Citations

Abstract Ovarian cancer is the deadliest gynecological cancer with a low 5-year overall survival rate that affects over 300,000 women globally each year. Given lack of routine screening procedures, ovarian cancer patients are frequently diagnosed with late-stage disease that rapidly progress despite initial responses to front line therapy. PARPi and VEGFi targeted therapies have improved progression free survival in small subsets of patients but have largely failed to improve overall survival. Since the robust uptake of PARPis in the front line setting, resistance to this class of drugs is a growing problem. The literature is filled with many novel treatment approaches, but the vast majority fail to gain traction in pre-clinical models and early phase trials. A contributing factor to these disappointments relates to the prevalent use of 2D monoculture model systems that do not recapitulate the tumor microenvironment. To address this issue, we utilized the Rastrum 3D cell printer to grow ovarian cancer cells and PDX models in bio-functional matrices which provide optimal stiffness and extracellular matrix components specific to the ovarian tumor microenvironment. We found that ovarian cancer cells grown under these conditions exhibit dramatic up-regulation of the JAK/STAT signaling pathway, including autocrine/paracrine signaling factors, which correlated with increased sensitivity to JAK/STAT inhibitors. This affect was lost when STAT1 and STAT3 knockout cell lines were grown in this 3D environment. Ovarian tumors are known to be rich in cancer-associated fibroblasts (CAFs) and tumor-associated macrophages (TAMs). We incorporated primary CAFs into this 3D culture system and found they could promote ovarian cancer cell growth only in cancer cells with intact JAK/STAT signaling further indicating the essential role of this pathway in mediating tumor progression. Co-culture with M2 macrophages was also found to induce ovarian cancer cell growth, particularly in resistant models. Conversely, co-culture with M1 macrophages inhibited treatment naïve ovarian cancer cell growth but not resistant cell line growth. Single-cell RNAseq of the complex 3D cultures elucidated profound differences in the cross-talk between these cell types that is dependent on cancer cell sensitivity to standard-of-care agents. Finally, the addition of JAK/STAT inhibitors was found to substantially alter this cross-talk between cell types and inhibit cancer cell viability. These data further implicate the importance of JAK/STAT signaling, specifically in clinically relevant 3D models, in supporting ovarian cancer progression and response to chemotherapy and PARPi treatment. Ongoing studies are aimed at confirming these findings in pre-clinical mouse models and to elucidate the most effective JAK/STAT inhibitors in vivo with the goal of informing the design of future clinical trials. Citation Format: Esther Rodman, Xiyin Wang, Hannah Smith, Xiaonan Hou, Scott Kaufmann, John Weroha, John Hawse. 3D models of chemotherapy- and PARPi-resistant ovarian cancer indicate essential roles for JAK/STAT signaling in mediating drug resistance [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 1224.

AbstractAtherosclerosis is the most common cause of heart disease and stroke. Plaque thickness ≥4 mm in the ascending aorta or aortic arch is strongly correlated with cerebral embolic events and ischemic stroke. However, despite imaging workup, the cause of embolic stroke remains unidentified in many patients. Transesophageal echocardiography (TEE) is the preferred echocardiographic method for the evaluation of cardiac source of emboli. 2D TEE imaging evaluates aortic root and aortic arch in a single plane or two planes with biplane imaging. However, 2D TEE often fails to detect mobile or complex components in the ascending aorta and aortic arch plaques. The routine availability of 3D TEE in current ultrasound systems may significantly improve the assessment of aortic plaques as a potential embolic source. In this case series, we present four consecutive patients with stroke who underwent TEE by a single cardiologist for possible cardioembolic source. Some of these patients may have been labelled as “cryptogenic stroke” or “embolic stroke of undetermined source” (ESUS) due to the presence of insignificant or nonmobile ascending aortic or aortic arch plaques on 2D TEE imaging. In our four consecutive patients with ESUS who underwent TEE by a single operator, 3D TEE showed complex aortic arch plaques with ulceration with mobile components and established these plaques as the likely source of embolic stroke.

Abstract Lung cancer is the leading cause of cancer-related deaths worldwide. Existing therapeutic options have limited efficacy, underscoring the critical need for the identification of new actionable therapeutic targets. We previously identified the Transmembrane Serine Protease TMPRSS11B as a novel gene that promotes the transformation of human bronchial epithelial cells in vitro and induces tumorigenesis in vivo. TMPRSS11B promotes extracellular release of Basigin, an obligate chaperone of the lactate monocarboxylate transporters MCT1/4, enhancing lactate export and glycolytic metabolism, and thereby promoting tumorigenesis. Importantly, TMPRSS11B is frequently overexpressed in human lung squamous cell cancers (LSCC) and high expression is associated with poor patient survival. Moreover, as a cell surface protein and enzyme, TMPRSS11B represents a tractable target for therapeutic intervention. To investigate whether TMPRSS11B activity impacts the host immune system and the tumor microenvironment (TME), we evaluated the effect of Tmprss11b depletion in a syngeneic LSCC mouse model, KLN205. Tmprss11b loss of function in KLN205 LSCC cells significantly reduced tumor burden in immunocompetent mice and triggered an accumulation of CD4+ T cells. We are currently extending these studies by investigating the effect of Tmprss11b loss of function using CRISPR/Cas9 editing in the Rosa26LSL-Sox2-IRES-GFP; Nkx2-1 fl/fl; Lkb1fl/fl (SNL) mouse model of LSCC. Tumor burden analysis and pH-sensitive fluorescent imaging are ongoing to assess changes in lactate accumulation. Moreover, RNA FISH analysis and spatial transcriptomics revealed that Tmprss11b expression is highly enriched in lung squamous tumors compared to lung adenocarcinomas and normal lung in SNL mice. Spatial analysis of the transcriptome is currently ongoing to assess the effects of Tmprss11b expression on the TME. Collectively, these studies will elucidate the molecular mechanisms through which TMPRSS11B promotes tumor growth and alters the tumor microenvironment in LSCC. Citation Format: Hari Shankar Sunil, Barrett L. Updegraff, Jingfei Zhu, Lisa Thomas, Bret M. Evers, Jean R. Clemenceau, Isabel Barnfather, John D. Minna, Ralph J. Deberardinis, Trudy G. Oliver, Tae Hyun Hwang, Kathryn A. O'Donnell. Transmembrane serine protease TMPRSS11B promotes tumorigenesis in lung squamous cell carcinoma through enhanced lactate export and modulation of the tumor microenvironment [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 1793.

Abstract Background: Immune checkpoint inhibitors (ICIs) targeting PD-1 or PD-L1 have dramatically improved survival of patients with gastric cancer (GC). However, recent clinical trials, including KEYNOTE-059, KEYNOTE-061, and ATTRACTION-2, show that the objective response rate (ORR) for ICIs is still less than 20% in patients with advanced GC. Therefore, predicting who will respond to ICIs in advance is essential to make better treatment plans for GC patients. There are potential biomarkers to predict ICI response, but most of them can only be applied to a limited population of patients. For example, Kim ST., et al., (PMID: 30013197) show that patients with MSI-high or EBV-positive responded well to ICIs, but these subtypes account for less than 30 percent of GC patients (PMID:25079317). In this study, we propose a prediction model of ICI response using the 32 GC-specific genes that we identified from mutation data (PMID: 26635139) and showed their close association with survival and ICI response in GC (PMID: 35140202; PMID: 36508166). In addition, since the number of available GC-ICI samples is small, we design our prediction model in Bayesian and ensemble learning frameworks which are robust to small sample size problems. Methods: We collected mRNA sequencing data from GC-ICI treated patients from our institutions and publications (PMID: 30013197; PMID: 35254400; PMID: 33846173). We used 108 samples previously included in our previous work (PMID: 36508166) as the training data and 27 samples (13 responders and 14 non-responders) from (PMID: 3384617) as the test data. We built and trained a classifier to separate responders from non-responders using the expressions of the 32 genes. We proposed to use a Deep Gaussian process (GP) model, a multi-layered extension of a GP that is itself a Bayesian method. We optimized the parameters of each GP model in variational inference. To implement ensemble learning, we trained multiple DGP models with different initializations of the model parameters and data splitting (training/validation sets). For each training run, the best model was selected based on the prediction performance on the validation set, measured by AUC. The final prediction for a test sample was made by combining the prediction results of all the DGP models by taking the average. Results: We implemented the DGP-based prediction model using PyTorch in Python, and the codes will be publicly available on the GitHub repository (https://github.com/hwanglab/GC_ICI_response_prediction). We achieved a prediction performance of 0.813 AUC on the test data (sensitivity = 0.769 and specificity = 0.714). Conclusion: We propose the prediction model of ICI response, which can handle small sample size problems in the framework of Bayesian and ensemble learning. The experimental results using the GC-ICI data demonstrate that the 32 genes can be used as predictive markers for ICI response in GC. Citation Format: Sunho Park, Minji Kim, Changjin Hong, Tae Hyun Hwang. A deep Gaussian process (DGP)-based prediction model for immunecheckpoint inhibitor (ICI) response in gastric cancer (GC) [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 2316.

Abstract Oncocytic carcinoma (Hurthle cell carcinoma) has the highest incidence of metastasis among the differentiated thyroid cancers. Metastatic disease is reported at the initial diagnosis in 10-20% of patients and 34% overall. Thyroid-stimulating hormone receptor (TSHR) expression is limited to the thyroid gland. It is abundantly expressed on thyroid tumor cells, making TSHR a compelling target for advanced thyroid cancer diagnostics and therapeutics. We developed a potent anticancer strategy for treating oncocytic carcinoma using a novel thyroid hormone stimulating receptor (TSHR)- targeted (chimeric antigen receptor) CAR T cell therapy. TSHR CAR T was generated by transducing T cells derived from healthy donors. In vitro effector functions (cytotoxicity, proliferation, degranulation) were tested in TSHR+ tumor models, and subsequent in vivo studies using NSG mice were performed to assess anti-tumor activity efficacy. We observed strong anti-tumor activity against metastatic oncocytic carcinoma cell line XCT.UC1 using the TSHR CAR T therapy in vivo. Re-challenging treated mice with XCT.UC1 cells reactivated TSHR CART cells with enhanced proliferation and complete suppression of tumor growth of the newly injected tumor cells. Our work represents a promising strategy to improve treatment outcomes of patients with metastatic oncocytic carcinoma that may provide a durable response. Citation Format: Justyna J. Gleba, Aylin Alasonyalilar-Demirer, Matthew Pawlush, Claudia Manriquez-Roman, Elizabeth L. Siegler, Robert C. Smallridge, Abba Zubair, Han W. Tun, Saad S. Kenderian, John A. Copland. Novel TSHR CAR T therapy for targeting oncocytic carcinoma [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 5082.

Abstract The success of precision cancer prevention and treatment hinges on accurate discrimination between benign and pathogenic germline alleles in cancer susceptibility genes. Variants of uncertain clinical significance (VUS) present a challenge for cancer risk assessment and functional data will be essential to resolve many VUS. To address this, we developed a cloud-based environment to collate, curate, integrate and analyze all published functional data related to BRCA1 and BRCA2 missense VUS. Then, functional evidence criteria for pathogenicity were determined for each assay using the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) classification guidelines and ClinGen criteria. Our approach involved retrieving published articles reporting one or more functional assays of BRCA1/2 missense variants reporting variant impact on various biochemical and cell biological functions. Functional results were recorded using original authors' thresholds and categories, then converted to ordinal variables to harmonize: [0 = no functional impact], [1 = intermediate impact], and [2 = functional impact]. For BRCA1, we updated our previous published integration (Genet Med. 2021;23:306-315) with 14 additional publications, collating results from 53 instances of functional assays reporting functional data on 3,219 unique missense variants. For BRCA2, 28 publications were identified reporting data from 141 instances of functional assays on 4,759 unique missense variants. Utilizing a panel of 542 and 396 known pathogenic and benign reference variants for BRCA1 and BRCA2, respectively, we determined the sensitivity, specificity, and ACMG/AMP odds of pathogenicity for each instance of the assay. The remaining variants were assigned a relevant functional assay code weight for each assay instance. Our study successfully derived ACMG/AMP evidence strength from functional data for 3,040 BRCA1 (94% of 3,219) and 2,704 BRCA2 (57% of 4,759) missense variants. This comprehensive work underscores the utility of functional data in informing classification of BRCA1 and BRCA2 missense VUS. Citation Format: Paulo Lyra, Lucas Dalcolmo, Michael Parsons, Thales Nepomuceno, Samuel Brito, Nam Phuong N. Nguyen, Geise de Oliveira, Joao Paulo da Siva, Laura Caleca, Tanisha Taneja, Chunling Hu, Marcy Richardson, Maria Rossing, Aditi Hazra, Alexandra Martins, Sandrine Caputo, Gael A. Millot, Joanne NgeowYuen Yie, Marcelo A. Carvalho, Melissa Cline, Paolo Radice, Rachael Carlsen, Romy Mesman, Valentina Zampiga, Rehan Villani, Vijay Josef, Shyam Sharan, Kyriaki Michailidou, Amanda B. Spurdle, Fergus Couch, Maaike P.G. Vreeswijk, Alvaro N. Monteiro. Integration of functional data to classify BRCA1/2 missense variants: An ENIGMA project [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 7325.

Abstract The Mayo Clinic Breast Disease Registry (MCBDR) was developed to serve as a cohort of newly diagnosed breast cancer patients to address questions of etiology, prognosis, and survivorship. Eligibility is limited to patients 18 years or older with a confirmed first stage 0-4 breast cancer diagnosis within the last year. Consent is completed via phone, patient portal, or in-person. Upon enrollment, a baseline questionnaire and blood collection are completed. Annual follow-up surveys that capture BC outcomes are sent to all living participants. The MCBDR cohort (N=9,215, enrolled between 2001 and 2023) is 99% female, with an average age at diagnosis of 58 years (SD=12.7). Currently, MCBDR has an average time since diagnosis of 9.8 years (SD=6.4). The participants are 94% white, and 55% live in Minnesota. At the time of baseline questionnaire completion, 77% were married, 84% had a bachelor’s degree or higher, and 8% reported financial hardship. Further, 35% reported a history of smoking, 11% consumed more than two drinks per day, and 9% reported fair or poor social relationships. Within MCBDR, 53% of the participants had stage 0 or 1 cancer at diagnosis, while 28% had stage 2, 9% stage 3, and 3% stage 4 BC. Tumors were triple negative in 9%, HER 2 positive in 9%, hormone receptor-positive and HER2 low or negative in 55%, and 27% had missing HER2 status. Pathological TNM staging was available on 98%, among which 33% were staged at T2 or higher and 27% were node-positive. Definitive BC surgery was completed at Mayo Clinic for 73%, with 35% undergoing mastectomies and 44% having lumpectomies. 74% were treated with radiation, 56% underwent chemotherapy, and 79% were treated with endocrine therapy. Clinical genetic testing results have been nurse-abstracted for 94% of the cohort. Of those known to be tested, 521 (6%) had a pathogenic or likely pathogenic mutation identified in a BC causing gene. In addition, whole exome sequencing was completed on 71% of MCBDR participants in 2020, in which 167 previously unknown pathogenic or likely pathogenic mutations were identified. After the initial diagnosis and active treatment phase, nurse abstraction identified 151 (2%) participants known to have been diagnosed with a contralateral BC diagnosis, and 4% known to have been diagnosed with a second primary other than breast. Recurrence in the same breast has been reported for 242 (3%), with 72% of those recurrences occurring within 5 years of initial diagnosis and another 19% occurring 5-10 years post diagnosis. Among the 1,262 (14%) who are deceased, 24% died from BC and 19% had distant metastases at diagnosis or a distant recurrence. Amongst all deceased, 6% died within 1 year of their diagnosis and 43% died within 5 years of diagnosis. For participants who died from BC, 10% died within 1 year of their diagnosis and 64% died within 5 years of diagnosis. MCBDR data has been used in numerous publications and is an essential resource for efficient observational research analyses. Citation Format: Nicole L. Larson, Janet Olson, Kathryn Ruddy, Fergus Couch, Denise Herman, Feven Abraha. Mayo Clinic breast cancer cohort: A valuable resource for breast cancer research [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7339.

Abstract Lung squamous cell carcinoma (LUSC) is a devastating disease, accounting for ~30% of all lung cancer diagnoses and ~40,000 deaths annually in the United States alone. LUSC patients suffer from high prevalence of relapse and a dismal 5-year survival of only ~24%. The lack of animal models that reflect the salient features of human disease to assess the safety and efficacy of drugs, and to explore the underlying molecular mechanisms of LUSC tumor biology, is a major impediment for LUSC patients. We have identified concomitant 3q26 copy number gain (CNG) and TP53 loss as a defining genetic alteration present in ~90% of LUSC tumors. Furthermore, we have identified and characterized three 3q26 oncogenes (PRKCI, ECT2 and SOX2) that genetically and biochemically collaborate to drive LUSC tumor formation. Using syngeneic mouse modeling, we have demonstrated that coordinate overexpression of Prkci, Ect2 and Sox2, and loss of Trp53 in ex vivo cultures of lung basal stem cells (LBSCs; a cell of origin for LUSC) drives transformation of these cells into tumors of exclusively LUSC histopathology. These findings lead to the hypothesis that PRKCI, ECT2 and SOX2 represent a multigenic driver of 3q26 CNG-driven LUSC, which we term the 3q26 OncCassette. Based in these findings, we have developed and begun characterizing the first autochthonous genetically engineered mouse model (GEMM) to study 3q26 OncCassette-driven tumorigenesis. Our novel immune competent GEMM will provide critical insight into tumor initiation and progression of preneoplastic lesions to malignant LUSC and allow characterization of the immune landscape in these tumors. Citation Format: Kayleah M. Meneses, Yi Liu, Capella R. Weems, Lee Jamieson, Duy T. Nguyen, Verline Justilien, Nicole R. Murray, Alan P. Fields. Modeling the 3q26 OncCassette using genetically engineered mice [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 1434.

Abstract Objective: LX-101 is a next-generation, targeted therapy directed to the insulin-like growth factor 1 receptor (IGF-1R). LX-101 consists of a proprietary IGF-1 variant coupled to a cytotoxic methotrexate payload. LX-101 was previously evaluated in Phase 1 trials of adult patients with advanced, pretreated cancers, where it was well-tolerated and demonstrated single agent activity. Neither a dose limiting toxicity, nor a maximum tolerated dose was reached, leaving potential room for additional dose escalation and schedule optimization. Multiple aggressive cancers of unmet need have genetic alterations affecting the IGF-1R pathway and/or high IGF-1R expression that correlates with poor outcomes, including certain cancers of the breast, head and neck, Ewing’s sarcoma, osteosarcoma, and others. Prior attempts at inhibiting IGF-1R with non-payload bearing naked monoclonal antibodies or small molecules produced a range of clinical outcomes including some partial and complete responses. None of these agents, however, were ultimately approved, potentially due to suboptimal potency that allowed for escape mechanisms, including redundant signaling pathways, and the lack of enrichment for select tumor types with strong ties to the IGF-1/IGF-1R pathway. Herein, we investigated the anti-tumor activity of the payload-bearing agent LX-101 against IGF-1R-involved cancer cell lines. Methods: Cell lines were incubated with LX-101 (~1.6 - 2500nM). Cell viability was assessed by CellTiter-Glo after 4 days. IC50s were calculated using GraphPad PRISM software. Results: LX-101 displayed potency against head and neck cancer (FaDu, IC50 = 9 nM), triple negative breast cancer (BT-20, IC50 = 17 nM), Ewing’s sarcoma, including EWSR1-FLI1 gene fusion-positive cell lines RD-ES (IC50 = 10 nM), A-673 (IC50 = 14 nM), and SK-ES-1 (IC50 = 29 nM) and EWSR1-ERG gene fusion-positive cell line CADO-ES1 (IC50 = 14 nM). LX-101 was also potent against PAX3-FOXO1 gene fusion positive alveolar rhabdomyosarcoma (SJCRH30, IC50 = 23 nM), osteosarcoma (143B, IC50 = 6 nM; HOS, IC50 = 7 nM; U2OS, IC50 = 32 nM), and neuroblastoma (SK-N-AS, IC50 = 16 nM; IMR-32, IC50 = 20 nM; SH-SY5Y, IC50 = 30 nM). Conclusion: These results demonstrate that LX-101 has potent preclinical anti-tumor activity against multiple cancer cell lines with well-established ties to the IGF-1/IGF-1R pathway, including with different genetic and epigenetic alterations. These data support further clinical development of LX-101 in IGF-1R-involved cancers. New clinical trials are planned. Citation Format: Matt Hoberman, Arkadiusz Z. Dudek. LX-101, a novel, clinical stage, payload-bearing targeted therapy directed to the insulin-like growth factor receptor (IGF-1R), demonstrates potent preclinical anti-tumor activity against multiple cancer types with well-established ties to the IGF-1/IGF-1R pathway [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 1918.