MDK Protein Overexpression Correlates with the Malignant Status and Prognosis of Non-small Cell Lung Cancer

An atlas of cell-type-specific interactome networks across 44 human tumor types

BACKGROUND

Biological processes are controlled by groups of genes acting in concert. Investigating gene-gene interactions within different cell types can help researchers understand the regulatory mechanisms behind human complex diseases, such as tumors.

METHODS

We collected extensive single-cell RNA-seq data from tumors, involving 563 patients with 44 different tumor types. Through our analysis, we identified various cell types in tumors and created an atlas of different immune cell subsets across different tumor types. Using the SCINET method, we reconstructed interactome networks specific to different cell types. Diverse functional data was then integrated to gain biological insights into the networks, including somatic mutation patterns and gene functional annotation. Additionally, genes with prognostic relevance within the networks were also identified. We also examined cell-cell communications to investigate how gene interactions modulate cell-cell interactions.

RESULTS

We developed a data portal called CellNetdb for researchers to study cell-type-specific interactome networks. Our findings indicate that these networks can be used to identify genes with topological specificity in different cell types. We also found that prognostic genes can deconvolved into cell types through analyzing network connectivity. Additionally, we identified commonalities and differences in cell-type-specific networks across different tumor types. Our results suggest that these networks can be used to prioritize risk genes.

CONCLUSIONS

This study presented CellNetdb, a comprehensive repository featuring an atlas of cell-type-specific interactome networks across 44 human tumor types. The findings underscore the utility of these networks in delineating the intricacies of tumor microenvironments and advancing the understanding of molecular mechanisms underpinning human tumors.

Midkine (MDK) in Hepatocellular Carcinoma: More than a Biomarker

Midkine (MDK) is a multifunctional secreted protein that can act as a cytokine or growth factor regulating multiple signaling pathways and being implicated in fundamental cellular processes, such as survival, proliferation, and migration. Although its expression in normal adult tissues is barely detectable, MDK serum levels are found to be elevated in several types of cancer, including hepatocellular carcinoma (HCC). In this review, we summarize the findings of recent studies on the role of MDK in HCC diagnosis and progression. Overall, studies show that MDK is a powerful biomarker for HCC early diagnosis, as it can differentiate not only between HCC patients and normal individuals but also between HCC patients and patients with other liver pathologies. It is correlated with high recurrence rates and was shown to be valuable for the diagnosis of early-stage HCC, even in patients negative for α-fetoprotein (AFP), the most commonly used biomarker for HCC diagnosis. A comparison with AFP reveals that MDK is inferior to AFP with regard to specificity but significantly superior with regard to sensitivity, which further indicates the need for using both biomarkers for more effective HCC diagnosis.

The role of midkine in health and disease

Midkine (MDK) is a neurotrophic growth factor highly expressed during embryogenesis with important functions related to growth, proliferation, survival, migration, angiogenesis, reproduction, and repair. Recent research has indicated that MDK functions as a key player in autoimmune disorders of the central nervous system (CNS), such as Multiple Sclerosis (MS) and is a promising therapeutic target for the treatment of brain tumors, acute injuries, and other CNS disorders. This review summarizes the modes of action and immunological functions of MDK both in the peripheral immune compartment and in the CNS, particularly in the context of traumatic brain injury, brain tumors, neuroinflammation, and neurodegeneration. Moreover, we discuss the role of MDK as a central mediator of neuro-immune crosstalk, focusing on the interactions between CNS-infiltrating and -resident cells such as astrocytes, microglia, and oligodendrocytes. Finally, we highlight the therapeutic potential of MDK and discuss potential therapeutic approaches for the treatment of neurological disorders.

Role of Midkine in Cancer Drug Resistance: Regulators of Its Expression and Its Molecular Targeting

Molecules involved in drug resistance can be targeted for better therapeutic efficacies. Research on midkine (MDK) has escalated in the last few decades, which affirms a positive correlation between disease progression and MDK expression in most cancers and indicates its association with multi-drug resistance in cancer. MDK, a secretory cytokine found in blood, can be exploited as a potent biomarker for the non-invasive detection of drug resistance expressed in various cancers and, thereby, can be targeted. We summarize the current information on the involvement of MDK in drug resistance, and transcriptional regulators of its expression and highlight its potential as a cancer therapeutic target.

Secreted proteins MDK, WFDC2, and CXCL14 as candidate biomarkers for early diagnosis of lung adenocarcinoma

BACKGROUND

Early diagnosis of lung adenocarcinoma (LUAD), one of the most common types of lung cancer, is very important to improve the prognosis of patients. The current methods can't meet the requirements of early diagnosis. There is a pressing need to identify novel diagnostic biomarkers. Secretory proteins are the richest source for biomarker research. This study aimed to identify candidate secretory protein biomarkers for early diagnosis of LUAD by integrated bioinformatics analysis and clinical validation.

METHODS

Differentially expressed genes (DEGs) of GSE31210, gene expression data of early stage of LUAD, were analyzed by GEO2R. Upregulated DEGs predicted to encode secreted proteins were obtained by taking the intersection of the DEGs list with the list of genes encoding secreted proteins predicted by the majority decision-based method (MDSEC). The expressions of the identified secreted proteins in the lung tissues of early-stage LUAD patients were further compared with the healthy control group in mRNA and protein levels by using the UALCAN database (TCGA and CPTAC). The selected proteins expressed in plasma were further validated by using Luminex technology. The diagnostic value of the screened proteins was evaluated by receiver operating characteristic (ROC) analysis. Cell counting kit-8 assay was carried out to investigate the proliferative effects of these screened proteins.

RESULTS

A total of 2183 DEGs, including 1240 downregulated genes and 943 upregulated genes, were identified in the GSE31210. Of the upregulated genes, 199 genes were predicted to encode secreted proteins. After analysis using the UALCAN database, 16 molecules were selected for further clinical validation. Plasma concentrations of three proteins, Midkine (MDK), WAP four-disulfide core domain 2 (WFDC2), and C-X-C motif chemokine ligand 14 (CXCL14), were significantly higher in LUAD patients than in healthy donors. The area under the curve values was 0.944, 0.881, and 0.809 for MDK, WFDC2, and CXCL14, 0.962 when combined them. Overexpression of the three proteins enhanced the proliferation activity of A549 cells.

CONCLUSIONS

MDK, WFDC2, and CXCL14 were identified as candidate diagnostic biomarkers for early-stage LUAD and might also play vital roles in tumorigenesis.

Construction of a prognostic model related to copper dependence in breast cancer by single-cell sequencing analysis

Purpose: To explore the clinical significance of copper-dependent-related genes (CDRG) in female breast cancer (BC).

Methods: CDRG were obtained by single-cell analysis of the GSE168410 dataset in the Gene Expression Omnibus (GEO) database. According to a 1:1 ratio, the Cancer Genome Atlas (TCGA) cohort was separated into a training and a test cohort randomly. Based on the training cohort, the prognostic model was built using COX and Lasso regression. The test cohort was used to validate the model. The GSE20685 dataset and GSE20711 dataset were used as two external validation cohorts to further validate the prognostic model. According to the median risk score, patients were classified as high-risk or low-risk. Survival analysis, immune microenvironment analysis, drug sensitivity analysis, and nomogram analysis were used to evaluate the clinical importance of this prognostic model.

Results: 384 CDRG were obtained by single-cell analysis. According to the prognostic model, patients were classified as high-risk or low-risk in both cohorts. The high-risk group had a significantly worse prognosis. The area under the curve (AUC) of the model was around 0.7 in the four cohorts. The immunological microenvironment was examined for a possible link between risk score and immune cell infiltration. Veliparib, Selumetinib, Entinostat, and Palbociclib were found to be more sensitive medications for the high-risk group after drug sensitivity analysis.

Conclusion: Our CDRG-based prognostic model can aid in the prediction of prognosis and treatment of BC patients.

Midkine-Notch2 Pathway Mediates Excessive Proliferation of Airway Smooth Muscle Cells in Chronic Obstructive Lung Disease

Inflammation-induced proliferation of airway smooth muscle cells (ASMCs) and subsequent airway remodeling is a hallmark of chronic obstructive lung disease (COPD). The role of midkine (MK) in COPD is unclear. In this work, we explored the role of MK-Notch2 signaling in COPD by inhibiting the expression of MK using lentivirus shRNA in ASMCs in vitro and instillation of AAV9-MK in the airway of a COPD rat model in vivo. The results demonstrated that LPS decreased ASMC migration and proliferation, increased apoptosis and induced the expression of MK and Notch2 signaling molecules. Inhibition of MK exacerbated the changes in migration and proliferation but decreased the expression of MK and Notch2 signaling molecules. Rats treated with smoke fumigation and LPS showed features of COPD. The small airways of COPD rats were remodeled and lung function was significantly reduced. The expressions of TGF-β, ICAM-1, HA, MMP-9, PC-III, and LN in BALF and the expression of MK and Notch2 signaling molecules were significantly increased in the COPD rats compared with controls. Inhibition of MK reversed these changes. In conclusion, the MK-Notch2 pathway plays a key role in airway remodeling induced by ASMC proliferation. Targeting the MK-Notch2 pathway may be a new strategy for improving airway remodeling and preventing progressive decline of pulmonary function in COPD.

Midkine promotes breast cancer cell proliferation and migration by upregulating NR3C1 expression and activating the NF-κB pathway

BACKGROUND

Breast cancer (BC) is the most common malignancy in females and is the second leading cause of cancer-related death among women worldwide. Midkine (MDK) is a heparin-binding growth factor that is abnormally expressed at high levels in various human malignancies. We aimed to uncover the biological function and molecular mechanism of MDK in BC cells.

METHODS AND RESULTS

MDA-MB-231-shMDK and T47D-shMDK BC cells were established. The in vitro biological functions of MDK were demonstrated by CCK-8 assays, Transwell assays and Western blotting, whereas qPCR pathway arrays were implemented to explore the mechanism of MDK in BC cells. Functionally, we verified that silencing MDK significantly suppressed BC cell proliferation and migration by inhibiting the activation of the nuclear factor kappa B (NF-κB) pathway and the nuclear distribution of NF-κB. Meanwhile, Ingenuity Pathway Analysis (IPA) and a qPCR pathway array revealed that silencing MDK decreased the expression of NR3C1, a potential downstream target of the NF-κB pathway. We also confirmed that treatment with an NF-κB inhibitor suppressed NR3C1 expression in BC cells. Finally, we demonstrated that silencing NR3C1 repressed BC cell proliferation and migration.

CONCLUSIONS

Our findings highlight a novel mechanism by which MDK influences BC progression via regulation of the NF-κB-NR3C1 pathway.

Midkine promotes glioblastoma progression via PI3K-Akt signaling

Background

Our previous bioinformatics-based study found that midkine (MDK) was associated with poor prognosis of glioblastoma (GBM). However, the mechanism of MDK in GBM remains elusive.

Methods

A public GBM-related dataset and GBM tissues from our center were used validate the aberrant expression of MDK in GBM at the RNA and protein levels. The relationship between MDK expression and survival of GBM patients was also explored through survival analysis. Subsequently, we identified MDK-related GBM-specific genes using differential expression analysis. Functional enrichment analyses were performed to reveal their potential biological functions. CCK-8, 5-ethynyl-2′-deoxyuridine, and Matrigel-transwell assays were performed in GBM cell lines in which MDK was knocked out or overexpressed in order assess the effects of MDK on proliferation, migration, and invasion of GBM cells. Western blotting was performed to detect candidate proteins.

Results

Our study showed MDK is a promising diagnostic and prognostic biomarker for GBM because it is highly expressed in the disease and it is associated with poor prognosis. MDK is involved in various cancer-related pathways, such as PI3K-Akt signaling, the cell cycle, and VEGF signaling. A comprehensive transcriptional regulatory network was constructed to show the potential pathways through which MDK may be involved in GBM. In vitro, Overexpression of MDK augmented proliferation, migration, and invasion of GBM cell lines, whereas suppression of MDK led to the opposite effects. Furthermore, our study confirmed that MDK promotes the progression of GBM by activating the PI3K-Akt signaling pathway.

Conclusions

Our present study proposes that MDK promotes GBM by activating the PI3K-Akt signaling pathway, and it describes a potential regulatory network involved.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02212-3.

Proteomic characteristics of PM2.5 -induced differentially expressed proteins in human renal tubular epithelial cells

Human renal epithelial (HK-2) cells were treated with PM_2.5 (50 μg/mL) from Shenzhen and Taiyuan, proteomics and bioinformatics were used to screen the differentially expressed proteins (DEPs). A total of 577 DEPs were screened after HK-2 cells exposed to Shenzhen PM_2.5, of which 426 were up-regulated and 151 were down-regulated. A total of 1250 DEPs were screened in HK-2 cells after exposure to Taiyuan PM_2.5, of which 488 were up-regulated and 185 were down-regulated. The top 10 proteins with the highest number of nodes were screened using the interaction network map of DEPs. HK-2 cells exposed to Shenzhen PM_2.5 contained CYR61, CTGF, and THBS1 proteins, while HK-2 cells exposed to Taiyuan PM_2.5 contained ALB, FN1, and CYR61 proteins. Additionally, PM_2.5 components were detected, PM_2.5 samples from Shenzhen and Taiyuan induced obvious changes in DEPs expression, the difference in DEPs between the two cities was probably associated with the different PM_2.5 components.

Serum midkine as non-invasive biomarker for detection and prognosis of non-small cell lung cancer

Lung cancer continues to be the leading cause for cancer-related deaths in men and women worldwide. Sufficient screening tools enabling early diagnosis are essential to improve patient outcomes. The aim of this study was to evaluate serum midkine (S-MK) both as a diagnostic and prognostic biomarker in non-small cell lung cancer (NSCLC). This single-center analysis included 59 NSCLC patients counting 30 squamous cell cancers and 29 adenocarcinomas. Preoperative S-MK concentration was determined using ELISA. Patients were followed up to five years. S-MK was found to be significantly overexpressed in patients with NSCLC compared to healthy controls (p < 0.001). The discriminative power of S-MK to differentiate NSCLC subjects from controls was fairly high with an area under the receiver operating characteristic curve of 0.83 (p < 0.001). Optimal sensitivity of 92% and reasonable specificity of 68% was reached at a threshold of 416 pg/ml S-MK. Patients with high S-MK concentration showed a significantly shorter overall survival compared to patients with low S-MK expression (p < 0.05). In conclusion, S-MK is overexpressed in patients with NSCLC and serves as an independent prognostic factor for overall survival. S-MK may thus be considered as an additional non-invasive biomarker not only for NSCLC screening but also for outcome prediction.

Midkine Is a Potential Therapeutic Target of Tumorigenesis, Angiogenesis, and Metastasis in Non-Small Cell Lung Cancer

Hypoxia-inducible factors (HIFs) induced by reduced O₂ availability activate the transcription of target genes encoding proteins that play important roles in communication between cancer and stromal cells. Cancer cells were incubated under hypoxic conditions: H1299, A549 (NSCLC); Hep3B, HepG2 (HCC); HCT116, CT26 (Colon cancer); MCF-7, MDAMB231 (Breast cancer); MKN1, MKN5 (Gastric cancer); U87MG, SHSY5Y (Brain cancer); and SKOV3, SNU840 (Ovary cancer). All cells expressed HIF-1α and HIF-2α mRNA and proteins. However, cell proliferation of NSCLC, breast, gastric, and brain cancer cells under hypoxia was more dependent on HIF-1α except for HCC cells where it was more dependent on HIF-2α. Among HIF-1α dependent cells H1299 was the most affected in terms of cell proliferation by HIF-1α knockdown. To examine which cytokines are secreted in NSCLC cells by HIF-1α to communicate with stromal cells, we performed a cytokine-profiling array with H1299. We screened the top 14 cytokines which were dependent on the HIF-1α expression pattern. Among them, midkine (MDK) expression was affected the most in response to HIF-1α. MDK is a heparin-binding growth factor that promotes angiogenesis and carcinogenesis. Indeed, MDK significantly increased HUVEV endothelial cell migration and neo- vascularization in chick chorioallantoic membrane assay (CAM) assay via paracrine signaling. In addition, MDK secreted from NSCLC cells interacted with Notch2 which activated the Notch signaling pathway and induced EMT, upregulated NF-κB, and increased cancer promotion. However, in response to MDK knock down, siRNA or the MDK inhibitor, iMDK treatment not only decreased MDK-induced migration and angiogenesis of endothelial cells but also abrogated the progression and metastasis of NSCLC cells in in vitro and in vivo orthotopic and spontaneous lung metastasis models. Consequently, iMDK treatment significantly increased mice survival rates compared with the control or MDK expression group. MDK plays a very important role in the progression and metastasis of NSCLC cells. Moreover, the MDK targeting strategy provides a potential therapeutic target for the treatment of MDK-expressing lung cancers.

MicroRNA-188 inhibits biological activity of lung cancer stem cells through targeting MDK and mediating the Hippo pathway

New Findings

What is the central question of this study?

The aim was to investigate the function of microRNA‐188 in the biological characteristics of lung cancer stem cells and the molecular mechanisms involved.

What is the main finding and its importance?

This study highlights a new molecular mechanism involving microRNA‐188, MDK and the Hippo signalling pathway that plays a suppressive role in biological activity of lung cancer stem cells. This finding might offer new insights into gene‐based therapy for lung cancer.

Abstract

MicroRNAs (miRNAs) have been implicated in lung cancer and reported as new promising diagnostic and therapeutic tools for cancer control. Here, we investigated the action of microRNA‐188 (miR‐188) in lung cancer stem cells. We first tested miR‐188 expression in clinical samples of lung cancer patients, and a low expression profile of miR‐188 was found. Next, we analysed the role of miR‐188 in lung cancer stem cells with cell growth assays. To verify the in vitro results, we used a xenograft model to validate the capability of miR‐188 in tumorigenesis. Overexpression of miR‐188 reduced viability and metastasis of cancer stem cells. Similar results were reproduced in vivo, where overexpression of miR‐188 retarded tumour growth in mice. We also identified MDK as a target of miR‐188, and overexpression of MDK was found in lung cancer samples. Overexpressed MDK promoted the malignant behaviours of lung cancer stem cells. In addition, the Hippo pathway was found to be inactivated in lung cancer tissues, presenting as increased levels of YAP and TAZ. Suppression of the Hippo pathway also enhanced lung cancer stem cell activity and promoted the growth of xenograft tumours. To sum up, our results reveal that miR‐188 inhibits the malignant behaviours of lung cancer stem cells and the growth of xenograft tumours. This study might offer new insights into gene‐based therapies for cancer.

Identifying critical state of complex diseases by single-sample Kullback-Leibler divergence

Background

Developing effective strategies for signaling the pre-disease state of complex diseases, a state with high susceptibility before the disease onset or deterioration, is urgently needed because such state usually followed by a catastrophic transition into a worse stage of disease. However, it is a challenging task to identify such pre-disease state or tipping point in clinics, where only one single sample is available and thus results in the failure of most statistic approaches.

Methods

In this study, we presented a single-sample-based computational method to detect the early-warning signal of critical transition during the progression of complex diseases. Specifically, given a set of reference samples which were regarded as background, a novel index called single-sample Kullback–Leibler divergence (sKLD), was proposed to explore and quantify the disturbance on the background caused by a case sample. The pre-disease state is then signaled by the significant change of sKLD.

Results

The novel algorithm was developed and applied to both numerical simulation and real datasets, including lung squamous cell carcinoma, lung adenocarcinoma, stomach adenocarcinoma, thyroid carcinoma, colon adenocarcinoma, and acute lung injury. The successful identification of pre-disease states and the corresponding dynamical network biomarkers for all six datasets validated the effectiveness and accuracy of our method.

Conclusions

The proposed method effectively explores and quantifies the disturbance on the background caused by a case sample, and thus characterizes the criticality of a biological system. Our method not only identifies the critical state or tipping point at a single sample level, but also provides the sKLD-signaling markers for further practical application. It is therefore of great potential in personalized pre-disease diagnosis.

MiR-326 targets MDK to regulate the progression of cardiac hypertrophy through blocking JAK/STAT and MAPK signaling pathways

Cardiac hypertrophy is a heart reaction to the increase of cardiac load, with the characteristics of increased expression of cardiac hypertrophy markers, enhanced protein synthesis, and enlarged cell area. However, molecular mechanisms in cardiac hypertrophy are still poorly substantiated. It has been reported that miRNAs can modulate human diseases, among which miR-326 has been reported as a biological regulator in human cancers, but its role in cardiac hypertrophy is rarely explored. This study focused on the exploration of the potential of miR-326 in cardiac hypertrophy. Our data revealed the downregulation of miR-326 in the TAC-induced hypertrophic mice and the Ang II-induced hypertrophic H9c2 cells. Functionally, miR-326 attenuated the effect of Ang II on cardiac hypertrophy in vitro. In addition, miR-326 negatively regulated JAK/STAT and MAPK signaling pathways. Mechanistically, miR-326 targeted and inhibited MDK to induce JAK/STAT and MAPK pathways. Rescue assays certified that miR-326 attenuated cardiac hypertrophy through targeting MDK and inhibiting JAK/STAT and MAPK signaling pathways. In brief, our study unveiled that miR-326 targets MDK to regulate the progression of cardiac hypertrophy through blocking JAK/STAT and MAPK signaling pathways, indicating that targeting miR-326 as a potential approach for cardiac hypertrophy treatment.

Midkine (MDK) growth factor: a key player in cancer progression and a promising therapeutic target

Midkine is a heparin-binding growth factor, originally reported as the product of a retinoic acid-responsive gene during embryogenesis, but currently viewed as a multifaceted factor contributing to both normal tissue homeostasis and disease development. Midkine is abnormally expressed at high levels in various human malignancies and acts as a mediator for the acquisition of critical hallmarks of cancer, including cell growth, survival, metastasis, migration, and angiogenesis. Several studies have investigated the role of midkine as a cancer biomarker for the detection, prognosis, and management of cancer, as well as for monitoring the response to cancer treatment. Moreover, several efforts are also being made to elucidate its underlying mechanisms in therapeutic resistance and immunomodulation within the tumor microenvironment. We hereby summarize the current knowledge on midkine expression and function in cancer development and progression, and highlight its promising potential as a cancer biomarker and as a future therapeutic target in personalized cancer medicine.

Identification of target gene and prognostic evaluation for lung adenocarcinoma using gene expression meta-analysis, network analysis and neural network algorithms

BACKGROUND

Lung adenocarcinoma (LUAD) is a heterogeneous disease with poor survival in the advanced stage and a high incidence rate in the world. Novel drug targets are urgently required to improve patient treatment. Therefore, we aimed to identify therapeutic targets for LUAD based on protein-protein and protein-drug interaction network analysis with neural network algorithms using mRNA expression profiles.

RESULTS

A comprehensive meta-analysis of selective non-small cell lung cancer (NSCLC) mRNA expression profile datasets from Gene Expression Omnibus were used to identify potential biomarkers and the molecular mechanisms related to the prognosis of NSCLC patients. Using the Network Analyst tool, based on combined effect size (ES) methods, we recognized 6566 differentially expressed genes (DEGs), which included 3036 downregulated and 3530 upregulated genes linked to NSCLC patient survival. ClueGO, a Cytoscape plugin, was exploited to complete the function and pathway enrichment analysis, which disclosed "regulated exocytosis", "purine nucleotide binding", "pathways in cancer", and "cell cycle" between exceptionally supplemented terms. Enrichr, a web tool examination, demonstrated "early growth response protein 1 (EGR-1)", "hepatocyte nuclear factor 4α (HNF4A)", "mitogen-activated protein kinase 14 (MAP3K14)", and "cyclin-dependent kinase 1 (CDK1)" to be among the most prevalent TFs and kinases associated with NSCLC. Our meta-analysis identified that MAPK1 and aurora kinase (AURKA) are the most obvious class of hub nodes. Furthermore, protein-drug interaction network and neural network algorithms identified candidate drugs such as phosphothreonine and 4-(4-methylpiperazin-1-yl)-n-[5-(2-thienylacetyl)-1,5-dihydropyrrolo[3,4-c]pyrazol-3-yl] benzamide and for the targets MAPK1 and AURKA, respectively.

CONCLUSION

Our study has identified novel candidate biomarkers, pathways, transcription factors (TFs), and kinases associated with NSCLC prognosis, as well as drug candidates, which may assist treatment strategy for NSCLC patients.

Exosomal miR-9 inhibits angiogenesis by targeting MDK and regulating PDK/AKT pathway in nasopharyngeal carcinoma

Background

Exosomes are small vesicles containing a wide range of functional proteins, mRNA and miRNA. Exosomal miRNAs from cancer cells play crucial roles in mediating cell-cell communication and tumor-microenvironment cross talk, specifically in enabling metastasis and promoting angiogenesis. We focused on miR-9 that was identified as a tumor suppressor previously in nasopharyngeal carcinoma (NPC) tumorigenesis.

Methods

Differential centrifugation, transmission electron microscopy and nanoparticle tracking analysis were used to isolate and identify exosomes. Quantitative PCR and western blotting analysis were used to detect miR-9, pri-miR-9, CD63, TSG101, MDK, P70S6K P-Ser424 and PDK1 P-Ser241 expression. Laser confocal microscopy was used to trace exosomal miR-9 secreted by NPC cells into HUVECs. The effect of exosomal miR-9 on cell migration and tube formation of HUVECs in vivo and vitro was assessed by using migration assay, tube formation assay and matrigel plug assay, respectively. Bioinformatics analysis and luciferase reporter assay were utilized to confirm the binding of exosomal miR-9 to the 3′untranslated region (3′-UTR) of MDK, while Phosphorylation Array was performed to identify AKT Pathway in HUVECs treated with exosomal miR-9. Furthermore, Immunohistochemistry (IHC) and in situ hybridization (ISH) was used to detected miR-9, CD31 and MDK expression in human NPC tumor samples.

Results

NPC cells transfected with miR-9-overexpressing lentivirus, released miR-9 in exosomes. Exosomal miR-9 directly suppressed its target gene - MDK in endothelial cells. Mechanistic analyses revealed that exosomal miR-9 from NPC cells inhibited endothelial tube formation and migration by targeting MDK and regulating PDK/AKT signaling pathway. Additionally, the level of MDK was upregulated in NPC tumor samples and was positively correlated with microvessel density. Notably, the level of exosomal miR-9 was positively correlated with overall survival, and MDK overexpression was positively associated with poor prognosis in NPC patients, suggesting the clinical relevance and prognostic value of exosomal miR-9 and MDK.

Conclusions

Taken together, our data identify an extracellular anti-angiogenic role for tumor-derived, exosome-associated miR-9 in NPC tumorigenesis and prompt further investigation into exosome-based therapies for cancer treatment.

Electronic supplementary material

The online version of this article (10.1186/s13046-018-0814-3) contains supplementary material, which is available to authorized users.

Positive expression of Midkine predicts early recurrence and poor prognosis of initially resectable combined hepatocellular cholangiocarcinoma

Background

Post-surgical prognosis is usually poor for combined hepatocellular cholangiocarcinoma (CHCC-CC), a rare primary liver cancer. Although midkine (MK) is a prognostic biomarker for several known cancers, it is not known whether it can be used as such in resectable CHCC-CC. This study examined whether MK expression can predict recurrence and survival in patients with resectable CHCC-CC.

Methods

We retrospectively enrolled 52 patients with resectable CHCC-CC who had received curative hepatic resections. MK expression was assessed in post-surgical immunohistochemical studies of specimens in paraffin blocks. Clinical outcomes were analyzed from medical records.

Results

Two-year disease-free and three-year overall survival rates were 42.1% and 44.6%. MK was expressed in 30 patients. Univariate analysis showed patients positively expressing MK had a significantly poorer 2-year disease free and three-year overall survival. Multivariate analysis found positive MK expression independently predicted recurrence.

Conclusions

Positive expression of MK predicts poor prognosis in patients with resectable CHCC-CC.

Midkine is a serum and urinary biomarker for the detection and prognosis of non-small cell lung cancer

Midkine, a heparin-binding growth factor, has been identified as a promising cancer biomarker. In non-small cell lung cancer (NSCLC), the serum and urine midkine levels have not been intensively investigated. The aim of the present study was to investigate the diagnostic and prognostic potential of serum and urine midkine levels in patients with NSCLC. The serum midkine levels were measured in 153 patients with NSCLC, 23 patients with benign pulmonary disease and 95 healthy controls using ELISA. Urine midkine levels were examined in 20 controls and 45 patients with NSCLC. Midkine expression in tumor tissues from 72 patients with NSCLC who underwent definitive surgical resection without any pre-operative treatments was examined by immunohistochemistry. Serum levels were significantly higher in patients with NSCLC than in healthy controls (657.36±496.58 pg/ml vs. 194.49±122.57 pg/ml, P<0.001). As shown in the ROC curve analysis, the sensitivity and specificity of the cut-off serum midkine concentration of 400 pg/ml for predicting the presence of NSCLC were 71.2% and 88.1%, respectively. Positive correlations between the serum midkine levels and immunohistochemistry staining scores (r=0.315, P=0.007) and between the serum midkine levels and urine midkine levels (r=0.636, P<0.001) were observed using Spearman's bivariate correlations. The serum midkine concentration was identified as an independent prognostic factor by multivariate analysis, and its overexpression yielded a relative risk of death of 2.072 (0.01<P<0.05, 95%CI: 1.104-3.890). Thus, the serum and urine midkine levels may be useful, minimally invasive biomarkers for detecting and predicting the prognosis of NSCLC.

Integration of zebrafish fin regeneration genes with expression data of human tumors in silico uncovers potential novel melanoma markers

Tissue regeneration requires expression of a large, unknown number of genes to initiate and maintain cellular processes such as proliferation, extracellular matrix synthesis, differentiation and migration. A unique model to simulate this process in a controlled manner is the re-growth of the caudal fin of zebrafish after amputation. Within this tissue stem cells differentiate into fibroblasts, epithelial and endothelial cells as well as melanocytes. Many genes implicated in the regeneration process are deregulated in cancer. We therefore undertook a systematic gene expression study to identify genes upregulated during the re-growth of caudal fin tissue. By applying a high stringency cut-off value of 4-fold change, we identified 54 annotated genes significantly overexpressed in regenerating blastema. Further bioinformatics data mining studies showed that 22 out of the 54 regeneration genes where overexpressed in melanoma compared to normal skin or other cancers. Whereas the role of TNC (tenascin C) and FN1 (fibronectin 1) in melanoma development is well documented, implication of MARCKS, RCN3, BAMBI, PEA3/ETV4 and the FK506 family members FKBP7, FKBP10 and FKBP11 in melanoma progression is unclear. Corresponding proteins were detected in melanoma tissue but not in normal skin. High expression of FKBP7, DPYSL5 and MDK was significantly associated with poor survival. We discuss a potential role of these novel melanoma genes, which have promising potential as new therapeutic targets or diagnostic markers.

Prognostic value of Midkine expression in patients with solid tumors: a systematic review and meta-analysis

Background

Accumulated studies have shown the important role of Midkine (MDK) protein in various solid tumors and indicated its correlation with patients' survival. This meta-analysis was performed to further explore the prognostic value of MDK expression in solid tumors.

Materials and Methods

We collected the literatures through searching PubMed, Embase and the Cochrane Library (last up to April 10, 2017) to assess the effect of MDK on survival in solid tumor patients. The STATA 12.0 software was used for the meta-analysis. Fixed-effects models or random-effects models were used to estimate the pooled hazard ratios (HRs) for overall survival (OS).

Results

A total of 2097 patients from 17 observational studies were summarized. High expression of MDK was notably associated with worse OS in solid tumor patients. (pooled HR = 1.96; 95% CI = 1.67-2.31). The subgroup analysis of tumor type demonstrated negative impact of elevated MDK on OS in most solid tumor patients (P < 0.05), while MDK had no relevance with OS in the patients with OSCC (pooled HR = 1.68; 95% CI = 0.84-3.36; P = 0.145) or HNSCC (pooled HR = 1.56; 95% CI = 0.96-2.51; P = 0.075).

Conclusions

The present meta-analysis clarifies that MDK is a potential prognostic biomarker in solid tumor patients. Future large-scale prospective clinical trials are needed to determine the prognostic value of MDK in solid tumor patients.

The role of MCM5 expression in cervical cancer: Correlation with progression and prognosis

Minichromosome maintenance protein 5 (MCM5) has been suggested overexpressed in cervical cancer, but the clinical value and biological function of MCM5 in cervical cancer is still unknown. In our study, MCM5 mRNA and protein were significantly overexpressed in cervical cancer tissues and cell lines compared with normal cervical tissues and cell lines, and were obviously increased in cervical adenocarcinoma tissues and cell lines in comparison to cervical squamous cell carcinoma tissues and cell lines. In cervical adenocarcinoma patients, we firstly found that MCM5 expression was closely correlated with clinical stage, lymph node metastasis, distant metastasis and histological grade. Univariate and multivariate analysis showed MCM5 high-expression was an independent unfavorable prognostic factor. In conclusion, MCM5 is associated with the malignant status and poor prognosis in cervical adenocarcinoma patients, and modulates cervical adenocarcinoma cells proliferation.

Construction of a 26‑feature gene support vector machine classifier for smoking and non‑smoking lung adenocarcinoma sample classification

The present study aimed to identify the feature genes associated with smoking in lung adenocarcinoma (LAC) samples and explore the underlying mechanism. Three gene expression datasets of LAC samples were downloaded from the Gene Expression Omnibus database through pre-set criteria and the expression data were processed using meta-analysis. Differentially expressed genes (DEGs) between LAC samples of smokers and non-smokers were identified using limma package in R. The classification accuracy of selected DEGs were visualized using hierarchical clustering analysis in R language. A protein-protein interaction (PPI) network was constructed using gene interaction data from the Human Protein Reference Database for the DEGs. Betweenness centrality was calculated for each node in the network and genes with the greatest BC values were utilized for the construction of the support vector machine (SVM) classifier. The dataset GSE43458 was used as the training dataset for the construction and the other datasets (GSE12667 and GSE10072) were used as the validation datasets. The classification accuracy of the classifier was tested using sensitivity, specificity, positive predictive value, negative predictive value and area under curve parameters with the pROC package in R language. The feature genes in the SVM classifier were subjected to pathway enrichment analysis using Fisher's exact test. A total of 347 genes were identified to be differentially expressed between samples of smokers and non-smokers. The PPI network of DEGs were comprised of 202 nodes and 300 edges. An SVM classifier comprised of 26 feature genes was constructed to distinguish between different LAC samples, with prediction accuracies for the GSE43458, GSE12667 and GSE10072 datasets of 100, 100 and 94.83%, respectively. Furthermore, the 26 feature genes that were significantly enriched in 9 overrepresented biological pathways, including extracellular matrix-receptor interaction, proteoglycans in cancer, cell adhesion molecules, p53 signaling pathway, microRNAs in cancer and apoptosis, were identified to be smoking-related genes in LAC. In conclusion, an SVM classifier with a high prediction accuracy for smoking and non-smoking samples was obtained. The genes in the classifier may likely be the potential feature genes associated with the development of patients with LAC who smoke.

Neighbours of cancer-related proteins have key influence on pathogenesis and could increase the drug target space for anticancer therapies

Even targeted chemotherapies against solid cancers show a moderate success increasing the need to novel targeting strategies. To address this problem, we designed a systems-level approach investigating the neighbourhood of mutated or differentially expressed cancer-related proteins in four major solid cancers (colon, breast, liver and lung). Using signalling and protein–protein interaction network resources integrated with mutational and expression datasets, we analysed the properties of the direct and indirect interactors (first and second neighbours) of cancer-related proteins, not found previously related to the given cancer type. We found that first neighbours have at least as high degree, betweenness centrality and clustering coefficient as cancer-related proteins themselves, indicating a previously unknown central network position. We identified a complementary strategy for mutated and differentially expressed proteins, where the affect of differentially expressed proteins having smaller network centrality is compensated with high centrality first neighbours. These first neighbours can be considered as key, so far hidden, components in cancer rewiring, with similar importance as mutated proteins. These observations strikingly suggest targeting first neighbours as a novel strategy for disrupting cancer-specific networks. Remarkably, our survey revealed 223 marketed drugs already targeting first neighbour proteins but applied mostly outside oncology, providing a potential list for drug repurposing against solid cancers. For the very central first neighbours, whose direct targeting would cause several side effects, we suggest a cancer-mimicking strategy by targeting their interactors (second neighbours of cancer-related proteins, having a central protein affecting position, similarly to the cancer-related proteins). Hence, we propose to include first neighbours to network medicine based approaches for (but not limited to) anticancer therapies.

Cancer is considered a systems disease in which the interactors of cancer-related proteins have a key role, also as targets to fight cancer. New therapeutic approaches are needed to improve success rates and to identify suitable proteins as novel, alternative drug targets. We designed a computational approach, combining mutation and differential expression data with network information, to analyse the interactions of cancer-related proteins in colon, breast, liver and lung cancer. We found that first (direct) neighbours, not linked previously to the given cancer type, are similarly important as mutated proteins known to be involved in cancer development. We found 223 drugs already in the clinic targeting these proteins but not yet used against cancer as their oncology relevance was hidden so far. Our observations open up new strategies for target selection and anti-cancer drug discovery.