EMMPRIN is associated with S100A4 and predicts patient outcome in colorectal cancer.
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ABSTRACT: Background
Proteolytic enzymes and their regulators have important biological roles in colorectal cancer by stimulating invasion and metastasis, which makes these factors attractive as potential prognostic biomarkers.Methods
The expression of extracellular matrix metalloproteinase inducer (EMMPRIN) was characterised using immunohistochemistry in primary tumours from a cohort of 277 prospectively recruited colorectal cancer patients, and associations with expression of S100A4, clinicopathological parameters and patient outcome were investigated.Results
One hundred and ninety-eight samples (72%) displayed positive membrane staining of the tumour cells, whereas 10 cases (4%) were borderline positive. EMMPRIN expression was associated with shorter metastasis-free, disease-specific and overall survival in both univariate and multivariate analyses. The prognostic impact was largely confined to TNM stage III, and EMMPRIN-negative stage III patients had an excellent prognosis. Furthermore, EMMPRIN was significantly associated with expression of S100A4, and the combined expression of these biomarkers conferred an even poorer prognosis. However, there was no evidence of direct regulation between the two proteins in the colorectal cancer cell lines HCT116 and SW620 in siRNA knockdown experiments.Conclusion
EMMPRIN is a promising prognostic biomarker in colorectal cancer, and our findings suggest that it could be used in the selection of stage III patients for adjuvant therapy.
SUBMITTER: Boye K
PROVIDER: S-EPMC3419949 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:PurposeExtracellular matrix metalloproteinase inducer (EMMPRIN) has been reported to play crucial roles, including in angiogenesis, in several carcinomas. However, the correlation between EMMPRIN levels and angiogenesis expression profile has not been reported, and the role of EMMPRIN in renal cell carcinoma (RCC) is unclear. In the present study, we evaluated the association of EMMPRIN with angiogenesis, its value in prognosis, and its roles in RCC.Experimental designEMMPRIN expression was examined in 50 RCC patients treated with radical nephrectomy. Angiogenesis, proliferation, and invasion activity were evaluated using EMMPRIN knockdown RCC cell lines. The size of EMMPRIN-overexpressing xenografts was measured and the degree of angiogenesis was quantified. EMMPRIN expression was evaluated in RCC patients who received sunitinib therapy and in sunitinib-resistant cells. Further, the relation between EMMPRIN expression and sensitivity to sunitinib was examined.ResultsEMMPRIN score was significantly associated with clinicopathological parameters in RCC patients, as well as being significantly correlated with microvessel area (MVA) in immature vessels and with prognosis. Down-regulation of EMMPRIN by siRNA led to decreased VEGF and bFGF expression, cell proliferation, and invasive potential. EMMPRIN over-expressing xenografts showed accelerated growth and MVA of immature vessels. EMMPRIN expression was significantly increased in patients who received sunitinib therapy as well as in sunitinib-resistant 786-O cells (786-suni). EMMPRIN-overexpressing RCC cells were resistant to sunitinib.ConclusionOur findings indicate that high expression of EMMPRIN in RCC plays important roles in tumor progression and sunitinib resistance. Therefore, EMMPRIN could be a novel target for the treatment of RCC.
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Project description:We obtained fibroblast cultures from fresh surgical specimen ressected from patients with primary colorectal carcinoma: normal colonic fibroblasts (NCF=9) from the normal colonic mucosa at least 5-10cm from the surgical margin, carcinoma-associated fibroblasts from the primary tumor (CAF-PT=14) and carcinoma-associated fibroblasts (CAF-LM=11) from fresh surgical specimens of liver metastases. We identified 277 probes, in common between the three types of fibroblasts, whose expression level is sequentially deregulated according to cancer progression (NCF→CAF-PT→CAF-LM; fold change Log2 normalized expression>1.5 in each step). Prediction Analysis of Microarrays was applied to obtain a 25-gene signature that better characterizes each fibroblast class. The signature is able to classify patients carrying primary tumors according to prognosis. This fact was exploited to obtain a 19-gene signature (from the 277 deregulated probes) predicting recurrence with high accuracy in stage II/III colorectal cancer patients. Signature validation has been carried out in two independent datasets and in a meta-cohort of 336 stage II/III patients. Since the 25-gene signature was obtained regardless of gene expression data of tumor specimens or patient’s clinical data, the prognostic power of this signature provides strong evidence of the link between the tumor stroma and cancer progression. Furthermore, the 19-gene signature was able to identify low-risk patients with very high accuracy, especially relevant for those high-risk stage-II patients. We hybridised fibroblast RNA in Affymetrix GeneChip 1.0 st arrays
2013-05-10 | E-GEOD-46824 | biostudies-arrayexpress
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Project description:Image-based machine learning and deep learning in particular has recently shown expert-level accuracy in medical image classification. In this study, we combine convolutional and recurrent architectures to train a deep network to predict colorectal cancer outcome based on images of tumour tissue samples. The novelty of our approach is that we directly predict patient outcome, without any intermediate tissue classification. We evaluate a set of digitized haematoxylin-eosin-stained tumour tissue microarray (TMA) samples from 420 colorectal cancer patients with clinicopathological and outcome data available. The results show that deep learning-based outcome prediction with only small tissue areas as input outperforms (hazard ratio 2.3; CI 95% 1.79-3.03; AUC 0.69) visual histological assessment performed by human experts on both TMA spot (HR 1.67; CI 95% 1.28-2.19; AUC 0.58) and whole-slide level (HR 1.65; CI 95% 1.30-2.15; AUC 0.57) in the stratification into low- and high-risk patients. Our results suggest that state-of-the-art deep learning techniques can extract more prognostic information from the tissue morphology of colorectal cancer than an experienced human observer.
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Project description:PurposeDEAD box protein 3 (DDX3) is an RNA helicase with oncogenic properties that shuttles between the cytoplasm and nucleus. The majority of DDX3 is found in the cytoplasm, but a subset of tumors has distinct nuclear DDX3 localization of yet unknown biological significance. This study aimed to evaluate the significance of and mechanisms behind nuclear DDX3 expression in colorectal and breast cancer.MethodsExpression of nuclear DDX3 and the nuclear exporter chromosome region maintenance 1 (CRM1) was evaluated by immunohistochemistry in 304 colorectal and 292 breast cancer patient samples. Correlations between the subcellular localization of DDX3 and CRM1 and the difference in overall survival between patients with and without nuclear DDX3 were studied. In addition, DDX3 mutants were created for in vitro evaluation of the mechanism behind nuclear retention of DDX3.ResultsDDX3 was present in the nucleus of 35% of colorectal and 48% of breast cancer patient samples and was particularly strong in the nucleolus. Nuclear DDX3 correlated with worse overall survival in both colorectal (hazard ratio [HR] 2.34, P<0.001) and breast cancer (HR 2.39, P=0.004) patients. Colorectal cancers with nuclear DDX3 expression more often had cytoplasmic expression of the nuclear exporter CRM1 (relative risk 1.67, P=0.04). In vitro analysis of DDX3 deletion mutants demonstrated that CRM1-mediated export was most dependent on the N-terminal nuclear export signal.ConclusionOverall, we conclude that nuclear DDX3 is partially CRM1-mediated and predicts worse survival in colorectal and breast cancer patients, putting it forward as a target for therapeutic intervention with DDX3 inhibitors under development in these cancer types.
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Project description:BACKGROUND:Prostate-specific membrane antigen (PSMA) is overexpressed on the endothelial cells of tumor neo-vessels of several solid malignancies, including differentiated thyroid cancer (DTC). We aimed to test the potential role of PSMA as a biomarker for DTC aggressiveness and outcome prediction. We retrospectively screened all patients who underwent thyroidectomy between 1 January 2010 and 31 December 2017 in our institution. Applying the inclusion (histological diagnosis of thyroid cancer and tissue availability) and exclusion criteria (no clinical or follow-up data or diagnosis of medullary thyroid cancer), a cohort of 59 patients was selected. The monoclonal mouse anti-human PSMA antibody was used to stain tissue sections. A 3-point scale was used to score PSMA positivity: 0-5% expression was considered as negative (score 0), 6-50% as moderately positive (score 1), and 51-100% as highly positive (score 2). A cumulative score (0-10%, 11-79%, and 80-100%) was also explored. Univariate and multivariate logistic regression analyses were performed to predict the presence of distant metastases, chosen as endpoint of aggressiveness. The area under the curve (AUC) was calculated. Cox models were built to predict patient outcome in terms of recurrence, iodine refractoriness, and status at last follow-up, which were calculated using the Kaplan-Meier failure function. RESULTS:At immunostaining, 12, 25, and 22 patients had scores of 0, 1, and 2, respectively. According to the cumulative score, PSMA expression was ≤ 10% in 17 cases, 11-79% in 31 cases, and ≥ 80% in 11 cases. At multivariate analysis, age, sex, histotype, vascular invasion, T and N parameters, and PSMA positivity were significant predictors of distant metastases. The AUC was 0.92. Recurrence or progression occurred in 19/59 patients. Twelve patients developed radioiodine (RAI) refractoriness, after a median time of 17 months (range 2-32). One patient died of DTC; 46 of the 58 patients alive at last follow-up were disease free. Median DFS was 23 months (range 3-82). The final multivariate model to predict RAI refractoriness included as covariates the stage, high PSMA expression (≥ 80%), and the interaction between moderate PSMA expression (11-79%) and stage. CONCLUSIONS:PSMA, a marker of neovasculature formation expressed by DTC, contributes in the prediction of tumor aggressiveness and patient outcome.
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