Differential expression of bone morphogenetic protein 5 in human lung squamous cell carcinoma and adenocarcinoma

Identifying General Tumor and Specific Lung Cancer Biomarkers by Transcriptomic Analysis

The bioinformatic pipeline previously developed in our research laboratory is used to identify potential general and specific deregulated tumor genes and transcription factors related to the establishment and progression of tumoral diseases, now comparing lung cancer with other two types of cancer. Twenty microarray datasets were selected and analyzed separately to identify hub differentiated expressed genes and compared to identify all the deregulated genes and transcription factors in common between the three types of cancer and those unique to lung cancer. The winning DEGs analysis allowed to identify an important number of TFs deregulated in the majority of microarray datasets, which can become key biomarkers of general tumors and specific to lung cancer. A coexpression network was constructed for every dataset with all deregulated genes associated with lung cancer, according to DAVID’s tool enrichment analysis, and transcription factors capable of regulating them, according to oPOSSUM´s tool. Several genes and transcription factors are coexpressed in the networks, suggesting that they could be related to the establishment or progression of the tumoral pathology in any tissue and specifically in the lung. The comparison of the coexpression networks of lung cancer and other types of cancer allowed the identification of common connectivity patterns with deregulated genes and transcription factors correlated to important tumoral processes and signaling pathways that have not been studied yet to experimentally validate their role in lung cancer. The Kaplan–Meier estimator determined the association of thirteen deregulated top winning transcription factors with the survival of lung cancer patients. The coregulatory analysis identified two top winning transcription factors networks related to the regulatory control of gene expression in lung and breast cancer. Our transcriptomic analysis suggests that cancer has an important coregulatory network of transcription factors related to the acquisition of the hallmarks of cancer. Moreover, lung cancer has a group of genes and transcription factors unique to pulmonary tissue that are coexpressed during tumorigenesis and must be studied experimentally to fully understand their role in the pathogenesis within its very complex transcriptomic scenario. Therefore, the downstream bioinformatic analysis developed was able to identify a coregulatory metafirm of cancer in general and specific to lung cancer taking into account the great heterogeneity of the tumoral process at cellular and population levels.

Identification of Novel Lung Cancer Driver Genes Connecting Different Omics Levels With a Heat Diffusion Algorithm

Cancer driver gene is a type of gene with abnormal alterations that initiate or promote tumorigenesis. Driver genes can be used to reveal the fundamental pathological mechanisms of tumorigenesis. These genes may have pathological changes at different omics levels. Thus, identifying cancer driver genes involving two or more omics levels is essential. In this study, a computational investigation was conducted on lung cancer driver genes. Four omics levels, namely, epigenomics, genomics, transcriptomics, and post-transcriptomics, were involved. From the driver genes at each level, the Laplacian heat diffusion algorithm was executed on a protein–protein interaction network for discovering latent driver genes at this level. A following screen procedure was performed to extract essential driver genes, which contained three tests: permutation, association, and function tests, which can exclude false-positive genes and screen essential ones. Finally, the intersection operation was performed to obtain novel driver genes involving two omic levels. The analyses on obtained genes indicated that they were associated with fundamental pathological mechanisms of lung cancer at two corresponding omics levels.

Overexpression of lncRNA A2M-AS1 inhibits cell growth and aggressiveness via regulating the miR-587/bone morphogenetic protein 3 axis in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is a malignant tumor that occurs in the lungs. Numerous reports have substantiated the participation of long non-coding RNAs (lncRNAs) in the tumorigenesis of LUAD. Previously, lncRNA alpha-2-macroglobulin antisense RNA 1 (A2M-AS1) was confirmed to be an important regulator in the biological processes of LUAD and dysregulation of A2M-AS1 was associated with non-small cell lung cancer (NSCLC) progression. However, the precise mechanism of A2M-AS1 in LUAD has not been elucidated. Therefore, our study was designed to investigate the detailed molecular mechanism of A2M-AS1 in LUAD. Herein, the expression of lncRNA A2M-AS1, microRNA (miRNA) miR-587, and bone morphogenetic protein 3 (BMP3) in LUAD cell lines and tissues were detected by real-time quantitative polymerase chain reaction (RT-qPCR) and western blotting. The viability, proliferation, migration and invasion of LUAD cells were tested by cell counting kit-8 (CCK-8), colony formation and Transwell assays. In vivo tumor growth was investigated by xenograft animal experiment. Interactions among A2M-AS1, miR-587 and BMP3 were measured by RNA pulldown and luciferase reporter assays. In this study, A2M-AS1 was downregulated in LUAD tissues and cells and related to poor prognosis in LUAD patients. A2M-AS1 overexpression suppressed LUAD cell proliferation, migration and invasion in vitro and inhibited tumor growth in vivo. Mechanistically, A2M-AS1 directly bound with miR-587 to promote BMP3 expression in LUAD cells. Low expression of BMP3 was found in LUAD tissues and cells and was closely correlated with poor prognosis in LUAD patients. BMP3 deficiency reserved the inhibitory influence of A2M-AS1 overexpression on LUAD cell behaviors. Overall, A2M-AS1 inhibits cell growth and aggressiveness via regulating the miR-587/BMP3 axis in LUAD.

Upregulated bone morphogenetic protein 5 enhances proliferation and epithelial-mesenchymal transition process in benign prostatic hyperplasia via BMP/Smad signaling pathway

BACKGROUND

Benign prostatic hyperplasia (BPH) is one of the most common illnesses in aging men. Recent studies found that bone morphogenetic protein 5 (BMP5) is upregulated in BPH tissues, however, the role of BMP5 in the development of BPH has not been examined. The current study aims to elucidate the potential roles of BMP5 and related signaling pathways in BPH.

METHODS

Human prostate cell lines (BPH-1, WPMY-1) and human/rat hyperplastic prostate tissues were utilized. Western blot, quantitative real-time polymerase chain reaction, immunofluorescent staining, and immunohistochemical staining were performed. BMP5-silenced and -overexpressed cell models were generated and then cell cycle progression, apoptosis, and proliferation were determined. The epithelial-mesenchymal transition (EMT) was also quantitated. And rescue experiments by BMP/Smad signaling pathway agonist or antagonist were accomplished. Moreover, BPH-related tissue microarray analysis was performed and associations between clinical parameters and expression of BMP5 were analyzed.

RESULTS

Our study demonstrated that BMP5 was upregulated in human and rat hyperplastic tissues and localized both in the epithelial and stromal compartments of the prostate tissues. E-cadherin was downregulated in hyperplastic tissues, while N-cadherin and vimentin were upregulated. Overexpression of BMP5 enhanced cell proliferation and the EMT process via phosphorylation of Smad1/5/8, while knockdown of BMP5 induced cell cycle arrest at G0/G1 phase and blocked the EMT process. Moreover, a BMP/Smad signaling pathway agonist and antagonist reversed the effects of BMP5 silencing and overexpression, respectively. In addition, BMP5 expression positively correlated with prostate volume and total prostate-specific antigen.

CONCLUSION

Our novel data suggest that BMP5 modulated cell proliferation and the EMT process through the BMP/Smad signaling pathway which could contribute to the development of BPH. However, further studies are required to determine the exact mechanism. Our study also indicated that BMP/Smad signaling may be rediscovered as a promising new therapeutic target for the treatment of BPH.

The Prognostic Value of Bone Morphogenetic Proteins and Their Receptors in Lung Adenocarcinoma

Background

Bone morphogenetic proteins (BMPs) regulate tumor progression via binding to their receptors (BMPRs). However, the expression and clinical significance of BMPs/BMPRs in lung adenocarcinoma remain unclear due to a lack of systematic studies.

Methods

This study screened differentially expressed BMPs/BMPRs (deBMPs/BMPRs) in a training dataset combining TCGA-LUAD and GTEx-LUNG and verified them in four GEO datasets. Their prognostic value was evaluated via univariate and multivariate Cox regression analyses. LASSO was performed to construct an initial risk model. Subsequently, after weighted gene co-expression network analysis (WGCNA), differential expression analysis, and univariate Cox regression analysis, hub genes co-expressed with differentially expressed BMPs/BMPRs were filtered out to improve the risk model and explore potential mechanisms. The improved risk model was re-established via LASSO combining hub genes with differentially expressed BMPs/BMPRs as the core. In the testing cohort including 93 lung adenocarcinoma patients, immunohistochemistry (IHC) was performed to verify BMP5 protein expression and its association with prognosis.

Results

BMP2, BMP5, BMP6, GDF10, and ACVRL1 were verified as downregulated in lung adenocarcinoma. Survival analysis identified BMP5 as an independent protective prognostic factor. We also found that BMP5 was significantly correlated with EGFR expression and mutations, suggesting that BMP5 may play a role in targeted therapy. The initial risk model containing only BMP5 showed a significant correlation (HR: 1.71, 95% CI: 1.28−2.28, p: 3e-04) but low prognostic accuracy (AUC of 1-year survival: 0.6, 3-year survival: 0.6, 5-year survival: 0.63). Seventy-nine hub genes co-expressed with BMP5 were identified, and their functions were enriched in cell migration and tumor metastasis. The re-established risk model showed greater prognostic correlation (HR: 2.58, 95% CI: 1.92–3.46, p: 0) and value (AUC of 1-year survival: 0.72, 3-year survival: 0.69, and 5-year survival: 0.68). IHC results revealed that BMP5 protein was also downregulated in lung adenocarcinoma and higher expression was markedly associated with better prognosis (HR: 0.44, 95% CI: 0.23–0.85, p: 0.0145).

Conclusion

BMP5 is a potential crucial target for lung adenocarcinoma treatment based on significant differential expression and superior prognostic value.

Abnormal Expression and Prognostic Significance of Bone Morphogenetic Proteins and Their Receptors in Lung Adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is one of the most life-threatening malignancies. The crucial role of bone morphogenetic protein (BMP)/BMP receptors reveals the significance of exploring BMP protein-related prognostic predictors in LUAD.

Methods

The mRNA expression of BMPs/BMP receptors was investigated in LUAD and normal lung tissues. Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes pathway analyses were performed, and the prognostic values were assessed by Kaplan-Meier Plotter. Univariate and multivariate Cox regression analyses were executed to ascertain the correlation between overall survival (OS) and the mRNA expression of BMPs/BMP receptors. The receiver operating characteristic (ROC) curves were implemented to evaluate the predictive power of the prognostic model. Then, the prognostic model was validated in the GEO cohort. Furthermore, a nomogram comprising the prognostic model was established.

Results

The mRNA expression of BMP2/5/6/R2, ACVRL1, and TGFBR2/3 was lower in LUAD tissues than in normal lung tissues. High expression of BMP2/4/5/R1A/R2, ACVR1/2A/L1, and TGFBR1/3 was associated with better OS, while BMP7 and ACVR1C/2B were associated with poorer OS. Three genes (BMP5, BMP7, and ACVR2A) were screened by univariate and multivariate Cox regression analyses to develop the prognostic model in TCGA. Significantly better survival was observed in LUAD patients with a low-risk score than those with a high-risk score. The ROC curves confirmed the good performance of the prognostic model, then, the prognostic model was validated in the GSE31210 dataset. A nomogram was constructed (AUCs>0.7). And hub genes were further evaluated, including gene set enrichment analysis and immune cell infiltration.

Conclusions

BMP5, BMP7, and ACVR2A are potential therapeutic targets in LUAD. The three-gene prognostic model and the nomogram are reliable tools for predicting the OS of LUAD patients.

Use of four genes in exosomes as biomarkers for the identification of lung adenocarcinoma and lung squamous cell carcinoma

The determination of biomarkers in the blood specific for lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) is crucial for the selection of effective treatment strategies and the prediction of prognosis. The purpose of the present study was to analyze the differentially expressed genes (DEGs) in LUSC and LUAD from The Cancer Genome Atlas (TCGA) database. In order to identify the potential biomarkers for non-small cell lung cancer (NSCLC) for clinical diagnosis, bioinformatics was used to analyze the DEGs of two subtypes of NSCLC, LUAD and LUSC. Exosomes were isolated from the serum of patients with LUAD or LUSC and identified using transmission electron microscopy, nanoparticle tracking analysis and western blot analysis. A total of four differential exosomal mRNAs were selected for validation with serum samples from 70 patients with NSCLC via reverse transcription-quantitative polymerase chain reaction. Receiver operating characteristic curves were established to evaluate the clinical diagnostic value of four DEGs for patients with LUAD and LUSC. The analysis based on TCGA data revealed the DEGs in LUSC and LUAD: A total of 1,619 genes were differentially expressed in patients with LUSC and LUAD. DEGs analyzed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses revealed that inflammation-related signaling pathways, such as complement pathways, and multiple autoimmune diseases, such as systemic lupus erythematosus and asthma were mainly enriched in LUAD. The cell cycle, Hippo signaling pathway, Rap1 signaling pathway and Wnt signaling pathway were the main signaling pathways enriched in LUSC. The combination of tumor protein P63 (TP63), keratin 5 (KRT5), CEA cell adhesion molecule 6 (CEACAM6) and surfactant protein B (SFTPB) improved the specificity and sensitivity in the diagnosis of different lung cancer subtypes. Exosomal TP63, KRT5, CEACAM6 and SFTPB mRNAs can thus be used as biomarkers to differentiate between LUSC and LUAD, and may provide a novel strategy for their differential diagnosis and treatment.

Learning from BMPs and their biophysical extracellular matrix microenvironment for biomaterial design

It is nowadays well-accepted that the extracellular matrix (ECM) is not a simple reservoir for growth factors but is an organization center of their biological activity. In this review, we focus on the ability of the ECM to regulate the biological activity of BMPs. In particular, we survey the role of the ECM components, notably the glycosaminoglycans and fibrillary ECM proteins, which can be promoters or repressors of the biological activities mediated by the BMPs. We examine how a process called mechano-transduction induced by the ECM can affect BMP signaling, including BMP internalization by the cells. We also focus on the spatio-temporal regulation of the BMPs, including their release from the ECM, which enables to modulate their spatial localization as well as their local concentration. We highlight how biomaterials can recapitulate some aspects of the BMPs/ECM interactions and help to answer fundamental questions to reveal previously unknown molecular mechanisms. Finally, the design of new biomaterials inspired by the ECM to better present BMPs is discussed, and their use for a more efficient bone regeneration in vivo is also highlighted.

Utilizing Experimental Mouse Model to Identify Effectors of Hepatocellular Carcinoma Induced by HBx Antigen

Hepatocellular carcinoma (HCC) is among the ten most commonly diagnosed cancers and the fourth leading cause of cancer-related death. Patients with hepatitis B virus (HBV) infection are prone to developing chronic liver diseases (i.e., fibrosis and cirrhosis), and the HBV X antigen plays an important role in the development of HCC. The difficulty in detecting HCC at the early stages is one of the main reasons that the death rate approximates the incidence rate. The regulators controlling the downstream liver protein expression from HBV infection are unclear. Mass spectrometric techniques and customized programs were used to identify differentially expressed proteins which may be involved in the development of liver fibrosis and HCC progression in hepatitis B virus X protein transgenic mice (HBx mice). FSTL1, CTSB, and TGF-β enhanced the signaling pathway proteins during the pathogenesis of HBx. Missing proteins can be essential in cell growth, differentiation, apoptosis, migration, metastasis or angiogenesis. We found that LHX2, BMP-5 and GDF11 had complex interactions with other missing proteins and BMP-5 had both tumor suppressing and tumorigenic roles. BMP-5 may be involved in fibrosis and tumorigenic processes in the liver. These results provide us an understanding of the mechanism of HBx-induced disorders, and may serve as molecular targets for liver treatment.

A Multi-Omics Analysis of Bone Morphogenetic Protein 5 (BMP5) mRNA Expression and Clinical Prognostic Outcomes in Different Cancers Using Bioinformatics Approaches

Cumulative studies have provided controversial evidence for the prognostic values of bone morphogenetic protein 5 (BMP5) in different types of cancers such as colon, breast, lung, bladder, and ovarian cancer. To address the inconsistent correlation of BMP5 expression with patient survival and molecular function of BMP5 in relation to cancer progression, we performed a systematic study to determine whether BMP5 could be used as a prognostic marker in human cancers. BMP5 expression and prognostic values were assessed using different bioinformatics tools such as ONCOMINE, GENT, TCGA, GEPIA, UALCAN, PrognoScan, PROGgene V2 server, and Kaplan-Meier Plotter. In addition, we used cBioPortal database for the identification and analysis of BMP5 mutations, copy number alterations, altered expression, and protein-protein interaction (PPI). We found that BMP5 is frequently down-regulated in our queried cancer types. Use of prognostic analysis showed negative association of BMP5 down-regulation with four types of cancer except for ovarian cancer. The highest mutation was found in the R321*/Q amino acid of BMP5 corresponding to colorectal and breast cancer whereas the alteration frequency was higher in lung squamous carcinoma datasets (>4%). In PPI analysis, we found 31 protein partners of BMP5, among which 11 showed significant co-expression (p-value < 0.001, log odds ratio > 1). Pathway analysis of differentially co-expressed genes with BMP5 in breast, lung, colon, bladder and ovarian cancers revealed the BMP5-correlated pathways. Collectively, this data-driven study demonstrates the correlation of BMP5 expression with patient survival and identifies the involvement of BMP5 pathways that may serve as targets of a novel biomarker for various types of cancers in human.

An Immune-Related Signature Predicts Survival in Patients With Lung Adenocarcinoma

We investigated the local immune status and its prognostic value in lung adenocarcinoma. In total, 513 lung adenocarcinoma samples from TCGA and ImmPort databases were collected and analyzed. The R package coxph was employed to mine immune-related genes that were significant prognostic indicators using both univariate and multivariate analyses. The R software package glmnet was then used for Lasso Cox regression analysis, and a prognosis prediction model was constructed for lung adenocarcinoma; clusterProfiler was selected for functional gene annotations and KEGG enrichment analysis. Finally, correlations between the RiskScore and clinical features or signaling pathways were established. Sixty-four immune-related genes remarkably correlated with patient prognosis and were further applied. Samples were hierarchically clustered into two subgroups. Accordingly, the LASSO regression algorithm was employed to screen the 14 most representative immune-related genes (PSMD11, PPIA, MIF, BMP5, DKK1, PDGFB, ANGPTL4, IL1R2, THRB, LTBR, TNFRSF1, TNFRSF17, IL20RB, and MC1R) with respect to patient prognosis. Then, the prognosis prediction model for lung adenocarcinoma patients (namely, the RiskScore equation) was constructed, and the training set samples were incorporated to evaluate the efficiency of this model to predict and classify patient prognosis. Subsequently, based on functional annotations and KEGG pathway analysis, the 14 immune-related genes were mainly enriched in pathways closely associated with lung adenocarcinoma and its immune microenvironment, such as cytokine–cytokine receptor interaction and human T-cell leukemia virus 1 infection. Furthermore, correlations between the RiskScore and clinical features of the training set samples and signaling pathways (such as p53, cell cycle, and DNA repair) were also demonstrated. Finally, the test set sample data were employed for independent testing and verifying the model. We established a prognostic prediction RiskScore model based on the expression profiles of 14 immune-related genes, which shows high prediction accuracy and stability in identifying immune features. This could provide clinical guidance for the diagnosis and prognosis of different immunophenotypes, and suggest multiple targets for precise advanced lung adenocarcinoma therapy based on subtype-specific immune molecules.

Analysis of the long non-coding RNA LINC01614 in non-small cell lung cancer

The aim of this study was toexplore the long non-coding RNA (lncRNA) expression pattern of non-small cell lung cancer (NSCLC) on a genome-wide scale and investigate their potential biological function in NSCLC.LncRNAs were investigated in 6 pairs of NSCLC and matched adjacent non-tumor lung tissues (NTL) by microarray. A validation cohort was obtained from The Cancer Genome Atlas (TCGA) database and the effect of LINC01614 on diagnosis and prognosis in NSCLC was analyzed. Gene set enrichment analysis (GSEA) was used to predict the potential molecular mechanism of LINC01614, one identified lncRNA.A total of 1392 differentially expressed lncRNAs were identified. LINC01614 was the most aberrantly expressed lncRNA in NSCLC compared with NTL. We confirmed the significantly upregulated LINC01614 in NSCLC patients from TCGA database. Furthermore, in TCGA database, LINC01614 was significantly upregulated in both adenocarcinoma and squamous cell carcinoma. And high expression of LINC01614 indicated poor overall survival of NSCLC patients. A sensitivity of 93% was calculated conditional on a high specificity of 95% for the discrimination of NSCLC tissues from normal tissues. Furthermore, the expression levels of LINC01614 were associated with the stage of tumor, but had no relationship with age and sex. Additionally, GSEA found that LINC01614 might be involved in TGF-β-, P53-, IGF-IR-mediated, Wnt and RTK/Ras/MAPK signaling pathways.lncRNAs may play key roles in the development of NSCLC. LINC01614 is the most aberrantly expressed lncRNA in NSCLC tissues in our experiment and is also significantly differentially expressed in NSCLC patients from TCGA database. LINC01614 could be a prognostic indicator and has the potential to be a diagnostic biomarker of NSCLC.

Non-small-cell lung cancer pathological subtype-related gene selection and bioinformatics analysis based on gene expression profiles

Lung cancer is one of the most common malignant diseases and a major threat to public health on a global scale. Non-small-cell lung cancer (NSCLC) has a higher degree of malignancy and a lower 5-year survival rate compared with that of small-cell lung cancer. NSCLC may be mainly divided into two pathological subtypes, adenocarcinoma and squamous cell carcinoma. The aim of the present study was to identify disease genes based on the gene expression profile and the shortest path analysis of weighted functional protein association networks with the existing protein-protein interaction data from the Search Tool for the Retrieval of Interacting Genes. The gene expression profile (GSE10245) was downloaded from the National Center for Biotechnology Information Gene Expression Omnibus database, including 40 lung adenocarcinoma and 18 lung squamous cell carcinoma tissues. A total of 8 disease genes were identified using Naïve Bayesian Classifier based on the Maximum Relevance Minimum Redundancy feature selection method following preprocessing. An additional 21 candidate genes were selected using the shortest path analysis with Dijkstra's algorithm. The AURKA and SLC7A2 genes were selected three and two times in the shortest path analysis, respectively. All those genes participate in a number of important pathways, such as oocyte meiosis, cell cycle and cancer pathways with Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. The present findings may provide novel insights into the pathogenesis of NSCLC and enable the development of novel therapeutic strategies. However, further investigation is required to confirm these findings.

Identification of lung adenocarcinoma specific dysregulated genes with diagnostic and prognostic value across 27 TCGA cancer types

As the most common histologic subtype of lung cancer, lung adenocarcinoma (LUAD) contributes to a majority of cancer-related deaths worldwide annually. In order to find specific biomarkers of LUAD that are able to distinguish LUAD from other types of cancer so as to improve the early diagnostic and prognostic power in LUAD, we analyzed 10098 tumor tissue samples across 27 TCGA cancer types and identified 112 specific expressed genes in LUAD. Meantime, 8240 LUAD dysregulated genes in tumor and normal samples were identified. Combining with the results of specific expressed genes and dysregulated genes in LUAD, we found there were 70 specific dysregulated genes in LUAD (LUAD-SDGs). Then ROC curve revealed six LUAD-SDGs that may be of strong diagnostic value to predict the existence of cancer (area under curve[AUC] > 95%). Kaplan-Meier survival analysis was performed to identify 6 LUAD-SDGs associated with patients' prognosis (P-values < 0.001). Multivariate Cox proportional hazards regression was employed to demonstrate that the six LUAD-SDGs were independent prognostic factors. Then, we used the six overall survival (OS)-related LUAD-SDGs constructing a six-gene signature. Multivariate Cox regression analysis suggested that the six-gene signature was an independent prognostic factor of other clinical variables (hazard ratio [HR] = 1.5098, 95%CI = 1.2996-1.7538, P < 0.0001). Based on our findings, we first presented the LUAD-SDGs for LUAD diagnosis and prognosis. Our results may provide efficient biomarkers to clinical diagnostic and prognostic evaluation in LUAD.

The depletion of PinX1 involved in the tumorigenesis of non-small cell lung cancer promotes cell proliferation via p15/cyclin D1 pathway

Background

The telomerase/telomere interacting protein PinX1 has been suggested as a tumor suppressor. However, the clinical and biological significance of PinX1 in human non-small cell lung cancer (NSCLC) is unclear.

Methods

PinX1 gene/expression pattern and its association with NSCLC patient survival were analyzed in cBioportal Web resource and two cohorts of NSCLC samples. A series of in vivo and in vitro assays were performed to elucidate the function of PinX1 on NSCLC cells proliferation and underlying mechanisms.

Results

More frequency of gene PinX1 homozygous deletion and heterozygote deficiency was first retrieved from cBioportal Web resource. Low expression of PinX1 correlated with smoking condition, histological type, T stage, N stage, M stage and TNM stage, and was an independent predictor for overall survival in a learning cohort (n = 93) and a validation cohort (n = 51) of NSCLC patients. Furthermore, knockdown of PinX1 dramatically accelerated NSCLC cell proliferation and G1/S transition, whereas ectopic overexpression of PinX1 substantially inhibited cell viability and cell cycle transition in vitro and in vivo. p15/cyclin D1 pathway and BMP5 might contribute to PinX1-associated cell proliferation and cell cycle transition.

Conclusion

The cost-effective expression of PinX1 could constitute a novel molecular predictor/marker for NSCLC management.

Electronic supplementary material

The online version of this article (doi:10.1186/s12943-017-0637-4) contains supplementary material, which is available to authorized users.

BMP9 inhibits the growth and migration of lung adenocarcinoma A549 cells in a bone marrow stromal cell‑derived microenvironment through the MAPK/ERK and NF-κB pathways

Bone is the most common distant metastatic site of lung cancer, and is particularly prone to osteolytic damage. Soluble factors secreted from bone marrow-derived cells and tumor cells contribute to the growth and metastasis of cancer cells, and enhance osteolytic damage. BMP9, as the most powerful osteogenetic factor of the bone morphogenetic protein (BMP) family, can regulate the development of various tumors. However, the effects and underlying mechanisms of BMP9 in regards to lung cancer and the bone metastatic microenvironment are poorly understood. Here, we determined the inhibitory effects of BMP9 on the proliferation and migration of lung adenocarcinoma A549 cells. When a co-culture system of A549 cells and bone marrow-derived cells (HS-5) was established, it was shown that HS-5 cells promoted the proliferation and migration of A549 cells, and metastasis and osteoclast-related factors IL-6 and IL-8 were increased in the A549 and HS-5 cells. However, BMP9 inhibited the proliferation and migration of the A549 cells in the bone microenvironment, and decreased the levels of IL-6 and IL-8. In addition, mitogen-activated protein kinase (MAPK/ERK) and nuclear factor-κB (NF-κB) signaling pathway may be involved in these effects.