Kai Zhu

Immune checkpoint inhibitor (ICI) based combined neoadjuvant/conversion therapy (NAT) is increasingly utilized in the management of initially unresectable intrahepatic cholangiocarcinoma (iCCA). However, immune-related pathologic response (irPR) features and immunotherapeutic response score (ITRS) remain poorly understood in iCCA.This study enrolled 147 iCCA patients who received NAT. irPR features (tumor infiltrating lymphocyte, tertiary lymphoid structure, lymphoid aggregate, plasma cell infiltration, granuloma, neutrophil, foamy macrophage, cholesterol cleft, hemosiderin macrophage, giant cell, neovascularization and mature fibrosis) were accessed on routinely processed hematoxylin-eosin stained post-NAT surgical resection specimen tumor bed slides. Kaplan-Meier and Cox regression analyses were used to investigate irPR features and ITRS correlations with recurrence-free survival (RFS) and overall survival (OS).The irPR features were identified in the post-NAT surgical resection specimen of iCCA. Six irPR features were included in ITRS. A binary ITRS scheme was developed, wherein patients classified as ITRS-low exhibited significantly better OS (hazard ratio [HR]:3.03; 95% confidence interval [CI]: 1.55-5.89, P < 0.01) and RFS (HR:1.94; CI: 1.24-3.03, P = 0.03) compared to those in the ITRS-high group, based on univariate analysis. In multivariate analysis including lymphovascular invasion, perineural invasion and major pathologic response, ITRS scheme was also found to be an independent prognostic factor for OS (HR: 1.95; 95% CI: 1.02-4.27, P = 0.04).An irPR features-based ITRS scheme significantly predicts OS and RFS in post NA iCCA patients. The ITRS is feasible for implementation in routine diagnostic pathology practice and offers novel insights into resistance mechanisms associated with immunotherapy.

Background and Aims: Accurate N-staging of intrahepatic cholangiocarcinoma (iCCA) remains challenging using noninvasive approaches. We aimed to develop a model to refine lymph node (LN) involvement stratification and inform therapeutic consideration. Approach and Results: This study enrolled a discovery cohort (n=682), an internal test cohort from the FU-iCCA (n=204), and an external multicenter cohort (n=88) for model development, and a neoadjuvant therapy (NAT) cohort (n=145) for therapeutic evaluation of the model. A SwinU–CliRad framework was constructed by integrating Swin UNEt TRansformers (Swin UNETR)–based magnetic resonance imaging–derived outputs of LN involvement with clinicoradiological features. Correlations between SwinU outputs and tumor multi-omics profiles were explored. The SwinU–CliRad model achieved areas under the curve (AUCs) of 0.932, 0.867, and 0.888 in LN risk stratification, and outperformed radiologist-based assessments by correcting more misclassifications than it introduced across the discovery, internal, and external test cohorts (18.8% vs. 7.3%, 18.1% vs. 4.9%, and 17.0% vs. 5.7%), respectively. In the NAT cohort, patients classified as high LN-involved risk by the SwinU–CliRad exhibited lower residual viable tumor rates than those with low LN-involved risk, with higher rates of pathological complete response (12.0% vs. 4.2%) and major pathological response (14.0% vs. 8.4%). SwinU outputs were associated with KRAS mutations, MUC5AC overexpression, and the large-duct histological subtype. Single-cell RNA sequencing analysis linked LN involvement to an immune-suppressive stroma tumor microenvironment. Conclusions: The SwinU–CliRad model can serve as a biologically interpretable tool for LN risk stratification in iCCA surgical candidates, with high-risk patients identified by the model potentially deriving benefit from NAT.

Neoadjuvant therapy (NAT) is increasingly used to treat patients with initially unresectable intrahepatic cholangiocarcinoma (iCCA). A histopathologic grading system for residual tumors that can predict patient survival is lacking in the literature. This retrospective study enrolled 151 iCCA patients who received NAT. The percentage of residual viable tumor (%RVT) extent was calculated by RVT surface area/total tumor bed area ×100 and scored in 5% increments. Kaplan-Meier and Cox regression analyses were used to investigate its correlations with recurrence-free survival (RFS) and overall survival (OS). Tumor regression grading by the College of American Pathologists (CAP) and MD Anderson (MDA) methodologies were also validated. A 10% RVT-based tumor regression score (TRS) showed a significant correlation with both OS and RFS. TRS and major pathologic response (mPR) were therefore defined as follows: TRS 1/mPR, tumor with 0 to 10% RVT; TRS 2, more than 10% RVT. Patients graded as TRS 1/mPR had superior OS (P=0.006) and RFS (PP=0.045) and RFS (HR: 0.474; 95% CI: 0.231-0.974, P=0.042). As for the CAP and MDA grading methodologies, they were found to correlate with RFS (CAP: P=0.002; MDA: P=0.001), but not with OS (CAP: P=0.181; MDA: P=0.09). Our study revealed that a TRS of ≤10% RVT significantly correlates with longer OS and RFS and can be suggested as an mPR in iCCA. This indicator is easily applicable, prognostically relevant, and could be further validated in future prospective clinical trials.

Tumor budding (TB) has been associated with poor survival in a variety of cancers including intrahepatic cholangiocarcinoma (iCCA). As tumor histomorphological features are significantly altered after neoadjuvant therapy (NAT), our study aims to assess the prognostic significance of TB in iCCA patients before and after NAT, by the modified International Tumor Budding Consensus Conference (ITBCC) criteria. 147 NAT-treated iCCA cases were included in this study. In biopsy specimens obtained before NAT, the TB-positive subgroup had lower overall survival (OS) in univariate analysis (P = 0.010). In resection specimens obtained after NAT, the TB-positive subgroup had reduced OS (P = 0.002) and recurrence-free survival (RFS) (P = 0.013) in univariate analysis. In multivariate analysis including TNM stage, lymphovascular invasion and perineural invasion, TB-positive in post-NAT resection was also found as an independent prognostic factor for both OS and RFS (OS, HR, 3.005; 95% CI, 1.333–6.775, P = 0.008; RFS, HR, 1.748; 95% CI, 1.085–2.816, P = 0.022). In conclusion, assessing the presence of TB by modified ITBCC criteria provides robust prognostic information in the NAT setting of iCCA patients and can be considered to be included in routine pathological reporting.

Background & Aims: We aimed to develop a Transformer‐based deep learning (DL) network for prognostic stratification in hepatocellular carcinoma (HCC) patients undergoing RFA.Methods: A Swin Transformer DL network was trained to establish associations between magnetic resonance imaging (MRI) datasets and the ground truth of microvascular invasion (MVI) based on 696 surgical resection (SR) patients with solitary HCC ≤3 cm, and was validated in an external cohort (n = 180). The multiphase MRI‐based DL risk outputs using an optimal threshold of .5 was employed as a MVI classifier for prognosis stratification in the RFA cohort (n = 180).Results: Over 90% of all enrolled patients exhibited hepatitis B virus infection. Liver cirrhosis was significantly more prevalent in the RFA cohort compared to the SR cohort (72.2% vs. 44.1%, p < .001). The MVI risk outputs exhibited good performance (area under the curve values = .938 and .883) for predicting MVI in the training and validation cohort, respectively. The RFA patients at high risk of MVI classified by the MVI classifier demonstrated significantly lower recurrence‐free survival (RFS) and overall survival rates at 1, 3 and 5 years compared to those classified as low risk (p < .001). Multivariate cox regression modelling of a‐fetoprotein > 20 ng/mL [hazard ratio (HR) = 1.53; 95% confidence interval (95% CI): 1.02–2.33, p = .047], high risk of MVI (HR = 3.76; 95% CI: 2.40–5.88, p < .001) and unfavourable tumour location (HR = 2.15; 95% CI: 1.40–3.29, p = .001) yielded a c‐index of .731 (bootstrapped 95% CI: .667–.778) for evaluating RFS after RFA. Among the three risk factors, MVI was the most powerful predictor for intrahepatic distance recurrence.Conclusions: The proposed MVI classifier can serve as a valuable imaging biomarker for prognostic stratification in early‐stage HCC patients undergoing RFA.

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the world. Currently, surgical resection, liver transplantation, and local ablation are considered curative therapeutic practices for HCC. The diagnosis of HCC without pathologic confirmation is achieved by analyzing serum alpha-fetoprotein (AFP) levels combined with imaging techniques, including ultrasonography, magnetic resonance imaging, and computerized tomography. Although progress has been made in the diagnosis and management of HCC, its prognosis remains dismal. Various new technologies have identified numerous novel biomarkers with potential diagnostic as well as prognostic value, including Dickkopf-1 and Golgi protein 73. These biomarkers not only help in the early diagnosis and prediction of prognosis, but also assist in identifying potential targets for therapeutic interventions. In this article, we provide an up-to-date review of the biomarkers that are used for early diagnosis, prognosis prediction, and personalized treatment of HCC.