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Molecular markers associated with outcome and metastasis in human pancreatic cancer

ABSTRACT: Pancreatic ductal adenocarcinoma (PDAC) is a heterogeneous cancer in which differences in survival rates might be related to a variety in gene expression profiles. Although the molecular biology of PDAC begins to be revealed, genes or pathways that specifically drive tumour progression or metastasis are not well understood. Therefore, we performed microarray analyses on whole-tumour samples of 2 human PDAC subpopulations with similar clinicopathological features, but extremely distinct survival rates after potentially curative surgery, i.e., good outcome (OS and DFS > 50 months) versus bad outcome (OS < 19 months and DFS < 7 months). Additionally, liver- and peritoneal metastases were analysed and compared to primary cancer tissue. The integrin and ephrin receptor families were upregulated in all PDAC samples, irrespective of outcome, supporting an important role of the interaction between pancreatic cancer cells and the surrounding desmoplastic reaction in tumorigenesis and cancer progression. Moreover, some components, such as ITGB1 and EPHA2, were upregulated in PDAC samples with a poor outcome, Additionally, overexpression of the non-canonical Wnt/β-catenin pathway and EMT genes in PDAC samples with bad versus good outcome suggests their contribution to the invasiveness of pancreatic cancer, with β-catenin being also highly upregulated in metastatic tissue. Thus, we conclude that components of the integrin and ephrin pathways and EMT-related genes might serve as molecular markers in pancreatic cancer as their expression seems to be related with prognosis. Microarray analysis was performed on 'Good' and 'Bad' patient samples (samples with similar pathological characteristics were chosen based on the definition of the 2 diverse survival outcome groups and the required RIN values above 7.1), on surrounding non-tumoural pancreatic control samples, liver metastasis (LM) and peritoneal metastasis (PM). Comparisons between good vs. control, bad vs. control, good vs. bad, and primary pancreatic cancer versus metastasis were performed.

ORGANISM(S): Homo sapiens

SUBMITTER: Van den Broeck A

PROVIDER: S-ECPF-GEOD-42952 | biostudies-other | 2012

REPOSITORIES: biostudies-other

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Project description:Pancreatic ductal adenocarcinoma (PDAC) is a heterogeneous cancer in which differences in survival rates might be related to a variety in gene expression profiles. Although the molecular biology of PDAC begins to be revealed, genes or pathways that specifically drive tumour progression or metastasis are not well understood. Therefore, we performed microarray analyses on whole-tumour samples of 2 human PDAC subpopulations with similar clinicopathological features, but extremely distinct survival rates after potentially curative surgery, i.e., good outcome (OS and DFSM-bM-^@M-^I>M-bM-^@M-^I50M-bM-^@M-^Imonths) versus bad outcome (OSM-bM-^@M-^I<M-bM-^@M-^I19M-bM-^@M-^Imonths and DFSM-bM-^@M-^I<M-bM-^@M-^I7M-bM-^@M-^Imonths). Additionally, liver- and peritoneal metastases were analysed and compared to primary cancer tissue. The integrin and ephrin receptor families were upregulated in all PDAC samples, irrespective of outcome, supporting an important role of the interaction between pancreatic cancer cells and the surrounding desmoplastic reaction in tumorigenesis and cancer progression. Moreover, some components, such as ITGB1 and EPHA2, were upregulated in PDAC samples with a poor outcome, Additionally, overexpression of the non-canonical Wnt/M-NM-2-catenin pathway and EMT genes in PDAC samples with bad versus good outcome suggests their contribution to the invasiveness of pancreatic cancer, with M-NM-2-catenin being also highly upregulated in metastatic tissue. Thus, we conclude that components of the integrin and ephrin pathways and EMT-related genes might serve as molecular markers in pancreatic cancer as their expression seems to be related with prognosis. Microarray analysis was performed on 'Good' and 'Bad' patient samples (samples with similar pathological characteristics were chosen based on the definition of the 2 diverse survival outcome groups and the required RIN values above 7.1), on surrounding non-tumoural pancreatic control samples, liver metastasis (LM) and peritoneal metastasis (PM). Comparisons between good vs. control, bad vs. control, good vs. bad, and primary pancreatic cancer versus metastasis were performed.

Project description:BackgroundBreast cancer heterogeneity is an essential element that plays a role in the therapy response variability and the patient's outcome. This highlights the need for more precise subtyping methods that focus not only on tumor cells but also investigate the profile of stromal cells as well as immune cells.ObjectivesTo mine publicly available transcriptomic breast cancer datasets and reanalyze their transcriptomic profiling using unsupervised clustering in order to identify novel subsets in molecular subtypes of breast cancer, then explore the stromal and immune cells profile in each subset using bioinformatics and systems immunology approaches.Materials and methodsTranscriptomic data from 1,084 breast cancer patients obtained from The Cancer Genome Atlas (TCGA) database were extracted and subjected to unsupervised clustering using a recently described, multi-step algorithm called Iterative Clustering and Guide-gene Selection (ICGS). For each cluster, the stromal and immune profile was investigated using ESTIMATE and CIBERSORT analytical tool. Clinical outcomes and differentially expressed genes of the characterized clusters were identified and validated in silico and in vitro in a cohort of 80 breast cancer samples by immunohistochemistry.ResultsSeven unique sub-clusters showed distinct molecular and clinical profiles between the well-known breast cancer subtypes. Those unsupervised clusters identified more homogenous subgroups in each of the classical subtypes with a different prognostic profile. Immune profiling of the identified clusters showed that while the classically activated macrophages (M1) are correlated with the more aggressive basal-like breast cancer subtype, the alternatively activated macrophages (M2) showed a higher level of infiltration in luminal A and luminal B subtypes. Indeed, patients with higher levels of M1 expression showed less advanced disease and better patient outcomes presented as prolonged overall survival. Moreover, the M1 high basal-like breast cancer group showed a higher expression of interferon-gamma induced chemokines and guanylate-binding proteins (GBPs) involved in immunity against microbes.ConclusionAdding immune profiling using transcriptomic data can add precision for diagnosis and prognosis and can cluster patients according to the available modalities of therapy in a more personalized approach.

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Molecular markers associated with outcome and metastasis in human pancreatic cancer

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