tbuckley/cabot-search huggingface dataset:
Abstract 553: Assessment of CNTN4 expression and its association with PD-L1 across 18 various cancers using an artificial intelligence-powered immunohistochemistry analyzer
Authors: Seunghwan Shin, Jimin Moon, Soo Ick Cho, Chan-Young Ock, Bu-Nam Jeon, Gyeongyeon Kim, Hyunkyung Yu, Miyoung Cha
Journal: Cancer Research (2024)

Abstract Background: Contactin-4 (CNTN4) has been identified as an inhibitory immune checkpoint protein and mainly expressed on tumor cells. It interacts with APP present in T cells, leading to a reduction in T cell proliferation, activation, and responsiveness to tumors. In this study, we applied artificial intelligence (AI)-powered analyzers to examine the expression of CNTN4 and its association with PD-L1 in various solid tumors. Methods: The AI-powered immunohistochemistry (IHC) analyzers were developed using pan-cancer whole slide images (WSIs) stained with 18 different IHC types. Pathologists annotated cells and tissues on the WSIs. The universal model was trained by annotations from IHC WSI, which could detect tumor cells with four grade intensities (strong, moderate, weak, and negative) and segment invasive cancer area. Finally, the AI analyzer can count the tumor cells in an invasive cancer area and calculate the ratio based on intensity. The AI analyzer was applied to the pan-cancer tissue microarray dataset (n=795) consisting of 18 cancers to validate the analyzer. The dataset was stained with rabbit monoclonal antibody (clone EPR 8735) and PD-L1 22C3 antibody, respectively. The expression levels of CNTN4 and PD-L1 were calculated with H-score (range 0 to 300) or tumor proportion score (TPS). Results: When positivity was defined as moderate-to-strong staining intensity in ≥ 30%, 50%, 75%, and 90%, 42.4% (337/795), 25.5% (203/795), 11.4% (91/795), and 5.2% (41/795) of samples were CNTN4 positive, respectively. In case of moderate-to-strong staining in ≥ 50% tumor cells, CNTN4 expression were most frequently observed in hepatocellular carcinoma (63.9%), endometrial carcinoma (50.0%), stomach cancer (43.9%), pancreatic cancer (40.0%), and prostate cancer (35.4%). Notably, 10% of cases with an H-score &amp;lt; 200 (75/757) showed a range of PD-L1 expression (PD-L1 TPS ≥ 1%), while all of the samples with an H-score ≥ 200 (n=38) were PD-L1 TPS &amp;lt;1%. Conclusions: This study describes the CNTN4 expression levels in various tumors using an AI-powered IHC analyzer. CNTN4 tends to be expressed in opposition to PD-L1, making it a viable immune therapeutic target in cancers that do not conventionally express PD-L1. Citation Format: Seunghwan Shin, Jimin Moon, Soo Ick Cho, Chan-Young Ock, Bu-Nam Jeon, Gyeongyeon Kim, Hyunkyung Yu, Miyoung Cha. Assessment of CNTN4 expression and its association with PD-L1 across 18 various cancers using an artificial intelligence-powered immunohistochemistry analyzer [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 553.
Abstract 7497: Advancing multi-biomarker CTC assay and CDx development through the automated GenoCTC system
Authors: Chaithanya Chelakkot, Jieun Park, Chae Rin Kim, Yeonu Lee, Yu Rim Lee, Saehyung Lee, Jun Young Choi, Young Ho Moon, Yoon-La Choi, Young Kee Shin, Hun Seok Lee
Journal: Cancer Research (2024)

Abstract Introduction: The successful outcomes observed in clinical trials emphasize the effectiveness of therapeutic approaches relying on biomarker tests, particularly in the development of cancer drugs. The parallel development of a drug and its associated predictive biomarker is considered an ideal strategy for achieving rapid and successful drug development in precision medicine. In this context, we employ an automated circulating tumor cell (CTC) isolation platform, known as GenoCTC, to facilitate the development of biomarker-driven CTC assays, with the ultimate goal of developing companion diagnostic (CDx) tests. Method: This study employed the 5th generation GenoCTC device, a fully automated system designed for marker-based CTC enrichment using immune magnetophoresis. We confirmed the isolation of CTCs through spiking tests, utilizing cancer biomarkers such as cMET, Mesothelin (MSLN), and Claudin 3 (CLDN3). cMET is a biomarker extensively studied in various cancers, particularly non-small cell lung cancer. We previously showed the prognostic significance of cMET expressing CTCs in HR+ and HER2- metastatic breast cancer patients. MSLN and CLDN3 are tumor-associated proteins showing overexpression across diverse cancer types, with a potential for the development of antibody-based cytotoxic drugs. The GenoCTC device allows efficient separation of CTCs expressing these biomarkers, ensuring high accuracy, precision, specificity, and sensitivity. Simultaneously, therapeutic drugs directed at these markers are progressing through phase trials or preclinical studies. Conclusion: Our results show that cMET, MSLN, and CLDN3 are potential markers for the development of biomarker tests, that can improve the patient selection process for personalized therapy targeting these biomarkers. Citation Format: Chaithanya Chelakkot, Jieun Park, Chae Rin Kim, Yeonu Lee, Yu Rim Lee, Saehyung Lee, Jun Young Choi, Young Ho Moon, Yoon-La Choi, Young Kee Shin, Hun Seok Lee. Advancing multi-biomarker CTC assay and CDx development through the automated GenoCTC system [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 7497.
Abstract 3606: Tumor-specific CD8+ Tc9 cells activate host CD4+ T cells to control antigen-lost tumors
Authors: Liuling Xiao, Qing Yi
Journal: Cancer Research (2024)

Abstract Cancer immunotherapies relying on targeted destruction of cancer cells by potent antitumor T cells have achieved unprecedented success in recent years. As a main form of cancer immunotherapies, adoptive T cell therapy (ACT) has shown a durable response in certain cancer patients. However, this response is often short-lived and tumor relapse occurs due to the outgrowth of antigen-lost-variant (ALV) tumors and poor antitumor immune response. Here, We reported that adoptively transfer of murine tumor-specific CD8+ Tc9 but not Tc1/CTL cells achieved long-term control of tumor growth in vivo. Here, we demonstrated that murine tumor-specific Tc9 cells not only killed antigen-expressing primary tumors but also controlled the outgrowth of antigen-lost relapsed tumors by recruiting and activating host effector CD4+ T cells that recognized relapsed tumors. Tc9 cells secreted IL-24 and recruited CCR7-expressing conventional type-2 dendritic cells (cDC2) into tumor-draining lymph nodes to prime host CD4+ T cell response against relapsed tumors. Depleting host CD4+ T cells or deficiency in CCR7 expression impaired Tc9 cell ability to control the outgrowth of relapsed tumor. We also observed that intratumoral IL24 expression was positively correlated with gene signatures of cDC2 and CD4+ T cells in human cancers and expression of IL24 and cDC2 and CD4+ T cell gene signatures were associated with patient’s overall survival. Thus, this study uncovers a novel mechanism underlying activation of tumor-specific CD4+ T cells in vivo. Citation Format: Liuling Xiao, Qing Yi. Tumor-specific CD8+ Tc9 cells activate host CD4+ T cells to control antigen-lost tumors [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 3606.
Abstract 1851: Comprehensive multi-level proteomics characterization of gastric cancer
Authors: Yuefan Wang
Journal: Cancer Research (2024)

Abstract Gastric cancer is the leading cause of cancer related deaths worldwide, accounts for over 700,000 deaths each year. There is an urgent need for advancing therapeutic strategies for patients with gastric cancer. Addressing this need, the Clinical Proteomics Tumor Analysis Consortium (CPTAC) has conducted a comprehensive characterization of gastric cancer, aiming to elucidate the complex molecular mechanisms driving this cancer type, and to discover underlying cancer biology that will form the basis for developing new approaches for precision medicine. This comprehensive study includes an integrated multi-level proteomics analysis of 165 surgically resected gastric cancer and 41 normal adjacent tissues. We employed a multi-faceted approach, analyzing the proteome, phosphoproteome and glycoproteome, along with other protein modifications including ubiquitination, acetylation, and tyrosine phosphorylation. Furthermore, we extended our research to include 74 pairs of early-onset gastric cancer and normal adjacent tissues, analyzed using a proteomic approach. We can totally identify more than 12,000 protein groups with median identification of 9750 protein groups per sample. This expansive dataset helps constructing a comprehensive multi-omics atlas of gastric cancer, offering a deep understanding into the disease's molecular landscape. The depth of this study was enhanced by incorporating multi-level proteomics data across 6 tiers, facilitating an unprecedented multi-level proteomics analysis. Our integrated approach allows us to illustrate the changes in protein expression, protein modifications, signaling pathways, and protein networks during tumorigeneis. This analysis uncovers potential therapeutic targets for personalized treatments. Overall, our study provides a multi-omics atlas for gastric cancer, a profound insight into gastric cancer biology, contributing significantly to the understanding of its pathogenesis. It could pave the way for precise treatments for gastric cancer, underscoring the potential of multi-level proteomics analyses in advancing personalized medicine. Citation Format: Yuefan Wang, Clinical Proteomic Tumor Analysis Consortium (CPTAC). Comprehensive multi-level proteomics characterization of gastric 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 1851.
Abstract 5897: Understanding and targeting fatty acid CoA ligase ACSL4 in human prostate cancer
Authors: Jinjin Wu, Mu-En Wang, Ming Chen, Pyeong Hwa Jeong, Jiyong Hong, Lixin Wan
Journal: Cancer Research (2024)

Abstract Prostate cancer (PCa) is the most common non-cutaneous malignancy among men. Although localized prostate cancer is curable, recurrence of metastatic castration-resistant prostate cancer (mCRPC) is almost inevitable and is the major cause of death in human PCa. Recent findings from our lab and others demonstrate that RB1 loss drives lineage plasticity, metastasis, and lethality of prostate tumors initiated by PTEN loss. A downstream target upregulated by RB1 loss is acyl CoA synthetase long chain family member 4 (ACSL4), a fatty acid ligase with an essential role in utilization of long chain fatty acids. ACSL4 has been reported to be upregulated in cancers of various histological origins, including prostate cancer, and its high expression is correlated with aggressiveness of cancer. We hypothesize that ACSL4 is a critical downstream effector of RB1 loss-driven prostate tumorigenesis and pharmacological inhibition of ACSL4 could represent a novel therapeutic approach to the treatment of lethal RB1 deficient or ACSL4 overexpressing prostate cancer. Here we aim to develop novel ACSL4 inhibitors for preclinical studies. Through a structure based virtual screening that targeted ATP binding domains of ACSL4, we successfully identified 15 potential ACSL4 inhibitors. To validate the result, we performed an in vitro screening using various parental and isogenic human PCa cell lines, and found that 4 out of 15 compounds effectively inhibited PCa cell proliferation in a dose-response manner and their inhibitory effects positively correlated with cellular levels of ACSL4. Next, we will perform isotope-labeling enzyme activity assays to determine the specificity of the 4 candidate drugs, and PDPK analyses followed by characterizing their in vivo efficacies in preclinical studies, with a final goal to develop a well-validated ACSL4 inhibitor. Successful completion of this work will provide great insights into contributions of ACSL4 to prostate tumorigenesis as well as preclinical data of ACSL4 inhibitors to treat lethal prostate cancer. Citation Format: Jinjin Wu, Mu-En Wang, Ming Chen, Pyeong Hwa Jeong, Jiyong Hong, Lixin Wan. Understanding and targeting fatty acid CoA ligase ACSL4 in human prostate 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 5897.
Abstract 3503: New generation drug development from <i>in-silico</i> identification to preclinical evaluation in glioblastoma
Authors: Mahesh Arunachalam, Shreyas Gaikwad, Sharavan Ramachandran, Sanjay K. Srivastava
Journal: Cancer Research (2024)

Abstract Glioblastoma(GBM) is the most common malignancy of the central nervous system in adults. Despite medical advancements, stagnant survival rate improvements (&amp;lt;13%) and failure of conventional treatments such as temozolomide, have warranted the need for novel drug discovery methodologies. Considering the enormous potential of drug repurposing, we developed a method to identify a safe, active, and effective treatment for GBM. This method comprises two key stages, drug-target prediction and preclinical functional evaluation. Stage 1 fabricated a novel five phase in-silico pipeline for drug-target prediction against Ephrin-Type-A Receptor 2, chosen through preliminary literature and genomic analysis. Around 1562 FDA approved drugs were screened against the developed criterion and analyzed for bond type, location, repulsion, Gibbs free energy, stability, interactions over time, blood brain barrier permeability, and possible false positives (PAINS). Our results provided five plausible hits: Empagliflozin, Mycophenolate mofetil, Canagliflozin, Rivaroxaban, and Carvedilol. We subsequently evaluated the anti-proliferative effects of these hits using Sulforhodamine-B cytotoxicity assay on glioblastoma cell lines U251 and SF295. Our results demonstrated that Canaglifozin and Empagliflozin reduced the proliferation of GBM cell lines with IC50 value ranging from 30-40 μM. On the other hand, Mycophenolate mofetil (IC50: 5μM) and Carvedilol (IC50:16μM) also exhibited significant cytotoxic effects. Effects of Mycophenolate mofetil and Carvedilol were further evaluated in pancreatic cell line SUIT-2 where results exhibited cytotoxic responses similar to those observed in GBM. Furthermore, Annexin V/FITC analysis showed apoptosis in SUIT-2 cells by Carvedilol. Taken together, our results show the anti-cancer repurposing candidates extracted from our in-silico pipeline show significant cytotoxic effects of compounds identified through in-silico screening. Further studies are currently underway in our laboratory to delineate the anti-cancer mechanism, toxicity and off-target effects of these compounds. Citation Format: Mahesh Arunachalam, Shreyas Gaikwad, Sharavan Ramachandran, Sanjay K. Srivastava. New generation drug development from in-silico identification to preclinical evaluation in glioblastoma [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 3503.
Abstract 3518: Next generation H&amp;E cell modeling: Using same-slide multiplex immunofluorescence (mIF) data to train H&amp;E
Authors: Becky Arbiv, Amit Bart, Tal Dankovich, Ron Elran, Shai Bookstein, Avi Laniado, Tomer Dicker, Sun Dagan, Oscar Puig, Kenneth Bloom, Ettai Markovits
Journal: Cancer Research (2024)

Abstract Haematoxylin &amp; Eosin (H&amp;E)-based deep learning algorithms require a large number of human-based cell annotations for model training, and are limited by what a human eye can see. Multiplex immunofluorescence (mIF) offers a more comprehensive and accurate method for classifying cells because annotations are based on cell status, i.e. whether a cell expresses certain markers or not. In this study, we leverage mIF-based cell type predictions1 to enhance H&amp;E model performance.We used a publicly available CODEX/PhenoCycler dataset2 consisting of 140 tissue cores obtained from 35 patients with colorectal cancer, which were stained with 56 protein markers and subsequently with H&amp;E. mIF data was used to create over 60,000 prediction-based annotations on the corresponding H&amp;E-stained images that were used to train deep learning H&amp;E classifiers. The final model performance reached AUC of 0.91 when evaluated on the H&amp;E test annotations and 0.90 on the mIF predictions. Notably, the mIF annotations-based H&amp;E model surpassed the manual annotations-based H&amp;E model in effectively identifying challenging cell types, demonstrating its superior performance. These findings highlight the potential of leveraging mIF cell type predictions to train accurate and automated H&amp;E models. 1Markovits et al, BioRxiv, https://doi.org/10.1101/2022.11.09.5157762Schürch et al, Cell. 2020,182(5): 1341-1359.PMID: 32763154 Citation Format: Becky Arbiv, Amit Bart, Tal Dankovich, Ron Elran, Shai Bookstein, Avi Laniado, Tomer Dicker, Sun Dagan, Oscar Puig, Kenneth Bloom, Ettai Markovits. Next generation H&amp;E cell modeling: Using same-slide multiplex immunofluorescence (mIF) data to train H&amp;E [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 3518.
Abstract 4528: Improving carboplatin therapy: A novel albumin-targeted platinum(IV) prodrug with superior anticancer activity <i>in vivo</i>
Authors: Hemma Schueffl, Regina Weinmuellner, Nadine Sommerfeld, Bernhard K. Keppler, Walter Berger, Christian R. Kowol, Petra Heffeter
Journal: Cancer Research (2024)

Abstract Platinum(II)-based chemotherapeutics are among the most commonly used anticancer drugs and are part of nearly every second treatment scheme. However, they lack in tumor specificity, causing severe sides effects, dose-dependent toxicity as well as drug resistance development. Due to their higher tolerability, platinum(IV) prodrugs are currently in the focus of interest. However, comparable to their platinum(II) counterparts, they show insufficient tumor accumulation and are frequently prematurely activated. A promising strategy to improve tumor targeting of anticancer drugs is to exploit the enhanced consumption and accumulation of albumin in the malignant tissue. Thus, we developed a new albumin-targeted maleimide-containing platinum(IV) prodrug, which releases carboplatin in a highly tumor-specific manner. The maleimide moieties enable the drug to selectively bind the endogenous albumin via its free thiol of cysteine 34. The aim of this study was to in-depth characterize the pharmacological behavior and anticancer activity in vivo of the new prodrug. To this end, several xenograft and allograft experiments were performed. To investigate tissue distribution and pharmacokinetics serum, urine, tumor and organ samples of mice were collected after drug treatment and were evaluated by (size-exclusion chromatography) inductively-coupled plasma mass spectrometry and immunohistochemistry (e.g cleaved caspase-3). These experiments revealed that the new prodrug fast and selectively binds to the serum albumin after intravenous injection, leading to an enhanced plasma half-life and an increased tumor accumulation in comparison to its corresponding platinum(II) drug carboplatin. Additionally, the new complex resulted in superior anticancer activity and prolonged overall survival based on the distinctly improved pharmacokinetic profile and enhanced apoptosis induction. In conclusion, these data support that albumin binding is a potent tool to increase the tumor specificity of platinum(IV) drugs and prevent their premature activation in other body compartments. Consequently, this very promising prodrug will be further developed towards clinical phase I testing. Citation Format: Hemma Schueffl, Regina Weinmuellner, Nadine Sommerfeld, Bernhard K. Keppler, Walter Berger, Christian R. Kowol, Petra Heffeter. Improving carboplatin therapy: A novel albumin-targeted platinum(IV) prodrug with superior anticancer activity in vivo [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 4528.
Abstract 6025: Discovery of novel macrocyclic peptide radioligands for tumor therapy by mRNA display
Authors: Anika Jaekel, Kathryn Sherry, Prachi Desai, David Fox, Tang Guo-Qing, Manuel Sturzbecher-Hoehne, Dennis Mewis, Kaori Noridomi, Liam Rayman, Ping Ye
Journal: Cancer Research (2024)

Abstract Radioligand therapeutics (RLT) aim to selectively deliver radioisotopes to cancer tissues to eradicate tumor cells while limiting the damage to surrounding tissues. They are composed of a tumor-targeting ligand and a radioactive payload. The therapeutic potential of RLT strongly depends on their biostability and residence time in tumor and healthy tissue after injection. Macrocyclic peptides are effective tumor-targeting ligands because their size and molecular characteristics confer optimal pharmacologic properties that can be fine-tuned during the development process. mRNA display is a powerful platform for macrocyclic peptide drug discovery that identifies high affinity peptide ligands through in vitro selection. Here, we describe the selection and initial characterization of macrocyclic peptides discovered by mRNA display that bind to the extracellular domain of a tumor target. Enrichment of the library for peptides that bound to the recombinant target protein was observed after four rounds of selection with no further enrichment in round five. The library of round 5 was sequenced by Illumina sequencing and the top 1,000 sequences (highest counts) were used to perform cluster analysis. We tested the top sequences of 43 different clusters in in vitro translation binding assays to validate the selection output and identify sequences for hit confirmation. Most of the sequences tested showed clear binding to the target protein and only a few peptides showed binding to a closely related protein from the same protein family. No non-specific binding of the discovered peptides to an irrelevant protein was observed showing the high specificity of the generated library. From this confirmatory selection data, we chose a subset of peptides for chemical synthesis. Binding affinity measurements were determined by surface plasmon resonance (SPR) and cellular binding of selected candidates to target-positive and -negative tumor cells was analyzed by flow cytometry. From this hit confirmation data, in vitro internalization and in vitro anti-tumor efficacy of radiolabeled peptide candidates for RLT are assessed. Our data highlights the potential of mRNA display platforms for fast and efficient discovery of highly specific macrocyclic peptides with optimal binding properties suitable for RLT. Citation Format: Anika Jaekel, Kathryn Sherry, Prachi Desai, David Fox, Tang Guo-Qing, Manuel Sturzbecher-Hoehne, Dennis Mewis, Kaori Noridomi, Liam Rayman, Ping Ye. Discovery of novel macrocyclic peptide radioligands for tumor therapy by mRNA display [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 6025.