Clinical significance of serum tenascin-C levels in breast cancer

Prognostic implications of tenascin C in peripheral blood and primary tumours at the time of uveal melanoma diagnosis

OBJECTIVE

To examine the prognostic implication of tenascin C (TNC) in posterior uveal melanoma (UM).

DESIGN

Retrospective cohort study.

PARTICIPANTS

A total of 162 patients diagnosed with posterior UM.

METHODS

A peripheral blood sample was obtained from 82 patients at the time of UM diagnosis between 1996 and 1999. Samples were kept frozen at -80°C until the concentration of TNC was measured in 2021. Primary tumour TNC RNA sequencing data were collected from another 80 patients (The Cancer Genome Atlas cohort). Patients were separated based on median TNC values. Cumulative incidences of metastatic death (UM mortality) from competing risks data were calculated as well as Cox regression hazard ratios.

RESULTS

Patients with high and low TNC levels had tumours of similar size and American Joint Committee on Cancer stage at Bonferroni-corrected significance levels. The exception was a significantly smaller tumour diameter in patients with high serum TNC levels (p = 0.003). In competing risks analysis, patients with high serum TNC levels (≥7 ng/mL) had a higher UM mortality rate (44% vs 17% at 20 years; p = 0.008). Similarly, patients with higher primary tumour TNC RNA levels (≥1 transcripts per million) had higher UM mortality (83% vs 27% at 5 years; p = 0.003). In multivariate Cox regressions, TNC levels in peripheral blood and primary tumours were predictors of metastatic death independent of American Joint Committee on Cancer stage.

CONCLUSIONS

TNC is a prognostic biomarker in UM. At the time of primary tumour diagnosis, it is measured in higher levels in both peripheral blood and tumour tissue from patients who will eventually suffer from metastatic death.

Identification of potential crucial genes associated with the pathogenesis and prognosis of prostate cancer

Aim: Prostate cancer (PCa) is the sixth leading cause of cancer-related deaths in men throughout the world. This study aimed to investigate genes associated with the pathogenesis and prognosis of PCa. Materials & methods: Data of PCa cases were obtained from public datasets and were analyzed using an integrated bioinformatics strategy. Results: A total of 969 differential expression genes were identified. Moreover, GSE16560 and The Cancer Genome Atlas (TCGA) data showed a prognostic prompt function of the nine-gene signature, as well as in PCa with Gleason 7. Finally, majority of the nine hub genes were associated with drug sensitivity, mutational landscape, immune infiltrates and clinical characteristics of PCa. Conclusion: The nine-gene signature was correlated with drug sensitivity, mutational landscape, immune infiltrates, clinical characteristics and survival from PCa.

Prognostic Role of Tenascin-C for Cancer Outcome: A Meta-Analysis

Background:

The prognostic value of tenascin-C in different types of cancers remains controversial. To clarify its prognostic value on overall survival rates, we have conducted a meta-analysis to quantitatively assess the prognostic roles of tenascin-C for patients with cancer.

Methods:

We systematically searched all published studies about the role of tenascin-C in cancers on PubMed, Web of Science, Cochrane Library, and Embase. The pooled hazard ratio with 95% confidence intervals was used to analyze the association between tenascin-C expression level and overall survival of patients with cancer. The pooled odds ratio with 95% confidence intervals was used to investigate the association between tenascin-C expression level and clinicopathologic features of patients with cancer. Trial sequential analysis was performed to obtain the required information size.

Results:

In this meta-analysis, 18 studies including 2732 patients were incorporated. The pooled hazard ratio of 18 trials was 1.73 (95% confidence interval: 1.29-2.32, P < .001) for overall survival, suggesting that elevated tenascin-C expression strongly predicted poor prognosis among patients with various cancers. Simultaneously, elevated tenascin-C expression was also significantly associated with lymph node metastasis (odds ratio = 2.42, 95% confidence interval: 1.79-3.26, P < .001). However, no significant correlation was observed between the tenascin-C expression and distant metastasis (odds ratio = 1.72, 95% confidence interval: 0.86-3.44, P = .127).

Conclusions:

Tenascin-C is considered as a promising unfavorable prognostic factor in human cancers. Likewise, tenascin-C can be used as a monitoring indicator for poor prognosis in a wide range of cancers.

The role of matricellular proteins and tissue stiffness in breast cancer: a systematic review

Malignancies consist not only of cancerous and nonmalignant cells, but also of additional elements, as extracellular matrix. The aim of this review is to summarize meta-analyses, describing breast tissue stiffness and risk of breast carcinoma (BC) assessing the potential relationship between matricellular proteins (MPs) and survival. A systematic computer-based search of published articles, according to PRISMA statement, was conducted through Ovid interface. Mammographic density and tissue stiffness are associated with the risk of BC development, suggesting that MPs may influence BC prognosis. No definitive conclusions are available and additional researches are required to definitively clarify the role of each MP, mammographic density and stiffness in BC development and the mechanisms involved in the onset of this malignancy.

GWAS-based machine learning approach to predict duloxetine response in major depressive disorder

Major depressive disorder (MDD) is one of the most prevalent psychiatric disorders and is commonly treated with antidepressant drugs. However, large variability is observed in terms of response to antidepressants. Machine learning (ML) models may be useful to predict treatment outcomes. A sample of 186 MDD patients received treatment with duloxetine for up to 8 weeks were categorized as "responders" based on a MADRS change >50% from baseline; or "remitters" based on a MADRS score ≤10 at end point. The initial dataset (N = 186) was randomly divided into training and test sets in a nested 5-fold cross-validation, where 80% was used as a training set and 20% made up five independent test sets. We performed genome-wide logistic regression to identify potentially significant variants related to duloxetine response/remission and extracted the most promising predictors using LASSO regression. Subsequently, classification-regression trees (CRT) and support vector machines (SVM) were applied to construct models, using ten-fold cross-validation. With regards to response, none of the pairs performed significantly better than chance (accuracy p > .1). For remission, SVM achieved moderate performance with an accuracy = 0.52, a sensitivity = 0.58, and a specificity = 0.46, and 0.51 for all coefficients for CRT. The best performing SVM fold was characterized by an accuracy = 0.66 (p = .071), sensitivity = 0.70 and a sensitivity = 0.61. In this study, the potential of using GWAS data to predict duloxetine outcomes was examined using ML models. The models were characterized by a promising sensitivity, but specificity remained moderate at best. The inclusion of additional non-genetic variables to create integrated models may improve prediction.

Tenascin-C serum levels and its prognostic power in non-small cell lung cancer

Background

Tenascin-C is overexpressed in the stroma of most solid malignancies and may function as a diagnostic tumor marker. This study was conducted to evaluate the potential significance of Tenascin-C as a predictive marker for tumor progression in the sera of non-small cell lung cancer (NSCLC) patients.

Results

Serum concentration of Tenascin-C is significantly elevated in NSCLC patients compared to healthy controls (p=0.013). The sensitivity of Tenascin-C in detecting NSCLC was 74% at a specificity of 57%. Elevated Tenascin-C serum values are associated with larger tumor size and lymph node involvement (p=0.022 and p=0.036, respectively). The Kaplan-Meyer-curves showed a significant association of Tenascin-C with the patient's overall survival (p=0.004), but not with the recurrence-free survival (p=0.328).

Methods

We quantified Tenascin-C in the sera of 103 NSCLC patients and 76 healthy blood donors by enzyme-linked immune-absorbance assay tests. Prognostic significance was determined by area under the curve analysis and Youden-index. The results were correlated with clinical, histopathological, and patient survival data (Chi-square test, Kaplan-Meier analysis, log-rank test, multivariate Cox-regression analysis).

Conclusion

Although significantly elevated in patients with NSCLC, the sensitivity and specificity of the Tenascin-C serum quantification test was low. However, although failing to be an independent prognosticator in multivariate analysis, the results implicate Tenascin-C as a predictive prognostic marker for NSCLC patients. The data must be further validated in future prospective trials with larger patient cohorts.

Tenascin C is a prognostic determinant and potential cancer-associated fibroblasts marker for breast ductal carcinoma

Tenascin C (TNC) is a key of extracellular matrix glycoprotein and highly express in numerous human malignancies. Herein, we attempted to clarify the clinicopathological significance of TNC as a prognostic determinant of breast ductal carcinoma. Then, we investigated TNC immunohistochemical expression in 150 breast ductal carcinomas and 27 normal breast tissue samples. Clinical relevance of TNC expression and the association TNC expression with other factors related to cancer-associated fibroblasts were also examined. In results, TNC expression was significantly higher in breast ductal carcinoma (56.0%) than normal breast tissues (25.9%). The upregulation TNC in cancer stromal were associated with pT stage (P=0.003), lymph node metastasis (P=0.002) and tumor node metastasis stage (P=0.001), also was correlated with an increase in tumor-associated macrophage population (P<0.001). The microvessel density (MVD) was significantly higher in TNC positive group than in negative group (P<0.001). In both univariate and multivariate Cox regression analyses, TNC was an independent poor prognostic factor for overall survival (OS) in breast ductal carcinoma patients. Importantly, over-expression TNC (P<0.001), FSP1 (P<0.001), SMA (P=0.002) and Vimentin (P=0.049) were significantly correlation with the lower OS (P<0.005). In addition, TNC expression in breast ductal carcinoma stromal was positively correlated with FSP1 (P<0.001), SMA (P=0.001) and Vimentin (P<0.001). In conclusion, the high expression of TNC could be a useful cancer-associated fibroblasts marker for the prediction of prognosis of breast ductal carcinoma patients.

How interacting pathways are regulated by miRNAs in breast cancer subtypes

BACKGROUND

An important challenge in cancer biology is to understand the complex aspects of the disease. It is increasingly evident that genes are not isolated from each other and the comprehension of how different genes are related to each other could explain biological mechanisms causing diseases. Biological pathways are important tools to reveal gene interaction and reduce the large number of genes to be studied by partitioning it into smaller paths. Furthermore, recent scientific evidence has proven that a combination of pathways, instead than a single element of the pathway or a single pathway, could be responsible for pathological changes in a cell.

RESULTS

In this paper we develop a new method that can reveal miRNAs able to regulate, in a coordinated way, networks of gene pathways. We applied the method to subtypes of breast cancer. The basic idea is the identification of pathways significantly enriched with differentially expressed genes among the different breast cancer subtypes and normal tissue. Looking at the pairs of pathways that were found to be functionally related, we created a network of dependent pathways and we focused on identifying miRNAs that could act as miRNA drivers in a coordinated regulation process.

CONCLUSIONS

Our approach enables miRNAs identification that could have an important role in the development of breast cancer.

Increased Obesity-Associated Circulating Levels of the Extracellular Matrix Proteins Osteopontin, Chitinase-3 Like-1 and Tenascin C Are Associated with Colon Cancer

BACKGROUND

Excess adipose tissue represents a major risk factor for the development of colon cancer with inflammation and extracellular matrix (ECM) remodeling being proposed as plausible mechanisms. The aim of this study was to investigate whether obesity can influence circulating levels of inflammation-related extracellular matrix proteins in patients with colon cancer (CC), promoting a microenvironment favorable for tumor growth.

METHODS

Serum samples obtained from 79 subjects [26 lean (LN) and 53 obese (OB)] were used in the study. Enrolled subjects were further subclassified according to the established diagnostic protocol for CC (44 without CC and 35 with CC). Anthropometric measurements as well as circulating metabolites and hormones were determined. Circulating concentrations of the ECM proteins osteopontin (OPN), chitinase-3-like protein 1 (YKL-40), tenascin C (TNC) and lipocalin-2 (LCN-2) were determined by ELISA.

RESULTS

Significant differences in circulating OPN, YKL-40 and TNC concentrations between the experimental groups were observed, being significantly increased due to obesity (P<0.01) and colon cancer (P<0.05). LCN-2 levels were affected by obesity (P<0.05), but no differences were detected regarding the presence or not of CC. A positive association (P<0.05) with different inflammatory markers was also detected.

CONCLUSIONS

To our knowledge, we herein show for the first time that obese patients with CC exhibit increased circulating levels of OPN, YKL-40 and TNC providing further evidence for the influence of obesity on CC development via ECM proteins, representing promising diagnostic biomarkers or target molecules for therapeutics.

Integration of Breast Cancer Secretomes with Clinical Data Elucidates Potential Serum Markers for Disease Detection, Diagnosis, and Prognosis

Cancer cells secrete factors that influence adjacent cell behavior and can lead to enhanced proliferation and metastasis. To better understand the role of these factors in oncogenesis and disease progression, estrogen and progesterone receptor positive MCF-7 cells, triple negative breast cancer MDA-MB-231, DT22, and DT28 cells, and MCF-10A non-transformed mammary epithelial cells were grown in 3D cultures. A special emphasis was placed on triple negative breast cancer since these tumors are highly aggressive and no targeted treatments are currently available. The breast cancer cells secreted factors of variable potency that stimulated proliferation of the relatively quiescent MCF-10A cells. The conditioned medium from each cell line was subjected to mass spectrometry analysis and a variety of secreted proteins were identified including glycolytic enzymes, proteases, protease inhibitors, extracellular matrix proteins, and insulin-like growth factor binding proteins. An investigation of the secretome from each cell line yielded clues about strategies used for breast cancer proliferation and metastasis. Some of the proteins we identified may be useful in the development of a serum-based test for breast cancer detection, diagnosis, prognosis, and monitoring.

Expression of the Extracellular Matrix Protein Tenascin-C Varies During Lactation

BACKGROUND

Women diagnosed with pregnancy-associated breast cancer postpartum have a worse prognosis, stage for stage, than other women with breast cancer. The time of breast involution is tumor promotional. The extracellular matrix protein tenascin-C is upregulated during involution in animal models and promotes breast cancer progression. It interacts with transforming growth factor (TGF)β, which also is involved in breast involution and breast cancer progression. Little is known about the expression of tenascin-C during human breast involution, nor its relationship to TGFβ. The purpose of this study was to investigate the expression of tenascin-C throughout lactation, as well as its relationship to TGFβ1 and TGFβ2.

MATERIAL AND METHODOLOGY

Three milk samples from 25 lactating women (transitional, whole, and wean) were collected, separated into components (cells, fat, and skim), and the skim fraction analyzed for total protein, tenascin-C, TGFβ1, and TGFβ2. Tenascin-C, TGFβ1, and TGFβ2 were detectable in all milk samples.

RESULTS

Highest tenascin-C levels on average were found in whole milk, whereas highest mean TGFβ1 and TGFβ2 levels were in wean milk. Wean samples on average had higher levels of both TGFβ1 (26%) and TGFβ2 (>500%) than matched transitional milk samples. Tenascin-C levels in wean milk were associated with nursing length (p = 0.048). Combining all three milk collection time points, tenascin-C exhibited a weak inverse correlation with TGFβ1 and TGFβ2 (p < 0.1). The inverse correlation at the wean time point was stronger for TGFβ2 than -1 (-0.37 versus -0.25). Tenascin-C, a protein known to promote breast cancer progression, is expressed throughout lactation.

CONCLUSION

The inverse correlation with TGFβ2 in wean milk suggests a possible interaction during breast involution, which should be further investigated.

Tenascin-C, a Prognostic Determinant of Esophageal Squamous Cell Carcinoma

BACKGROUND

Tenascin-C, an adhesion modulatory extracellular matrix molecule, is highly expressed in numerous human malignancies; thus, it may contribute to carcinogenesis and tumor progression. We explored the clinicopathological significance of Tenascin-C as a prognostic determinant of esophageal squamous cell carcinoma (ESCC).

METHODS

In ESCC patient tissues and cell lines, the presence of isoforms were examined using western blotting. We then investigated Tenascin-C immunohistochemical expression in 136 ESCC tissue samples. The clinical relevance of Tenascin-C expression and the correlation between Tenascin-C expression and expression of other factors related to cancer-associated fibroblasts (CAFs) were also determined.

RESULTS

Both 250 and 350 kDa sized isoforms of Tenascin-C were expressed only in esophageal cancer tissue not in normal tissue. Furthermore, both isoforms were also identified in all of four CAFs derived from esophageal cancer tissues. Tenascin-C expression was remarkably higher in ESCC than in adjacent non-tumor esophageal epithelium (p < 0.001). Tenascin-C expression in ESCC stromal fibroblasts was associated with patient's age, tumor (pT) stage, lymph node metastasis, clinical stage, and cancer recurrence. Tenascin-C expression in cancer cells was correlated with an increase in tumor-associated macrophage (TAM) population, cancer recurrence, and hypoxia inducible factor1α (HIF1α) expression. Moreover, Tenascin-C overexpression in cancer cells and stromal fibroblasts was an independent poor prognostic factor for overall survival (OS) and disease-free survival (DFS). In the Cox proportional hazard regression model, Tenascin-C overexpression in cancer cells and stromal fibroblasts was a significant independent hazard factor for OS and DFS in ESCC patients in both univariate and multivariate analyses. Furthermore, Tenascin-C expression in stromal fibroblasts of the ESCC patients was positively correlated with platelet-derived growth factor α (PDGFRα), PDGFRβ, and smooth muscle actin (SMA) expression. The 5-year OS and DFS rates were remarkably lower in patients with positive expressions of both Tenascin-C and PDGFRα (p < 0.001), Tenascin-C and PDGFRβ (p < 0.001), Tenascin-C and SMA (p < 0.001), Tenascin-C and fibroblast activation protein (FAP) (p < 0.001), and Tenascin-C and fibroblast-stimulating protein-1 (FSP1) (p < 0.001) in ESCC stromal fibroblasts than in patients with negative expressions of both Tenascin-C and one of the abovementioned CAF markers.

CONCLUSION

Our results show that Tenascin-C is a reliable and significant prognostic factor in ESCC. Tenascin-C may thus be a potent ESCC therapeutic target.

Tenascin-C: Form versus function

Tenascin-C is a large, multimodular, extracellular matrix glycoprotein that exhibits a very restricted pattern of expression but an enormously diverse range of functions. Here, we discuss the importance of deciphering the expression pattern of, and effects mediated by, different forms of this molecule in order to fully understand tenascin-C biology. We focus on both post transcriptional and post translational events such as splicing, glycosylation, assembly into a 3D matrix and proteolytic cleavage, highlighting how these modifications are key to defining tenascin-C function.

Tenascin-C: Exploitation and collateral damage in cancer management

Despite an increasing knowledge about the causes of cancer, this disease is difficult to cure and still causes far too high a death rate. Based on advances in our understanding of disease pathogenesis, novel treatment concepts, including targeting the tumor microenvironment, have been developed and are being combined with established treatment regimens such as surgical removal and radiotherapy. Yet it is obvious that we need additional strategies to prevent tumor relapse and metastasis. Given its exceptional high expression in most cancers with low abundance in normal tissues, tenascin-C appears an ideal candidate for tumor treatment. Here, we will summarize the current applications of targeting tenascin-C as a treatment for different tumors, and highlight the potential of this therapeutic approach.

Does Tenascin have Clinical Implications in Pathological Grade of Glioma Patients?: A Systematic Meta-Analysis

Tenascin (TN) is an extracellular oligomeric glycoprotein that participates in the adhesion of cells to extracellular matrixc (ECM). Studies have shown that the expression levels of TN are upregulated in a variety of cancers, including colon cancer, lung cancer, brain tumor, and breast cancer. However, the implications and utilities of TN in clinical grading and prognosis of glioma patients were seldom reported and the effects of its pathway are still unclear and controversial. Thus, it is essential to carry out a meta-analysis to draw a convincing conclusion.A literature search was carried out up to April 2015. Data was collected using a purpose-designed form including glioma's WHO grade, etc. Differences were expressed as odds ratios (ORs) or standard mean differences (SMDs) with 95% confidence intervals (CIs). Galbr figure, Cochran's Q test, and I test were all performed to judge the heterogeneity between included studies. To examine the stability of the pooled results, a sensitivity analysis was performed. Potential publication bias was assessed by visual inspection of funnel plot. As this meta-analysis, as a systematic review, does not involve animal experiments or direct human trials, there is no need to conduct special ethic review and the ethical approval is not necessary.In this meta-analysis, 8 eligible studies involving 456 patients were incorporated. Six studies with dichotomous data revealed TN overexpression in glioma tissues and/or surrounding neoplastic vessels was closely associated with high WHO grade (III + IV) (odds ratio 3.398, 95% confidence interval 1.933, 5.974; P = 0.000); three continuous data studies showed there were close statistical associations between TN and WHO grade (SMD -2.114, 95% CI -2.580, -1.649; P = 0.000) too. Sensitivity analysis indicated a statistically robust result. No publication bias was revealed.Our meta-analysis suggests that TN expression is potentially associated with higher WHO grade of gliomas. More evidences on the basis of the evidence-based medicine are needed to prove it.

PET imaging of tenascin-C with a radiolabeled single-stranded DNA aptamer

Tenascin-C is an extracellular matrix glycoprotein that is expressed by injured tissues and by various cancers. Recent publications showed that tenascin-C expression by cancer lesions predicts tumor growth, metastasis, and angiogenesis, suggesting tenascin-C as a potential therapeutic target. Currently there is no noninvasive method to determine tumoral tenascin-C expression in vivo. To address the need for an agent to image and quantify tenascin-C, we report the development of a radioactive PET tracer based on a tenascin-C-specific single-stranded DNA aptamer (tenascin-C aptamer).

METHODS

Tenascin-C aptamer was radiolabeled with (18)F and (64)Cu. PET imaging studies for the evaluation of tumor uptake and pharmacokinetics of tenascin-C aptamer were performed in comparison to a nonspecific scrambled aptamer (Sc aptamer).

RESULTS

The labeled tenascin-C aptamer provided clear visualization of tenascin-C-positive but not tenascin-C-negative tumors. The uptake of tenascin-C aptamer was significantly higher than that of Sc aptamer in tenascin-C-positive tumors. The labeled tenascin-C aptamer had fast clearance from the blood and other nonspecific organs through the kidneys, resulting in high tumor contrast.

CONCLUSION

Our data suggest that suitably labeled tenascin-C aptamer can be used as a PET tracer to image tumor expression of tenascin-C with a high tumor-to-background ratio and might provide insightful and personalized medical data that will help determine appropriate treatment and monitoring.