Emerging Technologies for the Diagnosis and Treatment of Pancreatic Cancer

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22 Emerging Technologies for the Diagnosis and Treatment of Pancreatic Cancer Magdalena Swierczewska1, Serguei Kozlov2 and Pavan P. Adiseshaiah1 1

Nanotechnology Characterization Laboratory, Cancer Research Technology Program, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD, United States 2Center for Advanced Preclinical Research, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD, United States

HISTOPATHOLOGIC AND MOLECULAR DIVERSITY OF PANCREATIC CANCER Pancreatic cancer continues to be the most fatal type of gastrointestinal malignancy, with the poorest prognosis compared to all other known cancers of the digestive tract (Enewold, Harlan, Tucker, & McKenzie, 2015). Estimations by the American Cancer Society predict that by the end of 2017, approximately 53,670 patients are expected to be newly diagnosed with pancreatic cancer in the United States alone (with the worldwide number reaching 230,000), while about 43,100 patients will ultimately succumb to the disease (American Cancer Society, 2017). The 5-year overall survival of patients with pancreatic

Oncogenomics DOI: https://doi.org/10.1016/B978-0-12-811785-9.00022-3

cancer is at a disheartening 8%, making this cancer the fourth leading cause of cancerrelated death in the United States (Siegel, Miller, & Jemal, 2017). By 2030 the death toll expected from pancreatic cancer is projected to be second among all cancers, conceding only to lung cancer (Rahib et al., 2014). Early detection of pancreatic tumors presents a formidable clinical challenge due to: (1) location of the pancreas deep in the abdominal cavity; (2) generally asymptomatic signs of pancreatic malignancy; (3) frequent misjudgment of initial symptoms as less severe gastrointestinal malfunctions; and (4) lack of minimally invasive diagnostic options, such as those based on reliable and validated molecular biomarkers to detect pancreatic cancer in patient blood or stool, for example.

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In over 95% of clinical pancreatic ductal adenocarcinoma (PDAC) cases, mutations of KRAS protein have been identified, predominantly represented by KRAS-G12D, KRAS-G12V, and KRAS-G13D aberrant isoforms known to render the KRAS-dependent signaling pathway constitutively active in transformed tissues (Stephen, Esposito, Bagni, & McCormick, 2014). As has been shown in preclinical PDAC models, reverting KRAS signaling back to physiological levels obliterates the aggressive phenotype of pancreatic carcinogenesis and results in tumor regression (Collins, Bednar, et al., 2012; Collins, Brisset, et al., 2012; di Magliano & Logsdon, 2013; Ying et al., 2012). These observations provide a foundation for the critical role of KRAS pathway networks in clinical PDAC, and fuel substantial interest in identifying treatments interfering with RAS signaling—efforts proven difficult thus far due to the low “druggability” of RAS pathway components, including the KRAS oncoprotein itself (Cohen et al., 2003; Shen et al., 2015). In addition to KRAS gene mutations, pancreatic tumors’ molecular pathology include a spectrum of pro-cancerous genetic events that confer a more aggressive and malignant phenotype. Specifically, loss or missense mutations in p53 and BRCA1/2 genes, aberrations in TGFβ/SMAD pathway, amplification of EGFR and c-MYC oncoprotein loci are key contributors to PDAC molecular patterns (Ryan, Hong, & Bardeesy, 2014). In addition to the genetic diversity of PDAC, intratumoral heterogeneity, complex cyto-histologic architecture, and mixed cellular composition of PDAC tumors can significantly hinder the clinical success in managing pancreatic cancer. Two components contributing to the progression of PDAC are the desmoplastic stroma and assorted population of infiltrating immune cells. These two prominent features are widely perceived to provide a favorable microenvironment for tumor invasion and metastasis, switching antitumor

immune cells into an anergic state. The hostile tumor microenvironment leads to low tissue patency and poor vascular permeability, which makes the tumor more refractory for drug intervention (Feig et al., 2012; Gore & Korc, 2014; Xu, Pothula, Wilson, & Apte, 2014). The desmoplastic stroma is largely composed of fibrous collagen deposits produced by cancer-associated fibroblasts, which are stimulated by activated pancreatic stellate cells (Apte, Wilson, Lugea, & Pandol, 2013; Erkan, 2013; Haqq et al., 2014; Ramirez et al., 2014). The dense stroma contributes to high solid stress within the tumor, resulting in vascular collapse, breakdown of the lymphatic network, and general hypoxia (Cowan & Maitra, 2014; Nielsen, Mortensen, & Detlefsen, 2016); all of which lead to poor drug delivery to the cancerous lesions (Koay, Baio et al., 2014; Koay, Truty et al., 2014). The majority of infiltrated immune cells in PDAC are tumor associated macrophages polarized by M2 type and regulatory T cells. These can stimulate a pro-inflammatory and pro-oncogenic microenvironment that suppresses surveillance of cancer cells by antitumor immunity (Shibuya et al., 2014). Overall, the hostile PDAC microenvironment plays a role in disease progression and drug resistance and has therefore become a target for therapeutic interventions, as evidenced by recent clinical trials to tackle the desmoplastic stroma (NCT01383538, NCT01839487, NCT01064622, NCT01803282) (Garrido-Laguna & Hidalgo, 2015; Sherman et al., 2014; Stromnes, Brockenbrough, et al., 2014; Stromnes, DelGiorno, Greenberg, & Hingorani, 2014). The interim clinical trial results from novel intervention strategies have demonstrated promising disease outcomes for pancreatic neoplasms (NCT01821729, NCT01839487) (Murphy et al., 2017; Hingorani et al., 2016). This chapter provides an overview of emerging technologies that have the potential to improve the treatment and early diagnosis of patients with pancreatic cancer (Fig. 22.1).

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FIGURE 22.1 Scheme of diagnostic and therapeutic challenges vs. possible solutions for effective management of pancreatic cancer. The challenges in poor therapeutic responses observed in patients with pancreatic cancer can be attributed to several factors—e.g., inadequate diagnosis/clinical signs of early-stage disease, significant pathophysiological barriers for intratumoral drug delivery, and a pro-inflammatory and pro-oncogenic microenvironment. A few of the proposed solutions to improve overall survival in patients with pancreatic cancer are early-stage/localized pancreatic cancer detection (e.g., imaging, reliable and validated clinical biomarkers, e.g., GPC1 positive exosomes) and overcoming pathophysiological barriers to improve anticancer drug delivery (e.g., targeting desmoplastic stroma by Hedgehog inhibitors, losartan, PEGPH20). The pro-inflammatory and immunosuppressive microenvironment further promotes a positive feedback loop to cause cancer aggressiveness and metastasis. Treatment with PD-1 checkpoint inhibitors, also in combination with cytotoxic agents, may recruit host immune recognition and response to tumor-specific neoantigens while disrupting the pro-cancerous signaling networks to effectively treat patients with advanced pancreatic cancer. Overall, an amalgamation of in-depth mechanistic appreciation of pancreatic cancer pathobiology with comprehensive novel treatment strategies is required to overcome the multiple antagonistic factors that contribute to the lethal nature of pancreatic cancer.

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CONVENTIONAL AND NANOMEDICINE TREATMENT STRATEGIES Surgery and Chemotherapy Conventional treatment strategies, such as surgery and chemotherapy, offer limited efficacy for patients with pancreatic cancer. Although surgical resection is the only opportunity of a cure, it is only performed on patients with localized pancreatic cancer, which account for less than one in five patients; and even then, the cancer may be too widespread to be completely resected (American Cancer Society, 2016; Ni, Yang, & Li, 2012). Minimally invasive laparoscopy is now the standard surgical treatment, with some studies showing that roboticassisted surgery is superior to laparoscopy (Baines, Martin, & Rorie, 2016). However, for a vast majority of patients, surgery is not an option and chemotherapy is the standard treatment approach. Gemcitabine monotherapy (Gemzar) has been the first-line chemotherapy treatment for metastatic pancreatic cancer since 1996, but the 5-year survival rate for this disease has not seen a significant increase in the past 20 years. Therefore, a number of combination strategies have been tested in the clinic to improve gemcitabine effectiveness, as summarized previously (Garrido-Laguna & Hidalgo, 2015). After nearly 10 years of gemcitabine as the only firstline chemotherapy, combination treatment of erlotinib, an EGFR tyrosine kinase inhibitor, with gemcitabine was FDA approved for patients with advanced pancreatic cancer. However, in a Phase III trial, erlotinib with gemcitabine treatment only provided a 12-day improvement in median survival over gemcitabine alone (Moore et al., 2007). FOLFIRINOX, a four-drug combination of folinic acid, 5-fluorouracil, irinotecan and oxaliplatin, is an FDA-approved, first-line treatment option for select patients (ECOG grade 0 1

performance status) with metastatic pancreatic cancer. When compared to gemcitabine, FOLFIRINOX treatment increases the overall survival by over 4 months, but also increases incidence of grades 3 and 4 toxicities (Conroy et al., 2011).

Nanotechnology-Based Drug Delivery Nanomedicine offers a mechanism to manipulate and control the release of systemically administered therapeutic agents on the temporal and spatial scale, which has been notably investigated in cancer indications (Shi, Kantoff, Wooster, & Farokhzad, 2017). As of 2017, two nanomedicines (Abraxane and Onivyde) have been FDA-approved in combination with other cytotoxic agents for use in patients with pancreatic cancer, and a number of nano-enabled therapies are undergoing clinical investigation (Adiseshaiah, Crist, Hook, & McNeil, 2016). Abraxane is an albumin-bound nanoparticle formulation (B130 nm) of paclitaxel (nab-paclitaxel) that was approved by the FDA in 2013 as a first-line treatment option for metastatic pancreatic cancer in combination with gemcitabine. Abraxane with gemcitabine treatment imparts a 2-month improvement in overall survival over gemcitabine alone. Recently, it has been revealed that Abraxane may be taken up by tumor-associated macrophages via macropinocytosis, which induces macrophage immunostimulatory cytokine expression (Cullis et al., 2017). This could potentially indicate a unique role of nab-paclitaxel over solvent-based paclitaxel to target the anergic state of immune cells in pancreatic cancer. A polymeric micellar formulation of paclitaxel (Genexol-PM) is being tested in phase 2 clinical trials in combination with gemcitabine for metastatic and recurrent pancreatic cancer (NCT02739633) (Saif et al., 2010). Two years after Abraxane’s FDA approval, Onivyde, a liposomal formulation of

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irinotecan, was approved as a second-line treatment regimen in combination with 5fluorouracil and folinic acid for patients with metastatic pancreatic cancer. In Phase 3 clinical trials, Onivyde combination therapy demonstrated a 1.9 month increase in overall survival over 5-fluorouracil and folinic acid treatment in patients previously treated with gemcitabine (Wang-Gillam et al., 2016). In addition to the above-mentioned examples of successful nanomedicines, several agents (e.g., TGF-beta type 1 receptor inhibitor, angiotensin II receptor inhibitor (losartan), PEGPH20 (PEGylated recombinant human hyaluronidase enzyme that can enzymatically digest hyaluronan), and Hedgehog inhibitors (saridegib and vismodegib)) have been used to disrupt/reduce the stromal compartment to improve tumor vessel perfusion and enhance drug efficacy in preclinical pancreatic cancer models (Cabral et al., 2011; Diop-Frimpong, Chauhan, Krane, Boucher, & Jain, 2011; Kano et al., 2007; Mpekris et al., 2017). Based on the encouraging preclinical results, several earlystage clinical trials (phase I/II) are ongoing with saridegib/losartan in combination with FOLFIRINOX (NCT01383538 [study completed, pending results]; NCT01821729) (Murphy et al., 2017), as well as Abraxane and gemcitabine treatment with: PEGPH20 (NCT01839487, NCT02921022, NCT02715804, NCT02487277), anti-MMP-9 monoclonal antibody (andecaliximab) (NCT01803282), and Hedgehog inhibitors (NCT01088815, although the clinical trial status is unknown).

PERSONALIZED MEDICINE Substantial tumor heterogeneity among patients and within the primary tumor itself further emphasizes the need to stratify patients based on well-characterized and validated biomarkers (Koay, Amer, Baio, Ondari, & Fleming, 2016). This section will discuss patient

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stratification strategies in clinical development based on the genetic aberrations or pathobiology of the disease, as well as discuss noninvasive imaging modalities used to detect biomarkers. These novel strategies aim to adequately inform clinicians on the most effective treatment regimens for select patient populations; an approach called “personalized medicine.”

Patient Stratification Based on Biomarkers Several genetic factors have been identified that can compromise the therapeutic response to standard-of-care chemotherapy. For example, therapeutic efficacy of gemcitabine can be impacted by decreased expression of equilibrative nucleoside transporter 1 (ENT1) and deoxycytidine kinase (dCK), increased expression of ribonucleotide reductase subunits M1 and M2 (RRM1 and RRM2), and epithelial-tomesenchymal transition (Zheng et al., 2015). Although the expression of ENT1 is required for cellular uptake of gemcitabine, a recent proteomic study of pancreatic cancer tissues from patients treated with gemcitabine did not demonstrate a correlation between ENT1 expression and progression-free survival (Ohmine et al., 2015). The protein expression levels of dCK, a protein required to metabolize gemcitabine to its active form, were shown to have good predictive value for survival of patients treated with gemcitabine (Ohmine et al., 2015). In a retrospective study, patients with pancreatic cancer that expressed wildtype KRAS compared to mutant KRAS experienced a survival advantage (9.7 vs. 5.2 months) with gemcitabine/erlotinib combination (Kim et al., 2011). The above finding emphasizes the need to determine the patient’s KRAS status prior to inclusion of an erlotinib treatment arm, as it is a predictor of therapeutic performance. In addition, skin response to initial anti-EGFR

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therapy may serve as a surrogate biomarker to therapeutic response of erlotinib, since clinical trials have demonstrated an improvement in survival of patients who developed a highgrade rash in response to erlotinib treatment (Petrelli, Borgonovo, Cabiddu, Lonati, & Barni, 2012; Wacker et al., 2007). In 2017, the FDA approved the use of pembrolizumab (Keytruda), an anti-programmed cell death protein (PD1) immunotherapy, for patients with solid tumors, including advanced pancreatic cancer, that have mismatch-repair (MMR) deficiency (FDA approves first cancer treatment for any solid tumor with a specific genetic feature, 2017). Keytruda is the first cancer treatment approved by the FDA that is based on a specific genetic biomarker. Patients with advanced pancreatic cancer that have this genetic biomarker have a better treatment response to pembrolizumab, leading to tumor shrinkage associated with less side effects versus chemotherapy. To determine if a tumor has MMR, patients can be screened for microsatellite instability (MSI), a hallmark of MMR-deficient cancer cells. Identifying specific biomarkers, like MMR deficiency, can help distinguish patients with treatment-responsive or -resistant pancreatic cancer. Additionally, targeting the immunosuppressive tumor microenvironment of pancreatic cancer could potentially overcome disease progression and poor responses to conventional chemotherapy. Ongoing clinical trials of immunotherapies are summarized elsewhere (Johnson, Yarchoan, Lee, Laheru, & Jaffee, 2017). Identification of reliable biomarkers/targets continues to be a challenge. Investigating the pathways involved in pancreatic cancer metastasis is critical to identify patient populations with predictable therapeutic outcomes. In a study sequencing 26 metastases from four patients with pancreatic cancer, researchers found identical mutations in known driver genes, those that promote cancer development, in every metastatic lesion for each patient

(Makohon-Moore et al., 2017). The remarkable uniformity among driver gene mutations in treatment-naı¨ve metastatic pancreatic cancer, as opposed to the passenger mutations that do not affect cancer development, provides an encouraging target for cancer screening and treatment of late-stage disease. A summary of the genes and pathways that have been implicated in pancreatic cancer progression is published in a recent review (Rebelo, Molpeceres, Rijo, & Reis, 2017). The identification and validation of several targets has also been summarized in a recent review (Giovannetti et al., 2017).

Patient Stratification Based on Noninvasive Imaging In addition to protein and genetic markers, the physical properties of the tumor can also affect the vascular, stromal, and even immune and metabolic properties. Therefore, discovery of quantitative physical biomarkers of pancreatic tumors can help in the design of treatment strategies (Koay et al., 2016). For example, pretherapy computed tomography (CT) imaging may be used to detect biomarkers of patient response to gemcitabine treatment, such as quantitative values for vascular density or collagen content (Koay, Baio et al., 2014; Koay, Truty et al., 2014). In a clinical trial of gemcitabine infusion in treatment-naı¨ve patients with pancreatic cancer, drug uptake into tumor cells was correlated with the amount of stroma in the tumor as measured by quantitative volumetric measurements from presurgery CT imaging (Koay et al., 2016; Poplin et al., 2013). Although ENT-1 expression alone was not a good predictor of treatment response (Ohmine et al., 2015), an indicator of tumor stroma status may enhance the predictive power of biomarkers, such as ENT-1, to gemcitabine treatment response in patients (Koay et al., 2016). In addition to CT, positron emission tomography (PET) and magnetic resonance imaging

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(MRI) may also be useful tools to detect functional (changes in drug uptake) and physical (changes in microvasculature) biomarkers of treatment response. Based on studies in an orthotopic pancreatic cancer mouse model, treatment response to a stroma-disrupting agent (losartan; Kim et al., 2014) could be predicted based on PET and MRI imaging analysis (Kumar et al., 2016). PET imaging analysis determined a 50% increase in intratumoral uptake of radiolabeled 5-fluouracil as compared to the control group (Kumar et al., 2016). Similarly, PET tracers of gemcitabine could potentially serve as diagnostic agents for in vivo treatment response to gemcitabine (Russell et al., 2017). Contrast-enhanced MRI with ferumoxytol, an FDA-approved iron oxide nanoparticle, could effectively distinguish changes in the fractional blood volume and vessel size index of pancreatic tumors after losartan treatment, as measured in an orthotopic cancer mouse model. Both measures were two-fold higher in the losartan treatment group over control animals (Kumar et al., 2016). Several other forms of iron oxide nanoparticles, including , 5 nm sized particles and molecularly-targeted particles, are being tested preclinically as MRI probes for pancreatic cancer (Wang et al., 2017; Zhou et al., 2015). Noninvasive imaging methods, like CT, MRI, and PET, are readily scaled from mice to humans and may serve as quick diagnostic tools to determine treatment response and/or inform effective treatment regimens for patients with pancreatic cancer.

EMERGING THERAPIES AND DIAGNOSTICS As the current understanding of pancreatic cancer is becoming more nuanced, there is an overwhelming need for advanced strategies to diagnose, target, and treat pancreatic cancer. Much of these new technologies in

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development build upon on the advances of the biological understanding of pancreatic cancer. In particular, predictive preclinical models of pancreatic cancer that simulate the molecular and pathophysiological features of the disease in the clinic support the discovery of diagnostics and therapeutics. In this section, we discuss the novel technologies being used to address the high unmet need for pancreatic cancer treatment along with the use of advanced preclinical models to study them.

Predictive Preclinical Models of PDAC Carcinogenesis Examining PDAC progression in genetically engineered mouse (GEM) models preprogrammed to develop pancreatic malignancy greatly facilitate: (1) in-depth analysis of molecular mechanisms governing PDAC disease etiology; (2) deciphering cellular and molecular networks wiring complex PDAC tumor architecture; (3) evaluation of the role of tumor stromal and immune constituents in fueling pro-oncogenic machinery; as well as (4) delineation of the hallmarks of early disease onset; and (5) discovery of prognostic and treatment outcome biomarkers. An impressive collection of GEM models based on pancreatic tissuespecific activation of Kras oncogene, alone or in combination with additional genetic perturbations co-detected in clinical PDAC biopsies, has been assembled. These genetic murine models of pancreatic cancer are facilitating translational discovery and preclinical drug development (Guerra & Barbacid, 2013; PerezMancera, Guerra, Barbacid, & Tuveson, 2012). Various combinations of pancreatic tissuespecific Cre driver lines (most frequently used being Pdx1-Cre, Pitf1a/p48-Cre, and ElastasetTA/TetO-Cre alleles) with conditionally activated KrasLSLG12D allele as the primary oncogene and a choice of p53lox/lox, p531/R172H, Ink4a/Arf-/-, Smad4lox/lox, Lkblox/lox, or Brca2Tr/1 as

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secondary contributing molecular aberrations, have been used to assemble models featuring all stages of precancerous pancreatic intraepithelial neoplastic (PanIN) lesions, in addition to advanced invasive PDAC disease. These models closely recapitulate desmoplastic stroma and inflammatory aspects of the disease histologically and molecularly equivalent to those found in clinical PDAC tumors (HerrerosVillanueva, Hijona, Cosme, & Bujanda, 2012). Despite their indisputable value for probing both fundamental and translational facets of pancreatic carcinogenesis, almost all existing PDAC models have an essential drawback: the inability to echo the clinically critical metastatic component of PDAC. A rare exception is the so-called KPC model (assembled via combining Kras1/LSLG12D and p53R172H/1, and Pdx1-Cre alleles) developed by Dr. David Tuveson that features detectable metastatic spread, albeit only in a minor fraction of animals bearing primary pancreatic lesions (Hingorani et al., 2005; Olive & Tuveson, 2006). Together, these GEM models are invaluable experimental tools for interrogation of candidate diagnostic biomarkers and therapeutic options for pancreatic cancer. The above-mentioned GEM models have enabled translation of novel therapeutic agents currently tested in clinical trials (NCT01821729, NCT01839487) (Olive et al., 2009; Provenzano et al., 2012).

Image-Guided Surgery Noninvasive imaging to detect small (submm sized) neoplasms and demarcate the tumor margins can enable surgeons to better resect tumor tissue. This can significantly improve the overall survival of patients afflicted with pancreatic cancer. Additionally, noninvasive imaging can overcome the surgeon’s limitations of mainly relying on visual inspection and palpation. Nanoparticles can act as targeted imaging tools to enhance detection and visualization of

pancreatic tumors during surgery. One such example is the design of highly fluorescent rhodamine-labeled expansile nanoparticles (HFR-eNPs). In animal models, the nanoparticles were able to “light-up” both cm and sub-mm sized pancreatic tumors with high specificity and sensitivity for pancreatic tumors (Colby et al., 2017). However, the disadvantage of visible-light fluorescence is the limited light penetration through tissue, which can prevent complete tumor detection during surgery. Employing near-infrared-tagged nanoprobes can enable imaging deep into the tissue, and the technology is relatively safe to the patient and doctor compared with radiolabeled probes for example (Vahrmeijer, Hutteman, van der Vorst, van de Velde, & Frangioni, 2013). The specificity of the imaging probe is dependent on the level and stage of expression of the molecular target. In a recent study, the integrin αvβ6, carcinoembryonic antigen (CEA), EGFR, and urokinase plasminogen activator receptor (uPAR) were found to be potentially useful targets in pancreatic cancer for image-guided surgery (de Geus et al., 2016).

Therapeutic Gene Silencing Exosomes derived from normal fibroblastlike mesenchymal cells were engineered as delivery agents of RNAi specific to oncogenic KrasG12D, a common mutation in pancreatic cancer. These iExosomes were able to suppress tumor growth and increase overall survival in a number of advanced PDAC mice models over liposomal formulations of the same RNAi (Kamerkar et al., 2017). The ability of exosomes to more effectively deliver RNAi over liposomes is attributed to the CD47 ligand on the exosomal surface, which evades phagocytosis by circulating monocytes and enhances macropinocytosis in Kras-mutant cancer cells. Based on the success of these studies, the investigators are translating the treatment to the clinic through the

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startup company, Codiak Biosciences. A delivery approach for KrasG12D siRNA utilizes a polymeric implant termed LODER (Local Drug EluteR) (Golan et al., 2015). Several early phase clinical trials have been conducted using lipidbased nanoformulations to deliver siRNA (e.g., PKN3 siRNA (NCT01437007), PLK1 siRNA (NCT01808638)) to invoke antitumor responses in patients with pancreatic cancer. The results from these clinical trials have not yet been reported.

Noninvasive Treatment Modalities High-intensity focal ultrasound (HIFU) and stereotactic body radiotherapy (SBRT) are emerging strategies aimed to reduce tumor volume and ease pain associated with pancreatic cancer (Herman et al., 2015; Khokhlova & Hwang, 2016). Based on a clinical study in patients with advanced pancreatic cancer, HIFU tumor ablation combined with chemotherapy could improve quality of life for patients facing limited treatment options (Wu et al., 2005). A summary of clinical trials and their outcomes is reviewed elsewhere (Wu, 2014). Although conventional radiotherapy is generally considered to be an inferior treatment option for pancreatic cancer, SBRT has demonstrated improvement in patient survival outcomes with localized yet unresected tumors over chemotherapy alone (de Geus et al., 2017; Herman et al., 2015; Petrelli et al., 2017). SBRT is an image-guided approach to deliver external beam radiation at high toxic doses directly to the site of tumor, reducing off-target toxicity and frequent dosing associated with standard radiotherapy (Myrehaug et al., 2016). SBRT can also help improve the pain score for patients to bolster quality of life (Herman et al., 2015).

Diagnostics There are no clear clinical symptoms or diagnostics to detect early stages of pancreatic

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cancer. Only 9% of pancreatic cancer patients are diagnosed with localized disease (Siegel et al., 2017), which is the only stage where a potential cure exists after surgical resection. Therefore, there is a dire need for methods that can detect early stages of pancreatic cancer, especially in a rapid and minimally invasive fashion. Protein biomarkers that can be collected from a simple blood draw, including CEA and CA19-9, have been useful to monitor cancer progression in patients. However, the protein biomarkers alone have low sensitivity or specificity for pancreatic cancer and are not reliable for early detection (Lennon & Goggins, 2010). Lipid biopsies are an emerging technology to rapidly probe the molecular markers of metastatic cancers (cell-free tumor DNA, tumor-derived RNA, exosomes, and circulating tumor cells) isolated from a blood draw (Siravegna, Marsoni, Siena, & Bardelli, 2017). Recently, Cohen et al. investigated a combinatorial screening approach to increase the sensitivity of a blood test for patients with early stage pancreatic cancer (Cohen et al., 2017). The screen with the greatest specificity and sensitivity (67% and 99%, respectively) assayed for a combination of genetic and elevated protein biomarkers, namely KRAS circulating tumor DNA, CA19-9, CEA, hepatocyte growth factor (HGF), and osteopontin (OPN). It is possible that this combinatorial assay, which can be collected by a blood draw, may be easily applied to patient populations at high risk for pancreatic cancer (Cohen et al., 2017). In another study, researchers identified that the cell surface proteoglycan, glypican-1 (GPC1) is a specific marker found on cancer cell exosomes, as opposed to healthy cell-derived exosomes (Melo et al., 2015). GPC1 exosomes were detected in serum of patients with pancreatic cancer with high specificity and sensitivity when compared with healthy patients and those with benign disease. In addition, the quantity of GPC1 exosomes correlated to tumor burden and survival in patients

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(Melo et al., 2015). Based on these promising results, GPC1 positive exosomes have the potential to serve as a noninvasive diagnostic tool to detect pancreatic cancer at much earlier stages than currently available. Investigators are translating this diagnostic system through the company, Codiak.

SUMMARY There is an urgent need for better therapeutic and diagnostic tools to overcome the dismal survival rate for pancreatic cancer. When pancreatic cancer is diagnosed at a localized and early stage, the 5-year survival rate is over nine times longer than when diagnosed at an advanced stage (Siegel et al., 2017). Therefore, early diagnosis is crucial. The emerging technologies introduced in this chapter aim to answer this urgent call by providing novel approaches to detect, diagnose, and treat pancreatic cancer. Nanotechnology, in particular, enables improved delivery strategies that can augment drug accumulation (or a synergistic combination of drugs) to cancer cells or enhance detection of early stage tumors via actively targeted imaging probes. Other therapeutic approaches target the hallmarks of pancreatic cancer by attempting to overcome the drug delivery challenges posed by the underlying genetic aberrations and pathology of this intractable disease (Fig. 22.1). Personalized medicine enabled by these emerging technologies is especially important for disease management. It can provide clinicians with a tool to identify efficient treatment regimens for specific patient populations, as is already done in the clinic for pembrolizumab treatment. Identifying patients with significant risk factors for pancreatic cancer, like family history, can not only improve early detection rates but also provide researchers with valuable information for the development of new diagnostics and therapeutics (Roberts & Klein, 2017).

Continued advances in the understanding of the disease can inform the discovery of more efficient diagnostics and therapeutics for patients afflicted with this lethal disease.

Acknowledgment The authors thank Dr. Rachael M. Crist of Leidos Biomedical Research for her critical review of the manuscript and Mr. Allen Kane and Mr. Joseph Meyer of Leidos Biomedical Research for assistance with the graphic illustration. This work has been funded, in whole or in part, with Federal funds from the National Cancer Institute, National Institutes of Health, under Contract No. HHSN261200800001E. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the US Government. The work was supported in part by the Intramural Research Program of the NIH, National Cancer Institute, Center for Cancer Research.

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FURTHER READING

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Further Reading http://www.nature.com/nature/journal/vaop/ncurrent/ abs/nature22341.html http://www.nature.com/ng/journal/v49/n3/abs/ ng.3764.html http://www.nature.com/nrclinonc/journal/v14/n9/abs/ nrclinonc.2017.14.html

III. GASTROINTESTINAL TUMORS: MOLECULAR DIAGNOSIS AND TREATMENT