Dataset Information

Novel stromal biomarker screening in pancreatic cancer patients using the in vitro cancer-stromal interaction model.

ABSTRACT: Background: Stromal fibroblasts associated with pancreatic ductal adenocarcinoma (PDAC) play an important role in tumor progression through interactions with cancer cells. Our proposed combination strategies of in vitro and in silico biomarker screening through a cancer-stromal interaction model were previously identified several actin-binding proteins in human colon cancer stroma. The main aim of the present study was to identify novel prognostic markers in human PDAC stroma using our strategies.

Methods: Five primary cultivated fibroblasts from human pancreas were stimulated by two types of pancreatic cancer-cell-conditioned medium (Capan-1 and MIA PaCa-2) followed by gene expression analysis to identify up-regulated genes. Publicly available microarray data set concomitant with overall survival was collected and prognostic marker candidates were selected among the genes that were found to be up-regulated. The mRNA expression levels of the selected genes were evaluated in 5 human fresh PDAC tissues. Finally, survival analysis was performed based on immunohistochemical results on tissue microarrays consisting of 216 surgically resected PDAC tissues.

Results: The microarray data of the cancer-stromal interaction model revealed that 188 probes were significantly regulated in pancreatic fibroblasts. Further, six genes were selected using publicly available microarray data set, and a single Diaphanous-related formin-3 (DIAPH3), actin-binding protein, was identified as a stromal biomarker in PDAC fibroblasts by RNA validation analysis. DIAPH3 exhibited strong immunohistochemical expression in stromal fibroblasts. The high stromal expression of DIAPH3 was associated with shorter survival times of PDAC patients.

Conclusions: DIAPH3 was identified as a prognostic marker in PDAC fibroblasts using our biomarker screening strategies through the cancer-stromal interaction model, indicating that stromal actin-binding proteins might have an important biological role in cancer progression. These strategies were also available in PDAC, and can be used for stromal biomarker screening in various cancers.

SUBMITTER: Nishida Y

PROVIDER: S-EPMC7724826 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Novel stromal biomarker screening in pancreatic cancer patients using the in vitro cancer-stromal interaction model.

Nishida Yasunori Y Nagatsuma Akiko Kawano AK Kojima Motohiro M Gotohda Naoto N Ochiai Atsushi A

BMC gastroenterology 20201209 1

<h4>Background</h4>Stromal fibroblasts associated with pancreatic ductal adenocarcinoma (PDAC) play an important role in tumor progression through interactions with cancer cells. Our proposed combination strategies of in vitro and in silico biomarker screening through a cancer-stromal interaction model were previously identified several actin-binding proteins in human colon cancer stroma. The main aim of the present study was to identify novel prognostic markers in human PDAC stroma using our st ...[more]

PMID: 33297976

Similar Datasets

Project description:BackgroundCYP26A1 has been reported in multiple cancers. However, the role of CYP26A1 in pancreatic cancer (PC) has not been explored.MethodThe public data used for this study was obtained from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Cancer Cell Line Encyclopedia (CCLE) cell lines. CCK8, colony formation, and EdU assay were used to assess the proliferation ability of cancer cells. Transwell and wound healing assays were used to evaluate the invasion and migration ability of cancer cells. qRT-PCR and western blot assays were used to analyze the RNA and protein level of genes. Survival package was used for prognosis analysis. Gene Set Enrichment Analysis (GSEA) was used to identify biological pathway differences between two groups. ssGSEA analysis was used to quantify the immune microenvironment in PC tissue. GDSC and TIDE analyses were used for sensitivity analysis of chemotherapy and immunotherapy.ResultsOur results showed that CYP26A1 was overexpressed in PC tissue and cell lines. Meanwhile, metastatic PC cell lines tend to have a higher CYP26A1 level compared with the primary PC cell lines based on CCLE data. Moreover, CYP26A1 was associated with worse clinical features. Also, we found that CYP26A1 had a satisfactory efficiency in predicting overall survival, disease-specific survival, and progression-free interval of PC patients, independent of other clinical features. In vitro experiments indicated that CYP26A1 could significantly facilitate the proliferation, invasion, and migration ability of PC cells. GSEA showed that the pathways of angiogenesis, E2F target, MYC target, mTORC signaling, G2M checkpoint, and epithelial-mesenchymal transition were activated in high CYP26A1 patients. Immune infiltration analysis showed that CYP26A1 was positively correlated with macrophages, Th1 cells, and Treg cells, but negatively correlated with Th17 cells. TIDE analysis showed that non_responder patients had a higher CYP26A1 level compared with predicted responder patients of immunotherapy. Drug sensitivity analysis and assay showed that CYP26A1 could increase the chemotherapy sensitivity of gemcitabine.ConclusionsIn summary, CYP26A1 promotes PC progression and is a novel biomarker of PC, with potential for clinical application.

Project description:BackgroundExtracellular signal-regulated kinases (ERKs) have been related to multiple cancers, including breast cancer, hepatocellular cancer, lung cancer and colorectal cancer. ERK1/2 inhibitor can suppress growth of KRAS-mutant pancreatic tumors by targeting cancer cell. However, no studies have shown the expression of ERK1/2 on pancreatic stromal and its effect on pancreatic cancer-stromal interaction.MethodsImmunohistochemistry and western blotting were performed to detect the expression of p-ERK1/2 in pancreatic tissues and cells. Cell viability assay was used to study IC50 of ERK inhibitor on pancreatic cancer cells (PCCs) and primary cancer-associated pancreatic stellate cells (PSCs). Transwell migration, invasion, cell viability assay, senescence β-galactosidase staining were performed to determine the effect of ERK inhibitor on PCCs and PSCs in vitro and in vivo. The expression of key factors involved in autophagy and epithelial-to-mesenchymal transition (EMT) process were evaluated by western blotting. The expression of key factors related to cell invasiveness and malignancy were confirmed by qRT-PCR. Co-transplantation of PCC Organoid and PSC using a splenic xenograft mouse model was used to evaluated combined treatment of ERK inhibitor and autophagy inhibitor.ResultsImmunohistochemical staining in pancreatic tumor samples and transgenetic mice detected p-ERK1/2 expression in both cancer cells and stromal cells. In pancreatic tissues, p-ERK1/2 was strongly expressed in cancer-associated PSCs compared with cancer cells and normal PSCs. PSCs were also significantly more sensitive to ERK1/2 inhibitor treatment. Inhibition of ERK1/2 suppressed EMT transition in HMPCCs, upregulated cellular senescence markers, activated autophagy in cancer-associated PSCs; and suppressed cancer-stromal interaction, which enhanced invasiveness and viability of cancer cells. We also found that chloroquine, an autophagy inhibitor, suppressed ERK inhibition-induced autophagy and promoted PSC cellular senescence, leading to significantly decreased cell proliferation. The combination of an ERK inhibitor and autophagy inhibitor suppressed liver metastasis in a splenic pancreatic cancer organoid xenograft mouse model.ConclusionsThese data indicate that inhibition of ERK1/2 in cancer-associated pancreatic stellate cells suppresses cancer-stromal interaction and metastasis.

Dataset Information

Novel stromal biomarker screening in pancreatic cancer patients using the in vitro cancer-stromal interaction model.

Publications

Novel stromal biomarker screening in pancreatic cancer patients using the in vitro cancer-stromal interaction model.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets