Myofibroblastic cancer-associated fibroblast subtype heterogeneity in pancreatic cancer

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) has a fibrotic stroma that has both tumor-promoting and tumor-restraining properties. Different types of cancer-associated fibroblasts (CAFs) have been described. Here, we investigated whether CAFs within the same subtype exhibit heterogeneous functions.

METHODS

We evaluated the gene and protein expression differences in two myofibroblastic CAF (myCAF) lines using single-cell and bulk RNA-sequencing. We utilized proliferation and migration assays to determine the effect of different CAF lines on a tumor cell line.

RESULTS

We found that myCAF lines express an activated stroma subtype gene signature, which is associated with a shorter survival in patients. Although both myCAF lines expressed α-smooth muscle actin (α-SMA), platelet-derived growth factor-α (PDGFR-α), fibroblast-activated protein (FAP), and vimentin, we observed heterogeneity between the two lines. Similarly, despite being consistent with myCAF gene expression overall, heterogeneity within specific genes was observed. We found that these differences extended to the functional level where the two myCAF lines had different effects on the same tumor cell line. The myCAF216 line, which had slightly increased inflammatory CAF-like gene expression and higher protein expression of α-SMA, PDGFR-α, and FAP was found to restrain migration of tumor cells.

CONCLUSIONS

We found that two myCAF lines with globally similar expression characteristics had different effects on the same tumor cell line, one promoting and the other restraining migration. Our study highlights that there may be unappreciated heterogeneity within CAF subtypes. Further investigation and attention to specific genes or proteins that may drive this heterogeneity will be important.

First-in-Class Humanized Antibody against Alternatively Spliced Tissue Factor Augments Anti-Metastatic Efficacy of Chemotherapy in a Preclinical Model of Pancreatic Ductal Adenocarcinoma

Alternatively spliced tissue factor (asTF) promotes the progression of pancreatic ductal adenocarcinoma (PDAC) by activating β1-integrins on PDAC cell surfaces. hRabMab1, a first-in-class humanized inhibitory anti-asTF antibody we recently developed, can suppress PDAC primary tumor growth as a single agent. Whether hRabMab1 has the potential to suppress metastases in PDAC is unknown. Following in vivo screening of three asTF-proficient human PDAC cell lines, we chose to make use of KRAS G12V-mutant human PDAC cell line PaCa-44, which yields aggressive primary orthotopic tumors with spontaneous spread to PDAC-relevant anatomical sites, along with concomitant severe leukocytosis. The experimental design featured orthotopic tumors formed by luciferase labeled PaCa-44 cells; administration of hRabMab1 alone or in combination with gemcitabine/paclitaxel (gem/PTX); and the assessment of the treatment outcomes on the primary tumor tissue as well as systemic spread. When administered alone, hRabMab1 exhibited poor penetration of tumor tissue; however, hRabMab1 was abundant in tumor tissue when co-administered with gem/PTX, which resulted in a significant decrease in tumor cell proliferation; leukocyte infiltration; and neovascularization. Gem/PTX alone reduced primary tumor volume, but not metastatic spread; only the combination of hRabMab1 and gem/PTX significantly reduced metastatic spread. RNA-seq analysis of primary tumors showed that the addition of hRabMab1 to gem/PTX enhanced the downregulation of tubulin binding and microtubule motor activity. In the liver, hRabMab1 reduced liver metastasis as a single agent. Only the combination of hRabMab1 and gem/PTX eliminated tumor cell-induced leukocytosis. We here demonstrate for the first time that hRabMab1 may help suppress metastasis in PDAC. hRabMab1's ability to improve the efficacy of chemotherapy is significant and warrants further investigation.

Efficient computation of high-dimensional penalized generalized linear mixed models by latent factor modeling of the random effects

Modern biomedical datasets are increasingly high-dimensional and exhibit complex correlation structures. Generalized linear mixed models (GLMMs) have long been employed to account for such dependencies. However, proper specification of the fixed and random effects in GLMMs is increasingly difficult in high dimensions, and computational complexity grows with increasing dimension of the random effects. We present a novel reformulation of the GLMM using a factor model decomposition of the random effects, enabling scalable computation of GLMMs in high dimensions by reducing the latent space from a large number of random effects to a smaller set of latent factors. We also extend our prior work to estimate model parameters using a modified Monte Carlo Expectation Conditional Minimization algorithm, allowing us to perform variable selection on both the fixed and random effects simultaneously. We show through simulation that through this factor model decomposition, our method can fit high-dimensional penalized GLMMs faster than comparable methods and more easily scale to larger dimensions not previously seen in existing approaches.

Integrated single-dose kinome profiling data is predictive of cancer cell line sensitivity to kinase inhibitors

Protein kinase activity forms the backbone of cellular information transfer, acting both individually and as part of a broader network, the kinome. Their central role in signaling leads to kinome dysfunction being a common driver of disease, and in particular cancer, where numerous kinases have been identified as having a causal or modulating role in tumor development and progression. As a result, the development of therapies targeting kinases has rapidly grown, with over 70 kinase inhibitors approved for use in the clinic and over double this number currently in clinical trials. Understanding the relationship between kinase inhibitor treatment and their effects on downstream cellular phenotype is thus of clear importance for understanding treatment mechanisms and streamlining compound screening in therapy development. In this work, we combine two large-scale kinome profiling data sets and use them to link inhibitor-kinome interactions with cell line treatment responses (AUC/IC50). We then built computational models on this data set that achieve a high degree of prediction accuracy (R2 of 0.7 and RMSE of 0.9) and were able to identify a set of well-characterized and understudied kinases that significantly affect cell responses. We further validated these models experimentally by testing predicted effects in breast cancer cell lines and extended the model scope by performing additional validation in patient-derived pancreatic cancer cell lines. Overall, these results demonstrate that broad quantification of kinome inhibition state is highly predictive of downstream cellular phenotypes.

Sub-Cluster Identification through Semi-Supervised Optimization of Rare-Cell Silhouettes (SCISSORS) in single-cell RNA-sequencing

MOTIVATION

Single-cell RNA-sequencing (scRNA-seq) has enabled the molecular profiling of thousands to millions of cells simultaneously in biologically heterogenous samples. Currently, the common practice in scRNA-seq is to determine cell type labels through unsupervised clustering and the examination of cluster-specific genes. However, even small differences in analysis and parameter choosing can greatly alter clustering results and thus impose great influence on which cell types are identified. Existing methods largely focus on determining the optimal number of robust clusters, which can be problematic for identifying cells of extremely low abundance due to their subtle contributions toward overall patterns of gene expression.

RESULTS

Here, we present a carefully designed framework, SCISSORS, which accurately profiles subclusters within broad cluster(s) for the identification of rare cell types in scRNA-seq data. SCISSORS employs silhouette scoring for the estimation of heterogeneity of clusters and reveals rare cells in heterogenous clusters by a multi-step semi-supervised reclustering process. Additionally, SCISSORS provides a method for the identification of marker genes of high specificity to the cell type. SCISSORS is wrapped around the popular Seurat R package and can be easily integrated into existing Seurat pipelines.

AVAILABILITY AND IMPLEMENTATION

SCISSORS, including source code and vignettes, are freely available at https://github.com/jr-leary7/SCISSORS.

Identifying patient profiles of disparate care in resectable pancreas cancer using latent class analysis

BACKGROUND AND OBJECTIVES: Disparities in pancreas cancer care are multifactorial, but factors are often examined in isolation. Research that integrates these factors in a single conceptual framework is lacking. We use latent class analysis (LCA) to evaluate the association between intersectionality and patterns of care and survival in patients with resectable pancreas cancer.

METHODS

LCA was used to identify demographic profiles in resectable pancreas cancer (n = 140 344) diagnosed from 2004 to 2019 in the National Cancer Database (NCDB). LCA-derived patient profiles were used to identify differences in receipt of minimum expected treatment (definitive surgery), optimal treatment (definitive surgery and chemotherapy), time to treatment, and overall survival.

RESULTS

Minimum expected treatment (hazard ratio [HR] 0.69, 95% confidence interval [CI]: 0.65, 0.75) and optimal treatment (HR 0.58, 95% CI: 0.55, 0.62) were associated with improved overall survival. Seven latent classes were identified based on age, race/ethnicity, and socioeconomic status (SES) attributes (zip code-linked education and income, insurance, geography). Compared to the referent group (≥65 years + White + med/high SES), the ≥65 years + Black profile had the longest time-to-treatment (24 days vs. 28 days) and lowest odds of receiving minimum (odds ratio [OR] 0.67, 95% CI: 0.64, 0.71) or optimal treatment (OR 0.76, 95% CI: 0.72, 0.81). The Hispanic patient profile had the lowest median overall survival-55.3 months versus 67.5 months.

CONCLUSIONS

Accounting for intersectionality in the NCDB resectable pancreatic cancer patient cohort identifies subgroups at higher risk for inequities in care. LCA demonstrates that older Black patients and Hispanic patients are at particular risk for being underserved and should be prioritiz for directed interventions.

Abstract 979: Development of a methylation-based classifier to identify pancreatic adenocarcinoma subtype

Background: Pancreatic ductal adenocarcinoma (PDAC) demonstrates variable prognosis and response to first-line FOLFIRINOX therapy depending on molecular subtype; patients with classical tumors showed a greater response compared to basal-like tumors. Identifying molecular subtype may inform treatment approaches, but current subtyping schemas rely on tumor biopsies which are invasive and can be technically challenging. Blood based epigenetic assays are commercially available, and identification of subtype-associated epigenetic modifications may provide a path toward blood-based PDAC molecular subtyping. We analyzed methylation levels and developed a subtype classifier using methylation data on PDAC tumors. Using this classifier, we then developed a methylation-specific qPCR assay to subtype PDAC tumors by analyzing methylation at particular sites in tumor DNA which may now be further adapted to more facile liquid biopsy approaches.

Methods: Using methylation data (n=150) from TCGA PAAD, we applied a random forest (RF) model followed by a k-Top Scoring Pairs (k-TSP) algorithm to develop a methylation site-based classifier that allows prediction of subtype by comparing methylation levels between paired sites. The classifier was validated on two independent datasets, including ICGC (n=82) and patient-derived xenografts (PDXs) (n=21). We designed methylation-specific qPCR primers for these sites and validated their specificity with fully methylated or fully unmethylated DNA. Using genomic DNA extracted from 10 PDAC PDXs of known molecular subtype, we obtained methylation levels at sites identified by the classifier via a SYBR Green-based qPCR assay. We then used our classifier to predict subtype of the PDX tumors.

Results: We validated our RF-kTSP methylation subtype classifier on two independent cohorts and predicted subtype using 20 methylation sites. In ICGC, we found balanced accuracy=0.94, AUROC=0.98, AU-PR=0.89. In PDX PDAC tumors, we found balanced accuracy=1, AUROC=1, AU-PR=1. We designed 14/20 primers for qPCR and confirmed specificity for methylated DNA. Using 14/20 methylation sites, we achieved 80% correct subtype prediction of 10 PDX tumors (5/5 basal-like, 3/5 classical).

Conclusion: We have developed a methylation-based classifier that accurately and replicably predicts PDAC subtype. We continue to develop a qPCR assay for PDAC subtype that so far has 80% accuracy using 14/20 probes. We are completing validation of the remaining 6 primers and correlating methylation levels at each site with those obtained from EPIC array methylation analysis. The long-term goal is to apply our complete set of primers in a digital droplet PCR assay that will be amenable for subtyping using circulating tumor DNA (ctDNA).

Citation Format: Zachary Schrank, Des Weighill, Hannah Thel, Hannah Trembath, Ashley Morrison, Jen Jen Yeh. Development of a methylation-based classifier to identify pancreatic adenocarcinoma subtype [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 979.

Abstract PR011: Proteomic profiling reveals subtype specific kinase expression in pancreatic cancer

We have previously identified two tumor specific molecular subtypes in pancreatic ductal adenocarcinoma (PDAC), basal-like and classical. Although basal-like tumors are found in less than 20% of patients, patients with basal-like tumors have a worse prognosis and are largely resistant to FOLFIRINOX chemotherapy. To identify targetable basal-like subtype specific vulnerabilities in PDAC, we utilized Multiplexed kinase Inhibitor Beads and Mass Spectrometry (MIB-MS) to profile the kinome in patient derived xenograft (PDX) models that recapitulate the tumor subtypes found in patients. MIB-MS results show that kinase expression is significantly associated with molecular subtype. Notably, basal-like tumors show increased expression of receptor tyrosine kinases (RTKs) including EGFR, MET, and IGF1R and MAP kinase members MEK2 and BRAF indicating activation of the MAP kinase signaling cascade. These RTKs including EGFR are also differentially expressed in primary patient tumors suggesting the true efficacy of EGFR and other kinase inhibitors in basal-like tumors may have been masked by the larger proportion of patients (>80%) with unresponsive classical tumors. Furthermore, inhibition of MAP kinase signaling with the MEK inhibitor trametinib results in kinome reprogramming exclusive to classical tumors. MIB-MS profiling reveals upregulation of TAOK3 and MEK3/6 indicating activation of p38 MAP kinase signaling as a classical subtype specific compensatory mechanism against MEK inhibition. Overall, these results present actionable basal-like subtype specific kinase targets by defining a novel subtype specific kinome in PDAC. Precision approaches in clinical trials are needed to determine if new and previously thought to be disappointing kinase inhibitors may be efficacious in patients with basal-like tumors.

Citation Format: Yi Xu, Ashley B. Morrison, Silvia G. Herrera, Michael P. East, Gary L. Johnson, Jen Jen Yeh. Proteomic profiling reveals subtype specific kinase expression in pancreatic cancer [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer; 2022 Sep 13-16; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2022;82(22 Suppl):Abstract nr PR011.

GM-CSF drives myelopoiesis, recruitment and polarisation of tumour-associated macrophages in cholangiocarcinoma and systemic blockade facilitates antitumour immunity

OBJECTIVE

Intrahepatic cholangiocarcinoma (iCCA) is rising in incidence, and at present, there are limited effective systemic therapies. iCCA tumours are infiltrated by stromal cells, with high prevalence of suppressive myeloid populations including tumour-associated macrophages (TAMs) and myeloid-derived suppressor cells (MDSCs). Here, we show that tumour-derived granulocyte-macrophage colony-stimulating factor (GM-CSF) and the host bone marrow is central for monopoiesis and potentiation of TAMs, and abrogation of this signalling axis facilitates antitumour immunity in a novel model of iCCA.

METHODS

Blood and tumours were analysed from iCCA patients and controls. Treatment and correlative studies were performed in mice with autochthonous and established orthotopic iCCA tumours treated with anti-GM-CSF monoclonal antibody.

RESULTS

Systemic elevation in circulating myeloid cells correlates with poor prognosis in patients with iCCA, and patients who undergo resection have a worse overall survival if tumours are more infiltrated with CD68+ TAMs. Mice with spontaneous iCCA demonstrate significant elevation of monocytic myeloid cells in the tumour microenvironment and immune compartments, and tumours overexpress GM-CSF. Blockade of GM-CSF with a monoclonal antibody decreased tumour growth and spread. Mice bearing orthotopic tumours treated with anti-GM-CSF demonstrate repolarisation of immunosuppressive TAMs and MDSCs, facilitating T cell response and tumour regression. GM-CSF blockade dampened inflammatory gene networks in tumours and TAMs. Human tumours with decreased GM-CSF expression exhibit improved overall survival after resection.

CONCLUSIONS

iCCA uses the GM-CSF-bone marrow axis to establish an immunosuppressive tumour microenvironment. Blockade of the GM-CSF axis promotes antitumour T cell immunity.

Truncated O-Glycan-Bearing MUC16 Enhances Pancreatic Cancer Cells Aggressiveness via α4β1 Integrin Complexes and FAK Signaling

Elevated levels of Mucin-16 (MUC16) in conjunction with a high expression of truncated O-glycans is implicated in playing crucial roles in the malignancy of pancreatic ductal adenocarcinoma (PDAC). However, the mechanisms by which such aberrant glycoforms present on MUC16 itself promote an increased disease burden in PDAC are yet to be elucidated. This study demonstrates that the CRISPR/Cas9-mediated genetic deletion of MUC16 in PDAC cells decreases tumor cell migration. We found that MUC16 enhances tumor malignancy by activating the integrin-linked kinase and focal adhesion kinase (ILK/FAK)-signaling axis. These findings are especially noteworthy in truncated O-glycan (Tn and STn antigen)-expressing PDAC cells. Activation of these oncogenic-signaling pathways resulted in part from interactions between MUC16 and integrin complexes (α4β1), which showed a stronger association with aberrant glycoforms of MUC16. Using a monoclonal antibody to functionally hinder MUC16 significantly reduced the migratory cascades in our model. Together, these findings suggest that truncated O-glycan containing MUC16 exacerbates malignancy in PDAC by activating FAK signaling through specific interactions with α4 and β1 integrin complexes on cancer cell membranes. Targeting these aberrant glycoforms of MUC16 can aid in the development of a novel platform to study and treat metastatic pancreatic cancer.

Aberrant Expression and Subcellular Localization of ECT2 Drives Colorectal Cancer Progression and Growth

ECT2 is an activator of RHO GTPases that is essential for cytokinesis. In addition, ECT2 was identified as an oncoprotein when expressed ectopically in NIH/3T3 fibroblasts. However, oncogenic activation of ECT2 resulted from N-terminal truncation, and such truncated ECT2 proteins have not been found in patients with cancer. In this study, we observed elevated expression of full-length ECT2 protein in preneoplastic colon adenomas, driven by increased ECT2 mRNA abundance and associated with APC tumor-suppressor loss. Elevated ECT2 levels were detected in the cytoplasm and nucleus of colorectal cancer tissue, suggesting cytoplasmic mislocalization as one mechanism of early oncogenic ECT2 activation. Importantly, elevated nuclear ECT2 correlated with poorly differentiated tumors, and a low cytoplasmic:nuclear ratio of ECT2 protein correlated with poor patient survival, suggesting that nuclear and cytoplasmic ECT2 play distinct roles in colorectal cancer. Depletion of ECT2 reduced anchorage-independent cancer cell growth and invasion independent of its function in cytokinesis, and loss of Ect2 extended survival in a Kras G12D Apc-null colon cancer mouse model. Expression of ECT2 variants with impaired nuclear localization or guanine nucleotide exchange catalytic activity failed to restore cancer cell growth or invasion, indicating that active, nuclear ECT2 is required to support tumor progression. Nuclear ECT2 promoted ribosomal DNA transcription and ribosome biogenesis in colorectal cancer. These results support a driver role for both cytoplasmic and nuclear ECT2 overexpression in colorectal cancer and emphasize the critical role of precise subcellular localization in dictating ECT2 function in neoplastic cells. SIGNIFICANCE: ECT2 overexpression and mislocalization support its role as a driver in colon cancer that is independent from its function in normal cell cytokinesis.

Abstract PO-055: Phase II clinical trial of subtype directed neoadjuvant therapy in patients with localized pancreatic cancer

Background: Preoperative (neoadjuvant) therapy has become the preferred treatment sequencing strategy for patients with localized pancreatic cancer. During neoadjuvant therapy, approximately 30% of patients will experience metastatic disease progression while on treatment. Therefore, tools to aid clinicians to select efficacious first-line chemotherapeutic regimens is a critical unmet need. The most common neoadjuvant chemotherapy regimens used are 5-fluorouracil/irinotecan/oxaliplatin (mFOLFIRINOX) and gemcitabine/nab-paclitaxel (GnP). There is growing data to suggest an association of pancreatic cancer subtype (classical versus basal-like) with treatment response to therapy. Recently, the translation of tumor subtyping to the clinic has been successfully achieved using the Purity Independent Subtyping of Tumors (PurIST) single sample classifier. We aim to assess the clinical response to pancreatic cancer subtype-directed therapy in patients with localized pancreatic cancer. Methods: This is a phase II, multicenter, single-arm clinical trial for previously untreated patients with localized (resectable or borderline resectable) pancreatic cancer. Patients will undergo endoscopic ultrasound guided biopsy of the primary tumor and PurIST classifier to determine classical versus basal-like subtype. Patients with classical subtype will be assigned to mFOLFIRINOX and patients with basal-like tumors will be assigned to GnP. Following two months of therapy, patients will be restaged with a computed tomography scan, carbohydrate antigen (CA19-9) levels, performance status assessment, and a repeat endoscopic ultrasound guided biopsy for research. The primary endpoint is composite clinical response as measured by radiographic response, CA19-9 decline, and performance status following two months of treatment. Correlative endpoints include blood-based biomarkers for association with clinical response and stroma-specific response to therapy. The study has enrolled 4 of the anticipated 41 patients at the time of submission. Clinical Trial information: NCT 04683315.

Citation Format: Susan Tsai, Erkut Borazanci, Margaret Gulley, Naim Rashid, Jason Merker, Abdul H. Khan, Phillip Chisholm, Bryan Hunt, Tamara Giorgadze, William Hall, Mandana Kamgar, Douglas B. Evans, Jen Jen Yeh. Phase II clinical trial of subtype directed neoadjuvant therapy in patients with localized pancreatic cancer [abstract]. In: Proceedings of the AACR Virtual Special Conference on Pancreatic Cancer; 2021 Sep 29-30. Philadelphia (PA): AACR; Cancer Res 2021;81(22 Suppl):Abstract nr PO-055.

Abstract PO-079: Proteomic profiling reveals subtype specific kinase expression in pancreatic cancer

Pancreatic adenocarcinoma (PDAC) remains an extremely lethal disease with few effective therapeutic options. Targeted therapy development has remained largely unsuccessful due to complex tumor heterogeneity and better molecular indicators of response are urgently needed. We have previously identified two distinct molecular tumor subtypes in PDAC, basal-like and classical, which are prognostic and dictate response to chemotherapy. We have also developed a patient derived xenograft (PDX) mouse model that maintains the integrity of patient tumor biology and recapitulates primary tumor subtypes in vivo. Here, we aim to utilize multiplexed kinase inhibitor beads and quantitative mass spectrometry (MIB-MS) to determine baseline kinase expression and adaptive kinome responses to therapy in PDAC PDX tumors. A total of 381 kinases were identified across all samples and tumor specific kinases were isolated by alignment to human peptides. Distinct kinase expression profiles were observed for basal-like and classical tumors. Basal-like tumors showed high expression of kinases involved in receptor tyrosine kinase activity, MAP kinase activity, and clathrin-dependent endocytosis. Classical subtype tumors showed increased expression of kinases involved in metabolism and cytoskeletal regulatory kinases. Differential protein expression was further validated by differential gene expression using RNAseq. MIB profiling of kinome response to EGFR inhibition by erlotinib indicated kinome reprogramming with upregulation of microtubule associated kinases and MAP kinase family members. Overall, these results suggest that basal-like and classical subtype tumors exhibit distinct kinome profiles that present possible subtype specific vulnerabilities to kinase inhibition. Stratifying kinase inhibitor therapies based on tumor subtype could improve response to targeted therapies in PDAC.

Citation Format: Yi Xu, Michael East, Ashley Morrison, Gabriela Herrera, Laura Peng, Gary Johnson, Jen Jen Yeh. Proteomic profiling reveals subtype specific kinase expression in pancreatic cancer [abstract]. In: Proceedings of the AACR Virtual Special Conference on Pancreatic Cancer; 2021 Sep 29-30. Philadelphia (PA): AACR; Cancer Res 2021;81(22 Suppl):Abstract nr PO-079.

The PDAC Extracellular Matrix: A Review of the ECM Protein Composition, Tumor Cell Interaction, and Therapeutic Strategies

Pancreatic ductal adenocarcinoma (PDAC) is notorious for a dense fibrotic stroma that is interlaced with a collagen-based extracellular matrix (ECM) that plays an important role in tumor biology. Traditionally thought to only provide a physical barrier from host responses and systemic chemotherapy, new studies have demonstrated that the ECM maintains biomechanical and biochemical properties of the tumor microenvironment (TME) and restrains tumor growth. Recent studies have shown that the ECM augments tumor stiffness, interstitial fluid pressure, cell-to-cell junctions, and microvascularity using a mix of biomechanical and biochemical signals to influence tumor fate for better or worse. In addition, PDAC tumors have been shown to use ECM-derived peptide fragments as a nutrient source in nutrient-poor conditions. While collagens are the most abundant proteins found in the ECM, several studies have identified growth factors, integrins, glycoproteins, and proteoglycans in the ECM. This review focuses on the dichotomous nature of the PDAC ECM, the types of collagens and other proteins found in the ECM, and therapeutic strategies targeting the PDAC ECM.

Pathology and Molecular Characteristics of Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is the most common type of pancreatic cancer. However, it should be kept in mind that there are other pancreatic cancers that are classified by their cellular lineage: acinar cell carcinomas (acinar differentiation), neuroendocrine neoplasms (arising from the islets), solid-pseudopapillary neoplasms (showing no discernible cell lineage), and pancreatoblastomas (characterized by multiphenotypic differentiation, including acinar endocrine and ductal). This article focuses on the molecular and pathology alterations in PDAC.

Single-cell transcriptome analysis defines heterogeneity of the murine pancreatic ductal tree

To study disease development, an inventory of an organ's cell types and understanding of physiologic function is paramount. Here, we performed single-cell RNA-sequencing to examine heterogeneity of murine pancreatic duct cells, pancreatobiliary cells, and intrapancreatic bile duct cells. We describe an epithelial-mesenchymal transitory axis in our three pancreatic duct subpopulations and identify osteopontin as a regulator of this fate decision as well as human duct cell dedifferentiation. Our results further identify functional heterogeneity within pancreatic duct subpopulations by elucidating a role for geminin in accumulation of DNA damage in the setting of chronic pancreatitis. Our findings implicate diverse functional roles for subpopulations of pancreatic duct cells in maintenance of duct cell identity and disease progression and establish a comprehensive road map of murine pancreatic duct cell, pancreatobiliary cell, and intrapancreatic bile duct cell homeostasis.

Gene Targeting in Disease Networks

Profiling of whole transcriptomes has become a cornerstone of molecular biology and an invaluable tool for the characterization of clinical phenotypes and the identification of disease subtypes. Analyses of these data are becoming ever more sophisticated as we move beyond simple comparisons to consider networks of higher-order interactions and associations. Gene regulatory networks (GRNs) model the regulatory relationships of transcription factors and genes and have allowed the identification of differentially regulated processes in disease systems. In this perspective, we discuss gene targeting scores, which measure changes in inferred regulatory network interactions, and their use in identifying disease-relevant processes. In addition, we present an example analysis for pancreatic ductal adenocarcinoma (PDAC), demonstrating the power of gene targeting scores to identify differential processes between complex phenotypes, processes that would have been missed by only performing differential expression analysis. This example demonstrates that gene targeting scores are an invaluable addition to gene expression analysis in the characterization of diseases and other complex phenotypes.

Pancreatic ductal adenocarcinoma progression is restrained by stromal matrix

Desmoplasia describes the deposition of extensive extracellular matrix and defines primary pancreatic ductal adenocarcinoma (PDA). The acellular component of this stroma has been implicated in PDA pathogenesis and is being targeted therapeutically in clinical trials. By analyzing the stromal content of PDA samples from numerous annotated PDA data sets and correlating stromal content with both anatomic site and clinical outcome, we found PDA metastases in the liver, the primary cause of mortality to have less stroma, have higher tumor cellularity than primary tumors. Experimentally manipulating stromal matrix with an anti-lysyl oxidase like-2 (anti-LOXL2) antibody in syngeneic orthotopic PDA mouse models significantly decreased matrix content, led to lower tissue stiffness, lower contrast retention on computed tomography, and accelerated tumor growth, resulting in diminished overall survival. These studies suggest an important protective role of stroma in PDA and urge caution in clinically deploying stromal depletion strategies.

Isoforms of MUC16 activate oncogenic signaling through EGF receptors to enhance the progression of pancreatic cancer

Aberrant expression of CA125/MUC16 is associated with pancreatic ductal adenocarcinoma (PDAC) progression and metastasis. However, knowledge of the contribution of MUC16 to pancreatic tumorigenesis is limited. Here, we show that MUC16 expression is associated with disease progression, basal-like and squamous tumor subtypes, increased tumor metastasis, and short-term survival of PDAC patients. MUC16 enhanced tumor malignancy through the activation of AKT and GSK3β oncogenic signaling pathways. Activation of these oncogenic signaling pathways resulted in part from increased interactions between MUC16 and epidermal growth factor (EGF)-type receptors, which were enhanced for aberrant glycoforms of MUC16. Treatment of PDAC cells with monoclonal antibody (mAb) AR9.6 significantly reduced MUC16-induced oncogenic signaling. mAb AR9.6 binds to a unique conformational epitope on MUC16, which is influenced by O-glycosylation. Additionally, treatment of PDAC tumor-bearing mice with either mAb AR9.6 alone or in combination with gemcitabine significantly reduced tumor growth and metastasis. We conclude that the aberrant expression of MUC16 enhances PDAC progression to an aggressive phenotype by modulating oncogenic signaling through ErbB receptors. Anti-MUC16 mAb AR9.6 blocks oncogenic activities and tumor growth and could be a novel immunotherapeutic agent against MUC16-mediated PDAC tumor malignancy.

High-Dimensional Precision Medicine From Patient-Derived Xenografts

The complexity of human cancer often results in significant heterogeneity in response to treatment. Precision medicine offers the potential to improve patient outcomes by leveraging this heterogeneity. Individualized treatment rules (ITRs) formalize precision medicine as maps from the patient covariate space into the space of allowable treatments. The optimal ITR is that which maximizes the mean of a clinical outcome in a population of interest. Patient-derived xenograft (PDX) studies permit the evaluation of multiple treatments within a single tumor, and thus are ideally suited for estimating optimal ITRs. PDX data are characterized by correlated outcomes, a high-dimensional feature space, and a large number of treatments. Here we explore machine learning methods for estimating optimal ITRs from PDX data. We analyze data from a large PDX study to identify biomarkers that are informative for developing personalized treatment recommendations in multiple cancers. We estimate optimal ITRs using regression-based (Q-learning) and direct-search methods (outcome weighted learning). Finally, we implement a superlearner approach to combine multiple estimated ITRs and show that the resulting ITR performs better than any of the input ITRs, mitigating uncertainty regarding user choice. Our results indicate that PDX data are a valuable resource for developing individualized treatment strategies in oncology. Supplementary materials for this article are available online.

Enhanced Efficacy of Combination of Gemcitabine and Phosphatidylserine-Targeted Nanovesicles against Pancreatic Cancer

Phosphatidylserine (PS) is often externalized in viable pancreatic cancer cells and is therapeutically targetable using PS-selective drugs. One of the first-line treatments for advanced pancreatic cancer disease, gemcitabine (GEM), provides only marginal benefit to patients. We therefore investigated the therapeutic benefits of combining GEM and the PS-targeting drug, saposin C-dioleoylphosphatidylserine (SapC-DOPS), for treating pancreatic ductal adenocarcinoma (PDAC). Using cell-cycle analyses and a cell surface PS-based sorting method in vitro, we observed an increase in surface PS as cells progress through the cell cycle from G1 to G2/M. We also observed that GEM treatment preferentially targets G1 phase cells that have low surface PS, resulting in an increased median surface PS level of PDAC cells. Inversely, SapC-DOPS preferentially targets high surface PS cells that are predominantly in the G2/M phase. Finally, combination therapy in subcutaneous and orthotopic PDAC tumors in vivo with SapC-DOPS and GEM or Abraxane (Abr)/GEM (one of the current standards of care) significantly inhibits tumor growth and increases survival compared with individual treatments. Our studies confirm a surface PS and cell cycle-based enhancement of cancer cytotoxicity following SapC-DOPS treatment in combination with GEM or Abr/GEM. Thus, PDAC patients treated with Abr/GEM may benefit from concurrent administration of SapC-DOPS.

Myosteatosis to predict postoperative morbidity in pancreatic ductal adenocarcinoma patients receiving neoadjuvant chemotherapy

e16754

Background: Myosteatosis (adipose deposits in muscle) can be detected on cross-sectional imaging through variations in Skeletal Muscle Density (SMD). Patients with myosteatosis tend to have lower overall survival, increased chemotherapy toxicity, and shorter progression-free intervals across cancer types. We investigated whether changes in myosteatosis during neoadjuvant chemotherapy can predict postoperative morbidity risk in patients with pancreatic ductal adenocarcinoma (PDAC). Methods: This is a retrospective cohort study from 2014-2019 of patients with biopsy-proven PDAC who completed neoadjuvant chemotherapy and R0/1 resection (R1: margin < 1mm or microscopically positive). We obtained preoperative patient (age at diagnosis, baseline body mass index (BMI), sex, race, comorbidities) and treatment data (neoadjuvant chemotherapy regimen and duration, time from completion of systemic therapy to surgery, type of operation). Primary outcomes were postoperative complications and 90-day readmission. Average SMD was measured using imaging analysis software at the L3 level on axial abdominal CT scans at the time of diagnosis and at completion of neoadjuvant therapy (SliceOmatic TomoVision QC, Can). We defined SMDΔ as the decrease in SMD during neoadjuvant chemotherapy. Descriptive statistics and Student’s t-test were performed with STATA. Results: We identified 44 patients who received neoadjuvant chemotherapy, achieved a R0/1 resection, and had available CT scans for body composition evaluation. The postoperative complication rate was 43% (n = 19) and 90-day readmission rate was 30% (n = 13). Lower SMD at diagnosis was associated with increased postoperative delirium (p < 0.01) and 90-day readmission (p = 0.02). Greater SMDΔ was associated with increased ICU utilization (p < 0.01) and tube feeding upon discharge (p = 0.03). There was no significant association between preoperative BMI or albumin and our primary outcomes. Conclusions: Preoperative SMD and SMDΔ, rather than albumin or BMI, can predict postoperative morbidity in PDAC patients who received neoadjuvant chemotherapy. This study provides the framework for future studies to develop and validate a tool to predict postoperative morbidity risk in these patients.

Irreversible JNK1-JUN inhibition by JNK-IN-8 sensitizes pancreatic cancer to 5-FU/FOLFOX chemotherapy

Over 55,000 people in the United States are diagnosed with pancreatic ductal adenocarcinoma (PDAC) yearly, and fewer than 20% of these patients survive a year beyond diagnosis. Chemotherapies are considered or used in nearly every PDAC case, but there is limited understanding of the complex signaling responses underlying resistance to these common treatments. Here, we take an unbiased approach to study protein kinase network changes following chemotherapies in patient-derived xenograft (PDX) models of PDAC to facilitate design of rational drug combinations. Proteomics profiling following chemotherapy regimens reveals that activation of JNK-JUN signaling occurs after 5-fluorouracil plus leucovorin (5-FU + LEU) and FOLFOX (5-FU + LEU plus oxaliplatin [OX]), but not after OX alone or gemcitabine. Cell and tumor growth assays with the irreversible inhibitor JNK-IN-8 and genetic manipulations demonstrate that JNK and JUN each contribute to chemoresistance and cancer cell survival after FOLFOX. Active JNK1 and JUN are specifically implicated in these effects, and synergy with JNK-IN-8 is linked to FOLFOX-mediated JUN activation, cell cycle dysregulation, and DNA damage response. This study highlights the potential for JNK-IN-8 as a biological tool and potential combination therapy with FOLFOX in PDAC and reinforces the need to tailor treatment to functional characteristics of individual tumors.

B cell-Derived IL35 Drives STAT3-Dependent CD8+ T-cell Exclusion in Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDA) is an aggressive malignancy characterized by a paucity of tumor-proximal CD8+ T cells and resistance to immunotherapeutic interventions. Cancer-associated mechanisms that elicit CD8+ T-cell exclusion and resistance to immunotherapy are not well-known. Here, using a Kras- and p53-driven model of PDA, we describe a mechanism of action for the protumorigenic cytokine IL35 through STAT3 activation in CD8+ T cells. Distinct from its action on CD4+ T cells, IL35 signaling in gp130+CD8+ T cells activated the transcription factor STAT3, which antagonized intratumoral infiltration and effector function of CD8+ T cells via suppression of CXCR3, CCR5, and IFNγ expression. Inhibition of STAT3 signaling in tumor-educated CD8+ T cells improved PDA growth control upon adoptive transfer to tumor-bearing mice. We showed that activation of STAT3 in CD8+ T cells was driven by B cell- but not regulatory T cell-specific production of IL35. We also demonstrated that B cell-specific deletion of IL35 facilitated CD8+ T-cell activation independently of effector or regulatory CD4+ T cells and was sufficient to phenocopy therapeutic anti-IL35 blockade in overcoming resistance to anti-PD-1 immunotherapy. Finally, we identified a circulating IL35+ B-cell subset in patients with PDA and demonstrated that the presence of IL35+ cells predicted increased occurrence of phosphorylated (p)Stat3+CXCR3-CD8+ T cells in tumors and inversely correlated with a cytotoxic T-cell signature in patients. Together, these data identified B cell-mediated IL35/gp130/STAT3 signaling as an important direct link to CD8+ T-cell exclusion and immunotherapy resistance in PDA.

Vitamin D receptor agonist paricalcitol plus gemcitabine and nab-paclitaxel in patients with metastatic pancreatic cancer

TPS784

Background: Patients(pts) with metastatic pancreatic cancer (PC) have a median survival of less than one year even with use of multiagent chemotherapy programs. Pancreatic tumors are composed of multiple cell types and a dense extracellular matrix that may support cancer cell proliferation and impede chemotherapy delivery. Cancer-associated fibroblasts (CAF’s) in the tumor microenvironment secrete pro-inflammatory factors and components of the extracellular matrix. In PC laboratory models, engagement of the vitamin D receptor (VDR) by VDR agonists shifts CAFs toward a more quiescent phenotype with reduced tumor growth and improved chemotherapy penetration (Sherman. Cell, 2014). Paricalcitol is a synthetic VDR agonist used in patients with secondary hyperparathyroidism due to chronic kidney disease. A prior pilot study evaluated IV paricalcitol with gemcitabine (G) and nab-paclitaxel (A) before surgical resection in patients with resectable PC (NCT02030860). Methods: Pts with previously-untreated metastatic PC will be enrolled in a two-stage study consisting of a safety run-in and a randomized phase 2 study (NCT03520790). In the run-in stage, 36 pts will be randomized 1:1:1 to G (1000 mg/m2) and A (125 mg/m2) given 3 weeks on and 1 week off plus: (a) paricalcitol 25mcg IV thrice weekly, (b) paricalcitol 16mcg oral daily, or (c) placebo oral daily. Grade 3/4 hypercalcemia or genitourinary stones will be considered dose limiting toxicities.Pts will undergo paired pre- and on-treatment tumor biopsies to examine pharmacodynamic (PD) markers by bulk and single cell RNA sequencing and multiplex immunofluoresence.Assuming safety and supportive PD assessments, the phase 2 study will randomize an additional 76 pts to two treatment arms with GA plus: (a) paricalcitol or (b) placebo.Paricalcitol formulation (IV or oral) will be determined based on data from the run-in stage.The primary endpoint of the phase 2 study is overall survival, with a total of 100 pts needed to identify a hazard ratio of 0.6 with 80% power and one-sided alpha of 0.10.Secondary endpoints include safety, response rate, and progression free survival.Trial funding provided by SU2C, CRUK,Lustgarten Foundation, and AACR. Clinical trial information: NCT03520790.

Abstract B41: Compartment deconvolution in pancreatic cancer with biologic and clinical implications

Pancreatic ductal adenocarcinoma (PDAC) is characterized by relatively low tumor purity and an abundant tumor microenvironment. To dissect the contribution of the biologic components, we developed DECODER, which performs de novo compartment deconvolution and weight estimation of tumor samples. DECODER is a sophisticated framework that integrates runs of non-negative matrix factorization (NMF) and non-negative least square (NNLS) algorithms and can be applied to any non-negative matrices without the need to know the number of resultant factors or compartments. DECODER was used to deconvolve the TCGA pancreatic adenocarcinoma (PAAD) RNA-seq dataset, which resulted in the identification of 7 major compartments (basal tumor, classical tumor, activated stroma, normal stroma, immune, endocrine, and exocrine), confirming prior manual NMF-based solutions. These results were then used for single-sample based weight estimation in the COMPASS trial and ICGC PACA-AU RNA-seq dataset. We saw a significant positive correlation between DECODER immune weight and leukocyte fraction (r = 0.757, p &lt; 0.001) or ESTIMATE immune score (r = 0.773, p &lt; 0.001). Samples with high immune weights corresponded to immune infiltration by histology. A significant correlation was found between the sum of basal and classical tumor weights, and tumor purity based on both ABSOLUTE (r = 0.699, p &lt; 0.001) and methylation (r = 0.71, p &lt; 0.001). Similarly, the sum of activated and normal stroma weights correlated with ESTIMATE stromal score (r = 0.729, p &lt; 0.001). Interestingly, we found that the ratio between the basal and classical compartment (bcRatio) was significantly associated with survival outcome (p = 0.049 in TCGA and 0.008 in ICGC) in all patients and treatment response in basal-like patients (r = 0.884, p &lt; 0.001 in COMPASS trial), suggesting that bcRatio may help explain the molecular basis for tumor behavior in PDAC. DECODER was also applied for de novo deconvolution for all the cancer types in TCGA RNA-seq dataset and identified the cancer type specific compartments. Results from DECODER can then be used for single-sample weight estimation of new samples for any cancer type. In addition, we applied DECODER on the PanCan ATAC-seq dataset containing 23 cancer types in a combined fashion, and identified compartments associated with cancer types or organ systems. This proves that DECODER is highly feasible to data of multiple platforms. In summary, we present an automated method for de novo deconvolution that may be used across tumor and data types. With deconvolved results as the reference, DECODER enables the single-sample weight estimation for a new sample, which is plausible in the clinical setting.

Citation Format: Xianlu L. Peng, Richard A. Moffitt, Robert J. Torphy, Keith E. Volmar, Jen Jen Yeh. Compartment deconvolution in pancreatic cancer with biologic and clinical implications [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer: Advances in Science and Clinical Care; 2019 Sept 6-9; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2019;79(24 Suppl):Abstract nr B41.

Abstract I08: Molecular subtypes - bench to bedside

Recent treatment advances in chemotherapy and targeted therapy regimens have provided pancreatic cancer patients and providers with better options. Molecular subtyping for pancreatic cancer has made substantial progress in recent years. With these advances, there is now an opportunity to enable precision medicine approaches for patients with pancreatic cancer. Transcriptomic molecular subtyping is currently an active area of study where several subtyping schemas have been proposed. This talk will present some of these schemas and attempt to reconcile them. Many subtyping approaches rely on the clustering of a new sample with an existing group of samples, the ability to determine the subtype of an individual tumor is limited. In addition, in order to use molecular subtypes in the clinic, subtypes need to be clinically replicable, robust, and have clinical implications. Developing a robust method for subtype classification is needed in order to study the role of molecular subtypes in the context of future clinical trials.

Citation Format: Jen Jen Yeh. Molecular subtypes - bench to bedside [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer: Advances in Science and Clinical Care; 2019 Sept 6-9; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2019;79(24 Suppl):Abstract nr I08.

Purity Independent Subtyping of Tumors (PurIST), A Clinically Robust, Single-sample Classifier for Tumor Subtyping in Pancreatic Cancer

PURPOSE

Molecular subtyping for pancreatic cancer has made substantial progress in recent years, facilitating the optimization of existing therapeutic approaches to improve clinical outcomes in pancreatic cancer. With advances in treatment combinations and choices, it is becoming increasingly important to determine ways to place patients on the best therapies upfront. Although various molecular subtyping systems for pancreatic cancer have been proposed, consensus regarding proposed subtypes, as well as their relative clinical utility, remains largely unknown and presents a natural barrier to wider clinical adoption.

EXPERIMENTAL DESIGN

We assess three major subtype classification schemas in the context of results from two clinical trials and by meta-analysis of publicly available expression data to assess statistical criteria of subtype robustness and overall clinical relevance. We then developed a single-sample classifier (SSC) using penalized logistic regression based on the most robust and replicable schema.

RESULTS

We demonstrate that a tumor-intrinsic two-subtype schema is most robust, replicable, and clinically relevant. We developed Purity Independent Subtyping of Tumors (PurIST), a SSC with robust and highly replicable performance on a wide range of platforms and sample types. We show that PurIST subtypes have meaningful associations with patient prognosis and have significant implications for treatment response to FOLIFIRNOX.

CONCLUSIONS

The flexibility and utility of PurIST on low-input samples such as tumor biopsies allows it to be used at the time of diagnosis to facilitate the choice of effective therapies for patients with pancreatic ductal adenocarcinoma and should be considered in the context of future clinical trials.

Modeling Between-Study Heterogeneity for Improved Replicability in Gene Signature Selection and Clinical Prediction

In the genomic era, the identification of gene signatures associated with disease is of significant interest. Such signatures are often used to predict clinical outcomes in new patients and aid clinical decision-making. However, recent studies have shown that gene signatures are often not replicable. This occurrence has practical implications regarding the generalizability and clinical applicability of such signatures. To improve replicability, we introduce a novel approach to select gene signatures from multiple datasets whose effects are consistently non-zero and account for between-study heterogeneity. We build our model upon some rank-based quantities, facilitating integration over different genomic datasets. A high dimensional penalized Generalized Linear Mixed Model (pGLMM) is used to select gene signatures and address data heterogeneity. We compare our method to some commonly used strategies that select gene signatures ignoring between-study heterogeneity. We provide asymptotic results justifying the performance of our method and demonstrate its advantage in the presence of heterogeneity through thorough simulation studies. Lastly, we motivate our method through a case study subtyping pancreatic cancer patients from four gene expression studies.

Antitumor Responses in the Absence of Toxicity in Solid Tumors by Targeting B7-H3 via Chimeric Antigen Receptor T Cells

The high expression across multiple tumor types and restricted expression in normal tissues make B7-H3 an attractive target for immunotherapy. We generated chimeric antigen receptor (CAR) T cells targeting B7-H3 (B7-H3.CAR-Ts) and found that B7-H3.CAR-Ts controlled the growth of pancreatic ductal adenocarcinoma, ovarian cancer and neuroblastoma in vitro and in orthotopic and metastatic xenograft mouse models, which included patient-derived xenograft. We also found that 4-1BB co-stimulation promotes lower PD-1 expression in B7-H3.CAR-Ts, and superior antitumor activity when targeting tumor cells that constitutively expressed PD-L1. We took advantage of the cross-reactivity of the B7-H3.CAR with murine B7-H3, and found that B7-H3.CAR-Ts significantly controlled tumor growth in a syngeneic tumor model without evident toxicity. These findings support the clinical development of B7-H3.CAR-Ts.

Tyrosyl phosphorylation of KRAS stalls GTPase cycle via alteration of switch I and II conformation

Deregulation of the RAS GTPase cycle due to mutations in the three RAS genes is commonly associated with cancer development. Protein tyrosine phosphatase SHP2 promotes RAF-to-MAPK signaling pathway and is an essential factor in RAS-driven oncogenesis. Despite the emergence of SHP2 inhibitors for the treatment of cancers harbouring mutant KRAS, the mechanism underlying SHP2 activation of KRAS signaling remains unclear. Here we report tyrosyl-phosphorylation of endogenous RAS and demonstrate that KRAS phosphorylation via Src on Tyr32 and Tyr64 alters the conformation of switch I and II regions, which stalls multiple steps of the GTPase cycle and impairs binding to effectors. In contrast, SHP2 dephosphorylates KRAS, a process that is required to maintain dynamic canonical KRAS GTPase cycle. Notably, Src- and SHP2-mediated regulation of KRAS activity extends to oncogenic KRAS and the inhibition of SHP2 disrupts the phosphorylation cycle, shifting the equilibrium of the GTPase cycle towards the stalled ‘dark state’.

Deregulation of the RAS GTPase cycle due to mutations in RAS genes is commonly associated with cancer development. Here authors use NMR and mass spectrometry to shows that KRAS phosphorylation via Src alters the conformation of switch I and II regions and thereby impacts the GTPase cycle.

Application of Integrated Drug Screening/Kinome Analysis to Identify Inhibitors of Gemcitabine-Resistant Pancreatic Cancer Cell Growth

Continuous exposure of a pancreatic cancer cell line MIA PaCa-2 (MiaS) to gemcitabine resulted in the formation of a gemcitabine-resistant subline (MiaR). In an effort to discover kinase inhibitors that inhibited MiaR growth, MiaR cells were exposed to kinase inhibitors (PKIS-1 library) in a 384-well screening format. Three compounds (UNC10112721A, UNC10112652A, and UNC10112793A) were identified that inhibited the growth of MiaR cells by more than 50% (at 50 nM). Two compounds (UNC10112721A and UNC10112652A) were classified as cyclin-dependent kinase (CDK) inhibitors, whereas UNC10112793A was reported to be a PLK inhibitor. Dose-response experiments supported the efficacy of these compounds to inhibit growth and increase apoptosis in 2D cultures of these cells. However, only UNC10112721A significantly inhibited the growth of 3D spheroids composed of MiaR cells and GFP-tagged cancer-associated fibroblasts. Multiplexed inhibitor bead (MIB)-mass spectrometry (MS) kinome competition experiments identified CDK9, CLK1-4, DYRK1A, and CSNK1 as major kinase targets for UNC10112721A in MiaR cells. Another CDK9 inhibitor (CDK-IN-2) replicated the growth inhibitory effects of UNC10112721A, whereas inhibitors against the CLK, DYRK, or CSNK1 kinases had no effect. In summary, these studies describe a coordinated approach to discover novel kinase inhibitors, evaluate their efficacy in 3D models, and define their specificity against the kinome.

Impact of neoadjuvant therapy on postoperative outcomes after pancreaticoduodenectomy

BACKGROUND

Surgical resection provides the only potentially curative treatment of pancreatic cancer. Neoadjuvant chemotherapy and/or radiation (NAT) is used to downstage patients with borderline resectable tumors. The objective of this study was to examine the postoperative morbidity and mortality of NAT after pancreaticoduodenectomy (PD) for pancreatic ductal adenocarcinoma (PDA).

METHODS

Using the American College of Surgeons-National Surgical Quality Improvement Project Targeted Pancreatectomy data, we identified patients who underwent a PD for PDA from 2014 to 2015. Patients were grouped by receipt of NAT 90 days before PD. Bivariable and multivariable analyses was used to compare postoperative outcomes.

RESULTS

A total of 3748 patients with PDA underwent PD; 926 (24.7%) received NAT. Those in the NAT group had more major vein resections, and longer operating times (all P < 0.001). On pathologic staging, those in the NAT group had smaller tumors (T1, 10.9% vs 5.1%; P < 0.001) and fewer nodes positive (N0, 49% vs 28%; P < 0.001). There were no differences in 30-day postoperative mortality or overall complications. On multivariable analysis, patients who received NAT had a lower likelihood of pancreatic fistula (OR, 0.67; P < 0.001).

CONCLUSION

NAT does not increase the overall postoperative morbidity or mortality of PD for PDA. There is a decreased likelihood of pancreatic fistulas in patients that receive neoadjuvant therapy.

Abstract 4189: Cationic polymer inhibits pancreatic cancer invasion and metastasis

Background and Hypothesis: Pancreatic cancer (PC) has the poorest prognosis of all major cancers, with a 5-year survival of less than 5%. Cell-free DNA (cfDNA) has been well validated as a biomarker that correlates with tumor burden. More recently, a role for cfDNA in tumor progression has also been identified. The latter occurs through activation of Toll-like receptors (TLRs) in both tumor cells and the host environment, which can upregulate prometastatic signaling pathways. In addition, tumor-derived extracellular vesicles (EVs) such as microparticles and exosomes have also been implicated in promoting metastasis by activating proinvasive pathways in tumor cells and preconditioning secondary sites for metastatic establishment. Our laboratory has previously shown that cationic polymers can neutralize cfDNA and abrogate inflammation in disease models of autoimmunity and infection. We investigated the ability of the cationic polymer, PAMAM-G3, to bind and inhibit cfDNA and EVs and thereby inhibit tumor invasion in vitro and metastasis in vivo.

Methods and Results: Transwell-Matrigel invasion assays were performed using multiple PC cell lines. Cells were plated in the upper chamber with no serum +/- cfDNA, EVs, or PAMAM-G3. The bottom chamber was plated with complete media as a chemo-attractant. Cells treated with cfDNA, EVs, or PAMAM-G3 were also analyzed for activation of pro-inflammatory pathways (NFkB, MAPK, etc.). The in vivo model was performed in C57B6 mice that were injected with bioluminescent murine PC cells into their spleens and followed for liver metastases with bioluminescent imaging. Experimental mice were treated biweekly with intraperitoneal PAMAM-G3 (20 mg/kg) or saline starting 48 hours after pancreatic tumor cell implantation. PAMAM-G3 significantly inhibited in vitro invasion of pancreatic cancer cell lines in response to cancer patient serum-derived cfDNA and extracellular vesicles. Moreover, PAMAM-G3 (20 mg/kg) treatment led to a significant reduction in liver metastasis without affecting primary tumor growth in vivo. Serum derived from saline-treated mice induced higher levels of invasion than serum from polymer-treated mice and exogenous polymer blocked this effect (**** = p&lt;0.0001, *** = p&lt;0.001, ** = p&lt;0.01, NS = not significant by t-test).

Discussion: Cationic polymers such as PAMAM-G3 may represent a novel class of therapeutics to combat pancreatic cancer metastasis. These polymers can bind and neutralize cfDNA and tumor-derived EVs, thereby blocking activation of pro-inflammatory pathways within tumor cells, and reducing tumor invasion and metastasis. Cationic polymers will be tested in other preclinical models of cancer and in dosing studies for potential progression to clinical translation.

Citation Format: Ibtehaj A. Naqvi, Ruwan Gunaratne, Jessica McDade, Douglas Rouse, Jen Jen Yeh, David Pisetsky, Jaewoo Lee, Rebekah White, Bruce Sullenger. Cationic polymer inhibits pancreatic cancer invasion and metastasis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4189.

Use of iontophoresis for the treatment of cancer

Despite major advancements in cancer treatments, there are still many limitations to therapy including off-target effects, drug resistance, and control of cancer-related symptoms. There are opportunities for local drug delivery devices to intervene at various stages of cancer to provide curative and palliative benefit. Iontophoretic devices that deliver drugs locally to a region of interest have been adapted for the treatment of cancer. These devices have shown promise in pre-clinical and clinical studies for retinoblastoma, skin, bladder, and pancreatic cancers. Herein, we review iontophoretic devices used in the management of cancer.

Real-time Genomic Characterization of Advanced Pancreatic Cancer to Enable Precision Medicine

Clinically relevant subtypes exist for pancreatic ductal adenocarcinoma (PDAC), but molecular characterization is not yet standard in clinical care. We implemented a biopsy protocol to perform time-sensitive whole-exome sequencing and RNA sequencing for patients with advanced PDAC. Therapeutically relevant genomic alterations were identified in 48% (34/71) and pathogenic/likely pathogenic germline alterations in 18% (13/71) of patients. Overall, 30% (21/71) of enrolled patients experienced a change in clinical management as a result of genomic data. Twenty-six patients had germline and/or somatic alterations in DNA-damage repair genes, and 5 additional patients had mutational signatures of homologous recombination deficiency but no identified causal genomic alteration. Two patients had oncogenic in-frame BRAF deletions, and we report the first clinical evidence that this alteration confers sensitivity to MAPK pathway inhibition. Moreover, we identified tumor/stroma gene expression signatures with clinical relevance. Collectively, these data demonstrate the feasibility and value of real-time genomic characterization of advanced PDAC.Significance: Molecular analyses of metastatic PDAC tumors are challenging due to the heterogeneous cellular composition of biopsy specimens and rapid progression of the disease. Using an integrated multidisciplinary biopsy program, we demonstrate that real-time genomic characterization of advanced PDAC can identify clinically relevant alterations that inform management of this difficult disease. Cancer Discov; 8(9); 1096-111. ©2018 AACR.See related commentary by Collisson, p. 1062This article is highlighted in the In This Issue feature, p. 1047.

Impact of formulation on the iontophoretic delivery of the FOLFIRINOX regimen for the treatment of pancreatic cancer

PURPOSE

Effective treatment of patients with locally advanced pancreatic cancer is a significant unmet clinical need. One major hurdle that exists is inadequate drug delivery due to the desmoplastic stroma and poor vascularization that is characteristic of pancreatic cancer. The local iontophoretic delivery of chemotherapies provides a novel way of improving treatment. With the growing practice of highly toxic combination therapies in the treatment of pancreatic cancer, the use of iontophoresis for local delivery can potentiate the anti-cancer effects of these therapies while sparing unwanted toxicity. The objective of this study was to investigate the impact of formulation on the electro-transport of the FOLFIRINOX regimen for the development of a new treatment for pancreatic cancer.

METHODS

Three formulations of the FOLFIRINOX regimen (5-fluorouracil, leucovorin, irinotecan, and oxaliplatin) were generated at a fixed pH of 6.0 and were referred to as formulation A (single drug solution with all four drugs combined), formulation B (two drug solutions with two drugs per solution), and formulation C (four individual drug solutions). Anodic iontophoresis of the three different formulations was evaluated in orthotopic patient-derived xenografts of pancreatic cancer.

RESULTS

Iontophoretic transport of the FOLFIRINOX drugs was characterized according to organ exposure after a single device treatment in vivo. We report that the co-iontophoresis of two drug solutions, leucovorin + oxaliplatin and 5-fluorouracil + irinotecan, resulted in the highest levels of cytotoxic drugs in the tumor compared to drugs delivered individually or combined into one solution. There was no significant difference in plasma, pancreas, kidney, and liver exposure to the cytotoxic drugs delivered by the three different formulations. In addition, we found that reducing the duration of iontophoretic treatment from 10 to 5 min per solution resulted in a significant decrease in drug concentrations.

CONCLUSIONS

Underlying the difference in drug transport of the formulations was electrolyte concentrations, which includes both active and inactive components. Electrolyte concentrations can hinder or improve drug electro-transport. Overall, balancing electrolyte concentration is needed for optimal electro-transport.

Sequencing Pancreatic Juice: Squeezing the Most Out of Surveillance

Next-generation sequencing of pancreatic juice can detect and quantify tumor-promoting mutations, supporting imaging and cytology findings to predict the degree of dysplasia in patients at high risk for pancreatic cancer. Future studies are needed to optimize this approach and determine how it best fits into clinical practice. Clin Cancer Res; 24(12); 2713-5. ©2018 AACRSee related article by Suenaga et al., p. 2963.

Genomics-driven precision medicine for advanced pancreatic ductal carcinoma (PDAC): Early results from the COMPASS trial (NCT02750657)

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Background: COMPASS is a prospective study with the primary aim to identify predictive mutational and transcriptional features in advanced PDAC for improved patient stratification and treatment selection. Methods: Patients with advanced PDAC were prospectively recruited prior to first-line combination chemotherapy for whole genome sequencing (WGS) and RNA sequencing (RNASeq). Fresh tumor tissue was acquired by image guided percutaneous core needle biopsy of locally advanced primary or metastatic tumors. Laser capture microdissection was performed for all cases to ensure high-resolution genomic analyses. Primary endpoint was feasibility to report WGS results prior to first disease assessment CT scan at 8 weeks. The main secondary endpoint was discovery of patient subsets with predictive mutational and transcriptional signatures. Results: Of 63 patients who underwent a tumor biopsy between December 2015 and June 2017, WGS and RNASeq were successful in 62 (98%) and 60 (95%), respectively. Genomic results were reported at a median of 35 days (range 19-52 days) from biopsy, meeting the primary feasibility endpoint. Three patients with an ‘unstable’ genomic subtype, including two with a novel ‘duplicator’ phenotype, responded well to m-FOLFIRINOX. Of two cases with the same germline BRCA2 mutation, only the chemotherapy responder had loss of heterozygosity and genomic hallmarks of double stranded break repair deficiency. Approximately 25% of tumors displayed the basal-like RNA expression signature and these were chemotherapy resistant, with tumor shrinkage mainly observed in those with the classical RNA subtype (P = 0.003). Thirty percent of patients had potentially actionable genetic alterations. Conclusions: Prospective comprehensive genomic profiling of advanced PDAC is feasible and our early data indicate that chemotherapy response differs among patients with different genomic/transcriptomic subtypes providing the impetus for further studies. Clinical trial information: NCT02750657.

Expression of immune genes and a signature of PD-1 inhibition resistance in basal-like pancreatic adenocarcinoma (PDAC) subtypes

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Background: PDAC is a lethal disease with poor survival even when detected at an early stage. Recurrence rates after surgical resection remain high. Recently, two distinct molecular subtypes of PDAC (basal-like and classical) have been identified with basal-like tumors demonstrating inferior outcomes. We hypothesize that differences in tumor immunogenicity may contribute to this aggressive biology and predict response to immune checkpoint inhibitors. Methods: RNA sequencing was performed on formalin-fixed paraffin embedded samples of 60 resected PDAC patients. We evaluated previously published immune gene expression signatures comprised of 1400 genes and used a single sample classifier to determine molecular subtypes. Results: Table 1 summarizes patient characteristics in our cohort. There were 35 classical and 25 basal-like tumors. PFS was significantly shorter in patients with basal-like compared to classical subtypes (9 vs 15 mo, p = 0.006). In a multivariable model with molecular subtype, lymph node and margin status, subtype was the only independent predictor of PFS (p=0.028). Unsupervised clustering identified two distinct immune groups that were associated with molecular subtypes (p=0.038) with higher expression of immune genes in basal-like tumors. Basal-like tumors were significantly associated with an immunosuppressive signature (p<0.001) and a signature associated with non-response to PD-1 inhibition in melanoma (p=0.001). Conclusions: This is the first study to show that basal-like pancreatic cancers are associated with increased immune gene expression and may help explain their inferior prognosis. We hypothesize that this reflects an increase in immunosuppressive cells in basal-like tumors that may predict decreased response to immune check point inhibitors. [Table: see text]

Stromal Content Is Correlated With Tissue Site, Contrast Retention, and Survival in Pancreatic Adenocarcinoma

PURPOSE

Desmoplastic stroma is a cardinal feature of primary pancreatic ductal adenocarcinoma (PDAC), but its effects on the biology, prognosis and therapeutic outcomes are not known. We developed an automated method to assess tumor stroma density (TSD) and investigated computed tomography (CT)-correlates of stroma in PDAC.

PATIENTS AND METHODS

We collected PDAC samples from rapid autopsy and resection series and digitally annotated samples to quantify TSD. A series of resected patients also underwent preoperative multiphasic CT.

RESULTS

Automated and manual assessments of TSD were highly correlated (ρ= 0.65, P < 0.001). Solid organ metastases had a lower median TSD than primary tumors (P < 0.001). Patients with high TSD enjoyed prolonged recurrence free survival (RFS) (P = 0.003; HR = 0.51) and overall survival (P = 0.008, HR = 0.57). In another independent dataset, patients with high TSD had decreased risk for recurrence (P = 0.003, HR = 0.03) and death (P = 0.003, HR = 0.03) at time of resection, however the protective effect diminished over time. Patients with normalized portovenous phase CT tumor enhancement ratio ≥0.40 had a longer RFS following resection (P = 0.020). Normalized portovenous phase CT tumor enhancement ratio was significantly correlated with TSD (P = 0.003).

CONCLUSIONS

Objective quantitative assessment of stroma in PDAC revealed several clinically relevant observations. Firstly, stroma was less abundant in metastatic PDAC, the cause of most PDAC mortality. Secondly, high stromal content correlates with favorable outcome in resected cases, implying a protective effect of stroma and suggesting careful consideration of active stromal depletion therapies. Finally, standard multiphase CT imaging correlates with stroma content as well as clinical outcome, indicating that non-invasive assessment of stroma is a feasible sensitivity enrichment approach in PDAC.

Genomics-Driven Precision Medicine for Advanced Pancreatic Cancer: Early Results from the COMPASS Trial

Purpose: To perform real-time whole genome sequencing (WGS) and RNA sequencing (RNASeq) of advanced pancreatic ductal adenocarcinoma (PDAC) to identify predictive mutational and transcriptional features for better treatment selection.Experimental Design: Patients with advanced PDAC were prospectively recruited prior to first-line combination chemotherapy. Fresh tumor tissue was acquired by image-guided percutaneous core biopsy for WGS and RNASeq. Laser capture microdissection was performed for all cases. Primary endpoint was feasibility to report WGS results prior to first disease assessment CT scan at 8 weeks. The main secondary endpoint was discovery of patient subsets with predictive mutational and transcriptional signatures.Results: Sixty-three patients underwent a tumor biopsy between December 2015 and June 2017. WGS and RNASeq were successful in 62 (98%) and 60 (95%), respectively. Genomic results were reported at a median of 35 days (range, 19-52 days) from biopsy, meeting the primary feasibility endpoint. Objective responses to first-line chemotherapy were significantly better in patients with the classical PDAC RNA subtype compared with those with the basal-like subtype (P = 0.004). The best progression-free survival was observed in those with classical subtype treated with m-FOLFIRINOX. GATA6 expression in tumor measured by RNA in situ hybridization was found to be a robust surrogate biomarker for differentiating classical and basal-like PDAC subtypes. Potentially actionable genetic alterations were found in 30% of patients.Conclusions: Prospective genomic profiling of advanced PDAC is feasible, and our early data indicate that chemotherapy response differs among patients with different genomic/transcriptomic subtypes. Clin Cancer Res; 24(6); 1344-54. ©2017 AACR.

Tumor Mitotic Rate and Association with Recurrence in Sentinel Lymph Node Negative Stage II Melanoma Patients

Tumor mitotic rate (TMR) is a known prognostic variable in thin melanoma patients. Its significance in stage II melanoma patients is yet to be demonstrated. Retrospective analysis of a prospective melanoma database from 9/1997 to 7/2015 was performed. All stage II melanoma, with documented TMR, and six months of follow-up were included. We evaluated the association of clinicopathologic variables, TMR, as a continuous and categorical variable with recurrence-free survival (RFS) and overall survival (OS) using Cox proportional hazards modeling. We used a statistical model, X-tile, to develop optimal categorizations of TMR. A total of 265 patient characteristics are included in this study. Recurrences occurred in 82 (30.9%) patients, including 5 local, 41 regional, and 36 distant patients. In multivariate model, ulceration, Breslow, and continuous TMR were associated with worse RFS\OS. Continuous TMR demonstrated worse RFS (hazards ratio [HR] 1.02 (1.00–1.05)) and OS (HR 1.02 (1.00–1.04)), whereas dichotomized TMR (≥1 vs <1) was not significant. TMR >10.4 mitoses/mm2 has a 5-year RFS\OS of 27.2 and 44.3 per cent, respectively, compared with 57.4 and 71.4 per cent, respectively, for TMR <3.2 mitoses/mm2. Continuous TMR predicts incidence of recurrence in stage II melanoma. We propose a new categorization method developed by statistical modeling for optimal stratification that may guide surveillance for this disparate patient population.

Tumor Mitotic Rate and Association with Recurrence in Sentinel Lymph Node Negative Stage II Melanoma Patients

Tumor mitotic rate (TMR) is a known prognostic variable in thin melanoma patients. Its significance in stage II melanoma patients is yet to be demonstrated. Retrospective analysis of a prospective melanoma database from 9/1997 to 7/2015 was performed. All stage II melanoma, with documented TMR, and six months of follow-up were included. We evaluated the association of clinicopathologic variables, TMR, as a continuous and categorical variable with recurrence-free survival (RFS) and overall survival (OS) using Cox proportional hazards modeling. We used a statistical model, X-tile, to develop optimal categorizations of TMR. A total of 265 patient characteristics are included in this study. Recurrences occurred in 82 (30.9%) patients, including 5 local, 41 regional, and 36 distant patients. In multivariate model, ulceration, Breslow, and continuous TMR were associated with worse RFS\OS. Continuous TMR demonstrated worse RFS (hazards ratio [HR] 1.02 (1.00-1.05)) and OS (HR 1.02 (1.00-1.04)), whereas dichotomized TMR (≥1 vs <1) was not significant. TMR >10.4 mitoses/mm2 has a 5-year RFS\OS of 27.2 and 44.3 per cent, respectively, compared with 57.4 and 71.4 per cent, respectively, for TMR <3.2 mitoses/mm2. Continuous TMR predicts incidence of recurrence in stage II melanoma. We propose a new categorization method developed by statistical modeling for optimal stratification that may guide surveillance for this disparate patient population.

Hexokinase 2 promotes tumor growth and metastasis by regulating lactate production in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is a KRAS-driven cancer with a high incidence of metastasis and an overall poor prognosis. Previous work in a genetically engineered mouse model of PDAC showed glucose metabolism to be important for maintaining tumor growth. Multiple glycolytic enzymes, including hexokinase 2 (HK2), were upregulated in primary PDAC patient tumors, supporting a role for glycolysis in promoting human disease. HK2 was most highly expressed in PDAC metastases, suggesting a link between HK2 and aggressive tumor biology. In support of this we found HK2 expression to be associated with shorter overall survival in PDAC patients undergoing curative surgery. Transient and stable knockdown of HK2 in primary PDAC cell lines decreased lactate production, anchorage independent growth (AIG) and invasion through a reconstituted matrix. Conversely, stable overexpression of HK2 increased lactate production, cell proliferation, AIG and invasion. Pharmacologic inhibition of lactate production reduced the HK2-driven increase in invasion while addition of extracellular lactate enhanced invasion, together providing a link between glycolytic activity and metastatic potential. Stable knockdown of HK2 decreased primary tumor growth in cell line xenografts and decreased incidence of lung metastasis after tail vein injection. Gene expression analysis of tumors with decreased HK2 expression showed alterations in VEGF-A signaling, a pathway important for angiogenesis and metastasis, consistent with a requirement of HK2 in promoting metastasis. Overall our data provides strong evidence for the role of HK2 in promoting PDAC disease progression, suggesting that direct inhibition of HK2 may be a promising approach in the clinic.

Discrete microfluidics for the isolation of circulating tumor cell subpopulations targeting fibroblast activation protein alpha and epithelial cell adhesion molecule

Circulating tumor cells consist of phenotypically distinct subpopulations that originate from the tumor microenvironment. We report a circulating tumor cell dual selection assay that uses discrete microfluidics to select circulating tumor cell subpopulations from a single blood sample; circulating tumor cells expressing the established marker epithelial cell adhesion molecule and a new marker, fibroblast activation protein alpha, were evaluated. Both circulating tumor cell subpopulations were detected in metastatic ovarian, colorectal, prostate, breast, and pancreatic cancer patients and 90% of the isolated circulating tumor cells did not co-express both antigens. Clinical sensitivities of 100% showed substantial improvement compared to epithelial cell adhesion molecule selection alone. Owing to high purity (>80%) of the selected circulating tumor cells, molecular analysis of both circulating tumor cell subpopulations was carried out in bulk, including next generation sequencing, mutation analysis, and gene expression. Results suggested fibroblast activation protein alpha and epithelial cell adhesion molecule circulating tumor cells are distinct subpopulations and the use of these in concert can provide information needed to navigate through cancer disease management challenges.

Outpatient Total Thyroidectomy is Safe for Moderate-Volume Surgeons

Traditionally, total thyroidectomy (TT) was an inpatient procedure, but recent trends indicate that patients are often discharged on the day of surgery. This has been proven safe for high-volume surgeons but has not been studied for low (<10 TT per year) and moderate volume surgeons (<24 TT per year). Retrospective review was performed for 414 total thyroidectomies between 2005 and 2013. Emergency department visits and readmissions within 30 days of surgery were captured, but were considered the same for the purpose of this analysis. Patients were identified as outpatient if the day of discharge matched the day of surgery. The groups were compared based on demographic variables, comorbidities, postop calcium supplementation, and serum calcium. We found that moderate-volume surgeons were more likely to perform outpatient TT than low-volume surgeons (31.6% vs 6.0%, P < 0.001), but there was no correlation between length of stay and readmission (P = 0.688). Readmitted patients had lower postop serum calcium (8.3 mg/dL) than patients who were not readmitted (8.8 mg/dL, P = 0.006). Our data show that moderate-volume surgeons performing outpatient TT have an acceptable safety profile with respect to emergency department visits and hospital readmissions, and that same day discharge had no bearing on readmission.

Outpatient Total Thyroidectomy Is Safe for Moderate-Volume Surgeons

Traditionally, total thyroidectomy (TT) was an inpatient procedure, but recent trends indicate that patients are often discharged on the day of surgery. This has been proven safe for high-volume surgeons but has not been studied for low (<10 TT per year) and moderate volume surgeons (<24 TT per year). Retrospective review was performed for 414 total thyroidectomies between 2005 and 2013. Emergency department visits and readmissions within 30 days of surgery were captured, but were considered the same for the purpose of this analysis. Patients were identified as outpatient if the day of discharge matched the day of surgery. The groups were compared based on demographic variables, comorbidities, postop calcium supplementation, and serum calcium. We found that moderate-volume surgeons were more likely to perform outpatient TT than low-volume surgeons (31.6% vs 6.0%, P < 0.001), but there was no correlation between length of stay and readmission (P = 0.688). Readmitted patients had lower postop serum calcium (8.3 mg/dL) than patients who were not readmitted (8.8 mg/dL, P = 0.006). Our data show that moderate-volume surgeons performing outpatient TT have an acceptable safety profile with respect to emergency department visits and hospital readmissions, and that same day discharge had no bearing on readmission.