Multiplex Patient-Based Drug Response Assay in Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDA) is an extremely lethal malignancy arising from the pancreas. The treatment of PDA is complicated by ineffective treatments and a lack of biomarkers predictive of treatment success. We have designed a patient-derived organoid (PDO) based high-throughput drug screening assay to model treatment response to a variety of conventional and investigational treatments for PDA. Consecutive patients undergoing endoscopic ultrasound-guided fine-needle biopsy for tissue diagnosis of PDA at Rush University Medical Center were offered to participate in the study. Biopsies were immediately processed to develop organoids. Fifteen PDOs were screened for sensitivity to 18 compounds, including conventional PDA chemotherapies and FDA-approved investigational targeted therapies in cancer using Cell-titer GLO 3D (Promega) cell viability assay. The area under the curve (AUC) was calculated and normalized to the maximum area under the curve to generate a normalized AUC between 0 and 1. Molecular profiling of PDOs was conducted using RNA-seq. Human PDA transcriptomic was extracted from The Cancer Genome Atlas (TCGA). The drug response curves were reproducible. We observed variation in response to conventional therapies overall as well as among individual patients. There were distinct transcriptome signatures associated with response to the conventional chemotherapeutics in PDA. The transcriptomic profile of overall resistance to conventional therapies in our study was associated with poor survival in PDA patients in TCGA. Our pathway analysis for targeted drugs revealed a number of predictors of response associated with the mechanism of action of the tested drug. The multiplex organoid-based drug assay could be used in preclinical to inform patient stratification and therapeutic selection in PDA. When combined with omics data, ex vivo response to treatment could help identify gene signatures associated with response to novel therapies.

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Application of the High-Throughput TAB-Array for the Discovery of Novel 5-Hydroxymethylcytosine Biomarkers in Pancreatic Ductal Adenocarcinoma

Epigenomes ◽

10.3390/epigenomes3030016 ◽

2019 ◽

Vol 3 (3) ◽

pp. 16 ◽

Cited By ~ 1

Author(s):

Chang Zeng ◽

Zhou Zhang ◽

Jun Wang ◽

Brian C-H Chiu ◽

Lifang Hou ◽

...

Keyword(s):

Pancreatic Ductal Adenocarcinoma ◽

Biomarker Discovery ◽

Medical Center ◽

Distribution Patterns ◽

Regulatory Elements ◽

The Cancer Genome Atlas ◽

Ductal Adenocarcinoma ◽

Marker Genes ◽

Liquid Biopsies ◽

Tissue Samples

The clinical outcomes of pancreatic ductal adenocarcinoma (PDAC) remain dismal, with an estimated five-year survival rate of less than 5%. Early detection and prognostic approaches, including robust biomarkers for PDAC, are critical for improving patient survival. Our goal was to explore the biomarker potential of 5-hydroxymethylcytosines (5hmC), an emerging epigenetic marker with a distinct role in cancer pathobiology, yet under-investigated, due largely to technical constraints relating to PDAC. The TET-assisted bisulfite (TAB)-Array assay represents state-of-the-art technology and was used to directly profile 5hmC at single-base resolution with the Illumina EPIC array (~850,000 cytosine modification sites) in 17 pairs of tumor/adjacent tissue samples from US patients collected at the University of Chicago Medical Center. The TAB-Array data were analyzed to explore the genomic distribution of 5hmC and evaluate whether 5hmC markers were differentially modified between tumors and adjacent tissues. We demonstrated distinctive distribution patterns of 5hmC in tissue samples from PDAC patients relative to cis-regulatory elements (e.g., histone modification marks for enhancers), indicating their potential gene regulatory relevance. Substantial differences in 5hmC-modified CpG sites were detected between tumors and adjacent tissues in genes related to cancer pathobiology. The detected 5hmC-contaning marker genes also showed prognostic value for overall survival in the US patients with PDAC from the Cancer Genome Atlas Project. This study demonstrated the technical feasibility of the TAB-Array approach in cancer biomarker discovery and the biomarker potential of 5hmC for PDAC. Future studies using tissues and/or liquid biopsies may include 5hmC as a potential epigenetic biomarker target for PDAC.

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Pancreatic Ductal Adenocarcinoma: Relating Biomechanics and Prognosis

Journal of Clinical Medicine ◽

10.3390/jcm10122711 ◽

2021 ◽

Vol 10 (12) ◽

pp. 2711

Author(s):

Benjamin M. MacCurtain ◽

Ned P. Quirke ◽

Stephen D. Thorpe ◽

Tom K. Gallagher

Keyword(s):

Pancreatic Ductal Adenocarcinoma ◽

Cancer Progression ◽

Ex Vivo ◽

Neoadjuvant Treatment ◽

Response To Treatment ◽

Ductal Adenocarcinoma ◽

Borderline Resectable ◽

Dismal Prognosis ◽

Clinical Consequences

Pancreatic ductal adenocarcinoma (PDAC) is the most common form of pancreatic cancer and carries a dismal prognosis. Resectable patients are treated predominantly with surgery while borderline resectable patients may receive neoadjuvant treatment (NAT) to downstage their disease prior to possible resection. PDAC tissue is stiffer than healthy pancreas, and tissue stiffness is associated with cancer progression. Another feature of PDAC is increased tissue heterogeneity. We postulate that tumour stiffness and heterogeneity may be used alongside currently employed diagnostics to better predict prognosis and response to treatment. In this review we summarise the biomechanical changes observed in PDAC, explore the factors behind these changes and describe the clinical consequences. We identify methods available for assessing PDAC biomechanics ex vivo and in vivo, outlining the relative merits of each. Finally, we discuss the potential use of radiological imaging for prognostic use.

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Circulating microRNAs as dynamic biomarkers of response to treatment with FOLFIRINOX in advanced pancreatic ductal adenocarcinoma

HPB ◽

10.1016/j.hpb.2019.10.1506 ◽

2019 ◽

Vol 21 ◽

pp. S760

Author(s):

L. Meijer ◽

I. Garajová ◽

C. Caparello ◽

T. Le Large ◽

N. Funel ◽

...

Keyword(s):

Pancreatic Ductal Adenocarcinoma ◽

Response To Treatment ◽

Ductal Adenocarcinoma ◽

Circulating Micrornas

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Carcinoembryonic antigen cell adhesion molecule 6 (CEACAM6) in Pancreatic Ductal Adenocarcinoma (PDA): An integrative analysis of a novel therapeutic target

Scientific Reports ◽

10.1038/s41598-019-54545-9 ◽

2019 ◽

Vol 9 (1) ◽

Cited By ~ 2

Author(s):

Ritu Pandey ◽

Muhan Zhou ◽

Shariful Islam ◽

Baowei Chen ◽

Natalie K Barker ◽

...

Keyword(s):

Cell Adhesion ◽

Pancreatic Ductal Adenocarcinoma ◽

Therapeutic Target ◽

Cell Activity ◽

Gene Expression Omnibus ◽

The Cancer Genome Atlas ◽

Ductal Adenocarcinoma ◽

Wild Type ◽

Cancer Genome Atlas ◽

Novel Therapeutic

AbstractWe investigated biomarker CEACAM6, a highly abundant cell surface adhesion receptor that modulates the extracellular matrix (ECM) in pancreatic ductal adenocarcinoma (PDA). The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) RNA-Seq data from PDA patients were analyzed for CEACAM6 expression and evaluated for overall survival, association, enrichment and correlations. A CRISPR/Cas9 Knockout (KO) of CEACAM6 in PDA cell line for quantitative proteomics, mitochondrial bioenergetics and tumor growth in mice were conducted. We found CEACAM6 is over-expressed in primary and metastatic basal and classical PDA subtypes. Highest levels are in classical activated stroma subtype. CEACAM6 over-expression is universally a poor prognostic marker in KRAS mutant and wild type PDA. High CEACAM6 expression is associated with low cytolytic T-cell activity in both basal and classical PDA subtypes and correlates with low levels of T-REG markers. In HPAF-II cells knockout of CEACAM6 alters ECM-cell adhesion, catabolism, immune environment, transmembrane transport and autophagy. CEACAM6 loss increases mitochondrial basal and maximal respiratory capacity. HPAF-II CEACAM6−/− cells are growth suppressed by >65% vs. wild type in mice bearing tumors. CEACAM6, a key regulator affects several hallmarks of PDA including the fibrotic reaction, immune regulation, energy metabolism and is a novel therapeutic target in PDA.

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Prognostic Nomogram for Patients With Pancreatic Ductal Adenocarcinoma of Pancreatic Head After Pancreaticoduodenectomy

Clinical Medicine Insights Oncology ◽

10.1177/11795549211024149 ◽

2021 ◽

Vol 15 ◽

pp. 117955492110241

Author(s):

Hongkai Zhuang ◽

Zixuan Zhou ◽

Zuyi Ma ◽

Shanzhou Huang ◽

Yuanfeng Gong ◽

...

Keyword(s):

Regression Analysis ◽

Pancreatic Ductal Adenocarcinoma ◽

Perineural Invasion ◽

Cox Regression ◽

Area Under The Curve ◽

Pancreatic Head ◽

Ductal Adenocarcinoma ◽

R0 Resection ◽

Cox Regression Analysis ◽

Ajcc Stage

Background: The prognosis of patients with pancreatic ductal adenocarcinoma (PDAC) of pancreatic head remains poor, even after potentially curative R0 resection. The aim of this study was to develop an accurate model to predict patients’ prognosis for PDAC of pancreatic head following pancreaticoduodenectomy. Methods: We retrospectively reviewed 112 patients with PDAC of pancreatic head after pancreaticoduodenectomy in Guangdong Provincial People’s Hospital between 2014 and 2018. Results: Five prognostic factors were identified using univariate Cox regression analysis, including age, histologic grade, American Joint Committee on Cancer (AJCC) Stage 8th, total bilirubin (TBIL), CA19-9. Using all subset analysis and multivariate Cox regression analysis, we developed a nomogram consisted of age, AJCC Stage 8th, perineural invasion, TBIL, and CA19-9, which had higher C-indexes for OS (0.73) and RFS (0.69) compared with AJCC Stage 8th alone (OS: 0.66; RFS: 0.67). The area under the curve (AUC) values of the receiver operating characteristic (ROC) curve for the nomogram for OS and RFS were significantly higher than other single parameter, which are AJCC Stage 8th, age, perineural invasion, TBIL, and CA19-9. Importantly, our nomogram displayed higher C-index for OS than previous reported models, indicating a better predictive value of our model. Conclusions: A simple and practical nomogram for patient prognosis in PDAC of pancreatic head following pancreaticoduodenectomy was established, which shows satisfactory predictive efficacy and deserves further evaluation in the future.

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Pancreatic Ductal Adenocarcinoma: Preclinical in vitro and ex vivo Models

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.741162 ◽

2021 ◽

Vol 9 ◽

Author(s):

Beate Gündel ◽

Xinyuan Liu ◽

Matthias Löhr ◽

Rainer Heuchel

Keyword(s):

Pancreatic Ductal Adenocarcinoma ◽

Ex Vivo ◽

Treatment Options ◽

3D Cell Culture ◽

Therapy Resistance ◽

Ductal Adenocarcinoma ◽

The Past ◽

Slow Progress

Pancreatic ductal adenocarcinoma (PDAC) is one of the most overlooked cancers despite its dismal median survival time of 6 months. The biggest challenges in improving patient survival are late diagnosis due to lack of diagnostic markers, and limited treatment options due to almost complete therapy resistance. The past decades of research identified the dense stroma and the complex interplay/crosstalk between the cancer- and the different stromal cells as the main culprits for the slow progress in improving patient outcome. For better ex vivo simulation of this complex tumor microenvironment the models used in PDAC research likewise need to become more diverse. Depending on the focus of the investigation, several in vitro and in vivo models for PDAC have been established in the past years. Particularly, 3D cell culture such as spheroids and organoids have become more frequently used. This review aims to examine current PDAC in vitro models, their inherent limitations, and their successful implementations in research.

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Comprehensive characterisation of pancreatic ductal adenocarcinoma with microsatellite instability: histology, molecular pathology and clinical implications

Gut ◽

10.1136/gutjnl-2020-320726 ◽

2020 ◽

Vol 70 (1) ◽

pp. 148-156 ◽

Cited By ~ 7

Author(s):

Claudio Luchini ◽

Lodewijk A A Brosens ◽

Laura D Wood ◽

Deyali Chatterjee ◽

Jae Il Shin ◽

...

Keyword(s):

Systematic Review ◽

Microsatellite Instability ◽

Pancreatic Ductal Adenocarcinoma ◽

Molecular Data ◽

The Cancer Genome Atlas ◽

Research Network ◽

Ductal Adenocarcinoma ◽

Precision Oncology ◽

Dna Mismatch ◽

Molecular Features

ObjectiveRecently, tumours with microsatellite instability (MSI)/defective DNA mismatch repair (dMMR) have gained considerable interest due to the success of immunotherapy in this molecular setting. Here, we aim to clarify clinical-pathological and/or molecular features of this tumour subgroup through a systematic review coupled with a comparative analysis with existing databases, also providing indications for a correct approach to the clinical identification of MSI/dMMR pancreatic ductal adenocarcinoma (PDAC).DesignPubMed, SCOPUS and Embase were searched for studies reporting data on MSI/dMMR in PDAC up to 30 November 2019. Histological and molecular data of MSI/dMMR PDAC were compared with non-MSI/dMMR PDAC and with PDAC reference cohorts (including SEER database and The Cancer Genome Atlas Research Network - TCGA project).ResultsOverall, 34 studies with 8323 patients with PDAC were included in the systematic review. MSI/dMMR demonstrated a very low prevalence in PDAC (around 1%–2%). Compared with conventional PDAC, MSI/dMMR PDAC resulted strongly associated with medullary and mucinous/colloid histology (p<0.01) and with a KRAS/TP53 wild-type molecular background (p<0.01), with more common JAK genes mutations. Data on survival are still unclear.ConclusionPDAC showing typical medullary or mucinous/colloid histology should be routinely examined for MSI/dMMR status using specific tests (immunohistochemistry, followed by MSI-PCR in cases with doubtful results). Next-generation sequencing (NGS) should be adopted either where there is limited tissue or as part of NGS tumour profiling in the context of precision oncology, acknowledging that conventional histology of PDAC may rarely harbour MSI/dMMR.

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Circulating microRNAs as dynamic biomarkers of response to treatment with FOLFIRINOX in advanced pancreatic ductal adenocarcinoma

HPB ◽

10.1016/j.hpb.2019.10.1404 ◽

2019 ◽

Vol 21 ◽

pp. S1019-S1020

Author(s):

L. Meijer ◽

I. Garajová ◽

C. Caparello ◽

T. Le Large ◽

N. Funel ◽

...

Keyword(s):

Pancreatic Ductal Adenocarcinoma ◽

Response To Treatment ◽

Ductal Adenocarcinoma ◽

Circulating Micrornas

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

Cancers ◽

10.3390/cancers12102750 ◽

2020 ◽

Vol 12 (10) ◽

pp. 2750

Author(s):

Pierre-Olivier Frappart ◽

Thomas G. Hofmann

Keyword(s):

Personalized Medicine ◽

Pancreatic Ductal Adenocarcinoma ◽

Drug Response ◽

Treatment Options ◽

Response Prediction ◽

Ductal Adenocarcinoma ◽

Chemotherapy Treatment ◽

The Past ◽

Therapeutic Tools ◽

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.

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A generalizable data-driven multicellular model of pancreatic ductal adenocarcinoma

GigaScience ◽

10.1093/gigascience/giaa075 ◽

2020 ◽

Vol 9 (7) ◽

Cited By ~ 2

Author(s):

Boris Aguilar ◽

David L Gibbs ◽

David J Reiss ◽

Mark McConnell ◽

Samuel A Danziger ◽

...

Keyword(s):

Tumor Microenvironment ◽

Pancreatic Ductal Adenocarcinoma ◽

Molecular Interactions ◽

Positive Impact ◽

Stellate Cells ◽

The Cancer Genome Atlas ◽

Data Driven ◽

Ductal Adenocarcinoma ◽

Modeling Framework ◽

Pertinent Data

Abstract Background Mechanistic models, when combined with pertinent data, can improve our knowledge regarding important molecular and cellular mechanisms found in cancer. These models make the prediction of tissue-level response to drug treatment possible, which can lead to new therapies and improved patient outcomes. Here we present a data-driven multiscale modeling framework to study molecular interactions between cancer, stromal, and immune cells found in the tumor microenvironment. We also develop methods to use molecular data available in The Cancer Genome Atlas to generate sample-specific models of cancer. Results By combining published models of different cells relevant to pancreatic ductal adenocarcinoma (PDAC), we built an agent-based model of the multicellular pancreatic tumor microenvironment, formally describing cell type–specific molecular interactions and cytokine-mediated cell-cell communications. We used an ensemble-based modeling approach to systematically explore how variations in the tumor microenvironment affect the viability of cancer cells. The results suggest that the autocrine loop involving EGF signaling is a key interaction modulator between pancreatic cancer and stellate cells. EGF is also found to be associated with previously described subtypes of PDAC. Moreover, the model allows a systematic exploration of the effect of possible therapeutic perturbations; our simulations suggest that reducing bFGF secretion by stellate cells will have, on average, a positive impact on cancer apoptosis. Conclusions The developed framework allows model-driven hypotheses to be generated regarding therapeutically relevant PDAC states with potential molecular and cellular drivers indicating specific intervention strategies.

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