Ex Vivo Testing of Patient-Derived Xenografts Mirrors the Clinical Outcome of Patients with Pancreatic Ductal Adenocarcinoma

AI-empowered perturbation proteomics for complex biological systems

The insufficient availability of comprehensive protein-level perturbation data is impeding the widespread adoption of systems biology. In this perspective, we introduce the rationale, essentiality, and practicality of perturbation proteomics. Biological systems are perturbed with diverse biological, chemical, and/or physical factors, followed by proteomic measurements at various levels, including changes in protein expression and turnover, post-translational modifications, protein interactions, transport, and localization, along with phenotypic data. Computational models, employing traditional machine learning or deep learning, identify or predict perturbation responses, mechanisms of action, and protein functions, aiding in therapy selection, compound design, and efficient experiment design. We propose to outline a generic PMMP (perturbation, measurement, modeling to prediction) pipeline and build foundation models or other suitable mathematical models based on large-scale perturbation proteomic data. Finally, we contrast modeling between artificially and naturally perturbed systems and highlight the importance of perturbation proteomics for advancing our understanding and predictive modeling of biological systems.

Unravelling the complexities of resistance mechanism in pancreatic cancer: Insights from in vitro and ex-vivo model systems

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer with poor prognosis and rising global deaths. Late diagnosis, due to absent early symptoms and biomarkers, limits treatment mainly to chemotherapy, which soon encounters resistance. PDAC treatment innovation is hampered by its complex and heterogeneous resistant nature, including mutations in key genes and a stromal-rich, immunosuppressive tumour microenvironment. Recent studies on PDAC resistance stress the need for suitable in vitro and ex vivo models to replicate its complex molecular and microenvironmental landscape. This review summarises advances in these models, which can aid in combating chemoresistance and serve as platforms for discovering new therapeutics. Immortalised cell lines offer homogeneity, unlimited proliferation, and reproducibility, but while many gemcitabine-resistant PDAC cell lines exist, fewer models are available for resistance to other drugs. Organoids from PDAC patients show promise in mimicking tumour heterogeneity and chemosensitivity. Bioreactors, co-culture systems and organotypic slices, incorporating stromal and immune cells, are being developed to understand tumour-stroma interactions and the tumour microenvironment's role in drug resistance. Lastly, another innovative approach is three-dimensional bioprinting, which creates tissue-like structures resembling PDAC architecture, allowing for drug screening. These advanced models can guide researchers in selecting optimal in vitro tests, potentially improving therapeutic strategies and patient outcomes.

BP1003 Decreases STAT3 Expression and Its Pro-Tumorigenic Functions in Solid Tumors and the Tumor Microenvironment

Overexpression and aberrant activation of signal transducer and activator of transcription 3 (STAT3) contribute to tumorigenesis, drug resistance, and tumor-immune evasion, making it a potential cancer therapeutic target. BP1003 is a neutral liposome incorporated with a nuclease-resistant P-ethoxy antisense oligodeoxynucleotide (ASO) targeting the STAT3 mRNA. Its unique design enhances BP1003 stability, cellular uptake, and target affinity. BP1003 efficiently reduces STAT3 expression and enhances the sensitivity of breast cancer cells (HER2+, triple negative) and ovarian cancer cells (late stage, invasive ovarian cancer) to paclitaxel and 5-fluorouracil (5-FU) in both 2D and 3D cell cultures. Similarly, ex vivo and in vivo patient-derived models of pancreatic ductal adenocarcinoma (PDAC) show reduced tissue viability and tumor volume with BP1003 and gemcitabine combination treatments. In addition to directly affecting tumor cells, BP1003 can modulate the tumor microenvironment. Unlike M1 differentiation, monocyte differentiation into anti-inflammatory M2 macrophages is suppressed by BP1003, indicating its potential contribution to immunotherapy. The broad anti-tumor effect of BP1003 in numerous preclinical solid tumor models, such as breast, ovarian, and pancreatic cancer models shown in this work, makes it a promising cancer therapeutic.

Transcriptomic analysis-guided assessment of precision-cut tumor slices (PCTS) as an ex-vivo tool in cancer research

With cancer immunotherapy and precision medicine dynamically evolving, there is greater need for pre-clinical models that can better replicate the intact tumor and its complex tumor microenvironment (TME). Precision-cut tumor slices (PCTS) have recently emerged as an ex vivo human tumor model, offering the opportunity to study individual patient responses to targeted therapies, including immunotherapies. However, little is known about the physiologic status of PCTS and how culture conditions alter gene expression. In this study, we generated PCTS from head and neck cancers (HNC) and mesothelioma tumors (Meso) and undertook transcriptomic analyses to understand the changes that occur in the timeframe between PCTS generation and up to 72 h (hrs) in culture. Our findings showed major changes occurring during the first 24 h culture period of PCTS, involving genes related to wound healing, extracellular matrix, hypoxia, and IFNγ-dependent pathways in both tumor types, as well as tumor-specific changes. Collectively, our data provides an insight into PCTS physiology, which should be taken into consideration when designing PCTS studies, especially in the context of immunology and immunotherapy.

Patient-Derived Models of Cancer in the NCI PDMC Consortium: Selection, Pitfalls, and Practical Recommendations

For over a century, early researchers sought to study biological organisms in a laboratory setting, leading to the generation of both in vitro and in vivo model systems. Patient-derived models of cancer (PDMCs) have more recently come to the forefront of preclinical cancer models and are even finding their way into clinical practice as part of functional precision medicine programs. The PDMC Consortium, supported by the Division of Cancer Biology in the National Cancer Institute of the National Institutes of Health, seeks to understand the biological principles that govern the various PDMC behaviors, particularly in response to perturbagens, such as cancer therapeutics. Based on collective experience from the consortium groups, we provide insight regarding PDMCs established both in vitro and in vivo, with a focus on practical matters related to developing and maintaining key cancer models through a series of vignettes. Although every model has the potential to offer valuable insights, the choice of the right model should be guided by the research question. However, recognizing the inherent constraints in each model is crucial. Our objective here is to delineate the strengths and limitations of each model as established by individual vignettes. Further advances in PDMCs and the development of novel model systems will enable us to better understand human biology and improve the study of human pathology in the lab.

Real time ex vivo chemosensitivity assay for pancreatic adenocarcinoma

BACKGROUND

Patient-derived organoids (PDOs) and xenografts (PDXs) have been extensively studied for drug-screening. However, their usage is limited due to lengthy establishment time, high engraftment failure rates and different tumor microenvironment from original tumors. To overcome the limitations, we developed real time-live tissue sensitivity assay (RT-LTSA) using fresh tumor samples.

METHODS

Tissue slices from resected pancreatic cancer samples were placed in 96-well plates, and the slices were treated with chemotherapeutic agents. The correlation between the chemo-sensitivity of tissue slices and each patient's clinical outcome was analyzed.

RESULTS

The viability and tumor microenvironment of the tissue slices are well-preserved over 5 days. The drug sensitivity assay results are available within 5 days after tissue collection. While all 4 patients who received RT-LTSA sensitive adjuvant regimens did not develop recurrence, 7 of 8 patients who received resistant adjuvant regimens developed recurrence. We observed significantly improved disease-free survival in the patients who received RT-LTSA sensitive adjuvant regimens (median: not reached versus 10.6 months, P = 0.02) compared with the patient who received resistant regimens. A significant negative correlation between RT-LTSA value and relapse-free survival was observed (Somer's D: -0.58; P = 0.016).

CONCLUSIONS

RT-LTSA which maintains the tumor microenvironment and architecture as found in patients may reflect clinical outcome and could be used as a personalized strategy for pancreatic adenocarcinoma. Further, studies are warranted to verify the findings.

Translational relevance of SOS1 targeting for KRAS-mutant colorectal cancer

It has been challenging to target mutant KRAS (mKRAS) in colorectal cancer (CRC) and other malignancies. Recent efforts have focused on developing inhibitors blocking molecules essential for KRAS activity. In this regard, SOS1 inhibition has arisen as an attractive approach for mKRAS CRC given its essential role as a guanine nucleotide exchange factor for this GTPase. Here, we demonstrated the translational value of SOS1 blockade in mKRAS CRC. We used CRC patient-derived organoids (PDOs) as preclinical models to evaluate their sensitivity to SOS1 inhibitor BI3406. A combination of in silico analyses and wet lab techniques was utilized to define potential predictive markers for SOS1 sensitivity and potential mechanisms of resistance in CRC. RNA-seq analysis of CRC PDOs revealed two groups of CRC PDOs with differential sensitivities to SOS1 inhibitor BI3406. The resistant group was enriched in gene sets involving cholesterol homeostasis, epithelial-mesenchymal transition, and TNF-α/NFκB signaling. Expression analysis identified a significant correlation between SOS1 and SOS2 mRNA levels (Spearman's ρ 0.56, p < 0.001). SOS1/2 protein expression was universally present with heterogeneous patterns in CRC cells but only minimal to none in surrounding nonmalignant cells. Only SOS1 protein expression was associated with worse survival in patients with RAS/RAF mutant CRC (p = 0.04). We also found that SOS1/SOS2 protein expression ratio >1 by immunohistochemistry (p = 0.03) instead of KRAS mutation (p = 1) was a better predictive marker to BI3406 sensitivity of CRC PDOs, concordant with the significant positive correlation between SOS1/SOS2 protein expression ratio and SOS1 dependency. Finally, we showed that GTP-bound RAS level underwent rebound even in BI3406-sensitive PDOs with no change of KRAS downstream effector genes, thus suggesting upregulation of guanine nucleotide exchange factor as potential cellular adaptation mechanisms to SOS1 inhibition. Taken together, our results show that high SOS1/SOS2 protein expression ratio predicts sensitivity to SOS1 inhibition and support further clinical development of SOS1-targeting agents in CRC.

A living biobank of matched pairs of patient-derived xenografts and organoids for cancer pharmacology

Patient-derived tumor xenograft (PDX)/organoid (PDO), driven by cancer stem cells (CSC), are considered the most predictive models for translational oncology. Large PDX collections reflective of patient populations have been created and used extensively to test various investigational therapies, including population-trials as surrogate subjects in vivo. PDOs are recognized as in vitro surrogates for patients amenable for high-throughput screening (HTS). We have built a biobank of carcinoma PDX-derived organoids (PDXOs) by converting an existing PDX library and confirmed high degree of similarities between PDXOs and parental PDXs in genomics, histopathology and pharmacology, suggesting "biological equivalence or interchangeability" between the two. Here we demonstrate the applications of PDXO biobank for HTS "matrix" screening for both lead compounds and indications, immune cell co-cultures for immune-therapies and engineering enables in vitro/in vivo imaging. This large biobank of >550 matched pairs of PDXs/PDXOs across different cancers could become powerful tools for the future cancer drug discovery.

3D imaging analysis on an organoid-based platform guides personalized treatment in pancreatic ductal adenocarcinoma

BACKGROUNDPancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies, with unpredictable responses to chemotherapy. Approaches to assay patient tumors before treatment and identify effective treatment regimens based on tumor sensitivities are lacking. We developed an organoid-based platform (OBP) to visually quantify patient-derived organoid (PDO) responses to drug treatments and associated tumor-stroma modulation for personalized PDAC therapy.METHODSWe retrospectively quantified apoptotic responses and tumor-stroma cell proportions in PDOs via 3D immunofluorescence imaging through annexin A5, α-smooth muscle actin (α-SMA), and cytokeratin 19 (CK-19) levels. Simultaneously, an ex vivo organoid drug sensitivity assay (ODSA) was used to measure responses to standard-of-care regimens. Differences between ODSA results and patient tumor responses were assessed by exact McNemar's test.RESULTSImmunofluorescence signals, organoid growth curves, and Ki-67 levels were measured and authenticated through the OBP for up to 14 days. ODSA drug responses were not different from patient tumor responses, as reflected by CA19-9 reductions following neoadjuvant chemotherapy (P = 0.99). PDOs demonstrated unique apoptotic and tumor-stroma modulation profiles (P < 0.0001). α-SMA/CK-19 ratio levels of more than 1.0 were associated with improved outcomes (P = 0.0179) and longer parental patient survival by Kaplan-Meier analysis (P = 0.0046).CONCLUSIONHeterogenous apoptotic drug responses and tumor-stroma modulation are present in PDOs after standard-of-care chemotherapy. Ratios of α-SMA and CK-19 levels in PDOs are associated with patient survival, and the OBP could aid in the selection of personalized therapies to improve the efficacy of systemic therapy in patients with PDAC.FUNDINGNIH/National Cancer Institute grants (K08CA218690, P01 CA117969, R50 CA243707-01A1, U54CA224065), the Skip Viragh Foundation, the Bettie Willerson Driver Cancer Research Fund, and a Cancer Center Support Grant for the Flow Cytometry and Cellular Imaging Core Facility (P30CA16672).

Assessment of stromal SCD-induced drug resistance of PDAC using 3D-printed zPDX model chips

Lipid metabolism is extensively reprogrammed in pancreatic ductal adenocarcinoma (PDAC). Stearoyl-coenzyme A desaturase (SCD) is a critical lipid regulator that was unexplored in PDAC. Here, we characterized the existence of cancer-associated fibroblasts (CAFs) with high SCD expression, and revealed them as an unfavorable prognostic factor. Therefore, primary CAFs and pancreatic cancer cells were harvested and genetically labeled. The mixture of CAFs and cancer cells were co-injected into scd^-/-; prkdc^-/-, or hIGF1/INS-expressing zebrafish to generate patient-derived xenograft models (zPDX). The models were aligned in 3D-printed chips for semi-automatic drug administration and high-throughput scanning. The results showed that chaperoning of the SCD-high CAFs significantly improved the drug resistance of pancreatic cancer cells against gemcitabine and cisplatin, while the administration of SCD inhibitors neutralized the protective effect. Our studies revealed the prognostic and therapeutic value of stromal SCD in PDAC, and proposed the application of zPDX model chips for drug testing.

Pharmacometabolomics reveals urinary diacetylspermine as a biomarker of doxorubicin effectiveness in triple negative breast cancer

Triple-negative breast cancer (TNBC) patients receive chemotherapy treatment, including doxorubicin, due to the lack of targeted therapies. Drug resistance is a major cause of treatment failure in TNBC and therefore, there is a need to identify biomarkers that determine effective drug response. A pharmacometabolomics study was performed using doxorubicin sensitive and resistant TNBC patient-derived xenograft (PDX) models to detect urinary metabolic biomarkers of treatment effectiveness. Evaluation of metabolite production was assessed by directly studying tumor levels in TNBC-PDX mice and human subjects. Metabolic flux leading to biomarker production was determined using stable isotope-labeled tracers in TNBC-PDX ex vivo tissue slices. Findings were validated in 12-h urine samples from control (n = 200), ER+/PR+ (n = 200), ER+/PR+/HER2+ (n = 36), HER2+ (n = 81) and TNBC (n = 200) subjects. Diacetylspermine was identified as a urine metabolite that robustly changed in response to effective doxorubicin treatment, which persisted after the final dose. Urine diacetylspermine was produced by the tumor and correlated with tumor volume. Ex vivo tumor slices revealed that doxorubicin directly increases diacetylspermine production by increasing tumor spermidine/spermine N¹-acetyltransferase 1 expression and activity, which was corroborated by elevated polyamine flux. In breast cancer patients, tumor diacetylspermine was elevated compared to matched non-cancerous tissue and increased in HER2+ and TNBC compared to ER+ subtypes. Urine diacetylspermine was associated with breast cancer tumor volume and poor tumor grade. This study describes a pharmacometabolomics strategy for identifying cancer metabolic biomarkers that indicate drug response. Our findings characterize urine diacetylspermine as a non-invasive biomarker of doxorubicin effectiveness in TNBC.

Precision oncology using ex vivo technology: a step towards individualised cancer care?

Despite advances in cancer genomics and the increased use of genomic medicine, metastatic cancer is still mostly an incurable and fatal disease. With diminishing returns from traditional drug discovery strategies, and high clinical failure rates, more emphasis is being placed on alternative drug discovery platforms, such as ex vivo approaches. Ex vivo approaches aim to embed biological relevance and inter-patient variability at an earlier stage of drug discovery, and to offer more precise treatment stratification for patients. However, these techniques also have a high potential to offer personalised therapies to patients, complementing and enhancing genomic medicine. Although an array of approaches are available to researchers, only a minority of techniques have made it through to direct patient treatment within robust clinical trials. Within this review, we discuss the current challenges to ex vivo approaches within clinical practice and summarise the contemporary literature which has directed patient treatment. Finally, we map out how ex vivo approaches could transition from a small-scale, predominantly research based technology to a robust and validated predictive tool. In future, these pre-clinical approaches may be integrated into clinical cancer pathways to assist in the personalisation of therapy choices and to hopefully improve patient experiences and outcomes.

Precision-Cut Tumor Slices (PCTS) as an Ex Vivo Model in Immunotherapy Research

Precision-cut tumor slices (PCTS) have recently emerged as important ex vivo human tumor models, offering the opportunity to study individual patient responses to targeted immunotherapies, including CAR-T cell therapies. In this review, an outline of different human tumor models available in laboratory settings is provided, with a focus on the unique characteristics of PCTS. Standard PCTS generation and maintenance procedures are outlined, followed by an in-depth overview of PCTS utilization in preclinical research aiming to better understand the unique functional characteristics of cytotoxic T cells within human tumors. Furthermore, recent studies using PCTS as an ex vivo model for predicting patient responses to immunotherapies and other targeted therapies against solid tumors are thoroughly presented. Finally, the advantages and limitations of the PCTS models are discussed. PCTS are expected to gain momentum and be fully utilized as a significant tool towards better patient stratification and personalized medicine.

Interplay between Cellular and Non-Cellular Components of the Tumour Microenvironment in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most common and lethal cancers worldwide. Currently, treatments available for advanced HCC provide dismal chances of survival, thus there is an urgent need to develop more effective therapeutic strategies. While much of the focus of recent decades has been on targeting malignant cells, promising results have emerged from targeting the tumour microenvironment (TME). The extracellular matrix (ECM) is the main non-cellular component of the TME and it profoundly changes during tumorigenesis to promote the growth and survival of malignant cells. Despite this, many in vitro models for drug testing fail to consider the TME leading to a high failure rate in clinical trials. Here, we present an overview of the function and properties of the ECM in the liver and how these change during malignant transformation. We also discuss the relationship between immune cells and ECM in the TME in HCC. Lastly, we present advanced, 3D culture techniques of cancer modelling and argue that the incorporation of TME components into these is essential to better recapitulate the complex interactions within the TME.

Models for Translational Proton Radiobiology-From Bench to Bedside and Back

The number of proton therapy centers worldwide are increasing steadily, with more than two million cancer patients treated so far. Despite this development, pending questions on proton radiobiology still call for basic and translational preclinical research. Open issues are the on-going discussion on an energy-dependent varying proton RBE (relative biological effectiveness), a better characterization of normal tissue side effects and combination treatments with drugs originally developed for photon therapy. At the same time, novel possibilities arise, such as radioimmunotherapy, and new proton therapy schemata, such as FLASH irradiation and proton mini-beams. The study of those aspects demands for radiobiological models at different stages along the translational chain, allowing the investigation of mechanisms from the molecular level to whole organisms. Focusing on the challenges and specifics of proton research, this review summarizes the different available models, ranging from in vitro systems to animal studies of increasing complexity as well as complementing in silico approaches.

Compound NSC84167 selectively targets NRF2-activated pancreatic cancer by inhibiting asparagine synthesis pathway

Nuclear factor erythroid 2-related factor 2 (NRF2) is aberrantly activated in about 93% of pancreatic cancers. Activated NRF2 regulates multiple downstream molecules involved in cancer cell metabolic reprogramming, translational control, and treatment resistance; however, targeting NRF2 for pancreatic cancer therapy remains largely unexplored. In this study, we used the online computational tool CellMinerTM to explore the NCI-60 drug databases for compounds with anticancer activities correlating most closely with the mRNA expression of NQO1, a marker for NRF2 pathway activity. Among the >100,000 compounds analyzed, NSC84167, termed herein as NRF2 synthetic lethality compound-01 (NSLC01), was one of the top hits (r = 0.71, P < 0.001) and selected for functional characterization. NSLC01 selectively inhibited the viabilities of four out of seven conventional pancreatic cancer cell lines and induced dramatic apoptosis in the cells with high NRF2 activation. The selective anticancer activity of NSLC01 was further validated with a panel of nine low-passage pancreatic patient-derived cell lines, and a significant reverse correlation between log(IC50) of NSLC01 and NQO1 expression was confirmed (r = -0.5563, P = 0.024). Notably, screening of a panel of nine patient-derived xenografts (PDXs) revealed six PDXs with high NQO1/NRF2 activation, and NSLC01 dramatically inhibited the viabilities and induced apoptosis in ex vivo cultures of PDX tumors. Consistent with the ex vivo results, NSLC01 inhibited the tumor growth of two NRF2-activated PDX models in vivo (P < 0.01, n = 7-8) but had no effects on the NRF2-low counterpart. To characterize the mechanism of action, we employed a metabolomic isotope tracer assay that demonstrated that NSLC01-mediated inhibition of de novo synthesis of multiple amino acids, including asparagine and methionine. Importantly, we further found that NSLC01 suppresses the eEF2K/eEF2 translation elongation cascade and protein translation of asparagine synthetase. In summary, this study identified a novel compound that selectively targets protein translation and induces synthetic lethal effects in NRF2-activated pancreatic cancers.

Does the Microenvironment Hold the Hidden Key for Functional Precision Medicine in Pancreatic Cancer?

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers and no significant improvement in patient survival has been seen in the past three decades. Treatment options are limited and selection of chemotherapy in the clinic is usually based on the performance status of a patient rather than the biology of their disease. In recent years, research has attempted to unlock a personalised treatment strategy by identifying actionable molecular targets in tumour cells or using preclinical models to predict the effectiveness of chemotherapy. However, these approaches rely on the biology of PDAC tumour cells only and ignore the importance of the microenvironment and fibrotic stroma. In this review, we highlight the importance of the microenvironment in driving the chemoresistant nature of PDAC and the need for preclinical models to mimic the complex multi-cellular microenvironment of PDAC in the precision medicine pipeline. We discuss the potential for ex vivo whole-tissue culture models to inform precision medicine and their role in developing novel therapeutic strategies that hit both tumour and stromal compartments in PDAC. Thus, we highlight the critical role of the tumour microenvironment that needs to be addressed before a precision medicine program for PDAC can be implemented.

Oncogenic KRAS Recruits an Expansive Transcriptional Network through Mutant p53 to Drive Pancreatic Cancer Metastasis

Pancreatic ductal adenocarcinoma (PDAC) is almost uniformly fatal and characterized by early metastasis. Oncogenic KRAS mutations prevail in 95% of PDAC tumors and co-occur with genetic alterations in the TP53 tumor suppressor in nearly 70% of patients. Most TP53 alterations are missense mutations that exhibit gain-of-function phenotypes that include increased invasiveness and metastasis, yet the extent of direct cooperation between KRAS effectors and mutant p53 remains largely undefined. We show that oncogenic KRAS effectors activate CREB1 to allow physical interactions with mutant p53 that hyperactivate multiple prometastatic transcriptional networks. Specifically, mutant p53 and CREB1 upregulate the prometastatic, pioneer transcription factor FOXA1, activating its transcriptional network while promoting WNT/β-catenin signaling, together driving PDAC metastasis. Pharmacologic CREB1 inhibition dramatically reduced FOXA1 and β-catenin expression and dampened PDAC metastasis, identifying a new therapeutic strategy to disrupt cooperation between oncogenic KRAS and mutant p53 to mitigate metastasis. SIGNIFICANCE: Oncogenic KRAS and mutant p53 are the most commonly mutated oncogene and tumor suppressor gene in human cancers, yet direct interactions between these genetic drivers remain undefined. We identified a cooperative node between oncogenic KRAS effectors and mutant p53 that can be therapeutically targeted to undermine cooperation and mitigate metastasis.This article is highlighted in the In This Issue feature, p. 1861.

Validation of a multicellular tumor microenvironment system for modeling patient tumor biology and drug response

Lung cancer rates are rising globally and non-small cell lung cancer (NSCLC) has a five year survival rate of only 24%. Unfortunately, the development of drugs to treat cancer is severely hampered by the inefficiency of translating pre-clinical studies into clinical benefit. Thus, we sought to apply a tumor microenvironment system (TMES) to NSCLC. Using microvascular endothelial cells, lung cancer derived fibroblasts, and NSCLC tumor cells in the presence of in vivo tumor-derived hemodynamic flow and transport, we demonstrate that the TMES generates an in-vivo like biological state and predicts drug response to EGFR inhibitors. Transcriptomic and proteomic profiling indicate that the TMES recapitulates the in vivo and patient molecular biological state providing a mechanistic rationale for the predictive nature of the TMES. This work further validates the TMES for modeling patient tumor biology and drug response indicating utility of the TMES as a predictive tool for drug discovery and development and potential for use as a system for patient avatars.

A triple-drug nanotherapy to target breast cancer cells, cancer stem cells, and tumor vasculature

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer, accounting for the majority of breast cancer-related death. Due to the lack of specific therapeutic targets, chemotherapeutic agents (e.g., paclitaxel) remain the mainstay of systemic treatment, but enrich a subpopulation of cells with tumor-initiating capacity and stem-like characteristics called cancer stem cells (CSCs); thus development of a new and effective strategy for TNBC treatment is an unmet medical need. Cancer nanomedicine has transformed the landscape of cancer drug development, allowing for a high therapeutic index. In this study, we developed a new therapy by co-encapsulating clinically approved drugs, such as paclitaxel, verteporfin, and combretastatin (CA4) in polymer-lipid hybrid nanoparticles (NPs) made of FDA-approved biomaterials. Verteporfin is a drug used in the treatment of macular degeneration and has recently been found to inhibit the Hippo/YAP (Yes-associated protein) pathway, which is known to promote the progression of breast cancer and the development of CSCs. CA4 is a vascular disrupting agent and has been tested in phase II/III of clinical trials. We found that our new three drug-NP not only effectively inhibited TNBC cell viability and cell migration, but also significantly diminished paclitaxel-induced and/or CA4-induced CSC enrichment in TNBC cells, partially through inhibiting the upregulated Hippo/YAP signaling. Combination of verteporfin and CA4 was also more effective in suppressing angiogenesis in an in vivo zebrafish model than single drug alone. The efficacy and application potential of our triple drug-NPs were further assessed by using clinically relevant patient-derived xenograft (PDX) models. Triple drug-NP effectively inhibited the viability of PDX organotypic slide cultures ex vivo and stopped the growth of PDX tumors in vivo. This study developed an approach capable of simultaneously inhibiting bulk cancer cells, CSCs, and angiogenesis.

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.

CES2 Expression in Pancreatic Adenocarcinoma Is Predictive of Response to Irinotecan and Is Associated With Type 2 Diabetes

PURPOSE

The combination chemotherapy of fluorouracil, leucovorin, irinotecan, and oxaliplatin (FOLFIRINOX) has provided clinically meaningful improvement for pancreatic ductal adenocarcinoma (PDAC). We previously uncovered a role for the serine hydrolase carboxylesterase 2 (CES2) in mediating intratumoral activation of the prodrug irinotecan, a constituent of FOLFIRINOX. We aimed to further test the predictive value of CES2 for response to irinotecan using patient-derived xenograft (PDX) models and to elucidate the determinants of CES2 expression and response to FOLFIRINOX treatment among patients with PDAC.

METHODS

PDXs were engrafted subcutaneously into nude mice and treated for 4 weeks with either saline control or irinotecan. CES2 and hepatocyte nuclear factor 4 alpha (HNF4A) expression in PDAC tissues was evaluated by immunohistochemical and Western blot analysis. Kaplan-Meier and Cox regression analyses were applied to assess the association between overall survival and hemoglobin A1C (HbA1C) levels in patients who underwent neoadjuvant FOLFIRINOX treatment.

RESULTS

High CES2 activity in PDAC PDXs was associated with increased sensitivity to irinotecan. Integrated gene expression, proteomic analyses, and in vitro genetic experiments revealed that nuclear receptor HNF4A, which is upregulated in diabetes, is the upstream transcriptional regulator of CES2 expression. Elevated CES2 protein expression in PDAC tissues was positively associated with a history of type 2 diabetes (odds ratio, 4.84; P = .02). High HbA1C levels were associated with longer overall survival in patients who received neoadjuvant FOLFIRINOX treatment (P = .04).

CONCLUSION

To our knowledge, we provide, for the first time, evidence that CES2 expression is associated with a history of type 2 diabetes in PDAC and that elevated HbA1C, by predicting tumor CES2 expression, may represent a novel marker for stratifying patients most likely to respond to FOLFIRINOX therapy.

Modern Approaches to Testing Drug Sensitivity of Patients' Tumors (Review)

Drug therapy is still one of the basic techniques used to treat cancers of different etiology. However, tumor resistance to drugs is a pressing problem limiting drug treatment efficacy. It is obvious for both modern fundamental and clinical oncology that there is the need for an individual approach to treating cancer taking into account the biological properties of a tumor when prescribing chemo- and targeted therapy. One of the promising strategies is to increase the antitumor therapy efficacy by developing predictive tests, which enable to evaluate the sensitivity of a particular tumor to a specific drug or a drug combination before the treatment initiation and, thus, make individual therapy selection possible. The present review considers the main approaches to drug sensitivity assessment of patients' tumors: molecular genetic profiling of tumor cells, and direct efficiency testing of the drugs on tumor cells isolated from surgical or biopsy material. There were analyzed the key directions in research and clinical studies such as: the search for predictive molecular markers, the development of methods to maintain tumor cells or tissue sections viable, i.e. in a condition maximum close to their physiological state, the development of high throughput systems to assess therapy efficiency. Special attention was given to a patient-centered approach to drug therapy in colorectal cancer.

Targeting Hypoxia Sensitizes TNBC to Cisplatin and Promotes Inhibition of Both Bulk and Cancer Stem Cells

Development of targeted therapies for triple-negative breast cancer (TNBC) is an unmet medical need. Cisplatin has demonstrated its promising potential for the treatment of TNBC in clinical trials; however, cisplatin treatment is associated with hypoxia that, in turn, promotes cancer stem cell (CSC) enrichment and drug resistance. Therapeutic approaches to attenuate this may lead to increased cisplatin efficacy in the clinic for the treatment of TNBC. In this report we analyzed clinical datasets of TNBC and found that TNBC patients possessed higher levels of EGFR and hypoxia gene expression. A similar expression pattern was also observed in cisplatin-resistant ovarian cancer cells. We, thus, developed a new therapeutic approach to inhibit EGFR and hypoxia by combination treatment with metformin and gefitinib that sensitized TNBC cells to cisplatin and led to the inhibition of both CD44+/CD24− and ALDH+ CSCs. We demonstrated a similar inhibition efficacy on organotypic cultures of TNBC patient samples ex vivo. Since these drugs have already been used frequently in the clinic; this study illustrates a novel, clinically translatable therapeutic approach to treat patients with TNBC.

Tumour-reprogrammed stromal BCAT1 fuels branched-chain ketoacid dependency in stromal-rich PDAC tumours

Branched-chain amino acids (BCAAs) supply both carbon and nitrogen in pancreatic cancers, and increased levels of BCAAs have been associated with increased risk of pancreatic ductal adenocarcinomas (PDACs). It remains unclear, however, how stromal cells regulate BCAA metabolism in PDAC cells and how mutualistic determinants control BCAA metabolism in the tumour milieu. Here, we show distinct catabolic, oxidative and protein turnover fluxes between cancer-associated fibroblasts (CAFs) and cancer cells, and a marked reliance on branched-chain α-ketoacid (BCKA) in PDAC cells in stroma-rich tumours. We report that cancer-induced stromal reprogramming fuels this BCKA demand. The TGF-β-SMAD5 axis directly targets BCAT1 in CAFs and dictates internalization of the extracellular matrix from the tumour microenvironment to supply amino-acid precursors for BCKA secretion by CAFs. The in vitro results were corroborated with circulating tumour cells (CTCs) and PDAC tissue slices derived from people with PDAC. Our findings reveal therapeutically actionable targets in pancreatic stromal and cancer cells.

Multiplexed drug testing of tumor slices using a microfluidic platform

Current methods to assess the drug response of individual human cancers are often inaccurate, costly, or slow. Functional approaches that rapidly and directly assess the response of patient cancer tissue to drugs or small molecules offer a promising way to improve drug testing, and have the potential to identify the best therapy for individual patients. We developed a digitally manufactured microfluidic platform for multiplexed drug testing of intact cancer slice cultures, and demonstrate the use of this platform to evaluate drug responses in slice cultures from human glioma xenografts and patient tumor biopsies. This approach retains much of the tissue microenvironment and can provide results rapidly enough, within days of surgery, to guide the choice of effective initial therapies. Our results establish a useful preclinical platform for cancer drug testing and development with the potential to improve cancer personalized medicine.

Quantification of fluorophore distribution and therapeutic response in matched in vivo and ex vivo pancreatic cancer model systems

Therapeutic resistance plagues cancer outcomes, challenging treatment particularly in aggressive disease. A unique method to decipher drug interactions with their targets and inform therapy is to employ fluorescence-based screening tools; however, to implement productive screening assays, adequate model systems must be developed. Patient-derived pancreatic cancer models (e.g., cell culture, patient-derived xenograft mouse models, and organoids) have been traditionally utilized to predict personalized therapeutic response. However, cost, long read out times and the inability to fully recapitulate the tumor microenvironment have rendered most models incompatible with clinical decision making for pancreatic ductal adenocarcinoma (PDAC) patients. Tumor explant cultures, where patient tissue can be kept viable for up to weeks, have garnered interest as a platform for delivering personalized therapeutic prediction on a clinically relevant timeline. To fully explore this ex vivo platform, a series of studies were completed to quantitatively compare in vivo models with tumor explants, examining gemcitabine therapeutic efficacy, small molecule uptake and drug-target engagement using a novel fluorescently-labeled gemcitabine conjugate. This initial work shows promise for patient-specific therapeutic selection, where tumor explant drug distribution and response recapitulated the in vivo behavior and could provide a valuable platform for understanding mechanisms of therapeutic response and resistance.

Conditionally reprogrammed colorectal cancer cells combined with mouse avatars identify synergy between EGFR and MEK or CDK4/6 inhibitors

Preclinical models, including patient-derived xenograft (PDX) and organoid and primary cell culture, are essential for studies of cancer cell biology and facilitate translational research and individualization of therapy. We explored the optimum preclinical model by modifying the conventional conditional reprogramming (CR) system followed by screening effective targeted drug combinations against colorectal cancer (CRC). By modifying the ingredients of the culture medium used in a conventional CR system, a novel individualized CR system (termed i-CR) was established. Tumor samples from CRC patients were collected and PDX models were derived followed by high-throughput i-CR drug screening and validation of the effective targeted drug combinations. The i-CR system selectively expanded tumor cells rather than normal epithelial cells and facilitated high-throughput drug screening when combined with high-content imaging and quantitative analysis of cell proliferation. Using inhibitors targeting multiple signaling pathways identified by high-throughput i-CR drug screening, we discovered that inhibition of the EGFR and MEK or CDK4/6 pathways exerted a synergistic inhibitory effect against CRC, and we noted super-synergistic effects when EGFR, MEK, and CDK4/6 inhibitors were used simultaneously. These data were validated using paired PDX models, which showed marked inhibition of tumor growth. The novel i-CR system combined with PDX models will enable individualization of therapy and drug discovery, and strategies combining EGFR, MEK, and CDK4/6 inhibitors warrant clinical validation.

Beclin 1 Promotes Endosome Recruitment of Hepatocyte Growth Factor Tyrosine Kinase Substrate to Suppress Tumor Proliferation

Beclin 1 has nonautophagic functions that include its ability to regulate endocytic receptor trafficking. However, the contribution of this function to tumor suppression is poorly understood. Here, we provide in vivo evidence that Beclin 1 suppresses tumor proliferation by regulating the endocytic trafficking and degradation of the EGFR and transferrin (TFR1) receptors. Beclin 1 promoted endosomal recruitment of hepatocyte growth factor tyrosine kinase substrate (HRS), which was necessary for sorting surface receptors to intraluminal vesicles for signal silencing and lysosomal degradation. In tumors with low Beclin 1 expression, endosomal HRS recruitment was diminished and receptor function was sustained. Collectively, our results demonstrate a novel role for Beclin 1 in impeding tumor growth by coordinating the regulation of key growth factor and nutrient receptors. These data provide an explanation for how low levels of Beclin 1 facilitate tumor proliferation and contribute to poor cancer outcomes. SIGNIFICANCE: Beclin 1 controls the trafficking fate of growth regulatory receptors to suppress tumor proliferation.

Clinical candidate and genistein analogue AXP107-11 has chemoenhancing functions in pancreatic adenocarcinoma through G protein-coupled estrogen receptor signaling

Despite advances in cancer therapeutics, pancreatic cancer remains difficult to treat and often develops resistance to chemotherapies. We have evaluated a bioavailable genistein analogue, AXP107-11 which has completed phase Ib clinical trial, as an approach to sensitize tumor cells to chemotherapy. Using organotypic cultures of 14 patient-derived xenografts (PDX) of pancreatic ductal adenocarcinoma, we found that addition of AXP107-11 indeed sensitized 57% of cases to gemcitabine treatment. Results were validated using PDX models in vivo. Further, RNA-Seq from responsive and unresponsive tumors proposed a 41-gene treatment-predictive signature. Functional and molecular assays were performed in cell lines and demonstrated that the effect was synergistic. Transcriptome analysis indicated activation of G-protein-coupled estrogen receptor (GPER1) as the main underlying mechanism of action, which was corroborated using GPER1-selective agonists and antagonists. GPER1 expression in pancreatic tumors was indicative of survival, and our study proposes that activation of GPER1 may constitute a new avenue for pancreatic cancer therapeutics.

Measuring human carboxylesterase 2 activity in pancreatic cancer patient-derived xenografts using a ratiometric fluorescent chemosensor

Irinotecan-based therapy is a common treatment for pancreatic cancer. To elicit its anticancer activity, the drug requires first the hydrolysis action of the enzyme human carboxylesterase 2 (hCES2). It has been established that pancreatic cancer patients have various levels of hCES2, whereby patients having low levels respond poorer to Irinotecan than patients with higher levels, suggesting that hCES2 can be used to predict response. However, current methods that measure hCES2 activity are inaccurate, complex or lengthy, thus being incompatible for use in a clinical setting. Here, we developed a small molecule ratiometric fluorescent chemosensor that accurately measures hCES2 activity in a single-step within complex mixtures. Our chemosensor is highly selective for hCES2 over hCES1, cell permeable and can measure hCES2 activity in pancreatic cancer patient-derived xenografts. Given the simplicity, accuracy and tissue compatibility of our assay, we anticipate our chemosensor can be used to predict patient response to Irinotecan-based therapy.

Addressing Patient Specificity in the Engineering of Tumor Models

Cancer treatment is challenged by the heterogeneous nature of cancer, where prognosis depends on tumor type and disease stage, as well as previous treatments. Optimal patient stratification is critical for the development and validation of effective treatments, yet pre-clinical model systems are lacking in the delivery of effective individualized platforms that reflect distinct patient-specific clinical situations. Advances in cancer cell biology, biofabrication, and microengineering technologies have led to the development of more complex in vitro three-dimensional (3D) models to act as drug testing platforms and to elucidate novel cancer mechanisms. Mostly, these strategies have enabled researchers to account for the tumor microenvironment context including tumor-stroma interactions, a key factor of heterogeneity that affects both progression and therapeutic resistance. This is aided by state-of-the-art biomaterials and tissue engineering technologies, coupled with reproducible and high-throughput platforms that enable modeling of relevant physical and chemical factors. Yet, the translation of these models and technologies has been impaired by neglecting to incorporate patient-derived cells or tissues, and largely focusing on immortalized cell lines instead, contributing to drug failure rates. While this is a necessary step to establish and validate new models, a paradigm shift is needed to enable the systematic inclusion of patient-derived materials in the design and use of such models. In this review, we first present an overview of the components responsible for heterogeneity in different tumor microenvironments. Next, we introduce the state-of-the-art of current in vitro 3D cancer models employing patient-derived materials in traditional scaffold-free approaches, followed by novel bioengineered scaffold-based approaches, and further supported by dynamic systems such as bioreactors, microfluidics, and tumor-on-a-chip devices. We critically discuss the challenges and clinical prospects of models that have succeeded in providing clinical relevance and impact, and present emerging concepts of novel cancer model systems that are addressing patient specificity, the next frontier to be tackled by the field.

Establishment and Analysis of a 3D Co-Culture Spheroid Model of Pancreatic Adenocarcinoma for Application in Drug Discovery

The high attrition rate of oncology drug candidates can be in part explained by the disconnect between the standard preclinical models (e.g., 2D culture, xenograft tumors) commonly employed for drug discovery and the complex multicellular microenvironment of human cancers. As such, significant focus has recently shifted to the establishment of preclinical models that more closely recapitulate human tumors, such as patient-derived xenografts, 3D spheroids, humanized mice, and mixed-culture models. For these models to be suited to drug discovery, they should optimally exhibit reproducibility, high-throughput, and robust and simple assay readouts. In this article, we describe a protocol for the generation of an in vitro 3D co-culture spheroid model that recapitulates the interaction of tumor cells with stromal fibroblasts in pancreatic adenocarcinoma. We additionally describe protocols relevant to the analysis of these spheroids in high-throughput drug discovery campaigns such as the assessment of spheroid proliferation, immunofluorescence and immunohistochemistry staining of spheroids, live-cell and confocal imaging and analysis of cell surface markers.

Antineoplastic effects of auranofin in human pancreatic adenocarcinoma preclinical models

Background

Auranofin, a Food and Drug Administration–approved anti-rheumatic agent with anticancer properties for lung and ovarian cancer, has never been studied for pancreatic cancer. We hypothesize that auranofin may prevent pancreatic ductal adenocarcinoma progression by inhibition of Txnrd1 and HIF-1α.

Methods

In vitro sensitivity of human pancreatic ductal adenocarcinoma cell lines was determined based on IC50. Western blot assays were used to interrogate mechanisms of apoptosis and resistance. Ex vivo live tissue slice assays of xenografts allowed for testing of a larger number of PDX samples with high efficiency. In vivo pancreatic ductal adenocarcinoma orthotopic mouse models using MiaPaCa-2 Luc + cells were designed to determine optimal dose and antitumor effect.

Results

We found that 10 of 15 tested pancreatic ductal adenocarcinoma cell lines were sensitive to auranofin based on IC50s below 5 μmol/L. Ex vivo tissue growth inhibition greater than 44% was observed for 13 PDX tissue cases treated with 10 μmol/L auranofin. High Txnrd1 expression was observed for resistant cell lines. In vivo studies showed 15 mg/kg IP as the optimal dose with absence of gross solid organ metastasis up to 13 weeks post-treatment (median survival 8 and 12 weeks, respectively; P = .0953).

Conclusions

We have demonstrated that auranofin prevents pancreatic ductal adenocarcinoma progression using multiple models. Our study suggests inhibition of Txnrd1 and HIF-1α as possible mechanisms of action, and Txnrd1 as a biomarker of resistance. Based on these data, an off-label Phase 0 clinical trial with this FDA-approved drug should be considered for patients with pancreatic cancer.

Development of a multicellular pancreatic tumor microenvironment system using patient-derived tumor cells

The development of drugs to treat cancer is hampered by the inefficiency of translating pre-clinical in vitro monoculture and mouse studies into clinical benefit. There is a critical need to improve the accuracy of evaluating pre-clinical drug efficacy through the development of more physiologically relevant models. In this study, a human triculture 3D in vitro tumor microenvironment system (TMES) was engineered to accurately mimic the tumor microenvironment. The TMES recapitulates tumor hemodynamics and biological transport with co-cultured human microvascular endothelial cells, pancreatic ductal adenocarcinoma, and pancreatic stellate cells. We demonstrate that significant tumor cell transcriptomic changes occur in the TMES that correlate with the in vivo xenograft and patient transcriptome. Treatment with therapeutically relevant doses of chemotherapeutics yields responses paralleling the patients' clinical responses. Thus, this model provides a unique platform to rigorously evaluate novel therapies and is amenable to using patient tumor material directly, with applicability for patient avatars.

Academic Discovery of Anticancer Drugs: Historic and Future Perspectives

The identification and prosecution of meritorious anticancer drug targets and the discovery of clinical candidates represent an extraordinarily time- and resource-intensive process, and the current failure rate of late-stage drugs is a critical issue that must be addressed. Relationships between academia and industry in drug discovery and development have continued to change over time as a result of technical and financial challenges and, most importantly, to the objective of translating impactful scientific discoveries into clinical opportunities. This Golden Age of anticancer drug discovery features an increased appreciation for the high-risk, high-innovation research conducted in the nonprofit sector, with the goals of infusing commercial drug development with intellectual capital and curating portfolios that are financially tenable and clinically meaningful. In this review, we discuss the history of academic-industry interactions in the context of antidrug discovery and offer a view of where these interactions are likely headed as we continue to reach new horizons in our understanding of the immense complexities of cancer biology.

Hypoxia-Induced Autophagy Degrades Stromal Lumican into Tumor Microenvironment of Pancreatic Ductal Adenocarcinoma: A Mini-Review

The extracellular matrix (ECM) in the tumor microenvironment (TME) has gained considerable interest in recent years as a crucial component in fundamental cellular processes and provides novel therapeutic targets. Lumican is a class II small leucine-rich proteoglycan with a key role in ECM organization and modulation of biological functions dependent on tumor type, abundance, and stage of disease. The presence of stromal lumican in the ECM surrounding pancreatic ductal adenocarcinoma (PDAC) inhibits cancer cell replication and is associated with improved patient outcomes after multimodal therapies. In this mini-review, were-present our novel findings describing how hypoxia (1% O2) within the TME influences stromal lumican expression and secretion. We observed that hypoxia specifically inhibited lumican expression and secretion post-transcriptionally only from pancreatic stellate cells. Hypoxia-induced increased lactate production did not influence lumican expression. Notably, autophagy was induced by hypoxia in ex vivo cultures of patient-derived primary PDAC xenograft and pancreatic stellate cells; however, the cancer cells remain unaffected. Moreover, hypoxia-inducible factor (HIF)-1α expression or inhibition of AMP-regulated protein kinase (AMPK) activation within hypoxic stellate cells restored lumican expression levels. Interestingly, AMPK inhibition attenuated hypoxia-reduced phosphorylation of the mTOR/p70S6K/4EBP signaling pathway. The aim of this mini-review is to summarize our recent publication that hypoxia reduces stromal lumican in PDAC through autophagy-mediated degradation and reduction in protein synthesis within pancreatic cancer stellate cells. This may provide another plausible mechanism by which hypoxia-induced stromal autophagy leads to cancer growth.

Hypoxia-Induced Autophagy Degrades Stromal Lumican into Tumor Microenvironment of Pancreatic Ductal Adenocarcinoma: A Mini-Review

The extracellular matrix (ECM) in the tumor microenvironment (TME) has gained considerable interest in recent years as a crucial component in fundamental cellular processes and provides novel therapeutic targets. Lumican is a class II small leucine-rich proteoglycan with a key role in ECM organization and modulation of biological functions dependent on tumor type, abundance, and stage of disease. The presence of stromal lumican in the ECM surrounding pancreatic ductal adenocarcinoma (PDAC) inhibits cancer cell replication and is associated with improved patient outcomes after multimodal therapies. In this mini-review, were-present our novel findings describing how hypoxia (1% O2) within the TME influences stromal lumican expression and secretion. We observed that hypoxia specifically inhibited lumican expression and secretion post-transcriptionally only from pancreatic stellate cells. Hypoxia-induced increased lactate production did not influence lumican expression. Notably, autophagy was induced by hypoxia in ex vivo cultures of patient-derived primary PDAC xenograft and pancreatic stellate cells; however, the cancer cells remain unaffected. Moreover, hypoxia-inducible factor (HIF)-1α expression or inhibition of AMP-regulated protein kinase (AMPK) activation within hypoxic stellate cells restored lumican expression levels. Interestingly, AMPK inhibition attenuated hypoxia-reduced phosphorylation of the mTOR/p70S6K/4EBP signaling pathway. The aim of this mini-review is to summarize our recent publication that hypoxia reduces stromal lumican in PDAC through autophagy-mediated degradation and reduction in protein synthesis within pancreatic cancer stellate cells. This may provide another plausible mechanism by which hypoxia-induced stromal autophagy leads to cancer growth.

Tumor Tissue Explant Culture of Patient-Derived Xenograft as Potential Prioritization Tool for Targeted Therapy

Despite of remarkable progress made in the head and neck cancer (HNC) therapy, the survival rate of this metastatic disease remain low. Tailoring the appropriate therapy to patients is a major challenge and highlights the unmet need to have a good preclinical model that will predict clinical response. Hence, we developed an accurate and time efficient drug screening method of tumor ex vivo analysis (TEVA) system, which can predict patient-specific drug responses. In this study, we generated six patient derived xenografts (PDXs) which were utilized for TEVA. Briefly, PDXs were cut into 2 × 2 × 2 mm3 explants and treated with clinically relevant drugs for 24 h. Tumor cell proliferation and death were evaluated by immunohistochemistry and TEVA score was calculated. Ex vivo and in vivo drug efficacy studies were performed on four PDXs and three drugs side-by-side to explore correlation between TEVA and PDX treatment in vivo. Efficacy of drug combinations was also ventured. Optimization of the culture timings dictated 24 h to be the time frame to detect drug responses and drug penetrates 2 × 2 × 2 mm3 explants as signaling pathways were significantly altered. Tumor responses to drugs in TEVA, significantly corresponds with the drug efficacy in mice. Overall, this low cost, robust, relatively simple and efficient 3D tissue-based method, employing material from one PDX, can bypass the necessity of drug validation in immune-incompetent PDX-bearing mice. Our data provides a potential rationale for utilizing TEVA to predict tumor response to targeted and chemo therapies when multiple targets are proposed.

Hypoxia-induced autophagy of stellate cells inhibits expression and secretion of lumican into microenvironment of pancreatic ductal adenocarcinoma

Lumican is secreted by pancreatic stellate cells and inhibits cancer progression. Extracellular lumican inhibits cancer cell replication and restrains growth of early-stage pancreatic adenocarcinoma (PDAC) such that patients with tumors containing stromal lumican experience a three-fold longer survival after treatment. In the present study, patient tumor tissues, ex-vivo cultures of patient-derived xenografts (PDX), PDAC stellate and tumor cells were used to investigate whether hypoxia (1% O2) within the tumor microenvironment influences stromal lumican expression and secretion. We observed that hypoxia significantly reduced lumican expression and secretion from pancreatic stellate cells, but not cancer cells. Although hypoxia enhanced lactate dehydrogenase A (LDHA) expression and lactate secretion from all cells, neither hypoxia-induced nor exogenous lactate influenced lumican expression. Autophagy was induced by hypoxia in ex vivo cultures of PDX and pancreatic stellate cells, but not cancer cells cultured in 2D. Autophagic flux inhibitors, bafilomycin A1, chloroquine diphosphate salt, and ammonium chloride prevented hypoxia-mediated reduction in lumican expression in stellate cells. Furthermore, inhibition of AMP-regulated protein kinase (AMPK) phosphorylation or hypoxia-inducible factor (HIF)-1α expression within hypoxic stellate cells restored lumican expression levels. Hypoxia did not affect lumican mRNA expression, indicating that hypoxia-induced reduction of lumican occurs post-transcriptionally; in addition, AMPK inhibition prevented hypoxia-reduced phosphorylation of the mTOR/p70S6K/4EBP signaling pathway, a key contributor to protein synthesis. Taken together, these findings demonstrate that hypoxia reduces stromal lumican in PDAC through autophagy-mediated degradation and reduction in protein synthesis within pancreatic cancer stellate cells.

A Visually Apparent and Quantifiable CT Imaging Feature Identifies Biophysical Subtypes of Pancreatic Ductal Adenocarcinoma

PURPOSE

Pancreatic ductal adenocarcinoma (PDAC) is a heterogeneous disease with variable presentations and natural histories of disease. We hypothesized that different morphologic characteristics of PDAC tumors on diagnostic computed tomography (CT) scans would reflect their underlying biology.

EXPERIMENTAL DESIGN

We developed a quantitative method to categorize the PDAC morphology on pretherapy CT scans from multiple datasets of patients with resectable and metastatic disease and correlated these patterns with clinical/pathologic measurements. We modeled macroscopic lesion growth computationally to test the effects of stroma on morphologic patterns, hypothesizing that the balance of proliferation and local migration rates of the cancer cells would determine tumor morphology.

RESULTS

In localized and metastatic PDAC, quantifying the change in enhancement on CT scans at the interface between tumor and parenchyma (delta) demonstrated that patients with conspicuous (high-delta) tumors had significantly less stroma, higher likelihood of multiple common pathway mutations, more mesenchymal features, higher likelihood of early distant metastasis, and shorter survival times compared with those with inconspicuous (low-delta) tumors. Pathologic measurements of stromal and mesenchymal features of the tumors supported the mathematical model's underlying theory for PDAC growth.

CONCLUSIONS

At baseline diagnosis, a visually striking and quantifiable CT imaging feature reflects the molecular and pathological heterogeneity of PDAC, and may be used to stratify patients into distinct subtypes. Moreover, growth patterns of PDAC may be described using physical principles, enabling new insights into diagnosis and treatment of this deadly disease.

Advancing precision medicine with personalized drug screening

Personalized drug screening (PDS) of approved drug libraries enables rapid development of specific small-molecule therapies for individual patients. With a multidisciplinary team including clinicians, researchers, ethicists, informaticians and regulatory professionals, patient treatment can be optimized with greater efficacy and fewer adverse effects by using PDS as an approach to find remedies. In addition, PDS has the potential to rapidly identify therapeutics for a patient suffering from a disease without an existing therapy. From cancer to bacterial infections, we review specific maladies addressed with PDS campaigns. We predict that PDS combined with personal genomic analyses will contribute to the development of future precision medicine endeavors.

Ex-vivo organ culture as potential prioritization tool for breast cancer targeted therapy

The growing use of genomic testing presents new treatment options but also new dilemmas. We describe here a heavily-pretreated metastatic triple negative breast cancer patient who failed to respond to conventional treatment. Genomic analyses were performed that discovered several targetable alterations (e.g. FGFR1, CDK6, INSR) and created a clinical challenge - which target to target first? Our solution to this relatively common scenario was using ex-vivo organ culture (EVOC) system to prioritize treatment directed toward the best molecular target. EVOC enabled the trial of several potent targeted agents (Everolimus, Linsitinib, Palbociclib, AZD4547) and allowed semi-quantitative measurement of tumor response. The best response was to FGFR inhibitor, AZD4547. Consequently, the most accessible FGFR inhibiting agents (Pazopanib, then Nintedanib) were administered and some response was achieved. This report provides a potential rationale for utilizing EVOC system to predict tumor response to targeted therapy when multiple targets are proposed.

Stromal barriers to nanomedicine penetration in the pancreatic tumor microenvironment

Pancreatic cancer is known for its dismal prognosis despite efforts to improve therapeutic outcome. Recently, cancer nanomedicine, application of nanotechnology to cancer diagnosis and treatment, has gained interest for treatment of pancreatic cancer. The enhanced permeability and retention (EPR) effect that promotes selective accumulation of nanometer‐sized molecules within tumors is the theoretical rationale of treatment. However, it is clear that EPR may be insufficient in pancreatic cancer as a result of stromal barriers within the tumor microenvironment (TME). These limit intratumoral accumulation of macromolecules. The TME and stromal barriers inside it consist of various stromal cell types which interact both with each other and with tumor cells. We are only beginning to understand the complexities of the stromal barriers within the TME and its functional consequences for nanomedicine. Understanding the complex crosstalk between barrier stromal cells is challenging because of the difficulty of modeling pancreatic cancer TME. Here we provide an overview of stromal barriers within the TME. We also describe the preclinical models, both in vivo and in vitro, developed to study them. We furthermore discuss the critical gaps in our understanding, and how we might formulate a better strategy for using nanomedicine against pancreatic cancer.

Angiogenin/Ribonuclease 5 Is an EGFR Ligand and a Serum Biomarker for Erlotinib Sensitivity in Pancreatic Cancer

Pancreatic ribonuclease (RNase) is a secreted enzyme critical for host defense. We discover an intrinsic RNase function, serving as a ligand for epidermal growth factor receptor (EGFR), a member of receptor tyrosine kinase (RTK), in pancreatic ductal adenocarcinoma (PDAC). The closely related bovine RNase A and human RNase 5 (angiogenin [ANG]) can trigger oncogenic transformation independently of their catalytic activities via direct association with EGFR. Notably, high plasma ANG level in PDAC patients is positively associated with response to EGFR inhibitor erlotinib treatment. These results identify a role of ANG as a serum biomarker that may be used to stratify patients for EGFR-targeted therapies, and offer insights into the ligand-receptor relationship between RNase and RTK families.

Patient Derived Xenografts (PDX) for personalized treatment of pancreatic cancer: emerging allies in the war on a devastating cancer?

The prognosis of pancreatic ductal adenocarcinoma (PDAC), the eighth most lethal cancer for men and ninth for women worldwide, remains dismal. The increasing rates of deaths by PDAC indicate that the overall management of the disease in 21st century is still insufficient. Thus it is obvious that there is an unmet need to improve management of PDAC by finding new biomarkers to screen high risk patients, confirm diagnosis, and predict response to treatment as well more efficacious and safer treatments. Patient Derived Xenografts (PDX) have been developed as a new promising tool in an effort to mirror genetics, tumor heterogeneity and cancer microenvironment of the primary tumor. Herein we aim to give an updated overview of the current status and the perspectives of PDX in the search for the identification of novel biomarkers and improved therapeutic outcomes for PDAC but also their use as a valuable tool towards individualized treatments to improve the outcome of the disease. Furthermore, we critically review the applications, advantages, limitations, and perspectives of PDX in the research towards an improved management of PDAC.

SIGNIFICANCE

This review provides a comprehensive overview of the current status and the potential role as well as the challenges of PDX in the road to fight one of the most lethal cancers in the developed countries, pancreatic ductal adenocarcinoma.

Anti-inflammatory drug resistance selects putative cancer stem cells in a cellular model for genetically predisposed colon cancer

Mutations in the adenomatous polyposis coli (Apc) tumor suppressor gene represent the primary genetic defect in colon carcinogenesis. Apc+/- mouse models exhibit pre-invasive small intestinal adenomas. Cell culture models exhibiting Apc defects in the colon and quantifiable cancer risk provide a novel clinically relevant approach. The tumor-derived Apc-/- colonic epithelial cell line 1638N COL-Pr1 represented the experimental model. The anti-inflammatory drugs sulindac (SUL) and celecoxib (CLX) represented the test compounds. Compared with non-tumorigenic Apc+/+ C57COL cells, the Apc+/- 1638N COL cells and Apc-/- 1638N COL-Pr1 cells exhibited progressive loss of homeostatic growth control. Compared with Apc+/- cells, Apc-/- cells displayed increased expression of biomarkers specific for hyper-proliferation. Treatment of Apc-/- cells with SUL and CLX resulted in inhibition of anchorage-independent colony formation in vitro, which is indicative of reduced cancer risk in vivo. Mechanistically, SUL and CLX suppressed the expression of the Apc target genes β-catenin, cyclin D1, c-Myc and cyclooxygenase-2. Long-term treatment with high concentrations of SUL and CLX led to the selection of hyper-proliferative drug-resistant phenotypes. The Apc-/- SUL-resistant phenotype displayed spheroid formation and enhanced the expression of the stem cell-specific molecular markers CD44, CD133 and c-Myc. These data demonstrated the growth-inhibitory efficacy of SUL and CLX and indicated that drug resistance leads to the selection of a putative cancer stem cell phenotype. The study outcome validates a stem cell-targeted mechanistic approach to identify testable alternative leads for chemotherapy-resistant colon cancer.