Clinical Research Research Articles

Abstract 5793: Measurement of basophil activation using a flow cytometry method for applications in clinical research and clinical trials

Abstract Background: Basophils are a type of white blood cell that play a role in the immune system, particularly in defending the body against allergens, pathogens, and parasites. Basophils also can contribute to the immune response directed against cancer cells by releasing histamine and other mediators that can enhance inflammation and recruit other immune cells to the tumor site. They express high-affinity immunoglobulin E (IgE) receptors, which are involved in recognizing and responding to antigens presented by cancer cells. Basophils may also play a role in modulating the tumor microenvironment, potentially influencing the effectiveness of immunotherapies and understanding the exact mechanisms make the study of basophil activation an exciting area for developing novel therapeutics. Methods: Basophil cells can become activated when the antigen loaded IgE antibody recognizes and binds to the Fc receptor (FcεRI) on the basophil surface. Basophil activation also causes certain markers to be upregulated on the surface of the cell that can be measured by flow cytometry to determine basophil activity. The basophil activation test (BAT) was conducted with human whole blood samples using a commercially available basophil activation kit. Whole blood specimens from human donors were collected in EDTA blood collection tubes. Blood was stimulated with FCεR1 and fMLP and staining reagent for 25 - 30 minutes at 37°C. Cells were lysed, washed and acquired on the flow cytometer. Results: CCR3 was used to identify the basophil population in human whole blood. CD63 and CD203c were then used to identify the unstimulated and stimulated state of the cells. Upon stimulation there was an increase in CD63 and CD203c expression on the surface of the basophils. Conclusions: These results showed that the basophil activation can be measured using flow cytometry with the increased expression of CD63 and CD203c on stimulated basophils. This method could be used to help scientists in clinical research and clinical trials to monitor allergic diseases, predict responses to immunotherapy, and assess the effectiveness of treatments, including immunoncology drugs. Citation Format: Jennifer J. Stewart, Lynette Brown. Measurement of basophil activation using a flow cytometry method for applications in clinical research and clinical trials [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5793.

Abstract 2973: Discovery of novel synthetic lethal targets for effective and safe colorectal cancer therapies

Colorectal cancer (CRC) poses a significant global health burden, highlighting the urgent need for innovative and effective treatment options. This study focuses on the discovery and validation of novel therapeutic targets, particularly synthetic lethal (SL) interactions, to exploit specific genetic vulnerabilities in CRC cells and enable the development of safer and more effective therapies. We employed a comprehensive strategy integrating healthy cells, genetically engineered isogenic cancer models derived from human intestinal stem cells (hISCs) with patient-derived xenografts (PDXs) and primary cell cultures. Using CRISPR/Cas9 technology, we introduced key CRC-associated mutations into the hISCs to replicate disease-specific contexts. Transcriptome profiling, coupled with machine learning, validated these models as robust, clinically relevant representations of tumor biology by aligning them with clinical datasets. Genome-wide CRISPR/Cas9 screenings conducted across the isogenic and patient-derived models revealed actionable vulnerabilities, including the identification of genes that are synthetically lethal with APC and KRAS mutations. Discovered SL targets were rigorously validated in vitro and in vivo using patient-derived cells with matching mutational profiles. This integrative approach bridges preclinical and clinical research, ensuring translational relevance. By identifying and validating SL targets tailored to CRC mutational landscapes, we provide a robust foundation for the development of novel treatment options for CRC patients. Citation Format: Andrzej Mazan, Marcin Duleba, Eliza Zimolag, Joanna Szuszkiewicz, Marcin Serocki, Joanna Krawczyk, Oleksii Bryzghalov, Agata Stachowicz-Walaszek, Izabella Wieckowska, Marcelina Chmiel, Alexander Kurzejamski, Barbara Lipert, Katarzyna Sarad, Michal Mikula, Rafal Dziadziuszko, Tomasz Rzymski, Andrew Thomason, Krzysztof Brzozka. Discovery of novel synthetic lethal targets for effective and safe colorectal cancer therapies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2973.

Abstract 2990: Single-slide FFPE proteomic profiling enables therapeutic target quantification and molecular subtyping in non-Hodgkin’s lymphoma and bone marrow tumor biopsies

Abstract Molecular profiling of formalin-fixed paraffin-embedded (FFPE) tumors in clinical research is performed with low-plex immunohistochemistry or genome-wide transcriptomics. The application of unbiased, highly multiplexed proteomics to FFPE is limited by sample input requirements, assay throughput and complex bioinformatics. Here we report a proteomic method amenable to low-input FFPE profiling which complements transcriptomics. We applied Biognosys’ mass-spectrometry platform (TrueDiscovery, DIA-MS) to samples encountered in routine histopathology laboratories (e.g. B-cell malignancies [n = 35], and breast, pancreatic and colorectal tumors [n=8]). FFPE samples were deparafinzed, de-crosslinked followed by trypsin digestion, and resulted peptides were analyzed by directDIA. Impact of tissue staining by Hematoxylin and Eosin (H&E) and acid decalcification was also assessed. We compared a deep-proteome workflow on a Thermo Scientific Orbitrap Exploris 480 to a novel high throughput workflow on a Bruker timsTOF HT. The deep-proteome workflow with single-slide FFPE tissues (median area 35mm2) generated comprehensive proteome coverage: ∼12,000 proteins detected overall and ∼7,000 detected in the majority of samples. The high throughput Bruker workflow delivered similar data with 80% less input in 20% of the time. Proteomes from H&E stained, cover-slipped slides were nearly identical to adjacent unstained tissue. Interestingly, proteomics profiling was successful in acid decalcified leukemia bone marrow biopsies whereas RNA was not recoverable. To assess the detection of key tissue biomarkers for therapeutic decision-making, we compiled a list of FDA approved antibody based therapeutic targets and found 20 of 21 were detectable in our samples (e.g. PDL1, PD1, LAG3, CD19, CD20 and CD38). Similarly, >80% of 55 immuno-oncology targets undergoing clinical development were detected. A key effector function of antibody therapeutics is complement-dependent cytotoxicity. The presence of complement components was confirmed by proteomics, however, some were undetectable by transcriptomics. Diffuse Large B-cell Lymphoma samples in this study were molecularly subtyped for a key prognostic, Cell of Origin (COO), using a CLIA validated RNA assay (Lymph2Cx). Well studied proteins (e.g. MUM1 and CD10) showed expected distribution based on patient COO, demonstrating proteomics can recapitulate established subtyping methods. We demonstrate that proteomics profiling can be conducted on single FFPE slides even with pre-processed tissue. This high-throughput workflow enables real-time analysis of Phase I trials or large tissue banks. Furthermore, proteome profiling provides an opportunity to consolidate testing for multiple therapeutic targets instead of serial IHC assays, maximizing the use of precious tissue biopsies. Citation Format: Matthew Loya, Tine Casneuf, Helene Bon, Manling Ma-Edmonds, Angelo Harris, Daniel Martin, Anantharaman Muthuswamy, Dominique Kamber, Martin Mehnert, Amaury Lachaud, Yuehan Feng, Mark Fereshteh, Omar Jabado. Single-slide FFPE proteomic profiling enables therapeutic target quantification and molecular subtyping in non-Hodgkin’s lymphoma and bone marrow tumor biopsies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2990.

Where is clinical research in radiation oncology going? a snapshot from Lombardy, Italy-a study endorsed by AIRO Lombardia.

The research activity is fundamental to improve knowledge in Medicine. In the setting of clinical oncology, radiotherapy (RT) represents a cornerstone for patients treated with curative intent. The aim of this snapshot was to investigate the number and the characteristics of clinical trials currently ongoing in the Lombardy (Italy) RT divisions highlighting involved resources and eventual needs to improve the process of study activation. In April 2024, a survey composed of two parts, a snapshot of clinical and research activity and a database to report data on ongoing clinical trials, was proposed to the 30 RT centers in Lombardy. The snapshot consisted of 19 short answer questions. A total of 26 (87%) centers answered the survey. The total number of active studies was 161. The median age among principal investigators was 51 years. Most studies were multicentric (61%) national (76%). Among 72 studies with available phase, 43% resulted phase III studies. Fifty-three (33%) studies were sponsored. IRCCS (Istituti di Ricovero e Cura a carattere scientifico) RT have a median of 11 active studies vs versus 6 in non-IRCCS structures. More resources are available in IRCCS centers compared to non-IRCCS: data management service 50% vs 25%, dedicated scientific nurses 20% vs 0%, clinical statistics services 60% vs 25%. The main difficulties in conducting clinical trials were bureaucratic difficulties with ethics committees (5 centers), time constraints (5 centers), and a lack of resources and staff (15 centers). The most frequently (58% of the centers) proposed solution was an increase in resources and staff. While the RT centers in Lombardy demonstrate a commendable commitment to clinical research, disparities in resources and infrastructure remain significantly challenging.

Abstract 5264: Harnessing glioma-inhibitory macrophages for sustained control of glioblastoma progression

Abstract Despite intensive basic and clinical research over the past 30 years, there has been minimal improvement in outcomes for patients with glioblastoma, the deadliest form of adult brain cancer. Several factors contribute to this therapeutic challenge, including a complex interaction between the tumor and the innate immune compartment of the brain microenvironment, that is thought to support glioma proliferation and treatment resistance. Previously, we established that glioma cells can communicate with microglia/macrophage by producing the dual-function (secreted and nuclear) cytokine interleukin 33 (IL33). We found that IL33 supports the recruitment and reprogramming of pro-tumorigenic macrophage to fuel rapid and fatal tumor growth. However, in contrast, when IL33 is prevented from entering the nucleus, by loss of its nuclear localization signal (ND-IL33), tumor growth is dramatically suppressed. Using multiplex immunohistochemistry across different stages of tumor progression, we uncovered a population of macrophages unique to this growth restrictive environment, which we term glioma-inhibitory macrophages (GIMs). To resolve the molecular features of GIMs, we performed spatial transcriptomics and a computational workflow based on unsupervised deconvolution to identify cell types and activities enriched within the ND-IL33 environment. This strategy revealed that GIMs upregulate phagocytosis and antigen processing/presentation pathways and exhibit features of granulocytic cells. When examining xenografts established from patient-derived brain tumor-initiating cells, we observed a notable increase in the presence of GIMs in xenografts that exhibited long-term survival (>300 days) compared to those with short-term survival (<100 days). The tumor-suppressive nature of GIMs was further supported by experiments in which tumors formed by a combination of ND-IL33-expressing cancer cells and highly tumorigenic cells led to a growth-restrictive environment that significantly extended survival. Further functional characterization of this macrophage phenotype and development of strategies to deliver ND-IL33 to brain tumors is necessary to determine whether the recruitment and activation of GIMs could be an effective therapeutic approach for patients with glioblastoma. Citation Format: Shyam V. Menon, Xueqing Lun, Tala-Maria Mouannes, Peipei Zeng, Varsha T. Manoharan, Jianbo Zhang, Isabelle Carrier, Eduardo Diez, Alisha Poole, Ngoc Ha Dang, Bo Young Ahn, Katalin Osz, Sorana A. Morrissy, Jennifer A. Chan, Daniela F. Quail, Stephen M. Robbins, Donna L. Senger. Harnessing glioma-inhibitory macrophages for sustained control of glioblastoma progression [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5264.

Abstract 1295: A translational approach to ADC evaluation: preclinical single-mouse basket trial with Bayesian modelling analysis

Abstract Introduction: Antibody-drug conjugates (ADCs) have revolutionized cancer therapy, exemplified by the clinical success of HER2-targeting ADCs like Trastuzumab-Deruxtecan (T-Dxd), which demonstrates efficacy across a spectrum of HER2 expression levels. However, ADC development remains challenging due to translational gaps between preclinical and clinical findings. This study introduces a robust translational approach for ADC evaluation, combining a single-mouse preclinical model using MiniPDX® technology with Bayesian statistical analysis—a widely recognized and commonly applied statistical approach in clinical research. Bayesian analysis offers the advantage of integrating prior knowledge with experimental data to generate probabilistic predictions, providing a dynamic and nuanced understanding of treatment efficacy. Our study mimics clinical trials of T-Dxd and Trastuzumab-Emtansine (T-DM1) using this robust, translational framework to bridge the gap between preclinical and clinical evaluation. Methods: We selected 20 PDX models over six cancer types, representing HER2 expression levels (high, medium, low, and negative control). Tumor tissues were dissociated into single-cell suspensions and implanted subcutaneously in mice via MiniPDX capsules. Each mouse received a single 10 mg/kg dose of T-Dxd or T-DM1 over 10 days. Tumor cell viability was assessed using CellTiter-Glo, and tumor relative proliferation rate was calculated as Treatment/Control ratios (T/C%). A T/C ratio <50% indicated significant response. Bayesian modelling was applied to estimate the probability of tumor inhibition across HER2 cohorts. Results: T-Dxd demonstrated a 100% overall response rate (ORR) in HER2-high models, with significant tumor inhibition. Additionally, T-Dxd exhibited substantial efficacy in HER2-medium (ORR 75%) and HER2-low (ORR 60%) groups. In contrast, T-DM1 displayed strong tumor inhibition in HER2-high models but limited efficacy in HER2-medium and HER2-low groups. In addition, Bayesian analysis yielded posterior probabilities of 83%, 66%, and 54% that T-Dxd slows down tumor growth by 50% when compared to control for the HER2-high, HER2-medium, and HER2-low groups, respectively. Conclusion: Our study demonstrates the feasibility and promising results of preclinical single-mouse trials using MiniPDX®. The Bayesian statistical analysis provides a rich summary of the effects of T-Dxd and T-DM1. This approach bridges the translational gap, offering a platform to predict ADC efficacy and guide candidate selection in the preclinical setting. Citation Format: Diandong Jiang, Yuan Ji, Jiaxin Liu, Bin Xie, Hongkui Chen, Shizhu Zhao, Le Li, Yu Di, Xinlei Chen, Xiaorong Gu, Huanhuan Zhang, Zhenle Bi, Kaimeng Hu, Loc Van, Josh Caggiula, Yulan Tang, Danyi Wen. A translational approach to ADC evaluation: preclinical single-mouse basket trial with Bayesian modelling analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 1295.

Abstract 2927: CS2011: A novel bispecific antibody targeting EGFR and HER3 that demonstrates promising antitumor activity in preclinical evaluation

Abstract Background: EGFR (also known as HER1) is an epidermal growth factor receptor with tyrosine kinase activity implicated in both tumorigenesis and tumor progression, and its overexpression in approximately 70% of colorectal cancer (CRC), 60% of lung cancers, and over 90% of head and neck squamous cell carcinoma (HNSCC) have been shown associated with advanced diseases. Approved anti-EGFR therapies, including cetuximab, pantitumumab, and necitumumab, are widely used in treating the aforementioned malignancies. Amivantamab, a bispecific antibody targeting EGFR and c-MET, has been approved for treating advanced NSCLC with EGFR mutations. HER3, another member of the HER family, is overexpressed in cancers including CRC and lung cancer. The upregulation of HER3 has been reported in tumors when treated with MAPK/PI3K inhibitors, EGFR TKIs, or hormone therapies. Daiichi’s HER3-ADC, U3-1402, has shown promising clinical results in advanced EGFR-mutant NSCLC, confirming HER3 as a valid therapeutic target. CS2011 is a bispecific antibody composed of a potent anti-EGFR arm and a fully functional anti-HER3 arm. Unlike anti-EGFR, anti-HER2 or anti-HER3 mono-targeting antibodies, CS2011 inhibits almost all functional membrane dimers formed with HER members, and therefore acts as a broad epithelial growth factor signaling blocker to address tumor heterogeneity effectively. Methods & Results: The lead molecule of CS2011, J17, was constructed with monovalent arms targeting EGFR and HER3. J17 showed high binding affinities to EGFR or HER3 respectively and dual binding to EGFR & HER3 concurrently, as assessed by BLI. Our data further demonstrated that J17 possessed single-digit nanomolar affinities to EGFR-positive and/or HER3-positive tumor cells, while demonstrating no binding activity to EGFR/HER3-negative cells. J17 induced faster and deeper internalization compared to anti-EGFR and anti-HER3 mono-targeting antibodies. J17 also effectively inhibited EGFR downstream signaling to levels similar to anti-EGFR antibodies. Furthermore, J17 inhibited NRG1 (HER3 ligand)-induced proliferation of A431 cells. In-vivo studies further demonstrated potent tumor growth inhibition by J17. J17 also demonstrated favorable stability and developability, achieving yields comparable to those of monoclonal antibodies. Pilot pharmacokinetic (PK) and toxicity studies in cynomolgus monkeys suggested a monoclonal antibody-like PK profile and favorable tolerability at 30 mg/kg. Conclusion: CS2011 is a promising bispecific antibody for the treatment of various advanced solid tumors. Current preclinical data support further IND-enabling development and clinical research on CS2011. Citation Format: Chuan Wang, Ning Zhang, Xinling Zhang, Yongwang Li, Yongli Yang, Mengyao Zhu, Yuxin Qian, Jingyu Sun, Xuelian Liu, Fei Ma, Yi Sun, Jianxin Yang. CS2A novel bispecific antibody targeting EGFR and HER3 that demonstrates promising antitumor activity in preclinical evaluation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2927.

Abstract 2239: FB849, a highly selective HPK1 inhibitor, reshapes the tumor immune microenvironment by modulating various immune cells

A highly unmet medical need exists for immuno-oncology agents to modulate the tumor microenvironment through broad-spectrum immune cell modulation by promoting crosstalk among T cells, B cells, and APCs, to exert a strong and durable anti-cancer immunity. Beyond T cells, other immune cells can play a crucial role in driving clinical activity, particularly in combination with current checkpoint inhibitors or patients with T cell dysfunction. We have discovered and developed FB849, a potent, highly selective, and orally bioavailable HPK1 inhibitor. FB849 has demonstrated robust anti-tumor activity across multiple preclinical models and is currently being evaluated in a Phase I/II clinical trial for advanced solid tumors (NCT05761223). To elucidate its immune-modulatory mechanisms and impact on both T cells and non-T cells, we extended our research to human primary immune cells and tumor-infiltrating lymphocytes (TILs). FB849 effectively activated T cells increasing IL-2 and IFNγ production, and stimulated B cell secreting IgG, IL-6 and IL-8. In monocyte-derived DCs, FB849 also significantly enhanced the secretion of IL-12 and IL-1β, and CD80 and CD86 expression. In vivo mouse TIL analyses revealed that FB849 increased T cell activation while re-shaped the myeloid compartment within the tumors by increasing dendritic cell infiltration with elevated cDC1, promoting tumor-associated macrophage (TAM) depletion with M1 polarization, and increasing NK cell infiltration. These create a tumor microenvironment favorable to anti-cancer immunity. Notably, FB849 retained anti-tumor activity even after CD8 T cell depletion, highlighting the pivotal role of non-T cells. To further delineate FB849’s effects on TILs, we conducted single-cell RNA sequencing and TCR sequencing with the single cell suspension samples from RCC, HCC, HNC and BRC patients. FB849 prominently expanded multiple types of T cell clones, especially the CXCL13+ CD8 TIL cluster enriched with neoantigen signature genes. Furthermore, TCR sequencing revealed a considerable overlap in between CXCL13+ CD8 and MKI67+ CD8 T cells when stimulated with autologous EpCAM+ tumor cells or NY-ESO-1 overlapping peptides, validating that CXCL13+ CD8 TILs are tumor-reactive. We hypothesize that the intra-tumoral expansion of CXCL13+ CD8+ T cells enhance interactions between T cells and various non-T cells including B cells and dendritic cells, potentially driving tertiary lymphoid structure (TLS) formation via the CXCL13 chemokine secretion, which warrants further validation in preclinical and clinical research. Altogether, our work represents a promising approach to modulate a broad spectrum of immune cells simultaneously and enhance their crosstalk, paving the way for durable clinical activity and supporting further development in the clinic. Citation Format: Seungmook Lim, A Yeong Park, Hyekyoung Kim, Seung Hyuck Jeon, Yong Joon Lee, Jamie Jae Eun Kim, Eui-Cheol Shin, Jinhwa Lee. FB849, a highly selective HPK1 inhibitor, reshapes the tumor immune microenvironment by modulating various immune cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2239.

Abstract 7122: Accelerating immuno-oncology research with flexible workflows using modular flex-fit CyTOF panels

Abstract Deep functional profiling of immuno-oncology markers and cytokines in whole blood (WB) reveals immune signatures that inform disease prognoses, immunotherapy selection, and outcomes in cancer patients. WB is best analyzed within 24 hours of collection to capture clinically relevant immune signatures; however, WB collection and cytometric analysis are often performed at different sites, which can lead to significant delays. WB stabilizers can overcome this challenge, yet not all antibody panels are compatible with these reagents. To enable flexible experimental workflows for deep profiling of immuno-oncology markers and cytokines in WB, we developed modular Flex-Fit CyTOF™ panels compatible with stabilizers. High-parameter flow cytometry mediated by CyTOF technology enables single-tube staining to identify 50-plus markers at the single-cell level. CyTOF technology provides exceptional resolution without spectral unmixing or compensation, while Flex-Fit CyTOF panels allow simple and quick panel design by combining a customizable selection of pre-validated subpanels. We built two high-parameter antibody panels for analysis of fresh and stabilized WB. The first panel has 21 markers and identifies 12 immuno-oncology markers in 10 major cell subsets. The second panel has 31 markers and identifies 10 cytokines in 32 cell subsets. Stimulated WB samples from two healthy donors were either freshly stained or stabilized with PROT1, RBC lysed and stained. Liquid antibodies in the panel were pooled together and frozen (-80 °C) as single-use aliquots for surface and intracellular staining to reduce technical variability from staining. Optimal panel design ensured that all markers in both panels could be used to accurately identify target cell populations in PROT1-stabilized WB. Following stabilization, nonspecific staining was not observed when compared with freshly stained samples. Cell populations maintained the anticipated co-expression of markers in PROT1-stabilized WB. Prominent cytokines such as IL-17A, TNF-α, IL-10, etc., could be detected in stabilized WB. Overall, we show that PROT1-compatible high-parameter antibody panels enable functional profiling of immune cells by identifying immuno-oncology markers and cytokines. Compatibility with WB stabilization reagents provides workflow flexibility for carrying out functional profiling in longitudinal and multi-center studies in clinical research and healthcare settings. Furthermore, freezing antibody cocktails is a unique feature of CyTOF flow cytometry, ensuring staining consistency. Together, flexible CyTOF workflows enable fast and convenient panel design for high-parameter cytometric analysis of WB and can facilitate biomarker discovery, immunotherapy selection and tracking disease prognoses in cancer. Citation Format: Shakir Hasan, Ling Wang, Stephen Li, Christina Loh. Accelerating immuno-oncology research with flexible workflows using modular flex-fit CyTOF panels [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 7122.

Abstract 968: Predictors of advance care planning documentation in female patients with breast cancer: A multilevel model analysis

Abstract Background: Advance care planning (ACP) is a process that supports adults at any age or stage of health in understanding and sharing their personal values, life goals, and preferences regarding future medical care. Likewise, ACP is associated with multiple benefits, such as lower rates of hospitalizations and reduced futile, aggressive cancer treatment at the end of life. However, ACP rates remain low in the U.S., especially for patients with advanced cancer. Despite being more likely to be diagnosed at advanced stages and hospitalized due to advanced cancer with poor prognosis, Black and Hispanic/Latino populations continue to have very low rates of ACP. Research has shown that both individual-level and systems-level factors contribute to these racial disparities in ACP. Considering these disparities among vulnerable populations, interventions that increase ACP among minority patients with cancer are needed. Objective: To analyze using multilevel model analysis the predictors of ACP documentation in female patients with breast cancer over 5 years in the UChicago Health System. Methods: Using the Clinical Data Research Warehouse, this study included women diagnosed with breast cancer (N=7,814) from 2016 to 2021. Descriptive statistics were performed to characterize ACP, and potential differences in ACP rates among control variables were assessed using odds ratio (OR) estimations. Analyses were conducted using random effects (mixed effects) multilevel modeling. To account for individual differences in ACP documentation completeness over time, both intercept and slope were included as random effects. In the multilevel model, level 1 modeled individual ACP documentation and level 2 tested the group effects in ACP documentation. The effect of time was tested in level 1, and the variances in the intercept and slopes were represented in level 2. Results: 8.74% of women with breast cancer had at least one type of ACP documented in their medical records; 4.25% had a power of attorney and 5.75% had an advanced directive. Age and the time elapsed between diagnosis and ACP completion are related to an increased likelihood of ACP completion over time. Being divorced increased the likelihood of ACP completion at baseline. Outpatient services decreased the likelihood of ACP completion over time. Conclusion: Understanding the factors that are related to ACP documentation will allow us to manage them and improve their completion. These results will help to inform the development of tools to increase the integration of ACP into care, especially those that are technology-based. Further work could include the design of a predictive model to prioritize patients who require ACP. Providing knowledge about ACP in nonclinical areas can lead to increased education about ACP and its benefits to families and communities. Citation Format: Andres Mauricio Garcia Sierra, Marcia Tan. Predictors of advance care planning documentation in female patients with breast cancer: A multilevel model analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 968.

Abstract 6853: A standardized drug selectivity profiling platform with a proteome coverage of more than 5,000 proteins

Abstract Drug hunters typically rely on a combination of biophysical/biochemical binding and efficacy assays to find and prioritize hit compounds in their drug discovery efforts. These activities are pivotal for success where the right assay combination can correlate productive binding (target engagement) with a biological effect. The earlier such correlations can be established, the better, as that speeds up the prioritization process and builds confidence in the lead series that are progressed to lead optimization. Currently, at that stage, selectivity assays for specific protein classes, typically including safety panels of up to 200 proteins, are applied. However, a limited number of proteins will result in a biased selectivity assessment. Instead, an unbiased and proteome-wide selectivity profiling assay, employed early in the drug discovery process, contributes to the correct prioritization of lead compounds. Pelago Bioscience has established a standardized assay for selectivity profiling, based on the Cellular Thermal Shift Assay (CETSA) with mass spectrometry (MS) detection, which enables discrimination between selective and more promiscuous molecules at the proteome level. As an example, we have profiled over 100 different drugs and probes used in clinical oncology and tumor biology research. Investigated drug classes include antimetabolites, alkylating agents, DNA intercalating agents, epigenetic modifiers, kinase inhibitors, and microtubule inhibitors. In the work presented here, we will show how compounds with similar structures and mode of action also display similar CETSA protein shift profiles with regards to intended targets and off-targets. Such reference data allows comparison of novel chemical hits to compounds with an established mode of action. High throughput and data quality, with an assessment of more than 5, 000 proteins, enables large compound batches to be assayed also during early phases of drug discovery. This speeds up the process and increases the confidence in lead series and future lead candidates. Citation Format: Tomas Friman, Tuomas Tolvanen, Tove Boström, Ying Sun, Alexey Chernobrovkin, Yasmin Andersson, Christina Velasco, Daniel Martinez Molina. A standardized drug selectivity profiling platform with a proteome coverage of more than 5, 000 proteins [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 6853.

Validation of the Russian-language version of the Self-Awareness Deficit Interview (SADI)

Thorough and early assessment of self-awareness deficits after brain injury is an important problem in neurorehabilitation that requires the development of both qualitative and quantitative methods to assess different levels of self-awareness to increase the efficacy of rehabilitation. Although there is no consensus on the determination and measurement of self-awareness impairment, several quantitative assessment methods have been developed in international practice. The Self-Awareness of Deficits Interview (SADI) technique is one of the most used structured interviews to assess self-awareness impairment in neurological patients. Objective: to conduct validation study and to develop the official Russian-language version of SADI. Material and methods. The study comprised two stages: in the first stage (n=17), a direct and reverse translation of the methodology was performed, followed by a pilot test; in the second stage (n=31), the reliability of the inter-rater and test-retest reliability, and the internal consistency of the methodology were evaluated. Three neuropsychological experts and two students took part in the evaluation of the results. Interviews were conducted with patients who were hospitalized to the Research Center of Neurology and N.I. Pirogov National Medical and Surgical Center of Ministry of Health of Russia. Inclusion criteria: verified neurological diagnosis, no pronounced speech disorders, Russian language fluency. Results. The study resulted in the cross-cultural SADI adaptation, leading to the development of the SADI-RU, the Russian-language version, including a scoring guide and a list of questions for patient's relatives. Pilot tests showed the suitability of the SADI-RU for clinical practice. An analysis of the psychometric indicators of the tool showed a “good” level of inter-rater consistency (ICC=0.81), high test-retest reliability (r=0.92) and internal consistency (α=0.77). Conclusion. The results of the study have shown that the developed SADI-RU is a reliable tool for assessing the self-awareness deficits, which is suitable for clinical practice and scientific research in neurological patients.

A novel child-centred core palliative care outcome measure for use in clinical practice and research: findings from a multinational validation study

A novel child-centred core palliative care outcome measure for use in clinical practice and research: findings from a multinational validation study

Abstract 1276: UNLOCK, a preclinical platform of PDX models resistant to innovative therapies

Abstract Introduction: Over the past 20 years, advances in precision oncology and cancer genetics have identified numerous actionable oncogenic drivers, leading to new drug development and clinical application. However, tumor cells can adapt and develop resistance mechanisms (MoR), and the mechanisms of action (MoA) of these drugs are only partially understood, highlighting the need for research focused on both MoR and MoA. Following the success of the MATCH-R clinical trial (NCT02517892, 2015-2022), the UNLOCK program was launched in 2022 to better understand the MoA and MoR of innovative drugs (phase 1 to approval) through integrated clinical and translational research. As part of this initiative, we developed preclinical models, including PDX models from patients who developed resistance, to support the development of new therapeutic strategies. Methods: Fresh tumor biopsy specimens were prospectively collected from patients through the MATCH-R clinical trial (NCT02517892) or the UNLOCK program. PDX models were established in NOD Scid Gamma (NSG) mice, which were then developed and characterized. These models underwent immunohistochemistry, comprehensive molecular profiling (including whole exome sequencing [WES] and bulk RNA sequencing [RNA-seq]), and pharmacological validation. Results: As of November 2024, 197 PDX models have been successfully generated from 519 biopsies, with a global take rate of 38%. These models are developed across several cohorts, including castration-resistant prostate cancer (22 PDX: 18 AR pathway inhibitors, 1 post-PARPi, and 3 Lu-PSMA), lung cancer (40 PDX with EGFR inhibitors, including 28 post-osimertinib, and 22 PDX with ALK inhibitors, including 2 post-brigatinib, 9 post-lorlatinib, and 6 post-alectinib). Additionally, 34 PDX models have been developed for the FGFR cohorts with FGFR2/FGFR3 alterations across various cancers, including cholangiocarcinomas, bladder carcinomas, gynecological carcinomas, and pancreatic cancers. We also developed 32 PDX models with KRAS mutations (G12C, n=23; G12D, n=9) from various tumors, including lung, pancreatic, gynecological, and colon cancers. Recently, we launched a new UNLOCK cohort focused on antibody-drug conjugate therapy, developing 12 additional PDX models. These PDX models faithfully replicate the genetic, transcriptional, phenotypic, and pharmacologic features of the original biopsies, providing a unique preclinical platform for testing novel drugs and combination therapies. Adaptive treatments with new or combinatorial strategies are being explored to restore drug sensitivity. Conclusion: The development of 197 PDX models under the UNLOCK program represents a significant resource, enabling the evaluation of novel drugs, adaptive treatment strategies, and combinatorial approaches. This unique collection of PDX models paves the way for advancing precision oncology and overcoming therapeutic resistance. Citation Format: Ludovic Bigot, Nobre Nobre, Alice Da silva, Melissandre Meteau, Mathis Delavigne, Miguel Soares, Francesco Facchinetti, Loic Poiraudeau, Floriane Braye, Inmaculada Inmaculada Alonso Garcia, Natalie Ngoi, Alexandre Halimi, Emlie Natali, Damien Vasseur, Kristi Beshiri, Claudio Claudio Nicotra, Maud Ngo-Camus, Lambros Tselikas, Beatriz Beatriz Alonso de Castro, Julieta Rodriguez, Maria Fernanda Mosele, Maud Kamal, Gérôme Jules-Clement, Karim Fizazi, Christophe Massard, Benjamin BESSE, Luc Friboulet, Yohann Loriot. UNLOCK, a preclinical platform of PDX models resistant to innovative therapies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 1276.

Abstract 2089: Spatial profiling of exhausted T cells using high-plex imaging mass cytometry

Abstract The spatial organization and cellular composition of the tumor microenvironment (TME) has the potential to inform clinical and translational researchers about mechanisms of disease progression and therapeutic success. Of particular interest are immune cells, especially T cells, which can become exhausted due to chronic stimulation. This poses a significant challenge in cancer therapy as exhausted T cells have reduced effector functions and sustained expression of inhibitory receptors such as PD-1 and CTLA-4, resulting in failure to effectively eliminate tumor cells. Imaging Mass Cytometry™ (IMC™) technology is a high-plex imaging technique that enables deep characterization of the heterogeneity and complexity of the TME. The Hyperion™ XTi Imaging System utilizes IMC technology to provide signal intensities over a wide dynamic range and entails one-step detection of 40-plus markers without issues of tissue autofluorescence, making it ideally suited for spatial biology applications. Whole slide imaging modes and an automated slide loader function enable a streamlined, versatile scalable workflow for high-throughput analysis. We used IMC technology to characterize immune cell populations and the spatial distribution of T cell exhaustion markers across various cancer types. We applied a 40-plus-marker IMC panel by integrating the Human Immuno-Oncology IMC Panel with the Human T Cell Exhaustion IMC Panel to study the TME of multiple human tissues. IMC analysis revealed striking heterogeneity with distinct tumor and immune-rich niches in the TME. In colon adenocarcinoma, we detected functional effector T cells and multiple tertiary lymphoid structures (TLSs). In contrast, we observed fewer TLSs and more T cells expressing PD-1 and TIM-3 at the tumor periphery in the urothelial carcinoma tissue, suggesting that they are in advanced exhaustion stages. We also observed expression of PD-L1, IDO and VISTA in the tumor cells. t-SNE and PhenoGraph clustering analysis of Cell Mode data segregated and spatially resolved the T cells into effector and exhausted T cell subpopulations, which were mapped back to the segmented cell masks. Unsupervised pixel clustering and analyses of Tissue Mode data further delineated distinct tumor areas based on the presence of infiltrating immune cells, tumor replicative activity and spatial proximity to stromal components. This work characterizing T cell exhaustion markers in multiple cancers showcases the capabilities of IMC technology and establishes it as a reliable high-plex, high-throughput spatial biology imaging platform. IMC technology is ideally suited for developing future translational and clinical applications and has the potential to help guide personalized therapeutic strategies for cancer treatment. For Research Use Only. Not for use in diagnostic procedures. Citation Format: Thomas D. Pfister, Jyh Yun Chwee, Qanber Raza, Nikesh Parsotam, David Howell, Liang Lim, Christina Loh. Spatial profiling of exhausted T cells using high-plex imaging mass cytometry [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2089.

Abstract 1061: Post-doctoral fellow

Introduction: Prostate cancer research spans genetics, proteomics, metabolomics, cell signaling, and tumor microenvironment domains. While this data is valuable, integrating clinical and basic research findings presents challenges. The Prostate Cancer Cartography Initiative (PCCI) offers a unified data model for efficient research across clinical, co-clinical, and mechanistic studies. The data model divides cases into anatomic and biological groups, facilitating cross-domain knowledge translation and hypothesis generation through efficient data integration. Materials & Methods: Our database incorporates data from 972 patients across three complementary sources: TCGA (primary prostate cancer), SU2C (metastatic patients), and MDA trials (intermediate-risk prostate cancer). For reproducibility and data consistency, we use NF core pipelines to harmonize data and derive copy loss, Single Nucleotide Variants/Insertions/Deletions (SNV & Indel), and gene expression. After analyzing this information, we group patients based on clinical information such as Gleason scores or genomic information such as copy loss and SNV/Indel to evaluate how these conditions affect gene expression and pathways. Results: In our initial work, we focused on TCGA patients with Gleason scores, categorizing them into three groups (3+3, 3+4/4+3, and 8 or higher). We further subdivided each category based on genetic alterations: patients with no copy loss, patients with at least one copy loss, and patients with Single Nucleotide Variants or Insertions/Deletions (SNV & Indel). We analyzed key genes including TP53 across these subgroups. Our initial results showed that medium-risk patients (Gleason scores 3+4/4+3) had significantly lower TP53 gene expression when they had both copy loss and SNV & Indel. Patients with SNV & Indel alone also showed lower TP53 gene expression, though this finding was not statistically significant (p = 0.06). High-risk patients (Gleason scores 8 or higher) demonstrated similar patterns. When analyzing how copy loss or SNV & Indel affect genes near TP53, we found reduced expression in nearby genes—ALOX15B (logFC: -1.0153, p<0.001), TMEM220 (logFC: -0.719, p<0.001), and MYO1C (logFC: -0.348, p<0.001)—in patients with TP53 copy loss or SNV & Indel. This pattern was confirmed in both medium-risk and high-risk groups. In our pathway analysis, including AD-target and homologous recombination pathways, patients without TP53 copy loss or SNV & Indel showed higher Enrichment Scores. Discussion: The PCCI provides a platform to integrate these data and generate hypotheses. Our results show that genetic alterations—such as copy loss and SNV & Indel—affect not only the TP53 but also nearby genes ALOX15B, TMEM220, and MYO1C. Notably, ALOX15B and MYO1C are tumor suppressor genes, which raises the question of how TP53 alteration leads to network changes in tumor suppressor genes. These findings further demonstrate the necessity of PCCI in facilitating hypothesis generation. Citation Format: Kang-Lin Hsieh, Sankar Maity, Ganiraju Manya, Bradley Broom, Christopher Logothetis, Patrick Pilie. Post-doctoral fellow [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 1061.

Abstract 1293: PMed-TRIAL database: an efficient and intelligent data integration platform shaping the future of drug development

Abstract With the rapid advancements in artificial intelligence (AI) and big data technologies, the fields of precision medicine and drug development have entered a transformative data-driven era. Leveraging years of accumulation and expertise, LIDE launched the PMed-TRIAL Database in 2023. Through continuous iteration and expansion, PMed-TRIAL has evolved into a comprehensive data integration and query platform, encompassing PDX (Patient-Derived Xenograft), CDX (Cell Line-Derived Xenograft), Syngeneic models, and Conditional Reprogramming Cell Lines. The platform enables efficient data retrieval and intelligent integration, providing indispensable support for clinical and drug research in this new era. The database currently hosts nearly 1, 800 PDX models, making it one of the largest PDX repositories worldwide. These models integrate and standardize a wide range of key datasets, including clinical information, treatment history, growth curves, SOC (standard of care), and H&E (hematoxylin and eosin staining) results, among others, which greatly facilitates the filtering and selection of suitable models for drug research. Furthermore, the associated whole-exome sequencing (WES) and RNA sequencing datasets provide critical evidence for drug mechanisms research. In addition to standard PDX models, the database also includes induced drug-resistance models, providing an essential resource for studying drug resistance mechanisms and screening drugs to overcome resistance. In addition to PDX models, the PMed-TRIAL Database incorporates information on Patient/PDX-derived conditional reprograming cell lines, PDXO (PDX Derived Organoids), Syngeneic models, and CDX models. This expanded scope addresses the multi-faceted demands of drug development, accelerating research timelines and enhancing the efficiency of the drug discovery process. Most importantly, the PMed-TRIAL Database standardizes and efficiently integrates diverse model datasets. The accumulation of large-scale, high-quality data not only streamlines current research efforts but also lays the groundwork for advancing AI applications in drug development in the future. By bridging innovative technologies with comprehensive data resources, PMed-TRIAL empowers researchers to unlock new possibilities in precision medicine and therapeutic innovation. Citation Format: Xinlei Chen, Youbing Guo, Loc Van, Josh Caggiula, Danyi Wen. PMed-TRIAL database: an efficient and intelligent data integration platform shaping the future of drug development [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 1293.

Study on the status and countermeasures of disease self-management ability in chronic kidney disease patients in cold regions

Abstract Objective Effective Chronic Kidney Disease (CKD) management is particularly important in cold regions of China, where climate and lifestyle factors play significant roles. However, there is a lack of relevant studies in this area. Therefore, the purpose of this study was: (1) to assess the status of self-management capacity in individuals with CKD in cold regions of China and analyze the factors influencing it; (2) to identify strategies to improve CKD management in primary care settings in these regions; and (3) to understand patients' attitudes toward eHealth services. Methods This was a regional, cross-sectional observational study. A questionnaire measuring CKD patients' self-management abilities was derived from the Perceived Kidney Disease Self-Management Scale, the Kidney Disease Behavioral Inventory (KDBI), and the Health Literacy Questionnaire. Data were collected from hospitalized CKD patients in Heilongjiang Province and analyzed using One-Way Analysis of Variance (ANOVA), Hierarchical Regression Analysis, and K-prototype cluster analysis. Results A total of 957 participants were tested. Of these, 70.64% had less than a bachelor's degree, and 56.27% had been diagnosed with hypertensive or diabetic nephropathy. The KDBI scale showed a lower overall score compared to the PKDSMS. Factors such as CKD stage 4 (F = 2.367, P = 0.042), last year's medical expenses (F = 3.974, P = 0.004), and poor self-rated health (F = 33.352, P < 0.01) were found to influence scores on both scales. The health literacy questionnaire revealed significant differences (P < 0.01) in health knowledge, except by sex. Additionally, healthcare expenditures and poor self-rated health were negatively associated with self-management capacity. Conclusions This study provides valuable insights into the self-management challenges faced by CKD patients in cold regions of China. Despite some difficulties in improving self-management, patients showed positive attitudes toward enhancing CKD management services in primary care and developing digital management tools. These findings offer useful references and recommendations for future clinical practice and research in this field.

Abstract 631: Building bridges between communities and cancer researchers through the CaRE2 Health Equity Center Community Scientist Research Advocacy Program

Abstract Building healthy and trustworthy relationships between communities and researchers is essential for cancer research endeavors. Training community advocates in cancer research can increase capacity among community members to leverage networks, participate in research teams and/or boards, and increase knowledge and insights to I'm prove patient outcomes through increased participation in cancer research. The Florida-California Cancer Research Education and Engagement (CaRE2) Health Equity Center designed a Community Scientist Research Advocacy (CSRA) program to inform, educate, and empower community members to become cancer research advocates. Our program was specifically tailored for Black/African American (B/AA) and Hispanic/Latino/a (H/L) adults living in Florida or California. Primary program objectives were to increase human capacity for cancer research advocacy and increase multi-directional communication between cancer advocates with cancer survivors, community members, academic scientists, and policy makers. The CSRA program was delivered over a 10-week period, with a hybrid model compromised of 90% virtual sessions via Zoom to allow for joint participation across the two coasts, and one in-person experiential lab day at each of our three institutions from our partnership. Didactic online learning sessions covered topics including cancers that disproportionately affect medically underserved populations, participation in clinical trials, genomics, social determinants of health, tissue donation/biorepository, and ethics in research studies. Participants completed pre- and post-surveys to assess knowledge, self-efficacy, and program satisfaction and evaluation; and they also completed a mentored advocacy project upon completion of the program. We provided simultaneous Spanish interpretation during all sessions, and materials were translated and provided in both English and Spanish. The 2024 CSRA cohort (N=18) included 12 females and 6 males; 11 were B/AA and 7 were H/L, 11 were from Florida and 7 were from California. Participants were required to attend at least 80% of sessions including one mandatory in-person lab visit activity; leading to a 100% program completion. When comparison pre- and post-attendance surveys, participants showed increases in knowledge (p-value = 0.007) and self-efficacy (p-value = 0.3). Program satisfaction and evaluation were rated as high. In summary, our program demonstrates the effectiveness of training community members to become cancer research advocates to help reduce the burden of inequities in cancer research and care. CSRA programs increase communication between scientists and communities to bring education and awareness about clinical studies and cancer research. Thus, promoting diverse participation in cancer studies, and eventually reducing cancer health disparities. Citation Format: Carolina Aristizabal, Fern Webb, Sandra Suther, John Luque, Eduardo Ibarra, Nazleen Del Rio, Ileana Guzman, Brooke Hensel, Janet Rodriguez, Rosa Barahona, Mariana Stern, Lourdes A. Baezconde-Garbanati. Building bridges between communities and cancer researchers through the CaRE2 Health Equity Center Community Scientist Research Advocacy Program [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 631.

The contribution of prolactin in the occurrence of premature cardiovascular disease predominantly through modulating the inflammatory cascade.

Cardiovascular disease, mainly coronary atherothrombosis, is an essential contributor to all-cause mortality, accounting for approximately 30% of all global deaths. Imbalances in hormone profiles may play a role in the evolution of atherothrombosis. In the last decade, our clinical research focused on the hormone prolactin (PRL) and its contribution to premature cardiovascular disease. In this narrative review, we aimed to give current insights into how PRL could modulate the inflammatory cascade within the microenvironment of the atherosclerotic plaque, which could lead to increased cardiovascular morbidity and mortality.