bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract 467: Genetic ablation of microRNA-10b improves treatment outcomes in mouse models of pancreatic cancer
Authors: Kempinska Katarzyna , Samuel Sudhakar , Rajesh Saiprashanth , Mallett Christiane , Sempere Lorenzo 
Published: March 2024

Abstract
Pancreatic ductal adenocarcinoma (PDAC) is a recalcitrant and lethal disease with an overall 5-year survival rate of less than 12%. PDAC is a heterogeneous disease characterized by highly aggressive cancer cells, extensive desmoplastic reaction, and hypovascularity. These unique features endow PDAC tumors with an array of innate resistance mechanisms against standard-of-care (SOC) chemotherapy: gemcitabine/nab-paclitaxel or FOLFIRINOX. Thus, there is clinical need to develop novel targets that enhance treatment efficacy of SOC chemotherapy. microRNA-10b (miR-10b) expression is frequently upregulated in PDAC and correlates with poor outcome. High levels of miR-10b expression within cancer cells correlates with poor treatment response to gemcitabine-containing neoadjuvant chemotherapy and poor overall clinical outcome. We and others reported that miR-10b exerts cancer cell-intrinsic pro-survival, anti-apoptotic, and pro-metastatic functions via downregulation of key target genes (i.e., BIM, PTEN, TIAM1). We hypothesize that upregulation of miR-10b expression is a chemoresistance mechanism to increase cell survival and inhibit apoptosis in PDAC. To test this hypothesis, we generated a KPC model (KrasG12D-driven, p53-deleted by Pdx1-Cre) with global Mir-10b gene knockout (Mir-10bKO). Animals were recruited when their tumor volume reached 200 mm3 by multi-mouse MR imaging and were randomly assigned to control or treatment groups (100 mg/kg of gemcitabine q4d). Tumor growth was monitored by weekly MR imaging sessions throughout the duration of the treatment. Untreated KPC;Mir-10bKO animals survived several weeks longer than untreated KPC animals (21.7 vs. 18 weeks, p = 0.056), suggesting a weak but detectable tumor promoting role of miR-10b. Remarkably, loss of miR-10b activity enhances treatment response to gemcitabine and significantly prolongs survival in this KPC model. Treated KPC animals lived only 5 weeks longer than untreated KPC (23 vs 18 weeks, p = 0.015), whereas KPC;Mir-10bKO lived 9 weeks longer (27 vs 18 weeks, p = 0.002). Notably, we observed a more durable response in treated female KPC;Mir-10bKO animals (n = 4) compared to any other experimental group (n &gt; 5). We are currently performing tissue and molecular analyses to identify direct target genes involved in chemoresistance and sex-specific modulation of treatment response.
Citation Format: Katarzyna Kempinska, Sudhakar Samuel, Saiprashanth Rajesh, Christiane Mallett, Lorenzo Sempere. Genetic ablation of microRNA-10b improves treatment outcomes in mouse 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 467.
Abstract 4774: Inhibition of pancreatic acinar ductal metaplasia by novel YAP/TAZ inhibitor, CV-4-26
Authors: Perkins Corey M. , Zhou Chen , Campbell-Thompson Martha , Mao Yating , Atanasova Kalina R. , Jiang Jinmai , Ratnayake Ranjala , Luesch Hendrik , Ali Jamel , Li Chenglong , Schmittgen Thomas D. 
Published: March 2024

Abstract
Current challenges for pancreatic ductal adenocarcinoma (PDAC) treatment include overcoming the disease’s fibrous tumor microenvironment with limited cytotoxicity- in which tissue stiffening is believed to occur even pre-disease onset. Acinar to ductal metaplasia (ADM), the transdifferentiation of acinar cells into duct-like cells, is a predisposing event to PDAC development that is also linked to Hippo signaling, a major pathway involved in fibrosis and inflammation. Hippo activation is initiated by the yes-associated protein (YAP) in conjunction with the PDAZ binding motif (TAZ) and TEA domain (TEAD) transcription factor. Thus, the synthesis of the novel covalent TEAD autopalmitoylation inhibitor, CV-4-26, presented an opportunity to therapeutically target ADM. CV-4-26 binds to the TEAD lipid binding pocket, which, in turns, hinders TEAD palmitoylation, thereby leading to the inhibition of the Hippo pathway. Utilizing our 3D organoid p48Cre/+LSL-KRASG12D/+ (KC) mouse model, we demonstrated pronounced phenotypic and molecular inhibition of ADM by CV-4-26, resulting in a conserved acinar phenotype, as well as downregulation of downstream markers of the YAP/TAZ complex. The compound did not reverse ADM to the acinar state once ducts were visibly formed. Yet, CV-4-26 demonstrated a lack of cytotoxicity (up to 25 µM) as determined by Calcein AM staining. Biomechanical measurements of extracellular matrix stiffness acquired through calculations of fluorescent nanoparticle displacement further displayed decreased moduli as a response to inhibition treatment. Moreover, a 56-fold downregulation of collagen (COL1A1, COL1A2) mRNA, markers for PDAC development, was observed. However, less reduction in the collagens and extracellular matrix stiffness was observed in the ADM reversal treatments, corroborating our morphology and gene expression results. Our data suggest that combining CV-4-26 by ADM inhibition with standard of care therapies for PDAC may enhance the penetration of small molecules through the tumor’s extracellular matrix.
Citation Format: Corey M. Perkins, Chen Zhou, Martha Campbell-Thompson, Yating Mao, Kalina R. Atanasova, Jinmai Jiang, Ranjala Ratnayake, Hendrik Luesch, Jamel Ali, Chenglong Li, Thomas D. Schmittgen. Inhibition of pancreatic acinar ductal metaplasia by novel YAP/TAZ inhibitor, CV-4-26 [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 4774.
Abstract 4776: The role of angiogenesis in gastric tumorigenesis
Authors: Akkanapally Venu , BASU SUJIT 
Published: March 2024

Abstract
Introduction: Gastric or stomach cancer remains one of the most lethal malignancies, with an estimated 1,089,103 new cases and 768,793 deaths worldwide in 2020. In the United States, it is estimated that there were 26,500 new cases and 11,130 deaths from stomach cancer in 2023. Unfortunately, despite improved treatment in recent years, ~65% of gastric cancer patients present with aggressive metastatic disease, and they die within one year of diagnosis. Therefore, the identification of newer and effective therapies to target the precancerous stages of the disease promises possibilities for the prevention of gastric cancer in patients harboring these lesions. Gastric metaplasia and dysplasia are precancerous lesions that often progress to gastric cancer. Since anti-VEGF-A anti-angiogenic agents have shown efficacy in advanced gastric cancer patients, we hypothesized that VEGF-A-mediated angiogenesis has a functional role in the pathogenesis of gastric metaplasia and dysplasia.
Experimental Procedures: The Initial experiments were undertaken in human gastric metaplasia and dysplasia tissues and murine gastric metaplasia and dysplasia tissues collected from a well-established Helicobacter felis (H. felis) induced murine model of gastric tumorigenesis simulating human patients to detect angiogenesis (CD31/MVD) and identify angiogenic pathways using GeoMx DSP Spatial Proteomics and NanoString nCounter assay. Thereafter, further experiments were undertaken in the H. felis-induced murine model of gastric metaplasia and dysplasia, simulating human patients using VEGF-A hypo mice to determine the role of VEGF-A-induced angiogenesis in the progression of these lesions.
Results and Conclusion: Although our results indicated angiogenesis and VEGF-A expression in both human and mouse gastric metaplasia and dysplasia, inhibition in the progression of the precancerous gastric lesions was observed in only 40% of the VEGF-A hypo mice, thereby suggesting that VEGF-A induced angiogenesis might not be the major angiogenic pathway in these precancerous lesions in every patient. A similar phenomenon is also seen in some gastric cancer patients.
Citation Format: Venu Akkanapally, SUJIT BASU. The role of angiogenesis in gastric tumorigenesis [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 4776.
Abstract 4853: Impact of different therapeutic strategies on survival in laryngeal squamous cell carcinoma (LSCC)
Authors: Alshwayyat Sakhr , Erjan Ayah , Rawashdeh Miassar , Abdulsalam Tala , Alshwayyat Mustafa 
Published: March 2024

Abstract
Background: LSCC has seen a rise in cases and deaths over the past 30 years. Considering advancements in the treatment landscape, therapeutic options for patients with LSCC were evaluated to assess their efficacy in improving survival rates.
Methods: Data were retrieved from the Surveillance, Epidemiology, and End Results (SEER) (2000-2020) for localized/regional-stage cancer only, including the glottis (GC), supraglottic (SuGC), and subglottic (SC). Patients with a histologically confirmed diagnosis, no other malignancies, and complete data were included. Eight therapeutic groups were identified: surgery (Sx), chemotherapy (CTX), radiotherapy (RT), Sx + adjuvant radiotherapy (ART), Sx + CTX, Sx + RT, Sx + CTX + RT, and CTX + RT. T-tests and chi-square tests were used to compare variables, while Kaplan-Meier, log-rank tests, and Cox regression were used to identify prognostic factors for overall survival (OS) and cancer-specific survival (CSS).
Results: 68,282 patients were included (43,434 GC, 24,010 SuGC, and 838 SGC). 12.8% underwent Sx, 0.8% CTX, 0.3% Sx + CTX, 17.1% Sx + ART, 35.3% RT, 1.5% Sx + RT, 5.1% Sx + CTX + RT and 21.5% CTX + RT. 80.8% were males and 63.5% were over 60 years old and white (n=56,171). The median age was 64 years, and median tumor size was 3.2 cm. 36.5% underwent surgery with local tumor excision in 23.9 % and total laryngectomy in 5.7%. White race, regional stage, large tumor size, and CTX were poor prognostic factors for GC. Asian, white race, and total laryngectomy were good prognostic factors for SuGC, whereas male sex and older age were poor prognostic factors. In terms of SCG, Sx + ART was associated with a better prognosis, while regional and white race were associated with a poor prognosis.
Conclusion: This study shows survival differences among treatment groups and identifies factors for personalized treatment. It is the first study on all types of laryngeal tumors with a large sample size. Further research is necessary to validate and expand these results.
The 5-year survival rates (as a percentage of OS/CSS) for each therapeutic group Cancer Type Sx CTX Sx + CTX RT Sx + RT CTX + RT Sx + CTX + RT Sx + ART GC 91.9/75.5 79.8/77.3 89.2/81.8 89.8/78.1 89.5/85.3 87.8/83 79.1/90.1 90/78.1 SuGC 54.7/56.5 12.9/46.7 25.6/56.2 43.1/51.9 33.5/56.4 45.7/49.7 50.5/59.4 49.3/59.3 SGC 42.2/42.2 75/75 17.7/17.7 53/53 44.4/44.4 47.2/47.2 44.1/41.1 58.7/58.7
Citation Format: Sakhr Alshwayyat, Ayah Erjan, Miassar Rawashdeh, Tala Abdulsalam, Mustafa Alshwayyat. Impact of different therapeutic strategies on survival in laryngeal squamous cell carcinoma (LSCC) [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 4853.
Abstract 4856: Sex differences in childhood leukemia genomics
Authors: Williams Lindsay A. , Mills Lauren J. , Barragan Sofia , Gordon Peter M. , Poynter Jenny N. 
Published: March 2024

Abstract
Males have higher ALL and AML incidence and worse ALL survival using population-based data. Somatic genetics may play a role in ALL survival disparities and highlight potential sex specific treatment strategies for future study. Therefore, we evaluated sex differences in gene expression (RNA seq), copy number variation (CNV), and somatic mutation in ALL and AML. We stratified by cytogenomic subtypes in publicly available data from clinical cohorts using St. Jude PeCan (subtypes in Table 1). Then, we explored survival differences by sex within cytogenetic subtypes in publicly available data collected from Children’s Oncology Group patients in the NCI TARGET dataset (ALL n=387, 63% male; AML n=151, 51% male). Differentially expressed genes by sex were identified for ALL adjusting for subtype (n=214) and within subtypes (Table 1). There were no sex differentially expressed genes shared across subtypes and pathways identified from sex differentially expressed genes were few. In ETV6-RUNX1, there was as suggestion of worse 10-year survival for males (n=44, 61% male; Log-Rank p=0.068). Differentially expressed genes by sex were identified for AML adjusting for subtype (n=537) and within subtypes (Table 1). There were no differentially expressed genes by sex shared across AML subtypes. KMT2A had the highest number of pathways identified from sex differentially expressed genes (Table 1). There were no sex differences in AML survival. In ALL and AML subtypes there were no sex differences in CNVs (all t-test p&gt;0.05) or somatic mutations (all Fisher’s Exact p&gt;0.05). There were no sex differences in AML survival in TARGET, in agreement with population-based studies, and few differentially expressed genes identified in PeCan by subtypes. Sex differences in ALL survival were subtype specific and not heavily dependent on differentially expressed genes, CNVs, or somatic mutation. Sex differences in ALL survival may depend on treatment received, response to therapy, or other characteristics.
Table 1. Select characteristics from leukemia cases PeCan ALL SubtypeTotal n=247, 58% male N (% male) Number of differentially expressed autosomal genes by sex (male-female expression) in PeCan Number of biologic pathways identified from differentially expressed genes (Reactome) BCR-ABL1 76 (68) 48 8 DUX4-IGH 54 (57) 218 0 ETV6-RUNX1 50 (52) 86 1 hyperdiploid 14 (64) 3,199 2 iAMP21 12 (50) 120 0 KMT2A 41 (51) 216 0 AML SubtypeTotal n=149, 51% male CBFB-MYH11 34 (55) 7 0 KMT2A 44 (50) 422 19 RUNX1-RUNX1T1 61 (46) 30 1
Citation Format: Lindsay A. Williams, Lauren J. Mills, Sofia Barragan, Peter M. Gordon, Jenny N. Poynter. Sex differences in childhood leukemia genomics [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 4856.
Abstract 4905: Multimodal transformer model improves survival prediction in lung cancer compared to unimodal approaches
Authors: Tripathi Aakash , Waqas Asim , Yilmaz Yasin , Rasool Ghulam 
Published: March 2024

Abstract
Integrating multimodal lung data including clinical notes, medical images, and molecular data is critical for predictive modeling tasks like survival prediction, yet effectively aligning these disparate data types remains challenging. We present a novel method to integrate heterogeneous lung modalities by first thoroughly analyzing various domain-specific models and selecting the optimal model for embedding feature extraction per data type based on performance on representative pretrained tasks. For clinical notes, the GatorTron models showed the lowest regression loss on an initial evaluation set, with the large GatorTron-medium model achieving 12.9 loss. After selecting the top performers, we extracted robust embeddings on the full lung dataset built using the Multimodal Integration of Oncology Data System (MINDS) framework. MINDS provides an end-to-end platform for aggregating and normalizing multimodal patient data. We aligned the multimodal embeddings to a central pre-trained language model using contrastive representation learning based on a cosine similarity loss function. To adapt the language model to the new modalities, we employed a parameter-efficient tuning method called adapter tuning, which introduces small trainable adapter layers that leave the base model weights frozen. This avoids catastrophic forgetting of the pretrained weights. We evaluated our multimodal model on prognostic prediction tasks including survival regression and subtype classification using both public and internal lung cancer datasets spanning multiple histologic subtypes and stages. Our aligned multimodal model demonstrated improved performance over models utilizing only single modalities, highlighting the benefits of integrating complementary information across diverse lung data types. This work illustrates the potential of flexible multimodal modeling for critical lung cancer prediction problems using heterogeneous real-world patient data. Our model provides a strong foundation for incorporating emerging data types, modalities, and predictive tasks in the future.
Citation Format: Aakash Tripathi, Asim Waqas, Yasin Yilmaz, Ghulam Rasool. Multimodal transformer model improves survival prediction in lung cancer compared to unimodal approaches [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 4905.
Abstract 4906: Biopsy free virtual histology to discriminate benign from malignant squamous neoplasms
Authors: Kokikian Nelly , Wahhab Rachel , Li Jingxi , Martin Stephanie , Beynet David P. , Ozcan Aydogan , Scumpia Phillip 
Published: March 2024

Abstract
Reflectance confocal microscopy (RCM) is a noninvasive optical imaging modality that allows for cellular-level resolution, in vivo images of skin without performing a traditional skin biopsy. RCM image interpretation currently requires specialized training to interpret the grayscale output images that are difficult to correlate with tissue pathology. Here, we use a deep learning-based framework that uses a convolutional neural network to transform grayscale output images into virtually-stained hematoxylin and eosin (H&E)-like images allowing for the visualization of various skin layers, including the epidermis, dermal-epidermal junction, and superficial dermis layers. To train the deep-learning framework, a stack of a minimum of 7 time-lapsed, successive RCM images of excised tissue were obtained from epidermis to dermis 1.52 microns apart to a depth of 60.96 microns using the Vivascope 3000. The tissue was embedded in agarose tissue and a curette was used to create a tunnel through which drops of 50% acetic acid was used to stain cell nuclei. These acetic acid-stained images were used as “ground truth” to train a deep convolutional neural network using a conditional generative adversarial network (GAN)-based machine learning algorithm to digitally convert the images into GAN-based H&E-stained digital images. We used the already trained machine learning algorithm and retrained the algorithm with new samples to include squamous neoplasms. Through further training and refinement of the algorithm, high-resolution, histological quality images can be obtained to aid in earlier diagnosis and treatment of cutaneous neoplasms. The overall goal of obtaining biopsy-free virtual histology images with this technology can be used to provide real-time outputs of virtually-stained H&E skin lesions, thus decreasing the need for invasive diagnostic procedures and enabling greater uptake of the technology by the medical community.
Citation Format: Nelly Kokikian, Rachel Wahhab, Jingxi Li, Stephanie Martin, David P. Beynet, Aydogan Ozcan, Phillip Scumpia. Biopsy free virtual histology to discriminate benign from malignant squamous neoplasms [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 4906.
Abstract 4918: Cancer mutations converge on a constellation of molecular assemblies to predict resistance to replication stress agents
Authors: Zhao Xiaoyu , Singhal Akshat , Park SungJoon , Kong JungHo , Bachelder Robin , Ideker Trey 
Published: March 2024

Abstract
Rapid proliferation is a hallmark of tumor cells, associated with sensitivity to therapeutics that cause DNA replication stress (RS). Many tumors exhibit drug resistance, however, via molecular pathways that are incompletely understood. Here, we develop an ensemble of predictive models that elucidate how cancer mutations impact the response to common RS-inducing (RSi) agents. The models implement recent advances in deep learning to facilitate multi-drug prediction and mechanistic interpretation. Instead of associating individual genetic alterations with RSi drug responses directly, the strategy is to project these alterations on a map of protein complexes and larger molecular assemblies associated with cancer. Initial studies in tumor cells identify 41 molecular assemblies that integrate alterations in hundreds of genes for accurate drug response prediction. These cover roles in transcription, repair, cell-cycle checkpoints, and growth signaling, of which 30 are shown by loss-of-function genetic screens to regulate drug sensitivity or replication restart. The model translates to cisplatin-treated cervical cancer patients, highlighting an RTK-JAK-STAT assembly governing resistance. This study defines a compendium of mechanisms by which mutations affect therapeutic responses, with implications for drug selection and combination.
Citation Format: Xiaoyu Zhao, Akshat Singhal, SungJoon Park, JungHo Kong, Robin Bachelder, Trey Ideker. Cancer mutations converge on a constellation of molecular assemblies to predict resistance to replication stress agents [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 4918.