tbuckley/cabot-search huggingface dataset:
Baseline disease characteristics of participants enrolled on ENZARAD (ANZUP1303) and DASL-HiCaP (ANZUP1801) trials of highly effective androgen receptor antagonists in high-risk localized or locally advanced prostate cancer (PCa).
Authors: Tamim Niazi, Paul L. Nguyen, Scott Williams, Martin R. Stockler, Andrew James Martin, Lisa Horvath, Hayley Thomas, Danka Sinikovic Zebic, Felicia Roncolato, Tee Lim, Chakiath Jose, Jarad Martin, Hans T. Chung, Annie Ebacher, Scott C. Morgan, Simon Hughes, Sean Matthew McBride, Paul J. Kelly, Ian D. Davis, Christopher Sweeney
Journal: Journal of Clinical Oncology (2024)

328 Background: ENZARAD investigates the addition of enzalutamide or conventional nonsteroidal anti-androgens (NSAA) to radiation therapy (RT) and ADT for high-risk localized PCa. DASL-HiCaP investigates the addition of darolutamide or placebo to RT and androgen deprivation therapy (ADT) using Luteinizing hormone releasing hormone analog (LHRHA) for very-high-risk localized PCa as either primary definitive therapy, or as early salvage treatment after prostatectomy where PSA has persisted or become detectable within 12 months. Methods: The eligibility of DASL-HiCaP differed from ENZARAD by excluding patients solely based on PSA &gt; 20ng/mL and also allowing a very-high risk patient population suitable for salvage radiation post prostatectomy. Participants in DASL-HiCaP were randomized 1:1 to darolutamide 600mg twice daily or placebo plus LHRHA for 96 weeks; all received external beam radiotherapy including mandated pelvic radiation. Participants in ENZARAD were randomized 1:1 to enzalutamide 160mg daily for 24 months or conventional NSAA for 6 months, plus LHRHA for 24 months, and EBRT. Brachytherapy boost was allowed in both trials and pelvic nodal radiation was at investigator’s discretion in ENZARAD. The primary end point for both trials is metastasis-free survival (MFS) (time from randomization to first evidence of metastasis or death from any cause). MFS events are based on conventional imaging with 99m Tc bone scan and CT, and/or MRI. Lesions evident only on PSMA PET are not counted as MFS events. Results: The median age for both trials was 71-years. Complete baseline characteristics are summarised in the Table. ENZARAD randomized 802 participants across 8 countries. Half had Gleason score 9 (52%), 45% had cT3 PCa, 42% had cT2, and 11% were cN1. Gleason score 7 was present in up to 11% of ENZARAD population. DASL-HiCaP randomized 1,107 participants across 6 countries. Most had Gleason score 9 (69%), 41% had cT3 PCa, 32% had cT2, and 28% were cN1. Gleason score 7 was present in &lt;5% of the DASL-HiCaP population. Conclusions: ENZARAD and DASL-HiCaP will define the efficacy of more potent hormonal therapy in the adjuvant setting of patients with both high- and very-high-risk disease and in both primary and salvage radiation settings. Clinical trial information: NCT02446444 and NCT04136353 . [Table: see text]
Correlation of artificial intelligence (AI)-based spatial characteristics of tumor-infiltrating lymphocytes outcomes with immune checkpoint inhibitors (ICIs) in patients (pts) with metastatic urothelial cancer (mUC).
Authors: Kamal Hammouda, Germán Corredor, Tilak Pathak, Omar Y. Mian, Paul G. Pavicic, C. Marcela Diaz-Montero, Tuomas Mirtti, Shilpa Gupta, Anant Madabhushi
Journal: Journal of Clinical Oncology (2024)

691 Background: Quantification of tumor-infiltrating lymphocytes (TILs) in archival hematoxylin and eosin (H&amp;E) specimens of muscle-invasive urothelial cancer (MIUC) specimens can help assess tumor microenvironment (TME) and serve as prognostic and predictive biomarkers to assess outcomes with ICI. There is an unmet need to develop non-invasive computational pathology-based models based on the spatial characteristics of TILs on H&amp;E tissue images for predicting outcomes with ICI in pts with mUC. Methods: We retrospectively analyzed 335 adult pts with mUC treated with ≥2 cycles of ICI with atezolizumab (A) or pembrolizumab (P) at Cleveland Clinic between 2015 and 2023. We used this cohort to validate a prognostic model for bladder cancer (BC) originally trained on the Cancer Genome Atlas (TCGA) dataset. Of the 335 pts in this cohort, we had archival H&amp;E slides from biopsy or radical surgery available for 56 pts (S 1 ). We developed a tumor segmentation model by leveraging the U-net deep learning network. Within the segmented regions, nuclei were segmented and classified into TILs and non-TILs using the HoVer-Net algorithm. Spatial graphs involving the TILs as the nodes of the graphs were constructed and a total of 350 spatial statistics relating to the distances between the TILs and non-TILs were extracted. Using the least absolute shrinkage and selection operator (LASSO) model, the 14 most prognostic features were identified using tissue images from a total of 361 patients with MIBC from the Cancer Genome Atlas (TCGA) (S 2 ). These features were utilized to develop a Cox regression model, aiming to assess the risk of death for individual patients from the S 2 . The Cox model was then applied to predict risk and outcome for patients from S 1 . Results: In S2, high-risk patients, as identified by the AI model, had a median overall survival (OS) of 16 months, while low-risk patients had a median OS of 21 months. The model's performance was validated using a blinded dataset from S1, and it showed significant prognostic value for OS in S1 patients, with Hazard Ratio (HR)=1.61 (95% Confidence Interval (CI)=1.18-2.2, and p-value=0.0013). The median OS for the high-risk group based on our model was 26 months and 39 months for the low-risk group, HR 1.90 (95% CI = 0.97-3.73, p-value = 0.036). Conclusions: Computational image features related to spatial architectural patterns of TILs and non-TILs on H&amp;E tissue images correlated with OS in pts with mUC receiving ICI in our real-world cohort. Additional independent multi-site and prospective validation of these findings are warranted.
HER2 mutation and bladder cancer (BC): Prevalence and clinical outcomes.
Authors: Neil J. Shah, David H Aggen, Junting Zheng, Andrew Niederhausern, Syed Muneeb Alam, Om Balar, Nadia Bahadur, Adam Watson, Ashley M. Regazzi, Neha Ratna, Samuel A Funt, Min Yuen Teo, Eugene J. Pietzak, David B. Solit, Dean F. Bajorin, John Philip, Jonathan E. Rosenberg, Irina Ostrovnaya, Hikmat A. Al-Ahmadie, Gopa Iyer
Journal: Journal of Clinical Oncology (2024)

574 Background: Novel HER2-directed targeted therapies have revolutionized the treatment paradigm for patients with breast cancer and are being actively investigated in BC. The impact of pathogenic HER2 mutation and/or its amplification on clinical outcomes across various stages of BC is underdefined. Methods: In our retrospective study, we identified 999 BC patients who underwent genetic profiling using MSKCC IMPACT and had at least one year of follow-up. The BC disease states included non-muscle invasive (NMIBC), muscle-invasive (MIBC), and metastatic (MetBC). Patient demographics and HER2 alteration (mutation or amplification) were analyzed and compared closest to the time of IMPACT sampling, using the Kruskal-Wallis rank sum test or the Fisher’s exact test. The Kaplan-Meier method was used to estimate overall survival (OS) and progression-free survival (PFS) for MIBC and MetBC, and advanced disease-free survival (ADFS) for NMIBC. The log-rank test and Cox proportional hazard regression were used in survival analyses. Results: The study cohort included NMIBC:359, MIBC:429, and MetBC:211 patients at the time of profiling and the overall incidence of HER2 alteration (mutation or amplification) was 13% (48), 17% (75), and 19% (41), respectively. HER2 Amplification was significantly lower for NMIBC (2.8%) compared to MIBC (9.3%) and MetBC (10%), p&lt;0.001. HER2 S310F and S310Y were the most common pathogenic mutations. Age, race, gender, and smoking status were not associated with the incidence of HER2 alteration for any BC disease states. The median follow-up for NMIBC, MIBC, and MetBC was 5.3, 3.6, and 6.5 years, respectively. HER2 status did not influence ADFS for NMIBC; PFS and OS for MIBC regardless of neoadjuvant cisplatin chemotherapy (chemo); OS for 1st line (1L) MetBC treated with gemcitabine plus platinum (GC) chemo or 2nd line (2L) immune checkpoint inhibitor (ICI) therapy post 1L-chemo (table). Conclusions: We present one of the largest and comprehensive study of HER2 mutation in BC. Overall, HER2 amplification was significantly less frequent for NMIBC. HER2 alterations were not a prognostic marker for NMIBC or MIBC independent of neoadjuvant cisplatin-based chemo, MetBC- 1L GC-chemo and 2L ICI post GC-chemo. Further studies examining IHC and functional HER2 PET imaging are needed to further define the HER2 BC landscape. [Table: see text]
Geriatric assessment (GA) in elderly patients with urothelial cancer (UC): Can GA select frail patients and avoid toxic treatment? Multidisciplinary single center experience.
Authors: Maria Regina Girones Sarrio, Maria Arnal Rondán, Miguel Angel Berenguer Francés, Alba Girones Torres Martínez, Antonio Jose Conde Moreno, José Luis Pontones, Francisco Delgado, Cristina Bonastre, David Ramos, Nuria Gómez Sepúlveda, David Lorente Estelles, Silvia Forcano
Journal: Journal of Clinical Oncology (2024)

564 Background: UC is a disease of the elderly. Median age at UC diagnosis is olderthan for other major tumours (73 years old). The correct management of UC in the elderly remains controversial. Treatment-decisions should be based on biological age, not in chronological one. The role of geriatric assessment (GA) evolution is potentially beneficial. It has been detected between 10% to 25% frailty patients aged over 65 years are characterised as frail on GA on other tumors. GA has not been studied prospectively in UC patients. Objective: to assess the paper of GA in elderly patients with UC patients attended in an outpatient medical oncology consultation. To confirm that GA can detect at least 25% of frailty patients unsuitable for active treatment. Methods: Prospective interventional study. GA was done by a Geriatrician at patient’s home. Treatment-decisions were based on GA results, physician choice and patients/caregivers goals. Population: patients ≥ 70 years old sent from January 2019 to September 2023 diagnosed with UC. Patients unsuitable to be ambulatory (Performance status PS ≥ 3) were excluded. Ethics review board approved the analysis. All participants signed informed consent. Results: 82 patients were aged ≥ 70 years old (57% of all patients attended). Table shows patient’s information. GA detected 24 (30%) of frailty patients. They were elder, former smokers, had worse PS and worse overall survival in all stages. Non frail patient received active treatment. Comorbid and polypharmacy population was found in all three GA groups. More fit and vulnerable patients were treated with cisplatin by GA assessment than if we have applied Galsky criteria. This suggests than the strict use of a CrcL &lt; 60 ml/min is still controversial. Conclusions: In a very selected population, GA can still find 30% of frail patients unsuitable for treatment. Frailty seems to be a predictive and prognostic factor in elderly patients with UC. Treatment selection based on GA increase the number of patients suitable for platinum treatment. Defining “platinum-ineligible” patients with metastatic urothelial cancer should be reviewed. Selection bias cannot be excluded from our analysis.
High expression of sialylated cancer-derived IgG and survival in metastatic clear cell renal cell carcinoma.
Authors: Jie Wu, Hong-Lei Cui, Hongzhe Shi, Ai-Ping Zhou, Jianzhong Shou
Journal: Journal of Clinical Oncology (2024)

443 Background: The treatment landscape of metastatic clear cell renal cell carcinoma (mccRCC) has evolved from cytokine regimens to targeted therapy, and now immunotherapy-based drug combinations over the past two decades. However, there is a lack of confirmed prognosis biomarkers for mccRCC patients. The International mRCC Database Consortium (IMDC) risk model is the most widely used effective biomarker for prognostication in mccRCC. Immunoglobulin G (IgG), well known as immune molecule secreted by B cells, has recently been detected in various types of cancer cells, named as cancer-derived IgG. Notably, it has been demonstrated that IgG derived from epithelial cancer cells displays unique N-glycosylation, which is highly sialylated (SIgG). In this study, we aimed to explore the expression of SIgG in mccRCC tissues using the monoclonal antibody RP215, and evaluated the correlation of SIgG expression level with clinicopathological factors and prognosis of mccRCC patients. Methods: A total of 179 mccRCC patients with complete clinicopathological information and survival data were enrolled. Tumor tissues were collected during surgery and fixed in 10% buffered formalin, embedded in paraffin. Tissue microarray slides were then constructed for immunohistochemistry (IHC). The primary end point was overall survival (OS), defined as the time from initiation of systemic treatment to death from any cause or last follow-up. Results: The results of IHC showed that SIgG was mainly expressed in the cell membrane and cytoplasm, and the high expression of SIgG was significant correlated with poor OS in mccRCC patients (HR = 2.281, P &lt; 0.001). Moreover, based on multivariate Cox regression analysis, high SIgG expression was identified as an independent prognostic variable for OS in mccRCC patients (HR = 2.110, P &lt; 0.001), as well as poor IMDC risk group (HR = 2.123, P = 0.018). The time-dependent ROC curve also suggested the promising prognostic value of SIgG expression, with a 5-year AUC of 0.679 for SIgG alone and 0.742 for SIgG combined with IMDC risk model. In addition, subgroup analyses were performed to further assess prognostic value of SIgG for mccRCC patients among groups based on IMDC risk group, metastatic site, and metastatic time. The prognostic value of SIgG was more marked in patients with intermediate (HR = 2.191, P = 0.019) and poor (HR = 2.111, P = 0.058) IMDC risk group, and lung metastasis (HR =1.970, P = 0.009). Notably, the prognostic value of SIgG was significant in both synchronous and metachronous metastasis patients. Conclusions: SIgG appears to be a reliable predictor for the outcome of mccRCC patients, and SIgG combined with IMDC risk model was a more effective prognostic model than IMDC risk group alone.
ABC transporter expression to predict therapeutic effect of enfortumab vedotin in urothelial cancer.
Authors: Hiroki Shimoda, Atsuko Takada-Owada, Toshiki Kijima, Hidetoshi Kokubun, Toshitaka Uematsu, Kohei Takei, Yoshimasa Nakazato, Masahiro Yashi, Kazuyuki Ishida, Takao Kamai
Journal: Journal of Clinical Oncology (2024)

693 Background: Enfortumab vedotin (EV) is an antibody-drug conjugate consisting of anti-Nectin-4 antibody and is approved for metastatic urothelial cancer. Predictors of therapeutic benefit of EV have not been established since nectin-4 expression varies widely with the course of treatment. ATP Binding Cassette (ABC) transporters which export the administered anti-cancer drugs out of the cells have been postulated as one of the mechanisms of therapeutic resistance to EV. In this study, we evaluated the expression of Nectin-4 and ABC transporters in primary biopsy tissues, primary radical resection tissues, and metastatic sites from urothelial cancer patients and evaluated their association with prognosis after EV therapy. Methods: We studied 16 patients who received enfortumab vedotin for metastatic urothelial cancer. Biopsy of primary tissue, radical surgery of primary tumor, and resection of metastatic sites was performed in 16, 7, and 4 patients, respectively. In these specimens, the expression of nectin-4 and ABC transporters was evaluated by immunostaining. Among ABC transporters, we evaluated MDR1 (ABCB1), MRP1 (ABCC1), and BCRP (ABCG2) since they have been reported to be associated with anticancer drug resistance. Staining intensity on the cell membrane was classified into 0 to 3 according to the evaluation criteria of HER2. We investigated the relationship between the expression of nectin-4 and ABC transporters and survival after EV therapy. Results: Nectin-4 was positive in all patients (score 3 in 12 patients, score 1 in 4 patients) in primary biopsy. All patients tested negative for MDR1. MRP1 was positive in 11 (score 2 in 2 patients and score 1 in 9 patients), and BCRP was positive in 14 (score 2 in 10 patients, score 1 in 4 patients). Nectin-4 expression decreased in radical surgery tissues and metastatic sites. On the other hand, ABC transporter expression remained unchanged or rather increased in radical surgery tissues and metastatic sites (Table). Patients with both MRP1 and BCRP expression in the primary biopsy specimen (n=8) had significantly worse PFS and OS after EV therapy while nectin-4 expression in the primary biopsy specimen was not associated with survival. Conclusions: Patients with ABC transporter expression had a poor prognosis after EV therapy, although nectin-4 expression in primary biopsies was not associated with prognosis. Nectin-4 expression tended to decrease, while the ABC transporter remained unchanged or enhanced as the disease progressed. [Table: see text]
Population based trends in intravesical gemcitabine use among patients with high-risk non-muscle invasive bladder cancer.
Authors: Stephen B. Williams, Jinghua He, Aeja Jackson, Andrea Ireland, Hiremagalur Parthasarathy Balaji, Wenxi Huang, Qian Shi, Lorie Ellis, Mukul Singhal
Journal: Journal of Clinical Oncology (2024)

699 Background: Intravesical gemcitabine (iGEM) use among patients with high-risk non-muscle invasive bladder cancer (HR NMIBC) has shown effectiveness towards preventing or delaying tumor recurrence, although Bacillus Calmette-Guérin (BCG) remains the standard of care for newly diagnosed HR NMIBC. This retrospective cohort study investigated iGEM users and reported their treatment patterns among SEER-Medicare enrollees newly diagnosed with HR NMIBC patients naïve (BCG-N) or exposed (BCG-Exp) to BCG therapy. Methods: Patients enrolled inMedicare Part A &amp; B fee-for-service enrolled, with HR NMIBC, defined by Tis, Ta, T1, N0, M0 and ≥65 years with iGEM use between 2008-2020 were evaluated. Patients with missing TNM stage, low/ intermediate risk NMIBC, or other primary cancers were excluded. Index date was defined as the first claim of iGEM after HR NMIBC diagnosis, regardless of their prior BCG use. Patients were followed until the earliest event of death, end of Medicare advantage enrollment, or data availability end (12/31/2020). Demographic and clinical characteristics were reported in the baseline period (12-month pre-index) and treatment patterns were reported calendar year post-index date for BCG-N and BCG-Exp cohorts. Results: The analysis included 277 BCG-N and 402 BCG-Exp patients receiving iGEM. In both cohorts, mean age was &gt;75 years, ≥80% were male, and &gt;90% were White. The mean (SD) national cancer index comorbidity index score was 0.85 (0.7) for BCG-N and 0.63 (0.7) for BCG-Exp. Intravesical therapy use beyond a perioperative instillation during the baseline period was observed in 27% of BCG-N and 14% of BCG-Exp patients; docetaxel (17% BCG-N, &lt;1% BCG-Exp) and mitomycin (12% BCG-N, 14% BCG-Exp) were most common. The median number of iGEM doses in the BCG-N group was 6 (IQR 1,8) with mean (SD) of 28 (43) days of retreatment interval. In BCG-Exp, the median number of iGEM doses was 6 (IQR 2,9) with mean (SD) of 23 (26) days of retreatment interval. The table shows increasing iGEM use in both BCG-N and BCG-Exp groups, with 70% of BCG-N in years 2019 through 2020, and 22-30% of BCG-Exp patients receiving iGEM in years 2017 through 2020. Conclusions: Recent BCG shortages may have played a significant role in recent increased uptake of iGEM in both BCG-N and BCG-Exp cohort among HR NMIBC patients. Further information on the efficacy and safety outcomes of iGEM vs BCG in various HR NMIBC populations are needed. [Table: see text]
Development of a novel machine learning-based predictive risk calculator for radical cystectomy.
Authors: Aravind Rajagopalan, Kevin J. Chua, Hiren V. Patel, John Pfail, Alain Kaldany, Melinda Fu, Sammy Elsamra, Thomas L. Jang, Henry Pitt, Saum Ghodoussipour
Journal: Journal of Clinical Oncology (2024)

578 Background: Radical cystectomy (RC) is a standard treatment for patients with muscle invasive and certain high-risk non-invasive bladder cancers. Existing clinical risk calculators based for RC on standard regression methods have demonstrated poor, inaccurate predictions of post-operative risks and adverse outcomes. We aimed to build a risk calculator using novel machine learning methods to predict complication rates and other outcomes based on clinical characteristics of patients undergoing RC. Methods: Patients who had an RC for bladder cancer between 2019 and 2021 were pulled from the National Surgical Quality Improvement Database. Potential predictors included clinically meaningful characteristics such as patient demographics, pre-operative labs, comorbidities, pre-operative bowel and antibiotic preparations, and prior treatment history, as well as cystectomy-specific characteristics such as diversion type and surgical approach. Outcomes included risk of any complication, infectious complication, mortality, and readmissions. Logistic regression, random forest, and support vector machine algorithms were used to build predictive models. Models were optimized assessed with area under the ROC curve (AUROC) and average precision (AP). Results: 8,936 patients were included in the sample dataset. Random forest classifiers outperformed other models for predicting risk of any complication (AUROC = 0.662; AP = 0.66), infectious complication (AUROC = 0.615; AP = 0.20), and mortality (AUROC = 0.603; AP = 0.03). The logistic regression model best predicted readmissions (AUROC = 0.587; AP = 0.26). Top predictors of complication risk included operation time, glomerular filtration rate, and type of procedure (robotic vs. open). Infectious complication was best predicted by wound classification and diversion type, mortality was best predicted by BMI and operation time, and readmissions was predicted most by pre-existing renal failure and emergent cases. Conclusions: Machine learning-based risk calculators were more effective in predicting morbidity and mortality after RC compared to more standard predictive algorithms. Machine learning algorithms therefore demonstrate greater predictive potential when given a wide range of clinical characteristics. [Table: see text]