Transcriptomic Analysis of Laser Capture Microdissected Tumors Reveals Cancer- and Stromal-Specific Molecular Subtypes of Pancreatic Ductal Adenocarcinoma

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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Application of laser capture microdissection combined with two-dimensional electrophoresis for the discovery of differentially regulated proteins in pancreatic ductal adenocarcinoma

PROTEOMICS ◽

10.1002/pmic.200300466 ◽

2003 ◽

Vol 3 (10) ◽

pp. 1988-2001 ◽

Cited By ~ 123

Author(s):

Ali R. Shekouh ◽

Christopher C. Thompson ◽

Wendy Prime ◽

Fiona Campbell ◽

Jane Hamlett ◽

...

Keyword(s):

Pancreatic Ductal Adenocarcinoma ◽

Laser Capture Microdissection ◽

Ductal Adenocarcinoma ◽

Two Dimensional ◽

Two Dimensional Electrophoresis ◽

Laser Capture ◽

Dimensional Electrophoresis

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

Clinical Cancer Research ◽

10.1158/1078-0432.ccr-19-1496 ◽

2019 ◽

Vol 26 (5) ◽

pp. 1065-1076 ◽

Cited By ~ 7

Author(s):

Henry C.-H. Law ◽

Dragana Lagundžin ◽

Emalie J. Clement ◽

Fangfang Qiao ◽

Zachary S. Wagner ◽

...

Keyword(s):

Liver Metastases ◽

Pancreatic Ductal Adenocarcinoma ◽

Clinical Response ◽

Molecular Subtypes ◽

Ductal Adenocarcinoma

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164 – Establishment of a Nomogram Comprising of Immune and Stromal Gene Signature for Predicting Survival and Identification of Poor Molecular Subtypes in Pancreatic Ductal Adenocarcinoma

Gastroenterology ◽

10.1016/s0016-5085(19)36877-5 ◽

2019 ◽

Vol 156 (6) ◽

pp. S-39

Author(s):

Raju Kandimalla ◽

Hideo Tomihara ◽

Jasjit K. Banwait ◽

Mitsuru Kanda ◽

Yasuhiro Kodera ◽

...

Keyword(s):

Pancreatic Ductal Adenocarcinoma ◽

Molecular Subtypes ◽

Gene Signature ◽

Ductal Adenocarcinoma

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Abstract 762: A non-invasive miRNA signature for the identification of pancreatic ductal adenocarcinoma (PDAC) patients with poor molecular subtypes and worse prognosis

10.1158/1538-7445.am2019-762 ◽

2019 ◽

Author(s):

Raju Kandimalla ◽

Tadanobu Shimura ◽

Saurav Mallik ◽

Susan Tsai ◽

Douglas B. Evans ◽

...

Keyword(s):

Pancreatic Ductal Adenocarcinoma ◽

Molecular Subtypes ◽

Ductal Adenocarcinoma ◽

Mirna Signature ◽

Non Invasive ◽

Worse Prognosis

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Relevance of Immune Infiltration and Clinical Outcomes in Pancreatic Ductal Adenocarcinoma Subtypes

Frontiers in Oncology ◽

10.3389/fonc.2020.575264 ◽

2021 ◽

Vol 10 ◽

Author(s):

Rong Liu ◽

Ya-Zhou Liao ◽

Wei Zhang ◽

Hong-Hao Zhou

Keyword(s):

Pancreatic Ductal Adenocarcinoma ◽

Clinical Outcomes ◽

Immune Cells ◽

Molecular Subtypes ◽

Molecular Subtype ◽

Critical Role ◽

Cell Subset ◽

Ductal Adenocarcinoma ◽

Support Vector ◽

Consensus Clustering

PurposePancreatic ductal adenocarcinoma (PDAC) is a lethal cancer with high heterogeneity and dismal survival rates. Tumor immune microenvironment plays a critical role in sensitive to chemotherapy and prognosis. Herein, we determined the relevance of the composition of tumor-infiltrating immune cells to clinical outcomes in PDACs, and we evaluated these effects by molecular subtype.Experimental DesignData of 1,274 samples from publically available datasets were collected. Molecular subtypes were predicted with support vector machine. Twenty-two subsets of immune cells were estimated with CIBERSORTx. The associations between each cell subset and overall survival (OS), relapse free survival (RFS), and complete response (CR) to chemotherapy were evaluated, modelling cellular proportions as quartiles.ResultsAn immune-related cluster was identified with unsupervised hierarchical clustering of hallmark pathways. Of the immune cells investigated, M0 macrophages emerged as closely associated with worse OS (HR =1.23, 95% CI = 1.15–1.31, p=1.57×10-9) and RFS (HR = 1.14, 95% CI =1.04–1.25, p=2.93×10-3), regardless of molecular subtypes. The CD8+ T cells conferred favorable survival. The neutrophils conferred poor OS overall (HR=1.17, 95% CI=1.10–1.23, p=1.74×10-7) and within the classical subtype. In the basal-like subtype, activated mast cells were associated with worse OS. Consensus clustering revealed six immune subgroups with distinct survival patterns and CR rates. The higher expression of PD1 was associated with better OS.ConclusionsThe immune cellular composition infiltrate in PDAC are likely to have effects on prognosis. Further exploration of the cellular immune response has the potential to identify candidates for immunotherapy.

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