High expression of TIMP-1 in human breast cancer tissues is a predictive of resistance to paclitaxel-based chemotherapy

The TIMP protein family: diverse roles in pathophysiology

The tissue inhibitors of matrix metalloproteinases (TIMPs) are a family of four matrisome proteins classically defined by their roles as the primary endogenous inhibitors of metalloproteinases (MPs). Their functions however are not limited to MP inhibition, with each family member harboring numerous MP-independent biological functions that play key roles in processes such as inflammation and apoptosis. Because of these multifaceted functions, TIMPs have been cited in diverse pathophysiological contexts. Herein, we provide a comprehensive overview of the MP-dependent and -independent roles of TIMPs across a range of pathological conditions. The potential therapeutic and biomarker applications of TIMPs in these disease contexts are also considered, highlighting the biomedical promise of this complex and often misunderstood protein family.

Role of DEK in carcinogenesis, diagnosis, prognosis, and therapeutic outcome of breast cancer: An evidence-based clinical review

Breast cancer is a significantly burdening women's cancer with limited diagnostic modalities. DEK is a novel biomarker overexpressed in breast cancers, currently exhaustively researched for its diagnosis and prognosis. Search for relevant meta-analyses, cohorts, and experimental studies in the last fifteen years was done in five large scientific databases. Non-English, non-full text articles or unrelated studies were excluded. Thirteen articles discussed the potential of DEK to estimate breast cancer characteristics, treatment outcomes, and prognosis. This proto-oncogene plays a role in breast carcinogenesis, increasing tumour proliferation and invasion, preventing apoptosis, and creating an immunodeficient tumour milieu with M2 tumour-associated macrophages. DEK is also associated with worse clinicopathological features and survival in breast cancer patients. Using a Kaplan-Meier plotter data analysis, DEK expression predicts worse overall survival (HR 1.24, 95%CI: 1.01-1.52, p = 0.039), comparable to other biomarkers. DEK is a promising novel biomarker requiring further research to determine its bedside applications.

Integrated Transcriptomic Analysis Revealed Hub Genes and Pathways Involved in Sorafenib Resistance in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC), a high mortality malignancy, has become a worldwide public health concern. Acquired resistance to the multikinase inhibitor sorafenib challenges its clinical efficacy and the survival benefits it provides to patients with advanced HCC. This study aimed to identify critical genes and pathways associated with sorafenib resistance in HCC using integrated bioinformatics analysis. Differentially expressed genes (DEGs) were identified using four HCC gene expression profiles (including 34 sorafenib-resistant and 29 sorafenib-sensitive samples) based on the robust rank aggregation method and R software. Gene ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID) online tool. A protein–protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes (STRING), and small molecules reversing sorafenib resistance were searched for using the connectivity map (CMAP) database. Pearson correlation and survival analyses of hub genes were performed using cBioPortal and Gene Expression Profiling and Interactive Analysis (GEPIA). Finally, the expression levels of hub genes in sorafenib-resistant HCC cells were verified using quantitative polymerase chain reaction (q-PCR). A total of 165 integrated DEGs (66 upregulated and 99 downregulated in sorafenib resistant samples compared sorafenib sensitive ones) primarily enriched in negative regulation of endopeptidase activity, extracellular exosome, and protease binding were identified. Some pathways were commonly shared between the integrated DEGs. Seven promising therapeutic agents and 13 hub genes were identified. These findings provide a strategy and theoretical basis for overcoming sorafenib resistance in HCC patients.

Biomarker analysis to predict the pathological response to neoadjuvant chemotherapy in locally advanced gastric cancer: An exploratory biomarker study of COMPASS, a randomized phase II trial

Background: The findings of COMPASS, a randomized phase II study, suggested that the regimens and courses of neoadjuvant chemotherapy (NAC) for locally advanced gastric cancer (GC) did not affect the pathological response. However, pathological complete response was achieved in 10% patients who received four courses of either S-1/cisplatin or paclitaxel/cisplatin. We hypothesized that if relevant biomarkers could be used to predict the suitable NAC regimen before treatment initiation, further improvements could be ensured in the outcomes of locally advanced GC.

Materials and Methods: mRNA extraction, real-time polymerase chain reaction, and immunohistochemical analyses were performed using endoscopic biopsy specimens of primary tumors, collected prior to NAC, to determine the clinically relevant biomarkers.

Results: TIMP1, DSG2, RRM1, MUC2, EGFR, ZDHHC14, and CLDN18.2 were identified as biomarker candidates, since their expression was significantly associated with the pathological responses to each NAC regimen. Furthermore, TIMP1 and DSG2 were identified as predictive biomarkers of the pathological response to each NAC regimen.

Conclusions: The effective prediction of the pathological response to NAC regimens in locally advanced GC using biomarkers identified from endoscopic biopsy specimens indicates the possibility of personalizing NAC based on biomarker analysis.

A Machine-Learning Approach to Identify a Prognostic Cytokine Signature That Is Associated With Nivolumab Clearance in Patients With Advanced Melanoma

Lower clearance of immune checkpoint inhibitors is a predictor of improved overall survival (OS) in patients with advanced cancer. We investigated a novel approach using machine learning to identify a baseline composite cytokine signature via clearance, which, in turn, could be associated with OS in advanced melanoma. Peripheral nivolumab clearance and cytokine data from patients treated with nivolumab in two phase III studies (n = 468 (pooled)) and another phase III study (n = 158) were used for machine-learning model development and validation, respectively. Random forest (Boruta) algorithm was used for feature selection and classification of nivolumab clearance. The 16 top-ranking baseline inflammatory cytokines reflecting immune-cell modulation were selected as a composite signature to predict nivolumab clearance (area under the curve (AUC) = 0.75; accuracy = 0.7). Predicted clearance (high vs. low) via the cytokine signature was significantly associated with OS across all three studies (P < 0.01), regardless of treatment (nivolumab vs. chemotherapy).

ERα propelled aberrant global DNA hypermethylation by activating the DNMT1 gene to enhance anticancer drug resistance in human breast cancer cells

Drug-induced aberrant DNA methylation is the first identified epigenetic marker involved in chemotherapy resistance. Understanding how the aberrant DNA methylation is acquired would impact cancer treatment in theory and practice. In this study we systematically investigated whether and how ERα propelled aberrant global DNA hypermethylation in the context of breast cancer drug resistance. Our data demonstrated that anticancer drug paclitaxel (PTX) augmented ERα binding to the DNMT1 and DNMT3b promoters to activate DNMT1 and DNMT3b genes, enhancing the PTX resistance of breast cancer cells. In support of these observations, estrogen enhanced multi-drug resistance of breast cancer cells by up-regulation of DNMT1 and DNMT3b genes. Nevertheless, the aberrant global DNA hypermethylation was dominantly induced by ERα-activated-DNMT1, since DNMT1 over-expression significantly increased global DNA methylation and DNMT1 knockdown reversed the ERα-induced global DNA methylation. Altering DNMT3b expression had no detectable effect on global DNA methylation. Consistently, the expression level of DNMT1 was positively correlated with ERα in 78 breast cancer tissue samples shown by our immunohistochemistry (IHC) analysis and negatively correlated with relapse-free survival (RFS) and distance metastasis-free survival (DMFS) of ERα-positive breast cancer patients. This study provides a new perspective for understanding the mechanism underlying drug-resistance-facilitating aberrant DNA methylation in breast cancer and other estrogen dependent tumors.

Prognostic impact of serum and tissue MMP-9 in non-small cell lung cancer: a systematic review and meta-analysis

Matrix metalloproteinases-9 (MMP-9) was one of the most important enzyme to breakdown extracellular matrix, aim to clarify the prognostic value of MMP-9 in non-small cell lung cancer (NSCLC), we investigated the serum MMP-9 of NSCLC patients and performed a meta-analysis of the published literature. The expression and activity of serum MMP-9 were assessed by ELISA and gelatin zymography in 163 NSCLC patients. Moreover, 26 studies were included in meta-analysis by searching Medline and ISI Web of Knowledge. Our own data revealed high activity but not expression of MMP-9 significantly correlated with advanced T category and positive metastasis. In contrast, the meta-analysis revealed that increased MMP-9 level indicate high T category (RR = 0.83, 95% CI: 0.73-0.94), tumor stage (RR = 0.72, 95% CI: 0.63-0.82) and poor OS (5-year overall survival, RR = 1.32, 95% CI: 1.19-1.48). Moreover, stratified analysis based on sample types found that high MMP-9 expression in tissue specimen but not serum was significant correlated with advanced T category (RR = 0.81, 95% CI: 0.72-0.92), tumor stage (RR = 0.69, 95% CI: 0.60-0.80) and poor 5-year OS (1.33, 95% CI: 1.18-1.50).In conclusion, the activity of MMP-9 was positively correlated with advanced T category and distant metastasis. Moreover, the meta-analysis revealed that overexpression of MMP-9 in tissue but not in serum was a risk factor of advanced T category, tumor stage and poor outcome.

Current status of the prognostic molecular biomarkers in breast cancer: A systematic review

Biomarkers that facilitate the prediction of breast cancer prognosis can improve the quality of life in patients during the long period of illness and treatment. Particularly in recent years, with the advent of a more exhaustive analysis of genetic information and gene products, the molecular mechanisms at play during breast cancer have gradually become clearer. In the present study, a systematic review of the literature between 2009 and 2014 was conducted by searching for the keywords 'breast cancer', 'biomarkers', 'diagnosis', 'prognosis' and 'drug response' to clarify the present state of knowledge regarding biomarkers. In the final analysis, 16 studies on biomarkers for the breast cancer prognosis were retrieved. From these, 7 biomarkers in 9 studies were found to be strongly reliable predictors of prognosis and a further 7 biomarkers in 7 studies were poorly reliable. The use of these prognostic biomarkers should increase the options available for treatment algorithms.

Anti-cancer effect of Annona Muricata Linn Leaves Crude Extract (AMCE) on breast cancer cell line

Background

Annona muricata Linn which comes from Annonaceae family possesses many therapeutic benefits as reported in previous studies and to no surprise, it has been used in many cultures to treat various ailments including headaches, insomnia, and rheumatism to even treating cancer. However, Annona muricata Linn obtained from different cultivation area does not necessarily offer the same therapeutic effects towards breast cancer (in regards to its bioactive compound production). In this study, anti-proliferative and anti-cancer effects of Annona muricata crude extract (AMCE) on breast cancer cell lines were evaluated.

Methods

A screening of nineteen samples of Annona muricata from different location was determined by MTT assay on breast cancer cell lines (MCF-7, MDA-MB-231, and 4 T1) which revealed a varied potency (IC₅₀) amongst them. Then, based on the IC₅₀ profile from the anti-proliferative assay, further downward assays such as cell cycle analysis, Annexin V/FITC, AO/PI, migration, invasion, and wound healing assay were performed only with the most potent leaf aqueous extract (B1 AMCE) on 4 T1 breast cancer cell line to investigate its anti-cancer effect. Then, the in vivo anti-cancer study was conducted where mice were fed with extract after inducing the tumor. At the end of the experiment, histopathology of tumor section, tumor nitric oxide level, tumor malondialdehyde level, clonogenic assay, T cell immunophenotyping, and proteome profiler analysis were performed.

Results

Annona muricata crude extract samples exhibited different level of cytotoxicity toward breast cancer cell lines. The selected B1 AMCE reduced the tumor’s size and weight, showed anti-metastatic features, and induced apoptosis in vitro and in vivo of the 4 T1 cells. Furthermore, it decreased the level of nitric oxide and malondialdehyde in tumor while also increased the level of white blood cell, T-cell, and natural killer cell population.

Conclusion

The results suggest that, B1 AMCE is a promising candidate for cancer treatment especially in breast cancer and deserves further research as an alternative to conventional drugs while also stressed out the selection of soursop sample which plays a significant role in determining its potential therapeutic effect on cancer.

Electronic supplementary material

The online version of this article (doi:10.1186/s12906-016-1290-y) contains supplementary material, which is available to authorized users.

Gene expression profile of normal and cancer-associated fibroblasts according to intratumoral inflammatory cells phenotype from breast cancer tissue

The biological heterogeneity of breast cancer leads to the need for finding new approaches to understand the mechanisms implicated in breast cancer progression. The tumor stroma appears as a key in the progression of solid tumors towards a malignant phenotype. Cancer associated fibroblasts (CAFs) may orchestrate a functional "corrupted" stroma which in turn helps metastatic spread. In this study, we investigated by real-time PCR, the expression of 19 factors by normal breast-associated fibroblasts (NAFs) and CAFs, which were implicated in several actions promoting tumor growth, such as extracellular matrix remodeling, inflammation and invasion. Also, we explored the influence of inflammatory cells phenotypes (MMP11 status) and breast cancer cell lines (MCF-7 and MDA-MB-231) on the molecular profile of CAFs. If we consider that one of the major sources of CAFs are resident NAFs, the transition of NAFs into CAFs is associated with molecular changes involving the overexpression of some molecular factors of biological importance in tumor progression. In addition, the characterization of the tumor stroma regarding to the MMP11 status by MICs reflects a type of fibroblasts which contribute even more to tumor progression. Moreover, different patterns in the induction of the expression of factors by CAFs were observed, depending on the tumor cell line which they were co-cultured with. Furthermore, CAFs influence TGFβ expression in both cancer cell lines. Therefore, this study can help to a better characterization of tumor stroma in order to improve the prognostic evaluation, as well as to define the different populations of CAFs as potential therapeutic targets in breast cancer. © 2015 Wiley Periodicals, Inc.

Far beyond the usual biomarkers in breast cancer: a review

Research investigating biomarkers for early detection, prognosis and the prediction of treatment responses in breast cancer is rapidly expanding. However, no validated biomarker currently exists for use in routine clinical practice, and breast cancer detection and management remains dependent on invasive procedures. Histological examination remains the standard for diagnosis, whereas immunohistochemical and genetic tests are utilized for treatment decisions and prognosis determinations. Therefore, we conducted a comprehensive review of literature published in PubMed on breast cancer biomarkers between 2009 and 2013. The keywords that were used together were breast cancer, biomarkers, diagnosis, prognosis and drug response. The cited references of the manuscripts included in this review were also screened. We have comprehensively summarized the performance of several biomarkers for diagnosis, prognosis and predicted drug responses of breast cancer. Finally, we have identified 15 biomarkers that have demonstrated promise in initial studies and several miRNAs. At this point, such biomarkers must be rigorously validated in the clinical setting to be translated into clinically useful tests for the diagnosis, prognosis and prediction of drug responses of breast cancer.

Analysis of serum protein glycosylation by a differential lectin immunosorbant assay (dLISA)

Background

Lectin immunosorbant assays (LISAs) have been widely used for analyzing protein glycosylation. However, the analysis of serum samples by LISAs could suffer from high sample-dependent background noise. The aim of this study is to develop a differential lectin immunosorbant assay (dLISA) with reduced background interferences.

Methods

For the analysis of protein glycosylation, dLISA establishes a dose–response curve for every serum sample. The sample is split into five aliquots. Four aliquots undergo differential removal of the glycoprotein of interest by immunoprecipitation. Then, all five aliquots are subject to two measurements: protein by immunoassay and protein glycans by LISA. A dose–response curve is established by plotting glycans signals on the y-axis and protein levels on the x-axis for all the aliquots. Slope of the curve, calculated by linear progression analysis and expressed as fluorescence per concentration of protein, is used for the measurement of protein glycosylation in the serum sample.

Results/conclusions

To demonstrate the feasibility of the dLISA approach, we used recombinant, fucosylated tissue inhibitor of metallopeptidase 1 (TIMP-1) as the target glycoprotein. Magnetic beads based TIMP1 immunoassay and TIMP-1 UEA LISA were developed for the measurement of TIMP1 protein and terminal α1, 2 fucosylated glycans on TIMP1, respectively. Serum samples supplemented with differentially fucosylated recombinant TIMP-1 were used to demonstrate that the slopes measured the TIMP-1 fucosylation, and were less prone to background interference.