tbuckley/cabot-search huggingface dataset:
Abstract 3577: The role of PLXND1 in lineage plasticity and progression to neuroendocrine prostate cancer
Authors: Bo Chen, Pengfei Xu, Joy C. Yang, Shu Ning, Leyi Wang, Christopher Nip, Allen C. Gao, Chengfei Liu
Journal: Cancer Research (2024)

Abstract Background: Neuroendocrine prostate cancer (NEPC) is a lethal subtype of prostate cancer and is commonly associated with therapy resistance and poor prognosis. Treatment-induced NEPC (t-NEPC) predominantly develops by lineage plasticity from adenocarcinoma in response to androgen receptor signaling inhibitors, such as enzalutamide. However, the mechanisms underlying the lineage plasticity and progression to NEPC are unclear. PLXND1 (PlexinD1) is a cellular receptor of the semaphorin family and has important functions in modulating the cytoskeleton and cell adhesion. However, the role of PLXND1 in lineage plasticity to NEPC development and progression is not well established. Methods: We performed transcriptomic analysis on NEPC patients’ cohorts and the enzalutamide-resistant prostate cancer cell lines. Correlation of PLXND1 with neuroendocrine feature genes and AR-targeting genes was determined. Kaplan-Meier method and the Cox proportional hazards model was used to estimate the correlation between PLXND1 expression level and patients’ survival. Immunohistochemistry was used to analyze PLXND1 expression in prostate adenocarcinoma and NEPC. Cell viability was determined in C4-2B MDVR, CWR22Rv1, and H660 cells after knocking down PLXND1 using siRNA or knocking out PLXND1 using CRISPR/CAS9. Organoids viability of patient-derived xenografts was measured after knocking down or knocking out PLXND1. Results: Our analysis on different patient cohorts suggests that PLXND1 is highly expressed in NEPC patients, and the expression of PLXND1 is positively correlated with neuroendocrine feature genes (CHGA, ENO2, SYP, and NCAM1). Kaplan-Meier survival analysis shows that high expression of PLXND1 is significantly associated with the poor prognosis of prostate cancer patients. PLXND1 is overexpressed and negatively regulated by androgen receptor signaling in enzalutamide-resistant cells and prostate cancer patients’ cohorts. Furthermore, downregulation of PLXND1 expression suppressed proliferation of the NEPC cells and viability of the PDX tumor organoids. Conclusions: PLXND1 expression is elevated in NEPC and correlated with the poor survival of prostate cancer patients, suggesting it is a potential molecular indicator and therapy target for NEPC. Citation Format: Bo Chen, Pengfei Xu, Joy C. Yang, Shu Ning, Leyi Wang, Christopher Nip, Allen C. Gao, Chengfei Liu. The role of PLXND1 in lineage plasticity and progression to neuroendocrine 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 3577.
Abstract 1849: High throughput interactome profiling of small bioactive peptides
Authors: Charles D. Warren, Noah Yardeny, Jacob B. Geri
Journal: Cancer Research (2024)

Abstract Interactions between individual biomolecules give rise to emergent signaling and regulatory networks that govern complex and varied biological processes. Disruption of these finely tuned interactions can result in imbalanced cellular states that drive diseases; for example, many metastatic cancers become desensitized to checkpoints encoded by molecular contacts. Still, numerous interaction networks remain unmapped within the cell, namely those between cryptic endogenous peptides and their protein targets. This is primarily due to the lack of investigation around translation events that occur from “noncoding” genetic material and limited knowledge of how translated polypeptides can mature into functional proteolytic fragments. Moreover, technologies to map protein-peptide interactions in an efficient and reliable manner are limited, leaving a gap in knowledge of how many bioactive peptides regulate cellular homeostasis. We aim to map the interactions of short (30 &amp;gt; amino acid), bioactive peptides that are (1) translated from noncanonical open reading frames or (2) generated through proteolytic cleavage of nascent proteins. To achieve these goals, we are leveraging the recently developed MicroMap technology and label-free mass spectrometry-based proteomics. A scalable and reliable platform to discover peptide binding targets will uncover the elusive functional roles of understudied endogenous peptides in cell signaling and their part in driving cancer cell survival. Citation Format: Charles D. Warren, Noah Yardeny, Jacob B. Geri. High throughput interactome profiling of small bioactive peptides [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 1849.
Abstract 6919: Cell line panel with HIBIT-tagged endogenous proteins to accelerate PROTAC drug discovery
Authors: Yunpeng Zhai, Jiayi Ma, Yu Wang, Meng Liang, Yao Peng, Jinying Ning, Feng Hao
Journal: Cancer Research (2024)

Abstract Small molecular drugs have been an important part of disease treatment, but there are also some problems along with time and intrinsic disadvantages of small molecular drugs. In recent years, the emergence of proteolysis targeting chimeras (PROTACs) is expected to overcome some defeats of traditional small molecules. PROTACs, also known as hetero-bifunctional compounds, are a new kind of therapeutic, that consists of a specific ligand to bind the target protein, a suitable linker, and an E3 ubiquitin ligase substrate. After binding to target proteins, PROTACs recruit E3 ligase and induce degradation of target proteins through the ubiquitin-proteasome system. Therefore, PROTACs are a good choice for some protein targets that have small molecular binding ligands but poor small molecular efficacy, which expands druggable targets. Meanwhile, the protein degradation induced by PROTACs destroys not only the enzymatic but also the non-enzymatic functions of targets, rather than only inhibiting the protein activity, which reduces drug resistance. In this study, in order to detect the degradation of intracellular target proteins by PROTACs, Kyinno has designed and constructed several HiBiT-tagged cell line models for different target proteins and their mutations, including KRA, CDK2, LDHA, and HPK. HiBiT is a small tag with 11 amino acids that don’t influence the expression, folding, and localization of target proteins, and luminesces with a detection buffer. All these cell lines with endogenous protein mutations and HiBiT knock-ins are constructed by CRISPR-Cas9 technology and validated by siRNA and PROTACs. Compared with overexpressed exogenous HiBiT-tagged target proteins, endogenous proteins can more accurately and stably reflect the efficacy of PROTACs. Our cell models can be used for high-throughput screening not only for PROTAC drugs but also for molecular glues, lysosome-targeting chimeras (LYTACs), and antibody-based PROTACs (AbTACs). Citation Format: Yunpeng Zhai, Jiayi Ma, Yu Wang, Meng Liang, Yao Peng, Jinying Ning, Feng Hao. Cell line panel with HIBIT-tagged endogenous proteins to accelerate PROTAC drug discovery [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 6919.
Abstract 3553: OralDB, A integrative data portal for oral and oropharyngeal cancer omics and clinical research
Authors: Junlin Wang, Pui Ying Lam, Yuxiong Su, Junwen Wang
Journal: Cancer Research (2024)

Abstract Oral and oropharyngeal cancer is one of the more common cancers worldwide, with a poor prognosis in advanced stages and a higher incidence in Asian populations than in other regions. Its affected Affected areas include the lips, gums, tongue, the inside of the cheeks, the roof of the mouth, the floor of the mouth, the tonsils, and the oropharynx. Currently, the distribution of RNA expression data and clinical data in oral and oropharyngeal cancer is fragmented, impeding effective data mining for the discovery of novel biological markers and testing of new hypotheses. We constructed an oral and oropharyngeal cancer-specific database with expression dataRNA expression and clinical data from more than 4,356 patients in 41 studies. The RNA Expression data from 23 genome-wide platforms are carefully processed and quality-controlled, while clinical data is standardized and tightly managed. With the support of this oral and oropharyngeal cancer-specific database oral cancer-specific database, we have created an open-access web resource, the Oral and Oropharyngeal Cancer Browser, to facilitate researchers interested in oral and Oropharyngeal cancer to quickly access and analyze all currently published RNAoral cancer expression data and clinical data. Users can perform a meta-analysis of Oral and oropharyngeal oropharyngeal cancer to quickly understand the results of tumor versus non-malignant tissue (normal), differential gene expression, and expression-survival associations. Flexible options for survival analysis, comparative analysis, and correlation analysis based on a single dataset are also available. At the same time, the database also accepts the user's own input data and allows the user to do theircarry out their own analysis by combining the input data with the existing data in the database. Citation Format: Junlin Wang, Pui Ying Lam, Yuxiong Su, Junwen Wang. OralDB, A integrative data portal for oral and oropharyngeal cancer omics and clinical research [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 3553.
Abstract 3546: Putting genes in context by linking gene signatures to established cancer hallmarks
Authors: Otília Menyhart, William Kothalawala, Balázs Győrffy
Journal: Cancer Research (2024)

Abstract The concept of the "Hallmarks of Cancer" provides a valuable framework for understanding fundamental organizing principles common to various types of cancers. However, the absence of a consensus gene set for cancer hallmarks poses data comparison and integration challenges, resulting in diverse biological interpretations across studies. Here, we first established a consensus cancer hallmark-gene set by merging data from available mapping resources. We searched the scientific literature for relevant publications from which a list of hallmark genes could be reconstructed. By consolidating data from seven publications, we identified 6,763 candidate cancer hallmark genes associated with ten cancer hallmarks. Of these, 1574 genes were part of at least two resources, forming a "core" hallmark gene set. Then, we compared the enrichment of cancer hallmarks by analyzing the prognostic genes associated with overall survival across twelve solid tumor types. Notably, the hallmark "tissue invasion and metastasis" was most prominent in the stomach (p=1.2E-11), pancreatic (p=1.5E-09), bladder (p=1.8E-08), and ovarian cancers (p=0.0002), aligning with their heightened potential to spread. "Sustained angiogenesis" predominated in lung squamous carcinomas (p=4.5E-08), while "genome instability" showed strong enrichment in lung adenocarcinomas (p=1.3E-09), liver (p=1.4E-10), pancreatic (p=1E-5) and kidney cancers (p=0.0025). Compelling evidence links lifestyle choices like alcohol consumption and smoking to genomic instability across tumors, suggesting a potential common underlying mechanism of tumorigenesis. Pancreatic cancers displayed the highest enrichment of hallmarks (8 out of 10), emphasizing the disease's complexity, while in melanomas, liver, and kidney cancer, a single hallmark (,,genomic instability”) was enriched among the prognostic markers of survival. These findings underscore the utility of the hallmark concept as an effective organizational tool, particularly when establishing a clear connection between genes and biological functions. Finally, we integrated the data into a publicly accessible and user-friendly online tool (available at www.cancerhallmarks.com) that allows users to identify the most relevant cancer-associated "candidate hallmark genes" in their datasets. In summary, we have established a consensus list of genes associated with cancer hallmarks. The analysis of survival-associated genes revealed a unique pattern of hallmark enrichment for each tumor type. Citation Format: Otília Menyhart, William Kothalawala, Balázs Győrffy. Putting genes in context by linking gene signatures to established cancer hallmarks [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 3546.
Abstract 4731: Targeting Lon protease as novel strategy to treat aggressive IDH mutant diffuse malignant astrocytoma
Authors: Christopher Douglas, Shashi Jain, Naomi Lomeli, Thao Vu, James Pham, Daniela A. Bota
Journal: Cancer Research (2024)

Abstract While isocitrate dehydrogenase (IDH) wild-type and mutant malignant astrocytoma (IDHwt, IDHmt) are diffuse CNS tumors that have a high degree of parallelism with one another, including microvascular proliferation and necrosis, the IDHwt tumors clinically presents with a higher tumor grade and thus poorer prognosis and survival rate. Isocitrate dehydrogenase mutation (IDH) hinders the hypoxia response in gliomas and promotes an advantageous reduction in both tumor growth and treatment resistance. Since recurrence is high, adequate characterization and identification of potential novel molecular targets in IDHmt mutant diffuse glioma is integral for developing new therapeutic strategies for better control of tumor burden and, thus, improved outcomes. Our previous published work has shown that the hypoxia responsive LONP1 mitochondrial protease is involved in glioma growth and treatment resistance and that LONP1 inhibitors can augment the effect of chemotherapy in IDHwt models. Here, we highlight the downstream activity of LONP1 via the NRF2 pathway and how synergistically, along with the IDH mutation, LONP1 overexpression can promote the subsequent proneural to mesenchymal transition (PMT) induced by stress and other tumor microenvironment signals. By characterizing the interplay between LONP1 and IDH mutation in in-vitro models, we demonstrate that oxidative stress modulates both PMT and TMZ drug resistance. When translated to an in-vivo patient-derived, intracranial orthotopic xenograft model, LONP1 overexpression is associated with decreased survival.Based on our findings, future clinical translation includes the possibility of using LONP1 as a novel target to optimize the standard of care treatment in IDH mutant diffuse astrocytoma. Citation Format: Christopher Douglas, Shashi Jain, Naomi Lomeli, Thao Vu, James Pham, Daniela A. Bota. Targeting Lon protease as novel strategy to treat aggressive IDH mutant diffuse malignant astrocytoma [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 4731.
Abstract 356: Developing a multiplex assay to monitor apoptosis and necrosis using the Cellaca® PLX Image Cytometer
Authors: Joydeep Mukherjee, Mackenzie Pierce, Yongyang Huang, Allen Lin, Leo Li-Ying Chan
Journal: Cancer Research (2024)

Abstract Apoptosis is a critical pathway for programmed cell death that cancer cells can evade to ensure survival. For pharmaceutical drug discovery, it is important to characterize and compare cancer therapeutics (i.e., small molecules, antibody drugs, cell therapies) that can initiate the process of apoptosis, allowing for the identification of potential therapeutic candidates. In this work, we developed and demonstrated a multiplex detection method for monitoring apoptosis and necrosis with Annexin V, Caspase 3/7, and Propidium Iodide (PI) using the Cellaca® PLX Image Cytometer. First, apoptosis was induced in Jurkat and K562 cell lines with staurosporine over the course of 24 h, and were monitored at 0, 1, 1.5, 2, 4, 20, and 24 h timepoints. Samples were stained with Hoechst 33342 (total dye), Annexin V-APC (early-stage apoptosis), Caspase-3 488 (late-stage apoptosis), and PI (necrosis) at each timepoint and evaluated using the Cellaca® PLX. Results showed that apoptotic factors and cascades were successfully detected along the pathway from early to late-stage apoptosis, and ultimately necrosis. A clear trend was observed during the first 2 h showing differences of up to 25% between the single Annexin V+ and Caspase-3+ populations in treated Jurkat cells, however, a significant increase in double positive apoptotic/necrotic cells for Annexin V+PI+ and Capase-3+PI+ was not observed until 20 h. Upon further analysis amongst apoptotic populations, Annexin V+ only populations were higher than Caspase-3+ only populations by up to 30% between 0-2 hours. Conversely, K562 cells did not exhibit a notable change in apoptotic and necrotic populations due to low sensitivity to staurosporine. The proposed image-based detection method using the Cellaca® PLX may provide an effective and efficient tool for rapid and reliable simultaneous detection of early, late-stage apoptosis, and necrosis. This may allow researchers to better characterize and screen potential cancer therapeutic drug candidates in a high-throughput manner to determine their treatment efficacy. Citation Format: Joydeep Mukherjee, Mackenzie Pierce, Yongyang Huang, Allen Lin, Leo Li-Ying Chan. Developing a multiplex assay to monitor apoptosis and necrosis using the Cellaca® PLX Image Cytometer [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 356.
Abstract 3559: A validated bioinformatics tool-set for predicting TCR specificity
Authors: Andreas Wilm, Florian Schmidt, Melissa Wirawan, Manisha Cooray, Kan Xing Wu, Katja Fink, Dan MacLeod
Journal: Cancer Research (2024)

Abstract Background: The T-cell receptor (TCR) is a transmembrane receptor on T cells, which is responsible for recognizing any foreign antigen derived peptide, presented on infected or abnormal cells by the MHC-I complex. Predicting TCR specificity computationally is a long-standing problem. Many methods leverage large libraries of TCR sequences and cognate epitopes as input for machine learning and predict specificity from sequence alone. Most methods generally do not perform very well, especially in the case of unseen peptides, i.e. for cases where peptides were not part of the input library. Methods: Here we describe three independent but interacting in-silico modules for TCR discovery. 1) The first module predicts specificity from deep phenotypic T cell profiles. We produce these profiles using a high-throughput pipeline, which combines multiplexed CyTOF with subsequent VDJ CITE-Seq. The generated multiomics data is aggregated into a database called TCAPS, which is the basis for machine learning models. These models can predict T cell specificity from the deep phenotype alone, i.e. without TCR sequence information. The resolution however is limited to the target class and hence the actual epitope has to be determined through subsequent deorphanization. This deorphanization step is augmented by the other two modules also described here. 2) The second module enables ultrafast sequence similarity search, which is used to find similar TCRs with known epitope specificity 3) The third module ranks TCR candidates for prioritisation for in-vitro validation. This is achieved by running the Alphafold-based structure prediction program TCRDock. Results: 1) We demonstrate how TCR specificity can be correctly predicted from multiomics deep T-cell profiles and specifically highlight two in-vitro validated predictions, for which the corresponding epitope/antigen were not part of the input panel. 2) Using a recently published TCR clustering benchmark TCRScapes, we demonstrate the superior performance of our ultrafast sequence similarity search. 3) We furthermore showcase TCRdock-directed experiments on TCRs specific for SF3B1mut-induced splice variants. TCRdock correctly ranked TCR candidates, including artificial combinations, whose functionality we prove through in-vitro validation. Conclusions: We describe three modules for TCR discovery and demonstrate their utility by benchmarking and in-vitro validation of multiple predictions, including two examples against unseen epitopes/antigens. Citation Format: Andreas Wilm, Florian Schmidt, Melissa Wirawan, Manisha Cooray, Kan Xing Wu, Katja Fink, Dan MacLeod. A validated bioinformatics tool-set for predicting TCR specificity [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 3559.
Abstract 6935: Non-genetic routes of lung cancer evolution
Authors: Giovanni Ciriello, Daniele Tavernari, Marco Varrone
Journal: Cancer Research (2024)

Abstract Cancer cell plasticity underlies the progression of several solid tumors. In lung adenocarcinoma, morphological changes characterizing the transition from indolent to aggressive disease exhibit profound epigenetic and transcriptional reprogramming1. However, the extent, features, and drivers of cancer cell plasticity in the progression of human lung adenocarcinoma is still largely unexplored. Here, we assembled and analyzed a meta-cohort of 119 human lung tumors analyzed by single-cell RNA-sequencing, for a total of ~730,000 cells. Cancer cell heterogeneity was the result of differential activation of 17 transcriptional programs associated with common cancer phenotypes, such as proliferation, cell migration, and response to hypoxia, as well as alveolar lineage identity (AT2). In particular, AT2-specific expression of MHC-II was down-regulated with the progression of the disease and markedly reduced in KEAP1 and/or STK11 mutated samples, providing a rationale for the association between these mutations and immunotherapy resistance. Co-activation of transcriptional programs clustered tumor cells in 4 major cell states, which emerged with the progression of the disease. To explore spatial distribution of different cancer cell states, we generated and analyzed multiple spatial transcriptomics and proteomics lung adenocarcinoma cohorts. To this purpose we developed a new algorithm called CellCharter2. CellCharter identified distinct cancer-enriched niches within individual samples, corresponding to the cancer cell states that we discovered in the scRNA-seq cohort and exhibited specific interactions with the tumor microenvironment (TME). In particular, we identified a cancer cell state characterized by response-to-hypoxia and migratory phenotypes, which spatially segregated from highly proliferative cancer cell niches and formed specific interactions with tumor associated neutrophils. This cell state was enriched in advanced primary samples, it uniquely characterized metastatic samples, and was an independent marker of poor prognosis across multiple independent datasets. Overall, our work uncovered cell plasticity trajectories associated with the progression of lung adenocarcinoma and shed new light into the tumor-TME interactions at their origin. 1 Tavernari et al., Cancer Discovery, 20212 Varrone et al, Nat. Genetics, (in press) Citation Format: Giovanni Ciriello, Daniele Tavernari, Marco Varrone. Non-genetic routes of lung cancer evolution [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 6935.