bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract 7193: ABCB1-mediated chemotherapeutic drug resistance is reversed by a potent p53-MDM2 inhibitor NVP-HDM201
Authors: Patel Harsh , Cai Chaoyun , Wu Zhuoxun , Teng Qiuxu , Li Hanli , Chen Zhe-Sheng 
Published: March 2024

Abstract
The failure of chemotherapy in cancer persists as a result of overexpression of various ATP-binding cassette (ABC) transporters. ABCB1 is one such transporter that actively pumps out chemotherapeutic drugs and it is one of the reasons for multidrug resistance (MDR). In the last few years, activation of p53 has been targeted as a therapeutic strategy in the treatment of cancers. Siremadlin (NVP-HDM201) is a potent and selective inhibitor of p53-MDM2 interaction. The objective of this study was to explore the ability of HDM201 to reverse tumor MDR attributable to overexpression of ABC transporters. According to our findings, HDM201 significantly increased the sensitivity of ABCB1-overexpressing cells to ABCB1 substrates, such as colchicine and doxorubicin. We found that HDM201 reverses ABCB1-mediated MDR by interacting with ABCB1 and blocking its function without affecting the expression and cellular localization of ABCB1. Moreover, HDM201 promoted the accumulation of paclitaxel in cell lines that overexpress ABCB1. At both high and low doses, HDM201 increased the ATPase activity of ABCB1. The computational support for the cross-reactivity of this p53 inhibitor with human ABCB1 comes from docking simulation results that align with the binding conformation of HDM201 within the vast cavity of the transmembrane region of ABCB1. In conclusion, by blocking the transport function of ABCB1, HDM201 can reverse ABCB1-mediated MDR in vitro.
Citation Format: Harsh Patel, Chaoyun Cai, Zhuoxun Wu, Qiuxu Teng, Hanli Li, Zhe-Sheng Chen. ABCB1-mediated chemotherapeutic drug resistance is reversed by a potent p53-MDM2 inhibitor NVP-HDM201 [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 7193.
Abstract 720: Combining zelasudil, a small molecule ROCK2 inhibitor, with chemotherapy or immunotherapy improves response in preclinical models of pancreatic cancer
Authors: Pajic Marina , McLean Benjamin , Fajardo Diego Chacon , Porazinski Sean , Upton Dannielle H. , Schuhmacher Diana , Istadi Aji , Cox Thomas , Timpson Paul , Wilcock Daniel J. , Anderson Katie J. , Mason Helen , Guisot Nicolas E. , Jones Clifford D. , Phillips Caroline , Armer Richard 
Published: March 2024

Abstract
Zelasudil (RXC007) is an orally available, highly selective small molecule inhibitor of Rho-associated coiled-coil containing protein kinase 2 (ROCK2), which has demonstrated pre-clinical anti-fibrotic efficacy and is currently being tested in a Phase 2a clinical trial for the treatment of idiopathic pulmonary fibrosis (IPF) (NCT05570058). Pancreatic ductal adenocarcinoma (PDAC) is an aggressive and therapeutically challenging disease with a dense and highly fibrotic tumor microenvironment which may limit efficacy of conventional therapies. Here, we investigate the benefit of combining an anti-fibrotic, RXC007, with either standard of care chemotherapy or immunotherapy in mouse models of PDAC.In a fibrotic patient-derived metastatic PDAC orthotopic model, RXC007 (10mg/kg, 50mg/kg and 100mg/kg BID 5d on/2d off PO) in combination with SoC chemotherapy Gemcitabine (100mg/kg IP QW)/Abraxane (30 mg/kg IP QW) improved survival in a dose-dependent manner (all P&lt;0.0001) compared to Gemcitabine/Abraxane alone.In the immunocompetent orthotopic LSL-KrasG12D/+; LSL-Trp53R172H/+; Pdx1-Cre (KPC) model of metastatic PDAC, survival was significantly increased (P&lt;0.0001) upon treatment with a combination of RXC007 (50 mg/kg BID 5d on/2d off PO) and anti-PD1 (200 ug BIW) compared to anti-PD1 alone. ROCK2 inhibition elicited positive immunomodulatory effects in KPC pancreatic tumors, with increase of CD8+ (P=0.0031) and CD4+ (P=0.008) T cell infiltrate into the tumor cortex and reduction in immunosuppressive FOXP3+ regulatory T cells at the tumor border. Furthermore, RXC007 monotherapy exhibited anti-fibrotic effects, via a decrease in collagen content and organization, effects associated with CAF reprogramming and reduced intra-tumoral aSMA+ PDPN+ myofibroblast-like CAFs (myCAFs; P=0.0406).This data highlights the potential for treating highly fibrotic tumours with RXC007 in combination with SoC chemotherapy or immunotherapy in order to improve patient outcomes in this aggressive and treatment-refractory cancer.
Citation Format: Marina Pajic, Benjamin McLean, Diego Chacon Fajardo, Sean Porazinski, Dannielle H. Upton, Diana Schuhmacher, Aji Istadi, Thomas Cox, Paul Timpson, Daniel J. Wilcock, Katie J. Anderson, Helen Mason, Nicolas E. Guisot, Clifford D. Jones, Caroline Phillips, Richard Armer. Combining zelasudil, a small molecule ROCK2 inhibitor, with chemotherapy or immunotherapy improves response in preclinical models of 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 720.
Abstract 7254: Evaluation of scFv and diabody pseudotyped Sindbis engineered retrovectors for targeted cancer therapy
Authors: Sato Makoto , Cunha Alexander , Collins Sara , Kasahara Noriyuki , Roh Cecilia , Johnson Robert G. 
Published: March 2024

Abstract
Engineering viral vectors to target specific cells and organs after intravenous delivery remains a challenge. Transcriptional targeting with cell-specific promoters is a commonly used approach but does not change vector biodistribution. We have developed a novel gene delivery system targeted to tumor cells by pseudotyping the vector with Sindbis Virus (SB) envelope bearing an antigen-binding domain. Prototype vectors were generated by inserting a universal IgG binding domain from Protein A into the SB envelope (SB-ZZ). Antibodies (Abs) against various cell-surface targets (HLA, HER2, CD47, EGFR, Nectin-4), were conjugated to SB-ZZ vectors delivering a luciferase (Luc) reporter gene. Targeted transduction was confirmed on cells expressing the corresponding antigens by significantly higher Luc activity compared to SB-ZZ vectors without Abs. SB envelopes were further engineered by adding or removing furin cleavage sites and linkers, transduction-enhancing point mutations, and direct incorporation of single-chain variable fragment (scFv) in different VH and VL orientations, or diabody (DB) sequences, against the same targets. The specificity of optimized HER2-targeting vectors delivering the Luc reporter was evaluated in SKBR3 (HER2 over-expressing) and MDA-MB-468 (HER2-null) cells. Robust Luc activity was observed in SKBR3 cells, but only negligible activity in MDA-MB-468 cells. In MDA-MB-468 cells overexpressing HER2, significantly higher transduction was observed compared to the wild-type cells. When comparing HER2-targeting vectors with scFv vs. DB sequences based on the same antibody, transduction capability was higher with the DB motif in HER2-positive cell lines. Targeting vectors delivering HSV-eTK were also constructed, and ganciclovir (GCV)-mediated cell killing was evaluated in vitro. SKBR3 cells transduced with HER2-targeting vectors showed significantly more cell killing after GCV treatment than after transduction with an amphotropic reference vector. Our results indicate a method for directing gene therapy vectors to specific populations of tumor cells, and provide a framework for highly modular targeted gene therapy and immunotherapeutics. Experiments are underway to examine in vivo delivery of targeted vs amphotropic vectors.
Citation Format: Makoto Sato, Alexander Cunha, Sara Collins, Noriyuki Kasahara, Cecilia Roh, Robert G. Johnson. Evaluation of scFv and diabody pseudotyped Sindbis engineered retrovectors for targeted cancer therapy [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 7254.
Abstract 728: Oral TGF-beta receptor1 inhibitor vactosertib promotes osteosarcoma regression by targeting tumor proliferation and enhancing anti-tumor immunity
Authors: Choi Sung Hee , Myers Jay , Tomchuck Suzanne , Bonner Melissa , Eid Saada , Kingsley Daniel , VanHeyst Kristen , Kim Seong-Jin , Kim Byung-Gyu , Huang Alex Y. 
Published: March 2024

Abstract
Osteosarcoma (OS) is an aggressive malignant bone cancer, with the lung as the most frequent site of metastasis. Unresectable pulmonary metastasis remains a significant challenge with a survival rate of less than 20%. Identification of novel therapeutic strategies are desperately needed. Transforming growth factor-β1 (TGF-β) is a potent immune suppressive cytokine in OS tumor microenvironment (TME). TGF-β1 expression is increased in the sera and tumor tissues of OS patients and this increase is associated with high-grade OS and lung metastases. Therefore, blocking TGF-β1 signaling may be a novel therapy for OS treatment. In this study, we show that blocking TGF-β1 signaling using the orally bioavailable small molecule TGF-βR1 inhibitor, Vactosertib, significantly inhibited OS proliferation in vitro and in vivo. Notably, Vactosertib inhibits c-Myc expression in the OS cells and oral administration of Vactosertib significantly reduces OS growth in vivo. Vactosertib increased immune effectors (e.g., IFNγ+CD8+ cells and NK cells) and inhibited immune suppressors (e.g., M2-like TAM, MDSC) in the OS TME. Our results suggest that inhibition of TGF-β1 signaling is an effective therapeutic strategy against OS through a multi-pronged approach that targets tumor intrinsic and extrinsic factors to achieve optimal immune-effector functions and maximal clinical response.
Citation Format: Sung Hee Choi, Jay Myers, Suzanne Tomchuck, Melissa Bonner, Saada Eid, Daniel Kingsley, Kristen VanHeyst, Seong-Jin Kim, Byung-Gyu Kim, Alex Y. Huang. Oral TGF-beta receptor1 inhibitor vactosertib promotes osteosarcoma regression by targeting tumor proliferation and enhancing anti-tumor immunity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 728.
Abstract 7326: TP53 p.Pro47Ser polymorphism in breast cancer susceptibility in Mali
Authors: Diakite Brehima , Kassogue Yaya , Maiga Mamoudou , Kassogue Oumar , Cisse Kadidiatou , Diarra Fousseyni , Traore Cheick Traore B. , Kamate Bakarou , Holl Jane L. , Hou Lifang 
Published: March 2024

Abstract
Background: The aim of this study was to assess the potential association of p.Pro47Ser polymorphisms of TP53 with the risk of developing breast cancer in the Malian population.
Methods: We analyzed DNA samples from 72 breast cancer patients and 121 unrelated healthy, age-matched individuals to examine the presence of the polymorphisms. The genotyping of TP53 polymorphism was performed using PCR-RFLP and HRM (high-resolution melting) methods.
Results: The genotypic frequencies of PP, PS, and SS were found to be 63.9% PP, 30.6% PS, and 5.6% SS in breast cancer patients, compared to 70.2% PP, 22.3% PS, and 7.4% SS in the control group. The frequencies of P and S alleles of TP53 p.P47S polymorphism were 79.2% vs 81.4%, 20.8% vs 18.6%, and 5% vs 4.5% in patients and controls, respectively. In this study, no significant correlation was observed between TP53 p.Pro47Ser polymorphism and breast cancer in the Malian population (Pro/Ser vs Pro/Pro: OR = 1.55, 95% CI = 0.80-3.05, P = 0.19; Ser/Ser vs Pro/Pro: OR = 1.27, 95% CI = 0.34-4.74, P = 0.71; and Ser vs Pro allele: OR = 1.39, 95% CI = 0.80-2.32, P = 0.24).
Conclusion: Despite the absence of a genetic association between TP53 p.Pro47Ser and the risk of breast cancer in Malian patients, our findings suggest that individuals carrying at least one minor Ser allele are not protected against the disease.
Citation Format: Brehima Diakite, Yaya Kassogue, Mamoudou Maiga, Oumar Kassogue, Kadidiatou Cisse, Fousseyni Diarra, Cheick Traore B. Traore, Bakarou Kamate, Jane L. Holl, Lifang Hou. TP53 p.Pro47Ser polymorphism in breast cancer susceptibility in Mali [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 7326.
Abstract 7345: Double-strand break inference from mosaic chromosomal alterations
Authors: Dutch Abraham , Bumgardner Cody , Jakubek Yasminka 
Published: March 2024

Abstract
Double-strand breaks (DSBs) can cause alterations and rearrangements in chromosomes leading to large structural mutations. There have been previous efforts to identify DSBs in tumors and utilize these as a measure of homologous repair deficiency and response to therapy. In contrast, DSBs have not been well characterized in non-tumor human tissues. To address this void, we explore the distribution of DSBs in hematopoietic stem cells (HSCs) through the analyses of mosaic chromosomal alteration (mCA) breakpoints. Specifically, this work explores the relationship between the likelihood of DSB occurrences and the chromosomes on which they occur. Using data from the UK Biobank, mCA breakpoints were labeled as either DSBs or nonDSBs by proximity to telomeres and centromeres. mCA calls from the UK Biobank were obtained from Loh et al 2020. The START_MB_RANGE and END_MB_RANGE fields were treated as two separate breakpoint events for each entry in the data. Each of these breakpoint ranges was checked to see if it was close to either of the telomeres or to the centromere. Those falling within one Mb were categorized as mCA breakpoints that were likely not a result of DSBs, but rather missegregation of chromosomes or chromosome arms. Ranges that met either of these conditions were labeled “nonDSB” while ranges that did not were labeled “DSB.” These labeled data were processed in R using the Hmisc package. The 1-alpha binomial probability was calculated for the total number of DSBs versus the total number of breakpoint events. The point estimate for each chromosome was plotted along with the upper and lower confidence intervals. This work investigates the properties of DSBs. It is important to note that the observed putative DSBs are not representative of the frequency of DSBs in HSCs, since the resulting mutations can have different impacts on cellular fitness. This point is highlighted by our finding of increased putative DSBs on chromosome 13, as copy number changes involving the 13q14 locus are well documented drivers of chronic lymphocytic leukemia. In this investigation we observe that the proportion of putative DSBs is not correlated with chromosome length (p = 0.2). This result is likely due to the differential fitness effect of mCAs. However, it may also reflect differences in the likelihood of DSBs across the genome. We are currently working on methods from Machine Learning to further understand if there are genetic features which can predict DSBs which give rise to mCAs in HSCs.
Citation Format: Abraham Dutch, Cody Bumgardner, Yasminka Jakubek. Double-strand break inference from mosaic chromosomal alterations [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 7345.
Abstract 7357: Comparative transcriptomic analysis reveals novel insights into targetable B-cell lymphoma mechanisms
Authors: Kim Sehi , Rapier-Sharman Naomi , Told Michael T. , O’Neill Kim L. , Pickett Brett E. 
Published: March 2024

Abstract
B-cell lymphoma is a severe type of lymphatic cancer that is often misdiagnosed in adolescents. While some cases of B-cell lymphoma respond well to chemo- and radiation therapy, there are severe side effects, and many cases are refractory and fail to achieve remission. On the other hand, though CD19 CAR T-cell therapy is highly effective at treating B-cell lymphoma, its association with long-term immunocompromisation justifies the exploration of alternative treatments. Comparing B-cell lymphomas to an autoimmune disease that affects the same tissue type may grant us additional insights into immuno-oncology related treatments for B-cell lymphoma. We have developed a novel tool to compare cancer and autoimmune disease by analyzing bulk RNA-sequencing (RNA-seq) data. This algorithmic approach uses the transcriptional profile to improve our understanding of B-cell specific mechanisms that can be targeted in B-cell lymphoma. Using this tool, we compared the transcriptional signatures of primary B-cell lymphomas with primary B-cells from patients with systemic lupus erythematosus, an autoimmune disease. We identified specific genes and enriched functions associated with B-cell lymphoma’s immune signature. We expect that the results of our B-cell lymphoma analysis could be used to develop beneficial treatments alternative to current therapies, potentially mitigating side effects for B-cell lymphoma patients and increasing their quality of life.
Citation Format: Sehi Kim, Naomi Rapier-Sharman, Michael T. Told, Kim L. O’Neill, Brett E. Pickett. Comparative transcriptomic analysis reveals novel insights into targetable B-cell lymphoma mechanisms [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 7357.
Abstract 7373: Generative Bayesian networks for augmentation of molecular data from commercial genetics panels
Authors: Tracy Dillon H. , Sherman Jeff , Baron Maayan 
Published: March 2024

Abstract
Background: Computational models in medical research which use molecular features to predict patient sensitivities or outcomes are traditionally limited to producing a scalar output for a given disease phenotype, e.g. progression-free survival or drug response. Even for relatively intelligible models, it is generally difficult to place confidence limits on the prediction or develop an intuition for how a prediction varies with respect to “what-if” changes in those features or how sensitive a prediction is to changes in input variables. Moreover, while essential for understanding and modeling tumor behavior, molecular features from patient tumors in real-world settings are typically limited to profiles of hundreds of genes, while the biologically relevant inputs to the patient’s condition can be much larger.
Approach: To generate data required to enhance the interpretation of predictive models and extend the utility of real-world patient oncology datasets, a distribution of conditions consistent with the observed features and their incidence across cancer patient cohorts is required. We hypothesized we could synthesize patient samples drawn from the joint probability distribution of a broader universe of features when a subset of them is held fixed at the observed values. We model this joint distribution by learning a Bayesian network over a broad feature set for which some training data is available and generate feature profiles by applying Gibbs sampling to the learned network.
Results: We assessed the potential clinical utility of using these generated feature profiles in predicting drug response and enhancing biological interpretation of different model outputs. We found generative somatic mutations were useful for predicting cancer patient outcomes, including drug response predictions in breast cancer tumors from AACR Project GENIE. Synthesized patient feature profiles enhanced biological interpretability of nominal panel data (100-200 genes), providing a means to assign probabilities to outcomes and uncovering previously described mechanisms of drug response in real-world patient data.
Conclusion: We introduce an approach that leverages Bayesian networks to synthesize richly annotated patient feature profiles from limited molecular data routinely collected in real-world settings. This approach addresses challenges associated with limited molecular data, biological interpretability and evaluation of predictive models and enhances the utility of real-world datasets for cancer research.
Citation Format: Dillon H. Tracy, Jeff Sherman, Maayan Baron. Generative Bayesian networks for augmentation of molecular data from commercial genetics panels [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 7373.
Abstract 7378: Using game theory to investigate the therapeutic potential of disrupting tumor-microenvironment interactions
Authors: Van Egeren Debra , Chen Andrew , Stoddard Madison , Yuan Lin , Chakravarty Arijit 
Published: March 2024

Abstract
Cancer is a complex disease involving the interplay of several types of malignant and nonmalignant cells. The growth of tumors and surrounding stromal cells can be modeled as an ecosystem, where populations of cancerous and healthy cells interact and compete for resources. In this work, we have explored the application of game theoretic models of cancer to the design of novel anticancer therapies. Notably, a game theoretic-model of tumor-stromal interactions can capture the impact of interactions between cell types and can be used to investigate frequency-dependent parameters describing the impact of drug action during the initiation and growth of metastatic cancers. Previous studies using game theoretic models to describe cancer have focused on explaining progression patterns of specific tumors with known tumor-stromal interactions. This study takes a more general approach to cancer growth dynamics, modeling cancer as a simple game between healthy and cancer cells. This simplified model is used to make general predictions about cancer progression and the efficacy of treatment strategies. Our work suggests that disruption of beneficial interactions between healthy and cancer cells may be a viable treatment strategy for small tumors and preventing metastasis by ensuring that the healthy cell strategy is evolutionarily stable. The efficacy of treatment strategies that disrupt cancer cell cooperation or tumor-stromal dynamics changes as the cancer cell frequency changes. Our work suggests that drugs that target tumor-stromal cell interactions would need to be combined with other types of treatments to be effective against large tumors. Although based on a simplistic model of cancer initiation and progression, the framework derived here can be extended to the real-world design of experimental anticancer therapeutics, and fundamental analyses of this nature can be of practical utility in setting strategy for Target Product Profile design.
Citation Format: Debra Van Egeren, Andrew Chen, Madison Stoddard, Lin Yuan, Arijit Chakravarty. Using game theory to investigate the therapeutic potential of disrupting tumor-microenvironment interactions [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 7378.