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13 citation(s) found for "Yuan, Gao".

Pediatric sarcomas: challenges and opportunities
Gao, Yuan, Bailey, Kelly M. , Blackman, Samuel C. , Bushweller, John H. , Chong, Shasha , DeHond, Kevin, Grembecka, Jolanta , Hatley, Mark E. , Kadoch, Cigall , Koehler, Angela N. , Linardic, Corinne M. , Renna, Phil, Stewart, Elizabeth A., Stillman, Bruce , Sweet-Cordero, E. Alejandro, Reu, Frederic J , Stillman, Bruce , Stegmaier, Kimberly , Vakoc, Christopher R , Guenther, Lillian M , Reu, Frederic J. , Rivera, Miguel N. , Stewart, Elizabeth A. , Sweet-Cordero, Alejandro

Genes & Development | August 4, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.1101/gad.353549.125 | PMID 42552078 Get It

Pediatric sarcomas are a heterogeneous group of rare mesodermal malignancies. These cancers, which affect children from infancy through adolescence and young adulthood, are in general challenging to treat with currently available therapies. Biologically, many are characterized by quiet genomes, fusion oncoproteins, immune “cold” microenvironments, and vast epigenetic deregulation that contributes to diverse and complex mechanistic drivers. Multifaceted advancements in research strategies, including high-throughput screening, new model systems, surfaceome profiling, and study of oncogenic fusion condensates have led to new opportunities for understanding the biology of pediatric sarcomas. To continue to make progress for these difficult to treat cancers, it will be critical to continue to improve access to bioinformatic data, approach patient care using innovative clinical trial frameworks, and foster interdisciplinary partnerships among medicinal chemists, scientists, clinicians, advocates, and industry partners.
Multi-modal AI for Opportunistic Screening, Staging and Progression Risk Stratification of Steatotic Liver Disease
Gao, Yuan , Li, Chun Li, Chang, W., Du, Bai , Ye, Xianghua , Xia, Ying , Liu, Wei , Bai, Ruo Bing, Li, Bei Bei, Hong, Yang , Cao, Kai , Yan, Ke , Li, Chunli , Chang, Wanxing , Du, Bai , Yeo, Yee Hui , Xia, Yingda , Guo, Heng, Zhang, Xiaoming , Bai, Ruobing , Li, Beibei , Hong, Yang , Yao, Jiawen , Lu, Le , Cao, Kai , Yan, Ke , Chen, Jun, Li, Jie , Hou, Yang (Greg), Zhang, Ling , Shi, Yu

No container title available | February 11, 2025 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.21203/rs.3.rs-5783643/v1 Get It

Abstract The prevalence of steatotic liver disease (SLD) is rising globally, presenting a significant public health challenge. While non-contrast computed tomography (CT) scans hold promise for the opportunistic detection of SLD, their full potential has not been systematically explored. Clinical indicators, such as serum data, are crucial for monitoring the progression of SLD. We introduce a novel Multimodal AI for Opportunistic Steatotic Liver Disease Screening (MAOSS), which integrates demographic data, serum tests, conventional CT biomarkers, and deep learning-derived CT image features to enhance model performance and explainability. MAOSS employs an innovative learning strategy, trained on a large-scale dataset (n = 1,783) encompassing both histopathologically-confirmed SLD and radiologically-reported steatosis cases. The model underwent extensive retrospective validation using steatosis grades derived from both histology and MRI-PDFF across internal and external datasets (n = 913), as well as real-world patient data (n = 18,504). It accurately detected mild to severe steatosis (≥ S1) with AUCs ranging from 0.903 to 0.929. Notably, MAOSS significantly improved the overall AUC for radiologists (n = 11) from 0.709 to 0.798 (p < 0.001). Furthermore, MAOSS was applied to optimize the standard clinical pathway for a simulated primary risk screening of SLD patients (n = 1,192), resulting in the identification of 31% more patients at risk of steatohepatitis and liver fibrosis progression, highlighting its potential to enhance SLD detection and management.
Characterization of Factors Associated With Death in Deceased Patients With Mitochondrial Disorders
Ivaniuk, Alina , Anselm, Irina , Bowen, Aaron B. , Cohen, Bruce H. , Eminoğlu, Fatma Tuba , Estrella, Jane , Gallagher, Renata C. , Gannon, Jennifer , Gorman, Gráinne S. , Greene, Carol L. , Haas, Richard , Kapoor, Seema , Karaa, Amel , Koenig, Mary Kay , Kornblum, Cornelia , Lichter‐Konecki, Uta , Lopriore, Piervito , McFarland, Robert , Moe, Aye , Ng, Yi Shiau , Saneto, Russell P. , Scaglia, Fernando , Tarnopolsky, Mark A. , Walker, Melissa , Group, as the Hong Kong Mitochondrial Diseases Interest, Fung, Cheuk Wing , Wong, Tsz-sum, Belaramani, Kiran , Chan, Chun-kong , Chan, Wing-ki, Chan, Wai-lun Larry, Cheung, H. M. E., Cheung, Ka-yin, Chang, Richard Shek‐kwan , Cheung, Sing-ngai, Cheung, Tsz-Fung, Cheung, Yuk-fai, Chong, Shuk-ching Josephine, Chow, Chi-kwan Jasmine , Fan, Florence , Fok, Wai-ming Joshua , Fung, Tsui-hang Sharon , Hui, Kwok-fai, Hui, Ting-hin, Ko, Chun Hung, Kwan, Min-chung, Kwok, Anne Mei Kwun , Kwok, Sung-shing Jeffrey, Lai, Moon-sing, Lam, Yau-on, Lam, Ching‐Wan , Lau, Ming-chung, Law, Hiu-Fung, Lee, Wing‐Cheong , Leung, Kin-hang, Leung, Kit-yan, Li, Siu-hung, Ling, Tsz-ki, Liu, Kam Tim , Lui, Colin H. T., Luk, Ching-on, Luk, Ho‐Ming , Ma, Che-Kwan, Ma, Karen , Ma, Kam-hung , Mew, Yuen-ni, Mo, Alex, Hg, Sui-Fun, Poon, Grace Wing-kit , Sheng, Bun , Szeto, Cheuk-ling Charing, Tai, Shuk‐Mui, Tang, Jing-Liang, Tse, Choi-ting Alan , Tsung, Li-yan Lilian, Wong, Ho-ming June, Wong, Wing-yin Winnie, Wong, Kwok-kui, Wong, Suet-na Sheila , Wong, Chun-nei Virginia, Wong, Wai-shan Sammy, Wong, Chi-kin Felix, Wu, Shun-Ping, Wu, Hiu-fung Jerome , Yau, Man-Mut, Yau, Eric Kin Cheong , Yeung, Wai Lan , Yeung, Hon‐Ming Jonas , Yip, Kin-keung Edwin, Young, Pui-hong Terence, Yuan, Gao , Yuen, Yuet‐Ping , Yuen, Chi-lap, Anselm, Irina A , Bowen, Aaron , Ganetzky, Rebecca D , Gannon, Jennifer , Gorman, Grainne S , Greene, Carol , Gropman, Andrea L , Haas, Richard H , Hirano, Michio , Kapoor, Seema , Karaa, Amel , Koenig, Mary Kay , Kornblum, Cornelia , Kose, Engin , Larson, Austin A , Lichter-Konecki, Uta , Lopriore, Piervito , Mancuso, Michelangelo , McFarland, Robert , Moe, Aye Myat , Ng, Yi Shiau , Saneto, Russell P , Scaglia, Fernando , Sue, Carolyn M , Tarnopolsky, Mark , Walker, Melissa A , Parikh, Sumit , Cheuk-Wing, Fung , Wong, Tsz-Sum , Belaramani, Kiran , Chan, Chun-Kong , Chan, Wing-Ki , Chan, Wai-Lun Larry , Cheung, Hon-Wing , Cheung, Ka-Yin , Chang, Shek-Kwan , Cheung, Sing-Ngai , Cheung, Tsz-Fung , Cheung, Yuk-Fai , Chow, Chi-Kwan Jasmine , Chung, Hon-Yin B , Fan, Sin-Ying Florence , Fok, Wai-Ming Joshua , Fung, Tsui-Hang Sharon , Hui, Kwok-Fai , Hui, Ting-Hin , Hui, Joannie , Ko, Chun Hung , Kwan, Min-Chung , Kwok, Mei-Kwan Anne , Kwok, Sung-Shing Jeffrey , Lai, Moon-Sing , Lam, Yau-On , Lam, Ching-Wan , Lau, Ming-Chung , Law, Chun-Yiu Eric , Law, Hiu-Fung , Lee, Wing-Cheong , Leung, Kin-Hang , Leung, Kit-Yan , Li, Siu-Hung , Liu, Kam-Tim Timothy , Lo, Fai-Man , Lui, Colin , Luk, Ho-Ming , Ma, Che-Kwan , Ma, Karen , Ma, Kam-Hung , Mo, Alex , Hg, Sui-Fun , Poon, Wing-Kit Grace , Sheng, Bun , Tse, Choi-Ting Alan , Wong, Ho-Ming June , Wong, Wing-Yin Winnie , Wong, Kwok-Kui , Wong, Suet-Na Sheila , Wong, Chun-Nei Virginia , Wong, Wai-Shan Sammy , Wu, Hiu-Fung Jerome , Yau, Kin-Cheong Eric , Yeung, Wai-Lan , Yeung, Hon-Ming Jonas , Yip, Kin-Keung Edwin , Young, Pui-Hong Terence , Yuan, Gao , Yuen, Yuet-Ping Liz , Ivaniuk, Alina , Cohen, Bruce H , Ganetzky, Rebecca , Larson, Austin , Morava, Éva , Sue, Carolyn M. , Parikh, Sumit , Group, as the Hong Kong Mitochondrial Diseases Interest, Fong, Ka-Wing, Lee, Han‐Chih Hencher , Tang, Jing-Liang, Wu, Hui-Jun

Neurology | January 30, 2025 | Volume: 104 | Issue: 4 | Pages: No page available

10.1212/wnl.0000000000209779 | PMID 39883904 Get It

Prostate Cancer, Version 3.2024
Schaeffer, Edward M. , Srinivas, Sandy, An, Yi , Bitting, Rhonda L. , Chapin, Brian F. , D’Amico, Anthony V. , Desai, Neil , Dorff, Tanya B. , Eastham, James A., Farrington, Thomas A., Gupta, Shilpa , Guzzo, Thomas, Karnes, R. Jeffrey , Kuettel, Michael, McKay, Rana R. , Morgan, Todd M. , Pow‐Sang, Julio M. , Reiter, Robert E. , Roach, Mack , Rosenfeld, Stan, Shabsigh, Ahmad , Valicenti, Richard K., Wong, J.K. , Snedeker, Jenna, Freedman-Cass, Deborah A., Morgan, Todd M , Robin, Tyler P. , Adra, Nabil , Cheng, Heather H. , Gao, Xin Yuan , Ippolito, Joseph E. , Lang, Joshua M. , Lotan, Tamara Levin , Spratt, Daniel E. , Szmulewitz, Russell Z , Teply, Benjamin A. , Tward, Jonathan D.

Journal of the National Comprehensive Cancer Network | April 16, 2024 | Volume: 22 | Issue: 3 | Pages: 140-150

10.6004/jnccn.2024.0019 | PMID 38626801 Get It

The NCCN Guidelines for Prostate Cancer include recommendations for staging and risk assessment after a prostate cancer diagnosis and for the care of patients with localized, regional, recurrent, and metastatic disease. These NCCN Guidelines Insights summarize the panel's discussions for the 2024 update to the guidelines with regard to initial risk stratification, initial management of very-low-risk disease, and the treatment of nonmetastatic recurrence.
Clinical outcomes of immune checkpoint inhibitor treatment in patients with classic cold tumors identified to have a high tumor mutational burden via ctDNA.
Lanka, Sree M , Clemens, Keelia , Kiedrowski, Lesli A. , Meyer, Haley M., Chang, Richard Y., Gulhati, Pat , Bilen, Mehmet Asım , Barnett, Reagan M. , Babiker, Hani M. , Bryce, Alan H. , Choi, Yujin , Garje, Rohan , Gao, Xin Yuan , Chang, Richard Y., Jang, Albert , Barata, Pedro C.

Journal of Clinical Oncology | June 4, 2023 | Volume: 41 | Issue: 16_suppl | Pages: 2561-2561

10.1200/jco.2023.41.16_suppl.2561 Get It

2561 Background: Some cancers, including breast, ovarian, pancreatic, and prostate cancers, are traditionally considered “cold” tumors, less likely to trigger an immune response and/or respond to immune checkpoint inhibitors (ICIs). However, some patients with these cancer types may benefit from ICIs. Here we investigate if a high blood tumor mutational burden (bTMB-H) may predict benefit to ICIs in such tumor types. Methods: We retrospectively queried the Guardant Health database for patients with advanced breast (n = 8531), ovarian (n = 1106), upper GI/pancreatic (n = 5110), and prostate (n = 7153) cancer who had ctDNA next-generation sequencing (Guardant360, Redwood City, CA) as part of routine clinical care from 2020-2022. Mutation profiles were evaluated for patients with bTMB-H (based on previously reported 80th percentiles for each tumor type, breast ≥15.31mut/Mb, ovarian ≥14.98mut/Mb, pancreatic ≥11.36mut/Mb, prostate ≥13.4mut/Mb) vs those with bTMB below this threshold (bTMB-L). A subset of cases were analyzed in a multi-institutional clinical cohort with a bTMB of ≥10mut/Mb (n = 35). Results: bTMB-H was observed in 9.5% of patients with breast cancer, 5.1% ovarian, 2.0% pancreatic, and 4.4% prostate. Genes more often mutated in patients with pTMB-H vs pTMB-L in each cancer type included TP53 and PIK3CA in breast cancer; TP53 and CHEK2 in ovarian; ATM and CHEK2 in pancreatic; TP53 and AR in prostate (all p values < 0.01). Patients in the clinical cohort (n = 35) had a median age of 74 (range: 40-85) 29/35 White / 4/35 Black, 27 prostate, 1 breast, 3 upper GI. Patients underwent first ctDNA analysis after a median of 3 (range 0-11) lines of therapy. The median bTMB detected was 16.59 mut/Mb (range: 10.02-152.85); six patients (6/35) were MSI-H. Twenty-three patients received ICI after a median of 6 (range: 0-8) lines of therapy, either alone (9, 39%) or in combination with hormonal therapy (5, 22%), chemotherapy (3, 13%) or targeted therapy (6, 26%). The median time to progression on ICI was 5.0 (95% CI, 3.6-6.4) months and median duration of response was 19.8 months (12.1-20.2). The ORR for evaluable patients was 13% and 74% of patients had progressed on therapy at time of data cut-off. Conclusions: "Cold” tumors represent a meaningful portion of patients with advanced cancer in which ICIs are not typically leveraged, and ctDNA was a feasible tool for identifying patients with bTMB-H who achieved durable responses from ICI-based therapy. The efficacy in this clinical cohort of traditionally “cold” tumors approaches other pan-cancer cohorts that include more traditionally immunoresponsive tumor types; further research is warranted to explore predictive value of bTMB, including potential tumor-specific thresholds, for optimizing patient selection for ICIs.
Blood-based tumor mutational burden from circulating tumor DNA and immune checkpoint inhibitors in advanced prostate cancer.
Rauterkus, Grant, Hadadi, Agreen , Weipert, Caroline , Drusbosky, Leylah , Lilly, Michael B. , Naqvi, Syed Arsalan Ahmed , Bilen, Mehmet Asım , Barnett, Reagan M. , Gao, Xin Yuan , Bryce, Alan H. , Barata, Pedro C.

Journal of Clinical Oncology | February 16, 2022 | Volume: 40 | Issue: 6_suppl | Pages: 165-165

10.1200/jco.2022.40.6_suppl.165 Get It

165 Background: A prior study of patients with advanced cancers treated with immune checkpoint inhibitors (ICI) associated improved overall survival with tissue tumor mutational burden above the 80th percentile in each histology (tTMB-H). TMB can also reliably be calculated via liquid biopsy (bTMB), and trends higher than tTMB in analogous tumors. Here, we generate a plasma-informed benchmark for bTMB-H in advanced prostate cancer and report preliminary data from an ongoing multi-institutional case series of patients treated with ICI. Methods: Circulating tumor DNA (ctDNA) next generation sequencing (NGS) results from 3,504 patients with advanced prostate cancer who received a Guardant360 liquid biopsy within a 12-month period were analyzed. The 80th percentile of TMB was defined as the benchmark for bTMB-H in this cohort, and prevalence of microsatellite instability (MSI-H) was determined. Subsequently, clinical data were collected from patients across five institutions who received pembrolizumab based on bTMB scores or other tumor characteristics (i.e. CDK12 mutation). Results: Overall, mean and median bTMB were calculated as 12.34 mut/Mb and 8.61 mut/Mb, respectively (range: 0 – 1164.75 mut/Mb). The 80th percentile of bTMB was 13.4 mut/Mb and the 90th percentile was 16.6 mut/Mb. 2.6% of patients were both MSI-H and bTMB-H. No patients with bTMB < 13.4 mut/Mb (TMB-L) were found to be MSI-H. Ten patients from five institutions received pembrolizumab (8 monotherapy) after a median of 4.5 lines of prior therapy (Table). Four patients were MSI-H. The 3 patients in the cohort with PSA decreases > 50% had both MSI-H and bTMB ≥ 13.4 mut/Mb. Per RECIST criteria, disease was controlled (CR, PR, SD) in 6 of 7 (86%) patients with bTMB scores ≥ 13.4 mut/Mb. Conclusions: These data continue to affirm that ctDNA NGS is a practical and cost-effective means of assessing potential predictors of ICI activity in patients with advanced prostate cancer. Preliminary data from this growing cohort of patients who have received ICI guided by bTMB scores and other molecular parameters identified via ctDNA NGS, including MSI-H, demonstrate a clinical benefit from therapy. Further studies are warranted for contextualizing individual tumor bTMB scores with established, pathology-specific benchmarks.[Table: see text]
Defining Proximity Proteome of Histone Modifications by Antibody-Mediated Protein A-APEX2 Labeling
Li, Xinran , Zhou, Jiaqi , Zhao, Wenjuan , Wen, Qing , Wang, Weijie , Peng, Huipai , Gao, Yuan , Bouchonville, Kelly J. , Offer, Steven M. , Chan, Kui Ming , Wang, Zhiquan , Li, Nan , Gan, Haiyun , Offer, Steven M , Wang, Zhiquan

Genomics, Proteomics & Bioinformatics | September 30, 2021 | Volume: 20 | Issue: 1 | Pages: 87-100

10.1016/j.gpb.2021.09.003 | PMID 34555496 Get It

Abstract Proximity labeling catalyzed by promiscuous enzymes, such as APEX2, has emerged as a powerful approach to characterize multiprotein complexes and protein–protein interactions. However, current methods depend on the expression of exogenous fusion proteins and cannot be applied to identify proteins surrounding post-translationally modified proteins. To address this limitation, we developed a new method to label proximal proteins of interest by antibody-mediated protein A-ascorbate peroxidase 2 (pA-APEX2) labeling (AMAPEX). In this method, a modified protein is bound in situ by a specific antibody, which then tethers a pA-APEX2 fusion protein. Activation of APEX2 labels the nearby proteins with biotin; the biotinylated proteins are then purified using streptavidin beads and identified by mass spectrometry. We demonstrated the utility of this approach by profiling the proximal proteins of histone modifications including H3K27me3, H3K9me3, H3K4me3, H4K5ac, and H4K12ac, as well as verifying the co-localization of these identified proteins with bait proteins by published ChIP-seq analysis and nucleosome immunoprecipitation. Overall, AMAPEX is an efficient method to identify proteins that are proximal to modified histones.
Phase 1/2 study of eprenetapopt (APR-246) in combination with pembrolizumab in patients with solid tumor malignancies.
Starr, Jason S. , Furqan, Muhammad , Ahrorov, Afzal, Hickman, Denice , Gubits, Amy, Attar, Eyal C. , Park, Haeseong , Dumbrava, Ecaterina E. , Mahipal, Amit , Gao, Xin Yuan , Shapiro, Geoffrey I. , Singh, Parminder Pal , Ahrorov, Afzal, Awad, Mark M. , Das, Satya Narayan

Journal of Clinical Oncology | June 2, 2021 | Volume: 39 | Issue: 15_suppl | Pages: TPS3161-TPS3161

10.1200/jco.2021.39.15_suppl.tps3161 Get It

TPS3161 Background: The p53 pathway has been implicated in antitumor immunity, including antigen presentation and T-cell proliferation. Loss of p53 function can increase resistance to immunotherapy across many tumor types. Eprenetapopt (eprenet) is a small molecule that stabilizes the folded structure of p53, resulting in activation of mutant p53 and stabilization of wild-type (WT) p53. It also targets the cellular redox homeostasis, resulting in induction of apoptosis in tumor cells. In vivo, mice carrying supernumerary copies of the TP53 gene harbor a pro-inflammatory tumor microenvironment, an effect recapitulated in TP53 normal-copy mice treated with eprenetapopt. Combining eprenetapopt and anti-PD1 or anti-CTLA4 therapy resulted in enhanced tumor growth inhibition and improved survival in TP53 WT mice inoculated with B16 melanoma and MC38 colon adenocarcinoma cells . Based on these results, we hypothesized that eprenet-induced p53 stabilization may augment response to immunotherapy. To test this hypothesis, we are conducting a phase 1b/2 study of eprenet in combination with pembrolizumab (eprenet+pembro) in pts with solid tumors. Methods: The primary objectives are to determine the maximum tolerated dose (MTD) and recommended phase 2 dose (RP2D) and to assess the safety and tolerability of eprenet+pembro in pts with advanced solid tumors. The secondary objectives are to estimate the anti-tumor activity and to describe the pharmacokinetics of the combination. Exploratory objectives include assessing predictive and pharmacodynamic markers of response. The study includes a safety lead-in with a 3+3 dose de-escalation design for pts with advanced solid tumors with known tumor TP53 mutation status ( TP53 WT is acceptable) (max 18 pts), followed by expansion cohorts in pts with NSCLC, gastric/GEJ and urothelial cancer (max 100 pts). In expansion, pts with urothelial and gastric cancers must be naïve to anti-PD-1/ L1 therapy. Eprenet is given IV once daily on Days 1–4 while pembro is administered on Day 3 of each 21-day cycle. The RP2D of eprenet+pembro is considered the dose at which ≤ 1 of 6 pts in a cohort has a dose-limiting toxicity (DLT). Primary endpoints are occurrence of DLTs, adverse events (AEs) and serious AEs with eprenet+pembro. Key secondary endpoints are best objective response, progression free survival and overall survival. Exploratory endpoints include gene mutations by next generation sequencing (including TP53), mRNA expression, multiplex immunohistochemistry and transcriptomics, multiplex flow cytometry on peripheral blood mononuclear cells and cytokines in serum. Continuous monitoring of toxicity will be conducted. The trial opened in May 2020 and is actively enrolling patients. Clinical trial information: NCT04383938.
Use of immune checkpoint inhibitors (ICIs) after prior ICI in metastatic renal cell carcinoma (mRCC): Results from a multicenter collaboration.
Ravi, Praful , Sorenson, K, Rathi, Nityam , Bakouny, Ziad , Agarwal, Neeraj , Costello, Brian A. , McKay, Rana R. , Alva, Ajjai , Bakouny, Ziad , Mantia, Charlene M. , Su, Christopher , Agarwal, Neeraj , Narayan, Vivek , McGregor, Bradley A. , Gao, Xin Yuan , McDermott, David F. , Choueiri, Toni K.

Journal of Clinical Oncology | May 25, 2020 | Volume: 38 | Issue: 15_suppl | Pages: 5077-5077

10.1200/jco.2020.38.15_suppl.5077 Get It

5077 Background: Several ICIs are used in first and subsequent lines of therapy for mRCC, either alone or in combination with another ICI or targeted therapy (TT). There are no data on the efficacy and safety of using an ICI in patients who have already received an ICI in a prior line of therapy. Methods: We reviewed patients with mRCC at 8 institutions who received 2 separate lines of ICI therapy (ICI-1, ICI-2), including as a single-agent and/or combination with other agents. The primary outcomes were overall response rate (ORR) and time to progression (TTP) with ICI-1 and ICI-2. Immune-related adverse events (irAEs) were graded using CTCAEv5.0. Results: 65 patients were included. Median age at diagnosis of mRCC was 60 years (range 30-86) and the majority had clear cell RCC (n=56, 86%). Median follow-up was 3.5 years (95% CI 2.9-4.4). Median lines at which ICI-1 and ICI-2 were received were 1 (1-6) and 3 (2-8) respectively. Reasons for discontinuing ICI-1 were disease progression (n=47, 72%), toxicity (n=15, 23%) or other (n=3, 5%). Therapies received at ICI-2 were single-agent ICI (n=26, 40%), or combinations of ICI with another ICI (n=20, 31%), TT (n=11, 17%) or other agent (n=8, 12%). Responses to ICI-1 and ICI-2 are shown in the Table; ORR to ICI-2 was significantly lower than to ICI-1 (23% vs. 36%, p=0.044). Amongst those who responded to ICI-2 (n=14), 7 (50%) received single-agent ICI, and the remainder received ICI in combination with another ICI (n=4, 29%) or TT (n=3, 21%); 7 patients (50%) had previously responded to ICI-1. The ORR to ICI-2 was higher in responders to ICI-1 (32%) compared to those with SD (17%) or PD (15%) to ICI-1. Median TTP (mTTP) at ICI-2 was shorter compared to ICI-1 (5.3 months vs. 8.5 months, Wilcoxon p=0.024). 29 patients (45%) experienced an irAE with ICI-2; 8 (12%) and 3 (5%) had a grade 3 or 4 irAE respectively, with 3 (30%) of these patients having previously had ≥grade 3 irAE to ICI-1. There were no treatment-related deaths. Conclusions: The ORR to ICI-2 was 23%, which is comparable to that seen with ICI after prior TT. Responses were seen even amongst those receiving single-agent ICI at ICI-2 and the likelihood of response to ICI-2 was higher if a patient had previously responded to ICI-1. No increase in toxicity with ICI-2 was apparent. Additional data from prospective studies are needed to determine whether sequential ICI has a role in treatment of mRCC. [Table: see text]