bluuebunny/crossref_metadata_2025 huggingface dataset:
Abstract 3175: Dear ABBIE, edit that colon cancer
Authors: Aguilar David C. , Gallegos Alfred
Published: March 2024

Genome editing has exciting potential for gene therapy of cancers. Colorectal cancer is the third most occurring cancer in both men and women. The current treatments for colon cancers include surgery, radiofrequency ablation, chemotherapies and immunotherapies. These either involve removal of intestinal tissue that can alter the quality of life of the patient, or require doses of drugs that generally result in various side effects. ABBIE (A Binding Based Integrase Enzyme) genome editing can insert operational gene sequences into a chosen site in the genomic DNA of cells via its targetability and integrase activity. The ABBIE system offers ease of use, faster time to a readout and decreased time per genome editing experiment. SW480 and Caco-2 colon adenocarcinoma cells were used with the ABBIE system to integrate a GFP donor sequence into a safe harbor locus of the genome. Integration is to be confirmed with fluorescence microscopy and DNA sequencing. The colon cancer cell line will then be edited with the ABBIE genome editing system to include a gene cassette that overexpresses caspase genes into the genomic DNA of these cells. ABBIE-Edited colon cancer cell lines are expected to exhibit increased apoptosis as compared to non-edited controls or controls edited with DNA that do not have the caspase genes. This strategy will help lead to novel and more targetable treatments for colon cancer.

Citation Format: David C. Aguilar, Alfred Gallegos. Dear ABBIE, edit that colon 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 3175.
Abstract 3202: Investigating the induction of ferroptosis by nano drug delivery system
Authors: Jacob Eden M. , Kim Sarah Y. , Sirohi Parul , Wang Mu-En , Davis Meredith L. , Bawcom Alyssa R. , Chilkoti Ashutosh , Wiesner Mark R. , Huang Jiaoti , Chen Ming
Published: March 2024

Prostate cancer is the second leading cause of cancer-related death in U.S. men. Genomic and clinical associations have identified loss of RB function as a dominant mechanism driving prostate cancer lethality. We recently demonstrated that ferroptosis induction in vivo by ferroptosis inducers blocks RB1-deficient prostate tumor growth and metastasis and leads to improved survival of the mice. As all ferroptosis inducers are newly discovered, there is a great need to improve their therapeutic potential through different avenues, including innovative drug delivery systems. Poly Lactic-co-glycolic acid (PLGA) is an FDA-approved biodegradable polymer. Due to their strong biocompatibility and consistent release, PLGA-based nanotherapeutics are an attractive carrier for small molecule drugs. This study aims to further improve the efficacy of ferroptosis induction against lethal RB1-deficient prostate cancer through PLGA-based ferroptosis-induced nanoparticles (NPs). The PLGA NPs encapsulating JKE-1674 were synthesized using the solvent evaporation method. The NPs were characterized using dynamic light scattering (DLS) and scanning electron microscopy (SEM) to assess the physicochemical properties of the NPs. The cell-killing efficacy of free-form or PLGA NP encapsulated JKE-1674 was then evaluated in vitro. Our analyses showed that the particle size and polydispersity index (PDI) of JKE-1674 PLGA NPs were 160.8 nm and 0.049, respectively. SEM images of JKE-1674 PLGA NPs further validated the DLS data. These findings suggest that encapsulation of JKE-1674 within the PLGA NPs results in a stable and biocompatible formation. Critically, JKE-1674 encapsulated by PLGA NPs is as potent as JKE-1674 in its free form to induce ferroptosis and associated lipid peroxidation in various human prostate cancer cell lines. This study presents the first effort to develop and validate PLGA-based ferroptosis-induced nanotherapeutics. Based on our in vitro data, we will test the in vivo efficacy of JKE-1674 PLGA NPs against lethal RB1 deficient prostate cancer.

Citation Format: Eden M. Jacob, Sarah Y. Kim, Parul Sirohi, Mu-En Wang, Meredith L. Davis, Alyssa R. Bawcom, Ashutosh Chilkoti, Mark R. Wiesner, Jiaoti Huang, Ming Chen. Investigating the induction of ferroptosis by nano drug delivery 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 3202.
Abstract 3209: Antibody mediated targeted drug delivery approach for pancreatic cancer
Authors: Dan Nirnoy , Setua Saini , Shaji Poornima , Kumari Sonam , Yallapu Murali Mohan , Khan Sheema S. , Chauhan Subhash
Published: March 2024

Pancreatic ductal adenocarcinomas, originating from the epithelial cell lining of ducts, account for approximately 95% of tumors in this category, showcasing a survival rate of less than 5-7%. Unfortunately, little progress has been seen in the outcomes of patients with PDAC as tumor develops high desmoplasia and chemo-resistance to chemotherapeutic drugs, such as gemcitabine (Gem). The therapies are unable to penetrate to the fibrotic tumors leading to insufficient availability of the therapeutic drugs at the tumor site. We and others have shown that MUC13 is aberrantly expressed in pancreatic tumors but not in normal pancreas, which makes MUC13 as an excellent protein for specifically targeting pancreatic tumors. Herein, we demonstrate a unique ability of our in-house generated mouse and humanized monoclonal antibody of MUC13 to penetrate and target pancreatic cancer. These antibodies have been conjugated with our recently developed novel patented superparamagnetic iron oxide nanoparticles (SPIONS) to deliver therapeutics specifically to pancreatic tumors. In this study, we are using curcumin that depletes tumor microenvironment and gemcitabine to investigate the efficacy of the MUC13 conjugated SPION in delivery of therapeutic drugs. Our results demonstrate that enhanced uptake of MUC13-SPION formulation in MUC13 positive (MUC13+) PanCa cells, compared with MUC13 null (MUC13-) cells as demonstrated by immunofluorescence, Prussian blue staining and flow cytometry experiments. Interestingly, the formulation resulted in sustained delivery of curcumin (CUR), enhanced inhibition of cell proliferation, migration and invasion in MUC13+ cells as compared with MUC13- cells, which suggests the targeting efficacy of the formulation. In PanCa orthotopic mice model, MUC13-SPION efficiently targeted pancreatic tumors resulting in significant tumor accumulation. We observed inhibition of tumor volume, metastasis, gem resistance and improved survival in mice treated with the formulation. Additionally, the tumor tissues from treated mice showed extensive downregulation of PCNA and expression of key proteins in SHH pathway, such as SHH, Gli-1, Gli-2, Patched 1, SMO, which has been associated with cancer progression and drug resistance. In conclusion, the results indicate high therapeutic significance of MUC13-SPIONS for achieving pancreatic tumor specific delivery of drugs.

Citation Format: Nirnoy Dan, Saini Setua, Poornima Shaji, Sonam Kumari, Murali Mohan Yallapu, Sheema S. Khan, Subhash Chauhan. Antibody mediated targeted drug delivery approach 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 3209.
Abstract 3264: Characterization of EGFR ectodomain mutation in acquired resistance to cetuximab in colorectal cancer
Authors: Joshi Neeraj , Deal Ramona Graves , Bogatcheva Galina , Higginbotham James N. , Ramirez Marisol , Brown Benjamin P. , Liu Qi , Meiler Jens , Singh Bhuminder
Published: March 2024

Colorectal cancer (CRC) remains the second leading cause of cancer-related deaths in the United States (US). Individuals with surgically unresectable stage four CRC have a five-year overall survival rate of 13%. Targeting of the receptor tyrosine kinase (RTK), EGF receptor (EGFR) with therapeutic monoclonal antibodies (cetuximab, panitumumab) is approved for use in wild-type (WT) KRAS/NRAS/BRAF (RAS/RAF) advanced CRC. However, these antibodies as a single agent have response rates of 12-17% and expected progression-free survivals of only 3-4 months. Accordingly, resistance may be present at the outset (de novo resistance) or develop during treatment (acquired resistance). Here, we report the identification of an EGFR ectodomain missense mutation acquired in vitro in response to treatment with anti-epidermal growth factor receptor (EGFR) antibody cetuximab. Using 2D and 3D drug sensitivity assays, our results demonstrate that this EGFR ectodomain mutation in addition to being resistant to cetuximab and panitumumab, also could not be targeted by the oligoclonal antibody cocktail MM-151. To determine whether this EGFR ectodomain mutation is necessary and sufficient to impart cetuximab resistance, we engineered CRC lines to inducibly overexpress mutant EGFR and showed that this was sufficient to induce cetuximab resistance. Further structural, and functional characterization is underway for this ectodomain mutation that confers resistance to cetuximab and will be shared during the meeting. These findings necessitate the need for additional treatment strategies for a subset of subjects with mCRC who do not respond to treatment with cetuximab/panitumumab and MM-151.

Citation Format: Neeraj Joshi, Ramona Graves Deal, Galina Bogatcheva, James N. Higginbotham, Marisol Ramirez, Benjamin P. Brown, Qi Liu, Jens Meiler, Bhuminder Singh. Characterization of EGFR ectodomain mutation in acquired resistance to cetuximab in colorectal 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 3264.
Abstract 33: Revitalizing CAR-T cells for TNBC: Targeting phosphorylation of TCF7 to overcome T cell exhaustion
Authors: Jiang Zhou , Chu Yu-Yi , Lee Heng-Huan , Hung Mien-Chie , Yang Liuqing , Lin Chunru
Published: March 2024

Breast cancer stands as the second leading cause of cancer-related deaths among women in the United States, with triple-negative breast cancer (TNBC) representing the most aggressive subtype. Although immune checkpoint inhibitors (ICI) demonstrated durable response in some TNBC patients, the added benefit of current FDA-approved ICI in combination with chemotherapy is estimated to be only around 10%. Fortunately, TNBC displays the highest number of tumor-infiltrating lymphocytes (TILs), compared to other BC subtypes, indicating an optimal context for the survival of T cells. Therefore, CAR-T therapy emerges as a promising therapeutic option for TNBC patients. Expanding the application of CAR-T therapies to solid tumors, including breast cancer, remains challenging. One of the key hurdles lies in the immunosuppressive tumor microenvironment, where the T cell receptor experiences long-term exposure to tumor antigens, leading to T cell exhaustion. This state impedes the T cells' capacity to efficiently target and eliminate cancer cells. Identifying key regulatory mechanisms downstream of the T cell receptor holds the potential to revolutionize existing immunotherapeutic strategies.

In our study, we discovered that the presence of the master transcriptional factor of T cell stemness, TCF1, in CD8+ T cells, is essential for controlling TNBC tumors. TCF1 undergoes phosphorylation by LCK, a crucial component of initiating T cell receptor signaling, upon T cell activation. We found this phosphorylation site is indispensable for TCF1's transcriptional activities, inhibiting the downstream program of T-cell persistence and causing T-cell exhaustion. Reversing this process, either through LCK inhibition or introducing a non-phosphorylated form of TCF1, results in a more sustained CAR-T cell-mediated anti-tumor response. Our findings reveal the significance of TCF1 post-translational modification in the development and longevity of stem-like CD8+ T cells, bridging the gap between TCR signaling and transcriptional and epigenetic programs of stem-like CD8+ T cells. This insight contributes to a potential cure for TNBC by maintaining T cell persistence.

Citation Format: Zhou Jiang, Yu-Yi Chu, Heng-Huan Lee, Mien-Chie Hung, Liuqing Yang, Chunru Lin. Revitalizing CAR-T cells for TNBC: Targeting phosphorylation of TCF7 to overcome T cell exhaustion [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 33.
Abstract 3353: The emerging role of extracellular HSP90 in prostate cancer progression to a metastatic phenotype
Authors: O'Neill Katelyn , Zigmond Johnny , Bergan Raymond
Published: March 2024

Background: Metastasis is the central cause of lethal prostate cancer (PCa). Mechanisms regulating metastasis represent high-potential therapeutic targets for preventing development of lethal PCa. Inhibitors of extracellular heat shock protein 90 (eHSP90) have been shown to inhibit prostate cell motility. In contrast to the intracellular HSP90 (iHSP90), whose biology has been extensively studied, and whose therapeutic targeting is associated with systemic toxicity, the biology of extracellular HSP90 is not well understood. We undertook a series of investigations to better understand eHSP90 biology in PCa.

Methods: Human PCa cells were subjected to cellular stress by heat shock combined with serum starvation. Resultant conditioned media was probed for matrix metalloproteinase 2 (MMP-2) by zymography and subject to scratch-wound and Boyden chamber invasion assays. Expression of HSP90 and CDC37 was measured by Western blot. Plasma from patients with PCa and healthy controls was probed for eHSP90 by ELISA.

Results: We have examined expression of iHSP90 and eHSP90 after cellular stress, induced by heat shock and serum starvation, in human PC3, LNCaP, C4-2B, 1532NPTX and 1532CPTX PCa cell lines. Cell stress induces increased eHSP90 in all PCa cell lines examined. This is associated with a decrease in MMP-2 activity in conditioned media. Conditioned media from stressed cells was also shown to decrease invasion of PC3 cells, consistent with changes in MMP-2. Of high interest, the addition of protease inhibitors to conditioned media led to a complete reversal of the MMP-2 response: its activity increased with cellular stress. When measuring HSP90α in plasma from healthy controls (N = 20) and patients with PCa (N = 40, 20 localized and 20 metastatic), we demonstrated a significant (p=.001) >2 fold increase in PCa compared to control. Further, a significant increase in HSP90α was observed when low versus high T stage lesions were compared. There was no statistically significant difference in HSP90α for those with metastasis to regional lymph nodes, non-regional lymph nodes, bone, or liver.

Conclusion: We demonstrate that increased eHSP90 due to cellular stress is a response observed across all PCa cell lines examined and should be considered typical. Its association with extracellular MMP-2 activity is dependent on the presence of other proteases and indicates a complex regulatory mechanism. Examination of eHSP90 in humans supports its association with aggressive disease. These factors support further investigation of underlying biology and therapeutic opportunities.

Citation Format: Katelyn O'Neill, Johnny Zigmond, Raymond Bergan. The emerging role of extracellular HSP90 in prostate cancer progression to a metastatic phenotype [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 3353.
Abstract 3367: R-loop type determines the orientation of transcription-replication conflicts attenuated by transcription factor IIS
Authors: Duardo Renée C. , Marinello Jessica , Russo Marco , Morelli Sara , Pepe Simona , Guerra Federico , Gomez-González Belen , Aguilera Andrés , Capranico Giovanni
Published: March 2024

During human Topoisomerase I (Top1) catalytic activity, a transient Top1-DNA cleavage complex (Top1cc) forms to allow DNA relaxation. Top1ccs can be stabilized by antitumor Top1 poisons, such as clinically-effective camptothecin analogs. Camptothecin-stabilized Top1ccs can lead to R-loop-dependent transcription-replication conflicts (TRCs), single-end DNA double-strand breaks (seDSBs) and genome instability in cancer cells. To define the genomic location of TRCs and the underlying mechanisms, we integrated genomic maps of Top1cc-induced DNA cleavage by END-seq and DNA:RNA hybrids by DRIP, determined the cell-cycle specificity of micronuclei formation and the effects of elongation transcription factor IIS (TFIIS). We have defined the genomic sites of both seDSBs and increased R-loop levels (gains) induced by Top1ccs. seDSBs are highly enriched at regions with R-loop gains at highly-transcribed genes in early replicating zones. Kinetics analyses of R-loops and genomic ChIP data of RNA polymerase II (RNAPII) revealed that R-loop gains can either be upstream or downstream of RNAPII. TFIIS effects showed that downstream R-loop gains can follow RNAPII backtracking and arrest. seDSB strandness showed that co-directional TRCs occur mainly at downstream hybrid-associated RNAPII, whereas head-on TRCs occur mainly at upstream hybrid-associated RNAPII. Therefore, Top1ccs can increase two structurally-different R-loops and R-loop-associated backtracked RNAPII causes co-directional TRCs at higher rate than head-on collisions. Moreover, Top1ccs trigger micronuclei formation at G1/early S, but not late S/G2, which are attenuated by TFIIS. Thus, our findings establish a role of RNAPII backtracking at highly-transcribed genes in Top1cc-induced co-directional TRCs and micronuclei formation. The findings can accelerate the development of new effective strategies to treat cancer patients. (Supported by Associazione Italiana per la Ricerca sul Cancro, Milan, Italy - IG 2019 - ID. 23032 to C.G. and by the European Union - NextGenerationEU through the Italian Ministry of University and Research under PNRR - M4C2-I1.3 Project PE_00000019 "HEAL ITALIA" to G.C., CUP J33C22002920006).

Citation Format: Renée C. Duardo, Jessica Marinello, Marco Russo, Sara Morelli, Simona Pepe, Federico Guerra, Belen Gomez-González, Andrés Aguilera, Giovanni Capranico. R-loop type determines the orientation of transcription-replication conflicts attenuated by transcription factor IIS [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 3367.
Abstract 3407: Physical activity and post-menopausal breast cancer in the Multiethnic Cohort Study
Authors: Gill Jasmeet K. , Maskarinec Gertraud , Park Song-Yi , Wilkens Lynne , Marchand Loic Le
Published: March 2024

Much research has been conducted on the relationship between physical activity and breast cancer, with meta-analyses showing 10 – 21% reduction in breast cancer risk for postmenopausal women with high compared to low level of physical activity. However, few studies have explored this relationship in non-Caucasian women. We analyzed data from 74,177 post-menopausal African American, Caucasian, Japanese American, Latina, and Native Hawaiian women in the Multiethnic Cohort in Hawaii and California. Data on physical activity (hours and metabolic equivalents (METs)) was based on a self-administered questionnaire at baseline (1993–1996). Multivariate Cox proportional hazards models provided estimates of hazard ratios (HRs) and 95% confidence intervals (CIs) adjusted for risk factors. We observed no associations between breast cancer risk and hours of moderate/vigorous activity per week (HR=1.01, 95% CI: 0.91-1.10, Ptrend=0.71), MET-hours of moderate/vigorous activity per week (HR=1.03, 95% CI: 0.94-1.13, Ptrend=0.92), and total METs-measured as average MET level per day multiplied by 7 (HR=0.94, 95% CI: 0.86-1.03, Ptrend=0.37) when comparing the highest quartile to the lowest. When examining the data across race/ethnicity, we observed a reduction in risk of breast cancer for total METs (HR=0.75, 95% CI: 0.61-0.94, Ptrend=0.05) among Latina women. Analysis across strata of BMI showed no differences across subgroups. In this study, we did not observe any consistent protective association between physical activity and breast cancer risk.

Citation Format: Jasmeet K. Gill, Gertraud Maskarinec, Song-Yi Park, Lynne Wilkens, Loic Le Marchand. Physical activity and post-menopausal breast cancer in the Multiethnic Cohort Study [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 3407.
Abstract 3454: Cell-free DNA methylation and fragmentomic signatures identify tissue damage and predict cancer risk
Authors: Cheng Nicholas , Skead Kimberly , Oullette Tom , Bratman Scott , De Carvalho Daniel , Soave David , Awadalla Philip
Published: March 2024

Cell-free DNA (cfDNA) epigenetic and fragmentomic profiling has emerged as prominent non-invasive approaches for early cancer detection and subtyping. However, owing to difficulties in observing the early development of human malignancies, most cancer biomarker and evolution studies to date have primarily examined biologics following a diagnosis. Utilizing cfDNA as a screening tool for early disease detection requires assessment of blood plasma samples collected from asymptomatic individuals prior to the diagnosis of cancers. Here, we leverage the Ontario Health Study (OHS), a prospective longitudinal population cohort, to assess cfDNA profiles in blood plasma collected from participants that developed breast (n=476), prostate (n=342) and pancreatic (n=32) cancers throughout the study follow up time between 2009 and 2019. We performed cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq) on baseline plasma samples from incident cancer cases up to eight years prior to diagnosis, in addition to matched controls (n=404) with no history of cancer through follow-up. Genome-wide plasma cfDNA differential methylation analysis revealed significantly hypermethylated regions, particularly among CpG island and shore regions, were predictive of early breast cancers, and overlapped hypermethylated regions in solid cancer tissues relative to adjacent normal tissues and peripheral blood leukocytes. Using a repeated cross-validation strategy we found that as few as 200 hypermethylated regions can identify individuals with breast cancer in blood up to seven years prior to diagnosis among discovery set samples (AUC=0.725) and are highly generalizable to samples processed in separate batches (AUC = 0.650). Remarkably, integrating biomarker hypermethylated regions with fragmentomic features including fragment length and 5’ tetranucleotide motif proportions further increased accuracy for detecting individuals with early prostate cancers (AUC=0.804). In addition, we observed shared genome-wide cfDNA methylome changes associated with aging and heavy alcohol consumption in cfDNA. We identified increased shedding of tissue-specific methylation markers from liver and pancreatic tissue among individuals consuming more than three drinks a week relative to non-drinkers, reflective of potential signatures of tissue damage.

Citation Format: Nicholas Cheng, Kimberly Skead, Tom Oullette, Scott Bratman, Daniel De Carvalho, David Soave, Philip Awadalla. Cell-free DNA methylation and fragmentomic signatures identify tissue damage and predict cancer risk [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 3454.
Abstract 3500: Refining diagnosis of renal cell carcinoma subtypes through single-cell resolution transcriptomic signatures
Authors: Kim Minjun , Madrigal Ariel , Mehrjoo Zohreh , Glennon Kate I. , Arseneault Madeleine , Park Morag , Brimo Fadi , Tanguay Simon , Najafabadi Hamed S. , Riazalhosseini Yasser
Published: March 2024

A remaining challenge in the field of renal cell carcinoma (RCC) is diagnosis of rare or mixed subtypes, which hampers the delivery of the most effective healthcare to patients. While a new classification scheme, integrating molecular characteristics of tumors, is emerging, it requires a deep understanding of the tumor heterogeneity and etiopathogenesis of each subtype. We have generated and analyzed single-cell transcriptome profiles of 38 human RCCs and normal kidneys 16 RCCs with diverse histological subtypes and established gene signatures specific to each cell type. We have applied these gene signatures to bulk RNA-sequencing data of 1000 RCC tumors with different histological subtypes and normal kidneys from The Cancer Genome Atlas (TCGA) to characterize different cancer types and cellular origins. Unsupervised clustering analysis of TCGA data shows diagnostic discrepancies for 9.3% cases and subclassifies each major subtype (clear cell, papillary and chromophobe) into clusters with differential clinical outcomes.[KM1]. The pathological marker expression in misdiagnosed tumors is consistent with clustering-based classification, not their original diagnosis. Notably, using unique and subtype-specific gene signature patterns, we identified clear cell papillary renal cell tumor (ccpRCT), which is a newly classified benign entity and the main tumor type representing the mis-diagnosed tumors. These observations have further been confirmed by reviewing histological images of the tumors by an experienced genitourinary pathologist. Interestingly, our gene signatures reveal that ccpRCT does not originate from proximal tubule cells unlike clear cell and papillary RCCs. Taken together, our approach suggests a potential new classification method connected to clinical behaviors and drug responses based on overall transcriptomic differences.

Citation Format: Minjun Kim, Ariel Madrigal, Zohreh Mehrjoo, Kate I. Glennon, Madeleine Arseneault, Morag Park, Fadi Brimo, Simon Tanguay, Hamed S. Najafabadi, Yasser Riazalhosseini. Refining diagnosis of renal cell carcinoma subtypes through single-cell resolution transcriptomic signatures [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 3500.
Abstract 3505: Classification of cancer subtypes by cfDNA fragmentomics analysis
Authors: Zhu Lisha , Dai Chao , Gan Shuang , Jia Shidong , Du Pan
Published: March 2024

Introduction Fragmentation patterns of cell-free DNA (cfDNA) from whole genome sequencing offer insights into nucleosome occupancy, providing a tool to infer epigenomic and transcriptomic information. The nucleosome complex, the primary protector of cfDNA, is reflected in the size distribution of cfDNA fragments, with a mode fragment size of 167 bp corresponding to the wrapping of DNA around a single nucleosome. Nucleosome occupancy patterns at transcription factor binding sites (TFBS) exhibit differences between circulating tumor DNA in cancer patients and normal plasma controls, as well as among different tumor subtypes. Therefore, cfDNA fragmentomics can be employed for cancer subtyping analysis.

Methods We utilized the Griffin framework to classify tumor subtypes based on nucleosome profiling of cancer-specific TFBS and tumor subtype-specific chromatin accessibility regions from low-pass whole genome sequencing data of cfDNA. For prostate cancer subtyping, AR and ASCL1 binding sites were used to distinguish between androgen receptor-dependent prostate cancer (ARPC) and neuroendocrine prostate cancer (NEPC). ER and ERBB2 were employed for breast cancer subtyping to differentiate between ER-positive and ER-negative tumor subtypes.

Results Nucleosome profiling patterns at AR binding sites (ARBS) were compared among over 500 prostate cancer plasma samples and 42 normal plasma backgrounds. The ARBS nucleosome profiling abnormality score (ARBS score) was quantified by comparing its GC-corrected fragment central coverage with the normal background using a standard Z-score.Majority of prostate cancer samples with a high ARBS score could be classified as ARPC. For 12 samples with high tumor fraction but low ARBS score and no AR copy number amplification, we found that 8 had a high ASCL1 nucleosome profiling abnormality score. All these samples also exhibited RB1 copy number loss, suggesting that these 8 samples likely belong to NEPC. Nucleosome profiling of 171 breast cancer plasma samples at breast cancer-specific ER binding sites revealed that majority of samples had a high ERBS abnormality score, indicating likely ER-positive breast cancer.

Conclusion Our results demonstrate that nucleosome profiling of tumor cfDNA exhibits distinct patterns across different tumor types. Integrating nucleosome profiling at cancer-specific transcription factor binding sites can facilitate cancer subtyping, highlighting its potential clinical utility for patient stratification.

Citation Format: Lisha Zhu, Chao Dai, Shuang Gan, Shidong Jia, Pan Du. Classification of cancer subtypes by cfDNA fragmentomics analysis [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 3505.
Abstract 3522: Application of large language models to nucleotide sequences for profiling signaling pathway disruptions in ovarian cancer patients
Authors: Chebanov Dmitrii K. , Tatevosova Nadezhda S.
Published: March 2024

Ovarian cancer is a challenging disease, often exhibiting recurrence after initial treatment. The complexity arises from simultaneous disruptions in multiple signaling pathways within tumor cells, rendering targeted inhibitors ineffective in providing sustained therapeutic impact. While targeted sequencing panels can identify specific therapeutically relevant events, they often fail to capture the complete picture of targetable tumor driving aberrations, and provide biomarkers relevant to disease resistance and/or recurrence. A potential solution lies in comprehensively defining the landscape of signaling pathway alterations by identifying molecular triggers underlying their dysregulation. While individual DNA mutations sometimes may not lead to carcinogenesis or changes in tumor cell behavior, combination of deactivating mutations in suppressor genes, can influence tumor development and prognosis, warranting a comprehensive delineation of their effect on the broad signaling network level. To this end, we propose the Large Language Models (LLMs), which have been successful in natural language processing, particularly in understanding context. Such tools are essential for discerning the effect of mutation combinations, their physical proximity to other mutations, and functional gene regions. We obtained mutation annotation files for 177 ovarian cancer patients from the TCGA database, reconstructing consensus nucleotide sequences using a reference genome. To input this data into LLMs, we generated embeddings for these sequences using the Nucleotide Transformer algorithm, pre-trained on 500 million variants of the reference genome. Additionally, we extracted data on detected disruptions in 10 signaling pathways (Cell Cycle, HIPPO, MYC, NOTCH, NRF2, PI3K, RTK RAS, TP53, TGF-Beta, WNT) for these patients from TCGA. Each pathway was associated with the percentage of its alteration. We trained a deep learning algorithm on these data to predict a combination of 10 numerical values, each corresponding to the percentage of disruption for a given signaling pathway. Our findings revealed that nearly half of the patients exhibited disruptions in 5 or more signaling pathways. The algorithm developed enables the determination of the extent of disruption in each pathway based on whole exome sequencing results. This approach facilitates more informed treatment strategy planning and enhances the efficient development of new drugs for ovarian cancer treatment.

Citation Format: Dmitrii K. Chebanov, Nadezhda S. Tatevosova. Application of large language models to nucleotide sequences for profiling signaling pathway disruptions in ovarian cancer 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 3522.
Abstract 3528: Constructing knowledge graph of N6-methyladnosion regulations in cancer from literature using ChatGPT-4
Authors: Jo Sumin , Wu Xidong , Zeng Yiming , Das Arun , Zhang Ting-He , Spellman David Alexander , Ferris Adam , Gao Shou-Jiang , Zhang Jianqiu (Michelle) , Chiu Yu-Chiao , Huang Yufei
Published: March 2024

N6-methyladenosine (m6A) is the most abundant mRNA modification with a crucial role in cellular processes. Its involvement in cancers is well-established. Dysregulation of m6A is linked to cancer initiation, progression, and therapy resistance, impacting the tumor microenvironment (TME) and promoting metastasis. Understanding m6A's regulatory role in cancer is essential for identifying new therapeutic targets. We considered the construction of a knowledge graph (KG) representing molecular regulatory mechanisms (MRMs) of m6A in healthy conditions and different cancers from PubMed papers. Such a KG consists of interconnected triplets of (head node, regulatory relationship, tail node), each denoting regulation between genes or a gene and a phenotype/process. Advances in natural language processing (NLP) have provided tools such as SemRep and GNBR to automate the extraction of these triplets from the literature. However, these methods don’t extract contextual information, such as the type of cancers or cells in which these MRMs occur, leading to contradictory regulations in the constructed KG. In addition, existing approaches were designed to extract generic regulatory relations and therefore struggled in properly capturing unique concepts associated with m6A regulatory mechanisms. To tackle this challenge, we designed a novel ChatGPT-4 prompt to extract relational graphs from papers tailored for m6A regulatory mechanisms. An annotated dataset of 400 titles on m6A-related MRMs were created to evaluate the performance. We then applied the prompt to 1023 papers to create a m6A Molecular Regulatory Mechanism Knowledge Graph (m6A-MRM-KG). This graph illuminates m6A's roles in gene expression regulation, especially in cancer and immunity. Anticipated to enhance our understanding of cancer development, it provides insights into potential therapeutic strategies. The m6A-MRM-KG not only organizes information but also empowers researchers to uncover novel insights in the dynamic relationships of m6A modifications in diverse biological contexts.

Citation Format: Sumin Jo, Xidong Wu, Yiming Zeng, Arun Das, Ting-He Zhang, David Alexander Spellman, Adam Ferris, Shou-Jiang Gao, Jianqiu (Michelle) Zhang, Yu-Chiao Chiu, Yufei Huang. Constructing knowledge graph of N6-methyladnosion regulations in cancer from literature using ChatGPT-4 [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 3528.
Abstract 3536: Paracell: A high throughput, deep learning-based pipeline for single-cell phenotypic profiling
Authors: Nguyen David L. , Chao Jesse T.
Published: March 2024

Variants of uncertain significance constitute the vast majority of missense variants, hampering the utility of genetic testing, despite its remarkable impacts on clinical diagnosis and decision-making. Although the sequencing and interpretation of genetic variants have been drastically improved in recent years, only about 2% of novel missense variants are currently clinically actionable. Therefore, a robust and scalable pipeline is desperately needed to provide functional evidence critical for variant interpretation. In this work, we demonstrate Paracell, a deep learning-based phenotypic profiling pipeline that leverages subcellular segmentation, high-dimensional single-cell phenotyping, and machine learning to classify the functional impact of variants. Paracell captures heterogeneity in cellular phenotypes and protein colocalization between variants and their signaling partners, as well as subcellular markers, and enables analysis at a single-cell resolution. Using a classification model trained on single-cell features extracted by Paracell, we were able to accurately classify cells from loss-of-function (LoF) variants based on their impact. After aggregating cellular profiles on a variant level, our pipeline was able to distinguish LoF variants from functional ones with high sensitivity and specificity. Our work demonstrates that Paracell is a robust and scalable method that can sensitively detect differences in single-cell phenotypic profiles. The systematic application of this pipeline will provide valuable functional evidence for variant interpretation, enhancing their clinical utility and accelerating personalized cancer care.

Citation Format: David L. Nguyen, Jesse T. Chao. Paracell: A high throughput, deep learning-based pipeline for single-cell phenotypic profiling [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 3536.
Abstract 3559: A validated bioinformatics tool-set for predicting TCR specificity
Authors: Wilm Andreas , Schmidt Florian , Wirawan Melissa , Cooray Manisha , Wu Kan Xing , Fink Katja , MacLeod Dan
Published: March 2024

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 360: Dissecting the role of oncogenic KRAS and ferroptosis within colorectal cancer
Authors: Rosa-Vázquez Alexandra , Bernard-Pagan Vincent , Chen Jasper , Taniguchi Cullen
Published: March 2024

Introduction: Ferroptosis is a novel iron-dependent regulated cell death mechanism triggered by a toxic accumulation of membrane lipid peroxidation. This mechanism is counteracted by ferroptosis defense systems, such as the GPX4/GSH system, which function as antioxidants that limit lipid peroxidation. Oncogenic KRAS (KRASmut) is a key driver for many aggressive cancers, including colorectal cancer (CRC). Previous studies have suggested that oncogenic KRAS plays a pleiotropic role in the ferroptosis pathway. Yet, the interplay between oncogenic KRAS and ferroptosis has not been fully elucidated in CRC. Here, we aimed to dissect the role of oncogenic KRAS in ferroptosis using CRC as a cancer model.

Methods: Cells from a KRAS-inducible model (iKAP) were seeded and treated with ferroptosis-inducing drugs (e.g., Erastin and RSL3) and/or a KRAS inhibitor (MRTX1133). Lipid peroxidation was then measured by BODIPY assay followed by flow cytometry to detect the quantity of BODIPY-stained cells. Protein expression of known ferroptosis defense mechanisms was also profiled (e.g., SLC7A11 [xCT] and GPX4).

Results: Results from this study demonstrate that KRASmut activation leads to a reduction in mean fluorescence intensity when compared to KRASWT of BODIPY-stained cells. This decreased mean fluorescence intensity is indicative of lower levels of lipid peroxidation and, consequently, ferroptosis. KRASmut cells were also found to be resistant to ferroptosis following treatment with ferroptosis inducers. To replicate a pharmacologically induced KRASWT phenotype, iKAP cells were treated with MRTX1133, which led to a significant decrease in viability when combined with RSL3. We observed a decreased protein expression of the membrane antiporter xCT following treatment with MRTX1133, which we believe works synergistically with the GPX4 inhibition of RSL3.

Conclusion: We observed that KRASmut may induce resistance to ferroptosis in vitro in CRC cells. Genetic and pharmacological inhibition of KRAS resulted in sensitization to ferroptosis inducers. Future work will uncover mechanisms through which oncogenic KRAS leads to ferroptosis resistance in CRC. More importantly, understanding the interaction between ferroptosis, oncogenic KRAS, and its antagonist systems has significant therapeutic potential in oncology.

Citation Format: Alexandra Rosa-Vázquez, Vincent Bernard-Pagan, Jasper Chen, Cullen Taniguchi. Dissecting the role of oncogenic KRAS and ferroptosis within colorectal 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 360.
Abstract 3710: Determining the efficacy of blood filtration in patients diagnosed with pancreatic cancer through the liquid biopsy
Authors: Suresh Divya D. , Courcoubetis George , Lin Emmeline , Mason Jeremy , Nissen Nicholas , Gaddam Srinivas , Lo Simon , Pandol Stephen , Kuhn Peter , Shishido Stephanie
Published: March 2024

Cancer becomes lethal as it spreads from the primary site to the rest of the body. Circulating tumor cells (CTCs) are considered a marker of disease progression and have been associated with decreased overall survival. Blood filtration is one such method of removing cancer cells from circulation to improve patient prognosis. This study utilizes the liquid biopsy to assess the efficacy of a proprietary filtration device on the blood of patients with pancreatic ductal adenocarcinoma (PDAC) using the third generation high-definition single cell assay (HDSCA3.0) workflow. Blood samples were collected and analyzed to characterize the CTCs and other rare cells present before and after filtration. Examination of 6 paired portal (PoVB) samples demonstrated a statistically significant decrease in total rare cells, total CK+ cells, and epi.CTCs across all patients due to filtration of the blood. Furthermore, analysis of 2 paired peripheral blood (PB) samples showed a decrease in total rare cells, total CK+ cells, and specific phenotypes of rare cells upon filtration. These preliminary results demonstrate initial proof of concept that this filtration device can remove CTCs from the circulation, which may be used as a potential therapeutic device for PDAC patient care.

Citation Format: Divya D. Suresh, George Courcoubetis, Emmeline Lin, Jeremy Mason, Nicholas Nissen, Srinivas Gaddam, Simon Lo, Stephen Pandol, Peter Kuhn, Stephanie Shishido. Determining the efficacy of blood filtration in patients diagnosed with pancreatic cancer through the liquid biopsy [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 3710.