Kidney Cancer Patients Research Articles

Risk factors of surgical compliance and impact on survival in patients with kidney cancer: a population-based, propensity score matching study.

To identify the impact of surgical compliance on survival in patients with kidney cancer and to explore the factors that influence surgical compliance. Clinical date of kidney cancer patients were identified from the SEER databases, and the patients were divided into surgical compliance group and surgical noncompliance group. Cox survival analysis and Kaplan-Meier curves were used to evaluate the effect of surgical compliance on overall survival (OS) and cancer-specific survival (CSS). A diagnostic nomogram was constructed to quantify individual differences in compliance, and receiver operating characteristics (ROC) curves and calibration curves were used to assess the accuracy of the nomogram. Propensity score matching (PSM) was performed to balance potential baseline confounding factors. Of the 133,950 patients eligible for surgical resection, 2,814 (2.1%) patients did not opt for surgery ultimately. Surgical noncompliance was associated with poor prognosis. In all patients, Cox regression analysis showed that surgical noncompliance was an independent predictor for OS [before: HR = 2.490, 95% CI 2.374-2.612, p < 0.001; after: HR = 2.380, 95% CI 2.202-2.573, p < 0.001] and CSS [before: HR = 2.490, 95% CI 2.318-2.675, p < 0.001; after: HR = 2.035, 95% CI 1.813-2.285, p < 0.001] of kidney cancer patients before and after PSM. Multivariable logistic regression revealed that older age, afro-american origin, lower household income, and advanced tumor grade were associated with surgical noncompliance. The ROC and calibration curves showed that the diagnostic nomogram had high predictive accuracy. Surgical compliance was an independent prognostic factor for OS and CSS in patients with kidney cancer, and surgical noncompliance was associated with poor survival.

Surgery or Comorbidities: What Is the Primum Movens of Kidney Dysfunction After Nephrectomy? A Multicenter Study in Living Donors and Cancer Patients.

Background and Hypothesis: Acute Kidney Injury (AKI) and Chronic Kidney Disease (CKD) are significant risks for kidney cancer (KC) patients undergoing partial (PN) or radical nephrectomy (RN) and for living kidney donors (LKD). This study compares AKI and CKD incidence in these groups with a pre-operative glomerular filtration rate (GFR) over 60 mL/min/1.73 m2. Methods: This study included 465 KC patients with cT1-2N0M0 kidney mass and 256 LKD who underwent nephrectomy at four Italian institutions from 2014 to 2021. Data on demographics, comorbidities, and therapies were analyzed. Serum creatinine and estimated GFR (eGFR) were measured before and after surgery. Outcomes were AKI (per KDIGO guidelines) and CKD stage progression. Analyses included descriptive statistics, ANOVA, logistic regression, and Kaplan-Meier survival. Results: Among 721 patients, significant age and gender differences were noted. Hypertension (41%) and diabetes (7.1%) were prevalent in RN and PN groups. Post-surgery AKI was more common in donors (84%), while CKD stage progression varied by surgery type (CKD stage G3 after 60 months: RN 48.91%, PN 18.22%, LKD 26.56%). Age, pre-surgery CKD, and surgery type predicted CKD progression. Limitations include retrospective design and bias. Conclusions: Both LKD and KC patients face similar AKI and CKD risks. Surgery type significantly influences AKI and CKD incidence, highlighting the importance of approach.

Comparative Proteomics of ccRCC Cell Lines to Identify Kidney Cancer Progression Factors.

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer, accounting for approximately 75% of kidney cancers. The objective of this study was to identify novel progression markers for ccRCC based on proteomics, with the goal of stage determination and early diagnosis of kidney cancer patients. We performed quantitative global proteomics coupled with Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC) and high-resolution tandem mass spectrometry on kidney-derived cells, including HEK-293, 786-O (primary ccRCC), and Caki-1 (metastatic ccRCC) cells, to investigate the novel progression factors of ccRCC. In this study, a total of 1,106 proteins were quantified. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted for differentially expressed proteins (DEPs) that were increased in ccRCC cells compared to HEK-293 cells. Ultimately, 99 DEPs including 75 up-regulated and 24 down-regulated proteins, that were significantly altered in both ccRCC cells, were identified. Among DEPs, vimentin was identified as the most significantly changed protein. Its increased expression in ccRCC was verified through immunoblotting in ccRCC cell lines and immunohistochemistry in kidney tumors. From the global proteomics data detected in ccRCC, we propose 99 DEPs including vimentin as progression factors.

Establishment of RNA modification regulators index predicting clinical outcomes and immune relevance of kidney cancer patients

Increasing evidence indicates that RNA modifications are misregulated in human cancers, which might be optimal targets of cancer therapy. However, important RNA regulators in kidney cancer still need further exploration. In this study, we collected regulators representing different types of RNA modification and identified the prognosis-related RNA regulators in kidney cancer patients. We further constructed a 4-gene RNA regulators signature and index called prognosis-related RNA regulators index (PRRI) by the Lasso-Cox regression algorithm. We found that PRRI could precisely predict prognosis of patients in the KIRC training (AUC at 3-/5-/7-years = 0.7132/0.7220/0.7283) and testing cohorts (AUC at 3-/5-/7-years = 0.7141/0.7403/0.7305) and two independent RCC cohorts - E-MTAB-1980 (AUC at 3-/5-/7-years = 0.7036/0.7385/0.7143) and KIRP (AUC at 3-/5-/7-years = 0.6203/0.6365/0.6941). Moreover, the high PRRI group showed a worse clinical outcome than the low PRRI group. PRRI demonstrated strong robustness and was related to histological grade and pathologic stage, which was also found to be an independent prognosis factor when other clinical variables adjusted it. We further found several immune-related pathways differentially enriched in the high or low PRRI group. The regulation of T cell migration, which has been proven to be an immunosuppressive cell, shows a high enrichment in the high PRRI group. Further analysis reveals that PRRI also shows a highly positive correlation with the activity of Tregs. TIDE analysis and two independent immune therapy cohorts revealed that the high PRRI group might resist immune therapy, while the low PRRI group might benefit from the treatment, indicating that PRRI could be a marker for predicting immune therapeutic response. All in all, we determined 4 potentially essential RNA regulators and illustrated their mechanisms concretely. Furthermore, we constructed a 4-gene index called PRRI to predict patients’ outcomes and immunotherapy response.

The immunotherapy-based combination associated score as a robust predictor for outcome and response to combination of immunotherapy and VEGF inhibitors in renal cell carcinoma

BackgroundOver the past decade, the realm of immunotherapy-based combination therapy has witnessed rapid growth for renal cell carcinoma (RCC), however, success has been constrained thus far. This limitation primarily stems from the absence of biomarkers essential for identifying patients likely to derive benefits from such treatments. MethodsIn this study, the immunotherapy-based combination associated score (IBCS) was established using single-sample gene set enrichment analysis (ssGSEA) based on the genes identified in the key modules extracted by weighted correlation network analysis (WGCNA) in the IMmotion151 dataset, a randomized, global phase III trial. ResultsHigh IBCS patients showed better responses to immunotherapy-based combinations and had longer progression-free survival (PFS). Further transcriptomic analysis revealed that IBCS was negatively correlated to TIDE score, identifying a subset of RCC patients characterized by enrichment of T-effector and moderate cell-cycle/angiogenesis gene expression. Our analysis of hub genes unveiled a novel molecule that could potentially serve as a target antigen in RCC. Validation through multiplex immunofluorescence assays on tissue microarrays (TMAs) containing 180 samples confirmed the pivotal role of this hub gene in immunoregulation. Furthermore, we developed an independent risk score model, which is significant for prognostic evaluation and patient stratification. Notably, we devised a forecasting nomogram using this risk score model, surpassing the IMDC score (a widely accepted risk score for predicting survival in patients undergoing VEGF-targeted therapy) in prognostic accuracy for patients treated with immunotherapy-based combinations. ConclusionThis study has collectively developed an immunotherapy-based combination associated score, pinpointed effective biomarkers for prognostic and responsiveness of kidney cancer patients to immunotherapy-based combinations, and delved into their potential biological mechanisms, offering promising targets for further exploration.

Abstract B128: Underlying factors influencing kidney cancer surgical treatment disparities: Patients, non-patient community members and urologists’ perspectives

Abstract Background: Racial and ethnic minority patients often delay or forgo kidney cancer (KCa) surgical treatment and have an invasive surgical treatment. This study aimed to understand the underlying factors of KCa surgical treatment disparities through interviews with KCa patients and non-patients from racial and ethnic minority communities in Arizona and online surveys with urologists who practice in the U.S. Methods: We conducted phone interviews with KCa patients (n=13) and interviews at health events with community members without KCa (n=61). Online surveys were conducted with urologists (n=54). Results: Many interview participants had healthcare access issues with 22% reporting not having a primary care doctor and 12% reporting that there was a time when they could not see a doctor because of cost. Almost 50% reported that they had delayed care because they could not get an appointment soon enough. Among 10 patients who responded to a question about diagnosis delay, 4 answered that they waited over a year to see their doctor when they had health issues before their diagnosis. A quarter of community participants (25%) and about a third of patients (31%) reported that cultural values or religious beliefs influenced their choice of treatment. When community participants were asked what they knew about KCa symptoms and treatments, many did not provide relevant or correct information. Only 51% of non-patients reported that they trusted their doctor’s judgements about their medical care, but 92% of patients reported that they trusted their doctor’s judgement. About 30% of urologists reported that patients from racial and ethnic minority backgrounds often have healthcare access challenges, but only 9% responded that NHW patients often have challenges. They did not report that racial and ethnic differences in treatment exist. About 10% of urologists reported socioeconomic backgrounds of patients affect treatment decision and timeliness often or all the time. Only 46% reported that they refer patients to necessary services all the time, when patients express concerns of finance and healthcare access challenges. Many urologists strongly or slightly agreed that treatment decisions should be made by the treating clinicians (82%) and based on clinical information (87%). Many also strongly or slightly agreed that patients and their family members should contribute to decision-making (98%), while 46% strongly or slightly agreed that patients’ cultural and religious backgrounds often affect their treatment choices. In open-ended questions, urologists responded that work and family obligations, healthcare access, and health literacy rather than race and ethnicity are factors influencing treatment, while mistrust was identified as one of factors influencing treatment delay. Conclusions: Barriers to healthcare access, lack of knowledge, and mistrust before diagnosis may be underlying factors among patients, while urologists view healthcare access, social and economic factors, and mistrust influence KCa surgical treatment decision and delay. Citation Format: Ken Batai, Alex Cruz, Juan Adrover, Daphne Larose, D'Andre Gomez, Francine C. Gachupin, Jacquanette R. Slowtalker, Benjamin R. Lee, Juan Chipollini. Underlying factors influencing kidney cancer surgical treatment disparities: Patients, non-patient community members and urologists’ perspectives [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr B128.

126 Canadian Kidney Cancer Patients’ Treatment Preferences for Early-Stage Disease

126 Canadian Kidney Cancer Patients’ Treatment Preferences for Early-Stage Disease

Blood and Serum Se and Zn Levels and 10-Year Survival of Patients after a Diagnosis of Kidney Cancer.

The aim of the project was to evaluate the association between selenium (Se) and zinc (Zn) levels in blood and serum and kidney cancer mortality. In a prospective group of 284 consecutive, unselected patients with kidney cancer, we evaluated their 10-year survival rate in relation to the levels of Se and Zn in their blood and serum. Micronutrient levels were measured using an inductively coupled plasma mass spectrometer. Patients were divided into quartiles based on the distribution of Se and Zn levels arranged in increasing order. The following variables were taken into account in the multivariable models: age at diagnosis, gender, smoking, type of surgery and histopathological examination results. We observed a statistically significant association of all-cause mortality when subgroups with low blood selenium levels were compared to patients with high selenium levels (HR = 7.74; p < 0.001). We found, in addition, that this correlation was much stronger when only men were assessed (HR = 11.6; p < 0.001). We did not find a statistically significant association for zinc alone. When we combined selenium and zinc levels (SeQI-ZnQI vs. SeQIV-ZnQIV), we observed the hazard ratio for kidney cancer death to be 12.4; p = 0.016. For patients in the highest quartile of blood zinc/selenium ratio, compared to those in the lowest, the HR was 2.53; p = 0.008. Our study suggests that selenium levels, combined selenium and zinc levels (SeQI-ZnQI vs. SeQIV-ZnQIV) and zinc-to-selenium ratio (Zn/Se) are attractive targets for clinical trials aimed at improving the survival of kidney cancer patients.

Abstract Introduction

Abstract The 6th Kidney Cancer Research Summit (KCRS) took place on July 11th &amp; 12th, 2024 as a hybrid event both in Boston, Massachusetts at the InterContinental Boston, and virtually via Zoom webinar. The conference format consists of oral presentations in an intimate setting that enables dynamic discussion among attendees. The meeting began with a keynote titled “How the Air We Breathe Can Impact Cancer,” showing the biological processes underlying how airborne microparticles drive inflammatory processes that fuel tumorigenesis. Sessions included Exploring Novel Drug Targets for RCC, Novel Imaging and Biomarkers to Guide RCC Patient Management, State of the Science, Trials in Progress, Clinical and Scientific Updates in Kidney Cancer, Immunotherapy Advances and Research, Oral Abstracts, and Rapid Abstracts. The KCRS was inaugurated in 2019 to congregate the community of researchers conducting projects involving kidney cancer with clinicians, industry partners, and patient advocates in order to foster new collaborations and generate constructive feedback. KCRS is funded through sponsors, partnerships, and grassroots supporters organized by KidneyCAN, a nationwide network of kidney cancer patients, caregivers, and family members who are committed to accelerating cures for kidney cancer. Basic through translational and clinical research are included, and the program is centered on projects funded through the Department of Defense’s Kidney Cancer Research Program awards. The goal is to give current and future projects the best chance to succeed and ensure the orientation of goals towards raising the standard of care and improving patient outcomes across all histological subtypes and stages of this disease. This supplement contains a complete list of scheduled abstract presentations that were accepted as of June 17th, 2024. Please be aware that some abstracts may have been withdrawn or rescheduled at the authors’ request.

Psychosocial distress after radical prostatectomy, radical cystectomy, or (partial) nephrectomy - a comprehensive analysis of 4,290 German cancer patients during the COVID-19 pandemic.

To evaluate and identify predictors of psychosocial distress (PD) in patients after surgical treatment for prostate cancer (PC), bladder cancer (BC), or kidney cancer (KC) during the COVID-19 pandemic in a large, multi-institutional cohort. Patients undergoing inpatient rehabilitation (IR) after radical prostatectomy (RP), radical cystectomy (RC), or (partial) nephrectomy in one IR center in 2021 were included. PD was evaluated by the Questionnaire on Stress in Cancer Patients (QSC-R23) at the beginning (T1) and the end (T2) of IR. Regression analyses were performed to identify disease-specific predictors for high PD. A total of 4,290 patients (3,413 after RP, 563 after RC, 314 after (partial) nephrectomy) were included in this study. Median PD decreased significantly during IR across all tumor entities (each p < 0.001). The number of PC and BC patients suffering from high PD decreased significantly (each p < 0.001), but not in KC patients (p = 0.310). Younger age independently predicts high PD in all three malignancies, while additionally positive surgical margins (p = 0.016), ileal conduit (IC; p < 0.001), and nephrectomy (p = 0.032) independently predict high PD in PC, BC, and KC patients, respectively. During the Covid-19 pandemic the demand for individual psycho-oncologic counseling increased significantly in PC (p = 0.03) and KC (p = 0.001) patients. Younger age independently predicts high PD in the three main urological malignancies. Positive surgical margins in PCa, IC in BCa, and nephrectomy in KC are disease-specific independent predictors for high PD in the early period after surgical treatment. Disease-specific predictors for high PD may help clinicians identify patients at risk and may guide timely referrals to psycho-oncologic counseling in the early period after uro-oncologic surgery.

Hospital-Level Variability in the Adoption of Image-Guided Focal Therapy for Localized Prostate and Kidney Cancer

BackgroundFocal therapy, a minimally invasive procedure, offers targeted treatment for kidney and prostate cancer using image guidance. However, the current institutional landscape of its adoption in localized prostate and kidney cancer remains less understood. This analysis compares its usage between the 2 cancers to discern health system determinants affecting the adoption of these treatments. MethodsThe study used data from adult patients with localized prostate and kidney cancer from the National Cancer Database. We calculated adjusted probabilities of focal therapy usage per facility via multivariable mixed-effects logistic regression model with hospital-level random effects. We analyzed interhospital variability through ranked caterpillar plots and Spearman correlation coefficient. ResultsAmong 1,559,334 prostate and 425,753 kidney cancer patients, 1.6% and 6.3% received focal therapy, respectively. The interhospital variation ranged from 0.13% to 32.17% for prostate cancer and 1.16% to 30.48% for kidney cancer. The hospital-level odds of focal therapy for prostate and kidney cancer were weakly correlated (Spearman's ρ = 0.21; P < .001). ConclusionsOur analysis revealed a substantial hospital-level discrepancy in the utilization of focal therapy. Despite this, there was a limited correlation between the use of focal therapy for these two types of cancer within the same hospital. Our findings emphasize the presence of multifaceted factors influencing the adoption of focal therapy, both at facility and healthcare system levels.

Lesion-aware cross-phase attention network for renal tumor subtype classification on multi-phase CT scans

Multi-phase computed tomography (CT) has been widely used for the preoperative diagnosis of kidney cancer due to its non-invasive nature and ability to characterize renal lesions. However, since enhancement patterns of renal lesions across CT phases are different even for the same lesion type, the visual assessment by radiologists suffers from inter-observer variability in clinical practice. Although deep learning-based approaches have been recently explored for differential diagnosis of kidney cancer, they do not explicitly model the relationships between CT phases in the network design, limiting the diagnostic performance. In this paper, we propose a novel lesion-aware cross-phase attention network (LACPANet) that can effectively capture temporal dependencies of renal lesions across CT phases to accurately classify the lesions into five major pathological subtypes from time-series multi-phase CT images. We introduce a 3D inter-phase lesion-aware attention mechanism to learn effective 3D lesion features that are used to estimate attention weights describing the inter-phase relations of the enhancement patterns. We also present a multi-scale attention scheme to capture and aggregate temporal patterns of lesion features at different spatial scales for further improvement. Extensive experiments on multi-phase CT scans of kidney cancer patients from the collected dataset demonstrate that our LACPANet outperforms state-of-the-art approaches in diagnostic accuracy.

Spectacular clinical benefit achieved by multidisciplinary management of a kidney cancer patient

Spectacular clinical benefit achieved by multidisciplinary management of a kidney cancer patient

Neurogenesis-Associated Protein, a Potential Prognostic Biomarker in Anti-PD-1 Based Kidney Renal Clear Cell Carcinoma Patient Therapeutics.

The transketolase 1 gene (TKTL1) is an essential factor that contributes to brain development. Some studies have shown the influence of TKTL1 in cancers, but it has been rarely reported in kidney cancer. Furthermore, the role of TKTL1 in the prognosis and tumor infiltration of immune cells in various cancers, particularly kidney cancer, remains unknown. In this study, TKTL1 expression and its clinical characteristics were investigated using a variety of databases. TIMER was used to investigate the relationship between TKTL1 and immune infiltrates in various types of cancer. We also studied the relationship between TKTL1 expression and response to PD-1 blocker immunotherapy in renal cancer. We conducted TKTL1 agonists virtual screening from 13,633 natural compounds (L6020), implemented secondary library construction according to the types of top results, and then conducted secondary virtual screening for 367 alkaloids. Finally, in vitro assays of cell viability assays and colony formation assays were performed to demonstrate the pharmacological potency of the screening of TKTL1 agonists. Using these methods, we determined that TKTL1 significantly affects the prognostic potential in different types of kidney cancer patients. The underlying mechanism might be that the TKTL1 expression level was positively associated with devious immunocytes in kidney renal clear cell carcinoma (KIRC) rather than in kidney renal papillary cell carcinoma (KIRP) and kidney chromophobe (KICH). This recruitment may result from the up-regulation of the mTOR signaling pathway affecting T cell metabolism. We also found that TKTL1 may act as an immunomodulator in KIRC patients' response to anti-PD-1 therapy. Moreover, we also found that piperine and glibenclamide are potent agonists of TKTL1. We have demonstrated, in vitro, that piperine and glibenclamide can inhibit the proliferation and clone formation of Caki-2 cell lines by agonizing the expression of TKTL1. In summary, our discovery implies that TKTL1 may be a promising prognostic biomarker for KIRC patients who respond to anti-PD-1 therapy. Piperine and glibenclamide may be effective therapeutic TKTL1 agonists, providing a theoretical basis for the clinical treatment of kidney cancer.

Swine pseudorabies virus attenuated vaccine reprograms the kidney cancer tumor microenvironment and synergizes with PD-1 blockade.

The global incidence rate of kidney cancer (KC) has been steadily increasing over the past 30 years. With the aging global population, kidney cancer has become an escalating concern that necessitates vigilant surveillance. Nowadays, surgical intervention remains the optimal therapeutic approach for kidney cancer, while the availability of efficacious treatments for advanced tumors remains limited. Oncolytic viruses, an emerging form of immunotherapy, have demonstrated encouraging anti-neoplastic properties and are progressively garnering public acceptance. However, research on oncolytic viruses in kidney cancer is relatively limited. Furthermore, given the high complexity and heterogeneity of kidney cancer, it is crucial to identify an optimal oncolytic virus agent that is better suited for its treatment. The present study investigates the oncolytic activity of the Pseudorabies virus live attenuated vaccine (PRV-LAV) against KC. The findings clearly demonstrate that PRV-LAV exhibits robust oncolytic activity targeting KC cell lines. Furthermore, the therapeutic efficacy of PRV-LAV was confirmed in both a subcutaneous tumor-bearing nude mouse model and a syngeneic mouse model of KC. Combined RNA-seq analysis and flow cytometry revealed that PRV-LAV treatment substantially enhances the infiltration of a diverse range of lymphocytes, including T cells, B cells, macrophages, and NK cells. Additionally, PRV-LAV treatment enhances T cell activation and exerts antitumor effects. Importantly, the combination of PRV-LAV with anti-PD-1 antibodies, an approved drug for KC treatment, synergistically enhances the efficacy against KC. Overall, the discovery of PRV-LAV as an effective oncolytic virus holds significant importance for improving the treatment efficacy and survival rates of KC patients.

Perioperative Complications and In-Hospital Mortality in Partial and Radical Nephrectomy Patients with Heart-Valve Replacement

BackgroundIn-hospital mortality and complication rates after partial and radical nephrectomy in patients with history of heart-valve replacement are unknown.Patients and MethodsRelying on the National Inpatient Sample (2000–2019), kidney cancer patients undergoing partial or radical nephrectomy were stratified according to presence or absence of heart-valve replacement. Multivariable logistic and Poisson regression models addressed adverse hospital outcomes.ResultsOverall, 39,673 patients underwent partial nephrectomy versus 94,890 radical nephrectomy. Of those, 248 (0.6%) and 676 (0.7%) had a history of heart-valve replacement. Heart-valve replacement patients were older (median partial nephrectomy 69 versus 60 years; radical nephrectomy 71 versus 63 years), and more frequently exhibited Charlson comorbidity index ≥ 3 (partial nephrectomy 22 versus 12%; radical nephrectomy 32 versus 23%). In partial nephrectomy patients, history of heart-valve replacement increased the risk of cardiac complications [odds ratio (OR) 4.33; p < 0.001), blood transfusions (OR 2.00; p < 0.001), intraoperative complications (OR 1.53; p = 0.03), and longer hospital stay [rate ratio (RR) 1.25; p < 0.001], but not in-hospital mortality (p = 0.5). In radical nephrectomy patients, history of heart-valve replacement increased risk of postoperative bleeding (OR 4.13; p < 0.001), cardiac complications (OR 2.72; p < 0.001), intraoperative complications (OR 1.53; p < 0.001), blood transfusions (OR 1.27; p = 0.02), and longer hospital stay (RR 1.12; p < 0.001), but not in-hospital mortality (p = 0.5).ConclusionsHistory of heart-valve replacement independently predicted four of twelve adverse outcomes in partial nephrectomy and five of twelve adverse outcomes in radical nephrectomy patients including intraoperative and cardiac complications, blood transfusions, and longer hospital stay. Conversely, no statistically significant differences were observed in in-hospital mortality.

Abstract 7379: Deep learning based risk stratification of pre-operative CT scans is prognostic of overall survival in kidney cancers

Abstract Introduction: Preoperative risk stratification of kidney cancer patients is critical for treatment selection and improving mortality rates. Current clinical approaches such as cancer grading are limited by inter-reviewer variability, require invasive biopsy procedures, and might not capture the full extent of patient risk. We sought to evaluate a deep learning (DL) model to quantify patient risk and prognosticate overall survival in kidney cancer patients via CT scans. Methods: This retrospective study used preoperative contrast CT scans from 4 public multi-institutional collections with date of death/censoring available. A deep learning (DL) network architecture was developed to analyze input CT scans via a convolutional feature extractor and a Cox proportional hazards-based cost function. The DL model assigned a risk score to each patient, with the median risk used as a cutoff for classifying patients as high-risk or low-risk. Model performance for prognosticating overall survival (OS) was evaluated separately in training, internal validation, and external validation cohorts via Kaplan-Meier analysis in terms of concordance index and hazard ratios, with risk groups compared via Wilcoxon log-rank tests (α = 0.05). Results: In the training/internal validation cohort (N=418, 8 institutions) and external validation cohort (N=102, 1 institution), the median age was 60 and 59 years, the male/female ratios were 62%/38% and 75%/25%, with a median follow up of 2.8 and 3.1 years, respectively. The DL model yielded a training c-index of 0.66 (95% CI: 0.63-0.68), internal validation c-index of 0.73 (95% CI: 0.70-0.76) and an external validation c-index of 0.67 (95% CI: 0.64-0.70). Kaplan-Meier analysis of associated survival curves based on DL-determined high- and low-risk patients demonstrated statistically significant separation in all cohorts: training (p = 0.003, HR = 8.63, 95% CI: 8.28-8.98), internal validation (p = 0.027, HR = 4.89, 95% CI: 4.52-5.26), and external validation (p = 0.01, HR = 6.54, 95% CI: 6.18-6.90). Baseline clinicopathological characteristics were not significantly different between DL high and low risk patients in external validation (chi-square testing; ISUP grade p=0.375, age p=0.824, race p=0.567, and sex p=0.440). ISUP grade was also not a significant predictor of OS in internal validation (HR=1.57, p=0.211, 95% CI: 1.28-1.85) or external validation (p = 0.465, HR=0.16, 95% CI: 0.33-0.74). Conclusion: A deep learning model based on pre-operative CT scans was found to accurately prognosticate overall survival in kidney cancers in a multi-institutional setting, independent of clinicopathological factors. This model is being validated on larger cohorts, and in the context of targeted therapies. Citation Format: Brennan Flannery, Mohsen Hariri, Thomas DeSilvio, Amir Sadri, Jane Nguyen, Erick M. Remer, Smitha Krishnamurthi, Satish E. Viswanath. Deep learning based risk stratification of pre-operative CT scans is prognostic of overall survival in kidney cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7379.

Abstract 2298: Optimization of high-volume cell free DNA extraction and end-to-end automation for TSO 500 ctDNA library prep

Abstract Liquid biopsy such as plasma, has emerged as one of the most valuable sample types for profiling circulating tumor DNA (ctDNA) for screening, response to treatment, and monitoring relapse in oncology patients. Due to the diffuse nature of ctDNA however, both extraction and library preparation must be optimized for the efficient downstream next-generation sequencing (NGS) application. We initially addressed the optimization of quality and quantity of cfDNA recovery from healthy and various oncology patients by evaluating QIAsymphony DSP Circulating DNA Kit and Apostle MiniMax cfDNA isolation kits. Overall, the cfDNA yields from Apostle MiniMax kit were approximately 12X higher. We then optimized high-volume automated cfDNA extraction from 1ml, 3ml and 6ml plasma samples using the Biomek i7 for Apostle MiniMax kit. Colorectal, Gastric and Ovarian cancer gave the highest yield of cfDNA whereas, Esophageal, Lung and Kidney cancers were the lowest cfDNA yielding samples. We then analyzed ctDNA from plasma from healthy donors, colorectal, kidney, Breast, and endometrial cancer patients along with Oncospan and Seraseq ctDNA mutation mix (5-0.5% AF) to evaluate the mutation detection efficacy, repeatability, and reproducibility by targeted NGS using TSO 500ctDNA assay ay 10ng, 20ng, and 30ng inputs. For library preparation batches of 48 samples were prepared using a fully automated processes for the library prep, Hybridization capture and post capture enrichment on the Beckman i5 robot. Libraries were sequenced on NovaSeq 6000 at 600M Paired-end depth. This method demonstrates an overall concordance of inter-run and intra-run accuracy of variant detection to be 90% demonstrating that this method run as described produces highly repeatable and reproducible variant detection to sub-1% allele frequencies. The inter-run, lot-to-lot, and operator-to-operator variability was ≥99%. Down-sample analysis demonstrated high levels of assay performance with sample inputs of 30 ng with ≥96% sample passing Illumina cut-off metrics at 150M PE read depth as compared to Illumina recommended 420M PE reads. Taken together, we provide a high-volume automated solution for cfDNA extraction from plasma samples, additionally these data demonstrate a robust, reproducible, and highly accurate targeted DNA sequencing method that can be used for low allele frequency variant detection in cfDNA. Citation Format: Nripesh Prasad, Rachel Rock, Rebecca Beatty, Melanie Robinson, Dineen Wildman, Michael Sykes, Boris Umylny, Thomas Halsey. Optimization of high-volume cell free DNA extraction and end-to-end automation for TSO 500 ctDNA library prep [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2298.

Abstract 1786: Metabolic rewiring induced by protein or calorie restriction provides unique therapeutic vulnerabilities in translocation and select clear cell renal cell carcinomas

Abstract While the approval of several combinations with immune checkpoint inhibitors have significantly improved the outcome of kidney cancer patients, advanced clear cell and non-clear cell renal cell carcinoma (RCC) remain a clinical challenge. There has been a longstanding interest in using dysregulated metabolism as a therapeutic target due to its association with the pathogenesis and progression of several cancer types. As one of these highly metabolic tumors, RCC has the potential to greatly benefit from strategies targeting tumor metabolism. Dietary interventions are an innovative adjunct therapy that has the potential to induce a wide range of anti-cancer effects by disrupting metabolism due to the role diet plays in providing tumors with macromolecules for energy metabolism. Unfortunately, tumor cell plasticity, intratumor heterogeneity, and a lack of understanding regarding metabolic vulnerabilities in tumors limit the efficacy of implementing these strategies and a fundamental gap in the field remains as to how basic metabolic requirements of the tumor can be targeted with specific dietary interventions. In this study, the inherent metabolic phenotypes of translocation RCC (tRCC) and clear cell RCC (ccRCC) were characterized by integrating in vivo metabolomics and transcriptomics data, assessing mitochondrial and glycolytic activity in vitro via Seahorse, and performing immunohistochemical analyses of patient samples. Interestingly, the respective mitochondrial and glycolytic dependencies in tRCC and ccRCC patient-derived xenograft (PDX) models appear to influence the response to nutrient deprivation as seen by in vitro assays conducted after amino acid or glucose restriction. Importantly, these results indicate that dietary interventions may be able to selectively target metabolic vulnerabilities in tRCC and ccRCC. Ongoing combination studies with either protein or calorie restriction and targeted therapies, such as standard of care receptor tyrosine-kinase inhibitors, suggest the benefit of using dietary interventions as an adjunct therapy in RCC. Overall, these studies reveal that selective dietary interventions alter the metabolic landscape of RCC and expose vulnerabilities that can be exploited with targeted therapy. As dietary interventions are a safe, affordable, and potentially well tolerated adjunct therapy, we anticipate that the results of these studies will provide the biologic and mechanistic support for translating this strategy to advanced RCC patients. Citation Format: Sabrina A. Orsi, Christopher Rupert, Sean Colligan, Musea Chang, Abbas Jawadwala, Ilaria Delle Fontane, Filomena de Nigris, Roberto Pili. Metabolic rewiring induced by protein or calorie restriction provides unique therapeutic vulnerabilities in translocation and select clear cell renal cell carcinomas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1786.

Abstract 7390: Learning Llama Agents for medical record analysis and standardization

Abstract Introduction: The purpose of this study is to develop custom, open source, LLM enabled pipelines and agents for the extraction and standardization of data from free text medical records. Procedures: This project aims to create a versatile tool for healthcare data analysis, with initial development utilizing our extensive collection (over 10,000 documents) of renal cell carcinoma pathology reports. These reports are an ideal starting point as they cover over 20 years of care and consist of a racially and ethnically diverse cohort with over a quarter of patients being from traditionally underrepresented backgrounds. The jargon-abundant and highly technical nature of kidney cancer pathology represents a major challenge. We will accomplish this objective using an approach that balances the harnessing advanced AI capabilities with ensuring practicality and efficiency in real-world applications. First, we will leverage the capabilities of GPT-3.5/4 to generate a comprehensive labeled dataset (referred to as pseudo labels - machine-applied labels that will be used for training a newmodel) tailored for pathology, radiology, and clinician reports of kidney cancer patients. Second, we will harness the pseudo labeled datasets to train a smaller, open-source, yet highly efficient model for our specific needs (termed model distillation). LLAMA 2, known for its high performance in diverse tasks, is our model of choice. Its open-source nature and relatively modest computational requirements make it ideal for deployment within medical institutions. The ability to run locally ensures the protection of patient health information and reduces reliance on costlier, proprietary models. The rationale is threefold: first, to benefit from the superior performance and reasoning capabilities of GPT models; second, to create a streamlined model that is resource-efficient and tailored to our specific requirements; third, to enable the final streamlined model to be freely available by utilizing open source LLMs (e.g., Llama 2). To assess the feasibility of our methodology, we evaluated the ability of GPT-3.5 to label our data with high accuracy. Data Summary: Our pilot set of pathology reports consisted of 109 documents and 3 extraction fields: histology type, biopsy site, and biopsy procedure. Using GPT 3.5 we achieved an accuracy of over 95% in each extracted field type thereby demonstrating its ability to act as a proficient “teacher” model for our future open source “student” model. Conclusions: Our preliminary results suggest that current state of the art LLMs are highly proficient in extracting and standardizing information from clinical reports. Building out a full, open source, LLM enabled pipeline will increase the accuracy, flexibility, and efficiency of medical data extraction across institutions and lead to quicker and more informed decision-making in patient care and research. Citation Format: David Hein, Alana Christie, Hua Zhong, Ellen Araj, James Brugarolas, Lindsay Cowell, Payal Kapur, Andrew Jamieson. Learning Llama Agents for medical record analysis and standardization [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7390.