Understanding the Genetics of Pancreatic Adenocarcinoma

10.2310/cgso.16077 ◽

2017 ◽

Author(s):

Apoorve Nayyar ◽

Jen Jen Yeh

Keyword(s):

Pancreatic Ductal Adenocarcinoma ◽

High Throughput Sequencing ◽

Cellular Proliferation ◽

Molecular Subtypes ◽

Expression Patterns ◽

Ductal Adenocarcinoma ◽

Early Event ◽

Familial Pancreatic Cancer ◽

Structural Variations ◽

Cancer Heterogeneity

The underlying molecular basis of pancreatic ductal adenocarcinoma (PDAC) is complex, with multiple genetic, epigenetic, and transcriptomic changes. Five to 10% of PDAC cases have a hereditary basis, with multiple risk-conferring genetic mutations running in the family. All PDAC tumors develop from noninvasive precursor lesions that reflect the temporal accumulation of mutations. Recent advances in high-throughput sequencing technologies have facilitated a better understanding of the diverse mutational landscape of PDAC, reaffirming the role of genes previously known to be mutated (K-ras, CDKN2A, TP53, SMAD4, SLIT/ROBO, SWI/SNF) and revealing novel insights into the differential gene expression patterns and structural variations involved. K-ras mutation, an early event in disease pathogenesis, plays a pivotal role in the initiation, progression, and maintenance of PDAC, with the mutation type impacting disease pathophysiology and prognosis. The subsequent loss of tumor suppressors (CDKN2A, TP53, SMAD4) promotes genetic instability and uncontrolled cellular proliferation. Molecular subtypes with potential prognostic and therapeutic relevance have been identified. The challenge now is to translate this wealth of knowledge to the clinic. This review contains 3 figures, 3 tables and 50 references Key words: familial pancreatic cancer, heterogeneity, molecular subtypes, pancreatic ductal adenocarcinoma, whole genome/exome sequencing

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Betulinic Acid Affects the Energy-Related Proteomic Profiling in Pancreatic Ductal Adenocarcinoma Cells

Molecules ◽

10.3390/molecules26092482 ◽

2021 ◽

Vol 26 (9) ◽

pp. 2482

Author(s):

Ching-Feng Chiu ◽

Hsin-Yi Chang ◽

Chun-Yine Huang ◽

Chen-Zou Mau ◽

Tzu-Ting Kuo ◽

...

Keyword(s):

Pancreatic Ductal Adenocarcinoma ◽

Betulinic Acid ◽

Expression Patterns ◽

Apolipoprotein A1 ◽

Ductal Adenocarcinoma ◽

Therapeutic Window ◽

Pdac Cell ◽

Cell Growth And Migration ◽

Altered Expression ◽

Clinical Prognosis

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive disease with a 5-year survival rate of <8%. Therefore, finding new treatment strategies against PDAC cells is an imperative issue. Betulinic acid (BA), a plant-derived natural compound, has shown great potential to combat cancer owing to its versatile physiological functions. In this study, we observed the impacts of BA on the cell viability and migratory ability of PDAC cell lines, and screened differentially expressed proteins (DEPs) by an LC-MS/MS-based proteomics analysis. Our results showed that BA significantly inhibited the viability and migratory ability of PDAC cells under a relatively low dosage without affecting normal pancreatic cells. Moreover, a functional analysis revealed that BA-induced downregulation of protein clusters that participate in mitochondrial complex 1 activity and oxidative phosphorylation, which was related to decreased expressions of RNA polymerase mitochondrial (POLRMT) and translational activator of cytochrome c oxidase (TACO1), suggesting that the influence on mitochondrial function explains the effect of BA on PDAC cell growth and migration. In addition, BA also dramatically increased Apolipoprotein A1 (APOA1) expression and decreased NLR family CARD domain-containing protein 4 (NLRC4) expression, which may be involved in the dampening of PDAC migration. Notably, altered expression patterns of APOA1 and NLRC4 indicated a favorable clinical prognosis of PDAC. Based on these findings, we identified potential proteins and pathways regulated by BA from a proteomics perspective, which provides a therapeutic window for PDAC.

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The Proteomic Landscape of Pancreatic Ductal Adenocarcinoma Liver Metastases Identifies Molecular Subtypes and Associations with Clinical Response—Response

Clinical Cancer Research ◽

10.1158/1078-0432.ccr-21-1220 ◽

2021 ◽

Vol 27 (14) ◽

pp. 4127-4127

Author(s):

Henry C.-H. Law ◽

Emalie J. Clement ◽

Paul M. Grandgenett ◽

Michael A. Hollingsworth ◽

Nicholas T. Woods

Keyword(s):

Liver Metastases ◽

Pancreatic Ductal Adenocarcinoma ◽

Clinical Response ◽

Molecular Subtypes ◽

Ductal Adenocarcinoma

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Upregulated MicroRNA-483-3p is an Early Event in Pancreatic Ductal Adenocarcinoma (PDAC) and as a Powerful Liquid Biopsy Biomarker in PDAC

OncoTargets and Therapy ◽

10.2147/ott.s288936 ◽

2021 ◽

Vol Volume 14 ◽

pp. 2163-2175

Author(s):

Huilin Shao ◽

Yue Zhang ◽

Jie Yan ◽

Xinchao Ban ◽

Xiaojie Fan ◽

...

Keyword(s):

Pancreatic Ductal Adenocarcinoma ◽

Liquid Biopsy ◽

Ductal Adenocarcinoma ◽

Early Event

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Pancreatic Ductal Adenocarcinoma: Molecular Expression Patterns after Neoadjuvant FOLFIRINOX Treatment.

European Journal of Surgical Oncology ◽

10.1016/j.ejso.2019.11.316 ◽

2020 ◽

Vol 46 (2) ◽

pp. e123

Author(s):

Floris Vuijk ◽

Lizzie de Muynck ◽

Lotte Franken ◽

Olivier Busch ◽

Hanneke Wilmink ◽

...

Keyword(s):

Pancreatic Ductal Adenocarcinoma ◽

Expression Patterns ◽

Ductal Adenocarcinoma ◽

Molecular Expression

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Aberrant (pro)renin receptor expression induces genomic instability in pancreatic ductal adenocarcinoma through upregulation of SMARCA5/SNF2H

Communications Biology ◽

10.1038/s42003-020-01434-x ◽

2020 ◽

Vol 3 (1) ◽

Author(s):

Yuki Shibayama ◽

Kazuo Takahashi ◽

Hisateru Yamaguchi ◽

Jun Yasuda ◽

Daisuke Yamazaki ◽

...

Keyword(s):

Pancreatic Ductal Adenocarcinoma ◽

Genomic Instability ◽

Chromosomal Abnormalities ◽

Point Mutations ◽

Nuclear Bodies ◽

Receptor Expression ◽

Ductal Adenocarcinoma ◽

Structural Variations ◽

Aberrant Expression ◽

Genome Level

Abstract(Pro)renin receptor [(P)RR] has a role in various diseases, such as cardiovascular and renal disorders and cancer. Aberrant (P)RR expression is prevalent in pancreatic ductal adenocarcinoma (PDAC) which is the most common pancreatic cancer. Here we show whether aberrant expression of (P)RR directly leads to genomic instability in human pancreatic ductal epithelial (HPDE) cells. (P)RR-expressing HPDE cells show obvious cellular atypia. Whole genome sequencing reveals that aberrant (P)RR expression induces large numbers of point mutations and structural variations at the genome level. A (P)RR-expressing cell population exhibits tumour-forming ability, showing both atypical nuclei characterised by distinctive nuclear bodies and chromosomal abnormalities. (P)RR overexpression upregulates SWItch/Sucrose Non-Fermentable (SWI/SNF)-related, matrix-associated, actin-dependent regulator of chromatin, subfamily a, member 5 (SMARCA5) through a direct molecular interaction, which results in the failure of several genomic stability pathways. These data reveal that aberrant (P)RR expression contributes to the early carcinogenesis of PDAC.

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Morphological classification of pancreatic ductal adenocarcinoma that predicts molecular subtypes and correlates with clinical outcome

Gut ◽

10.1136/gutjnl-2019-318217 ◽

2019 ◽

Vol 69 (2) ◽

pp. 317-328 ◽

Cited By ~ 9

Author(s):

Sangeetha N Kalimuthu ◽

Gavin W Wilson ◽

Robert C Grant ◽

Matthew Seto ◽

Grainne O’Kane ◽

...

Keyword(s):

Pancreatic Ductal Adenocarcinoma ◽

Molecular Subtypes ◽

Differentially Expressed Gene ◽

Biological Significance ◽

Treatment Strategies ◽

Ductal Adenocarcinoma ◽

Rna Seq ◽

Gene Signatures ◽

Significant Difference ◽

Morphological Patterns

IntroductionTranscriptional analyses have identified several distinct molecular subtypes in pancreatic ductal adenocarcinoma (PDAC) that have prognostic and potential therapeutic significance. However, to date, an indepth, clinicomorphological correlation of these molecular subtypes has not been performed. We sought to identify specific morphological patterns to compare with known molecular subtypes, interrogate their biological significance, and furthermore reappraise the current grading system in PDAC.DesignWe first assessed 86 primary, chemotherapy-naive PDAC resection specimens with matched RNA-Seq data for specific, reproducible morphological patterns. Differential expression was applied to the gene expression data using the morphological features. We next compared the differentially expressed gene signatures with previously published molecular subtypes. Overall survival (OS) was correlated with the morphological and molecular subtypes.ResultsWe identified four morphological patterns that segregated into two components (‘gland forming’ and ‘non-gland forming’) based on the presence/absence of well-formed glands. A morphological cut-off (≥40% ‘non-gland forming’) was established using RNA-Seq data, which identified two groups (A and B) with gene signatures that correlated with known molecular subtypes. There was a significant difference in OS between the groups. The morphological groups remained significantly prognostic within cancers that were moderately differentiated and classified as ‘classical’ using RNA-Seq.ConclusionOur study has demonstrated that PDACs can be morphologically classified into distinct and biologically relevant categories which predict known molecular subtypes. These results provide the basis for an improved taxonomy of PDAC, which may lend itself to future treatment strategies and the development of deep learning models.

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MicroRNA-21 Is Induced Early in Pancreatic Ductal Adenocarcinoma Precursor Lesions

Clinical Chemistry ◽

10.1373/clinchem.2009.137364 ◽

2010 ◽

Vol 56 (4) ◽

pp. 603-612 ◽

Cited By ~ 142

Author(s):

Maël Chalret du Rieu ◽

Jérôme Torrisani ◽

Janick Selves ◽

Talal Al Saati ◽

Anny Souque ◽

...

Keyword(s):

Early Detection ◽

Mouse Model ◽

Pancreatic Ductal Adenocarcinoma ◽

Early Stage ◽

Survival Rates ◽

Ductal Adenocarcinoma ◽

Early Event ◽

Precursor Lesions ◽

Tissue Samples ◽

Ductal Cells

Abstract Background: Pancreatic ductal adenocarcinoma (PDAC) has the poorest overall prognosis among gastrointestinal cancers; however, curative resection in early-stage PDAC greatly improves survival rates, indicating the importance of early detection. Because abnormal microRNA production is commonly detected in cancer, we investigated noninvasive precursor pancreatic intraepithelial neoplasia (PanIN) lesions for microRNA production as a potential early biomarker of PDAC. Methods: Pathologists identified and classified ductal lesions. We extracted total RNA from laser-capture microdissected PanIN tissue samples from a conditional KRAS(G12D) mouse model (n = 29) or of human origin (n = 38) (KRAS is v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog). MicroRNA production was quantified by quantitative real-time PCR. Internal controls included 5S and U6 RNAs. Results: Production of microRNAs miR-21, miR-205, and miR-200 paralleled PanIN progression in the KRAS(G12D) mouse model, compared with microRNA production in samples of nonpathologic ducts. miR-21 demonstrated the highest relative concentrations in the precursor lesions. Interestingly, miR-205 and miR-21 up-regulation preceded phenotypic changes in the ducts. The production of microRNAs miR-21, miR-221, miR-222, and let-7a increased with human PanIN grade, with peak production occurring in hyperplastic PanIN-2/3 lesions. In situ hybridization analysis indicated miR-21 production to be concentrated in pathologic ductal cells. miR-21 production was regulated by KRAS(G12D) and epidermal growth factor receptor in PDAC-derived cell lines. Conclusions: Aberrant microRNA production is an early event in the development of PanIN. Our findings indicate that miR-21 warrants further investigation as a marker for early detection of PDAC.

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A machine learning algorithm predicts molecular subtypes in pancreatic ductal adenocarcinoma with differential response to gemcitabine-based versus FOLFIRINOX chemotherapy

10.1101/664540 ◽

2019 ◽

Cited By ~ 1

Author(s):

Georgios Kaissis ◽

Sebastian Ziegelmayer ◽

Fabian Lohöfer ◽

Katja Steiger ◽

Hana Algül ◽

...

Keyword(s):

Machine Learning ◽

Overall Survival ◽

Pancreatic Ductal Adenocarcinoma ◽

Median Overall Survival ◽

Molecular Subtypes ◽

Supervised Machine Learning ◽

Ductal Adenocarcinoma ◽

Chemotherapy Response ◽

Response To Chemotherapy ◽

Sensitivity Specificity

AbstractPurposeDevelopment of a supervised machine-learning model capable of predicting clinically relevant molecular subtypes of pancreatic ductal adenocarcinoma (PDAC) from diffusion-weighted-imaging-derived radiomic features.MethodsThe retrospective observational study assessed 55 surgical PDAC patients. Molecular subtypes were defined by immunohistochemical staining of KRT81. Tumors were manually segmented and 1606 radiomic features were extracted withPyRadiomics. A gradient-boosted-tree algorithm (XGBoost) was trained on 70% of the patients (N=28) and tested on 30% (N=17) to predict KRT81+ vs. KRT81-tumor subtypes. The average sensitivity, specificity and ROC-AUC value were calculated. Chemotherapy response was assessed stratified by subtype. Radiomic feature importance was ranked.ResultsThe mean±STDEV sensitivity, specificity and ROC-AUC were 0.90±0.07, 0.92±0.11, and 0.93±0.07, respectively. Patients with a KRT81+ subtype experienced significantly diminished median overall survival compared to KRT81-patients (7.0 vs. 22.6 months, HR 1.44, log-rank-test P=<0.001) and a significantly improved response to gemcitabine-based chemotherapy over FOLFIRINOX (10.14 vs. 3.8 months median overall survival, HR 0.85, P=0.037) compared to KRT81-patients, who responded significantly better to FOLFIRINOX over gemcitabine-based treatment (30.8 vs. 13.4 months median overall survival, HR 0.88, P=0.027).ConclusionsThe machine-learning based analysis of radiomic features enables the prediction of subtypes of PDAC, which are highly relevant for overall patient survival and response to chemotherapy.

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