A Comparative Quantitative LC-MS/MS Profiling Analysis of Human Pancreatic Adenocarcinoma, Adjacent-Normal Tissue, and Patient-Derived Tumour Xenografts

Mass spectrometry–based proteomics technology in pancreatic cancer research

Pancreatic ductal adenocarcinoma (PDAC) has become a significant health concern with increasing incidence and mortality rates over the past few decades. Researchers have turned their attention to cutting-edge mass spectrometry (MS) technology due to its high-throughput and accurate detection capacity, which plays a vital role in understanding the mechanisms and discovering biomarkers for pancreatic diseases. In this review, we comprehensively investigate various methodologies of quantitative and qualitative proteomics MS technologies, alongside bioinformatical platforms employed in pancreatic cancer research. The integration of these optimized approaches provides novel insights into the molecular mechanisms underlying tumorigenesis and disease progression, ultimately facilitating the discovery of potential diagnostic, prognostic biomarkers, and therapeutic targets. The robust MS-based strategy shows promise in paving the way for early diagnosis and personalized medicine for pancreatic cancer patients.

Direct identification of T cell epitopes in cancer tissues

Prediction of tumor-specific T cell epitopes is an important part of cancer immunotherapies. In the past, tumor-specific T cell epitopes were identified by mapping the epitopes on the known cancer-testis antigens and tumor-associated antigens or antigens that react to the T cells induced by the cancer vaccine therapy. More recently, in silico prediction of mutation-associated neoepitopes from the whole-exome sequencing (WES) results has become another approach. However, although this approach often identifies many predicted peptides, only few have been shown to be immunogenic. Mass spectrometry (MS) has also been used to directly identify the T cell epitopes presented on tumor cell by eluting the peptides from human leukocyte antigens (HLA) class I and class II molecules. This approach of identifying neoepitopes was demonstrated to be feasible in high tumor mutation burden (TMB) tumors such as melanoma. However, identifying low-TMB-tumor-specific T cell epitopes has been challenging. Recently, Fujiwara et al. reported their successful result in identifying T cell epitopes in a low TMB tumor, namely pancreatic ductal adenocarcinoma (PDAC). Using the MS approach, they identified T cell epitopes shared by multiple pancreatic cancer patients with different HLA types. Moreover, they demonstrated that the identified epitopes bound non-matched HLA molecules and induced T cell response in peripheral T cells from non-HLA-type matched patients. Their study has opened a new venue for identifying T cell epitopes in a non-immunogenic tumor such as PDAC for the design and development of vaccine and T cell therapy.

Long-circulating magnetoliposomes as surrogates for assessing pancreatic tumour permeability and nanoparticle deposition

Nanocarriers are candidates for cancer chemotherapy delivery, with growing numbers of clinically-approved nano-liposomal formulations such as Doxil® and Onivyde® (liposomal doxorubicin and irinotecan) providing proof-of-concept. However, their complex biodistribution and the varying susceptibility of individual patient tumours to nanoparticle deposition remains a clinical challenge. Here we describe the preparation, characterisation, and biological evaluation of phospholipidic structures containing solid magnetic cores (SMLs) as an MRI-trackable surrogate that could aid in the clinical development and deployment of nano-liposomal formulations. Through the sequential assembly of size-defined iron oxide nanoparticle clusters with a stabilizing anionic phospholipid inner monolayer and an outer monolayer of independently-selectable composition, SMLs can mimic physiologically a wide range of nano-liposomal carrier compositions. In patient-derived xenograft models of pancreatic adenocarcinoma, similar tumour deposition of SML and their nano-liposomal counterparts of identical bilayer composition was observed in vivo, both at the tissue level (fluorescence intensities of 1.5 × 108 ± 1.8 × 107 and 1.2 × 108 ± 6.3 × 107, respectively; ns, 99% confidence interval) and non-invasively using MR imaging. We observed superior capabilities of SML as a surrogate for nano-liposomal formulations as compared to other clinically-approved iron oxide nano-formulations (ferumoxytol). In combination with diagnostic and therapeutic imaging tools, SMLs have high clinical translational potential to predict nano-liposomal drug carrier deposition and could assist in stratifying patients into treatment regimens that promote optimal tumour deposition of nanoparticulate chemotherapy carriers. STATEMENT OF SIGNIFICANCE: Solid magnetoliposomes (SMLs) with compositions resembling that of FDA-approved agents such as Doxil® and Onivyde® offer potential application as non-invasive MRI stratification agents to assess extent of tumour deposition of nano-liposomal therapeutics prior to administration. In animals with pancreatic adenocarcinoma (PDAC), SML-PEG exhibited (i) tumour deposition comparable to liposomes of the same composition; (ii) extended circulation times, with continued tumour deposition up to 24 hours post-injection; and (iii) MRI capabilities to determine tumour deposition up to 1 week post-injection, and confirmation of patient-to-patient variation in nanoparticulate deposition in tumours. Hence SMLs with controlled formulation are a step towards non-invasive MRI stratification approaches for patients, enabled by evaluation of the extent of deposition in tumours prior to administration of nano-liposomal therapeutics.

Alteration in Levels of Specific miRNAs and Their Potential Protein Targets between Human Pancreatic Cancer Samples, Adjacent Normal Tissue, and Xenografts Derived from These Tumors

Herein, we describe the global comparison of miRNAs in human pancreatic cancer tumors, adjacent normal tissue, and matched patient-derived xenograft models using microarray screening. RNA was extracted from seven tumor, five adjacent normal, and eight FI PDX tumor samples and analyzed by Affymetrix GeneChip miRNA 4.0 array. A transcriptome analysis console (TAC) was used to generate comparative lists of up- and downregulated miRNAs for the comparisons, tumor vs. normal and F1 PDX vs. tumor. Particular attention was paid to miRNAs that were changed in the same direction in both comparisons. We identified the involvement in pancreatic tumor tissue of several miRNAs, including miR4534, miR3154, and miR4742, not previously highlighted as being involved in this type of cancer. Investigation in the parallel mRNA and protein lists from the same samples allowed the elimination of proteins where altered expression correlated with corresponding mRNA levels and was thus less likely to be miRNA regulated. Using the remaining differential expression protein lists for proteins predicted to be targeted for differentially expressed miRNA on our list, we were able to tentatively ascribe specific protein changes to individual miRNA. Particularly interesting target proteins for miRs 615-3p, 2467-3p, 4742-5p, 509-5p, and 605-3p were identified. Prominent among the protein targets are enzymes involved in aldehyde metabolism and membrane transport and trafficking. These results may help to uncover vulnerabilities that could enable novel approaches to treating pancreatic cancer.

Clinical Proteomics: Liquid Chromatography-Mass Spectrometry (LC-MS) Purification Systems

Liquid chromatography/mass spectrometry (LC/MS) has become a routine powerful technology in clinical proteomic studies for protein identification, protein characterization, and the discovery of biomarkers. In this chapter, we describe two protocol methods to analyze clinical patient samples using a resin-based depletion column followed by either protein In-Gel enzymatic digestion or protein In-Solution enzymatic digestion using a simple kit-based approach (i.e., using the PreOmics iST sample preparation kit), followed by analysis using one-dimensional reverse-phase chromatography (RPC) or high pH reversed-phase peptide fractionation.

Neoadjuvant chemotherapy is associated with an altered metabolic profile and increased cancer stemness in patients with pancreatic ductal adenocarcinoma

The modest clinical benefits of neoadjuvant chemotherapy (NAT) in pancreatic ductal adenocarcinoma (PDAC) are associated with a lack of robust data on treatment-induced changes in the tumor. To this end, comparative proteomic profiling of tumor tissue samples from treatment-naïve (TN, n = 20) and NAT-treated (n = 22) PDACs was performed. Differentially expressed proteins were identified and correlation with overall survival (OS) was performed. Tumors were also examined for histopathological changes and expression of cancer stem cell (CSC) markers. Serum from 33 matched patients was analyzed for metabolic markers. Cytotoxicity, proliferation, and expression of CSC markers were assessed in chemoresistant Panc-1 and Mia PaCa-2 cells. Of the 2265 proteins identified, 227 and 144 proteins showed significantly altered expression and differential phosphorylation, respectively, in NAT compared with TN samples. The majority of these were metabolism-related proteins, and 14 of these correlated moderately with OS. NAT-treated tumors and chemoresistant cancer cells showed increased expression of CSC markers. Serum ALDH1A1 was higher in NAT compared with TN. Differentially phosphorylated proteins were mainly involved in cytoskeleton organization, cell locomotion, motility, and migration, and 17 of these showed a strong positive correlation with OS. This study provides evidence of the effects of NAT on PDAC metabolism at both the tumor and the systemic levels. NAT-treated tumors showed significantly lower expression of metabolic proteins, and patients who underwent NAT showed reduced serum lactate and high-density lipoprotein-cholesterol. Lastly, cancer cells that survived cytotoxic treatment expressed higher CSC markers, both in vivo and in vitro.

Identification of potential plasma protein biomarkers for feline pancreatic carcinoma by liquid chromatography tandem mass spectrometry

In both humans and cats, pancreatic carcinoma is an aggressive cancer with a grave prognosis. Proteomics techniques have successfully identified several blood-based biomarkers of human pancreatic neoplasia. Thus, this study aims to investigate whether similar biomarkers can be identified in the plasma of cats with FePAC by using liquid chromatography tandem mass spectrometry (LC-MS/MS). To facilitate evaluation of the low abundance plasma proteome, a human-based immunodepletion device (MARS-2) was first validated for use with feline plasma. Marked reduction and/or complete removal of albumin and immunoglobulins was confirmed by analysis of electrophoretograms and mass spectral data. Subsequently, plasma collected from 9 cats with pancreatic carcinoma (FePAC), 10 cats with symptomatic pancreatitis, and 10 healthy control cats was immunodepleted and subjected to LC-MS/MS. Thirty-seven plasma proteins were found to be differentially expressed (p < .05 in one-way ANOVA, FC >2 in fold change analysis). Among these proteins, ETS variant transcription factor 4 (p < .05) was overexpressed, while gelsolin (p < .01), tryptophan 2,3-dioxygenase (p < .05), serpin family F member 1 (p < .01), apolipoprotein A-IV (p < .01) and phosphatidylinositol-glycan-specific phospholipase D (p < .05) were down-regulated in cats with FePAC. Further studies on these potential biomarkers are needed to investigate their diagnostic value.

Extracellular vesicles from pancreatic ductal adenocarcinoma endoscopic ultrasound-fine needle aspiration samples contain a protein barcode

BACKGROUND

The survival rate of pancreatic ductal adenocarcinoma (PDAC) is very poor because early detection is difficult. Extracellular vesicles (EVs) are released from cells associating with the cellular condition and circulated in the blood. We aimed to identify EV proteins from endoscopic ultrasound-fine needle aspiration (EUS-FNA) biopsy samples in order to develop novel biomarkers for PDAC.

METHODS

Extracellular vesicles were isolated from EUS-FNA samples of 40 PDAC patients and six autoimmune pancreatitis (AIP) patients to be used as a control. EV proteins were identified using nanoLC-MS/MS.

RESULTS

Intact EVs approximately 200 nm in diameter were detected from EUS-FNA samples. We identified 2059 or 1032 EV proteins in PDAC or AIP, respectively, and 1071 EV proteins were detected only in PDAC. One hundred and fifty-three EV proteins were significantly different between PDAC and AIP: 64 proteins were down-regulated in PDAC whereas 89 EV proteins were up-regulated in PDAC including mucins, keratins, Ras-related proteins, and olfactomedin-4, which proteins have been reported to be elevated in PDAC tissue/blood, or cultured pancreatic cancer cell lines. Notably, in the 89 up-regulated PDAC EV proteins we identified novel proteins including ADP-ribosylation factor 3, CD55, pyruvate kinase, and lipopolysaccharide-induced tumor necrosis factor. Out of 89 proteins, a total of 13 proteins including Ras-related proteins were significantly elevated in PDAC stages II-IV compared to PDAC stage I, including Ras-related proteins, moesin, and CD55.

CONCLUSIONS

The EV proteins obtained from EUS-FNA samples contain a PDAC-specific protein barcode. The EV proteins identified from EUS-FNA samples include promising biomarkers for the diagnosis and clinical staging of PDAC.

Copper toxicity of inflection point in human intestinal cell line Caco-2 dissected: influence of temporal expression patterns

We previously described a non-monotonic dose response curve at low copper concentrations where 3.125 μM CuSO₄ (the early inflection point) was more toxic than 25 μM CuSO₄ in Caco-2 cells. We employed global proteomics to investigate this observation. The altered expression levels of a small number of proteins displaying a temporal response may provide the best indication of the underlying mechanism; more well-known copper response proteins including the metal binding metallothioneins (MT1X, MT1F, MT2A) and antioxidant response proteins including Heme oxygenase were upregulated to a similar level in both copper concentrations and so are less likely to underpin this phenomenon.The temporal response proteins include Granulins, AN1-type zinc finger protein 2A (ZFAND2A), and the heat shock proteins (HSPA6 and HSPA1B). Granulins were decreased after 4 h only in 25 μM CuSO₄ but from 24 h, were decreased in both copper concentrations to a similar level. Induction of ZFAND2A and increases in HSPA6 and HSPA1B were observed at 24 h only in 25 μM CuSO₄ but were present at 48 h in both copper conditions. The early expression of ZFAND2A, HSPs, and higher levels of α-crystallin B (CRYAB) correlated with lower levels of misfolded proteins in 25 μM CuSO₄ compared to 3.125 μM CuSO₄ at 48 h. These results suggest that 3.125 μM CuSO₄ at early time points was unable to activate the plethora of stress responses invoked by the higher copper concentration, paradoxically exposing the Caco-2 cells to higher levels of misfolded proteins and greater proteotoxic stress.

Preclinical models of pancreatic ductal adenocarcinoma: challenges and opportunities in the era of precision medicine

Pancreatic ductal adenocarcinoma (PDAC) is an extremely lethal malignancy, with an average 5-year survival rate of 9% (Siegel RL, Miller KD, Jemal A. Ca Cancer J Clin. 2019;69(1):7-34). The steady increase in mortality rate indicates limited efficacy of the conventional regimen. The heterogeneity of PDAC calls for personalized treatment in clinical practice, which requires the construction of a preclinical system for generating patient-derived models. Currently, the lack of high-quality preclinical models results in ineffective translation of novel targeted therapeutics. This review summarizes applications of commonly used models, discusses major difficulties in PDAC model construction and provides recommendations for integrating workflows for precision medicine.

Metabolomic Detection Between Pancreatic Cancer and Liver Metastasis Nude Mouse Models Constructed by Using the PANC1-KAI1/CD82 Cell Line

Background: Pancreatic cancer (PC) has a poor prognosis and is prone to liver metastasis. The KAI1/CD₈₂ gene inhibits PC metastasis. This study aimed to explore differential metabolites and enrich the pathways in serum samples between PC and liver metastasis nude mouse models stably expressing KAI1/CD₈₂. Methods: KAI1/CD₈₂-PLV-EF1α-MCS-IRES-Puro vector and PANC1 cell line stably expressing KAI1/CD₈₂ were constructed for the first time. This cell line was used to construct 3 PC nude mouse models and 3 liver metastasis nude mouse models. The different metabolites and Kyoto encyclopedia of genes and genomes (KEGG) and human metabolome database (HMDB) enrichment pathways were analyzed using the serum samples of the 2 groups of nude mouse models on the basis of untargeted ultra-performance liquid chromatography-tandem mass spectrometry platform. Results: KAI1/CD₈₂-PLV-EF1α-MCS-IRES-Puro vector and PANC1 cell line stably expressing KAI1/CD₈₂ were constructed successfully, and all nude mouse models survived and developed cancers. Among the 1233 metabolites detected, 18 metabolites (9 upregulated and 9 downregulated) showed differences. In agreement with the literature data, the most significant differences between both groups were found in the levels of bile acids (taurocholic acid, chenodeoxycholic acid), glycine, prostaglandin E2, vitamin D, guanosine monophosphate, and inosine. Bile recreation, primary bile acid biosynthesis, and purine metabolism KEGG pathways and a series of HMDB pathways (P < .05) contained differential metabolites that may be associated with liver metastasis from PC. However, the importance of these metabolites on PC liver metastases remains to be elucidated. Conclusions: Our findings suggested that the metabolomic approach may be a useful method to detect potential biomarkers in PC.

Pancreatic Ductal Adenocarcinoma (PDAC) Organoids: The Shining Light at the End of the Tunnel for Drug Response Prediction and Personalized Medicine

Pancreatic ductal adenocarcinoma (PDAC) represents 90% of pancreatic malignancies. In contrast to many other tumor entities, the prognosis of PDAC has not significantly improved during the past thirty years. Patients are often diagnosed too late, leading to an overall five-year survival rate below 10%. More dramatically, PDAC cases are on the rise and it is expected to become the second leading cause of death by cancer in western countries by 2030. Currently, the use of gemcitabine/nab-paclitaxel or FOLFIRINOX remains the standard chemotherapy treatment but still with limited efficiency. There is an urgent need for the development of early diagnostic and therapeutic tools. To this point, in the past 5 years, organoid technology has emerged as a revolution in the field of PDAC personalized medicine. Here, we are reviewing and discussing the current technical and scientific knowledge on PDAC organoids, their future perspectives, and how they can represent a game change in the fight against PDAC by improving both diagnosis and treatment options.

Proteomic Analysis of Cell Lines and Primary Tumors in Pancreatic Cancer Identifies Proteins Expressed Only In Vitro and Only In Vivo

OBJECTIVES

A limited repertoire of good pancreatic ductal adenocarcinoma (PDAC) models is one of the main barriers in developing effective new PDAC treatments. We aimed to characterize 6 commonly used PDAC cell lines and compare them with PDAC patient tumor samples using proteomics.

METHODS

Proteomic methods were used to generate an extensive catalog of proteins from 10 PDAC surgical specimens, 9 biopsies of adjacent normal tissue, and 6 PDAC cell lines. Protein lists were interrogated to determine what extent the proteome of the cell lines reflects the proteome of primary pancreatic tumors.

RESULTS

We identified 7973 proteins from the cell lines, 5680 proteins from the tumor tissues, and 4943 proteins from the adjacent normal tissues. We identified 324 proteins unique to the cell lines, some of which may play a role in survival of cells in culture. Conversely, a list of 63 proteins expressed only in the patient samples, whose expression is lost in culture, may place limitations on the degree to which these model systems reflect tumor biology in vivo.

CONCLUSIONS

Our work offers a catalog of proteins detected in each of the PDAC cell lines, providing a useful guide for researchers seeking model systems for PDAC functional studies.

Proteomic analysis of pancreatic ductal adenocarcinoma

INTRODUCTION

Pancreatic ductal adenocarcinoma (PDAC), which represents approximately 80% of all pancreatic cancers, is a highly aggressive malignant disease and one of the most lethal among all cancers. Overall, the 5-year survival rate among all pancreatic cancer patients is less than 9%; these rates have shown little change over the past 30 years. A more comprehensive understanding of the molecular mechanisms underlying this complex disease is crucial to the development of new diagnostic tools for early detection and disease monitoring, as well as to identify new and more effective therapeutics to improve patient outcomes.

AREA COVERED

We summarize recent advances in proteomic strategies and mass spectrometry to identify new biomarkers for early detection and monitoring of disease progression, predict response to therapy, and to identify novel proteins that have the potential to be 'druggable' therapeutic targets. An overview of proteomic studies that have been conducted to further our mechanistic understanding of metastasis and chemotherapy resistance in PDAC disease progression will also be discussed.

EXPERT COMMENTARY

The results from these PDAC proteomic studies on a variety of PDAC sample types (e.g., blood, tissue, cell lines, exosomes, etc.) provide great promise of having a significant clinical impact and improving patient outcomes.

LC-MS proteomic profiling of Caco-2 human intestinal cells exposed to the copper-chelating agent, triethylenetetramine: A preliminary study

Homeostasis of metal micronutrients such as copper is tightly regulated to ensure deficiency does not occur while restricting damage resulting from excess accumulation. Using LC-MS the effect on the proteome of intestinal Caco-2 cells of exposure to the chelator triethylenetetramine (TETA) was investigated. Continuous exposure of TETA at 25 μM to Caco-2 cells caused decreased cell yields and morphological changes. These effects were reversed when cells were no longer exposed to TETA. Quantitative proteomic analysis identified 957 mostly low-fold differentially expressed proteins, 41 of these returned towards control Caco-2 expression following recovery. Proteins exhibiting this "reciprocal" behaviour included upregulated deoxyhypusine hydroxylase (DOHH, 15.69- fold), a protein essential for eIF-5A factor hypsuination, a post translational modification responsible for eIF-5A maturation, which in turn is responsible for translation elongation. Exposure to TETA also resulted in 87 proteins, the expression of which was stable and remained differentially expressed following recovery. This study helps to elucidate the stable and transient proteomic effects of TETA exposure in intestinal cells.

ZIP4 Increases Expression of Transcription Factor ZEB1 to Promote Integrin α3β1 Signaling and Inhibit Expression of the Gemcitabine Transporter ENT1 in Pancreatic Cancer Cells

BACKGROUND & AIMS

Pancreatic tumors undergo rapid growth and progression, become resistant to chemotherapy, and recur after surgery. We studied the functions of the solute carrier family 39 member 4 (SLC39A4, also called ZIP4), which regulates concentrations of intracellular zinc and is increased in pancreatic cancer cells, in cell lines and mice.

METHODS

We obtained 93 pancreatic cancer specimens (tumor and adjacent nontumor tissues) from patients who underwent surgery and gemcitabine chemotherapy and analyzed them by immunohistochemistry. ZIP4 and/or ITGA3 or ITGB1 were overexpressed or knocked down with short hairpin RNAs in AsPC-1 and MIA PaCa-2 pancreatic cancer cells lines, and in pancreatic cells from KPC and KPC-ZEB1-knockout mice, and pancreatic spheroids were established; cells and spheroids were analyzed by immunoblots, reverse transcription polymerase chain reaction, and liquid chromatography tandem mass spectrometry. We studied transcriptional regulation of ZEB1, ITGA3, ITGB1, JNK, and ENT1 by ZIP4 using chromatin precipitation and luciferase reporter assays. Nude mice were given injections of genetically manipulated AsPC-1 and MIA PaCa-2 cells, and growth of xenograft tumors and metastases was measured.

RESULTS

In pancreatic cancer specimens from patients, increased levels of ZIP4 were associated with shorter survival times. MIA PaCa-2 cells that overexpressed ZIP4 had increased resistance to gemcitabine, 5-fluorouracil, and cisplatin, whereas AsPC-1 cells with ZIP4 knockdown had increased sensitivity to these drugs. In mice, xenograft tumors grown from AsPC-1 cells with ZIP4 knockdown were smaller and more sensitive to gemcitabine. ZIP4 overexpression significantly reduced accumulation of gemcitabine in pancreatic cancer cells, increased growth of xenograft tumors in mice, and increased expression of the integrin subunits ITGA3 and ITGB1; expression levels of ITGA3 and ITGB1 were reduced in cells with ZIP4 knockdown. Pancreatic cancer cells with ITGA3 or ITGB1 knockdown had reduced proliferation and formed smaller tumors in mice, despite overexpression of ZIP4; spheroids established from these cells had increased sensitivity to gemcitabine. We found ZIP4 to activate STAT3 to induce expression of ZEB1, which induced expression of ITGA3 and ITGB1 in KPC cells. Increased ITGA3 and ITGB1 expression and subsequent integrin α3β1 signaling, via c-Jun-N-terminal kinase (JNK), inhibited expression of the gemcitabine transporter ENT1, which reduced gemcitabine uptake by pancreatic cancer cells. ZEB1-knockdown cells had increased sensitivity to gemcitabine.

CONCLUSIONS

In studies of pancreatic cancer cell lines and mice, we found that ZIP4 increases expression of the transcription factor ZEB1, which activates expression of ITGA3 and ITGB1. The subsequent increase in integrin α3β1 signaling, via JNK, inhibits expression of the gemcitabine transporter ENT1, so that cells take up smaller amounts of the drug. Activation of this pathway might help mediate resistance of pancreatic tumors to chemotherapeutic agents.

Establishment and Characterisation by Expression Microarray of Patient-Derived Xenograft Panel of Human Pancreatic Adenocarcinoma Patients

Pancreatic cancer remains among the most lethal cancers worldwide, with poor early detection rates and poor survival rates. Patient-derived xenograft (PDX) models have increasingly been used in preclinical and clinical research of solid cancers to fulfil unmet need. Fresh tumour samples from human pancreatic adenocarcinoma patients were implanted in severe combined immunodeficiency (SCID) mice. Samples from 78% of treatment-naïve pancreatic ductal adenocarcinoma patients grew as PDX tumours and were confirmed by histopathology. Frozen samples from F1 PDX tumours could be later successfully passaged in SCID mice to F2 PDX tumours. The human origin of the PDX was confirmed using human-specific antibodies; however, the stromal component was replaced by murine cells. Cell lines were successfully developed from three PDX tumours. RNA was extracted from eight PDX tumours and where possible, corresponding primary tumour (T) and adjacent normal tissues (N). mRNA profiles of tumour vs. F1 PDX and normal vs. tumour were compared by Affymetrix microarray analysis. Differential gene expression showed over 5000 genes changed across the N vs. T and T vs. PDX samples. Gene ontology analysis of a subset of genes demonstrated genes upregulated in normal vs. tumour vs. PDX were linked with cell cycle, cycles cell process and mitotic cell cycle. Amongst the mRNA candidates elevated in the PDX and tumour vs. normal were SERPINB5, FERMT1, AGR2, SLC6A14 and TOP2A. These genes have been associated with growth, proliferation, invasion and metastasis in pancreatic cancer previously. Cumulatively, this demonstrates the applicability of PDX models and transcriptomic array to identify genes associated with growth and proliferation of pancreatic cancer.

Characterisation and proteomic profiling of continuously exposed Cu-resistant variants of the Caco-2 cell line

Studies in hepatic systems identify multiple factors involved in the generation of copper resistance. As the intestine is the route of exposure to dietary copper, we wanted to understand how intestinal cells overcome the toxic effects of high copper and what mechanisms of resistance develop. Using the intestinal cell line Caco-2, resistance was developed by serial subculture in 50 μM copper in inorganic (CuSO₄) or organic (Cu proteinate) forms. Caco-2 variants exhibited resistance to copper and retained the non-monotonic dose response while displaying stable phenotypes following repeated subculture in the absence of copper. Phenotypic changes on exposure to copper in parental Caco-2 cells included significantly increased total protein yield, ROS, SOD, metallothionein expression, GSH and total glutathione. These phenotypic changes were not replicated in resistant variants on a per cell basis. Quantitative label-free LC-MS/MS proteomic analysis identified 1113 differentially expressed proteins (DEPs) between parental Caco-2 and resistant cells. With some exceptions, most of the DEPs were overexpressed to a low level around 2-fold suggesting resistance was supported by multiple small changes in protein expression. These variants may be a useful tool in studying the toxicity of stress responses in further Cu-related studies.

The fidelity of cancer cells in PDX models: Characteristics, mechanism and clinical significance

Patient-derived xenograft (PDX) models are widely used as preclinical cancer models and are considered better than cell culture models in recapitulating the histological features, molecular characteristics and intratumoral heterogeneity (ITH) of human tumors. While the PDX model is commonly accepted for use in drug discovery and other translational studies, a growing body of evidence has suggested its limitations. Recently, the fidelity of cancer cells within a PDX has been questioned, which may impede the future application of these models. In this review, we will focus the variable phenotypes of xenograft tumors and the genomic instability and molecular inconsistency of PDX tumors after serial transplantation. Next, we will discuss the underlying mechanism of ITH and its clinical relevance. Stochastic selection bias in the sampling process and/or deterministic clonal dynamics due to murine selective pressure may have detrimental effects on the results of personalized medicine and drug screening studies. In addition, we aim to identify a possible solution for the issue of fidelity in current PDX models and to discuss emerging next-generation preclinical models.

Omics Approaches in Pancreatic Adenocarcinoma

Pancreatic ductal adenocarcinoma, which represents 80% of pancreatic cancers, is mainly diagnosed when treatment with curative intent is not possible. Consequently, the overall five-year survival rate is extremely dismal—around 5% to 7%. In addition, pancreatic cancer is expected to become the second leading cause of cancer-related death by 2030. Therefore, advances in screening, prevention and treatment are urgently needed. Fortunately, a wide range of approaches could help shed light in this area. Beyond the use of cytological or histological samples focusing in diagnosis, a plethora of new approaches are currently being used for a deeper characterization of pancreatic ductal adenocarcinoma, including genetic, epigenetic, and/or proteo-transcriptomic techniques. Accordingly, the development of new analytical technologies using body fluids (blood, bile, urine, etc.) to analyze tumor derived molecules has become a priority in pancreatic ductal adenocarcinoma due to the hard accessibility to tumor samples. These types of technologies will lead us to improve the outcome of pancreatic ductal adenocarcinoma patients.

Quantitative proteomics identifies brain acid soluble protein 1 (BASP1) as a prognostic biomarker candidate in pancreatic cancer tissue

BACKGROUND

Pancreatic cancer is a heterogenous disease with a poor prognosis. This study aimed to discover and validate prognostic tissue biomarkers in pancreatic cancer using a mass spectrometry (MS) based proteomics approach.

METHODS

Global protein sequencing of fresh frozen pancreatic cancer and healthy pancreas tissue samples was conducted by MS to discover potential protein biomarkers. Selected candidate proteins were further verified by targeted proteomics using parallel reaction monitoring (PRM). The expression of biomarker candidates was validated by immunohistochemistry in a large tissue microarray (TMA) cohort of 141 patients with resectable pancreatic cancer. Kaplan-Meier and Cox proportional hazard modelling was used to investigate the prognostic utility of candidate protein markers.

FINDINGS

In the initial MS-discovery phase, 165 proteins were identified as potential biomarkers. In the subsequent MS-verification phase, a panel of 45 candidate proteins was verified by the development of a PRM assay. Brain acid soluble protein 1 (BASP1) was identified as a new biomarker candidate for pancreatic cancer possessing largely unknown biological and clinical functions and was selected for further analysis. Importantly, bioinformatic analysis indicated that BASP1 interacts with Wilms tumour protein (WT1) in pancreatic cancer. TMA-based immunohistochemistry analysis showed that BASP1 was an independent predictor of prolonged survival (HR 0.468, 95% CI 0.257-0.852, p = .013) and predicted favourable response to adjuvant chemotherapy, whereas WT1 indicated a worsened survival (HR 1.636, 95% CI 1.083-2.473, p = .019) and resistance to chemotherapy. Interaction analysis showed that patients with negative BASP1 and high WT1 expression had the poorest outcome (HR 3.536, 95% CI 1.336-9.362, p = .011).

INTERPRETATION

We here describe an MS-based proteomics platform for developing biomarkers for pancreatic cancer. Bioinformatic analysis and clinical data from our study suggest that BASP1 and its putative interaction partner WT1 can be used as biomarkers for predicting outcomes in pancreatic cancer patients.