Combining endocrine therapy with immunotherapy is a potential treatment approach for promoting prostate cancer prognosis.