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Advanced cervical cancer (CESC) is a common gynecological malignancy that threatens females' lives and existing treatments remain ineffective. This study focused on discovering potential biomarkers for the prognosis of CESC patients and exploring potential curative mechanisms and possible therapeutic directions. Based on the gene expression profile and CESC patient survival data in The Cancer Genome Atlas (TCGA) database, prognostic signatures were obtained and using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses to understand related gene functions, functional and pathway enrichment of potential biomarkers. Gene set enrichment analysis and gene set variation analysis were performed to understand further the biological characteristics and regulatory networks of potential biomarker expression levels on the prognosis of CESC. Immune infiltration analysis to comprehend the functional correlation between potential biomarkers and immune cells and the receiver operating characteristic (ROC) curves to assess the degree of CESC differentiation identification by prognostic signature and hazard score in predicting patient prognosis. Brain-Specific Angiogenesis Inhibitor 1-Associated Protein 2-Like Protein 1 (BAIAP2L1) and secreted phosphoprotein 1 (SPP1) (hazard ratio (HR) >1) were highly expressed in tumor tissues as CESC risk factors, while DES (Desmin) and EF-Hand Calcium Binding Domain 1 (EFCAB1) (HR <1) were expressed at low levels in tumor tissues as prognostic protective factors. SPP1 had the highest positive correlation with Macrophages M0 and IL3RA had the highest positive correlation with T cells CD8. Patients with high expression of the risk factor gene SPP1 had a significant reduction in overall survival (OS) time, whereas those with high expression of the protective factor gene interleukin-3 receptor alpha chain (IL3RA) had a long OS time. Our results showed that the prognostic signature, either risk or protective factors, have a great effect on the prognosis of CESC, and understanding the role of these genes in the development of CESC may provide new directions. [ABSTRACT FROM AUTHOR]

Secreted phosphoprotein 1 (SPP1), also known as osteopontin, is a phosphorylated protein. High SPP1 expression levels have been detected in multiple cancers and are associated with poor prognosis and reduced survival rates. However, only a few pan‐cancer analyses have targeted SPP1. We conducted a comprehensive analysis using multiple public databases, including TIMER and TCGA, to investigate the expression levels of SPP1 in 33 different tumor types. In addition, we verified the effect of SPP1 on osteosarcoma. To assess the impact of SPP1 on patient outcomes, we employed univariate Cox regression and Kaplan–Meier survival analyses to analyze overall survival (OS), disease‐specific survival (DSS), and progression‐free interval (PFI) in these tumor patients. We also explored SPP1 gene alterations in various tumor tissues using cBioPortal. We then examined the relationship between SPP1 and clinical characteristics, TME, immune regulatory genes, immune checkpoints, TMB, and MSI using R language. In addition, we used GSEA to investigate the molecular mechanisms underlying the role of SPP1. Bioinformatics analysis indicated that SPP1 was upregulated in 17 tumors. Overexpression of SPP1 results in poor OS, DSS, and PFI in CESC, ESCA, GBM, LGG, LIHC, PAAD, PRAD, and skin cutaneous melanoma. SPP1 expression was positively associated with immunocyte infiltration, immune regulatory genes, immune checkpoints, TMB, MSI, and drug sensitivity in certain cancers. We found that high expression of SPP1 in osteosarcoma was related to drug resistance and metastasis and further demonstrated that SPP1 can stimulate osteosarcoma cell proliferation via CCND1 by activating the PI3K/Akt pathway. These findings strongly suggest that SPP1 is a potential prognostic marker and novel target for cancer immunotherapy. [ABSTRACT FROM AUTHOR]

Abstract The tumor microenvironment (TME) is an intricate system comprised of tumor cells and the surrounding cellular and non-cellular components, exerting a pivotal influence on the initiation and progression of tumors. Exhibiting dynamic and diverse compositions as well as functional states across various tumors and patients, a profound comprehension of its specific internal interactions is indispensable for formulating efficacious anti-cancer treatment strategies. Extensive interactions among various immune cell types within the TME are well-documented, with their phenotypes and abundances closely linked to clinical prognoses. TME research is progressing towards greater complexity and precision, yet, to date, no representative TME biomarkers suitable for clinical applications have been definitively identified and validated. In a recent study, the collaborative actions of CXCL9 and SPP1 (CXCL9:SPP1) were found to collectively dictate the polarity of tumor-associated macrophages (TAMs) within the TME, exerting profound effects on tumor progression and treatment responses. The mutually exclusive expression of CXCL9:SPP1 in the TME not only governs TAM polarity but also exhibits strong correlations with immune cell profiles, antitumor factors, and patient outcomes, significantly influencing prognosis. This article consolidates the significance and prospects of CXCL9:SPP1 as a novel indicator for tumor development and prognosis, while also proposing future research directions and addressing potential challenges in this promising field.

Osteopontin (OPN)-CD44 signaling plays an important role in promoting tumor progression and metastasis. In cancer, OPN and CD44 overexpression is a marker of aggressive disease and poor prognosis, and correlates with therapy resistance. In this study, we aimed to evaluate the association of single nucleotide polymorphisms (SNPs) in the OPN and CD44 genes with clinical outcomes in 307 non-small cell lung cancer (NSCLC) patients treated with radiotherapy or chemoradiotherapy. The potential impact of the variants on plasma OPN levels was also investigated. Multivariate analysis showed that OPN rs11730582 CC carriers had a significantly increased risk of death (p = 0.029), while the CD44 rs187116 A allele correlated with a reduced risk of locoregional recurrence (p = 0.016) in the curative treatment subset. The rs11730582/rs187116 combination was associated with an elevated risk of metastasis in these patients (p = 0.016). Furthermore, the OPN rs1126772 G variant alone (p = 0.018) and in combination with rs11730582 CC (p = 7 × 10−5) was associated with poor overall survival (OS) in the squamous cell carcinoma subgroup. The rs11730582 CC, rs187116 GG, and rs1126772 G, as well as their respective combinations, were independent risk factors for unfavorable treatment outcomes. The impact of rs11730582-rs1126772 haplotypes on OS was also observed. These data suggest that OPN and CD44 germline variants may predict treatment effects in NSCLC. [ABSTRACT FROM AUTHOR]

Background: Secretory phosphoprotein 1 (SPP1), also known as Osteopontin, is part of the small integrin-binding ligand N-linked glycoprotein family. Its overexpression in various cancers, including colorectal cancer (CRC), has been linked to prognosis. However, its role in the survival and immune infiltration in CRC, particularly in athletes and fitness enthusiasts, requires further investigation. Methods: Utilizing data from The Cancer Genome Atlas (TCGA) and the Genotype Tissue Expression Project (GTEx), we analyzed the expression profiles and clinical data of CRC patients, focusing on the relationship between SPP1 expression and cancer development. Wilcoxon rank tests compared SPP1 expression in normal and cancerous colorectal tissues. The predictive power of SPP1 in CRC was assessed using the receiver operating characteristic (ROC) curve. Logistic regression and Wilcoxon rank sum tests were used to correlate SPP1 expression with clinical features. Kaplan-Meier survival analysis, Progno Scan database, and Cox multivariate regression analysis evaluated SPP1's prognostic significance. R-package Cluster profiler enrichment analysis identified SPP1's biological functions and signaling pathways. Correlations between SPP1 and immune-infiltrating cells were appraised using single-sample gene set enrichment analysis (ssGSEA) and TIMER database, with further exploration of SPP1 and immune cell gene markers through TIMER and GEPIA databases. Results: SPP1 was found to be highly expressed in CRC, significantly more so than in normal colorectal tissues, with an AUC of 0.846 indicating high accuracy in CRC prognosis prediction. SPP1 expression correlated with pathological stage and diseasespecific survival (DSS), with overexpression leading to reduced overall survival (OS), DSS, and disease-free survival (DFS). Multivariable Cox regression analysis confirmed SPP1 as an independent prognostic biomarker for CRC (HR = 1.459; 95% CI: 1.030-2.067; P = 0.033). SPP1 was associated with various biological functions and signaling pathways. It also showed a positive correlation with the infiltration levels of macrophages, dendritic cells (DCs), CD8+ T cells, and neutrophils in CRC. SPP1 was strongly correlated with immune gene markers, including TAM, DC, T cell exhaustion, and Tregs. Conclusion: SPP1's elevated expression in CRC is closely associated with poor immune infiltration and prognosis. In athletes and fitness enthusiasts, who might experience unique immune system challenges due to their intense physical regimes, SPP1's role becomes particularly crucial. Understanding SPP1's impact on immune infiltration in this group could lead to tailored therapeutic approaches in CRC, positioning SPP1 as a promising prognostic biomarker in this demographic. [ABSTRACT FROM AUTHOR]

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Background: Lymph node metastasis (LNM) is an important cause leading to recurrence and development of head and neck carcinoma (HNC), with the precise mechanisms unclear. Thus, we aimed to identify the key genes involved in LNM and further evaluate their expressions and roles.Methods: A cohort of HNC in the TCGA was analyzed. The study involved three phases (one screening and two validation phases). First, the differentially expressed genes regarding LNM were screened, from which a key gene was identified by a series of data mining approaches. Then, the expressions and roles of the key gene were validated in HNC through bioinformatics. Afterward, the expression of the key gene was detected by qPCR, western blot, and Immunohistochemistry based on a cell model and a tissue microarray. Further, colony formation and transwell migration and invasion assays were used to evaluate the roles of the key gene.Results: SPP1 was overexpressed in HNC tissues and was identified as the key gene. Overexpression of SPP1 in HNC was correlated with advanced pathological stages and T-stage, as well as the presence of LNM, which predicted poor prognosis. The expression of SPP1 was closely associated with the infiltration of immune cells in HNC, especially M2 macrophages. Lab experiments confirmed that SPP1 silence in HNC cells resulted in weakened invasive and metastatic abilities.Conclusion: This study reveals that SPP1 may be a key gene associated with LNM in HNC, raising the possibility of SPP1 as a target for HNC prevention and treatment. [ABSTRACT FROM AUTHOR]

To screen diagnostic biomarkers for lung adenocarcinoma (LUAD) using bioinformatic approach and analyze immune cell infiltration in lung adenocarcinoma, expression datasets of lung adenocarcinoma were downloaded from GEO and TCGA databases. Differentially expressed genes (DEGs) between lung adenocarcinoma and normal lung tissues were screened using R software, and GO and KEGG enrichment analysis of DEGs was performed using DAVID tools. Protein interaction networks were constructed and hub genes of DEGs were screened using tools such as STRING and Cytoscape. Kaplan-Meier method was used for survival analysis of DEGs, ROC analysis of hub genes was performed to screen for diagnostic biomarkers, GSEA was utilized to predict the signaling pathways involved in genes with prognostic value, and Cibersort software was adopted to analyze immune cell infiltration in lung adenocarcinoma. A total of 234 DEGs of lung adenocarcinoma were obtained, which were mainly involved in signaling, substance metabolism, immune response, and other related signaling pathways. Eight of the 20 hub genes screened by PPI network had prognostic value (CCNA2, DLGAP5, HMMR, MMP1, MMP9, MMP13, SPP1, TOP2A), and according to ROC analysis. The values of DLGAP5 and SPP1 were 0.703 and 0.706 respectively. DLGAP5 and SPP1 gene expression levels were closely correlated to plasma cells in lung adenocarcinoma tissue, unactivated CD4+ memory cells, regulatory T cells, macrophage M0, M1, M2, and neutrophil infiltration (P < 0.05). To conclude, DLGAP5 and SPP1 have high diagnostic values in lung adenocarcinoma and are involved in immune cell infiltration in lung adenocarcinoma tissues. DLGAP5 and SPP1 genes can be used as biomarkers for lung adenocarcinoma diagnosis and can provide new ideas for targeted therapy research of lung adenocarcinoma. [ABSTRACT FROM AUTHOR]

Head and neck squamous cell carcinoma (HNSCC) is one of the most common malignancies and has a low 5-year survival rate. Mounting evidence suggests that oral potentially malignant disorders, such as oral leukoplakia (OLK), may progress to HNSCC. Given that OLK and HNSCC are often insidious and asymptomatic, the identification of markers of OLK malignant transformation and therapeutic targets in HNSCC is critical. Using various online tools and publicly available gene expression datasets, the secreted phosphoprotein 1 gene (SPP1) was identified as a significant differentially expressed gene among OLK, HNSCC, and non-cancerous tissues. SPP1 mRNA levels were elevated in HNSCC tissues and were associated with cancer stage, tumor grade, and human papillomavirus infection status. High SPP1 mRNA levels were correlated with poor overall survival of HNSCC patients. In contrast, SPP1 mutations were not significantly associated with overall survival, although their frequency in HNSCC was very low (0.6%). Furthermore, SPP1 expression levels in HNSCC were positively correlated with the infiltration of CD4+ cells, macrophages, neutrophils, and dendritic cells. The study results suggest that SPP1 may represent a diagnostic and prognostic biomarker, as well as a potential therapeutic target in HNSCC. [ABSTRACT FROM AUTHOR]

Background: Neutrophils form extracellular net-like structures called neutrophil extracellular traps (NETs). Emerging evidence has shown that cancer can induce NET formation; however, it is not fully understood how NETs influence cancer biology, and no consensus has been reached on their pro- or antitumor effects. A comprehensive analysis of the global NET-associated gene regulatory network is currently unavailable and is urgently needed. Methods: We systematically explored and discussed NET enrichment, NET-associated gene regulatory patterns, and the prognostic implications of NETs in approximately 8,000 patients across 22 major human cancer types. We identified NET-associated regulatory gene sets that we then screened for NET-associated regulatory patterns that might affect patient survival. We functionally annotated the NET-associated regulatory patterns to compare the biological differences between NET-related survival subgroups. Results: A gene set variation analysis (GSVA) based on 23 major component genes was used to calculate a metric called the NET score. We found that the NET score was closely associated with many important cancer hallmarks, particularly inflammatory responses and epithelial-to-mesenchymal transition (EMT)-induced metastasis. Higher NET scores were related to poor immunotherapy response. Survival analysis revealed that NETs had diverse prognostic impacts among various cancer types. The NET-associated regulatory patterns linked to shorter or longer cancer patient survival were distinct from each other. Functional analysis revealed that more of the NET-associated regulatory genes linked to poor cancer survival were associated with extracellular matrix (ECM) remodeling and pan-cancerous risk factors. SPP1 was found to be highly expressed and correlated with NET formation in cancers with poor survival. We also found that the co-upregulation of NET formation and SPP1 expression was closely linked to increased EMT and poor survival, that SPP1 influenced NET-induced malignant capacity, and that SPP1 overproduction induced a robust formation of metastatic-promoting NETs. Conclusion: NETs were common across cancers but displayed a diverse regulatory pattern and outcome readouts in different cancer types. SPP1 is potentially the key to NET-related poor outcomes. [ABSTRACT FROM AUTHOR]

Background: SPP1 , secreted phosphoprotein 1, is a member of the small integrin-binding ligand N-linked glycoprotein (SIBLING) family. Previous studies have proven SPP1 overexpressed in a variety of cancers and can be identified as a prognostic factor, while no study has explored the function and carcinogenic mechanism of SPP1 in cervical cancer. Methods: We aimed to demonstrate the relationship between SPP1 expression and pan-cancer using The Cancer Genome Atlas (TCGA) database. Next, we validated SPP1 expression of cervical cancer in the Gene Expression Omnibus (GEO) database, including GSE7803, GSE63514, and GSE9750. The receiver operating characteristic (ROC) curve was used to evaluate the feasibility of SPP1 as a differentiating factor by the area under curve (AUC) score. Cox regression and logistic regression were performed to evaluate factors associated with prognosis. The SPP1 -binding protein network was built by the STRING tool. Enrichment analysis by the R package clusterProfiler was used to explore potential function of SPP1. The single-sample GSEA (ssGSEA) method from the R package GSVA and TIMER database were used to investigate the association between the immune infiltration level and SPP1 expression in cervical cancer. Results: Pan-cancer data analysis showed that SPP1 expression was higher in most cancer types, including cervical cancer, and we got the same result in the GEO database. The ROC curve suggested that SPP1 could be a potential diagnostic biomarker (AUC = 0.877). High SPP1 expression was associated with poorer overall survival (OS) (P = 0.032). Further enrichment and immune infiltration analysis revealed that high SPP1 expression was correlated with regulating the infiltration level of neutrophil cells and some immune cell types, including macrophage and DC. Conclusion: SPP1 expression was higher in cervical cancer tissues than in normal cervical epithelial tissues. It was significantly associated with poor prognosis and immune cell infiltration. Thus, SPP1 may become a promising prognostic biomarker for cervical cancer patients. [ABSTRACT FROM AUTHOR]

Liver cancer accounts for 6% of all malignancies causing death worldwide, and hepatocellular carcinoma (HCC) is the most common histological type. HCC is a heterogeneous cancer, but how the tumour microenvironment (TME) of HCC contributes to the progression of HCC remains unclear. In this study, we investigated the immune microenvironment by multiomics analysis. The tumour immune infiltration characteristics of HCC were determined at the genomic, epigenetic, bulk transcriptome and single-cell levels by data from The Cancer Genome Atlas portal and the Gene Expression Omnibus (GEO). An epigenetic immune-related scoring system (EIRS) was developed to stratify patients with poor prognosis. SPP1, one gene in the EIRS system, was identified as an immune-related predictor of poor survival in HCC patients. Through receptor-ligand pair analysis in single-cell RNA-seq, SPP1 was indicated to mediate the crosstalk between HCC cells and macrophages via SPP1-CD44 and SPP1-PTGER4 association. In vitro experiments further validate SPP1 can trigger the polarization of macrophages to M2-phenotype tumour-associated macrophages (TAMs). [ABSTRACT FROM AUTHOR]

BackgroundNeutrophils form extracellular net-like structures called neutrophil extracellular traps (NETs). Emerging evidence has shown that cancer can induce NET formation; however, it is not fully understood how NETs influence cancer biology, and no consensus has been reached on their pro- or antitumor effects. A comprehensive analysis of the global NET-associated gene regulatory network is currently unavailable and is urgently needed.MethodsWe systematically explored and discussed NET enrichment, NET-associated gene regulatory patterns, and the prognostic implications of NETs in approximately 8,000 patients across 22 major human cancer types. We identified NET-associated regulatory gene sets that we then screened for NET-associated regulatory patterns that might affect patient survival. We functionally annotated the NET-associated regulatory patterns to compare the biological differences between NET-related survival subgroups.ResultsA gene set variation analysis (GSVA) based on 23 major component genes was used to calculate a metric called the NET score. We found that the NET score was closely associated with many important cancer hallmarks, particularly inflammatory responses and epithelial-to-mesenchymal transition (EMT)-induced metastasis. Higher NET scores were related to poor immunotherapy response. Survival analysis revealed that NETs had diverse prognostic impacts among various cancer types. The NET-associated regulatory patterns linked to shorter or longer cancer patient survival were distinct from each other. Functional analysis revealed that more of the NET-associated regulatory genes linked to poor cancer survival were associated with extracellular matrix (ECM) remodeling and pan-cancerous risk factors. SPP1 was found to be highly expressed and correlated with NET formation in cancers with poor survival. We also found that the co-upregulation of NET formation and SPP1 expression was closely linked to increased EMT and poor survival, that SPP1 influenced NET-induced malignant capacity, and that SPP1 overproduction induced a robust formation of metastatic-promoting NETs.ConclusionNETs were common across cancers but displayed a diverse regulatory pattern and outcome readouts in different cancer types. SPP1 is potentially the key to NET-related poor outcomes.

Background:SPP1, secreted phosphoprotein 1, is a member of the small integrin-binding ligand N-linked glycoprotein (SIBLING) family. Previous studies have proven SPP1 overexpressed in a variety of cancers and can be identified as a prognostic factor, while no study has explored the function and carcinogenic mechanism of SPP1 in cervical cancer.Methods: We aimed to demonstrate the relationship between SPP1 expression and pan-cancer using The Cancer Genome Atlas (TCGA) database. Next, we validated SPP1 expression of cervical cancer in the Gene Expression Omnibus (GEO) database, including GSE7803, GSE63514, and GSE9750. The receiver operating characteristic (ROC) curve was used to evaluate the feasibility of SPP1 as a differentiating factor by the area under curve (AUC) score. Cox regression and logistic regression were performed to evaluate factors associated with prognosis. The SPP1-binding protein network was built by the STRING tool. Enrichment analysis by the R package clusterProfiler was used to explore potential function of SPP1. The single-sample GSEA (ssGSEA) method from the R package GSVA and TIMER database were used to investigate the association between the immune infiltration level and SPP1 expression in cervical cancer.Results: Pan-cancer data analysis showed that SPP1 expression was higher in most cancer types, including cervical cancer, and we got the same result in the GEO database. The ROC curve suggested that SPP1 could be a potential diagnostic biomarker (AUC = 0.877). High SPP1 expression was associated with poorer overall survival (OS) (P = 0.032). Further enrichment and immune infiltration analysis revealed that high SPP1 expression was correlated with regulating the infiltration level of neutrophil cells and some immune cell types, including macrophage and DC.Conclusion:SPP1 expression was higher in cervical cancer tissues than in normal cervical epithelial tissues. It was significantly associated with poor prognosis and immune cell infiltration. Thus, SPP1 may become a promising prognostic biomarker for cervical cancer patients.

Background: Hepatocellular carcinoma (HCC) is a typical inflammatory-related malignant tumor with complex immune tolerance microenvironment and poor prognosis. In this study, we aimed to construct a novel immune-related gene signature for the prognosis of HCC patients, exploring tumor microenvironment (TME) cell infiltration characterization and potential mechanisms. Methods: A total of 364 HCC samples with follow-up information in the TCGA-LIHC dataset were analyzed for the training of the prognostic signature. The Least Absolute Shrinkage and Selector Operation (LASSO) regression based on the IRGs was conducted to identify the prognostic genes and establish an immune risk signature. The immune cell infiltration in TME was estimated via the CIBERSORT method. Gene Set Variation Analysis (GSVA) was conducted to compare the biological pathways involved in the low-risk and high-risk groups. Furthermore, paraffin sections of HCC tissue microarrays containing 77 patients from Fudan University Shanghai Cancer Center were used for IHC staining. The clinical characteristics of the 77 HCC patients were collected and summarized for survival analysis validation via the Kaplan–Meier (KM) method. Results: Three-gene signature with close immune correlation (Risk score = EPO * 0.02838 + BIRC5 * 0.02477 + SPP1 * 0.0002044) was constructed eventually and proven to be an effective prognostic factor for HCC patients. The patients were divided into a high-risk and a low-risk group according to the optimal cutoff, and the survival analysis revealed that HCC samples with high-risk immuno-score had significantly poorer outcomes than the low-risk group (p < 0.0001). The results of CIBERSORT suggested that the immune cell activation was relatively higher in the low-risk group with better prognosis. Besides, GSVA analysis showed multiple signaling differences between the high- and low-risk group, indicating that the three-gene prognostic model can affect the prognosis of patients by affecting immune-related mechanisms. Tissue microarray (TMA) results further confirmed that the expression of three genes in HCC tissues was closely related to the prognosis of patients, respectively. Conclusion: In this study, we constructed and validated a robust three-gene signature with close immune correlation in HCC, which presented a reliable performance in the prediction of HCC patients' survival. [ABSTRACT FROM AUTHOR]

Background: Hepatocellular carcinoma (HCC) is a typical inflammatory-related malignant tumor with complex immune tolerance microenvironment and poor prognosis. In this study, we aimed to construct a novel immune-related gene signature for the prognosis of HCC patients, exploring tumor microenvironment (TME) cell infiltration characterization and potential mechanisms.Methods: A total of 364 HCC samples with follow-up information in the TCGA-LIHC dataset were analyzed for the training of the prognostic signature. The Least Absolute Shrinkage and Selector Operation (LASSO) regression based on the IRGs was conducted to identify the prognostic genes and establish an immune risk signature. The immune cell infiltration in TME was estimated via the CIBERSORT method. Gene Set Variation Analysis (GSVA) was conducted to compare the biological pathways involved in the low-risk and high-risk groups. Furthermore, paraffin sections of HCC tissue microarrays containing 77 patients from Fudan University Shanghai Cancer Center were used for IHC staining. The clinical characteristics of the 77 HCC patients were collected and summarized for survival analysis validation via the Kaplan–Meier (KM) method.Results: Three-gene signature with close immune correlation (Risk score = EPO * 0.02838 + BIRC5 * 0.02477 + SPP1 * 0.0002044) was constructed eventually and proven to be an effective prognostic factor for HCC patients. The patients were divided into a high-risk and a low-risk group according to the optimal cutoff, and the survival analysis revealed that HCC samples with high-risk immuno-score had significantly poorer outcomes than the low-risk group (p < 0.0001). The results of CIBERSORT suggested that the immune cell activation was relatively higher in the low-risk group with better prognosis. Besides, GSVA analysis showed multiple signaling differences between the high- and low-risk group, indicating that the three-gene prognostic model can affect the prognosis of patients by affecting immune-related mechanisms. Tissue microarray (TMA) results further confirmed that the expression of three genes in HCC tissues was closely related to the prognosis of patients, respectively.Conclusion: In this study, we constructed and validated a robust three-gene signature with close immune correlation in HCC, which presented a reliable performance in the prediction of HCC patients’ survival.

BackgroundOsteomimicry of cancer cells had been widely reported in prostate cancer and breast cancer. However, the prognostic value of osteomimicry in various cancer types remained unclear. We hypothesized that osteomimicry would result in remodeling of the tumor microenvironment and was eligible to predict patient prognosis.MethodsA comprehensive transcriptomic analysis of the osteomimicry, which was characterized by mRNA expression of SPARC, SPP1, and BGLAP, across 20 solid tumors (7564 patients) using RNA-seq data from The Cancer Genome Atlas (TCGA) was conducted. Samples of each cancer type were classified into subgroups (high vs. low) based on median value of osteomimetic markers, the associations of these markers with clinical outcomes, immune cell infiltration and immune checkpoints expression were explored.ResultsEach osteomimetic marker harbored prognostic value in the pan-cancer analyses [SPARC: hazard ratio (HR) = 1.10, p = 0.028; SPP1: HR = 1.25, p < 0.001; BGLAP: HR = 1.13, p = 0.005]. Patients with high expression of all the three genes also had significantly unfavorable survival (HR = 1.61, p < 0.0001) compared with those of low expression. Correlation analyses demonstrated that osteomimicry was closely related to tumor purity, dendritic cells (DC) infiltration and expression of immune checkpoints.ConclusionOsteomimicry had prognostic value in various cancer types and the underlying mechanism might correlate to the trapping and dysfunction of DCs in the tumor microenvironment, revealing the potential of osteomimicry as a target of immunotherapy.

Background/Aims: Gastric cancer (GC) is an important health problem. Classification based on molecular subtypes may help to determine the prognosis of patients with GC. Tumor invasion and metastasis are important factors affecting the prognosis of cancer. We aimed to identify genes related to tumor invasion and metastasis, which may serve as indicators of good GC prognosis. Methods: Tumor tissues and adjacent normal tissues were collected from 105 patients with primary GC who were treated by undergoing radical surgery. Samples were used for tissue microarray analysis. Identified genes with altered expression were further analyzed using the Gene Ontology (Go) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. The expression levels of THBS2, COL1A2 and SPP1 were analyzed by RT-PCR, western blot and immunohistochemistry. The overall survival curves of patients with high and low expression of each gene of interest were plotted and compared. Results: Forty-three genes were identified. THBS2, COL1A2 and SPP1 were selected for further analysis. Altered expression levels of THBS2, COL1A2 and SPP1 in tumor tissues were confirmed. Patients with low THBS2 expression had a better prognosis; the expression of COL1A2 and SPP1 might not affect the prognosis of patients with GC. Conclusion: THBS2, but not COL1A2 and SPP1, may serve as an indicator of GC prognosis. [ABSTRACT FROM AUTHOR]

The prognosis associated with clear cell renal carcinoma (cc RCC) can vary widely and novel molecular prognostic markers are needed to assess prognosis at an earlier stage. Several gene products have been investigated for this purpose, but none of them have been implemented in clinical practice. Here we hypothesized that we, using TaqMan® Array, could identify superior prognostic messenger RNA (mRNA)s in long-term follow-up. Messenger RNA level of 19 candidate genes was investigated in 97 patients with cc RCC. Three genes impacted significantly on prognosis in both univariate and multivariate analysis. In univariate analysis, CSNK2A1 was a strong indicator of a poor overall survival (OS) ( HR = 5.01, p < 0.001), disease specific survival (DSS) ( HR = 6.21, p = 0.007) and progression free survival ( PFS) ( HR = 5.93, p = 0.005). High expression of SPP1 was associated to poor PFS ( HR = 4.41, p = 0.04). DEFB1 was associated with a better PFS ( HR = 0.24, p = 0.006). In multivariate analysis, CSNK2A1 was associated to a worse OS ( HR = 3.56, p = 0.008) and PFS ( HR = 3.84, p = 0.005), whereas SPP1 was an independent predictor of a worse PFS ( HR = 3.46, p = 0.007) and DEFB1 of a better PFS ( HR = 0.37, p = 0.027). These results show that with TaqMan® Array we could identify three superior gene products related to prognosis. Further studies are needed to elucidate the pathways and roles of these genes in renal cancer development. [ABSTRACT FROM AUTHOR]

Stratification of colorectal cancer for better management and tangible clinical outcomes is lacking in clinical practice. To reach this goal, the identification of reliable biomarker(s) is a prerequisite to deliver personalized colorectal cancer theranostics. Osteopontin (SPP1) is a key extracellular matrix protein involved in several pathophysiological processes including cancer progression and metastasis. However, the exact molecular mechanisms regulating its expression, localization, and molecular functions in cancer are still poorly understood. This study was designed to investigate the SPP1 expression profiles in Saudi colorectal cancer patients, and to assess its prognostic value. Hundred thirty-four (134) archival paraffin blocks of colorectal cancer were collected from King Abdulaziz University Hospital, Saudi Arabia. Tissue microarrays were constructed, and automated immunohistochemistry was performed to evaluate SPP1 protein expression patterns in colorectal cancer. About 20% and 23% of our colorectal cancer samples showed high SPP1 cytoplasmic and nuclear expression patterns, respectively. Cytoplasmic SPP1 did not correlate with age, gender, tumor size, and location. However, significant correlations were observed with tumor grade (p = 0.008), tumor invasion (p = 0.01), and distant metastasis (p = 0.04). Kaplan–Meier survival analysis showed a significantly lower recurrence rate in patients with higher SPP1 cytoplasmic expression (p = 0.05). At multivariate analysis, high SPP1 cytoplasmic expression was an independent favorable prognostic marker (p = 0.02). However, nuclear SPP1 expression did not show any prognostic value (p = 0.712). Our results showed a particular SPP1 prognostic relevance that is not in line with most colorectal cancer previous studies that may be attributed to the molecular pathophysiology of our colorectal cancer cohort. Saudi Arabia has both specific genomic makeup and particular environment that could lead to distinctive molecular roots of cancer. SPP1 has several isoforms, tissue localizations and molecular functions, signaling pathways, and downstream molecular functions. Therefore, a more individualized approach for CRC studies and particularly SPP1 prognosis outcomes' assessment is highly recommended toward precision oncology. [ABSTRACT FROM AUTHOR]

Osteopontin (OPN) is an extracellular matrix protein that is overexpressed in various cancers and promotes oncogenic features including cell proliferation, survival, migration, and angiogenesis, among others. OPN can participate in the regulation of the tumor microenvironment, affecting both cancer and neighboring cells. Here, we review the roles of OPN splice variants (a, b, c) in cancer development, progression, and prognosis, and also discuss the identities of isoforms 4 and 5. We also discussed how single-nucleotide polymorphisms (SNPs) of the OPN gene are an additional factor influencing the level of OPN in individuals, modulating the risks of cancer development and outcome. [ABSTRACT FROM AUTHOR]