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Table S4

Supplementary Methods

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.

Table S5

Supplementary Figures

Table S2

Table S1

Table S6

Table S3

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.

In the last decade, the use of microRNA (miRNA) and extracellular vesicle (EV) therapies has emerged as an alternative approach to mitigate the negative effects of several disease pathologies ranging from cancer to tissue and organ regeneration; however, delivery approaches towards target tissues have not been optimized. To alleviate these challenges, including rapid diffusion upon injection and susceptibility to degradation, porcine-derived decellularized extracellular matrix (ECM) hydrogels are examined as a potential delivery platform for miRNA and EV therapeutics. The incorporation of EVs and miRNA antagonists, including anti-miR and antago-miR, in ECM hydrogels results in a prolonged release as compared to the biologic agents alone. In addition, individual in vitro assessments confirm the bioactivity of the therapeutics upon release from the ECM hydrogels. This work demonstrates the feasibility of encapsulating miRNA and EV therapeutics in ECM hydrogels to enhance delivery and potentially efficacy in later in vivo applications.

The receptor of epidermal growth factor (EGFR) critically regulates tumor cell invasion and is a potent therapeutic target for treatment of many types of cancers, including carcinomas and glioblastomas. It is known that EGF regulates cell motility when tumor cells are embedded within a 3D biomatrix. However, roles of EGF in modulating tumor cell motility phenotype are largely unknown. In this article, we report that EGF promotes a mesenchymal over an amoeboid motility phenotype using a malignant breast tumor cell line, MDA-MB-231, embedded within a 3D collagen matrix. Amoeboid cells are rounded in shape, while mesenchymal cells are elongated, and their migrations are governed by a distinctly different set of biomolecules. Using single cell tracking analysis, we also show that EGF promotes cell dissemination through a significant increase in cell persistence along with a moderate increase of speed. The increase of persistence is correlated with the increase of the percentage of the mesenchymal cells within the population. Our work reveals a novel role of microenvironmental cue, EGF, in modulating heterogeneity and plasticity of tumor cell motility phenotype. In addition, it suggests a potential visual cue for diagnosing invasive states of breast cancer cells. This work can be easily extended beyond breast cancer cells.