ABSTRACT
BACKGROUND: Overall Survival (OS) and Progression-Free Survival (PFS) analyses are crucial metrics for evaluating the efficacy and impact of treatment. This study evaluated the role of clinical biomarkers and dosimetry parameters on survival outcomes of patients undergoing 90Y selective internal radiation therapy (SIRT). MATERIALS/METHODS: This preliminary and retrospective analysis included 17 patients with hepatocellular carcinoma (HCC) treated with 90Y SIRT. The patients underwent personalized treatment planning and voxel-wise dosimetry. After the procedure, the OS and PFS were evaluated. Three structures were delineated including tumoral liver (TL), normal perfused liver (NPL), and whole normal liver (WNL). 289 dose-volume constraints (DVCs) were extracted from dose-volume histograms of physical and biological effective dose (BED) maps calculated on 99mTc-MAA and 90Y SPECT/CT images. Subsequently, the DVCs and 16 clinical biomarkers were used as features for univariate and multivariate analysis. Cox proportional hazard ratio (HR) was employed for univariate analysis. HR and the concordance index (C-Index) were calculated for each feature. Using eight different strategies, a cross-combination of various models and feature selection (FS) methods was applied for multivariate analysis. The performance of each model was assessed using an averaged C-Index on a three-fold nested cross-validation framework. The Kaplan-Meier (KM) curve was employed for univariate and machine learning (ML) model performance assessment. RESULTS: The median OS was 11 months [95% CI: 8.5, 13.09], whereas the PFS was seven months [95% CI: 5.6, 10.98]. Univariate analysis demonstrated the presence of Ascites (HR: 9.2[1.8,47]) and the aim of SIRT (segmentectomy, lobectomy, palliative) (HR: 0.066 [0.0057, 0.78]), Aspartate aminotransferase (AST) level (HR:0.1 [0.012-0.86]), and MAA-Dose-V205(%)-TL (HR:8.5[1,72]) as predictors for OS. 90Y-derived parameters were associated with PFS but not with OS. MAA-Dose-V205(%)-WNL, MAA-BED-V400(%)-WNL with (HR:13 [1.5-120]) and 90Y-Dose-mean-TL, 90Y-D50-TL-Gy, 90Y-Dose-V205(%)-TL, 90Y-Dose- D50-TL-Gy, and 90Y-BED-V400(%)-TL (HR:15 [1.8-120]) were highly associated with PFS among dosimetry parameters. The highest C-index observed in multivariate analysis using ML was 0.94 ± 0.13 obtained from Variable Hunting-variable-importance (VH.VIMP) FS and Cox Proportional Hazard model predicting OS, using clinical features. However, the combination of VH. VIMP FS method with a Generalized Linear Model Network model predicting OS using Therapy strategy features outperformed the other models in terms of both C-index and stratification of KM curves (C-Index: 0.93 ± 0.14 and log-rank p-value of 0.023 for KM curve stratification). CONCLUSION: This preliminary study confirmed the role played by baseline clinical biomarkers and dosimetry parameters in predicting the treatment outcome, paving the way for the establishment of a dose-effect relationship. In addition, the feasibility of using ML along with these features was demonstrated as a helpful tool in the clinical management of patients, both prior to and following 90Y-SIRT.
ABSTRACT
Background & Aims: Emerging evidence suggests that maternal obesity negatively impacts the health of offspring. Additionally, obesity is a risk factor for hepatocellular carcinoma (HCC). Our study aims to investigate the impact of maternal obesity on the risk for HCC development in offspring and elucidate the underlying transmission mechanisms. Methods: Female mice were fed either a high-fat diet (HFD) or a normal diet (ND). All offspring received a ND after weaning. We studied liver histology and tumor load in a N-diethylnitrosamine (DEN)-induced HCC mouse model. Results: Maternal obesity induced a distinguishable shift in gut microbial composition. At 40 weeks, female offspring of HFD-fed mothers (HFD offspring) were more likely to develop steatosis (9.43% vs. 3.09%, p = 0.0023) and fibrosis (3.75% vs. 2.70%, p = 0.039), as well as exhibiting an increased number of inflammatory infiltrates (4.8 vs. 1.0, p = 0.018) and higher expression of genes involved in fibrosis and inflammation, compared to offspring of ND-fed mothers (ND offspring). A higher proportion of HFD offspring developed liver tumors after DEN induction (79.8% vs. 37.5%, p = 0.0084) with a higher mean tumor volume (234 vs. 3 µm3, p = 0.0041). HFD offspring had a significantly less diverse microbiota than ND offspring (Shannon index 2.56 vs. 2.92, p = 0.0089), which was rescued through co-housing. In the principal component analysis, the microbiota profile of co-housed animals clustered together, regardless of maternal diet. Co-housing of HFD offspring with ND offspring normalized their tumor load. Conclusions: Maternal obesity increases female offspring's susceptibility to HCC. The transmission of an altered gut microbiome plays an important role in this predisposition. Impact and implications: The worldwide incidence of obesity is constantly rising, with more and more children born to obese mothers. In this study, we investigate the impact of maternal diet on gut microbiome composition and its role in liver cancer development in offspring. We found that mice born to mothers with a high-fat diet inherited a less diverse gut microbiome, presented chronic liver injury and an increased risk of developing liver cancer. Co-housing offspring from normal diet- and high-fat diet-fed mothers restored the gut microbiome and, remarkably, normalized the risk of developing liver cancer. The implementation of microbial screening and restoration of microbial diversity holds promise in helping to identify and treat individuals at risk to prevent harm for future generations.
