bluuebunny/crossref_metadata_2025_split huggingface dataset:
The potential of transcriptomic profiling to predict immune-checkpoint inhibitor (ICIs) response in locally advanced (La) and metastatic urothelial carcinoma (mUC).
Authors: Caramelo Belen , Muñoz Unceta Nerea , Freire Javier , Varela Ignacio , Martin David , Del Carmen Sofía , Azueta Ainara , Diaz Pilar , Garcia-Berbel Pilar , Sagastibelza Marinelarena Naiara , Rey-Cárdenas Macarena , Castellano Daniel , Climent Miguel Ángel , Puente Javier , Irure Juan , Revuelta Laura , Genre Fernanda , Cacho Diego , Gómez Javier , Duran Ignacio 
Published: January 2024

668 Background: Immune checkpoint inhibitors (ICIs) have proven to be an effective therapy for locally advanced (La) and metastatic (mUC) urothelial carcinoma. However, response rates are typically modest, and patient (pt) selection remains a challenge, especially in the era of ICIs-based combos. The current study analyzes the differential RNA expression as a predictor of ICI response or resistance in La/mUC. Methods: Clinical information and formalin-fixed paraffin embedded (FFPE) samples from pts with La/mUC treated with single agent ICIs [2014 -2021] were obtained and RNA sequencing (RNA-seq) analysis performed. According to response, pts were assigned to one of these three groups: Primary resistant [PR] (progressive disease (PD) as the best response); Secondary resistant [SR] (initial response followed by PD); and Long responders [LR] (stable disease/partial or complete response maintained > 16 months). Results: Clinical data and FFPE samples from 46 patients were available. Nineteen, twelve and fifteen pts respectively were in the PR, SR and LR groups. Clinical characteristics were well-balanced among groups, except for higher percentage of liver metastasis in PR and SR pts. The median overall survival was 11.2 and 18.2 months for the PR and the SR groups and has not yet been reached for the LR cohort, where 80% of the pts remain alive, with 50% achieving complete response. RNA-seq analysis unveiled distinct patterns of differential gene expression in the resistance groups compared to the LR. Notably, an upregulation of the epithelial-mesenchymal transition pathway was observed, with interleukin 2 emerging as a potential surrogate marker of this activity. Additionally, an overactivation of the KRAS pathway was evident, irrespective of its mutational status. Furthermore, in a comparison between the two resistance groups, the SR group displayed increased activation of DNA damage control mechanisms. Conclusions: Our RNA-seq analysis could provide relevant information and holds promise as a valuable tool for predicting responses to ICIs in La-mUC. Nonetheless, further validation on a larger cohort of patients is required.
MAPK pathway alterations as a targetable vulnerability in bladder cancer.
Authors: D'Andrea Vincent , Bekele Raie , Hanlon Timothy , Zhou Yuzhen , Chroneos Rea , Stelter Isabella , Mouw Kent William 
Published: January 2024

672 Background: Large-scale genomic studies of bladder cancer (BC) have identified MAPK as a recurrent pathway alteration. The MAPK pathway is a signaling cascade comprising of the proteins RAF, MEK, and ERK, which together control critical cellular processes. Currently, cisplatin-based chemotherapy and anti-PD1/PD-L1 agents are the backbone of systemic therapy in BC, yet only a subset of patients respond. As such, additional novel therapeutic strategies, such as targeting the MAPK pathway, are needed. Herein, we describe the impact of MAPK alterations on BC tumor properties sensitivity to novel MAPK-directed agents. Methods: The activity of the activity of RAF inhibitors (including RAF265 and the novel RAF dimerization inhibitor LXH254) was tested in BC cell lines with diverse MAPK pathway alterations including RAF1 amplification and NRAS mutations. Relative cell viability was measured by luminescence assay following treatment. RAF1-amplified UMUC9 cells were implanted as mouse flank xenografts which were randomized to treatment with vehicle or RAF inhibitor alone or in combination with a MEK inhibitor, trametinib. Mouse weights and tumor measurements were monitored during the treatment period and tumors were excised and weighed. C57BL/6 mice were orthotopically implanted with BBN cells with and without a RAF1 amplification using a surgical approach and tumor volumes were measured under ultrasound (US). Results: RAF1-amplified and NRAS-mutated cell lines demonstrated higher sensitivity to RAF inhibition than non-altered lines. There was a significant reduction in tumor volumes of UMUC9-engrafted mice treated with RAF265 (n=10) or RAF265 plus trametinib (n=8) compared to vehicle controls (n=14). Mice treated with RAF265 alone or with RAF265 plus trametinib had significantly lower tumor weights than vehicle-treated mice. US monitoring showed that mice orthotopically implanted with RAF1-amplified BBN cells (RAF1, n=9) and empty vector cells (EV, n=9) showed take rates [RAF1=67%, EV=78%], mean tumor sizes [RAF1=23.0mm2, EV=12.5mm2, p=0.07], and tumor growth rates [RAF1=0.60mm2/day, EV=0.40mm2/day, p=0.19]. Conclusions: We sought to explore the vulnerabilities incurred by MAPK pathway alterations in BC. We tested the activity of a RAF inhibitors in BC cell lines with RAF1 amplifications and NRAS mutations and found that MAPK pathway-altered models displayed increased sensitivity to RAF inhibition compared to MAPK-unaltered models. We further showed this sensitivity in vivo with RAF1-amplified mouse xenografts and elucidated the synergistic effect of concurrent RAF and MEK inhibition. There was a trend towards larger tumors and more rapid growth rate in orthotopically-implanted RAF1-amplified BC cells compared to controls. Taken together, these data identify MAPK pathway alterations as a novel dependency in BC that may be clinically targeted with small molecule inhibitors.
Number of prescription medications and overall survival in veterans with metastatic hormone-sensitive prostate cancer.
Authors: Karunanandaa Krishny , Pickett Carley , Eaton Daniel B. , Tohmasi Steven , Ingram Kara , Gopukumar Deepika , Puri Varun , Schoen Martin W. 
Published: January 2024

68 Background: Robustassessment of comorbid conditions is essential to clinical care and the risk-stratification of patients for adverse events and death. Prescription medications may be a simple and readily available tool to estimate patient risk independent of established comorbidity indices, such as the Charlson Comorbidity Index (CCI). Clinicians have access to medication lists, facilitating assessment of comorbidities. We sought to examine the relationship between prescription medications and long-term outcomes in veterans treated for metastatic hormone-sensitive prostate cancer (mHSPC). Methods: We conducted a nationwide retrospective observational study of United States Veterans diagnosed with mHSPC in the Veterans Health Administration from 2010-2021. We determined the number of unique drugs and their respective Anatomic Therapeutic Chemical (ATC) Level One classes prescribed in the year prior to the initiation of treatment. Multivariable logistic regression and Cox proportional hazard modeling was used to assess the association between number of drugs with all-cause 90-day mortality and overall survival (OS) while accounting for covariates including age, CCI, body mass index, prostate specific antigen, and race. Results: Among 8,434 Veterans, a median (IQR) of 9 (5-14) unique medications and 5 (3-7) unique ATC medication classes were filled in the year prior to treatment. The mean age was 74.2 (SD 10.1) years, and 2,126 Veterans were black (25.2%). The median CCI was 3 (2.75-6). Increasing age was associated with increased CCI across age strata with mean CCI of 3.16 in age <60, 3.76 in 60-70, 4.43 in 70-80, and 5.25 in 80+ (p<0.001). Increasing age was associated with an increased number of unique medicines with mean 8.59 in age <60, 9.53 in 60-70, 10.1 in 70-80, and 10.4 in 80+ (p<0.001). There was no significant difference in the number of medications prescribed based on race. Veterans with 1-4 medicines had the longest average survival at 38.2 months compared to 5-9 medicines (33.1 months), 10-14 medicines (27.1 months), and 15+ medicines (22.0 months) (p<0.001). After adjusting for relevant patient, tumor, and treatment factors, the number of medications and drug classes were each independently associated with increased mortality with adjusted HR (95% CI) of 1.03 (1.02-1.03) and 1.05 (1.04-1.07), respectively. Veterans treated with 5-9, 10-14, and 15+ medicines had an increased risk of death compared to Veterans on 1-4 medicines [aHR 1.11 (1.03-1.19); 1.29 (1.19-1.39); and 1.51 (1.39-1.65) respectively]. Conclusions: The number of prescription medications and drug classes are independently associated with OS in patients diagnosed with mHSPC, even after accounting for important covariates including age and CCI. Assessment of patient medications may provide a simple, yet reliable tool to assess comorbidities, risk of adverse events, and death.
Longitudinal whole exome sequencing of cell-free DNA in advanced bladder cancer.
Authors: Ravi Arvind , Epstein Ilana , Freeman Dory , Ravi Praful , Coorens Tim , Danysh Brian , Miller Mendy , Leshchiner Ignaty , Hess Julian , Stewart Chip , Riaz Irbaz Bin , McGregor Bradley Alexander , Bellmunt Joaquim , Van Allen Eliezer Mendel , Mantia Charlene , Kilbridge Kerry L. , Clinton Timothy , Mossanen Matthew , Mouw Kent William , Hirsch Michelle S. 
Published: January 2024

681 Background: The recent approval of agents from novel therapeutic classes including immunotherapy and antibody-drug conjugates has transformed the treatment landscape of advanced bladder cancer. However, even among patients with initially favorable responses to therapy, a subset of patients develop acquired resistance for reasons that are yet to be fully elucidated. Methods: To gain insight into the dynamics of tumor evolution during the course of treatment, we performed longitudinal profiling of plasma cell-free DNA in a cohort of 71 patients with muscle-invasive or advanced disease before, during, and/or after specific lines of therapy. To further resolve evolutionary dynamics during the course of treatment, we additionally performed Whole Exome Sequencing (WES) on 47 plasma samples across 25 patients. Results: We observed a median tumor purity of 3.8% in the plasma with a range from undetectable (N = 24 samples out of 217 total) to 61%, with tumor purity generally increasing in patients with progressing disease as compared to stable (p = 0.037) or to responding disease (p = 0.002), consistent with the notion that tumor DNA content in the circulation may act as a proxy for overall tumor burden. Phylogenetic reconstruction in 14 patients using WES data identified growing subclones with potential resistance drivers including TP53, PTEN, and FAM46C. In addition, we identified two cases in which growing subclones showed few shared mutations with regressing clones, demonstrating instead largely distinct somatic mutation profiles. Conclusions: Longitudinal WES of cfDNA is feasible in a subset of advanced bladder cancer patients with sufficiently high tumor purity in the blood. In addition, based on our findings of substantial variation in somatic mutations within two reconstructed patient phylogenies, we hypothesize that acquired resistance could in some cases be enabled by marked transitions in the neoantigen repertoire.
AI-based morphologic model for prediction of individual patient response to immune checkpoint inhibitors for bladder cancer.
Authors: Nair Monica , Liao Ross , Jain Parag , Xie Chensu , Muhammad Hassan , Huang Wei , Basu Hirak S , Wilding George , Roy Rajat , Diaz-Montero C. Marcela , Hwang Tae Hyun , Dawsey Scott , Nguyen Jane , Klein Eric A. , Gupta Shilpa , Mian Omar Y. 
Published: January 2024

686 Background: Immune checkpoint inhibitors (ICI) have been used to treat advanced muscle invasive and/or metastatic bladder cancer. However, ICIs are only effective in 30-40% of cases. In light of potentially significant IRAE’s, tools to predict individual patient level benefits are desirable. AI technology offers the opportunity to apply computational methods to predict outcomes from readily available digitized pathology slides. We investigated the utility of an AI platform integrating computational biomarkers based on morphological characterization of digitized H&E slide whole images (WSI) to predict response to ICI. Methods: We analyzed H&E-stained whole slide images (WSI) of bladder tumor tissue collected from transurethral resection of bladder tumor (TURBT) from 116 patients with advanced or metastatic bladder cancer at a single institution between 2015-2020. Adjacent multiplex IHC stained specimens were analyzed myeloid and lymphoid marker panels. 20 patients from the overall cohort treated with ICI were designated ‘responders’ (complete response, partial response, stable disease) and 20 patients were identified as non-responders (progressive disease) based on ICI best clinical/radiographic response. WSIs were divided into small non-overlapping image patches. These image tiles were processed into multiple AI encoder models to extract morphological features. The tile morphological features, represented by high dimensional vectors, were combined by an aggregation model to represent the whole slide morphology and then used to classify the patients into responders vs non-responders to immunotherapy. Area-under-the-receiver operating characteristic (AUC) was used to measure the performance of response prediction. Results: Our method shows AUC of 0.708 at classification of the patients (n=40) into responder and non-responder groups. With a cutoff that identifies the top 50% patients (n=20) of high probability of responding to immunotherapy predicted by our models, 75% of them are responders. In the bottom 50% patients (n=20) of the low scores, 75% of them are non-responders. . Multiplex IHC (myeloid and lymphoid panel) was performed using adjacent sections and were characterized yielding deeper mechanistic insight into the inflammatory populations driving predictive morphologic patterns. Conclusions: By applying innovative AI morphological analysis on patient WSIs, we generated a computational biomarker that shows promising ability to predict patient response to immunotherapy in bladder cancer. This approach merits future prospective validation and additional patient level analysis in broader cohorts. [Table: see text]
Dicycloplatin: Assessing the efficacy of a novel platinum analog for treatment of urothelial carcinoma of the bladder.
Authors: Zekan David , Jackson Barbara , Hogan Thomas F. , Kandzari Stanley 
Published: January 2024

689 Background: Platinum-based chemotherapies are a component of standard-of-care regimens for urothelial carcinoma (UC). These nephrotoxic drugs are often dose-limiting, with cisplatin and carboplatin most used. Dicycloplatin (DCP) has better solubility and stability, with comparable efficacy and better tolerability. Some suggest use of DCP as primary treatment for non-muscle-invasive bladder cancer. We exposed UC cell lines to DCP in vitro to assess efficacy. Methods: A high grade (IV) in vitro UC cell line (TCCSUP) was exposed to varying concentrations of cisplatin (0-600 ug/mL), carboplatin (0-600 ug/mL), oxaliplatin (0-4.0 ug/mL), and DCP (0-350 ug/mL). Grade II-IV cells were exposed to concentrations of DCP (0-350 ug/mL) to assess time- and concentration-dependence of growth inhibition, and intravesical simulation. Growth inhibition was determined following exposures of 24, 48, and 72 hours using exposure to a tetrazolium dye assessing mitochondrial dehydrogenase activity. Results: DCP, cisplatin, and carboplatin effectively achieved >90% cell-kill at 72 hours. Concentrations of 325 ug/mL DCP, 50 ug/mL cisplatin, and 600 ug/mL carboplatin are sufficient for >90% cell-kill, with cisplatin boasting highest kills at lowest concentration/time intervals. Dose- and time-dependent cell-kill were demonstrated at varying concentrations of DCP in grade II-IV cell lines, including cells exposed in a intravesical fashion. Conclusions: DCP has in vitro cell-kill efficacy in a time- and concentration-dependent manner in grade II-IV UC cell lines, showing promise for its IV, PO, and intravesical use for UC of the bladder in the primary and adjuvant/neoadjuvant setting. Animal studies are forthcoming to assess in vivo efficacy prior to proceeding with clinical trials.
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: Hammouda Kamal , Corredor Germán , Pathak Tilak , Mian Omar Y. , Pavicic Paul G. , Diaz-Montero C. Marcela , Mirtti Tuomas , Gupta Shilpa , Madabhushi Anant 
Published: January 2024

691 Background: Quantification of tumor-infiltrating lymphocytes (TILs) in archival hematoxylin and eosin (H&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&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&E slides from biopsy or radical surgery available for 56 pts (S1). 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) (S2). These features were utilized to develop a Cox regression model, aiming to assess the risk of death for individual patients from the S2. The Cox model was then applied to predict risk and outcome for patients from S1. 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&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.
Development and validation of a novel prognostic model for disease-specific survival in patients with non-metastatic small cell carcinoma of the bladder.
Authors: Diamantopoulos Leonidas Nikolaos , Childs Daniel S , Lewis Akeem Ronell , Lucien Fabrice , Basourakos Spyridon P. , Kase Adam McLain , Singh Parminder , Tyson Mark , Boorjian Stephen A. , Pagliaro Lance C. , Costello Brian Addis , Orme Jacob 
Published: January 2024

695 Background: Small cell carcinoma of the bladder (SCCB) is a rare variant of bladder cancer with limited data informing prognosis. We present a novel prognostic model for disease specific survival (DSS) for patients with non-metastatic (M0) SCCB, derived from the Surveillance, Epidemiology and End Results (SEER) database. Methods: The SEER database (18 registries/November 2020) was queried with the ICD-10 topography codes C67.0-C67.9 (bladder), and the morphologic code 8041 (SCCB). Eligible patients (adults, histologic confirmation, available follow-up/staging data, M0) were randomly divided into a training (TC) and a validation cohort (VC) (7:3 ratio). Variables significantly associated with DSS were identified with multivariate Cox regression and backwards stepwise conditional approach and inserted in the model. Points were assigned to each variable based on the formula: Probability of an event at time t=S0(t)exp(β1x1, β2x2...), (β = regression coefficients, x = observed covariate values, S0(t) = survival function). Cumulative risk points were assigned to each patient and three distinct risk categories for DSS were constructed. Harrel’s C-statistic with bootstrap resampling was used for internal (TC) and external (VC) validation. Model performance was compared to the AJCC 8th edition (likelihood ratio test -LRT). Results: A total of 1039 patients were included (739 TC, 300 VC). No statistically significant differences in baseline characteristics/survival outcomes were identified between TC and VC. Age (years), T/N stage, radical cystectomy, chemotherapy, and radiation were significant variables inserted in the multivariate model (table). Patients were stratified to three risk groups (low, intermediate, high) based on the total cumulative risk points collected. Median DSS was NR (95%CI; NR, NR), 25 (95% CI; 18-32) and 9 months (95% CI; 7-11) for the low, intermediate, and high-risk category, log-rank p<.001. Harrel's C-statistic for the model was 0.70 (95%CI;0.67-0.73) in the TC and 0.66 (95%CI; 0.61-0.71) in the VC. In comparison, C-statistic for the AJCC 8th edition was 0.56 (95% CI; 0.52-0.59) and 0.53 (95% CI; 0.51 to 0.57), respectively. The LRT demonstrated superior performance of the model compared to AJCC (p<.001). Conclusions: We present a novel prognostic model for DSS in patients with locoregional SCCB composed of variables readily available in daily practice, which may serve as a useful tool for individualized risk assessment of patients with this rare malignancy. Further validation in prospective studies/clinical trials is warranted. [Table: see text]