Dataset Information

Identification of serologic biomarkers for predicting microvascular invasion in hepatocellular carcinoma.

ABSTRACT: Microvascular invasion (MVI) of hepatocellular carcinoma (HCC) is a major risk factor for early recurrence and poor survival after curative surgical therapies. However, MVI can only be diagnosed by pathological examination following resection. The aim of this study is to identify serologic biomarkers for predicting MVI preoperatively to help facilitate treatment decisions. We used the sero-proteomic approach to identify antigens that induce corresponding antibody responses either specifically in the serum from MVI (+) patients or from MVI (-) patients. Six antigens were subsequently identified as HSP 70, HSP 90, alpha-enolase (Eno-1), Annexin A2, glutathione synthetase and beta-actin by mass spectrometry. The antibodies titers in sera corresponding to four of these six antigens were measured by ELISA and compared between 35 MVI (+) patients and 26 MVI (-) patients. The titers of anti-HSP 70 antibodies were significantly higher in MVI (-) patients than those in MVI (+) patients; and the titers of anti-Eno-1 antibodies were significantly lower in MVI (-) patients than those in MVI (+) patients. The results were subjected to multivariate analysis together with other clinicopathologic factors, suggesting that antibodies against HSP 70 and Eno-1 in sera are potential biomarkers for predicting MVI in HCC prior to surgical resection. These biomarkers should be further investigated as potential therapeutic targets.

SUBMITTER: Yu YQ

PROVIDER: S-EPMC4941320 | biostudies-literature | 2016 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identification of serologic biomarkers for predicting microvascular invasion in hepatocellular carcinoma.

Yu Yuan-Quan YQ Wang Liang L Jin Yun Y Zhou Jia-Le JL Geng Yan-Hua YH Jin Xing X Zhang Xiao-Xiao XX Yang Jun-Jie JJ Qian Cheng-Ming CM Zhou Dong-Er DE Liu Da-Ren DR Peng Shu-You SY Luo Yan Y Zheng Lei L Li Jiang-Tao JT

Oncotarget 20160301 13

Microvascular invasion (MVI) of hepatocellular carcinoma (HCC) is a major risk factor for early recurrence and poor survival after curative surgical therapies. However, MVI can only be diagnosed by pathological examination following resection. The aim of this study is to identify serologic biomarkers for predicting MVI preoperatively to help facilitate treatment decisions. We used the sero-proteomic approach to identify antigens that induce corresponding antibody responses either specifically in ...[more]

PMID: 26918350

Similar Datasets

Project description:ObjectiveThe aim of this study was to assess the diagnostic performance of radiomics-based MRI in predicting microvascular invasion (MVI) in hepatocellular carcinoma (HCC).MethodThe databases of PubMed, Cochrane library, Embase, Web of Science, Ovid MEDLINE, Springer, and Science Direct were searched for original studies from their inception to 20 August 2022. The quality of each study included was assessed according to the Quality Assessment of Diagnostic Accuracy Studies 2 and the radiomics quality score. The pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) were calculated. The summary receiver operating characteristic (SROC) curve was plotted and the area under the curve (AUC) was calculated to evaluate the diagnostic accuracy. Sensitivity analysis and subgroup analysis were performed to explore the source of the heterogeneity. Deeks' test was used to assess publication bias.ResultsA total of 15 studies involving 981 patients were included. The pooled sensitivity, specificity, PLR, NLR, DOR, and AUC were 0.79 (95%CI: 0.72-0.85), 0.81 (95%CI: 0.73-0.87), 4.1 (95%CI:2.9-5.9), 0.26 (95%CI: 0.19-0.35), 16 (95%CI: 9-28), and 0.87 (95%CI: 0.84-0.89), respectively. The results showed great heterogeneity among the included studies. Sensitivity analysis indicated that the results of this study were statistically reliable. The results of subgroup analysis showed that hepatocyte-specific contrast media (HSCM) had equivalent sensitivity and equivalent specificity compared to the other set. The least absolute shrinkage and selection operator method had high sensitivity and specificity than other methods, respectively. The investigated area of the region of interest had high specificity compared to the volume of interest. The imaging-to-surgery interval of 15 days had higher sensitivity and slightly low specificity than the others. Deeks' test indicates that there was no publication bias (P=0.71).ConclusionRadiomics-based MRI has high accuracy in predicting MVI in HCC, and it can be considered as a non-invasive method for assessing MVI in HCC.

Project description:BackgroundAs an indicator of tumor invasiveness, microvascular invasion (MVI) is a crucial risk factor for postoperative relapse, metastasis, and unfavorable prognosis in hepatocellular carcinoma (HCC). Nevertheless, the genetic mechanisms underlying MVI, particularly for Chinese patients, remain mostly uncharted.MethodsWe applied deep targeted sequencing on 66 Chinese HCC samples. Focusing on the telomerase reverse transcriptase (TERT) promoter (TERTp) and TP53 co-mutation (TERTp+/TP53+) group, gene set enrichment analysis (GSEA) was used to explore the potential molecular mechanisms of the TERTp+/TP53+ group on tumor progression and metastasis. Additionally, we evaluated the tumor immune microenvironment of the TERTp+/TP53+ group in HCC using multiplex immunofluorescence (mIF) staining.ResultsAmong the 66 HCC samples, the mutated genes that mostly appeared were TERT, TP53, and CTNNB1. Of note, we found 10 cases with TERTp+/TP53+, of which nine were MVI-positive and one was MVI-negative, and there was a co-occurrence of TERTp and TP53 (p < 0.05). Survival analysis demonstrated that patients with the TERTp+/TP53+ group had lower the disease-free survival (DFS) (p = 0.028). GSEA results indicated that telomere organization, telomere maintenance, DNA replication, positive regulation of cell cycle, and negative regulation of immune response were significantly enriched in the TERTp+/TP53+ group (all adjusted p-values (p.adj) < 0.05). mIF revealed that the TERTp+/TP53+ group decreased CD8+ T cells infiltration (p = 0.25) and enhanced PDL1 expression (p = 0.55).ConclusionsTERTp+/TP53+ was significantly enriched in MVI-positive patients, leading to poor prognosis for HCC patients by promoting proliferation of HCC cell and inhibiting infiltration of immune cell surrounding HCC. TERTp+/TP53+ can be utilized as a potential indicator for predicting MVI-positive patients and poor prognosis, laying a preliminary foundation for further exploration of co-mutation in HCC with MVI and clinical treatment.

Project description:BackgroundRadiomics has emerged as a new approach that can help identify imaging information associated with tumor pathophysiology. We developed and validated a radiomics nomogram for preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC).MethodsTwo hundred and eight patients with pathologically confirmed HCC (training cohort: n = 146; validation cohort: n = 62) who underwent preoperative gadoxetic acid-enhanced magnetic resonance (MR) imaging were included. Least absolute shrinkage and selection operator logistic regression was applied to select features and construct signatures derived from MR images. Univariate and multivariate analyses were used to identify the significant clinicoradiological variables and radiomics signatures associated with MVI, which were then incorporated into the predictive nomogram. The performance of the radiomics nomogram was evaluated by its calibration, discrimination, and clinical utility.ResultsHigher α-fetoprotein level (p = 0.046), nonsmooth tumor margin (p = 0.003), arterial peritumoral enhancement (p < 0.001), and the radiomics signatures of hepatobiliary phase (HBP) T1-weighted images (p < 0.001) and HBP T1 maps (p < 0.001) were independent risk factors of MVI. The predictive model that incorporated the clinicoradiological factors and the radiomic features derived from HBP images outperformed the combination of clinicoradiological factors in the training cohort (area under the curves [AUCs] 0.943 vs. 0.850; p = 0.002), though the validation did not have a statistical significance (AUCs 0.861 vs. 0.759; p = 0.111). The nomogram based on the model exhibited C-index of 0.936 (95% CI 0.895-0.976) and 0.864 (95% CI 0.761-0.967) in the training and validation cohort, fitting well in calibration curves (p > 0.05). Decision curve analysis further confirmed the clinical usefulness of the nomogram.ConclusionsThe nomogram incorporating clinicoradiological risk factors and radiomic features derived from HBP images achieved satisfactory preoperative prediction of the individualized risk of MVI in patients with HCC.

Dataset Information

Identification of serologic biomarkers for predicting microvascular invasion in hepatocellular carcinoma.

Publications

Identification of serologic biomarkers for predicting microvascular invasion in hepatocellular carcinoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets