Citations

Abstract Pancreatic ductal adenocarcinoma (PDAC) is a deadly malignancy with a dismal 5-year survival rate, highlighting the urgent need to improve drug response and overcome primary or acquired (secondary) resistance to conventional chemotherapy. Glycogen synthase kinase 3β (GSK-3β) is a target in PDAC and the GSK-3 inhibitor, elraglusib, has been shown to improve chemosensitivity of PDAC and survival in preclinical cancer models. In addition, data from phase II clinical trials in patients with previously untreated metastatic pancreatic cancer is demonstrating preliminary evidence of clinical benefit in patients receiving a combination of gemcitabine/nab-paclitaxel. While this early evidence is highly encouraging, the biological determinants of elraglusib response are unknown. Using genome wide CRISPR/Cas9 library screening, we identify aurora kinase A (AURKA), an oncogenic kinase with major roles in mitosis, as a critical regulator for elraglusib sensitivity. Elraglusib treatment activates AURKA by inducing a G2/M cell cycle arrest. We show that knocking out AURKA reduces the phosphorylation of polo like kinase 1 (PLK1), arresting cells in mitosis, and leading to mitotic catastrophe and significant apoptosis after elraglusib treatment. Strikingly, the AURKA inhibitor, alisertib, works synergistically with elraglusib to inhibit PDAC cell line growth and induce apoptosis. In summary, our results demonstrate that targeting AURKA is an effective approach to sensitize PDAC tumors to elraglusib. Citation Format: Li Ding, Easton Maeder, Cheng Zhang, Taylor Weiskittel, Daniel Schmitt, Andrew Mazar, Hu Li, Daniel Billadeau. Genome wide CRISPR/Cas9 library screening identifies aurora kinase A as a regulator of elraglusib sensitivity in 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 4658.

Abstract Given the morbidity and mortality associated with colorectal cancer, novel biomarkers are clearly warranted, especially for early detection, particularly for advanced adenomas. An earlier 1317-plex aptamer-based proteomic screen of stool proteins revealed 92 proteins to be significantly elevated in CRC stool, with the most discriminatory proteins being MMP9, haptoglobin, myeloperoxidase, fibrinogen, and adiponectin (PMID: 34117903). Results from a recent 2000-plex proteomic screen of CRC stools are detailed below, while a 11,000-plex aptamer based proteomic screen is in progress. Comprehensive proteomic screening revealed 116 proteins to be differentially expressed in CRC stool compared to control stool, with 45 being elevated 2-fold or higher. 37 of these proteins were ELISA validated in 3 independent cohorts. Stool MMP-8, MMP-9, Hemoglobin, PGRP-S, Haptoglobin, Myeloperoxidase and Fibrinogen emerged as being most discriminatory for distinguishing CRC from healthy controls (AUC: 0.91-0.95), while Stool Fibrinogen, MMP-9, Hemoglobin, MMP-8, and PGRP-S best distinguished advanced adenoma from healthy control (HC) stool, with stool Fibrinogen topping the list with an ROC AUC value of 0.86, as detailed in Table 1. Functional pathway analysis revealed a significant over-representation of pathways related to anti-oxidant activity, integrin/receptor binding, cytokines, blood coagulation, and lipoprotein biosynthesis in patients with CRC compared to HC. Nuclear Factor IC (NFIC) and IKZF2 were identified as key regulators of the molecular cascades over-represented in CRC. Stool Fibrinogen, MMP-8, MMP-9, PGRP-S, Haptoglobin, and Myeloperoxidase emerge as promising biomarkers for distinguishing CRC/advanced adenomas/healthy stools, outperforming Hemoglobin. Thus, comprehensive proteomics and independent ELISA validation have uncovered novel stool biomarkers for identifying CRC and advanced adenomas, that warrant further head to head comparison against current diagnostic tests. Citation Format: Chandra Mohan, Kamala Vanarsa, Jessica Castillo, Robert Bresalier, Nicholas Chia. 11,000-plex aptamer based proteomics of colorectal cancer stools for the discovery of novel disease biomarkers [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 1845.

Abstract Introduction: Screening for prostate cancer (PCa) with molecular markers is hindered by low tumor allele fraction (TAF) in liquid biopsy samples such as blood or urine. Others have suggested that tumor allele enrichment can be achieved by evaluating fragment-level methylation patterns generated by next generation sequencing (NGS). Here, we test this concept using target capture NGS on cfDNA from prediagnostic collected urine samples to discriminate PCa from otherwise healthy men. Methods: Buffered urines were collected from 23 patients with biopsy confirmed PCa (Gleason score 6-9) and 24 otherwise healthy age matched cancer-free controls. cfDNA was isolated and enzymatic methyl-seq libraries were prepared and enriched by hybrid capture using probes mapping to 197 differentially methylated regions (DMRs) from a previous PCa/normal tissue marker discovery study in our lab. These DMRs were subsequently vetted independently using a methylome-wide dataset from a cohort of 36 clean and disease control urines to ensure low non-cancer background signal (<1%). Indexed libraries were sequenced at 560X deduplicated coverage and fragment-level CpG methylation information was extracted from individual sample .bam files. Mapped sequencing reads exhibiting concordant methylation were used to derive a quantitative α-score. Reads had to contain at minimum 5 CpGs and have an α-value (% 5mC per read) > 60%. Positivity for the 197 markers required an α-score greater than 6 sigma (σ) above the mean of the control arm. Values were variance-adjusted to ensure equal weighting. Beta (β) analysis (mean % 5mC across all reads) of the data was also performed for comparison. Results: Of the 197 markers, 187 were positive for one or more PCa patients. Tumor-derived fragments were detected in 22 of 23 cases, which included 8 G-6, 9 G-7, 2 G-8, and 3 G-9 patients. 1 G-7 was missed, however the sequencing coverage for this sample was significantly lower than the others due to poor library enrichment. 2 of the 24 healthy controls were positive, one with extremely high fragment counts. Upon re-review of the full control cohort, this patient had been diagnosed with bladder cancer 2 years after urine collection. The 2nd patient had was diagnosed with lung cancer in a similar timeframe. The other 22 confirmed cancer-free controls had α-scores below the 6σ threshold. Using a co-captured reference gene (B3GALT6) to mimic genomic equivalents, the TAFs ranged from 0.015% to 8%. β analysis of the data detected only 13 PCa patients (>6σ) and marker positivity was lower than the fragment-level approach. Conclusion: Target capture NGS coupled with fragment-level analysis is a rational approach for sensitive and specific detection of low tumor-derived DNA in liquid biopsy samples. For PCa assay in urine, we were able to uncover positivity in cancer patients approaching 1 in 10,000 ctDNA dilution levels. These results warrant further validation studies with this and other cancers. Citation Format: Tibor Bedekovics, William R. Taylor, Zhifu Sun, Saurabh Baheti, Xiaoming Cao, Kelli N. Burger, Karen A. Doering, Patrick H. Foote, Benjamin Gochanour, Douglas, W. Mahoney, Matthew T. Gettman, John B. Kisiel. Detection of prostate cancer in urine by fragment-level DNA methylation analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2424.

Abstract Glioblastoma (GBM) is the most common and lethal primary brain tumor in adults. Within the tumor, there is a subtype of cells deemed brain tumor initiating cells (BTICs), which contribute to tumor progression, therapy resistance, and tumoral heterogeneity. The tumor microenvironment, surrounding tumors, contains an ecosystem of cells in which BTICs can interact with and further promote tumor progression. In the lateral wall of the lateral ventricles, the neurogenic niche of the subventricular zone (SVZ), contains neural progenitor cells (NPCs) that self-renew and generate highly migratory neuroblasts. Interestingly, GBM tumors proximal to the SVZ are more proliferative, migratory, and negatively impact the survival of patients. We have previously observed that the presence of GBM induces reciprocal changes to the SVZ altering its neurogenic capacity and resulting in a more proliferative tumor. BTICs share similar self-renewal capacity to NPCs and may exert intercellular communication resulting in increased malignancy features. The mechanisms of intercellular communication, present in the SVZ include paracrine, autocrine, direct cell contact, gap junctions, nanotubes, and more recently extracellular vesicles (EVs). However, the exact mechanisms of how BTICs communicate with NPCs is not well understood. EVs are a heterogenous group of cell-derived membranous structures that serve as means of intercellular communication, allowing for cells to exchange proteins, lipids, RNA, and other genetic material. Cancer cells release higher amounts of EVs than non-malignant cells, and these EVs help communicate with other nearby cells, leading to promotion of tumorigenesis. We have observed that BTICs-derived EVs increase the proliferation of human NPCs, while altering their morphology and expression of stem cell markers. These effects are not observed when NPCs are treated with vesicle-free BTIC-derived secreted factors. To investigate the distinctions between BTIC secreted factors and protein cargo contained in BTIC-EVs, we employ the proximity protein labelling system, TurboID, and express this system in BTIC-EVs. The overarching goal of this project is to characterize BTIC-derived EV cargo to identify proteins that modify the GBM tumor microenvironment. We hypothesize that the phenotype of non-cancer NPCs is altered by distinct protein cargo contained in BTIC-derived EVs. The results of these experiments will help us to elucidate what BTIC-specific EV cargo impacts the tumor microenvironment, with the potential of revealing therapeutic targets for GBM. Citation Format: Marissa Russo, Maria Jose Ulloa Navas, Emily Norton-Ramos, Alfredo Quiñones Hinojosa, Hugo Guerrero Cazares. Exploring the differences between brain tumor initiating cell extracellular vesicles and secreted factors that influence 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 2776.

Abstract Melanoma is a uniquely difficult cancer to treat due to complex tumor heterogeneity and resistance, where upon dissemination, survival drops to less than 17%. Drug resistance has arisen for the current standard of care and combinatorial therapies, expediting the need for new efficacious agents. The lack of physiologically relevant preclinical models has impeded the development of these therapeutics. Potential melanoma drugs are typically assayed using cell lines on tissue culture plastic, then tested for in vivo efficacy and side effects in animals. This paradigm is inherently unsuitable for the generation of effective therapies as typical cell culture platforms fail to replicate the complex microenvironments known to play critical roles in tumor pathology and rodent models are prohibitively expensive for optimizing novel and combination therapies. Thus, our goal is to synthesize tissue-engineered melanoma models using biomimetic polymers that recapitulate patient tumor characteristics to assess combination and novel therapies that attenuate resistance and disrupt metastatic processes. In this study, patient melanoma cells, which were unable to recapitulate drug responses on traditional cell culture platforms, were cultured in a controlled spatial and temporal manner on polyacrylamide hydrogels. The hydrogel scaffolds feature stiffnesses spanning that of physiological tissue, with microcontact printed human fibronectin for biomimetic protein presentation to create a microtumor array. Cells cultured on the hydrogel showed a 2.5-fold increase in expression of the cancer stem cell biomarkers, CD271 and ABCB5, which play a key role in melanoma survival and recurrence, compared to cells cultured on plastic or glass substrates. Further study identified BRAF mutant, drug resistant patient cells, regained resistance to standard of care targeted therapies, trametinib and dabrafenib. Through hydrogel microarrays featuring physiological similarities, the technology has enabled the exploration of heterogeneous cell populations with novel and combinatorial therapeutics. Citation Format: Yi L. Liu, Justyna Gleba, Chantal Kopecky, Matthew Pawlush, John A. Copland, Kristopher A. Kilian. Biomimetic hydrogels at physiological stiffness reprogram patient derived melanoma cells [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 6896.

Abstract Mayo Clinic has developed 111 GBM PDXs from newly diagnosed (72 PDX) and recurrent (39 PDX) patients. This large collection of PDXs provides a broad representation of genetic heterogeneity seen in patients. GBM PDXs that perform well in both in vitro and in vivo settings can be extensively utilized in the preclinical setting for downstream analysis. Based on 20 years of experience, we have defined the attributes that best enable preclinical use of our GBM PDX models. Among them are short-term in vitro culturing performance, large scale genomic evaluation data, benchmarked responses to standards of care, and median time to moribund for untreated orthotopic tumors. PDXs with prolonged survival timelines delay study readouts and, in some situations, confound efficacy results due to age-related animal decline. Setting median survival thresholds as part of the upfront experimental design allows for more timely study readouts that are unaffected by these confounding variables. Our preferred cutoff for the Mayo GBM PDX collection is 70 days median survival (n=64). Using this 64 PDX line panel, regimens expected to double survival would produce results within 4-5 months. This timeframe is well within the range of robust health for athymic nude mice. This 64-line collection features both newly diagnosed (nGBM; n=42) and recurrent (rGBM; n=22) tumors. MGMT promoter methylation status was determined by qMS-PCR (25 methylated, 37 unmethylated, 2 indeterminate). Available WES (n=62) and RNAseq (n=42) data, along with our tissue microarray (n=42), are critical resources for biomarker-based evaluations aimed at defining patient populations that are most likely to benefit from a given therapeutic. From these data, the molecular subtypes available include 26 classical, 14 proneural, and 3 mesenchymal. Twenty-seven of these 64 PDX models have also been successfully cultured from fresh as well as cryopreserved cell stocks to further expand their experimental value. Correlative clinical data including diagnosis and treatments are also available (n=61). Current standards of care for GBM include radiation, temozolomide, and bevacizumab. Defining sensitivity to these therapies is an important first step for evaluating the integration of novel therapeutics with these standards. Since the creation of our GBM PDX collection, efficacy of these therapies has been evaluated as follows: RT 26 PDXs, TMZ 20 PDXs, and Avastin 23 PDXs. The Mayo Clinic GBM PDX collection provides an important platform for preclinical evaluation of novel therapeutics. Through careful selection of PDX lines with favorable growth characteristics and known genetic features, researchers can select the most relevant models for their study. This approach will enable more meaningful preclinical work in the hopes of providing more tangible clinical benefits for GBM patients. Citation Format: Danielle M. Burgenske, Ann C. Mladek, Katrina K. Bakken, Zeng Hu, Brett L. Carlson, Paul A. Decker, Jeanette E. Eckel-Passow, Jann N. Sarkaria. Defining critical features for successful preclinical use of glioblastoma patient-derived xenografts (PDX) models for therapeutic assessment and clinical trial development [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 6897.

Abstract Background Cholangiocarcinoma (CCA) is a heterogeneous malignancy. Platinum-based chemotherapy (Gemcitabine and Cisplatin) has been the standard treatment for over a decade and is the base for the current immunotherapy combinations. Response rates are typically between 20-30%. Herein, we present outcomes of preclinical efficacy trials on CCA PDX models in correlation with baseline multiomics profiling of CCA patient-derived xenograft (PDX) models to identify molecular features associated with response. Methods Tumor samples from twenty-eight CCA PDX were used to isolate RNA and protein to be included in multiomics analysis (Phosphoproteomics, Proteomics, and Transcriptomics). A subset of PDX models were treated with various doses of Gemcitabine and Cisplatin. The Median Efficacy Index (MEI) was calculated as the ratio of the difference in median of delta in tumor volume at the last day of the study between the treatment and the control arms divided by the median of delta in tumor volume of the control at the last day of the treatment (positive= growth, negative=inhibition, and 0=no efficacy). A Hierarchical All-Against-All algorithm was utilized to compare multiomics features to the MEI and pathway analysis completed for identified molecular features. Results After conducting preclinical efficacy trials, the five tested CCA PDX models were classified into sensitive, moderately sensitive, and resistant models based on the MEI on each treatment arm. The top up-regulated genes were identified for Gemcitabine response (SRPK2, GLK2, and RIOK2) and Cisplatin response (NTRK1, PRPF4B, and SRPK2). The top up-regulated genes related to Gemcitabine resistance were NTRK1, PIP5K1C, and CSNK2A2, while those related to Cisplatin resistance were SRPK1, PRPF4B, and CSNK2A1. Conclusion Cholangiocarcinoma multiomics signatures can predict therapeutic response to standard-of-care chemotherapy in preclinical models. Novel mechanisms of Gemcitabine and Cisplatin resistance were identified related to NTRK1, SRPK1 and SRPK2. Resistant signatures will be challenged with the appropriate targeted therapies on the resistant CCA PDX models. Citation Format: Amro M. Abdelrahman, Danielle M. Carlson, Erik Jessen, Dong-Gi Mun, Isaac Lynch, Alessandro Fogliati, Stella Konadu Adjei Antwi, Aushinie Abeynayake, Akhilesh Pandey, Mark J. Truty, Gregory J. Gores, Rory L. Smoot. Pretreatment multiomics in conjunction with preclinical trials on patient-derived xenograft models of cholangiocarcinoma can identify chemotherapy response signatures [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6912.

Abstract Background: Though widely recognized in cancer pathogenesis, inflammatory pathways of allostatic load remain vaguely understood. A partial explanation may be found within the realm of food insecurity and micronutrient inadequacies, defined as nutrient intake less than the estimated average requirement. Many micronutrient deficiencies contribute to pro-inflammatory and immunocompromised milieus. Inadequacies, however, which may present without overt symptoms, are not currently well studied. The purpose of this study was to examine relationships between known inflammation-associated nutritional biomarkers of micronutrients and biomarker variables of allostatic load. Methods: Using NHANES 2017/2018 surveys, adults > 18 years without renal or hepatic disorders, pregnancy, alcohol, or supplement use were included. Plasma levels of vitamins A, B9, C, D, E, calcium (Ca), ferritin (Fe), phosphorus (P), potassium (K) and sodium (Na) were grouped into deficiency, inadequate and adequate groups based on clinically recognized standards. Micronutrient prevalence was assessed and variables of allostatic load [blood pressure, glucose, albumin, creatinine, red cell distribution width (RDW), high density lipoprotein (HDL), low density lipoprotein (LDL), cholesterol and triglycerides] were analyzed for mean differences among micronutrient groups, food security and poverty. Results: From 3,317 unique participants, inadequacy prevalence percentages were quantified as: vitamins A (0.4%), B9 (12.2%), C (58.3%), D (39.6%), E (21.0%), P (11.4%), K (3.4%), Na (24.2%), Ca (59.5%), and Fe (37.4%) [p < 0.001]. Statistically significant differences were identified in age [C, D, E, Ca, Fe, P, Na (p < 0.004)], race/ethnicity [B9, C, D (p < 0.006)], gender [C, E, Ca, Fe, P, K, Na (p < 0.018)], poverty [A, B9, C, D, E, Fe, K (p < 0.025)], and food security [B9, C, D, E, P (p < 0.032)]. Associations to allostatic load were discovered in: albumin [A, C, D, Ca, Fe, P, Na (p < 0.025)], glucose [C, E, Fe, P, Na (p < 0.009)], HDL [C, D, E, Fe, P, K (p<0.045)], LDL [E, Ca, Fe, Na (p<0.028)], creatinine [C, D, Ca, Fe (p<0.001)], triglycerides [B9, D, E, Fe (p<0.033)], cholesterol [C, D, E, Ca, Fe, Na (p<0.006)], B/P [C, E, Fe, P, Na (p < 0.035)], and RDW [C, D, Ca, Fe (p < 0.001)]. Poverty was significantly associated with all variables of allostatic load (F = 2.85, p = 0.002). Food security was significantly correlated with albumin (p < 0.001), glucose (p = 0.005) and HDL (p < 0.001). Conclusion: Allostatic load, poverty, and food security were significantly associated with subclinical micronutrient statuses, which may not present with signs of deficiency and are not currently well assessed. Similarly, poverty was significantly associated with all variables of allostatic load, though food security was only identified to be associated with albumin, glucose, and HDL, suggesting that food security may not be currently adequately defined for surveillance. Citation Format: Jennifer M. Crook, Eunkyung Lee, Opeyemi Bolajoko, Rui Xie. Poverty, food insecurity, and nutritional inflammatory mediators of allostatic load [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 2198.

Abstract Background: Plant-based diet is recommended by multiple cancer survivorship guidelines and was reported to be associated with better survival among patients with non-metastatic colorectal cancer. However, the association between plant-based diet and survival in metastatic colorectal cancer is unknown. Methods: Using an NCI-sponsored systemic therapy trial conducted from 2005 to 2015 (CALGB/SWOG 80405), we included 1,279 patients who completed validated food frequency questionnaires at the initiation of treatment for metastatic colorectal cancer. To emphasize different impact of healthful plant foods, less healthful plant foods, and animal foods, we used 18 food groups to calculate three plant-based indexes (ranges: 18-90 points): overall plant-based diet index (PDI), healthful plant-based diet index (hPDI), and unhealthful plant-based diet index (uPDI). The primary outcome was overall survival, and the secondary outcome was progression-free survival. We estimated the associations of three indexes (quintiles) with survival using multivariable Cox proportional hazards regression. Results: Of 1,279 patients (median follow-up: 6.1 years), mean (SD) age at diagnosis was 58.8 (11.7) years, 57.4% were men, 85.6% were White, and 1,096 deaths and 1,201 events of progression occurred. The mean (SD) points of three indexes were 51.2 (6.3) for PDI, 51.1 (6.7) for hPDI, and 51.2 (8.1) for uPDI. Compared to the lowest quintile (Q1), the highest quintile (Q5) of PDI was significantly associated with better overall survival (HR: 0.80 [0.65-0.99]) and progression-free survival (HR: 0.80 [0.65-0.98]). Similar findings were observed for hPDI, but uPDI was not significantly associated with worse survival. Conclusions: Our findings suggest that plant-based diet is associated with better survival among patients with metastatic colorectal cancer, and plant-based dietary interventions should be considered for future trials in metastatic colorectal cancer. Table. Adjusted Associations of Plant-Based Diet with Survival in Metastatic Colorectal Cancer Q1 Q2 Q3 Q4 Q5 P for trend Overall Survival PDI 1.00 0.96 (0.80-1.16) 0.93 (0.77-1.14) 0.82 (0.67-0.99) 0.80 (0.65-0.99) 0.01 hPDI 1.00 0.95 (0.78-1.14) 0.94 (0.77-1.15) 0.86 (0.70-1.04) 0.84 (0.68-1.03) 0.07 uPDI 1.00 1.14 (0.95-1.39) 1.07 (0.87-1.31) 1.18 (0.97-1.45) 1.17 (0.95-1.45) 0.15 Progression-free Survival PDI 1.00 0.84 (0.70-1.01) 0.94 (0.78-1.14) 0.93 (0.77-1.12) 0.80 (0.65-0.98) 0.10 hPDI 1.00 0.86 (0.72-1.03) 0.83 (0.69-1.01) 0.80 (0.67-0.97) 0.80 (0.66-0.97) 0.03 uPDI 1.00 1.12 (0.94-1.34) 1.11 (0.91-1.34) 1.10 (0.91-1.34) 1.15 (0.94-1.41) 0.23 Citation Format: En Cheng, Fang-Shu Ou, Chao Ma, Alan P. Venook, Heinz-Josef Lenz, Eileen M. O’Reilly, Peter T. Campbell, Chaoyuan Kuang, Bette J. Caan, Kimmie Ng, Jeffrey A. Meyerhardt. Plant-based diet and survival among patients with metastatic colorectal cancer: Findings from CALGB/SWOG 80405 (Alliance) [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 2200.

Abstract The microbiome refers to the diverse community of microorganisms, including bacteria, viruses, fungi, and other microbes, that inhabit various parts of the human body, such as the skin, mouth, gut, and other mucosal surfaces. The role of the microbiome in cancer is a complex and evolving area of research. While much is still being learned, there is evidence suggesting that the microbiome can influence cancer development and progression in several ways. Some bacteria within the microbiome can produce substances that may be either carcinogenic or protective against cancer. For instance, the conversion of certain dietary components by gut bacteria can produce metabolites that may either promote or inhibit cancer development. Different cancers may be associated with specific alterations in the microbiome, for example, the gut microbiome has been extensively studied in relation to colorectal cancer, with certain bacterial species potentially contributing to the development of this cancer. However, the role of microbiome in Pancreatic cancer is still not extensively studied, henceforth, we did a preliminary study to identify novel bacterial communities around pancreatic cancer microbiome by 16SrDNA sequencing in human pancreatic cancer xenograft model mice. Isolating total genomic DNA from the pancreatic model mice feces, 16SrDNA PCR was done using specific primers and the amplicon obtained as PCR product was confirmed by standard DNA gel electrophoresis with a 1 kb standard ladder to be 1.5kb in size universal for all bacterial 16SrDNA. The amplicon was then sent for Next Generation Sequencing at Zymo Research Corporation (CA). The resultant DNA sequences were analyzed by bioinformatics studies and their phylogeny identified by comparing with 16SrDNA data base. Differential abundance of the bacteria’s of the genera Lachnoclostridium, Robinsoniella, Alistipes, Akkermansia and Lactobacillus were observed analyzing the data along with other bacterial communities. We are currently continuing the project to identify more bacterial communities of significance in the pancreatic cancer microbiome and investigating the role and significance of these bacterial communities in pancreatic cancer tumor microenvironment. Acknowledgement This study was done by a joint collaboration between scientists and students of Elizabeth City State University (ECSU) campus of the University of North Carolina Systems and Mayo Clinic, Jacksonville. This research is supported by the NIH-NIGMS grant#T34GM100831-10 to Dr. H. Banerjee and a University of North Carolina General Administration Grant to Dr. Colby Hunter at ECSU. Citation Format: Hirendra N. Banerjee, Colby Hunter, Narendra Banerjee, Karrington Perry, Khadimou Dia, Anasua Banerjee, Santanu Bhattacharya, Hari Krishnareddy Rachamala, Enfang Wang, Shamit Dutta. An investigation to identify the phylogeny of bacterial communities in the pancreatic cancer microbiome by 16SrDNA sequencing and bioinformatic analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2795.