Comparative proteomics analysis of human osteosarcomas and benign tumor of bone

Aggrephagy-related gene signature correlates with survival and tumor-associated macrophages in glioma: Insights from single-cell and bulk RNA sequencing

BACKGROUND

Aggrephagy is a lysosome-dependent process that degrades misfolded protein condensates to maintain cancer cell homeostasis. Despite its importance in cellular protein quality control, the role of aggrephagy in glioma remains poorly understood.

OBJECTIVE

To investigate the expression of aggrephagy-related genes (ARGs) in glioma and in different cell types of gliomas and to develop an ARGs-based prognostic signature to predict the prognosis, tumor microenvironment, and immunotherapy response of gliomas.

METHODS

ARGs were identified by searching the Reactome database. We developed the ARGs-based prognostic signature (ARPS) using data from the Cancer Genome Atlas (TCGA, n = 669) by Lasso-Cox regression. We validated the robustness of the signature in clinical subgroups and CGGA cohorts (n = 970). Gene set enrichment analysis (GSEA) was used to identify the pathways enriched in ARPS subgroups. The correlations between ARGs and macrophages were also investigated at single cell level.

RESULTS

A total of 44 ARGs showed heterogeneous expression among different cell types of gliomas. Five ARGs (HSF1, DYNC1H1, DYNLL2, TUBB6, TUBA1C) were identified to develop ARPS, an independent prognostic factor. GSEA showed gene sets of patients with high-ARPS were mostly enriched in cell cycle, DNA replication, and immune-related pathways. High-ARPS subgroup had higher immune cell infiltration states, particularly macrophages, Treg cells, and neutrophils. APRS had positive association with tumor mutation burden (TMB) and immunotherapy response predictors. At the single cell level, we found ARGs correlated with macrophage development and identified ARGs-mediated macrophage subtypes with distinct communication characteristics with tumor cells. VIM+ macrophages were identified as pro-inflammatory and had higher interactions with malignant cells.

CONCLUSION

We identified a novel signature based on ARGs for predicting glioma prognosis, tumor microenvironment, and immunotherapy response. We highlight the ARGs-mediated macrophages in glioma exhibit classical features.

Identification of the Key Immune Cells and Genes for the Diagnostics and Therapeutics of Meningioma

BACKGROUND

Dysregulation of immune infiltration critically contributes to the tumorigenesis and progression of meningiomas. However, the landscape of immune microenvironment and key genes correlated with immune cell infiltration remains unclear.

METHODS

Four Gene Expression Omnibus data sets were included. CIBERSORT algorithm was utilized to analyze the immune cell infiltration in samples. Wilcoxon test, Random Forest algorithm, and Least Absolute Shrinkage and Selection Operator regression were adopted in identifying significantly different infiltrating immune cells and differentially expressed genes (DEGs). Functional enrichment analysis was performed by Kyoto Encyclopedia of Genes and Genomes and Gene Ontology. The correlation between genes and immune cells was evaluated via Spearman's correlation analysis. Receiver Operator Characteristic curve analysis evaluated the markers' diagnostic effectiveness. The mRNA-miRNA and Drug-Gene-Immune cell interaction networks were constructed to identify potential diagnostic and therapeutic targets.

RESULTS

Plasma cells, M1 macrophages, M2 macrophages, neutrophils, eosinophils, and activated NK cells were the significantly different infiltrating immune cells in meningioma. A total of 951 DEGs, associated with synaptic function and structure, ion transport regulation, brain function, and immune-related pathways, were identified. Among 11 hub DEGs, RYR2 and TTR were correlated with plasma cells; SNCG was associated with NK cells; ADCY1 exhibited excellent diagnostic effectiveness; and ADCY1, BMX, KCNA5, SLCO4A1, and TTR could be considered as therapeutic targets.

CONCLUSIONS

ADCY1 can be identified as a diagnostic marker; ADCY1, BMX, KCNA5, SLCO4A1, and TTR are potential therapeutic targets, and their associations with macrophages, neutrophils, NK cells, and plasma cells might impact the tumorigenesis of meningiomas.

ZNF133 is a potent suppressor in breast carcinogenesis through dampening L1CAM, a driver for tumor progression

Due to the complexity and heterogeneity of breast cancer, the therapeutic effects of breast cancer treatment vary between subtypes. Breast cancer subtypes are classified based on the presence of molecular markers for estrogen or progesterone receptors and human epidermal growth factor 2. Thus, novel, comprehensive, and precise molecular indicators in breast carcinogenesis are urgently needed. Here, we report that ZNF133, a zinc-finger protein, is negatively associated with poor survival and advanced pathological staging of breast carcinomas. Moreover, ZNF133 is a transcription repressor physically associated with the KAP1 complex. It transcriptionally represses a cohort of genes, including L1CAM, that are critically involved in cell proliferation and motility. We also demonstrate that the ZNF133/KAP1 complex inhibits the proliferation and invasion of breast cancer cells in vitro and suppresses breast cancer growth and metastasis in vivo by dampening the transcription of L1CAM. Taken together, the findings of our study confirm the value of ZNF133 and L1CAM levels in the diagnosis and prognosis of breast cancer, contribute to a deeper understanding of the regulation mechanism of ZNF133 for the first time, and provide a new therapeutic strategy and precise intervention target for breast cancer.

Reticulocalbin 3 Is a Novel Mediator of Glioblastoma Progression

Glioblastoma is the most common malignant primary brain tumor. Molecular mechanisms underlying the pathobiology of glioblastoma are incompletely understood, emphasizing an unmet need for the identification of new therapeutic candidates. Reticulocalbin 3 (RCN3), an ER lumen-residing Ca2+ binding protein, plays an essential role in protein biosynthesis processes via the secretory pathway. Emerging studies demonstrated that RCN3 is a target for therapeutic intervention in various diseases. However, a knowledge gap exists about whether RCN3 plays a role in glioblastoma. Publicly available datasets suggest RCN3 is overexpressed in glioblastoma and portends poor survival rates. The knockdown or knockout of RCN3 using shRNA or CRISPR/Cas9 gRNA, respectively, significantly reduced proliferation, neurosphere formation, and self-renewal of GSCs. The RNA-seq studies showed downregulation of genes related to translation, ribosome, and cytokine signaling and upregulation of genes related to immune response, stem cell differentiation, and extracellular matrix (ECM) in RCN3 knockdown cells. Mechanistic studies using qRT-PCR showed decreased expression of ribosomal and increased expression of ER stress genes. Further, in silico analysis of glioblastoma patient datasets showed RCN3 expression correlated with the ribosome, ECM, and immune response pathway genes. Importantly, the knockdown of RCN3 using shRNA significantly enhanced the survival of tumor-bearing mice in orthotopic glioblastoma models. Our study suggests that RCN3 could be a potential target for the development of a therapeutic intervention in glioblastoma.

CUX2 prevents the malignant progression of gliomas by enhancing ADCY1 transcription

Gliomas are one of the most prevalent brain tumors. This study sought to elucidate the mechanism of CUX2 in glioma development via ADCY1. CUX2 and ADCY1 expression in glioma predicted by bioinformatics analysis. Subsequent to gain- and loss-of-function experiments in glioma cells, cell proliferation was tested by CCK8 and plate clone formation assays, and cell migration and invasion by Transwell assay. The binding between CUX2 and ADCY1 was examined with dual-luciferase gene reporter and ChIP assays. The xenograft mouse model was established to verify the effect of the CUX2/ADCY1 axis on glioma cell growth in vivo. CUX2 and ADCY1 expression was low in glioma. The overexpression of CUX2 repressed the proliferative, migrating, and invasive abilities of glioma cells. Moreover, CUX2 was enriched in the ADCY1 promoter to enhance ADCY1 expression. ADCY1 upregulation diminished glioma cell proliferative, migrating, and invasive properties. Silencing of ADCY1 abrogated and upregulation of ADCY1 promoted the inhibitory influence of CUX2 upregulation on the malignant behaviors of glioma cells in vitro and gliomas cell growth in vivo. Collectively, CUX2 promoted ADCY1 transcription to delay glioma cell migration, proliferation, and invasion.

Mass Spectrometric-Based Proteomics for Biomarker Discovery in Osteosarcoma: Current Status and Future Direction

Due to a lack of novel therapies and biomarkers, the clinical outcomes of osteosarcoma patients have not significantly improved for decades. The advancement of mass spectrometry (MS), peptide quantification, and downstream pathway analysis enables the investigation of protein profiles across a wide range of input materials, from cell culture to long-term archived clinical specimens. This can provide insight into osteosarcoma biology and identify candidate biomarkers for diagnosis, prognosis, and stratification of chemotherapy response. In this review, we provide an overview of proteomics studies of osteosarcoma, indicate potential biomarkers that might be promising therapeutic targets, and discuss the challenges and opportunities of mass spectrometric-based proteomics in future osteosarcoma research.

RCN3: a Ca2+ homeostasis regulator that promotes esophageal squamous cell carcinoma progression and cisplatin resistant

Esophageal squamous cell carcinoma (ESCC) is one of the most prevalent cancers worldwide. There is a critical need to identify new mechanisms that contribute to ESCC progression. Reticulocalbin3 (RCN3) is mainly located in the endoplasmic reticulum and Ca²⁺‐binding protein containing EF‐hands. The function of RCN3 in tumor progression has not been clarified. We observed that the expression level of RCN3 was higher in ESCC tissues than in paired normal tissues. Overexpression of RCN3 was positively associated with tumor size, lymph node metastasis, TNM stage, lymphatic vessel infiltration, and poor outcome in patients with ESCC. Increased malignant phenotypes were observed in RCN3 overexpressing ESCC cells, whereas the opposite effects were achieved in RCN3‐silenced cells. Reticulocalbin3 promoted the expression of MMP‐2 and MMP‐9 by regulating the inositol 1,4,5‐trisphosphate receptor 1 (IP3R1)–Ca²⁺–calcium/calmodulin‐dependent protein kinase II–c‐Jun signaling pathway. Reticulocalbin3 induced cisplatin resistance by regulating IP3R1/Ca²⁺ to maintain intracellular Ca²⁺ homeostasis and reduced reactive oxygen species in ESCC cells. Finally, the expression of RCN3 was regulated by hypoxia inducible factor‐1α. Collectively, these data strongly support that RCN3 regulates Ca²⁺ homeostasis by targeting IP3R1 to promote the progression and platinum resistance of ESCC. Our studies suggest that RCN3 could serve as predictive factor of poor prognosis and potential therapeutic target for ESCC patients.

Pan-Cancer Analysis of the Oncogenic and Immunological Role of RCN3: A Potential Biomarker for Prognosis and Immunotherapy

Despite emerging publications have elucidated a functional association between RCN3 and tumors, no evidence about a pan-cancer analysis of RCN3 is available. Our study first conducted a comprehensive assessment of its expression profiles, prognosis value, immune infiltration, and relevant cellular pathways via bioinformatics techniques based on the public database of TCGA (The Cancer Genome Atlas). RCN3 is highly expressed in most tumors, and it is associated with poor prognosis. Kaplan-Meier analysis and Cox regression analysis suggested that the high expression of RCN3 was associated with poor overall survival (OS) in pan-cancer, Cox regression analysis also indicated high RCN3 expression was correlated with disease-specific survival (DSS) and progression-free interval (PFI) in most tumors. We observed a regulation function of RCN3 at genetic and epigenetic levels through CNA and DNA methylation using cBioPortal database. Based on Gene Set Enrichment Analysis, we first identified related pathways of RCN3 and its potential biological functions in pan-cancer, RCN3 was implicated in oncogenic pathways, and was related to extracellular matrix and immune regulation. We found that RCN3 positively correlated with the levels of infiltrating cells such as TAMs and CAFs, but negatively correlated with CD8⁺ T-cells by analyzing immune cell infiltration data we downloaded from published work and online databases, further investigation of the correlation between immunosuppressive genes, chemokines, chemokines receptors, and high RCN3 expression showed a significant positive association in the vast majority of TCGA cancer types. These results indicated its role as an immune regulatory in cancers and suggested that RCN3 is a potential biomarker for immunotherapy. Also, we found that expression of RCN3 was much higher in CRC tissues than in normal tissues with a higher expression level of RCN3 closely correlating to advanced American Joint Committee on Cancer (AJCC) stage, poor differentiation, increased tumor size, and poor prognosis of CRC. Biological function experiments showed that RCN3 regulated CRC cells’ proliferation and metastasis ability. Upregulation of RCN3 in CRC cells increased the expression of immune related factor, including TGFβ1, IL-10, and IL-6. Thus, our pan-cancer analysis offers a deep understanding of potential oncogenic roles of RCN3 in different cancers.

TUBA1C is a Prognostic Marker in Low-grade Glioma and Correlates with Immune Cell Infiltration in the Tumor Microenvironment

TUBA1C, a microtubule component, contributes to the development of several cancers. Our purpose was to study the expression of TUBA1C, its potential prognostic value, and its effects on the infiltration of immune cells of low-grade glioma (LGG). Through applying multiple bioinformatics analyses, we extracted and analyzed datasets from TCGA, TIMER, GTEx, GEPIA, and HPA to investigate the potential oncogenic mechanisms of TUBA1C, including the correlation between TUBA1C and prognosis, immune-checkpoints, tumor microenvironment (TME), and infiltration of immune cells in LGG. GO functional annotations and KEGG pathway analyses were further applied to investigate the potential action of TUBA1C in LGG. We revealed that the mRNA levels of TUBA1C were increased in LGG tumor tissues than in normal tissues. Additionally, TUBA1C was up-regulated in the grade III of LGG than in grade II. Moreover, we found that TUBA1C may be an independent prognostic factor of LGG, and high TUBA1C expression correlated to a poor prognosis of LGG. TUBA1C expression was positively associated with the infiltration of B cells, CD8 T+ cells, CD4⁺ T cells, macrophages, dendritic cells, and neutrophils. TUBA1C was also verified to be co-expressed with immune-related genes and immune-checkpoints. GO and KEGG pathway analyses indicated that TUBA1C may potentially regulate the pathogenesis of LGG through immune-related pathways, including chemokine pathway; JAK-STAT pathway; natural killer cell mediated cytotoxicity; T cell receptor pathway; leukocyte migration; negative regulation of immune system process; regulation of lymphocyte activation; T cell activation and other pathways. In conclusion, TUBA1C expression is increased in LGG and high TUAB1C expression is related to a poor prognosis. TUBA1C may influence tumor development by regulating the tumor-infiltrating cells in the TME. TUBA1C may be a potential target for immunotherapy.

GNG7 and ADCY1 as diagnostic and prognostic biomarkers for pancreatic adenocarcinoma through bioinformatic-based analyses

Pancreatic adenocarcinoma (PAAD) is one of the most lethal malignant tumors in the world. The GSE55643 and GSE15471 microarray datasets were downloaded to screen the diagnostic and prognostic biomarkers for PAAD. 143 downregulated genes and 118 upregulated genes were obtained. Next, we performed gene ontology (GO) and The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis on these genes and constructed a protein-protein interaction (PPI) network. We screened out two important clusters of genes, including 13 upregulated and 5 downregulated genes. After the survival analysis, 3 downregulated genes and 10 upregulated genes were identified as the selected key genes. The KEGG analysis on 13 selected genes showed that GNG7 and ADCY1 enriched in the Pathway in Cancer. Next, the diagnostic and prognostic value of GNG7 and ADCY1 was investigated using independent cohort of the Cancer Genome Atlas (TCGA), GSE84129 and GSE62452. We observed that the expression of the GNG7 and ADCY1 was decreased in PAAD. The diagnostic receiver operating characteristic (ROC) analysis indicated that the GNG7 and ADCY1 could serve as sensitive diagnostic markers in PAAD. Survival analysis suggested that expression of GNG7, ADCY1 were significantly associated with PAAD overall survival (OS). The multivariate cox regression analysis showed that the expression of GNG7, ADCY1 were independent risk factors for PAAD OS. Our study indicated GNG7 and ADCY1 may be potential diagnostic and prognostic biomarkers in patients with PAAD.

Long non-coding RNA DPP10-AS1 exerts anti-tumor effects on colon cancer via the upregulation of ADCY1 by regulating microRNA-127-3p

Herein we hypothesized that DPP10-AS1 could affect the development of colon cancer via the interaction with miR-127-3p and adenylate cyclase 1 (ADCY1). After sorting of CD133 positive cells, sphere formation, colony formation, proliferation, invasion, migration, and apoptosis were detected to explore the involvement of DPP10-AS1 and miR-127-3p in the colon cancer stem cell (CCSC) properties through gain- and loss-of function approaches. Furthermore, tumor xenograft in nude mice was conducted to investigate the effect of DPP10-AS1 and miR-127-3p on tumor growth in vivo. Poorly expressed DPP10-AS1 and ADCY1, while highly expressed miR-127-3p were found in CCSCs. Low expression of DPP10-AS1 was correlated with TNM stage, lymphatic node metastasis, and tumor differentiation. Upregulation of DPP10-AS1 increased ADCY1 protein expression, decreased the protein expression of CCSC-related factors, inhibited sphere formation, colony formation, proliferation, invasion and migration, and accelerated apoptosis of HT-29 and SW480 cells by suppressing the expression of miR-127-3p. Further, the above in vitro findings were also confirmed by in vivo assays. Taken together, this study demonstrates that DPP10-AS1 inhibits CCSC proliferation by regulating miR-127-3p and ADCY1, providing fresh insight into a promising novel treatment strategy for colon cancer.

KRAB-ZFP Transcriptional Regulators Acting as Oncogenes and Tumor Suppressors: An Overview

Krüppel-associated box zinc finger proteins (KRAB-ZFPs) constitute the largest family of transcriptional factors exerting co-repressor functions in mammalian cells. In general, KRAB-ZFPs have a dual structure. They may bind to specific DNA sequences via zinc finger motifs and recruit a repressive complex through the KRAB domain. Such a complex mediates histone deacetylation, trimethylation of histone 3 at lysine 9 (H3K9me3), and subsequent heterochromatization. Nevertheless, apart from their repressive role, KRAB-ZFPs may also co-activate gene transcription, likely through interaction with other factors implicated in transcriptional control. KRAB-ZFPs play essential roles in various biological processes, including development, imprinting, retroelement silencing, and carcinogenesis. Cancer cells possess multiple genomic, epigenomic, and transcriptomic aberrations. A growing number of data indicates that the expression of many KRAB-ZFPs is altered in several tumor types, in which they may act as oncogenes or tumor suppressors. Hereby, we review the available literature describing the oncogenic and suppressive roles of various KRAB-ZFPs in cancer. We focused on their association with the clinicopathological features and treatment response, as well as their influence on the cancer cell phenotype. Moreover, we summarized the identified upstream and downstream molecular mechanisms that may govern the functioning of KRAB-ZFPs in a cancer setting.

Gene signatures with predictive and prognostic survival values in human osteosarcoma

Osteosarcoma is a common malignancy seen mainly in children and adolescents. The disease is characterized by poor overall prognosis and lower survival due to a lack of predictive markers. Many gene signatures with diagnostic, prognostic, and predictive values were evaluated to achieve better clinical outcomes. Two public data series, GSE21257 and UCSC Xena, were used to identify the minimum number of robust genes needed for a predictive signature to guide prognosis of patients with osteosarcoma. The lasso regression algorithm was used to analyze sequencing data from TCGA-TARGET, and methods such as Cox regression analysis, risk factor scoring, receiving operating curve, KMplot prognosis analysis, and nomogram were used to characterize the prognostic predictive power of the identified genes. Their utility was assessed using the GEO osteosarcoma dataset. Finally, the functional enrichment analysis of the identified genes was performed. A total of twenty-gene signatures were found to have a good prognostic value for predicting patient survival. Gene ontology analysis showed that the key genes related to osteosarcoma were categorized as peptide–antigen binding, clathrin-coated endocytic vesicle membrane, peptide binding, and MHC class II protein complex. The osteosarcoma related genes in these modules were significantly enriched in the processes of antigen processing and presentation, phagocytosis, cell adhesion molecules, Staphylococcus aureus infection. Twenty gene signatures were identified related to osteosarcoma, which would be helpful for predicting prognosis of patients with OS. Further, these signatures can be used to determine the subtypes of osteosarcoma.

Dose and Sequence Dependent Synergism from the Combination of Oxaliplatin with Emetine and Patulin Against Colorectal Cancer

BACKGROUND

Colorectal cancer is the third most commonly diagnosed cancer in the world, causing many deaths every year. Combined chemotherapy has opened a new horizon in treating colorectal cancer. The objective of the present study is to investigate the activity of oxaliplatin in combination with emetine and patulin against colorectal cancer models.

METHODS

IC50 values of oxaliplatin, emetine and patulin were determined against human colorectal cancer cell lines (HT-29 and Caco-2) using MTT reduction assay. Synergistic, antagonistic and additive effects from the selected binary combinations were determined as a factor of sequence of administration and added concentrations. Proteomics was carried out to identify the proteins which were accountable for combined drug action applying to the selected drug combination.

RESULTS

Oxaliplatin in combination with patulin produced synergism against human colorectal cancer models depending on dose and sequence of drug administration. Bolus administration of oxaliplatin with patulin proved to be the best in terms of synergistic outcome. Altered expressions of nine proteins (ACTG, PROF1, PPIA, PDIA3, COF1, GSTP1, ALDOA, TBA1C and TBB5) were considered for combined drug actions of oxaliplatin with patulin.

CONCLUSION

Bolus administration of oxaliplatin with patulin has the potential to be used in the treatment of colorectal cancer, and would warrant further evaluation using suitable animal model.

Molecular karyotyping and gene expression analysis in childhood cancer patients

Abstract

The genetic etiology of sporadic childhood cancer cases remains unclear. We recruited a cohort of 20 patients who survived a childhood malignancy and then developed a second primary cancer (2N), and 20 carefully matched patients who survived a childhood cancer without developing a second malignancy (1N). Twenty matched cancer-free (0N) and additional 1000 (0N) GHS participants served as controls. Aiming to identify new candidate loci for cancer predisposition, we compared the genome-wide DNA copy number variations (CNV) with the RNA-expression data obtained after in vitro irradiation of primary fibroblasts. In 2N patients, we detected a total of 142 genes affected by CNV. A total of 53 genes of these were not altered in controls. Six genes (POLR3F, SEC23B, ZNF133, C16orf45, RRN3, and NTAN1) that we found to be overexpressed after irradiation were also duplicated in the genome of the 2N patients. For the 1N collective, 185 genes were affected by CNV and 38 of these genes were not altered in controls. Five genes (ZCWPW2, SYNCRIP, DHX30, DHRS4L2, and THSD1) were located in duplicated genomic regions and exhibited altered RNA expression after irradiation. One gene (ABCC6) was partially duplicated in one 1N and one 2N patient. Analysis of methylation levels of THSD1 and GSTT2 genes which were detected in duplicated regions and are frequently aberrantly methylated in cancer showed no changes in patient’s fibroblasts. In summary, we describe rare and radiation-sensitive genes affected by CNV in childhood sporadic cancer cases, which may have an impact on cancer development.

Key messages

• Rare CNV’s may have an impact on cancer development in sporadic, non-familial, non-syndromic childhood cancer cases.

• In our cohort, each patient displayed a unique pattern of cancer-related gene CNVs, and only few cases shared similar CNV.

• Genes that are transcriptionally regulated after radiation can be located in CNVs in cancer patients and controls.

• THSD1 and GSTT2 methylation is not altered by CNV.

Electronic supplementary material

The online version of this article (10.1007/s00109-020-01937-4) contains supplementary material, which is available to authorized users.

Identification of a Two-Gene (PML-EPB41) Signature With Independent Prognostic Value in Osteosarcoma

Background: Osteosarcoma (OSA) is the most prevalent form of malignant bone cancer and it occurs predominantly in children and adolescents. OSA is associated with a poor prognosis and highest cause of cancer-related death. However, there are a few biomarkers that can serve as reasonable assessments of prognosis.

Methods: Gene expression profiling data were downloaded from dataset GSE39058 and GSE21257 from the Gene Expression Omnibus database as well as TARGET database. Bioinformatic analysis with data integration was conducted to discover the significant biomarkers for predicting prognosis. Verification was conducted by qPCR and western blot to measure the expression of genes.

Results: 733 seed genes were selected by combining the results of the expression profiling data with hub nodes in a human protein-protein interaction network with their gene functional enrichment categories identified. Following by Cox proportional risk regression modeling, a 2-gene (PML-EPB41) signature was developed for prognostic prediction of patients with OSA. Patients in the high-risk group had significantly poorer survival outcomes than in the low-risk group. Finally, the signature was validated and analyzed by the external dataset along with Kaplan–Meier survival analysis as well as biological experiment. A molecular gene model was built to serve as an innovative predictor of prognosis for patients with OSA.

Conclusion: Our findings define novel biomarkers for OSA prognosis, which will possibly aid in the discovery of novel therapeutic targets with clinical applications.

CADM1 inhibits ovarian cancer cell proliferation and migration by potentially regulating the PI3K/Akt/mTOR pathway

Previous studies have shown that cell adhesion molecule 1 (CADM1), an immunoglobulin superfamily member, is frequently inactivated but functions as a tumor suppressor in many solid tumors. However, the characterization of CADM1 expression in ovarian cancer cells and the mechanisms of its tumor suppressor function are not fully understood. We generated ovarian cancer cell lines in which CADM1 was stably upregulated or downregulated. CADM1 expression was significantly decreased in ovarian cancer tissue and cells lines. Functionally, knockdown of CADM1 promoted the growth, migration and invasion of ovarian cancer cells. Conversely, further experimental evidence indicated that overexpression of CADM1 inhibited the migration and invasion of ovarian cancer cells potentially through inhibition of the PI3K/Akt/mTOR signaling pathway by regulating upstream regulators (LXR/RXR, IGF1, IFI44L and C4BPA) and downstream effectors (APP, EDN1, TGFBI and Rap1A). In conclusion, CADM1 inhibits ovarian cancer cell proliferation and migration by potentially regulating the PI3K/Akt/mTOR signaling pathway. CADM1 could be a potential therapeutic target for ovarian cancer.

Protein profiling of osteosarcoma tissue and soft callus unveils activation of the unfolded protein response pathway

Oncogenic drivers of osteosarcoma remain controversial due to the complexity of the genomic background of the disease. There are limited novel therapeutic options, and the survival rate of patients with osteosarcoma has not improved in decades. Genomic instability leads to complexity in various pathways, which is potentially revealed at the protein level. Therefore, the present study aimed to identify the mechanisms involved in the oncogenesis of osteosarcoma using proteomics and bioinformatics tools. As clinical specimens from patients are the most relevant disease-related source, expression patterns of proteins in osteosarcoma tissues were compared with soft tissue callus from donors containing high numbers of osteoblastic cells. Two-dimensional electrophoresis and liquid chromatography-tandem mass spectrometry (LC-MS/MS) successfully identified 33 differentially expressed proteins in the osteosarcoma tissues compared with the soft tissue callus. Among these proteins, 29 proteins were significantly upregulated in osteosarcoma. A functionally grouped network of the overexpressed proteins, that was created using the ClueGo and CluePedia applications, demonstrated that the unfolded protein response (UPR) pathway was activated mainly through the activating transcription factor 6 arm in osteosarcoma. The results of proteomics analysis were confirmed by elevated expression of UPR-related chaperone proteins, including 78 kDa glucose-related protein (GRP78), endoplasmin, calreticulin and prelamin-A/C, in the patient-derived primary cells and osteosarcoma cell lines. Furthermore, the expression of GRP78, a master regulator of the UPR, was enhanced in the osteosarcoma tissues of patients that were resistant to double regimen of doxorubicin and a platinum-based drug. The findings of the present study suggest that targeting the UPR pathway may be promising for the treatment of osteosarcoma.

Development of somatic mutation signatures for risk stratification and prognosis in lung and colorectal adenocarcinomas

Background

Prognostic signatures are vital to precision medicine. However, development of somatic mutation prognostic signatures for cancers remains a challenge. In this study we developed a novel method for discovering somatic mutation based prognostic signatures.

Results

Somatic mutation and clinical data for lung adenocarcinoma (LUAD) and colorectal adenocarcinoma (COAD) from The Cancer Genome Atlas (TCGA) were randomly divided into training (n = 328 for LUAD and 286 for COAD) and validation (n = 167 for LUAD and 141 for COAD) datasets. A novel method of using the log2 ratio of the tumor mutation frequency to the paired normal mutation frequency is computed for each patient and missense mutation. The missense mutation ratios were mean aggregated into gene-level somatic mutation profiles. The somatic mutations were assessed using univariate Cox analysis on the LUAD and COAD training sets separately. Stepwise multivariate Cox analysis resulted in a final gene prognostic signature for LUAD and COAD. Performance was compared to gene prognostic signatures generated using the same pipeline but with different somatic mutation profile representations based on tumor mutation frequency, binary calls, and gene-gene network normalization. Signature high-risk LUAD and COAD cases had worse overall survival compared to the signature low-risk cases in the validation set (log-rank test p-value = 0.0101 for LUAD and 0.0314 for COAD) using mutation tumor frequency ratio (MFR) profiles, while all other methods, including gene-gene network normalization, have statistically insignificant stratification (log-rank test p-value ≥0.05). Most of the genes in the final gene signatures using MFR profiles are cancer-related based on network and literature analysis.

Conclusions

We demonstrated the robustness of MFR profiles and its potential to be a powerful prognostic tool in cancer. The results are robust according to validation testing and the selected genes are biologically relevant.

Hornerin promotes tumor progression and is associated with poor prognosis in hepatocellular carcinoma

Background

The function of hornerin (HRNR), a member of the S100 protein family, is poorly clarified in the development of human tumors. The role of HRNR in hepatocellular carcinoma (HCC) progression is investigated in the study.

Methods

The expression levels of HRNR were assessed in tumor samples from a cohort of 271 HCC patients. The effect of HRNR on proliferation, colony formation and invasion of tumor cells was examined. We further determined the role of HRNR in tumor growth in vivo by using xenograft HCC tumor models. The possible mechanism of the HRNR promotion of HCC progression was explored.

Results

We found that HRNR was overexpressed in HCC tissues. The high expression of HRNR in HCCs was significantly associated with vascular invasion, poor tumor differentiation, and advanced TNM stage. The disease-free survival (DFS) and overall survival (OS) of HCC patients with high HRNR expression were poorer than those in the low HRNR expression group. HRNR expression was an independent risk factor linked to both poor DFS (HR = 2.209, 95% CI = 1.627–2.998,P <  0.001) and OS (HR = 2.459,95% CI = 1.736–3.484, P <  0.001). In addition, the knockdown of HRNR by shRNAs significantly inhibited the proliferation, colony formation, migration and invasion of HCC tumor cells. HRNR silencing led to the decreased phosphorylation of AKT signaling. Notably, tumor growth was markedly inhibited by HRNR silencing in a xenograft model of HCC.

Conclusions

HRNR promotes tumor progression and is correlated with a poor HCC prognosis. HRNR may contribute to HCC progression via the regulation of the AKT pathway.

ZNF280B promotes the growth of gastric cancer in vitro and in vivo

Zinc finger protein 280B (ZNF280B) mediates pro-survival and pro-growth functions in prostate cancer. However, in gastric cancer, its clinical significance remains poorly characterized. In the present study, the expression levels of ZNF280B in 60 patients with gastric cancer were examined using immunohistochemistry. The association between ZNF280B expression and clinicopathological features was assessed. Positive ZNF280B staining was demonstrated for 38 (63.3%) samples out of 60 gastric cancer cases in immunohistochemical analysis. ZNF280B expression was significantly associated with tumor size (P=0.017) and TNM stage (P=0.001). Furthermore, the proliferation index in the positive ZNF280B expression group was significantly higher (38.8±6.2) compared with that of the negative ZNF280B expression group (16.9±8.9; P<0.01). These results suggest that ZNF280B expression may be associated with the proliferation of gastric cancer cells. The role of ZNF280B in the growth of gastric cancer cells (MGC-803) was also investigated in vitro and in vivo by enhancing the expression of ZNF280B. A colony formation assay indicated that the number of colonies in the MGC-803 cells with enhanced ZNF280B (146±5.8) was significantly higher than that of the MGC-803 control group (97±5.1) and the negative control group (101±6.5; P<0.05). An MTT assay demonstrated that ZNF280B significantly promoted the proliferation of MGC-803 cells at days 3 and 4 (P<0.05). It was observed that the overexpression of ZNF280B may promote the growth of gastric cancer in vivo in xenograft studies. These findings indicate that ZNF280B may be a novel therapeutic target for gastric cancer.

QuaDMutEx: quadratic driver mutation explorer

BACKGROUND

Somatic mutations accumulate in human cells throughout life. Some may have no adverse consequences, but some of them may lead to cancer. A cancer genome is typically unstable, and thus more mutations can accumulate in the DNA of cancer cells. An ongoing problem is to figure out which mutations are drivers - play a role in oncogenesis, and which are passengers - do not play a role. One way of addressing this question is through inspection of somatic mutations in DNA of cancer samples from a cohort of patients and detection of patterns that differentiate driver from passenger mutations.

RESULTS

We propose QuaDMutEx, a method that incorporates three novel elements: a new gene set penalty that includes non-linear penalization of multiple mutations in putative sets of driver genes, an ability to adjust the method to handle slow- and fast-evolving tumors, and a computationally efficient method for finding gene sets that minimize the penalty, through a combination of heuristic Monte Carlo optimization and exact binary quadratic programming. Compared to existing methods, the proposed algorithm finds sets of putative driver genes that show higher coverage and lower excess coverage in eight sets of cancer samples coming from brain, ovarian, lung, and breast tumors.

CONCLUSIONS

Superior ability to improve on both coverage and excess coverage on different types of cancer shows that QuaDMutEx is a tool that should be part of a state-of-the-art toolbox in the driver gene discovery pipeline. It can detect genes harboring rare driver mutations that may be missed by existing methods. QuaDMutEx is available for download from https://github.com/bokhariy/QuaDMutEx under the GNU GPLv3 license.

CSE1L interaction with MSH6 promotes osteosarcoma progression and predicts poor patient survival

To discover tumor-associated proteins in osteosarcoma, a quantitative proteomic analysis was performed to identify proteins that were differentially expressed between osteosarcoma and human osteoblastic cells. Through clinical screening and a functional evaluation, chromosome segregation 1-like (CSE1L) protein was found to be related to the growth of osteosarcoma cells. To date, little is known about the function and underlying mechanism of CSE1L in osteosarcoma. In the present study, we show that knockdown of CSE1L inhibits osteosarcoma growth in vitro and in vivo. By co-immunoprecipitation and RNA-seq analysis, CSE1L was found to interact with mutS homolog 6 (MSH6) and function as a positive regulator of MSH6 protein in osteosarcoma cells. A rescue study showed that decreased growth of osteosarcoma cells by CSE1L knockdown was reversed by MSH6 overexpression, indicating that the activity of CSE1L was an MSH6-dependent function. In addition, depletion of MSH6 hindered cellular proliferation in vitro and in vivo. Notably, CSE1L expression was correlated with MSH6 expression in tumor samples and was associated with poor prognosis in patients with osteosarcoma. Taken together, our results demonstrate that the CSE1L-MSH6 axis has an important role in osteosarcoma progression.

CNOT1 cooperates with LMNA to aggravate osteosarcoma tumorigenesis through the Hedgehog signaling pathway

While treatments for childhood osteosarcoma have improved, the overall survival for this common type of bone cancer has not changed for three decades, and thus, new targets for therapeutic development are needed. To identify tumor-related proteins in osteosarcoma, we used isobaric tags in a relative and absolute quantitation proteomic approach to analyze the differentially expressed proteins between osteosarcoma cells and human osteoblastic cells. Through clinical screening and functional evaluation, CCR4-NOT transcription complex subunit 1 (CNOT1) correlated with the growth of osteosarcoma cells. To date, the mechanisms and regulatory roles of CNOT1 in tumors, including osteosarcoma, remain largely elusive. Here, we present evidence that knockdown of CNOT1 inhibits the growth of osteosarcoma in vitro and in vivo. Mechanistically, we observed that CNOT1 interacted with LMNA (lamin A) and functioned as a positive regulator of this intermediate filament protein. The RNA-seq analysis revealed that CNOT1 depletion inhibited the Hedgehog signaling pathway in osteosarcoma cells. A rescue study showed that the decreased growth of osteosarcoma cells and inhibition of the Hedgehog signaling pathway by CNOT1 depletion were reversed by LMNA overexpression, indicating that the activity of CNOT1 was LMNA dependent. Notably, the CNOT1 expression was significantly associated with tumor recurrence, Enneking stage, and poor survival in patients with osteosarcoma. Examination of clinical samples confirmed that CNOT1 expression positively correlated with LMNA protein expression. Taken together, these results suggest that the CNOT1-LMNA-Hedgehog signaling pathway axis exerts an oncogenic role in osteosarcoma progression, which could be a potential target for gene therapy.

Exploring targeted therapy of osteosarcoma using proteomics data

Despite multimodal therapeutic treatments of osteosarcoma (OS), some patients develop resistance to currently available regimens and eventually end up with recurrent or metastatic outcomes. Many attempts have been made to discover effective drugs for improving outcome; however, due to the heterogeneity of the disease, new therapeutic options have not yet been identified. This study aims to explore potential targeted therapy related to protein profiles of OS. In this review of proteomics studies, we extracted data on differentially expressed proteins (DEPs) from archived literature in PubMed and our in-house repository. The data were divided into three experimental groups, DEPs in 1) OS/OB: OS vs osteoblastic (OB) cells, 2) metastasis: metastatic vs non-metastatic sublines plus fresh tissues from primary OS with and without pulmonary metastasis, and 3) chemoresistance: spheroid (higher chemoresistance) vs monolayer cells plus fresh tissues from biopsies from good and poor responders. All up-regulated protein entities in the list of DEPs were sorted and cross-referenced with identifiers of targets of US Food and Drug Administration (FDA)-approved agents and chemical inhibitors. We found that many targets of FDA-approved antineoplastic agents, mainly a group of epigenetic regulators, kinases, and proteasomes, were highly expressed in OS cells. Additionally, some overexpressed proteins were targets of FDA-approved non-cancer drugs, including immunosuppressive and antiarrhythmic drugs. The resulting list of chemical agents showed that some transferase enzyme inhibitors might have anticancer activity. We also explored common targets of OS/OB and metastasis groups, including amidophosphoribosyltransferase (PPAT), l-lactate dehydrogenase B chain (LDHB), and pyruvate kinase M2 (PKM2) as well as the common target of all categories, cathepsin D (CTSD). This study demonstrates the benefits of a text mining approach to exploring therapeutic targets related to protein expression patterns. These results suggest possible repurposing of some FDA-approved medicines for the treatment of OS and using chemical inhibitors in drug screening tests.

Overexpression of KH-type splicing regulatory protein regulates proliferation, migration, and implantation ability of osteosarcoma

Osteosarcoma is a common malignant bone tumor in children and adolescents. The current 5-year survival rate is ~60% and that seems to be reaching a plateau. In order to improve treatment outcomes of osteosarcoma, a better understanding of tumorigenesis and underlying molecular mechanisms is required for searching out possible new treatment targets. This study aimed to identify the potential proteins involving the pathogenesis of osteosarcoma using a proteomics approach. Proteins extracted from primary cell culture of osteosarcoma (n=7) and osteoblasts of cancellous bone (n=7) were studied. Using 2-DE based proteomics and LC-MS/MS analysis, we successfully determined seven differentially expressed protein spots. Four upregulated proteins and three downregulated proteins were observed in this study in which KH-type splicing regulatory protein (KSRP) was selected for further exploration. KSRP was significantly upregulated in osteosarcoma cells compared to osteoblasts using western blot assay. In addition, immunohistochemistry demonstrated that KSRP was also highly expressed in osteosarcoma tissue of independent cases from the experimental group. More importantly, KSRP silencing of osteosarcoma cell lines significantly decreased cell proliferation, migration ability, as well as implantation and growth ability in chick chorioallantoic membrane assay. Taken together, these findings demonstrate, that KSRP plays important roles in regulatory controls of osteosarcoma pathogenesis and serves as a potentially therapeutic target of osteosarcoma.

Tumor promotion by γ and suppression by β non-muscle actin isoforms

Here we have shown that β-cytoplasmic actin acts as a tumor suppressor, inhibiting cell growth and invasion in vitro and tumor growth in vivo. In contrast, γ-cytoplasmic actin increases the oncogenic potential via ERK1/2, p34-Arc, WAVE2, cofilin1, PP1 and other regulatory proteins. There is a positive feedback loop between γ-actin expression and ERK1/2 activation. We conclude that non-muscle actin isoforms should not be considered as merely housekeeping proteins and the β/γ-actins ratio can be used as an oncogenic marker at least for lung and colon carcinomas. Agents that increase β- and/or decrease γ-actin expression may be useful for anticancer therapy.

Increased cathepsin D protein expression is a biomarker for osteosarcomas, pulmonary metastases and other bone malignancies

Cancer proteomics provide a powerful approach to identify biomarkers for personalized medicine. Particularly, biomarkers for early detection, prognosis and therapeutic intervention of bone cancers, especially osteosarcomas, are missing. Initially, we compared two-dimensional gel electrophoresis (2-DE)-based protein expression pattern between cell lines of fetal osteoblasts, osteosarcoma and pulmonary metastasis derived from osteosarcoma. Two independent statistical analyses by means of PDQuest® and SameSpot® software revealed a common set of 34 differentially expressed protein spots (p < 0.05). 17 Proteins were identified by mass spectrometry and subjected to Ingenuity Pathway Analysis resulting in one high-ranked network associated with Gene Expression, Cell Death and Cell-To-Cell Signaling and Interaction. Ran/TC4-binding protein (RANBP1) and Cathepsin D (CTSD) were further validated by Western Blot in cell lines while the latter one showed higher expression differences also in cytospins and in clinical samples using tissue microarrays comprising osteosarcomas, metastases, other bone malignancies, and control tissues. The results show that protein expression patterns distinguish fetal osteoblasts from osteosarcomas, pulmonary metastases, and other bone diseases with relevant sensitivities between 55.56% and 100% at ≥87.50% specificity. Particularly, CTSD was validated in clinical material and could thus serve as a new biomarker for bone malignancies and potentially guide individualized treatment regimes.

Quantitative proteomic study of human prostate cancer cells with different metastatic potentials

Metastatic dissemination is a feature of most cancers including prostate cancer (PCa), and is the main cause of treatment failure and mortality. The aim of the study is to explore the mechanisms of PCa metastasis and to search for potential prognostic markers using proteomics. Two-dimensional fluorescent differential gel electrophoresis (2D-DIGE) was used to quantify proteins in normal prostate epithelial cells, bone metastasis-derived PC-3 cells, and visceral metastasis-derived PC-3M cells. Metastatic potential was confirmed by flow cytometry, electron microscopy, proliferating cell nuclear antigen assay, and wound healing assay. Differential protein expression was compared between PCa cells with different metastatic potentials (LNcap, DU145, PC-3 and PC-3M) and normal prostate epithelial cells (RWPE-1). Selected candidate proteins in human prostate tissues were analyzed using GOA, UniProt and GeneCards analyses. Eighty-six proteins were differentially expressed between cell lines (>1.5-fold, P<0.05). Among them, twelve proteins were identified by MALDI-TOF-MS. One protein was upregulated in normal prostate epithelial cells, nine proteins were upregulated in PC-3, and two proteins were upregulated in PC-3M. Proteins were divided into five groups according to their functions. The SETDB1 protein was closely associated with the prognosis of PCa. Bioinformatics suggested that SETDB1 might promote PCa bone metastasis through the WNT pathway. In conclusion, SETDB1 might be associated with the development of bone metastases from PCa. Further study is necessary to assess its exact role in PCa.

Biomarkers for Bone Tumors: Discovery from Genomics and Proteomics Studies and Their Challenges

Diagnosis of bone tumor currently relies on imaging and biopsy, and hence, the need to find less invasive ways for its accurate detection. More recently, numerous promising deoxyribonucleic acid (DNA) and protein biomarkers with significant prognostic, diagnostic and/or predictive abilities for various types of bone tumors have been identified from genomics and proteomics studies. This article reviewed the putative biomarkers for the more common types of bone tumors (that is, osteosarcoma, Ewing sarcoma, chondrosarcoma [malignant] and giant cell tumor [benign]) that were unveiled from the studies. The benefits and drawbacks of these biomarkers, as well as the technology platforms involved in the research, were also discussed. Challenges faced in the biomarker discovery studies and the problems in their translation from the bench to the clinical settings were also addressed.

Quantitative proteomic analysis of mitochondria from human ovarian cancer cells and their paclitaxel-resistant sublines

Paclitaxel resistance is a major obstacle for the treatment of ovarian cancer. The chemoresistance mechanisms are partly related to the mitochondria. Identification of the relevant proteins in mitochondria will help in clarifying the possible mechanisms and in selecting effective chemotherapy for patients with paclitaxel resistance. In the present study, mitochondria from two paclitaxel-sensitive human ovarian cancer cell lines (SKOV3 and A2780) and their corresponding resistant cell lines (SKOV3-TR and A2780-TR) were isolated. Guanidine-modified acetyl-stable isotope labeling and liquid chromatography-hybrid linear ion trap Fourier-transform ion cyclotron resonance mass spectrometry (LC-FTICR MS) were performed to find the expressed differential proteins. Comparative proteomic analysis revealed eight differentially expressed proteins in the ovarian cancer cells and their paclitaxel-resistant sublines. Among them, mimitin and 14-3-3 ζ/δ were selected for further research. The effects of mimitin and 14-3-3 ζ/δ were explored using specific siRNA interference in ovarian cancer cell lines and immunohistochemistry in human tissue specimens. The downregulation of mimitin and 14-3-3 ζ/δ using specific siRNA in paclitaxel-resistant ovarian cancer cells led to an increase in the resistance index to paclitaxel. Multivariate analyses demonstrated that lower expression levels of the mimitin and 14-3-3 ζ/δ proteins were positively associated with shorter progression-free survival (PFS) and overall survival (OS) in patients with primary ovarian cancer (mimitin: PFS: P = 0.041, OS: P = 0.003; 14-3-3 ζ/δ: PFS: P = 0.031, OS: P = 0.011). Mimitin and 14-3-3 protein ζ/δ are potential markers of paclitaxel resistance and prognostic factors in ovarian cancer.

Detection of Serum Protein Biomarkers for the Diagnosis and Staging of Hepatoblastoma

The present study aimed to identify serum biomarkers for the detection of hepatoblastoma (HB). Serum samples were collected from 71 HB patients (stage I, n = 19; stage II, n = 19, stage III, n = 19; and stage IV, n = 14) and 23 age- and sex-matched healthy children. Differential expression of serum protein markers were screened using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS), and the target proteins were isolated and purified using HPLC and identified using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS), SEQUEST, and bioinformatics analysis. Differential protein expression was confirmed by enzyme-linked immunosorbent analysis (ELISA). SELDI-TOF-MS screening identified a differentially expressed protein with an m/z of 9348 Da, which was subsequently identified as Apo A–I; its expression was significantly lower in the HB group as compared to the normal control group (1546.67 ± 757.81 vs. 3359.21 ± 999.36, respectively; p < 0.01). Although the expression level decreased with increasing disease stage, pair-wise comparison revealed significant differences in Apo A–I expression between the normal group and the HB subgroups (p < 0.01). ELISA verified the reduced expression of Apo A–I in the HB group. Taken together, these results suggest that Apo A–I may represent a serum protein biomarker of HB. Further studies will assess the value of using Apo A–I expression for HB diagnosis and staging.

Integrated Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC) and Isobaric Tags for Relative and Absolute Quantitation (iTRAQ) Quantitative Proteomic Analysis Identifies Galectin-1 as a Potential Biomarker for Predicting Sorafenib Resistance in Liver Cancer

Sorafenib has become the standard therapy for patients with advanced hepatocellular carcinoma (HCC). Unfortunately, most patients eventually develop acquired resistance. Therefore, it is important to identify potential biomarkers that could predict the efficacy of sorafenib. To identify target proteins associated with the development of sorafenib resistance, we applied stable isotope labelling with amino acids in cell culture (SILAC)-based quantitative proteomic approach to analyze differences in protein expression levels between parental HuH-7 and sorafenib-acquired resistance HuH-7 (HuH-7(R)) cells in vitro, combined with an isobaric tags for relative and absolute quantitation (iTRAQ) quantitative analysis of HuH-7 and HuH-7(R) tumors in vivo. In total, 2,450 quantified proteins were identified in common in SILAC and iTRAQ experiments, with 81 showing increased expression (>2.0-fold) with sorafenib resistance and 75 showing decreased expression (<0.5-fold). In silico analyses of these differentially expressed proteins predicted that 10 proteins were related to cancer with involvements in cell adhesion, migration, and invasion. Knockdown of one of these candidate proteins, galectin-1, decreased cell proliferation and metastasis in HuH-7(R) cells and restored sensitivity to sorafenib. We verified galectin-1 as a predictive marker of sorafenib resistance and a downstream target of the AKT/mTOR/HIF-1α signaling pathway. In addition, increased galectin-1 expression in HCC patients' serum was associated with poor tumor control and low response rate. We also found that a high serum galectin-1 level was an independent factor associated with poor progression-free survival and overall survival. In conclusion, these results suggest that galectin-1 is a possible biomarker for predicting the response of HCC patients to treatment with sorafenib. As such, it may assist in the stratification of HCC and help direct personalized therapy.

Zinc finger protein 139 expression in gastric cancer and its clinical significance

AIM: To investigate the expression of zinc finger protein 139 (ZNF139) in gastric cancer (GC), and to analyze its clinical significance.

METHODS: A total of 108 patients who were diagnosed with GC and underwent surgery between January 2005 and March 2007 were enrolled in this study. Gastric tumor specimens and paired tumor-adjacent tissues were collected and paraffin-embedded, and the clinicopathologic characteristics and prognosis were recorded. The expression of ZNF139, Bcl-2, Bax, and caspase-3 were determined by immunohistochemistry, and apoptosis was assessed by terminal deoxynucleotidyl transferase-mediated dUTP-biotin nick end labeling. SPSS 13.0 software was used for data processing and analyses, and significance was determined at P < 0.05.

RESULTS: The expression of ZNF139 was stronger in tumors than in tumor-adjacent tissues (66.67% vs 44.44%; P < 0.01). Overexpression of ZNF139 correlated with tumor differentiation, invasion depth, clinical stage, lymphatic metastasis, and blood vessel invasion (all Ps < 0.05). Patients with overexpression of ZNF139 had a poorer prognosis (P < 0.01), and overexpression of ZNF139 was an independent factor for the prognosis of GC patients by a Cox survival analysis (P = 0.02). A negative relationship between ZNF139 and the apoptosis index was observed (r = -0.686; P < 0.01). The expression of Bcl-2 in GC was stronger than in tumor-adjacent tissues (66.67% vs 41.67%), whereas the expression levels of Bax and caspase-3 were lower in primary tumors (54.63% and 47.22%, respectively) than in tumor-adjacent tissues (73.15% and 73.15%, respectively) (all Ps < 0.05). The expression of ZNF139 negatively correlated with caspase-3 (r = -0.370; P < 0.01). The expressions of Bcl-2 and Bax were also negatively correlated (r = -0.231; P = 0.02). The expressions of caspase-3 and Bax protein were positively correlated (r = 0.217; P = 0.024).

CONCLUSION: ZNF139 is related to clinicopathologic characteristics and prognosis of GC. Furthermore, it is overexpressed and involved in apoptosis in GC tissues by regulating caspase-3.

Differential expression analysis of Golgi apparatus proteomes in hepatocellular carcinomas and the surrounding liver tissues

AIM

Hepatocellular carcinoma (HCC) is the sixth most common malignancy worldwide. Liver is the largest human digestive gland with abundant Golgi apparatus involved in cell division, migration and apoptosis and others.

METHODS

In the present study, Golgi apparatus of HCC and the surrounding liver tissues were isolated by sucrose density gradient centrifugation and identified by electron microscopy and enzymology methods. Using 2-D gel electrophoresis and mass spectrometry, 17 differentially expressed protein of Golgi apparatus in HCC and the surrounding liver tissue were screened and identified in the Mascot database.

RESULTS

Of those differentially expressed proteins, six were upregulated and 11 were downregulated, some of them were related to the biological processes such as protein sorting, glycosylation, cell cycle regulation, transcription regulation and Golgi integrity. One protein, annexin A5, was verified to be upregulated in HCC by western blot.

CONCLUSION

The differentially expressed proteins may provide new insight into HCC biology and potential diagnostic and therapeutic biomarkers.

Proteomics of osteosarcoma

Osteosarcoma (OS) is the most common primary malignant tumor of bone and the third most common cancer in childhood and adolescence. Nowadays, early diagnosis, drug resistance and recurrence of the disease represent the major challenges in OS treatment. Post-genomics, and in particular proteomic technologies, offer an invaluable opportunity to address the level of biological complexity expressed by OS. Although the main goal of OS oncoproteomics is focused on diagnostic and prognostic biomarker discovery, in this review we describe and discuss global protein profiling approaches to other aspects of OS biology and pathophysiology, or to investigate the mechanism of action of chemotherapeutics. In addition, we present proteomic analyses carried out on OS cell lines as in vitro models for studying osteoblastic cell biology and the attractive opportunity offered by proteomics of OS cancer stem cells.

Mass spectrometric identification of ancient proteins as potential molecular biomarkers for a 2000-year-old osteogenic sarcoma

Osteosarcoma is the most common primary malignant tumor of bone usually occurring in young adolescent and children. This disease has a poor prognosis, because of the metastases in the period of tumor progression, which are usually developed previous to the clinical diagnosis. In this paper, a 2000-year-old ancient bone remain with osteogenic sarcoma was analyzed searching for tumor biomarkers which are closely related to this disease. After a specific extraction SDS-PAGE gel electrophoresis followed by tryptic digestion was performed. After the digestion the samples were measured using MALDI TOF/TOF MS. Healthy bone samples from same archaeological site were used as control samples. Our results show that in the pathological skeletal remain several well known tumor biomarkers are detected such as annexin A10, BCL-2-like protein, calgizzarin, rho GTPase-activating protein 7, HSP beta-6 protein, transferrin and vimentin compared to the control samples. The identified protein biomarkers can be useful in the discovery of malignant bone lesions such as osteosarcoma in the very early stage of the disease from paleoanthropological remains.

Proteomic analysis of gingival tissue and alveolar bone during alveolar bone healing

Bone tissue regeneration is orchestrated by the surrounding supporting tissues and involves the build-up of osteogenic cells, which orchestrate remodeling/healing through the expression of numerous mediators and signaling molecules. Periodontal regeneration models have proven useful for studying the interaction and communication between alveolar bone and supporting soft tissue. We applied a quantitative proteomic approach to analyze and compare proteins with altered expression in gingival soft tissue and alveolar bone following tooth extraction. For target identification and validation, hard and soft tissue were extracted from mini-pigs at the indicated times after tooth extraction. From triplicate experiments, 56 proteins in soft tissue and 27 proteins in alveolar bone were found to be differentially expressed before and after tooth extraction. The expression of 21 of those proteins was altered in both soft tissue and bone. Comparison of the activated networks in soft tissue and alveolar bone highlighted their distinct responsibilities in bone and tissue healing. Moreover, we found that there is crosstalk between identified proteins in soft tissue and alveolar bone with respect to cellular assembly, organization, and communication. Among these proteins, we examined in detail the expression patterns and associated networks of ATP5B and fibronectin 1. ATP5B is involved in nucleic acid metabolism, small molecule biochemistry, and neurological disease, and fibronectin 1 is involved in cellular assembly, organization, and maintenance. Collectively, our findings indicate that bone regeneration is accompanied by a profound interaction among networks regulating cellular resources, and they provide novel insight into the molecular mechanisms involved in the healing of periodontal tissue after tooth extraction.

Systems genetic analysis of osteoblast-lineage cells

The osteoblast-lineage consists of cells at various stages of maturation that are essential for skeletal development, growth, and maintenance. Over the past decade, many of the signaling cascades that regulate this lineage have been elucidated; however, little is known of the networks that coordinate, modulate, and transmit these signals. Here, we identify a gene network specific to the osteoblast-lineage through the reconstruction of a bone co-expression network using microarray profiles collected on 96 Hybrid Mouse Diversity Panel (HMDP) inbred strains. Of the 21 modules that comprised the bone network, module 9 (M9) contained genes that were highly correlated with prototypical osteoblast maker genes and were more highly expressed in osteoblasts relative to other bone cells. In addition, the M9 contained many of the key genes that define the osteoblast-lineage, which together suggested that it was specific to this lineage. To use the M9 to identify novel osteoblast genes and highlight its biological relevance, we knocked-down the expression of its two most connected “hub” genes, Maged1 and Pard6g. Their perturbation altered both osteoblast proliferation and differentiation. Furthermore, we demonstrated the mice deficient in Maged1 had decreased bone mineral density (BMD). It was also discovered that a local expression quantitative trait locus (eQTL) regulating the Wnt signaling antagonist Sfrp1 was a key driver of the M9. We also show that the M9 is associated with BMD in the HMDP and is enriched for genes implicated in the regulation of human BMD through genome-wide association studies. In conclusion, we have identified a physiologically relevant gene network and used it to discover novel genes and regulatory mechanisms involved in the function of osteoblast-lineage cells. Our results highlight the power of harnessing natural genetic variation to generate co-expression networks that can be used to gain insight into the function of specific cell-types.

The osteoblast-lineage consists of a range of cells from osteogenic precursors that mature into bone-forming osteoblasts to osteocytes that are entombed in bone. Each cell in the lineage serves a number of distinct and critical roles in the growth and maintenance of the skeleton, as well as many extra-skeletal functions. Over the last decade, many of the major regulatory pathways governing the differentiation and activity of these cells have been discovered. In contrast, little is known regarding the composition or function of gene networks within the lineage. The goal of this study was to increase our understanding of how genes are organized into networks in osteoblasts. Towards this goal, we used microarray gene expression profiles from bone to identify a group of genes that formed a network specific to the osteoblast-lineage. We used the knowledge of this network to identify novel genes that are important for regulating various aspects of osteoblast function. These data improve our understanding of the gene networks operative in cells of the osteoblast-lineage.

Discovery of biomarkers for osteosarcoma by proteomics approaches

Osteosarcomas are the most common malignant bone tumors, and the identification of useful tumor biomarkers and target proteins is required to predict the clinical outcome of patients and therapeutic response as well as to develop novel therapeutic strategies. Global protein expression studies, namely, proteomic studies, can offer important clues to understanding the tumor biology that cannot be obtained by other approaches. These studies, such as two-dimensional gel electrophoresis and mass spectrometry, have provided protein expression profiles of osteosarcoma that can be used to develop novel diagnostic and therapeutic biomarkers, as well as to understand biology of tumor progression and malignancy. In this paper, a brief description of the methodology will be provided followed by a few examples of the recent proteomic studies that have generated new information regarding osteosarcomas.

Screening and identification of lung cancer metastasis-related genes by suppression subtractive hybridization

BACKGROUND AND OBJECTIVE

  Lung cancer metastasis is a complicated process in which multiple stages and multiple genes are involved. There is an urgent need to use new molecular biology techniques to get more systematic information and have a general idea of the molecular events that take place in lung cancer metastasis. The object of this study was to construct the subtracted cDNA libraries of different metastatic potential lung cancer cell lines, NL9980 and L9981, which were established and screened from human lung large cell carcinoma cell line, WCQH-9801.

METHOD

  The forward and reverse subtracted cDNA libraries were constructed in the large cell lung cancer cell lines NL9980 and L9981 with the same heredity background but different metastatic potential, by suppression subtractive hybridization (SSH). The positive clones were preliminarily screened by blue-white colony and precisely identified by PCR. The forward and reverse subtracted libraries were screened and identified by dot blot so as to obtain the clones corresponding to gene segments with differential expression. DNA sequencing was performed to analyze the sequences of differential expression segments, which were then searched and compared using the Basic Local Alignment Search Tool from The National Center for Biotechnology Information NCBI BLAST tools. Quantitative real-time reverse transcription polymerase chain reaction (RT-PCR) and western blotting were performed to confirm the differential expressed genes both on RNA and protein levels.

RESULTS

  The forward and reverse subtracted cDNA libraries of the different large cell lung cancer cell lines with metastatic potential were successfully constructed. With blue-white colony and dot blot, 307 positive clones in the forward subtracted library and 78 positive clones in the reverse subtracted library were obtained. Fifty-five clones were successfully sequenced in the forward subtracted library while 31 clones were successfully sequenced in the reverse subtracted library. One new expressed sequence tag (EST) segment was identified from the reverse subtracted cDNA library and was successfully submitted to GenBank and embodied by GenBank. For the differentially expressed genes between L9981 and NL9980 screened by SSH, four genes, ANXA2, KRT18, ACTG1 was upregulated in L9981 cells compared to NL9980 cells. Annexin A2 (which was encoded by ANXA2), γ-actin (which was encoded by ACTG1), and aldose reductase (which was encoded by AKR1B1) proteins were upregulated in L9981 cells compared to NL9980 cells by western blotting.

CONCLUSION

  The forward and reverse subtracted cDNA libraries of different metastatic potential large cell lung cancer cell lines were successfully constructed by SSH. A series of genes have been screened out to have significantly different expression levels between lung cancer cell lines NL9980 and L9981. A new EST segment that may represent a new metastasis-related gene has been identified. Consistent with the result of SSH, both quantitative real-time RT-PCR and western Blotting confirmed the upregulation of ANXA2, ACTG1 and AKR1B1 in lung cancer cell line L9981 compared with NL9980. These three genes may play important roles in lung cancer metastasis.

Comparative proteomic analysis for the insoluble fractions of colorectal cancer patients

We used label-free quantitative proteomics with the insoluble fractions from colorectal cancer (CRC) patients to gain further insight into the utility of profiling altered protein expression as a potential biomarker for cancer. The insoluble fractions were prepared from paired tumor/normal biopsies from 13 patients diagnosed with CRC (stages I to IV). Fifty-six proteins identified in data pooled from the 13 cases were differentially expressed between the tumor and adjacent normal tissue. The connections between these proteins are involved in reciprocal networks related to tumorigenesis, cancer incidence based on genetic disorder, and skeletal and muscular disorders. To assess their potential utility as biomarkers, the relative expression levels of the proteins were validated using personal proteomics and a heat map to compare five individual CRC samples with five normal tissue samples. Further validation of a panel of proteins (KRT5, JUP, TUBB, and COL6A1) using western blotting confirmed the differential expression. These proteins gave specific network information for CRC, and yielded a panel of novel markers and potential targets for treatment. It is anticipated that the experimental approach described here will increase our understanding of the membrane environment in CRC, which may provide direction for making diagnoses and prognoses through molecular biomarker targeting.

Proteomic technologies for the study of osteosarcoma

Osteosarcoma is the most common primary bone cancer of children and is established during stages of rapid bone growth. The disease is a consequence of immature osteoblast differentiation, which gives way to a rapidly synthesized incompletely mineralized and disorganized bone matrix. The mechanism of osteosarcoma tumorogenesis is poorly understood, and few proteomic studies have been used to interrogate the disease thus far. Accordingly, these studies have identified proteins that have been known to be associated with other malignancies, rather than being osteosarcoma specific. In this paper, we focus on the growing list of available state-of-the-art proteomic technologies and their specific application to the discovery of novel osteosarcoma diagnostic and therapeutic targets. The current signaling markers/pathways associated with primary and metastatic osteosarcoma that have been identified by early-stage proteomic technologies thus far are also described.

Post-genomics of bone metabolic dysfunctions and neoplasias

Post-genomic research on osteoblastic and osteoclastic cells, in contrast to that on many other cell types, has only been undertaken recently. Nevertheless, important information has been gained from these investigations on the mechanisms involved in osteoblast differentiation and on markers relevant for tissue regeneration and therapeutic validation of drugs, hormones and growth factors. These protein indicators may also have a diagnostic and prognostic value for bone dysfunctions and tumors. Some reviews have already focused on the application of transcriptomics and/or proteomics for exploring skeletal biology and related disorders. The main goal of the present review is to systematically summarize the most relevant post-genomic studies on various metabolic bone diseases (osteoporosis, Paget's disease and osteonecrosis), neoplasias (osteosarcoma) and metabolic conditions that indirectly affect bone tissue, such as alkaptonuria.

Plasma membrane proteomic analysis of human osteosarcoma and osteoblastic cells: revealing NDRG1 as a marker for osteosarcoma

Osteosarcoma (OS) is the most common primary malignant bone tumor in children and adolescents. To identify new biomarkers for early diagnosis of OS and novel therapeutic candidates, we carried out a plasma membrane proteomic study based on two-dimensional electrophoresis (2DE). The OS cell line MG-63 and the human osteoblastic cell line hFOB1.19 were adopted as the comparison model. We extracted plasma membrane by aqueous two-phase partition extraction. The proteins were separated through 2DE. We analyzed the differentially expressed proteins by Imagemaster software and then identified them by liquid chromatography-tandem mass spectrometry, and the location and function of differential proteins were searched through the Gene Ontology database. In total, 220 protein spots were separated by 2DE. Seven proteins with more than 2.0-folds of difference were successfully identified from 13 gel spots, with 6 up-regulated and 1 down-regulated. Gene Ontology analysis of the differentially expressed proteins indicated that these proteins were involved in seven kinds of functions including binding, structural, cell motility, receptor activity, electron carrier activity, NADH dehydrogenase (ubiquinone) activity, and transcription repressor activity. The up-regulation of NDRG1 was verified in osteosarcoma through Western blotting and by immunohistochemistry in paraffin-embedded tissues. The plasma membrane proteins identified in this study may provide new insights into osteosarcoma cancer biology and potential diagnostic and therapeutic biomarkers.