Quantitative phosphoproteomic analysis identifies novel functional pathways of tumor suppressor DLC1 in estrogen receptor positive breast cancer

Protein Profiling of Breast Cancer for Treatment Decision-Making

The increasing use of neoadjuvant therapy has resulted in therapeutic decisions being made on the basis of diagnostic needle core biopsy. For many patients, this method might yield the only fragment of tumor available for biomarker analysis, necessitating judicious use. Many multiplex protein analytic methods have been developed that employ fluorescence or other tags to overcome the limitations of immunohistochemistry while still retaining the spatial annotation. Interpretation of the data can be difficult because of the limitations of the human eye. Computational deconvolution of the signals may be necessary for some of these methods to enable identification of cell-specific localization and coexpression of biomarkers. Herein, we present the different methods that are coming of age and their application in cancer research, with a focus on breast cancer. We also discuss the limitations, which include high costs and long turnaround times. The methods are also based on the premise that preanalytical factors will have identical impact on all proteins analyzed. There is a need to establish standards to normalize the data and enable cross-sample comparisons. In spite of these limitations, the multiplex technologies are extremely valuable discovery tools and can provide novel insights into the biology of cancer and mechanisms of drug resistance.

CircZKSCAN1 Suppresses Hepatocellular Carcinoma Tumorigenesis by Regulating miR-873-5p/Downregulation of Deleted in Liver Cancer 1

BACKGROUND

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-associated mortality worldwide. CircZKSCAN1 (hsa_circ_0001727) was reported to be related to HCC development. The present study aims to elucidate the potential role and molecular mechanism of circZKSCAN1 in the regulation of HCC progression.

METHODS

CircZKSCAN1, miR-873-5p, and downregulation of deleted in liver cancer 1 (DLC1) in HCC tissues and cells were detected by RT-qPCR. Correlation between circZKSCAN1 expression and overall survival rate was measured by Kaplan-Meier survival analysis. The effects of circZKSCAN1, miR-873-5p, and DLC1 on proliferation, migration, and invasion were analyzed by CCK-8 and transwell assays, respectively. CyclinD1, Matrix metalloproteinase (MMP)-9, MMP-2, and DLC1 in HCC cells were detected by Western blot assay. The binding relationship between miR-873-5p and circZKSCAN1 or DLC1 was predicted by the Circinteractome or Starbase, and then confirmed by dual-luciferase reporter assays, respectively. Tumor volume and tumor weight were measured in vivo.

RESULTS

CircZKSCAN1 was downregulated in HCC tissues and cells. Kaplan-Meier survival analysis suggested that there was a positive correlation between circZKSCAN1 expression and overall survival rate. Functionally, circZKSCAN1 blocked proliferation, migration, and invasion of HCC cells. MiR-873-5p was a target miRNA of circZKSCAN1, and miR-873-5p directly bound with DLC1. Rescue experiments confirmed that miR-873-5p overexpression or DLC1 knockdown attenuated the suppressive effects of circZKSCAN1 on HCC tumor growth in vitro. Besides, circZKSCAN1 inhibited HCC cell growth in vivo.

CONCLUSIONS

This study firstly revealed that circZKSCAN1 curbed HCC progression via modulating miR-873-5p/DLC1 axis, providing a potential therapeutic target for HCC treatment.

Proteomics and its applications in breast cancer

Breast cancer is an individually unique, multi-faceted and chameleonic disease, an eternal challenge for the new era of high-integrated precision diagnostic and personalized oncomedicine. Besides traditional single-omics fields (such as genomics, epigenomics, transcriptomics and metabolomics) and multi-omics contributions (proteogenomics, proteotranscriptomics or reproductomics), several new "-omics" approaches and exciting proteomics subfields are contributing to basic and advanced understanding of these "multiple diseases termed breast cancer": phenomics/cellomics, connectomics and interactomics, secretomics, matrisomics, exosomics, angiomics, chaperomics and epichaperomics, phosphoproteomics, ubiquitinomics, metalloproteomics, terminomics, degradomics and metadegradomics, adhesomics, stressomics, microbiomics, immunomics, salivaomics, materiomics and other biomics. Throughout the extremely complex neoplastic process, a Breast Cancer Cell Continuum Concept (BCCCC) has been modeled in this review as a spatio-temporal and holistic approach, as long as the breast cancer represents a complex cascade comprising successively integrated populations of heterogeneous tumor and cancer-associated cells, that reflect the carcinoma's progression from a "driving mutation" and formation of the breast primary tumor, toward the distant secondary tumors in different tissues and organs, via circulating tumor cell populations. This BCCCC is widely sustained by a Breast Cancer Proteomic Continuum Concept (BCPCC), where each phenotype of neoplastic and tumor-associated cells is characterized by a changing and adaptive proteomic profile detected in solid and liquid minimal invasive biopsies by complex proteomics approaches. Such a profile is created, beginning with the proteomic landscape of different neoplastic cell populations and cancer-associated cells, followed by subsequent analysis of protein biomarkers involved in epithelial-mesenchymal transition and intravasation, circulating tumor cell proteomics, and, finally, by protein biomarkers that highlight the extravasation and distant metastatic invasion. Proteomics technologies are producing important data in breast cancer diagnostic, prognostic, and predictive biomarkers discovery and validation, are detecting genetic aberrations at the proteome level, describing functional and regulatory pathways and emphasizing specific protein and peptide profiles in human tissues, biological fluids, cell lines and animal models. Also, proteomics can identify different breast cancer subtypes and specific protein and proteoform expression, can assess the efficacy of cancer therapies at cellular and tissular level and can even identify new therapeutic target proteins in clinical studies.

Tumor suppressor gene DLC1: Its modifications, interactive molecules, and potential prospects for clinical cancer application

Deleted in liver cancer 1 (DLC1) is a recognized tumor suppressor gene that negatively regulates Rho family proteins by hydrolyzing the active GTP-bound state to its inactive GDP-bound state. Active Rho proteins play a positive role in tumorigenesis. Numerous in vitro and in vivo experiments have shown that DLC1 is downregulated or inactivated in various solid tumors, which may be due to the following five reasons: genomic deletion, epigenetic modification and ubiquitin-dependent proteasomal degradation may cause DLC1 underexpression; phosphorylation at the post-translation level may cause DLC1 inactivation; and failure to localize at focal adhesions (FAs) may prevent DLC1 from exerting full activity. All of the causes could be attributed to molecular binding. Experimental evidence suggests that direct or indirect targeting of DLC1 is feasible for cancer treatment. Therefore, elucidating the interaction of DLC1 with its binding partners might provide novel targeted therapies for cancer. In this review, we summarized the binding partners of DLC1 at both the gene and protein levels and expounded a variety of anticancer drugs targeting DLC1 to provide information about DLC1 as a cancer diagnostic indicator or therapeutic target.

DLC1 inhibits lung adenocarcinoma cell proliferation, migration and invasion via regulating MAPK signaling pathway

Lung adenocarcinoma (LUAD), one of the most common cancers, is a major threat to people's health due to its high mortality, and the survival of most patients suffering LUAD remains poor. This study aimed to explore the mechanism of Deleted in Liver Cancer 1 (DLC1) as a tumor suppressor underlying the occurrence and progression of LUAD. As revealed by bioinformatics analysis and qRT-PCR, DLC1 was significantly down-regulated in LUAD tumor tissue and cells. A series of cellular experiments including CCK-8, wound healing and Transwell assays were performed to detect the effect of DLC1 on the biological function of LUAD cells. It was found that overexpressing DLC1 significantly inhibited LUAD cell proliferative, migratory and invasive abilities, while knockdown of DLC1 promoted these abilities. Gene Set Enrichment Analysis (GSEA) and dual-luciferase assay were used to explore the downstream signaling pathway of DLC1, finding that DLC1 could remarkably inhibit the activity of mitogen-activated protein kinase (MAPK) signaling pathway. Western blot implemented for MAPK signaling pathway-related proteins further identified that DLC1 restrained the activation of MAPK/ERK signaling pathway. Furthermore, rescue experiments suggested that DLC1 inhibited LUAD cell proliferation and invasion by suppressing the MAPK/ERK signaling pathway. Overall, our study discussed the DLC1-dependent mechanism involved in LUAD. We found that the up-regulation of DLC1 may inhibit the malignant progression of LUAD by suppressing MAPK signaling pathway, which supports the view that DLC1 may serve as a molecular target for the targeted therapy of LUAD patients.

MIR-301b-3p Promotes Lung Adenocarcinoma Cell Proliferation, Migration and Invasion by Targeting DLC1

BACKGROUND

miR-301b-3p is reported in various human cancers for its abnormal expression, while the role and molecular mechanisms in lung adenocarcinoma (LUAD) remain unclear, and this is the focus of the present study.

MATERIALS AND METHODS

TCGA database was consulted to know gene expression in LUAD tissue. CCK-8, colony formation assay and Transwell assay were applied to identify the role of target genes in regulating LUAD cell biological properties. Bioinformatics analysis plus dual-luciferase assay were performed to validate the potential connection between genes.

RESULTS

miR-301b-3p and DLC1 were the target genes of this study and respectively differentially up-regulated and down-regulated in LUAD. Functional experiments indicated that miR-301b-3p contributed to cancer cell proliferation, migration and invasion, while this effect was reversed with overexpressed DLC1 which was identified as a direct target of and regulated by miR-301b-3p.

CONCLUSIONS

Collectively, miR-301b-3p was identified to actively function on LUAD malignant progression by suppressing DLC1 expression. This discovery provides a novel therapeutic strategy for LUAD patients, which helps improve the survival of patients.

A Quantitative Global Proteomics Approach Identifies Candidate Urinary Biomarkers That Correlate With Intraductal Papillary Mucinous Neoplasm Dysplasia

OBJECTIVES

A proteomic discovery study was performed to determine if urine possesses a unique biosignature that could form the basis for a noninvasive test able to predict intraductal papillary mucinous neoplasm (IPMN) dysplasia.

METHODS

Urine was collected from patients undergoing surgery for IPMN (72 low/moderate, 27 high-grade/invasive). Quantitative mass spectrometry-based proteomics was performed. Proteins of interest were identified by differential expression analysis followed by principal component analysis.

RESULTS

Proteomics identified greater than 4800 urinary proteins. Low/moderate and high-grade/invasive IPMN were distinguished by 188 proteins (P < 0.05). Following principal component analysis and heatmap visualization, vitamin D binding protein (DBP), apolipoprotein A1 (APOA1), and alpha-1 antitrypsin (A1AT) were selected. The proteomic abundance of DBP (median [interquartile range]) was significantly higher for high-grade/invasive than for low/moderate IPMN (219,735 [128,882-269,943] vs. 112,295 [77,905-180,773] normalized reporter ion intensity units; P = 0.001). Similarly, APOA1 was more abundant in the high-grade/invasive than low/moderate groups (235,420 [144,933-371,247] vs 150,095 [103,419-236,591]; P = 0.0007) as was A1AT (567,514 [358,544-774,801] vs 358,393 [260,850-477,882]; P = 0.0006).

CONCLUSIONS

Urinary DBP, APOA1, and A1AT represent potential biomarker candidates that may provide a noninvasive means of predicting IPMN dysplastic grade.

circRNA-associated ceRNA network construction reveals the circRNAs involved in the progression and prognosis of breast cancer

Recently, increasing evidences show that circular RNAs (circRNAs) are important regulators of various diseases, especially cancer. However, the regulatory role and the potential mechanism of action of circRNAs in breast cancer remain largely unknown. In this study, weighted gene co-expression network analysis was conducted with the differentially expressed miRNAs and mRNAs in breast cancer from The Cancer Genome Atlas database to identify the key modules associated with the carcinogenesis of breast cancer. In the significant turquoise and brown modules, 22 miRNAs and 1877 mRNAs were identified, respectively. Then, We compared and predicted the target genes and performed survival analysis to identify the miRNAs and mRNAs related to the prognosis of breast cancer. A circRNA-related competitive endogenous RNA network was identified by database co-screening, and deleted in liver cancer 1 (DLC1) was identified as a key gene. Finally, to assess how genes in key modules and key genes contribute to the development of breast cancer, relevant pathway information was obtained through DAVID and Gene Set Enrichment Analysis. These data demonstrated that three circRNAs (hsa-circ-0083373, hsa-circ-0083374, and hsa-circ-0083375) that regulate DLC1 expression via hsa-mir-511 and are involved in the pathogenesis and development of breast cancer.

Bioinformatics analysis of potential therapeutic targets among ARHGAP genes in breast cancer

GTPase activating proteins (RhoGAPs) serve significant roles in multiple aspects of tumor biology. Genes encoding RhoGAPs (ARHGAP), which switch off Rho-like GTPases, are responsible for breast cancer biogenesis. However, the identification of suitable and novel biomarkers for precision treatment and prognosis remains challenging. The present study aimed to evaluate the expression of ARHGAP family genes in breast cancer and investigate the survival data using the Oncomine, Kaplan-Meier Plotter, bcGenExMiner and cBioPortal online databases. The results demonstrated low expression of ARHGAP6, 7, 10, 14, 19, 23 and 24 and high expression of ARHGAP9, 11, 15, 18 and 30 in patients with breast cancer compared with that in healthy individuals. The survival analysis revealed that low expression levels of ARHGAP6, 7 and 19 were associated with poor relapse-free survival (RFS) and overall survival (OS), whereas high expression levels of ARHGAP9, 15 and 30 were associated with preferable RFS and OS. Metastatic relapse data demonstrated that higher expression of ARHGAP9, 15, 18, 19, 25 and 30 were associated with better prognosis and increased expression of ARHGAP11A and 14 exerted negative effects on patient prognosis. The overlapping genes ARHGAP9, 15, 19 and 30 obtained from these bioinformatics analysis tools exhibited significant association with clinical parameters including age, the presence of estrogen receptor, progesterone receptor and epidermal growth factor receptor-2, Scarff-Bloom-Richardson grade and Nottingham prognostic index. In conclusion, bioinformatics analysis revealed that ARHGAP9, 15, 19 and 30, but not other ARHGAP family genes may be promising targets with prognostic value and biological function for precision treatment of breast cancer.