Regulation of dual specificity phosphatases in breast cancer during initial treatment with Herceptin: a Boolean model analysis

Oncogenes and tumor suppressor genes: functions and roles in cancers

Cancer, being the most formidable ailment, has had a profound impact on the human health. The disease is primarily associated with genetic mutations that impact oncogenes and tumor suppressor genes (TSGs). Recently, growing evidence have shown that X-linked TSGs have specific role in cancer progression and metastasis as well. Interestingly, our genome harbors around substantial portion of genes that function as tumor suppressors, and the X chromosome alone harbors a considerable number of TSGs. The scenario becomes even more compelling as X-linked TSGs are adaptive to key epigenetic processes such as X chromosome inactivation. Therefore, delineating the new paradigm related to X-linked TSGs, for instance, their crosstalk with autosome and involvement in cancer initiation, progression, and metastasis becomes utmost importance. Considering this, herein, we present a comprehensive discussion of X-linked TSG dysregulation in various cancers as a consequence of genetic variations and epigenetic alterations. In addition, the dynamic role of X-linked TSGs in sex chromosome-autosome crosstalk in cancer genome remodeling is being explored thoroughly. Besides, the functional roles of ncRNAs, role of X-linked TSG in immunomodulation and in gender-based cancer disparities has also been highlighted. Overall, the focal idea of the present article is to recapitulate the findings on X-linked TSG regulation in the cancer landscape and to redefine their role toward improving cancer treatment strategies.

lncRNA-disease association prediction method based on the nearest neighbor matrix completion model

State-of-the-art medical studies proved that long noncoding ribonucleic acids (lncRNAs) are closely related to various diseases. However, their large-scale detection in biological experiments is problematic and expensive. To aid screening and improve the efficiency of biological experiments, this study introduced a prediction model based on the nearest neighbor concept for lncRNA-disease association prediction. We used a new similarity algorithm in the model that fused potential associations. The experimental validation of the proposed algorithm proved its superiority over the available Cosine, Pearson, and Jaccard similarity algorithms. Satisfactory results in the comparative leave-one-out cross-validation test (with AUC = 0.96) confirmed its excellent predictive performance. Finally, the proposed model's reliability was confirmed by performing predictions using a new dataset, yielding AUC = 0.92.

Connecting Cancer Pathways to Tumor Engines: A Stratification Tool for Colorectal Cancer Combining Human In Vitro Tissue Models with Boolean In Silico Models

To improve and focus preclinical testing, we combine tumor models based on a decellularized tissue matrix with bioinformatics to stratify tumors according to stage-specific mutations that are linked to central cancer pathways. We generated tissue models with BRAF-mutant colorectal cancer (CRC) cells (HROC24 and HROC87) and compared treatment responses to two-dimensional (2D) cultures and xenografts. As the BRAF inhibitor vemurafenib is-in contrast to melanoma-not effective in CRC, we combined it with the EGFR inhibitor gefitinib. In general, our 3D models showed higher chemoresistance and in contrast to 2D a more active HGFR after gefitinib and combination-therapy. In xenograft models murine HGF could not activate the human HGFR, stressing the importance of the human microenvironment. In order to stratify patient groups for targeted treatment options in CRC, an in silico topology with different stages including mutations and changes in common signaling pathways was developed. We applied the established topology for in silico simulations to predict new therapeutic options for BRAF-mutated CRC patients in advanced stages. Our in silico tool connects genome information with a deeper understanding of tumor engines in clinically relevant signaling networks which goes beyond the consideration of single drivers to improve CRC patient stratification.

Kinetic Modeling of DUSP Regulation in Herceptin-Resistant HER2-Positive Breast Cancer

BACKGROUND

HER2 (human epidermal growth factor 2)-positive breast cancer is an aggressive type of breast cancer characterized by the overexpression of the receptor-type protein tyrosine kinase HER2 or amplification of the HER2 gene. It is commonly treated by the drug trastuzumab (Herceptin), but resistance to its action frequently develops and limits its therapeutic benefit. Dual-specificity phosphatases (DUSPs) were previously highlighted as central regulators of HER2 signaling; therefore, understanding their role is crucial to designing new strategies to improve the efficacy of Herceptin treatment. We investigated whether inhibiting certain DUSPs re-sensitized Herceptin-resistant breast cancer cells to the drug. We built a series of kinetic models incorporating the key players of HER2 signaling pathways and simulating a range of inhibition intensities. The simulation results were compared to live tumor cells in culture, and showed good agreement with the experimental analyses. In particular, we observed that Herceptin-resistant DUSP16-silenced breast cancer cells became more responsive to the drug when treated for 72 h with Herceptin, showing a decrease in resistance, in agreement with the model predictions. Overall, we showed that the kinetic modeling of signaling pathways is able to generate predictions that assist experimental research in the identification of potential targets for cancer treatment.

Nuclear-Biased DUSP6 Expression is Associated with Cancer Spreading Including Brain Metastasis in Triple-Negative Breast Cancer

DUSP6 is a dual-specificity phosphatase (DUSP) involved in breast cancer progression, recurrence, and metastasis. DUSP6 is predominantly cytoplasmic in HER2+ primary breast cancer cells, but the expression and subcellular localization of DUSPs, especially DUSP6, in HER2-positive circulating tumor cells (CTCs) is unknown. Here we used the DEPArray system to identify and isolate CTCs from metastatic triple negative breast cancer (TNBC) patients and performed single-cell NanoString analysis to quantify cancer pathway gene expression in HER2-positive and HER2-negative CTC populations. All TNBC patients contained HER2-positive CTCs. HER2-positive CTCs were associated with increased ERK1/ERK2 expression, which are direct DUSP6 targets. DUSP6 protein expression was predominantly nuclear in breast CTCs and the brain metastases but not pleura or lung metastases of TNBC patients. Therefore, nuclear DUSP6 may play a role in the association with cancer spreading in TNBC patients, including brain metastasis.

Modelling the role of dual specificity phosphatases in herceptin resistant breast cancer cell lines

BACKGROUND

Breast cancer remains the most lethal type of cancer for women. A significant proportion of breast cancer cases are characterised by overexpression of the human epidermal growth factor receptor 2 protein (HER2). These cancers are commonly treated by Herceptin (Trastuzumab), but resistance to drug treatment frequently develops in tumour cells. Dual-specificity phosphatases (DUSPs) are thought to play a role in the mechanism of resistance, since some of them were reported to be overexpressed in tumours resistant to Herceptin.

RESULTS

We used a systems biology approach to investigate how DUSP overexpression could favour cell proliferation and to predict how this mechanism could be reversed by targeted inhibition of selected DUSPs. We measured the expression of 20 DUSP genes in two breast cancer cell lines following long-term (6 months) exposure to Herceptin, after confirming that these cells had become resistant to the drug. We constructed several Boolean models including specific substrates of each DUSP, and showed that our models correctly account for resistance when overexpressed DUSPs were kept activated. We then simulated inhibition of both individual and combinations of DUSPs, and determined conditions under which the resistance could be reversed.

CONCLUSIONS

These results show how a combination of experimental analysis and modelling help to understand cell survival mechanisms in breast cancer tumours, and crucially enable us to generate testable predictions potentially leading to new treatments of resistant tumours.

Dual-specificity phosphatase 5 suppresses ovarian cancer progression by inhibiting IL-33 signaling

Ovarian cancer (OC) is the leading cause of death from gynecological malignancy. Dual-specificity phosphatases (DUSPs) are proteins that are reported involved in carcinogenesis, but their roles in OC have not be extensively studied. Here, we found that DUSP5 is markedly down-regulated in OC tissues. We reanalyzed DUSP5 expression in OC using published microarray data from the Gene Expression Omnibus (GEO) database and found that patients with low DUSP5 expression have significantly shorter overall survival than those with high expression (P < 0.001). Down-regulation of DUSP5 in OC tissues was immunohistochemically confirmed in tissue microarrays containing 15 normal ovary tissue samples and 60 OC specimens. Functional studies suggest that DUSP5 silence facilitates cell proliferation, migration, and invasion of OC cells in vitro. DUSP5 over-expression inhibits cell proliferation but has no effect on OC cell migration or invasion. Mechanistically, silencing DUSP5 transcriptionally activates interleukin 33 (IL-33) expression and secretion. Blockage of IL-33 with a neutralizing anti-IL33 antibody attenuates the effect of DUSP5 silencing to promote cell proliferation, migration, and invasion. Moreover, recombinant IL-33 protein treatment dramatically promotes OC cell proliferation, migration, and invasion with DUSP5 over-expression. Our study provides proof of principle that DUSP5 down-regulation promotes proliferation, migration, and invasion of OC cells via activation of IL-33 signaling.