Carr, Ryan M

e16368 Background: Pancreatic ductal adenocarcinoma (PDAC) is predicted to be the second cause of cancer death in the US by 2040. For the minority of patients who are candidates for curative-intent surgical resection, a neoadjuvant approach with chemotherapy or chemotherapy followed by chemoradiotherapy (chemoRT) has become the standard of care. The tumor microenvironment (TME) has been recognized as a key factor in therapeutic resistance and disease progression. This study aims to explore the prognostic value of human-interpretable machine learning image features (HIFs) derived from whole-slide H&E images. Methods: Consecutive PDAC patients who underwent neoadjuvant therapy followed by surgical resection were studied in this single-institution retrospective study. Clinical variables collected include tumor site (head/body/tail), surgery extent, histology, sex, age at diagnosis, grade, treatment response (4-point scale), LVI, PNI, resection margin status, pathological TNM staging, number of lymph nodes removed/positive, neoadjuvant strategy (chemotherapy vs chemoRT), and number of neoadjuvant chemo cycles. These factors were analyzed with a multivariable Cox proportional hazards model for disease-free survival (DFS) after surgery. Additionally, 420 human-interpretable image features (HIFs) derived from a commercial machine learning software were analyzed with a univariable Cox model on a binary outcome of 1-yr DFS, applying a Bonferroni correction for multiple comparisons to identify significant predictors. Results: Increased neoadjuvant chemotherapy cycles (HR = 0.62, p = 0.001, [median: 8, IQR: 6-12]) and receipt of combination neoadjuvant therapy (HR = 0.15, p = 0.020, [29% chemo, 71% +chemoRT]) exhibited a protective effect in the multivariable DFS model. 3 HIFs quantifying immune cells and macrophages within the cancerous tissue and its stroma were associated with an improved probability of 1-year DFS. Conclusions: In addition to clinical factors, HIFs may offer valuable insights into the tumor microenvironment's influence on PDAC progression, paving the way for improved prognostic models and therapeutic strategies. Future work will integrate clinical predictors with HIFs in a combined model.

Abstract Aberrant activation of GLI transcription factors has been implicated in the pathogenesis of different tumor types including pancreatic ductal adenocarcinoma. However, the mechanistic link with established drivers of this disease remains in part elusive. In this study, using a new genetically engineered mouse model overexpressing constitutively active mouse form of GLI2 and a combination of genome-wide assays, we provide evidence of a novel mechanism underlying the interplay between KRAS, a major driver of pancreatic ductal adenocarcinoma development, and GLI2 to control oncogenic gene expression. These mice, also expressing KrasG12D, show significantly reduced median survival rate and accelerated tumorigenesis compared with the KrasG12D only expressing mice. Analysis of the mechanism using RNA sequencing demonstrate higher levels of GLI2 targets, particularly tumor growth–promoting genes, including Ccnd1, N-Myc, and Bcl2, in KrasG12D mutant cells. Furthermore, chromatin immunoprecipitation sequencing studies showed that in these cells KrasG12D increases the levels of trimethylation of lysine 4 of the histone 3 (H3K4me3) at the promoter of GLI2 targets without affecting significantly the levels of other major active chromatin marks. Importantly, Gli2 knockdown reduces H3K4me3 enrichment and gene expression induced by mutant Kras. In summary, we demonstrate that Gli2 plays a significant role in pancreatic carcinogenesis by acting as a downstream effector of KrasG12D to control gene expression.

Purpose: To investigate the molecular characteristics of and potential for precision medicine in KRAS wildtype pancreatic ductal adenocarcinoma (PDAC). Patients and Methods: We investigated 27 patients with KRASWT PDAC at our institution. Clinical data were obtained via chart review. Tumor specimens for each subject were interrogated for somatic single nucleotide variants, insertion and deletions, and copy number variants by DNA sequencing. Gene fusions were detected from RNA-seq. A patient-derived organoid (PDO) was developed from a patient with a MET translocation and expanded ex vivo to predict therapeutic sensitivity prior to enrollment in a phase 2 clinical trial. Results: Transcriptomic analysis showed our cohort may be stratified by the relative gene expression of the KRAS signaling cascade. The PDO derived from our patient harboring a TFG-MET rearrangement was found to have in vitro sensitivity to the multi-tyrosine kinase inhibitor crizotinib. The patient was enrolled in the phase 2 SPARTA clinical trial and received monotherapy with vebrelitinib, a c-MET inhibitor, and achieved a partial and durable response. Conclusions: KRASWT PDAC is molecularly distinct from KRASMUT and enriched with potentially actionable genetic variants. In our study, transcriptomic profiling revealed that the KRAS signaling cascade may play a key role in KRASWT PDAC. Our report of a KRASWT PDAC patient with TFG-MET rearrangement who responded to a cMET inhibitor further supports the pursuit of precision oncology in this sub-population. Identification of targetable mutations, perhaps through approaches like RNA-seq, can help enable precision-driven approaches to select optimal treatment based on tumor characteristics.

Abstract Pancreatic ductal adenocarcinoma (PDAC) is predicted to be the second cause of cancer death in the US by 2040. Five-year overall survival is only ~12% despite decades of research. The mainstay of treatment remains chemotherapy in the absence of highly recurrent, therapeutically actionable, genetic targets. For the minority of patients (~15-20%) who are candidates for curative-intent surgical resection, six months of intensive neoadjuvant chemotherapy with/without chemoradiation has become standard-of-care. However, despite evidence of radiographic, metabolic, and biochemical responses, significant viable residual disease on pathologic analysis is almost universally observed with approximately 40-60% risk of disease recurrence. Thus, there is a critical need to better understand why PDAC remains recalcitrant to current therapeutic modalities. Pathologic evaluation of PDAC reveals a complex microenvironment consisting of neoplastic cells dynamically interacting with both “normal” cellular (e.g. mesenchymal, immune) and non-cellular (e.g. collagen) stromal elements. While biologically important, experimental models and small-scale efforts to dissect the PDAC ecosystem are limited by focus on individual tumor compartments and generation of conflicting results. Consequently, there is a need for a more comprehensive understanding of the structure and dynamics of the PDAC TME through the theoretical lens of evolutionary ecology. Current therapies are not focused on the PDAC ecosystem. We hypothesize that cell-cell interactions of PDAC cells with its local niche are important for conferring treatment resistance. Thus, better understanding of said interactions could yield novel ecologically-informed therapies. Consequently, we developed a digital pathology library of approximately 1000 PDAC resection cases (whole-slide H&E images) performed at Mayo Clinic between 2013-2021. Approximately 400 cases are treatment naive while about 600 were treated with neoadjuvant therapy. While some qualitative features of pathologic analysis have prognostic value (e.g., pathologic treatment response, presence of perineural or lymphovascular invasion, extent of desmoplasia), we aim to identify prognostic spatial relationships using tools from landscape ecology. We utilized the HoVer-Net model for nuclei segmentation and classification and spatial statistics methods and landscape fragmentation analysis to understand the spatial organization within the PDAC tumor ecology. With these methodologies, we can assess the spatial context of cell interactions, habitat/niche/microenvironment formation, ecological relationships between cell populations, and the different tissue components. The different spatial statistics/metrics are used to quantify levels of immune cell infiltration, mixing, as well as the complexity and diversity of microenvironment phenotypes leading to high levels of tumor heterogeneity. Such measurements can help predict the likelihood of a PDAC tumor adaptive potential that could lead to fast evolutionary responses to therapy, progression, and poor prognosis. Citation Format: Merih D. Toruner, Luis Cisneros, Zafar Siddiqui, Chady Meroueh, Ritambhara Singh, Carlo Maley, Martin E. Fernandez-Zapico, Ryan M. Carr. Dissecting the pancreatic cancer microenvironment using landscape ecology [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr B026.

Abstract Background: KRAS is a significant driver gene for pancreatic ductal adenocarcinoma (PDAC) and is present in up to 90% of PDAC cases. KRAS mutant (mt) PDAC tends to have worse prognosis compared to KRAS wild-type (wt) PDAC. However, the clinical and biological impact of the KRAS mutation subtypes (e.g. G12D, G12R, G12V, G12C and Q61) remains unclear. We sought to explore the clinical and molecular characteristics of the KRAS mt subtypes. Methods: We performed a retrospective review of patients with KRAS mt PDAC who underwent next generation sequencing at our institution from December 1, 2018 to December 1, 2021. We collected patient demographics, disease characteristics, clinical outcomes, DNA and RNA sequencing results via chart review. Bulk RNA-seq was performed via Tempus and The Cancer Genome Atlas. Count data were processed and separated by KRAS mutation subtype using a custom python script. Differential gene expression was performed using the DifSeq2 R package. Results: A total of 158 KRAS mt patients (at diagnosis, average age 63.8 years, 57% male, 88 (56%) Stage IV) were included. 10% of patients had KRAS Q61 mutation, 14% G12R, 30% G12V and 46% G12D; only 1.1% had the potentially actionable G12C mutation. G12R had a longer overall survival (OS) compared to the others (median 24.8 vs 17.5 months (m), p=0.05). Among patients with de novo metastatic disease, G12V had the lowest OS (median 9.8 vs 12.4 m, p=0.02). Between the KRAS mt subtypes, there were no statistically significant differences in tumor mutation burden, location of PDAC or subsequent metastasis, lines of treatment (average 2.3), age at diagnosis, gender, or stage at diagnosis. One hundred thirty-seven (87%) patients had at least one pathogenic somatic variant, 14 of which had statistically significant differences between KRAS mt subtypes. 82 (52%) patients had at least one RNA expression variant and bulk RNA-seq showed that each KRAS G12 mutation subtype had unique gene expression patterns, including several oncogenes and tumor suppressor genes. Conclusions: Our data suggest that KRAS mt subtypes may confer different clinically significant phenotypes of PDAC. We found G12R to be associated with improved prognosis compared to other KRAS mt subtypes and that among patients with de novo metastatic disease, G12V had the worst prognostic implication. As there were no statistically significant differences in patient demographics between the KRAS mt subtypes, we hypothesize survival differences are driven by biological phenotype. This is supported by our RNA-seq findings, which demonstrated unique gene expression patterns for each KRAS mt subtype. Citation Format: Alexander Xiao, Jack Korleski, Ryan Carr. KRAS mutation subtypes are associated with clinical and phenotypic differences in pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr C095.

e16259 Background: Patients with KRAS mutant (mt) pancreatic ductal adenocarcinoma (PADC) have worse survival outcomes compared to KRAS wild-type (wt) PDAC patients. However, the prognostic implication of the KRAS mutation subtype (e.g. G12D, G12R, G12V and Q61) remains unclear. Furthermore, the clinical and molecular characteristics associated with these mutation subtypes remain not well defined. Methods: A retrospective review was conducted on patients with KRAS PDAC who underwent Next Generation Sequencing at Mayo Clinic between December 1, 2018 and December 1, 2021. Their somatic mutations, RNA expression, demographics, disease characteristics, therapies offered, and clinical outcomes were collected via chart review. Results on KRAS wt were reported previously; KRAS mt are reported here. Results: A total of 158 KRAS mt patients (at diagnosis: average age 63.8 years, 57% male, 88 (56%) Stage IV) were included. 10% of patients had KRAS Q61 mutation, 14% G12R, 30% G12V and 46% G12D. G12R had a longer overall survival (OS) compared to the others (median 24.8 vs 17.5 months, unadjusted hazard ratio (HR) 0.68, p=0.05), particularly in patients with localized disease at diagnosis (median 35.4 vs 28.3 months, p=0.08). Among patients with metastatic disease at diagnosis, G12V had the lowest OS (median 9.8 vs 12.4 months, unadjusted HR 1.8, p=0.02). 137 (87%) patients had at least one pathogenic somatic variant, with statistically significant differences in SMAD4, TP53, MYC, RB1, KMT2D, RBM10, RNF43, KDM6A, KMT2C, RBM10, LRP1B, PIK3CA, and SMARC among the KRAS mt subtypes. 82 (52%) patients had at least one RNA expression variant, with statistically significant differences in CCND1, CCNE1, HRAS, MET, EGFR, and ERB3 among KRAS mt subtypes. Between these subtypes, there were no statistically significant differences in TMB value, location of PDAC or subsequent metastasis, lines of treatment (average 2.3), age at diagnosis, or gender. Conclusions: KRAS mt subtypes may confer different PDAC phenotypes. In our cohort, G12R is associated with improved OS while G12V correlates with worse prognosis in de novo metastatic disease. Additionally, there are differences in genomic variations and RNA expression between the KRAS mt subtypes. To further examine this, transcriptomic analysis is underway. [Table: see text]

TPS780 Background: Pancreatic adenocarcinoma is an aggressive malignancy with a limited number of therapeutic options. One subset of patients (up to 15%) carries germline and/or somatic mutations in homologous recombination repair genes, most notably BRCA1, BRCA2 and PALB2 amongst others, that confer sensitivity to PARP inhibition. Combinations of PARP inhibitors with anti-PD1 immunotherapy have shown activity in breast and ovarian cancer and have not yet been thoroughly studied in pancreatic cancer. Methods: We designed a single-arm phase 2 investigator-initiated study utilizing the combination of niraparib, a highly selective PARP inhibitor and a dostarlimab, an anti PD1 antibody, in the subset of pancreatic cancer patients with germline or somatic mutations in BRCA1/2, PALB2, BARD1, RAD51C, or RAD51D. Additional inclusion criteria include metastatic pancreatic adenocarcinoma, receipt of a platinum agent in 1st or 2nd line unless contraindicated, and at least 1 but not more than 2 prior lines of systemic therapy not including maintenance. Prior PARP inhibition is allowed, but not immediately prior to enrollment. Exclusion criteria include active unstable autoimmune disease or prior malignancy requiring active treatment within 2 years. Patients are treated with niraparib 200 mg orally once daily on days 1 through 21 of a 21 day cycle. Dostarlimab is administered IV 500 mg every 3 weeks for the 1st 4 cycles and then 1000 mg IV every 6 weeks subsequently. The primary endpoint of the study is the disease control rate at 12 weeks using standard iRECIST criteria. Twenty patients will be enrolled to ensure 19 evaluable. The design has 80% power to detected improvement in disease control rate from 25-50% with significance level of 0.10. Descriptive factors include gene mutated for inclusion, germline/somatic, and platinum refractoriness. Given the size of the study along with genetic heterogeneity there will be no interim analysis. Patients are being enrolled at 3 Mayo clinic sites in Rochester Minnesota, Phoenix Arizona, Jacksonville Florida. To date, 13 patients have been enrolled across all 3 sites. Full accrual is anticipated by early 2023. Correlative studies include genomic characterization of baseline tumors, assessment of immune infiltration of tumor microenvironment, tumor collection for organoid/xenograft, and serial circulating cell-free DNA and immune biomarkers. Trial Identifiers: NCT04493060, Mayo: MC1841. Supported by Glaxo Smith Kline. Clinical trial information: NCT04493060 .

BACKGROUND A patient-derived organoid (PDO) platform may serve as a promising tool for translational cancer research. In this study, we evaluated PDO’s ability to predict clinical response to gastrointestinal (GI) cancers. METHODS We generated PDOs from primary and metastatic lesions of patients with GI cancers, including pancreatic ductal adenocarcinoma, colorectal adenocarcinoma, and cholangiocarcinoma. We compared PDO response with the observed clinical response for donor patients to the same treatments. RESULTS We report an approximately 80% concordance rate between PDO and donor tumor response. Importantly, we found a profound influence of culture media on PDO phenotype, where we showed a significant difference in response to standard-of-care chemotherapies, distinct morphologies, and transcriptomes between media within the same PDO cultures. CONCLUSION While we demonstrate a high concordance rate between donor tumor and PDO, these studies also showed the important role of culture media when using PDOs to inform treatment selection and predict response across a spectrum of GI cancers. TRIAL REGISTRATION Not applicable. FUNDING The Joan F. & Richard A. Abdoo Family Fund in Colorectal Cancer Research, GI Cancer program of the Mayo Clinic Cancer Center, Mayo Clinic SPORE in Pancreatic Cancer, Center of Individualized Medicine (Mayo Clinic), Department of Laboratory Medicine and Pathology (Mayo Clinic), Incyte Pharmaceuticals and Mayo Clinic Hepatobiliary SPORE, University of Minnesota-Mayo Clinic Partnership, and the Early Therapeutic program (Department of Oncology, Mayo Clinic).

Abstract Despite development of personalized treatments GI cancer like pancreatic ductal adenocarcinoma (PDAC) and colorectal cancer (CRC) remain dismal outcomes. While some patients are potentially curable with surgery and chemotherapy, most unresectable cases are invariably lethal. To advance patient care, we rely on clinical trials to test new therapeutic approaches. Here, we assume that the highest dose of a drug that does not cause severe toxicities is optimal for cancer treatment. However, this treatment strategy, in many cases, may be more harmful for the patient. Adopting principles from the field of evolutionary biology and pest management could offer more effective strategies that can be used for patients with metastatic PDAC and CRC. Resistance mechanisms are assumed to come with an energy cost, making the organism/cell less fit than others in the population. When high doses of treatment are applied, it results in a significant selection gradient by eliminating sensitive populations, freeing resources and facilitating resistant population growth. Such evolutionary dynamics and interactions within the tumor microenvironment can be modeled and exploited, in the form of adaptive strategies, for treatment of CRC and PDAC. It is our central hypothesis that integration of evolutionary dynamics and into PDAC and CRC treatment will delay emergence of resistance, enhance quality of life, and improve clinical outcomes. Our preliminary observations in co-cultured drug sensitive and resistant cell containing spheroids show that a higher proportion of drug sensitive cells inhibits the proliferation of drug resistant cells over time, in the presence of chemotherapeutic agents 5-FU and Oxaliplatin. We also demonstrate a role for the MLL family of histone methyltransferases in the epigenetic regulation of genes involved in chemoresistance. RNA-seq data has shown differential gene expression in metabolic genes regulated by histone methyltransferase KMT2A, KM2TB and KMT2D knockout (KO) cells including Gstt1, CYP26B1 and PYGL. In addition to this, KMT2A, KM2TB and KMT2D KOs show differential sensitivity to chemotherapeutic agents Gemcitabine, SN-38, 5-FU and Oxaliplatin. Further, analysis of KMT2A, KM2TB and KMT2D KO cells will provide mechanistic insight of the epigenetic regulation of metabolic patterns in drug resistant cells. This strategy would provide an approach for reducing exposure to toxic drugs, improving patient quality of life and renewing hope for prolonged control of metastatic PDAC and CRC. This proposal represents a bedside-to-bench-to-bedside project; identifying a shortcoming in how we currently treat PDAC and CRC patients, developing solutions in the lab and ultimately translating such strategies to benefit patients. Citation Format: Glancis Luzeena Raja Arul, Ezequiel Tolosa, Ryan M. Carr, Martin E. Fernandez-Zapico. Modeling evolutionary therapy for GI malignancies [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr B002.