tbuckley/cabot-search huggingface dataset:
Abstract 1356: The VISTA blocking antibody HMBD-002 promotes type-I interferon signaling and drives anti-tumor responses through macrophage reprograming and cytotoxic CD8+ T cell activation
Authors: Bhushan Dharmadhikari, Olga Zharkova, Dipti Thakkar, Roberto Tirado-Magallanes, Konrad Paszkiewicz, Piers J. Ingram, Jerome D. Boyd-Kirkup
Journal: Cancer Research (2024)

Abstract VISTA, a predominantly myeloid immune checkpoint, promotes an immunosuppressive tumor microenvironment and has been associated with resistance to approved checkpoint therapies. While blockade of VISTA with antibodies has shown anti-tumor efficacy in preclinical models, the biological mechanisms that underlie this effect remain poorly understood. To investigate the mechanistic basis of anti-tumor responses, we performed single-cell RNA sequencing of tumor infiltrating leukocytes from the cell-derived murine colon carcinoma xenograft model, CT26, which is known to be sensitive to VISTA blockade. We used HMBD-002, a uniquely blocking but non-depleting clinical-stage IgG4 anti-VISTA antibody, to identify the key immune cells and pathways impacted by VISTA blockade in the absence of Fc-mediated cell depletion. The translatability of these findings was validated in a human PBMC mixed leukocyte reaction assay. Subsequently, targeted depletion or inhibition of the identified immune populations and pathways was performed to confirm their contribution to the anti-tumor efficacy of HMBD-002.The blockade of VISTA by HMBD-002 significantly increased CD8+ T cells in the CT26 tumors, promoting an activated cytotoxic Tc1 program without inducing exhaustion. Concurrently, a substantial increase in proinflammatory M1 tumor-associated macrophages (TAMs) was noted within treated tumors, while other immune cell populations remained unaffected. Among the signaling pathways, the type-I interferon (IFN) response exhibited a significant upregulation, particularly in TAMs, indicating a type-I IFN-driven M1 reprogramming by HMBD-002. Validation experiments further demonstrated that the depletion of TAMs or CD8+ T cells, but not CD4+ T cells, abrogated the efficacy of HMBD-002. Moreover, blocking the type-I IFN signaling effectively impeded HMBD-002-induced TAM reprogramming and subsequent anti-tumor efficacy, thus confirming the pivotal roles of CD8+ T cells, TAMs, and type-I IFN signaling in driving the anti-tumor response to VISTA blockade. In conclusion, VISTA blockade with HMBD-002 promotes an anti-tumor response by type-I IFN mediated reprogramming of TAMs and activation of cytotoxic CD8+ T cells. Citation Format: Bhushan Dharmadhikari, Olga Zharkova, Dipti Thakkar, Roberto Tirado-Magallanes, Konrad Paszkiewicz, Piers J. Ingram, Jerome D. Boyd-Kirkup. The VISTA blocking antibody HMBD-002 promotes type-I interferon signaling and drives anti-tumor responses through macrophage reprograming and cytotoxic CD8+ T cell activation [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 1356.
Abstract 144: Sex bias in neuroblastoma: Worse outcomes for female patients are associated with dysregulation of <i>DLK1</i> and <i>H19</i>
Authors: Mariya Raleigh, Vishwa Patel, Lorraine R. Benhamou, Xin Shen, Dennis A. Sheeter, Erika C. Espinosa, Niharika Reddy Badi, Chase Calvert, Garrett Bourne, John T. Powers
Journal: Cancer Research (2024)

Abstract Neuroblastoma (NB) is a devastating neural crest-derived tumor primarily affects children under five. Forty percent of NB patients are classified as high-risk (HR), and less than half of them survive. HR disease is split into two equally sized groups: one exhibiting genetic amplification of the MYCN proto-oncogene (MA), and another where MYCN is non-amplified (MNon). Overall survival (OS) studies are often either poorly annotated or focused on outcomes across the entire patient group, which may mask differential outcomes or biases among NB subgroups. Here we report our assessment of OS among several genetic, histopathological, and sex-based subgroups in three different well annotated NB patient datasets. Our analysis reveals a previously unseen sex-bias in HR MNon patients, where female patients have significantly worse OS than males. This disparity carries into stage 4s NB, defined by high survival in infants despite the presence of broadly disseminated disease. In stage 4s patients across two studies, we observe no deaths among males (n=66) and 6 among females (n=48), again marking significantly worse OS in females. Expression analysis comparing male and female HR MNon patients identifies DLK1 and H19, two imprinted genes implicated in multiple malignancies, as frequently overexpressed in females. A similar pattern is seen in RNA seq analysis of human MA (n=4) and MNon (n=4) cell lines. In addition, both DLK1 and H19 are associated with worse prognosis in female but not male patients. We also report that depletion of either gene results in reduced growth in vitro. Moreover, the NB-related ATRX tumor suppressor has been shown to inhibit H19 via insertion of histone variant H3.3. We observe an inverse correlation between H3.3B and H19 expression in female HR MNon patients. Further, H19 levels increase upon ATRX depletion in human NB cells, suggesting that ATRX indeed regulates H19 in NB. These findings provide the first evidence of female-biased outcomes in NB and suggest functional involvement of DLK1, H19 and ATRX. Citation Format: Mariya Raleigh, Vishwa Patel, Lorraine R. Benhamou, Xin Shen, Dennis A. Sheeter, Erika C. Espinosa, Niharika Reddy Badi, Chase Calvert, Garrett Bourne, John T. Powers. Sex bias in neuroblastoma: Worse outcomes for female patients are associated with dysregulation of DLK1 and H19 [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 144.
Abstract 7659: AI-driven hypothesis-free analysis for biomarker discovery: Introducing the Biomarkers Navigator Framework
Authors: Ioannis Kagiampakis, Mishka Gidwani, Iaroslav Korkodinov, Georgiy Ponomarev, Etai Jacob
Journal: Cancer Research (2024)

Abstract The pivotal role of biomarkers in personalizing patient treatment and guiding drug development is well-recognized, with the ultimate goal of enhancing therapeutic efficacy and patient quality of life by minimizing adverse events. Their development, however, is challenged by strict regulations and high costs, leading to sparse and varied data collected over extended periods and through diverse technologies. These variations complicate the harmonization and analysis of the data. Traditional methods struggle to navigate these complexities, further obscuring biomarker identification. For instance, PDL-1, approved as a biomarker by the FDA, has its effectiveness debated in several studies. To address these issues, we introduce Biomarkers Navigator, a flexible and automated analysis framework engineered explicitly for the robust identification of biomarkers. This framework is designed to aggregate, standardize, and store expansive biomarker information, ensuring efficient and traceable knowledge retrieval. By pre-calculating each potential biomarker, Biomarkers Navigator enables immediate and comprehensive meta-analyses, facilitating rapid decision-making tailored to the level of risk acceptance. Large Language Models (LLMs) further enhance the framework's capability to uncover signatures of response and resistance. LLM integration has accelerated the discovery of new potential biomarkers for hematological malignancies by combining prior knowledge and previously obscured associations. Our approach demonstrates the feasibility of large-scale hypothesis-free analysis and substantiates the utility of AI in unveiling hidden biological connections within clinical data. Our findings underscore the potential of AI-augmented frameworks in revolutionizing biomarker discovery and advancing personalized medicine. Citation Format: Ioannis Kagiampakis, Mishka Gidwani, Iaroslav Korkodinov, Georgiy Ponomarev, Etai Jacob. AI-driven hypothesis-free analysis for biomarker discovery: Introducing the Biomarkers Navigator Framework [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 7659.
Abstract 5517: Chronic stress causes metastasis via neutrophil-mediated changes to the microenvironment
Authors: Xue-Yan He, Yuan Gao, David Ng, Evdokia Michalopoulou, Shanu George, Jose M. Adrover, Lijuan Sun, Jean Albrengues, Juliane Daßler-Plenker, Xiao Han, Ledong Wan, Xiaoli S. Wu, Longling S. Shui, Yu-Han Huang, Bodu Liu, Chang Su, David L. Spector, Christopher R. Vakoc, Linda VanAelst, Mikala Egeblad
Journal: Cancer Research (2024)

Abstract Chronic stress is associated with increased risk of metastasis and poor survival in cancer patients, yet the reasons are unclear. We show that chronic stress increased lung metastasis from disseminated cancer cells 2- to 4-fold in mice. Chronic stress significantly altered the lung microenvironment, with fibronectin accumulation, reduced T cell infiltration, and increased neutrophil infiltration. Depleting neutrophils abolished stress-induced metastasis, indicating their critical role. Chronic stress shifted neutrophils’ normal circadian rhythm, and, via glucocorticoid release, caused increased neutrophil extracellular trap (NET) formation. Importantly, in mice with neutrophil-specific glucocorticoid receptor deletion, chronic stress failed to increase NETs and metastasis. Furthermore, digesting NETs with deoxyribonuclease (DNase) I prevented chronic stress-induced metastasis. Together, our data show that glucocorticoids released during chronic stress cause NET formation and establish a metastasis-promoting microenvironment. Therefore, NETs could be targets for preventing metastatic recurrence in cancer patients, many of whom will experience chronic stress due to their disease. Citation Format: Xue-Yan He, Yuan Gao, David Ng, Evdokia Michalopoulou, Shanu George, Jose M. Adrover, Lijuan Sun, Jean Albrengues, Juliane Daßler-Plenker, Xiao Han, Ledong Wan, Xiaoli S. Wu, Longling S. Shui, Yu-Han Huang, Bodu Liu, Chang Su, David L. Spector, Christopher R. Vakoc, Linda VanAelst, Mikala Egeblad. Chronic stress causes metastasis via neutrophil-mediated changes to the microenvironment [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 5517.
Abstract 4318: CD24 enhances cisplatin resistance in ovarian cancer by suppressing autophagy
Authors: Yuh-Ling Chen, Tse-Ming Hong, Yu-Yi Wen
Journal: Cancer Research (2024)

Abstract Ovarian cancer is one of the most common gynecological cancers with the highest mortality rate. Most patients are diagnosed with advanced disease and will relapse due to chemoresistance. CD24, a highly glycosylated GPI-anchored membrane protein. Recent studies have shown that CD24 expression is significantly up-regulated in ovarian cancer and is associated with chemotherapy resistance, and CD24 also plays an inhibitory role in tumor immunity by binding to Siglec-10 on macrophages. However, the molecular mechanisms of how CD24 affects chemotherapy resistance in ovarian cancer remain unclear. In this study, we used shRNAs to knockdown CD24 and explore the impact and mechanism of CD24 on the chemotherapy resistance of ovarian cancer cells. The results showed that knockdown of CD24 in ovarian cancer cells SKOV3 and TOV21G significantly reduced cell proliferation and arrested the cell cycle in S phase. Knockdown of CD24 also significantly increased the sensitivity of ovarian cancer cells to cisplatin but had no effect on paclitaxol treatment. Further experiments showed that knockdown of CD24 increased cisplatin sensitivity by promoting autophagy-induced cell death. In addition, Gene Set Enrichment Analysis (GSEA) was used to analyze the correlation between the expression of CD24 and its biological functions in the TCGA ovarian cancer dataset. The results showed that CD24 is mostly correlated to cell proliferation and autophagy-related pathways in ovarian cancers. Further mouse xenograft tumor transplantation experiments also confirmed that knockdown of CD24 reduced tumor size and increased sensitivity to cisplatin treatment by increasing cell autophagy. Taken together, these results indicate that CD24 regulates cell growth and chemoresistance in ovarian cancer cells and that inhibition of CD24 may be helpful in the treatment of ovarian cancer. Citation Format: Yuh-Ling Chen, Tse-Ming Hong, Yu-Yi Wen. CD24 enhances cisplatin resistance in ovarian cancer by suppressing autophagy [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 4318.
Abstract 6177: Machine learning enables prediction of ADC targets from whole slide H&amp;E images
Authors: Zachary Ryan McCaw, Anna Shcherbina, Yajas Shah, Philip Tagari, Daphne Koller, Christopher Probert
Journal: Cancer Research (2024)

Abstract Background: The efficacy of antibody-drug conjugates (ADCs) depends on the expression and specificity of the target antigen by tumor cells. Although H&amp;E-stained slides are routinely collected during cancer care, specialized IHC staining is typically required to ascertain antigen expression. Such stains are not always available or readily deployed. The need to perform separate IHC tests for each candidate ADC may burden clinical labs and can hinder access to care in resource-limited settings. Here we develop an ensemble of machine learning models to accurately predict the expression of 166 distinct ADC targets directly from H&amp;E images. Methods: For each ADC-targeted gene, patients with copy-number amplifications (CNAs) were identified from somatic whole exome sequencing. Genes differentially expressed in patients with CNAs were identified from bulk transcriptomics. For each gene, an expression signature was developed based on the expression levels of differentially upregulated genes. Next, whole-slide, H&amp;E-stained histopathology images were embedded into a lower-dimensional representation via a transformer model trained with self-supervised learning. Neural networks were developed to predict a patient’s probability of having a CNA in an ADC-targeted gene, as indicated by an expression signature exceeding the p90. All evaluation metrics were ascertained by 5-fold cross-validation, with training and evaluation on independent patients. Results: For each of the 166 ADC-targeted genes, a median of 154 patients were found to harbor a CNA, and the expression signature included a median of 180 genes. In all cases, patients with CNAs had significantly higher expression signatures than those without. For predicting likely CNA status directly from H&amp;E histopathology images, the mean AUROC was 0.888 (95% CI, 0.876-0.900) and the mean AUPRC was 0.571 (95% CI, 0.531-0.611). Among the 166 ADC-targeted genes, the AUROC exceeded 0.95 for 31.3%, 0.8 for 80.7%, and 0.725 for 100%. The best-predicted ADC target was SLC7A5 (AUROC: 0.995 [95% CI, 0.994-0.998]; AUPRC: 0.967 [95% CI, 0.963-0.976]). Conclusion: We have developed models that accurately predict the likely expression of ADC targets based solely on H&amp;E images. The ability to accurately discern the presence of ADC antigens from H&amp;E images has numerous potential applications, including cohort refinement, computer-aided diagnosis, and personalized treatment planning. Citation Format: Zachary Ryan McCaw, Anna Shcherbina, Yajas Shah, insitro Research Team, Philip Tagari, Daphne Koller, Christopher Probert. Machine learning enables prediction of ADC targets from whole slide H&amp;E images [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 6177.
Abstract 5038: Validation of a comprehensive next-generation sequencing liquid biopsy assay for clinical diagnostics and clinical trial applications
Authors: Xin-Xing Tan, Tricia Peters, Meredith Berry, Kimberly Barber, Kristyn Jeter, Brigitte Lovell, Paula Elizondo, Yanglong Mou, Brad Thomas, Heng Xie, Jiannan Guo
Journal: Cancer Research (2024)

Abstract Liquid biopsy next generation sequencing (NGS) provides a powerful non-invasive approach to detect solid tumor derived somatic variants in a massively parallel manner. Liquid biopsy NGS has rapidly become an invaluable choice of testing technologies for clinical utility where invasive tissue biopsy is inaccessible and/or inadequate for molecular characterization. We present here a targeted NGS gene panel assay designed and validated specifically for liquid biopsy characterization. The assay was designed to test cell free DNA and cell free RNA from blood plasma for detection of single nucleotide variants (SNV), insertion/deletion (Indel), copy number variants (CNV), and gene fusions present in 52 most commonly mutated genes in cancers. The validation was performed to assess assay accuracy, specificity, sensitivity, repeatability, and reproducibility, with including pre-characterized reference controls, retrospective plasma samples from cancer patients, and prospectively-collected clinic blood specimen. Triplicates were included and testing was performed at different times and by different operators to assess the assay precision. Over 100 clinic blood specimens were collected in Streck cfDNA tubes from multiple trial centers, including treatment naïve phase III-IV patients with solid tumor (lung cancer, breast cancer, brain cancer, prostate cancer, kidney cancer, melanoma, etc) as well as heathy donors, processed within 7 days for plasma separation and total nucleotide acid (TNA) extraction, and assessed by the NGS assay for mutation detection. The identified mutations and wild-types were verified with orthogonal ddPCR. Assay sensitivity as low as 0.1% for SNV and Indel, 1.3 fold change for CNV, and 10 copies for gene fusion were observed, with near-perfect assay specificity (&amp;gt;99.99%) at these sensitivity levels. In conclusion, a targeted NGS liquid biopsy assay was analytically validated under medical oversight, with a demonstrated rigor of the test by its high sensitivity/specificity and robust reproducibility. The validated assay has been utilized for clinical diagnostics and to support research and development efforts in clinical trials. Citation Format: Xin-Xing Tan, Tricia Peters, Meredith Berry, Kimberly Barber, Kristyn Jeter, Brigitte Lovell, Paula Elizondo, Yanglong Mou, Brad Thomas, Heng Xie, Jiannan Guo. Validation of a comprehensive next-generation sequencing liquid biopsy assay for clinical diagnostics and clinical trial applications [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 5038.
Abstract 4435: Taurine metabolism as a marker for pancreatic cancer
Authors: Hoonsik Nam, Woohyung Lee, Ha T. Nguyen, Linh X. Mai, Song Cheol Kim, Sunghyouk Park
Journal: Cancer Research (2024)

Abstract Pancreatic ductal adenocarcinoma (PDAC), known for its aggressive nature and poor prognosis, presents a significantly altered metabolic landscape compared to normal pancreatic tissue, a feature that has been the focus of recent research but remains underexplored in actual pancreatic tissues. In this study, we undertook an untargeted metabolomics analysis to compare the metabolic profiles of PDAC with matched normal tissues, revealing a notable elevation in taurine levels in PDAC. This increase was further validated through immunohistochemistry in separate PDAC and normal tissue samples. To delve deeper, we conducted a comprehensive bioinformatics analysis, integrating transcriptomic and proteomic data, which identified the taurine metabolism pathway as significantly altered, with ADO emerging as a pivotal gene in this process. Further investigations, including gene modulation and xenograft models, demonstrated that ADO knockdown curtails cancer cell proliferation and tumor growth, potentially impacting the Raf-MEK-ERK signaling pathway. Clinically, the ADO-Taurine axis was found to have substantial prognostic significance, correlating with recurrence rates and survival in PDAC patients. These insights collectively suggest that the ADO-Taurine axis, through its modulation of taurine metabolism, presents as a promising biomarker for PDAC prognosis and a potential avenue for therapeutic development. Citation Format: Hoonsik Nam, Woohyung Lee, Ha T. Nguyen, Linh X. Mai, Song Cheol Kim, Sunghyouk Park. Taurine metabolism as a marker for pancreatic cancer [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 4435.
Abstract 4950: Applying fragmentomics profiles of plasma cell-free DNA for breast cancer detection
Authors: Yaxin Liu, Shuang Gan, Hang Dong, Haoran Tang, Nan Wang, Xinyu Gui, Anjie Zhu, Ruyan Zhang, Pan Du, Shidong Jia
Journal: Cancer Research (2024)

Abstract The liquid biopsy approach focusing on DNA molecules supports the non-invasive diagnosis of breast cancer. Low-pass whole genome sequencing(lpWGS) for breast cancer detection has been validated for accuracy and cost-effectiveness, especially with copy number variant (CNV) analysis. However, detecting breast cancer with cell-free DNA (cfDNA) CNV was limited by tumor fraction. Utilizing cell-free DNA fragmentation characteristics for cancer detection has shown potential in plasma with high precision and applicability with low tumor fraction. In this study, 217 patients with breast cancer and 10 healthy individuals were enrolled. The cfDNA was extracted and performed using PredicineSCORE, a low-coverage whole genome sequencing assay to identify tumor-specific features. The cfDNA fragmentomics profiles including the coverage at specific regions, length and end-motif of fragment were implemented. We also investigated the copy number variation and the inferred tumor fraction which was adjusted by the Expectation-Maximum (EM) algorithm. Combining, an ensembled machine learning model was constructed for the classification of breast cancer and normal control. We observed a high correlation between tumor fraction and features. The absolute correlation coefficient scores between tumor fraction with the LYL1, MAF, FOXA1, and GRHL2 bonding sites' relative depth were over 0.82, 0.71,0.89,0.87. The insert size ratio of short reads and the CCCA end motif were over 0.77 and 0.72, respectively. We then diluted the tumor samples of tumor fraction at 0.1% to 50% by manually mixing reads from tumor samples into normal samples. By applying the XGBoost algorithm, the performance (F1 score &amp;gt; 0.95) showed a promising ability to distinguish tumors from normal samples. The limit of detection (LOD) was less than 1% which is more sensitive than previously proposed models. Those samples detected mutations with high through panel which can confirm the accuracy of the assay. Our results discovered that profiling the cell-free DNA fragment could facilitate the way of non-invasively detection of breast cancer with high precisions. Citation Format: Yaxin Liu, Shuang Gan, Hang Dong, Haoran Tang, Nan Wang, Xinyu Gui, Anjie Zhu, Ruyan Zhang, Pan Du, Shidong Jia. Applying fragmentomics profiles of plasma cell-free DNA for breast cancer detection [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 4950.