Clinicopathological and prognostic significance of osteopontin expression in patients with prostate cancer: a systematic review and meta-analysis

Prognostic and clinicopathological value of osteopontin expression in non-small cell lung cancer: a meta-analysis and systematic review

BACKGROUND

Although Osteopontin (OPN) has been reported to be associated with many different human cancers, the data on non-small cell lung cancer (NSCLC) are not definitive. This study aimed to explore the prognostic effect of OPN expression and clinicopathological characteristics in patients with NSCLC.

METHODS

This study followed all aspects of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) report. PubMed, Embase and the Cochrane Library were searched to identify the relative studies. The pooled hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated to estimate the prognostic value of the OPN in patients with NSCLC. The odds ratio (OR) was calculated to represent the relationship between OPN expression and clinicopathological parameters.

RESULTS

A total of fifteen studies with 2173 participants were finally included. The results revealed that high expression of OPN was significantly associated with poorer overall survival (OS) (HR = 1.89; 95%CI = 1.68-2.11; p < 0.001). Moreover, a significant correlation was observed between increased OPN expression and poorly differentiated (well and moderately differentiated vs. poorly differentiated; pooled OR = 0.38; 95% CI = 0.23-0.64; p < 0.001), lymph node metastasis (absence vs. presence; pooled OR = 0.49; 95%CI = 0.32-0.74; p < 0.001), and distant metastasis (absence vs. presence; pooled OR = 0.18; 95%CI = 0.11-0.29; p < 0.001).

CONCLUSION

This meta-analysis implies that OPN might be a valuable biomarker for a poor prognosis and poor clinicopathological outcomes for patients with NSCLC.

The Potential of Extracellular Matrix- and Integrin Adhesion Complex-Related Molecules for Prostate Cancer Biomarker Discovery

Prostate cancer is among the top five cancer types according to incidence and mortality. One of the main obstacles in prostate cancer management is the inability to foresee its course, which ranges from slow growth throughout years that requires minimum or no intervention to highly aggressive disease that spreads quickly and resists treatment. Therefore, it is not surprising that numerous studies have attempted to find biomarkers of prostate cancer occurrence, risk stratification, therapy response, and patient outcome. However, only a few prostate cancer biomarkers are used in clinics, which shows how difficult it is to find a novel biomarker. Cell adhesion to the extracellular matrix (ECM) through integrins is among the essential processes that govern its fate. Upon activation and ligation, integrins form multi-protein intracellular structures called integrin adhesion complexes (IACs). In this review article, the focus is put on the biomarker potential of the ECM- and IAC-related molecules stemming from both body fluids and prostate cancer tissue. The processes that they are involved in, such as tumor stiffening, bone turnover, and communication via exosomes, and their biomarker potential are also reviewed.

Entrectinib a Plausible Inhibitor for Osteopontin (SPP1) in Cervical Cancer-Integrated Bioinformatic Approach

Cervical cancer is one of the major causes of death in women, especially in developing countries bearing more than a quarter of the global burden. Secreted phosphoprotein-1, also known as OPN (osteopontin), is an integrin-binding glycophosphoprotein that is overexpressed in a variety of tumors. OPN is a chemokine-like calcified ECM-associated protein that plays a crucial role in evaluating the metastatic potential of various cancers. However, the role of SPP1 in the tumor microenvironment and associated signaling pathways in CC is still unclear. In our study, three CC microarray datasets (GSE9750, GSE46857, and GSE67522) were obtained from the GEO database to identify the differentially expressed genes. Enrichment analysis was carried out by Enrichr and ShinyGO and the PPI interaction network was created by using String and Cytoscape. GEPIA datasets were used to validate the top 10 hub genes, and virtual screening, docking, and dynamic simulation studies were used to identify a suitable inhibitor against the OPN protein using MVD, PyRx, and GROMACS respectively. Our results show that a total of 11 DEGs were common for three datasets and gene ontology pathway enrichment analysis revealed that 2 biological processes i.e. programmed cell death and animal organ development commonly affected mechanisms in all three datasets. Docking and dynamic studies revealed that Entrectinib showed excellent binding affinity against OPN protein. Based on the results, we conclude that OPN is one of the most upregulated genes in cervical cancer and Entrectinib emerges to be a promising potential OPN inhibitor to curtail cervical cancer progression. Schematic representation: The schematic representation of methodology steps is illustrated in the graphical abstract. Schematic representation of methodology.

Biomarkers for Prostate Cancer Bone Metastasis Detection and Prediction

Prostate cancer (PCa) causes deaths worldwide, ranking second after lung cancer. Bone metastasis (BM) frequently results from advanced PCa, affecting approximately 90% of patients, and it also often results in severe skeletal-related events. Traditional diagnostic methods for bone metastases, such as tissue biopsies and imaging, have substantial drawbacks. This article summarizes the significance of biomarkers in PCa accompanied with BM, including (1) bone formation markers like osteopontin (OPN), pro-collagen type I C-terminal pro-peptide (PICP), osteoprotegerin (OPG), pro-collagen type I N-terminal pro-peptide (PINP), alkaline phosphatase (ALP), and osteocalcin (OC); (2) bone resorption markers, including C-telopeptide of type I collagen (CTx), N-telopeptide of type I collagen (NTx), bone sialoprotein (BSP), tartrate-resistant acid phosphatase (TRACP), deoxypyridinoline (D-PYD), pyridoxine (PYD), and C-terminal pyridinoline cross-linked telopeptide of type I collagen (ICTP); (3) prostate-specific antigen (PSA); (4) neuroendocrine markers, such as chromogranin A (CgA), neuron-specific enolase (NSE), and pro-gastrin releasing peptide (ProGRP); (5) liquid biopsy markers, such as circulating tumor cells (CTCs), microRNA (miRNA), circulating tumor DNA (ctDNA), and cell-free DNA (cfDNA) and exosomes. In summary, some of these markers are already in widespread clinical use, while others still require further laboratory or clinical studies to validate their value for clinical application.

Novel serum proteomic biomarkers for early diagnosis and aggressive grade identification of prostate cancer

BACKGROUND

Prostate cancer (PCa) is one of the most common tumors and the second leading cause of cancer-related death in men. The discovery of novel biomarkers for PCa diagnosis in the early stage, as well as discriminating aggressive PCa from non-aggressive PCa continue to pose a challenge. The aim of this study was to identify serum proteins that were sensitive and specific enough to detect early-stage and aggressive PCa.

METHODS

The serum proteomic profiling of patients with PCa and benign prostatic hyperplasia (BPH) was comprehensively analyzed using data-independent acquisition mass spectrometry (DIA-MS), and the bioinformatics analysis was performed. The differentially expressed proteins (DEPs) of interest were further verified by enzyme-linked immunosorbent assay (ELISA) and immunoturbidimetry assay.

RESULTS

Statistically significant difference in abundance showed 56 DEPs between early-stage PCa and BPH and 47 DEPs between aggressive and non-aggressive PCa patients. In addition, the verification results showed that serum L-selectin concentration was significantly higher (p<0.05) in Gleason 6 PCa when compared with BPH, and the concentration of osteopontin (SPP1) and ceruloplasmin (CP) increased with higher Gleason score.

CONCLUSIONS

DIA-MS has great potential in cancer-related biomarker screening. Our data demonstrated that adding SPP1 and CP to PSA improved the separation of Gleason 7 (4 + 3) or above from Gleason 7 (3 + 4) or below compared with PSA diagnosis alone. Serum SPP1 and CP could be effective biomarkers to differentiate aggressive PCa (especially Gleason 7 (4 + 3) or above) from non-aggressive disease.

Application of Proteogenomics to Urine Analysis towards the Identification of Novel Biomarkers of Prostate Cancer: An Exploratory Study

Simple Summary

Prostate cancer (PCa) is one of the most common cancers. Due to the limited and invasive approaches for PCa diagnosis, it is crucial to identify more accurate and non-invasive biomarkers for its detection. The aim of our study was to non-invasively uncover new protein targets for detecting PCa using a proteomics and proteogenomics approach. This work identified several dysregulated mutant protein isoforms in urine from PCa patients, some of them predicted to have a protective or an adverse role in these patients. These results are promising given urine’s non-invasive nature and offers an auspicious opportunity for research and development of PCa biomarkers.

Abstract

To identify new protein targets for PCa detection, first, a shotgun discovery experiment was performed to characterize the urinary proteome of PCa patients. This revealed 18 differentially abundant urinary proteins in PCa patients. Second, selected targets were clinically tested by immunoblot, and the soluble E-cadherin fragment was detected for the first time in the urine of PCa patients. Third, the proteogenome landscape of these PCa patients was characterized, revealing 1665 mutant protein isoforms. Statistical analysis revealed 6 differentially abundant mutant protein isoforms in PCa patients. Analysis of the likely effects of mutations on protein function and PPIs involving the dysregulated mutant protein isoforms suggests a protective role of mutations HSPG2*Q1062H and VASN*R161Q and an adverse role of AMBP*A286G and CD55*S162L in PCa patients. This work originally characterized the urinary proteome, focusing on the proteogenome profile of PCa patients, which is usually overlooked in the analysis of PCa and body fluids. Combined analysis of mass spectrometry data using two different software packages was performed for the first time in the context of PCa, which increased the robustness of the data analysis. The application of proteogenomics to urine proteomic analysis can be very enriching in mutation-related diseases such as cancer.

βKlotho Inhibits Cell Proliferation by Downregulating ELK4 and Predicts Favorable Prognosis in Prostate Cancer

Objective

Prostate cancer (PCa) ranks as the second common malignancy in males worldwide. Although conspicuous progressions in diagnosis and treatment have been achieved in the past decades, the prognosis expectation of PCa remains unsatisfied yet. To improve the prognosis prediction of PCa, more specific biomarkers are needed. In this retrospective research, we focused on βKlotho and ETS-like transcription factor 4 (ELK4), aiming to identify potential prognostic biomarkers for PCa.

Methods

Western blotting was used to determine the expression of βKlotho, ELK4, and PARP in C4-2B and PC3 PCa cell lines. CCK-8 assay and colony formation assay were applied to examine the roles of βKlotho and ELK4 in the proliferation of PCa cells. The expression of βKlotho and ELK4 in PCa tissue samples was determined by immunochemistry. Pearson's χ2 test and Fisher's exact test were performed to investigate the associations among βKlotho, ELK4 and various clinical factors. Kaplan-Meier curves and Cox regression model were established to reveal the correlation among βKlotho, ELK4 expression and the prognosis of patients.

Results

βKlotho overexpression down-regulated the ELK4 expression, induced apoptosis and inhibited cell proliferation in both C4-2B and PC3 cells, which were reversed by ELK4 overexpression. βKlotho expression in PCa tissue samples had negative correlation with the ELK4 expression, and higher βKlotho expression was associated with lower Gleason score, absent distant metastasis and lower prostate-specific antigen (PSA) level. On the contrast, higher ELK4 expression was correlated with distant metastasis and higher PSA level. Moreover, βKlotho and ELK4 were both recognized as independent factors for the prognosis of patients with PCa.

Conclusion

βKlotho inhibits proliferation of prostate cancer cells by downregulating ELK4. Both βKlotho and ELK4 expressions correlate with the prognosis of PCa, which may serve as potential biomarkers for follow-up surveillance and prognostic assessments.