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

Abstract Background Estimates of the incidence and prognosis of developing liver metastases at the pancreatic ductal adenocarcinoma (PDAC) diagnosis are lacking.Methods In this study, we analyzed the association of liver metastases and the PDAC patients outcome. The risk factors associated with liver metastases in PDAC patients were analyzed using multivariable logistic regression analysis. The overall survival (OS) was estimated using Kaplan-Meier curves and log-rank test. Cox regression was performed to identify factors associated with OS.Results Patients with primary PDAC in the tail of the pancreas had a higher incidence of liver metastases (62.2%) than those with PDAC in the head (28.6%). Female gender, younger age, primary PDAC in the body or tail of the pancreas, and larger primary PDAC tumor size were positively associated with the occurrence of liver metastases. The median survival of patients with liver metastases was significantly shorter than that of patients without liver metastases. Older age, unmarried status, primary PDAC in the tail of the pancreas, and tumor size ≥4 cm were risk factors for OS in the liver metastases cohort.Conclusions Population-based estimates of the incidence and prognosis of PDAC with liver metastases may help decide whether diffusion-weighted magnetic resonance imaging should be performed in patients with primary PDAC in the tail or body of the pancreas. The location of primary PDAC should be considered during the diagnosis and treatment of primary PDAC.

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Complete Response of Synchronous Liver Metastasis in a Pancreatic Ductal Adenocarcinoma, When Surgery Could Represent a Therapeutic Option

Canadian Journal of Gastroenterology and Hepatology ◽

10.1155/2020/8679751 ◽

2020 ◽

Vol 2020 ◽

pp. 1-7 ◽

Cited By ~ 1

Author(s):

Antonella Argentiero ◽

Angela Calabrese ◽

Angela Monica Sciacovelli ◽

Sabina Delcuratolo ◽

Antonio Giovanni Solimando ◽

...

Keyword(s):

Liver Metastases ◽

Pancreatic Ductal Adenocarcinoma ◽

Lung Metastases ◽

Therapeutic Option ◽

Disease Free Survival ◽

Complete Response ◽

Ductal Adenocarcinoma ◽

Pancreatic Lesion ◽

Link Type ◽

Multiple Liver Metastases

Metastatic pancreatic ductal adenocarcinoma (PDAC) is characterized by poor prognosis and short survival. Today, the use of new polytherapeutic regimens increases clinical outcome of these patients opening new clinical scenario. A crucial issue related to the actual improvement achieved with these new regimens is represented by the occasional possibility to observe a radiological complete response of metastatic lesions in patients with synchronous primary tumor. What could be the best therapeutic management of these patients? Could surgery represent an indication? Herein, we reported a case of a patient with PDAC of the head with multiple liver metastases, who underwent first-line chemotherapy with mFOLFIRINOX. After 10 cycles, he achieved a complete radiological response of liver metastases and a partial response of pancreatic lesion. A duodenocephalopancreasectomy was performed. Due to liver a lung metastases after 8 months from surgery, a second-line therapy was started with a disease-free survival and overall survival of 8 months and 45 months, respectively. Improvement in the molecular characterization of PDAC could help in the selection of patients suitable for multimodal treatments. This trial is registered with NCT02892305 and NCT00855634.

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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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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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