tbuckley/cabot-search huggingface dataset:
Abstract 2304: Detection of early-disseminated cancer cells with deep learning-enabled holographic imaging
Authors: Nicholas Heller, Kevin Mallery, Nathaniel Bristow, Yash Travadi, Eng Hock Lee, Jiarong Hong
Journal: Cancer Research (2024)

Abstract Recent research increasingly validates the early dissemination of tumor cells in peripheral blood during the nascent stages of cancer, often preceding clinical identification of the primary tumor. This emerging evidence emphasizes the potential of Circulating Tumor Cells (CTCs) as early indicators for cancer. Despite their significance, CTCs are exceptionally rare compared to normal blood cells, which presents a considerable challenge in detection, particularly during early stages of cancer. Traditional detection methods, such as those based on nucleated cell enrichment, antibody labeling and fluorescence imaging, encounter notable limitations when applied in the context of early detection. These limitations arise from the inherent heterogeneity of CTCs, and the multistep process involved in labeling and manual enumeration, compromising cell viability and resulting in cell loss. This loss becomes particularly problematic in the context of early cancer detection scenarios where the tumor burden is extremely low, and any cell loss can significantly impact assay sensitivity. To overcome these challenges, we propose an innovative CTC detection approach employing a deep learning framework combined with holographic imaging. This technique utilizes coherent light to generate holograms from cell samples, capturing detailed 3D morphological and optical properties of individual cells. We developed a custom convolutional neural network designed to facilitate high-throughput cell sorting in real-time. Trained on healthy blood samples and diverse cancer cell lines, the dataset consists of more than 50 million cellular holograms enhanced by proprietary Gaussian annotation and image augmentation strategies. Moreover, by combining the morphological signatures from holography with antigen signatures (e.g. HER2/ER/PR) in real-time, our model demonstrates the ability to detect less than 1 false positive per 1 million nucleated cells, highlighting its potential as a robust tool for targeted early-stage breast cancer detection. Our technology represents highly sensitive alternative to traditional screening methods, with the promise of enhancing patient outcomes. Citation Format: Nicholas Heller, Kevin Mallery, Nathaniel Bristow, Yash Travadi, Eng Hock Lee, Jiarong Hong. Detection of early-disseminated cancer cells with deep learning-enabled holographic imaging [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 2304.
Abstract 497: Plant viruses against cancer
Authors: Nicole F. Steinmetz, Young Hun Chung, Miguel Moreno-Gonzalez, Zhongchao Zhao
Journal: Cancer Research (2024)

Abstract Immunotherapy has significantly transformed the landscape of cancer treatment; however, concerns about safety, efficacy, and long-term outcomes across various tumor types persist. We have developed an intratumoral immunotherapy strategy with an engineered plant virus nanotechnology and demonstrated efficacy in tumor mouse models and canine cancer patients. This method is designed to elicit a systemic (abscopal effect), safe, and enduring anti-tumor immune response that is not limited by tumor type. The power of immunotherapy lies in synergistic combination treatments and toward this goal, we are engineering the next-generation plant virus nanotechnologies. We demonstrate synergistic combination with chemotherapy and immunization strategies the hone in on tumor-associated antigens and key players of inflammation. The combinatorial immunotherapy strategies prevent recurrence post-surgery in mice and canine patients. We will discuss the engineering design principles leading toward synergetic combination immunotherapies to treat and prevent cancer; efficacy studies and underlying mechanism is elucidated through immunomics studies. Selected references: Steinmetz N.F. et al (2023) Viral nanoparticle vaccines against S100A9 reduce lung tumor seeding and metastasis. Proc. Natl. Acad. Sci. U.S.A. 120 (43) e2221859120. Wang C. and Steinmetz N.F. (2020) A Combination of Cowpea mosaic virus and Immune Checkpoint Therapy Synergistically Improves Therapeutic Efficacy in Three Tumor Models. Advanced Functional Materials, 2002299. Citation Format: Nicole F. Steinmetz, Young Hun Chung, Miguel Moreno-Gonzalez, Zhongchao Zhao. Plant viruses against 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 497.
Abstract 784: Proteome-wide mendelian randomization identifies causal association between plasma proteins and lung cancer
Authors: Guojin Si, Wenxuan Li, Yacong Zhang, Zhangyan Lyu, Fengju Song, Kexin Chen
Journal: Cancer Research (2024)

Abstract Background: Lung cancer is one of the world's main health issues, and the exploration of novel protein markers can help to understand the mechanisms of lung cancer development and the discovery of therapeutic targets. Based on this, we used proteome-wide Mendelian Randomization to determine causal associations between plasma protein levels and the risk of developing lung cancer and subtypes. Methods: We performed a two-sample Mendelian Randomization analysis using genome-wide association data for 4907 proteins from the deCODE genetics study and five lung cancer and its subtypes from the FinnGen database. Causal effects were estimated using the Wald-ratio method or the inverse variance weighted (IVW) method, with additional analyses using the other four common methods when the number of SNPs was more than one. The Steiger filter method was used to test the correct direction of the causal effect. Multiple corrections were utilized by the Benjamini-Hochberg method. Results: After filtering, we finally analyzed 4645 proteins for the causal association with lung cancer, and the F-statistic of the instrumental variable for each protein was more than 10. After multiple tests, the levels of four genetically predictive proteins were found to be associated with the risk of lung cancer, and one protein was associated with the risk of small-cell lung cancer. In detail, elevated levels of three genetically predicted proteins were significantly associated with increased risk of lung cancer, namely, SYSC (OR:4.75, 95%CI: 2.47-9.16, FDR=0.007), TM11D (OR: 1.34, 95%CI: 1.17-1.53, FDR=0.02), and PDC6I (OR: 2.35, 95%CI: 1.58-3.49, FDR=0.03). Elevated levels of FASLG (OR: 0.87, 95%CI: 0.82-0.92, FDR=0.007) were associated with a reduced risk of lung cancer. In addition, genetically predicted elevated levels of GRP (OR: 0.05, 95%CI: 0.01-0.17, FDR=0.02) were associated with an increased risk of small-cell lung cancer. The Steiger filter test showed that all directions were from proteins to lung cancer. Conclusion: In this study, we found that five proteins may have effects on the risk of lung cancer, in which genetically predicted SYSC, TM11D, and PDC6I were significantly associated with an increased risk of lung cancer, whereas FASLG and GRP were associated with a decreased risk of lung cancer and small-cell lung cancer, respectively. The above may help to explore the pathogenesis of lung cancer, but further comprehensive studies are still needed. Citation Format: Guojin Si, Wenxuan Li, Yacong Zhang, Zhangyan Lyu, Fengju Song, Kexin Chen. Proteome-wide mendelian randomization identifies causal association between plasma proteins and lung 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 784.
Abstract 7351: Delineating the prostate cancer tumor microenvironment through scRNA-seq profiling at different timepoints
Authors: Itzel Valencia, Hubert Pakula, Mohamed Omar, Massimo Loda, Luigi Marchionni
Journal: Cancer Research (2024)

Abstract Distant metastasis remains the leading cause of death in patients with prostate cancer (PCa), however, the underlying mechanisms of this process remain unclear. Using samples from genetically-engineered mouse models (GEMMs) of PCa, we have identified eight different stromal cell states linked to epithelial mutations that may impact PCa progression to metastatic stages. To further investigate the unique intercellular interactions in the tumor microenvironment (TME) involved in mediating disease progression, we use single cell RNA sequencing (scRNA-seq) to profile primary PCa samples from different GEMMs including TRAMP, Hi-MYC, and FVBN, at different timepoints. Analysis of the scRNA-seq data revealed a significant enrichment of three clusters, designated as stromal c6 (s6), epithelial c7 (e7), and epithelial c10 (e10), exclusively in TRAMP, each expressing proliferative markers such as Mki67 and Top2a. To investigate the intercellular interactions among these clusters, we conducted ligand-receptor (LR) interaction analysis using CellChat. Notably, s6 is expressing the genes encoding ligands Bmp4, Fn1, and Igf1, which interact with the receptors Bmpr1b/Bmpr2, Itga3/Itgb1, and Igf1r, respectively expressed in e7. Subsequently, the transcriptomic profiles of these cells were used to build and validate a robust gene signature that can predict metastasis and survival in patients with PCa using a large cohort of 1239 samples, 930 of which were used for training while the remaining 309 samples were used for testing the model’s performance. In conclusion, these results underscore the role of the TME mediating PCa progression and highlight the potential of leveraging the TME to extract predictive and prognostic features which can be later employed to build predictive and prognostic models for patients with PCa. Citation Format: Itzel Valencia, Hubert Pakula, Mohamed Omar, Massimo Loda, Luigi Marchionni. Delineating the prostate cancer tumor microenvironment through scRNA-seq profiling at different timepoints [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 7351.
Abstract 1562: HMGA2 regulates GPX4 expression and oxidative stress
Authors: Precious Elechi Dike, Taaliah Campbell, Mojisoluwa Awolowo, Valerie Odero-Marah
Journal: Cancer Research (2024)

Abstract Prostate cancer (PCa) is a leading cause of mortality, primarily due to its ability to metastasize to the bone. The High Mobility Group AT-Hook 2 (HMGA2) plays a crucial role in regulating gene expression and has been implicated in tumorigenesis and the metastatic process. Our recent study revealed that overexpression of the wild-type/full-length HMGA2 isoform in PCa cells promotes cancer progression by triggering epithelial mesenchymal transition (EMT), whereas truncated HMGA2 isoform promotes progression through oxidative stress signaling. We hypothesize that HMGA2 regulates GPX4 expression and oxidative stress in PCa. We studied the expression of HMGA2 and GPX4 in various PCa cell lines including enzalutamide resistant cell line (C4-2B MDVR), LNCaP cells overexpressing HMGA2 isoforms (wild type and truncated HMGA2). Our analysis of HMGA2 and GPX4 expression in diverse PCa cell lines, shows an inverse relationship between HMGA2 and GPX4 levels. Elevated HMGA2 expression coincides with reduced GPX4 expression, leading to heightened oxidative stress and susceptibility to ferroptosis. Moreover, treatment of enzalutamide resistant cell line C4-2B MDVR with ferroptosis inducer RSL3, further suppresses GPX4 expression, resulting in decreased cell proliferation. Our results unveils the intricate relationship between HMGA2, GPX4 regulation and oxidative stress in the context of prostate cancer progression. Exploiting this oxidative stress pathway offers a promising therapeutic approach for cancer treatment, especially for enzalutamide-resistant cancer cells. Acknowledgements: These studies were supported by NIH/NIGMS/RISE SR25GM060414 and NIH/NIMHD 2U54MD007590; 5U54MD013376. Citation Format: Precious Elechi Dike, Taaliah Campbell, Mojisoluwa Awolowo, Valerie Odero-Marah. HMGA2 regulates GPX4 expression and oxidative stress [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 1562.
Abstract 2282: Predictive association of tumor cells hijacked NFATC2 activities with resistance to immune checkpoint inhibition in melanoma patients
Authors: Bashir Lawal, Yue Wang, Parisa Lotfinejad, Xiaosong Wang
Journal: Cancer Research (2024)

Abstract Background: Immune checkpoint blockade (ICB) has emerged as an effective cancer therapy. However, only a small fraction of patients receives benefits whereas a significant subset of patients experienced severe or even lethal autoimmune diseases. Stratifying patients that would benefit from immunotherapy remain a highly unmet clinical need. Dysregulations of transcriptional programs have been implicated in cancer initiation and progression. To date, there is a paucity of studies on the predictive values of transcriptional factors on ICB response based on the most recently emerged ICB clinical trial datasets. We reasoned that cancer cells may hijack key transcriptional programs in hematological cells to evade the attack from immune cells and acquired tolerance to immunotherapy. Method: Herein, we used an R package singscore/1.14.0 to compute the TFs activity scores based on their validated gene targets (TGs). Leveraging melanoma clinical trial datasets, we analyzed the predictive association of the TF scores with resistance to anti-PD1 ICB. The R package, iGenSig was used to evaluate the potential confounding variables. Results: Our landscape correlation analysis revealed NFATC2 (Nuclear Factor Of Activated T Cells 2)-TGs as the most significant predictor of anti-PD-1 ICB resistance in melanoma. NFATCT-TGS as a predictor of anti-PD1 resistance is confounded by liver metastasis and achieved AUC range between 0.71 to 0.74 in three datasets (PRJEB23709, GSE160638, and Phs000452). In addition, prior anti-CTLA4 exposure (AUC=0.87 and 0.89) is associated with higher predictive efficacy of NFATC2-TGS than anti-CTLA4 naïve tumor (AUC=0.61 and 0.69) in phs000452 and GSE91061 datasets. Survival analysis revealed that NFATC2 is a better predictor of progressive-free survival (PFS; HR=5.95), and overall survival (OS; HR= 3.28-3.38) in anti-CTLA4 exposed tumor than anti-CTLA4 naïve tumor (PFS: HR=1.92, and OS; HR=1.64-2.17). Finally, NFATC2-TGS show strong inhibitory correlation with B cells and T cells infiltration, but strongly correlated with tumor purity. Conclusion: We demonstrate that NFATC2 TGS predicts ICB benefits in melanoma patients, and thus may guide the recruitment of melanoma patients for anti-PD1 ICB. Our data provide support to the hypothesis that melanoma acquired NFATC2 transcriptional program to avoid immune cells evasion and acquired tolerance to ICB immunotherapy Citation Format: Bashir Lawal, Yue Wang, Parisa Lotfinejad, Xiaosong Wang. Predictive association of tumor cells hijacked NFATC2 activities with resistance to immune checkpoint inhibition in melanoma patients [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 2282.
Abstract 2992: miR-200-mediated inactivation of cancer-associated fibroblasts attenuates lung cancer invasion and metastasis
Authors: Inyoung Cheon, Sieun Lee, Young-Ho Ahn
Journal: Cancer Research (2024)

Abstract Cancer-associated fibroblasts (CAFs) play a crucial role in the tumor microenvironment and contribute to the development and progression of lung cancer. We aimed to elucidate whether miRNA-200 (miR-200), which is recognized for its ability to suppress EMT, prevents CAFs from promoting cancer progression. Inactivation of CAFs mediated by miR-200 suppressed lung cancer cell invasion, migration, tumorigenesis, and metastasis. Additionally, miR-200 attenuated the ability of CAFs to facilitate the aggressiveness of lung cancer cells, encourage M2 polarization of macrophages, and increase the angiogenic sprouting of vascular endothelial cells. NRP2, known as a co-receptor of VEGFR, was identified as a target of miR-200, mediating the functional activity of miR-200 in CAFs. NRP2-VEGFR signaling promoted the secretion of VEGFD and PTN from CAFs to activate cancer cell migration and invasion. Based on these findings, we suggest that miR-200 impedes cancer progression and metastasis by remodeling CAFs, and that miR-200 and NRP2 are potential therapeutic targets in the treatment of lung cancer. Citation Format: Inyoung Cheon, Sieun Lee, Young-Ho Ahn. miR-200-mediated inactivation of cancer-associated fibroblasts attenuates lung cancer invasion and metastasis [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 2992.
Abstract 4985: Pivotal roles for cancer cell-intrinsic mPGES-1 and autocrine EP4 signaling in suppressing anti-tumor immunity
Authors: Nune Markosyan, Ilkyu Kim, Charu Arora, Noah Cheng, Emma Schechter, John Tobias, Ben Stanger, Robert Vonderheide
Journal: Cancer Research (2024)

Abstract Tumor cell-derived prostaglandin E2 (PGE2) is a tumor cell-intrinsic factor that supports immunosuppression in the tumor microenvironment (TME). Using a genetically engineered mouse model of pancreatic ductal adenocarcinoma, we demonstrate that deleting the terminal PGE2 synthesis enzyme or disrupting autocrine PGE2 signaling through cognate EP4 receptors on tumor cells reverses the T cell-low, myeloid cell-rich TME to activate T cell immunity and suppress tumor growth. Knockout (KO) of Ptges (the gene encoding PGE2 synthesis enzyme mPGES-1) or the EP4 receptor gene (Ptger4) in KPCY (KrasG12D/P53R172H/Yfp/CrePd) pancreatic tumor cells abolished growth of implanted tumors in a T cell-dependent manner (KO vs control p&amp;lt;0.0001 for both). Blockade of the EP4 receptor in combination with immunotherapy, but not immunotherapy alone, induced complete tumor regressions and immunological memory. Mechanistically, Ptges and Ptger4 KO tumor cells exhibited altered T and myeloid cell attractant chemokines, became more susceptible to TNF-α killing, and exhibited reduced adenosine synthesis. In hosts treated with an adenosine deaminase inhibitor, Ptger4 KO tumor cells accumulated adenosine and gave rise to tumors. These studies reveal an unexpected role for autocrine mPGES1-PGE2-EP4 signaling axis in pancreatic cancer cells, nominating mPGES-1 inhibition and EP4 blockade as immune-sensitizing approaches in cancer therapy. Citation Format: Nune Markosyan, Ilkyu Kim, Charu Arora, Noah Cheng, Emma Schechter, John Tobias, Ben Stanger, Robert Vonderheide. Pivotal roles for cancer cell-intrinsic mPGES-1 and autocrine EP4 signaling in suppressing anti-tumor immunity [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 4985.
Abstract 2946: Characterizing the genomic landscapes of breast and lung tumors using cost-effective whole genome sequencing
Authors: Hila Benjamin, Ilya Soifer, Doron Shem-Tov, Maya Levy, Islam Oguz Tuncay, Baek-Lok Oh, Jong-Yeon Shin, Young Seok Ju, Sangmoon Lee, Omer Barad, Doron Lipson
Journal: Cancer Research (2024)

Abstract Whole Genome Sequencing (WGS) has emerged as a pivotal tool for unraveling the intricate genomic alterations underlying cancer, enabling the detection of a broad spectrum of somatic changes in cancer genomes, including single nucleotide variants, insertions, deletions, copy number variations, and structural rearrangements. Characterizing somatic variants across the entire genome significantly benefits from novel cost-efficient sequencing platforms, such as UG100. In the current study, we aim to demonstrate the utility of UG100 WGS in characterizing the landscape of somatic events in breast and lung cancer. Over 35 tumor-normal cancer sample pairs were profiled using UG100 WGS (mean tumor coverage: &amp;gt;100x; normal: &amp;gt;50x). Variant calling was done using a somatic deep-variant algorithm, optimized to UG100 data. Results were compared to Illumina sequencing and high concordance was observed, with over 97% of SNVs and over 93% of indels detected by Illumina identified also by UG100. UG100 sequencing was deeper and allowed for identification of a larger number of genomic variations, including known driver events in cancer-related genes. The somatic mutational signatures by UG100 were concordant with the Illumina platform, with a cosine similarity higher than 99%. Copy number variation and structural variation analysis was performed on all sample pairs, revealing a wide range of genomic aberrations. The integration of genetic sequencing into routine clinical oncology practices has proven instrumental in identifying actionable mutations, predicting treatment responses, and monitoring minimal residual disease. Moving from targeted sequencing to WGS provides a more comprehensive and unbiased assessment of the entire genome, uncovering rare or unexpected mutations that might be missed by targeted approaches. WGS allows for the simultaneous evaluation of both coding and non-coding regions of the genome, providing a deeper understanding of the regulatory elements influencing gene expression. This broader scope enhances our understanding of cancer biology and contributes to a more accurate assessment of the tumor's functional landscape. Citation Format: Hila Benjamin, Ilya Soifer, Doron Shem-Tov, Maya Levy, Islam Oguz Tuncay, Baek-Lok Oh, Jong-Yeon Shin, Young Seok Ju, Sangmoon Lee, Omer Barad, Doron Lipson. Characterizing the genomic landscapes of breast and lung tumors using cost-effective whole genome sequencing [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 2946.