Dataset Information

Platelets' RNA as biomarker trove for differentiation of early-stage hepatocellular carcinoma from underlying cirrhotic nodules.

ABSTRACT:

Background & aims

Among the multiplicity of factors involved in rising incidence of hepatocellular carcinoma (HCC)-the second deadliest cancer, late diagnosis of early-stage HCC nodules originating from late-stage cirrhotic nodules is the most crucial. In recent years, Tumor-educated platelets (TEPs) have emerged as a strong multimodal tool to be used in liquid-biopsy of cancers because of changes in their mRNA content. This study assessed the reliability of selected mRNA repertoire of platelets as biomarkers to differentiate early HCC from late-stage cirrhotic nodules.

Methods

Quantitative real time PCR (qRT-PCR) was used to evaluate expression levels of selected platelets-specific mRNA between HCC patients compared to cirrhosis patients. ROC curve analysis assessed the sensitivity and specificity of the biomarkers.

Results

RhoA, CTNNB1 and SPINK1 showed a significant 3.3-, 3.2- and 3.18-folds upregulation, respectively, in HCC patients compared to cirrhosis patients while IFITM3 and SERPIND1 presented a 2.24-fold change. Strikingly, CD41+ platelets also demonstrated a marked difference of expression in HCC and cirrhosis groups.

Conclusions

Our study reports liquid biopsy-based platelets mRNA signature for early diagnosis of HCC from underlying cirrhotic nodules. Moreover, differential expression of CD41+ platelets in two groups provides new insights into a probable link between CD41 expression on platelets with the progression of cirrhosis to HCC.

SUBMITTER: Waqar W

PROVIDER: S-EPMC8409664 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundTo investigate whether fractal analysis of perfusion differentiates hepatocellular adenoma (HCA) subtypes and hepatocellular carcinoma (HCC) in non-cirrhotic liver by quantifying perfusion chaos using four-dimensional dynamic contrast-enhanced magnetic resonance imaging (4D-DCE-MRI).ResultsA retrospective population of 63 patients (47 female) with histopathologically characterized HCA and HCC in non-cirrhotic livers was investigated. Our population consisted of 13 hepatocyte nuclear factor (HNF)-1α-inactivated (H-HCAs), 7 β-catenin-exon-3-mutated (bex3-HCAs), 27 inflammatory HCAs (I-HCAs), and 16 HCCs. Four-dimensional fractal analysis was applied to arterial, portal venous, and delayed phases of 4D-DCE-MRI and was performed in lesions as well as remote liver tissue. Diagnostic accuracy of fractal analysis was compared to qualitative MRI features alone and their combination using multi-class diagnostic accuracy testing including kappa-statistics and area under the receiver operating characteristic curve (AUC). Fractal analysis allowed quantification of perfusion chaos, which was significantly different between lesion subtypes (multi-class AUC = 0.90, p < 0.001), except between I-HCA and HCC. Qualitative MRI features alone did not allow reliable differentiation between HCA subtypes and HCC (κ = 0.35). However, combining qualitative MRI features and fractal analysis reliably predicted the histopathological diagnosis (κ = 0.89) and improved differentiation of high-risk lesions (i.e., HCCs, bex3-HCAs) and low-risk lesions (H-HCAs, I-HCAs) from sensitivity and specificity of 43% (95% confidence interval [CI] 23-66%) and 47% (CI 32-64%) for qualitative MRI features to 96% (CI 78-100%) and 68% (CI 51-81%), respectively, when adding fractal analysis.ConclusionsCombining qualitative MRI features with fractal analysis allows identification of HCA subtypes and HCCs in patients with non-cirrhotic livers and improves differentiation of lesions with high and low risk for malignant transformation.