Osteopontin in hepatocellular carcinoma: A possible biomarker for diagnosis and follow-up

Cabiati, Manuela; Gaggini, Melania; Cesare, Maria Michela; Caselli, Chiara; Simone, Paolo De; Filipponi, Franco; Basta, Giuseppina; Gastaldelli, Amalia; Ry, Silvia Del

doi:10.1016/j.cyto.2017.07.004

Cited by 36 publications

(30 citation statements)

References 35 publications

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“…The biological functions of osteopontin are diverse [40]. It is overexpressed during the development and progression of different cancers, and has been suggested as a potential prognostic biomarker and therapeutic target [41]. KIF20A accumulates in the nucleus during the G2 phase of the cell cycle [42], and contributed to cellular proliferation, apoptosis and metastasis by regulating various signaling pathways, such as the E2F-retinoblastoma protein-p16 pathway and the PI3K/Akt signaling pathways.…”

Section: Discussionmentioning

confidence: 99%

A robust twelve-gene signature for prognosis prediction of hepatocellular carcinoma

Ouyang

Pan

et al. 2020

Cancer Cell Int

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Background: The prognosis of hepatocellular carcinoma (HCC) patients remains poor. Identifying prognostic markers to stratify HCC patients might help to improve their outcomes. Methods: Six gene expression profiles (GSE121248, GSE84402, GSE65372, GSE51401, GSE45267 and GSE14520) were obtained for differentially expressed genes (DEGs) analysis between HCC tissues and non-tumor tissues. To identify the prognostic genes and establish risk score model, univariable Cox regression survival analysis and Lasso-penalized Cox regression analysis were performed based on the integrated DEGs by robust rank aggregation method. Then Kaplan-Meier and time-dependent receiver operating characteristic (ROC) curves were generated to validate the prognostic performance of risk score in training datasets and validation datasets. Multivariable Cox regression analysis was used to identify independent prognostic factors in liver cancer. A prognostic nomogram was constructed based on The Cancer Genome Atlas (TCGA) dataset. Finally, the correlation between DNA methylation and prognosis-related genes was analyzed. Results: A twelve-gene signature including SPP1, KIF20A, HMMR, TPX2, LAPTM4B, TTK, MAGEA6, ANX10, LECT2, CYP2C9, RDH16 and LCAT was identified, and risk score was calculated by corresponding coefficients. The risk score model showed a strong diagnosis performance to distinguish HCC from normal samples. The HCC patients were stratified into high-risk and low-risk group based on the cutoff value of risk score. The Kaplan-Meier survival curves revealed significantly favorable overall survival in groups with lower risk score (P < 0.0001). Time-dependent ROC analysis showed well prognostic performance of the twelve-gene signature, which was comparable or superior to AJCC stage at predicting 1-, 3-, and 5-year overall survival. In addition, the twelve-gene signature was independent with other clinical factors and performed better in predicting overall survival after combining with age and AJCC stage by nomogram. Moreover, most of the prognostic twelve genes were negatively correlated with DNA methylation in HCC tissues, which SPP1 and LCAT were identified as the DNA methylation-driven genes. Conclusions: We identified a twelve-gene signature as a robust marker with great potential for clinical application in risk stratification and overall survival prediction in HCC patients.

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Section: Discussionmentioning

confidence: 99%

A robust twelve-gene signature for prognosis prediction of hepatocellular carcinoma

Ouyang

Pan

et al. 2020

Cancer Cell Int

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“…Previous studies have shown that OPN plays an important role in the immune response and the development, invasion and metastasis of various malignant tumors (9)(10)(11). Cabiati et al (12) found that the expression of plasma and tissue OPN concentrations increase in liver cancer patients with clinical severity. They considered that OPN may be a useful starting point for prognostic and diagnostic markers of liver cancer, and that OPN overexpression is associated with an invasive phenotype of human NSCLC.…”

Section: Introductionmentioning

confidence: 99%

Comparison of the diagnostic value of CEA combined with OPN or DKK1 in non‑small cell lung cancer

2020

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Carcinoma embryonic antigen (CEA), osteopontin (OPN), and Dickkopf-1 (DKK1) expressed in serum are associated with hypoxia in tumor progression. However, the role of these proteins in the plasma of patients with non-small cell lung cancer (NSCLC) is poorly understood. The diagnostic values of CEA combined with OPN or DKK1 were compared in non-small cell lung cancer. This study investigated the diagnostic value of CEA combined with OPN and DKK1, respectively, in NSCLC. Eighty patients with NSCLC (NSCLC group) and 60 patients with benign lung diseases (benign lung disease group) admitted to Shandong Provincial Third Hospital from May 2014 to January 2015 were selected as the study subjects. In addition, 60 healthy subjects undergoing normal physical examination were selected as healthy control group. The OPN and DKK1 in serum of the two groups were detected by enzyme linked immunosorbent assay (ELISA), and the CEA expression was measured by Electrochemical Photometric method. The diagnostic value of CEA combined with OPN and DKK1, respectively, in NSCLC was analyzed. The expression of CEA, OPN, and DKK1 in serum of NSCLC group was significantly higher than that of healthy control group and benign lung disease group (P<0.05). The expression of CEA, OPN and DKK1 in serum of NSCLC patients was correlated with tumor diameter, lymph node metastasis, degree of pathological differentiation and clinical stage (P<0.05). ROC curve for diagnosis of NSCLC was drawn by further combination of serum CEA and OPN. The AUC of combined diagnosis of CEA and OPN for NSCLC was 0.920 (95% CI, 0.875-0.964), and the diagnostic sensitivity and specificity were 87.50 and 86.67%, respectively; the AUC of combined diagnosis of CEA and DKK1 for NSCLC was 0.912 (95% CI, 0.866-0.958), and the diagnostic sensitivity and specificity were 92.50 and 76.67%, respectively. CEA, OPN and DKK1 may be involved in the occurrence and progression of NSCLC and have good sensitivity and specificity in the diagnosis of NSCLC and may be new biomarkers for the diagnosis of NSCLC.

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“…In recent years, a number of novel biomarkers, such as AFP [41, 42], glypican 3 [43], Osteopontin [44], CXCL1 [45], UQCRH [46], TIP30 [47], neutrophil–lymphocyte ratio [48], have emerged for diagnosing HCC and predicting patient outcome. Among these biomarkers, AFP is a well-known serum diagnostic and prognostic biomarker for HCC [49].…”

Section: Discussionmentioning

confidence: 99%

Expression of the Wnt ligands gene family and its relationship to prognosis in hepatocellular carcinoma

Dong

Shi

2019

Cancer Cell Int

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Background The Wnt gene family members are known to participate regulating various normal and pathological processes including tumorigenesis. However, the association between Wnt ligands gene family and prognosis in hepatocellular carcinoma has not been systematically studied. Therefore, we evaluated the role of Wnt ligands gene family in hepatocellular carcinoma using publicly available data from The Cancer Genome Atlas (TCGA). Methods Clinical information and RNA-Seq mRNA expression data were derived from TCGA hepatocellular carcinoma cohort. Differences in overall survival (OS) and disease-free survival (DFS) between increased and decreased expression groups (defined by X-tile analyses) of Wnt ligands gene family were compared using Kaplan–Meier method and Cox regression model, with p-values calculated via log-rank test. Gene Set Enrichment Analysis (GSEA) was performed. Results Multivariate analysis adjusted for patient age, sex, BMI, tumor grade, and TMN stage revealed that Wnt1, Wnt3 and Wnt5B expressions were independent prognostic factors for OS and DFS (OS: HR = 0.58, P = 0.006; HR = 0.65, P = 0.03; HR = 0.56, P = 0.023, respectively; DFS: HR = 0.52, P < 0.001; HR = 1.93, P = 0.003; HR = 0.59, P = 0.011, respectively). Furthermore, expression of Wnt1 and Wnt5B was significantly associated with TMN stage (P = 0.02 and P = 0.03 for OS; P = 0.02 and P = 0.02 for DFS). GSEA showed that nucleotide excision repair was differentially enriched in Wnt1 low expression phenotype and aminoacyl trna biosynthesis and basal transcription factors were differentially enriched in Wnt5B low expression phenotype. Conclusions Our results identified associations of several Wnt ligands with prognosis of HCC patients, indicating that these genes could serve as prognostic biomarkers of HCC. Electronic supplementary material The online version of this article (10.1186/s12935-019-0743-z) contains supplementary material, which is available to authorized users.

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Osteopontin in hepatocellular carcinoma: A possible biomarker for diagnosis and follow-up

Cited by 36 publications

References 35 publications

A robust twelve-gene signature for prognosis prediction of hepatocellular carcinoma

A robust twelve-gene signature for prognosis prediction of hepatocellular carcinoma

Comparison of the diagnostic value of CEA combined with OPN or DKK1 in non‑small cell lung cancer

Expression of the Wnt ligands gene family and its relationship to prognosis in hepatocellular carcinoma

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