Bioinformatics analysis of differentially expressed proteins in prostate cancer based on proteomics data

P300 reduces TUBB4B expression to facilitate the biological process of migration and invasion of non-small cell lung cancer cells

This article explored the mechanism of E1A binding protein p300 (P300) and beta-tubulin 4B isotype-encoding gene (TUBB4B) in regulating the migration and invasion of non-small cell lung cancer (NSCLC) cells. TUBB4B and P300 expression in NSCLC tissues and cells was monitored by real-time quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and Western blot. TUBB4B function on NSCLC cell migration, invasion and epithelial-mesenchymal transition (EMT) was monitored by wound healing assay, Transwell experiment and Western blot. The regulation of P300 on TUBB4B was monitored by qRT-PCR and Western blot. Mechanism of P300 and TUBB4B in regulating NSCLC cell migration and invasion was explored by rescue experiment. A xenograft tumor model was established by using nude mouse. As a result, low TUBB4B expression and high P300 expression was discovered in NSCLC tissues and cells. TUBB4B and P300 expression showed a negative correlation in NSCLC tissues. Lower TUBB4B but higher P300 was observed in tumor tissues of NSCLC patients with metastasis. TUBB4B overexpression suppressed NSCLC cell migration, invasion and EMT. TUBB4B silencing had opposite results. P300 overexpression inhibited TUBB4B expression, and P300 silencing facilitated TUBB4B overexpression in NSCLC cells. TUBB4B overexpression counteracted the promotion of P300 overexpression on NSCLC cell invasion and migration. TUBB4B silencing abrogated the inhibition of P300 knockdown on NSCLC cell invasion and migration. TUBB4B overexpression suppressed NSCLC cell in vivo growth. Thus, TUBB4B could be reduced by P300 in NSCLC. It exerted suppression role on NSCLC cell migration, invasion and EMT. TUBB4B may be a novel target for NSCLC treatment.

Metabolomics and Proteomics in Prostate Cancer Research: Overview, Analytical Techniques, Data Analysis, and Recent Clinical Applications

Prostate cancer (PCa) is a significant global contributor to mortality, predominantly affecting males aged 65 and above. The field of omics has recently gained traction due to its capacity to provide profound insights into the biochemical mechanisms underlying conditions like prostate cancer. This involves the identification and quantification of low-molecular-weight metabolites and proteins acting as crucial biochemical signals for early detection, therapy assessment, and target identification. A spectrum of analytical methods is employed to discern and measure these molecules, revealing their altered biological pathways within diseased contexts. Metabolomics and proteomics generate refined data subjected to detailed statistical analysis through sophisticated software, yielding substantive insights. This review aims to underscore the major contributions of multi-omics to PCa research, covering its core principles, its role in tumor biology characterization, biomarker discovery, prognostic studies, various analytical technologies such as mass spectrometry and Nuclear Magnetic Resonance, data processing, and recent clinical applications made possible by an integrative "omics" approach. This approach seeks to address the challenges associated with current PCa treatments. Hence, our research endeavors to demonstrate the valuable applications of these potent tools in investigations, offering significant potential for understanding the complex biochemical environment of prostate cancer and advancing tailored therapeutic approaches for further development.

Proteomic-based stratification of intermediate-risk prostate cancer patients

Gleason grading is an important prognostic indicator for prostate adenocarcinoma and is crucial for patient treatment decisions. However, intermediate-risk patients diagnosed in the Gleason grade group (GG) 2 and GG3 can harbour either aggressive or non-aggressive disease, resulting in under- or overtreatment of a significant number of patients. Here, we performed proteomic, differential expression, machine learning, and survival analyses for 1,348 matched tumour and benign sample runs from 278 patients. Three proteins (F5, TMEM126B, and EARS2) were identified as candidate biomarkers in patients with biochemical recurrence. Multivariate Cox regression yielded 18 proteins, from which a risk score was constructed to dichotomize prostate cancer patients into low- and high-risk groups. This 18-protein signature is prognostic for the risk of biochemical recurrence and completely independent of the intermediate GG. Our results suggest that markers generated by computational proteomic profiling have the potential for clinical applications including integration into prostate cancer management.

Association between Expression of Connective Tissue Genes and Prostate Cancer Growth and Progression

To find an association between genomic features of connective tissue and pejorative clinical outcomes on radical prostatectomy specimens. We performed a retrospective analysis of patients who underwent radical prostatectomy and underwent a Decipher transcriptomic test for localized prostate cancer in our institution (n = 695). The expression results of selected connective tissue genes were analyzed after multiple t tests, revealing significant differences in the transcriptomic expression (over- or under-expression). We investigated the association between transcript results and clinical features such as extra-capsular extension (ECE), clinically significant cancer, lymph node (LN) invasion and early biochemical recurrence (eBCR), defined as earlier than 3 years after surgery). The Cancer Genome Atlas (TCGA) was used to evaluate the prognostic role of genes on progression-free survival (PFS) and overall survival (OS). Out of 528 patients, we found that 189 had ECE and 27 had LN invasion. The Decipher score was higher in patients with ECE, LN invasion, and eBCR. Our gene selection microarray analysis showed an overexpression in both ECE and LN invasion, and in clinically significant cancer for COL1A1, COL1A2, COL3A1, LUM, VCAN, FN1, AEBP1, ASPN, TIMP1, TIMP3, BGN, and underexpression in FMOD and FLNA. In the TCGA population, overexpression of these genes was correlated with worse PFS. Significant co-occurrence of these genes was observed. When presenting overexpression of our gene selection, the 5-year PFS rate was 53% vs. 68% (p = 0.0315). Transcriptomic overexpression of connective tissue genes correlated to worse clinical features, such as ECE, clinically significant cancer and BCR, identifying the potential prognostic value of the gene signature of the connective tissue in prostate cancer. TCGAp cohort analysis showed a worse PFS in case of overexpression of the connective tissue genes.

A Boolean-based machine learning framework identifies predictive biomarkers of HSP90-targeted therapy response in prostate cancer

Precision medicine has emerged as an important paradigm in oncology, driven by the significant heterogeneity of individual patients' tumour. A key prerequisite for effective implementation of precision oncology is the development of companion biomarkers that can predict response to anti-cancer therapies and guide patient selection for clinical trials and/or treatment. However, reliable predictive biomarkers are currently lacking for many anti-cancer therapies, hampering their clinical application. Here, we developed a novel machine learning-based framework to derive predictive multi-gene biomarker panels and associated expression signatures that accurately predict cancer drug sensitivity. We demonstrated the power of the approach by applying it to identify response biomarker panels for an Hsp90-based therapy in prostate cancer, using proteomic data profiled from prostate cancer patient-derived explants. Our approach employs a rational feature section strategy to maximise model performance, and innovatively utilizes Boolean algebra methods to derive specific expression signatures of the marker proteins. Given suitable data for model training, the approach is also applicable to other cancer drug agents in different tumour settings.

Proteomic Analysis of Prostate Cancer FFPE Samples Reveals Markers of Disease Progression and Aggressiveness

Simple Summary

Prostate cancer (PCa) is the second most frequently diagnosed type of cancer in men. The lack of tools for accurate risk assessment is causing over-treatment of men with indolent PCa but also delayed detection of metastatic disease and thus high mortality. The aim of our study was to identify proteins related to the progression and aggressiveness of PCa that could serve as potential biomarkers for better risk stratification. To this end, we performed proteomic analysis of Formalin Fixed Paraffin Embedded (FFPE) prostate tissue specimens (n = 86) and compared them based on grade groups and biochemical recurrence status. Based on the valuable data generated by these comparisons, we have selected seven proteins (NMP1, UQCRH, HSPA9, MRPL3, VCAN, SERBP1, HSPE1) as common denominators of PCa aggressiveness and persistence that could potentially be used for the development of risk assessment tools. Notably, our observations are largely validated by transcriptomics data and literature.

Abstract

Prostate cancer (PCa) is the second most common cancer in men. Diagnosis and risk assessment are widely based on serum Prostate Specific Antigen (PSA) and biopsy, which might not represent the exact degree of PCa risk. Towards the discovery of biomarkers for better patient stratification, we performed proteomic analysis of Formalin Fixed Paraffin Embedded (FFPE) prostate tissue specimens using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). Comparative analysis of 86 PCa samples among grade groups 1–5 identified 301 significantly altered proteins. Additional analysis based on biochemical recurrence (BCR; BCR+ n = 14, BCR- n = 51) revealed 197 significantly altered proteins that indicate disease persistence. Filtering the overlapping proteins of these analyses, seven proteins (NPM1, UQCRH, HSPA9, MRPL3, VCAN, SERBP1, HSPE1) had increased expression in advanced grades and in BCR+/BCR- and may play a critical role in PCa aggressiveness. Notably, all seven proteins were significantly associated with progression in Prostate Cancer Transcriptome Atles (PCTA) and NPM1NPM1, UQCRH, and VCAN were further validated in The Cancer Genome Atlas (TCGA), where they were upregulated in BCR+/BCR-. UQCRH levels were also associated with poorer 5-year survival. Our study provides valuable insights into the key regulators of PCa progression and aggressiveness. The seven selected proteins could be used for the development of risk assessment tools.

Tubulin TUBB4B Is Involved in Spermatogonia Proliferation and Cell Cycle Processes

Tubb4b (tubulin β-4b chain) is essential for cell growth and development as a microtubule network protein. Previous studies have shown that TUBB4B affects mouse pronucleus migration, but the gene function has yet to be elucidated. To study TUBB4B-related functions in mouse reproductive development, we designed a single sgRNA in chromosome 2 and generated a knockout spermatogonia cell line of the β-tubulin isoform Tubb4b by the CRISPR/Cas9 system. Tubb4b-KO spermatogonia recognized abnormal lysosomal membranes and cell morphology defects. Compared to control mouse spermatogonia, the proliferation rate was significantly slower and cycling stagnated in the G1/0 population. Although spermatogonia lacking TUBB4B have abnormal divisions, they are not lethal. We detected the mRNA levels of the cell-regulating cyclins CyclinsD1, CyclinsE, Cdk2, Cdk4, P21, Skp2 and the cell growth factors C/EBP α, C/EBP β, and G-CSF in the spermatogonia of Tubb4b-KO and found that the expressions of CyclinsD1, Skp2 and cell growth factors were significantly reduced. Further analysis revealed that 675 genes were expressed differently after Tubb4b deletion and were enriched in negative regulation of cell population proliferation (GO:0008285), negative regulation of cell cycle G2/M phase transition (GO:1902750), and positive regulation of cell death (GO: 0010942). We also found that there is a common gene Cdkn1a (P21) in these three GO pathways related to cell proliferation and cell cycle, and both quantitative analysis and transcriptome sequencing results showed that the expression of this gene was up-regulated in Tubb4b knockout cells. This implies that Tubb4b may be involved in the division of spermatogonia with multiple cell cycle regulatory proteins. Overall, these data indicate that Tubb4b has a specific role in regulating spermatogonia proliferation and cell cycle.

Comparative Proteomic Analysis Reveals Novel Biomarkers for Gastric Cancer in South Indian Tamil Population

BACKGROUND

Gastric cancer (GC) remains a major global health problem due to a poor understanding of its progression at the molecular level and a lack of early detection or diagnosis. Early detection is highly crucial for improving prognosis. The incidence of GC is very high in countries like India due to the limitations among the established biomarkers for GC owing to poor sensitivity and specificity.

OBJECTIVE

To identify the novel biomarkers from serum samples obtained from GC patients when compared with healthy subjects.

METHODS

Serum samples from GC patients were analyzed by two-dimensional gel electrophoresis (2DGE) coupled with tandem mass spectrometry (MS), including both matrix-assisted laser desorption/ionization-time of flight (MALDI-ToF) and liquid chromatography-MS (LC-MS/MS) analysis. Identified proteins were further analyzed by gene ontology and protein interaction studies.

RESULTS

A total of 73 protein spots were detected in 2DGE image analysis. Among them, seven differentially-expressed proteins were identified using MS analyses, which included serotransferrin/transferrin, albumin, ceruloplasmin, C-reactive protein (CRP), fibrinogen γ-chain (FGG), and two unreported novel proteins, immunoglobulin kappa constant (IgκC) region and Homo sapiens zinc finger protein 28 (ZNF28) homolog. Among these proteins, serotransferrin, albumin, ceruloplasmin, FGG, and ZNF28 were down-regulated in GC samples (p < 0.05), while IgκC region and CRP were up-regulated significantly.

CONCLUSION

Most of the differentially expressed proteins were involved in angiogenesis, plasminogen-activating cascade, and blood coagulation pathways which are known to play a critical role in gastric tumorigenesis. Our current results provide a panel of candidate biomarkers for GC with novel biomarkers which were not reported earlier.

Distinct roles for the RNA-binding protein Staufen1 in prostate cancer

BACKGROUND

Prostate cancer is one of the most common malignant cancers with the second highest global rate of mortality in men. During the early stages of disease progression, tumour growth is local and androgen-dependent. Despite treatment, a large percentage of patients develop androgen-independent prostate cancer, which often results in metastases, a leading cause of mortality in these patients. Our previous work on the RNA-binding protein Staufen1 demonstrated its novel role in cancer biology, and in particular rhabdomyosarcoma tumorigenesis. To build upon this work, we have focused on the role of Staufen1 in other forms of cancer and describe here the novel and differential roles of Staufen1 in prostate cancer.

METHODS

Using a cell-based approach, three independent prostate cancer cell lines with different characteristics were used to evaluate the expression of Staufen1 in human prostate cancer relative to control prostate cells. The functional impact of Staufen1 on several key oncogenic features of prostate cancer cells including proliferation, apoptosis, migration and invasion were systematically investigated.

RESULTS

We show that Staufen1 levels are increased in all human prostate cancer cells examined in comparison to normal prostate epithelial cells. Furthermore, Staufen1 differentially regulates growth, migration, and invasion in the various prostate cancer cells assessed. In LNCaP prostate cancer cells, Staufen1 regulates cell proliferation through mTOR activation. Conversely, Staufen1 regulates migration and invasion of the highly invasive, bone metastatic-derived, PC3 prostate cells via the activation of focal adhesion kinase.

CONCLUSIONS

Collectively, these results show that Staufen1 has a direct impact in prostate cancer development and further demonstrate that its functions vary amongst the prostate cancer cell types. Accordingly, Staufen1 represents a novel target for the development of much-needed therapeutic strategies for prostate cancer.

Bioinformatic analysis of dysregulated proteins in prostate cancer patients reveals putative urinary biomarkers and key biological pathways

Prostate cancer (PCa) is one of the most common cancer types among men. The quantification of prostate-specific antigen used for PCa detection has revealed limited applicability. Thus, it is crucial to identify new minimally invasive biomarkers for PCa. It is believed that the integration of proteomics data from different studies is vital for identifying new biomarkers for PCa, but studies carried out in this regard have few converging results. Using a different approach, this study aimed to unveil molecular features consistently dysregulated in PCa and potential urinary biomarkers for PCa. The novelty of this analysis relies on the comparison of urinary and tissue proteomes from PCa patients and consequent exclusion of kidney and bladder cancer interference. The conducted bioinformatic analysis revealed molecular processes dysregulated in urine from PCa patients that mirror the alterations in prostate tumor tissue. To identify putative urinary biomarkers, proteins previously detected in kidney and bladder tissues were eliminated from the final list of potential urinary biomarkers for PCa. After a detailed analysis, MSMB, KLK3, ITIH4, ITIH2, HPX, GP2, APOA2 and AZU1 proteins stood out as candidate urinary biomarkers for PCa.

The mechanobiome: a goldmine for cancer therapeutics

Cancer progression is dependent on heightened mechanical adaptation, both for the cells' ability to change shape and to interact with varying mechanical environments. This type of adaptation is dependent on mechanoresponsive proteins that sense and respond to mechanical stress, as well as their regulators. Mechanoresponsive proteins are part of the mechanobiome, which is the larger network that constitutes the cell's mechanical systems that are also highly integrated with many other cellular systems, such as gene expression, metabolism, and signaling. Despite the altered expression patterns of key mechanobiome proteins across many different cancer types, pharmaceutical targeting of these proteins has been overlooked. Here, we review the biochemistry of key mechanoresponsive proteins, specifically nonmuscle myosin II, α-actinins, and filamins, as well as the partnering proteins 14-3-3 and CLP36. We also examined a wide range of data sets to assess how gene and protein expression levels of these proteins are altered across many different cancer types. Finally, we determined the potential of targeting these proteins to mitigate invasion or metastasis and suggest that the mechanobiome is a goldmine of opportunity for anticancer drug discovery and development.

A modern era of personalized medicine in the diagnosis, prognosis, and treatment of prostate cancer

The present era is witnessing rapid advancements in the field of medical informatics and modern healthcare management. The role of translational bioinformatics (TBI), an infant discipline in the field of medical informatics, is pivotal in this revolution. The development of high-throughput technologies [e.g., microarrays, next-generation sequencing (NGS)] has propelled TBI to the next stage in this modern era of medical informatics. In this review, we assess the promising translational outcomes of microarray- and NGS-based discovery of genes, proteins, micro RNAs, and other active biological compounds aiding in the diagnosis, prognosis, and therapy of prostate cancer (PCa) to improve treatment strategies at the localized and/or metastatic stages in patients. Several promising candidate biomarkers in circulating blood (miR-25-3p and miR-18b-5p), urine (miR-95, miR-21, miR-19a, and miR-19b), and prostatic secretions (miR-203) have been identified. AURKA and MYCN, novel candidate biomarkers, were found to be specifically expressed in neuroendocrine PCa. The use of BTNL2 gene mutations and inflammasomes as biomarkers in immune function-mediated, inherited PCa has also been elucidated based on NGS data. Although TBI discoveries can benefit clinical performance metrics, the translational potential and the in vivo performance of TBI outcomes need to be verified. In conclusion, TBI aids in the effective clinical management of PCa; furthermore, the fate of personalized/precision medicine mostly relies on the enhanced diagnostic, prognostic, and therapeutic potential of TBI.

Identification of β tubulin IVb as a pattern recognition receptor with opsonic activity

Previous studies have shown that tubulins play important role in immune responses of both plants and animals, but no experiments have been performed to study the mode of action of tubulins in immune defense. In addition, there is little convincing experimental evidence of functional commitment for specific tubulin isotypes in animals. In the present, we showed that expression of β-tubulin IVb gene was affected by both LPS and LTA, hinting its involvement in anti-infectious response. We also showed that recombinant zebrafish β-tubulin IVb not only interacted with LPS and LTA as well as Gram-negative and -positive bacteria but also agglutinated both Gram-negative and -positive bacteria in a Ca²⁺-dependent fashion. Interestingly, recombinant β-tubulin IVb could enhance the phagocytosis of bacteria by macrophages. Moreover, we demonstrated that β-tubulin IVb was present extracellularly in the serum of zebrafish and mouse. Collectively, these suggest that β-tubulin IVb may be physiologically involved in the systematic immunity of host via acting as a pattern recognition receptor and an opsonin. This also provides a new angle to understand the roles of β-tubulin IVb.

Identification of Novel Prognosis and Prediction Markers in Advanced Prostate Cancer Tissues Based on Quantitative Proteomics

BACKGROUND/AIM

Prostate cancer (PCa) is the most frequent cancer found in males worldwide, and its mortality rate is increasing every year. However, there are no known molecular markers for advanced or aggressive PCa, and there is an urgent clinical need for biomarkers that can be used for prognosis and prediction of PCa.

MATERIALS AND METHODS

Mass spectrometry-based proteomics was used to identify new biomarkers in tissues obtained from patients with PCa who were diagnosed with T2, T3, or metastatic PCa in regional lymph nodes.

RESULTS

Among 1,904 proteins identified in the prostate tissues, 344 differentially expressed proteins were defined, of which 124 were up-regulated and 216 were down-regulated. Subsequently, based on the results of partial least squares discriminant analysis and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses, we proposed that spermidine synthase (SRM), nucleolar and coiled-body phosphoprotein 1 (NOLC1), and prostacyclin synthase (PTGIS) represent new protein biomarkers for diagnosis of advanced PCa. These proteomics results were verified by immunoblot assays in metastatic PCa cell lines and by indirect enzyme-linked immunosorbent assay in prostate specimens.

CONCLUSION

SRM was significantly increased depending on the cancer stage, confirming the possibility of using SRM as a biomarker for prognosis and prediction of advanced PCa.

FGB and FGG derived from plasma exosomes as potential biomarkers to distinguish benign from malignant pulmonary nodules

Previous proteomic analysis (label-free) of plasma exosomes revealed that the expression of FGG and FGB was significantly higher in the malignant pulmonary nodules group, compared to the benign pulmonary nodules group. The present study was performed to evaluate the role of plasma exosomal proteins FGB and FGG in the diagnosis of benign and malignant pulmonary nodules. We examined the expression levels of FGB and FGG in plasma exosomes from 63 patients before surgery. Postoperative pathological diagnosis confirmed that 43 cases were malignant and 20 cases were benign. The ROC curve was used to describe the sensitivity, specificity, area under the curve (AUC) of the biomarker and the corresponding 95% confidence interval. We confirmed that the expression levels of FGB and FGG were higher in the plasma exosomes of malignant group than in the benign group. The sensitivity and AUC of FGB combined with FGG detection to determine the nature of pulmonary nodules are superior to single FGB or FGG detection. FGB and FGG might represent novel and sensitive biomarker to distinguish benign from malignant pulmonary nodules.

Glycopatterns and Glycoproteins Changes in MCN and SCN: A Prospective Cohort Study

Background. Advances in imaging improve the detection of malignant pancreatic cystic including mucinous cystic neoplasm (MCN), intraductal papillary mucinous neoplasm (IPMN), and mucinous cystic adenocarcinoma (MCA), but the distinction between benign and malignant lesions remains a problem. In an effort to establish glycopatterns as potential biomarkers for differential diagnosis between MCN and SCN, we systematically investigated the alterations of glycopatterns in cystic fluids for both SCN and MCN. Methods. Among the 75 patients enrolled, 37 were diagnosed as MCN and 38 as SCN based on histology. Lectin microarray analysis was performed on each sample, and the fluorescence intensity was used to obtain the fold-change. Then, mixed cyst fluids of MCN group and SCN group were cross bonded with magnetic particles coupled by Lectin STL and WGA, respectively. Hydrophilic interaction liquid chromatography (HILIC) enrichment was performed, liquid chromatography (LC)/mass spectrometry (MS) analysis and bioinformatical analysis was conducted to find the differential glycoproteins between MCNs and SCNs. Results. Through analysis of lectin microarray between MCNs and SCNs, stronger lectin signal patterns were assigned to Lectin WFA, DBA, STL, WGA, and BPL; and weaker signal patterns were assigned to Lectin PTL-I, Con A, ACA, and MAL-I. The glycoproteins were enriched by STL or WGA-coupled magnetic particles. Furthermore, the 10 identified correspondding genes were found to be significantly elevated in the mucinous cystadenoma: CLU, A2M, FGA, FGB, FGG, PLG, SERPINA1, SERPING1, C5, C8A, and C9. Bioinformatics analysis revealed that the above genes may activate the KEGG pathway: immune complement system. Conclusion. This study shows changes in glycopatterns and glycoproteins are associated with MCNs and SCNs.

Identification of the Altered Proteins Related to Colon Carcinogenesis by iTRAQ-based Quantitative Proteomic Analysis

Background:

The molecular mechanisms or valuable biomarkers for early diagnosis of colorectal cancer (CRC) are not fully elucidated yet.

Objective:

To understand the proteomic changes at the global level in the carcinogenesis of CRC, differentially expressed proteins between normal intestinal epithelial cells CCD841 and colorectal cancer cells HCT116 were identified.

Method:

The isobaric tags for relative and absolute quantitation (iTRAQ) coupled with 2D LC-MS/MS proteomic approach were performed for screening the altered proteins between cells CCD841 and HCT116.

Results:

A total of 1947 proteins were identified after filtering and using a 1% false discovery rate. Based on a final cutoff (> 3.16 and < 0.32), 229 proteins were found to be significantly altered, among which 95 (41%) were up-regulated while 134 (59%) were down-regulated. Gene Ontology analysis revealed that the differentially expressed proteins were mainly cell part proteins involved in cellular process and binding in terms of subcellular distribution, biological process, and molecular function. KEGG analysis indicated that the differentially expressed proteins were significantly involved in the process of focal adhesion, pathogenic Escherichia coli infection, leukocyte transendothelial migration, bacterial invasion of epithelial cells, regulation of actin cytoskeleton, DNA replication and so on.

Conclusion:

Collectively, our data identified differentially expressed proteins in colon cancer carcinogenesis, which could provide the clues on unraveling the molecular mechanism of CRC.

Long non-coding RNA MEG3 suppresses the development of bladder urothelial carcinoma by regulating miR-96 and TPM1

We aimed at investigating effects of long non-coding RNA maternally expressed 3 (MEG3) on the proliferation, cell cycle and apoptosis of bladder urothelial carcinoma cells and regulatory relationships among lncRNA MEG3, miR-96 and α-tropomyosin 1 (TPM1). Human clinical data from The Cancer Genome Atlas (TCGA) which contains bladder urothelial carcinoma tissues and adjacent tissues were used for analysis. The expression profiles of MEG3, miR-96, TPM1, cell cycle-related genes and apoptosis-related genes were examined by real-time quantitative polymerase chain reaction (RT-qPCR) and western blot. Regulating relationship among MEG3, miR-96 and TPM1 was confirmed by dual luciferase reporter assay. MTT assay and flow cytometry were performed to observe cell proliferation, cell cycle and apoptosis. The effects of lncRNA MEG3 on bladder urothelial carcinoma were confirmed both in vivo and in vitro. The mRNA expression and protein expression of MEG3, TPM1 were down-regulated in carcinoma tissues, whereas miR-96 expression was up-regulated. MEG3 overexpression resulted in miR-96 downregulation along with TPM1 upregulation, which inhibited cell proliferation and cell cycle but promoted cell apoptosis of bladder urothelial carcinoma cells in vitro, and at the same time inhibited tumor growth in vivo. In this process, expressions of apoptosis-related protein BCL2 associated X (Bax), cleaved-caspase 3 was up-regulated, whereas apoptosis regulator protein (Bcl-2) expression was suppressed when MEG3 was overexpressed, and cell cycle-related protein Cyclin D1 was down-regulated. LncRNA MEG3 low-expression promotes the proliferation and inhibits apoptosis of bladder urothelial carcinoma cells by regulating miR-96 along with TPM1.

Novel prognostic biomarkers of gastric cancer based on gene expression microarray: COL12A1, GSTA3, FGA and FGG

Gastric cancer (GC) is the fifth most common malignancy and the third leading cause of cancer-associated mortality in the world. However, its mechanisms of occurrence and development have not been clearly elucidated. Furthermore, there is no effective tumor marker for GC. Using DNA microarray analysis, the present study revealed genetic alterations, screened out core genes as novel markers and discovered pathways for potential therapeutic targets. Differentially expressed genes (DEGs) between GC and adjacent normal tissues were identified, followed by pathway enrichment analysis of DEGs. Next, the protein-protein interaction (PPI) network of DEGs was built and visualized. Analyses of modules in the PPI network were then performed to identify the functional core genes. Finally, survival analysis of core genes was conducted. A total of 256 genes were identified as DEGs between the GC samples and normal samples, including 169 downregulated and 87 upregulated genes. Through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, the present study identified a total of 143 GO terms and 21 pathways. Six clusters of functional modules were identified, and the genes associated with these modules were screened out as the functional core genes. Certain core genes, including collagen type 12 α1 chain (COL12A1), glutathione S-transferase α3 (GSTA3), fibrinogen α chain (FGA) and fibrinogen γ chain (FGG), were the first reported to be associated with GC. Survival analysis suggested that these four genes, COL12A1 (P=0.002), GSTA3 (P=3.4×10⁻⁶), FGA (P=0.00075) and FGG (P=1.4×10-5), were significant poor prognostic factors and therefore, potential targets to improve diagnosis, optimize chemotherapy and predict prognostic outcomes.

Prostate cancer proteomics: clinically useful protein biomarkers and future perspectives

INTRODUCTION

Although prostate cancer constitutes one of the most important, death-related diseases in the male population, there is still a need for identification of sensitive biomarkers that could precociously detect the disease and differentiate aggressive from indolent cancers, in order to decrease overtreatment. Proteomics research has improved understanding on mechanisms underlying tumorigenesis, cancer cells migration and invasion potential, and castration resistance. This review has focused on proteomic studies of prostate cancer published in the recent years, with a special emphasis on determination of biomarkers for cancer progression and diagnosis. Areas covered: Shotgun and targeted-proteomic studies of prostate cancer in different matrices are reviewed, i.e., prostate tissue, prostate cell lines, blood (serum and plasma), urine, seminal plasma, and exosomes. The most important biomarkers for cancer diagnosis and aggressiveness characterization are highlighted. Expert commentary: In general, results demonstrate alteration in cell cycle control, DNA repair, proteasomal degradation, and metabolic activity. However, these studies suffer from low reproducibility due to heterogeneity of the cancer itself, as well as to techniques utilized for protein identification/quantification. Downstream confirmatory studies in separate cohorts are warranted in order to demonstrate accuracy of these results.

Tropomyosin-1 acts as a potential tumor suppressor in human oral squamous cell carcinoma

It is widely accepted that oral squamous cell carcinoma (OSCC) is a major contributor to the incidence and mortality of neck and head cancer. Tropomyosin-1 (TPM1), which is expressed at a low level, has been considered a prominent tumor-suppressing gene in a variety of solid tumors, although the precise mechanism of the TPM1 gene in OSCC progression remains unknown. We found that TPM1 expression levels decreased in OSCC patients and OSCC cell lines. The overall and cancer-specific survival of patients who exhibited low TPM1 levels were inferior to those of patients who had high TPM1 levels. It was also found that OSCC patients who suffered from disease stageⅠ-Ⅱ were more likely to have an up-regulated TPM1 expression level, and OSCC patients with lymph node metastasis had a higher probability of exhibiting reduced TPM1 expression. We show that overexpression of TPM1 can promote cell apoptosis and inhibit migration. Our results suggest that TPM1 can suppress tumors in OSCC, and the TPM1 expression level is related to OSCC patient prognosis.