Three-dimensional visualization and evaluation of hilar cholangiocarcinoma resectability and proposal of a new classification.

BACKGROUND: As digital medicine has exerted profound influences upon diagnosis and treatment of hepatobiliary diseases, our study aims to investigate the accuracy of three-dimensional visualization and evaluation (3DVE) system in assessing the resectability of hilar cholangiocarcinoma (hCCA), and explores its potential clinical value. MATERIALS AND METHODS: The discovery cohort, containing 111 patients from April 2013 to December 2019, was retrospectively included to determine resectability according to revised criteria for unresectability of hCCA. 3D visualization models were reconstructed to evaluate resectability parameters including biliary infiltration, vascular involvement, hepatic atrophy and metastasis. Evaluation accuracy were compared between contrast-enhanced CT and 3DVE. Logistic analysis was performed to identify independent risk factors of R0 resection. A new comprehensive 3DVE classification of hCCA based on factors influencing resectability was proposed to investigate its role in predicting R0 resection and prognosis. The main outcomes were also analyzed in cohort validation, including 34 patients from January 2020 to August 2022. RESULTS: 3DVE showed an accuracy rate of 91% (95%CI 83.6-95.4%) in preoperatively evaluating hCCA resectability, significantly higher than 81% (95%CI 72.8-87.7%) of that of CT (p = 0.03). By multivariable analysis, hepatic artery involvement in 3DVE was identified an independent risk factor for R1 or R2 resection (OR = 3.5, 95%CI 1.4,8.8, P < 0.01). New 3DVE hCCA classification was valuable in predicting patients' R0 resection rate (p < 0.001) and prognosis (p < 0.0001). The main outcomes were internally validated. CONCLUSIONS: 3DVE exhibited a better efficacy in evaluating hCCA resectability, compared with contrast-enhanced CT. Preoperative 3DVE demonstrated hepatic artery involvement was an independent risk factor for the absence of R0 margin. 3DVE classification of hCCA was valuable in clinical practice.

Circulating immune index predicting the prognosis of patients with hepatocellular carcinoma treated with lenvatinib and immunotherapy.

Background: Immune checkpoint inhibitor (ICI)-based combination therapy has opened a new avenue for the treatment of multiple malignancies including hepatocellular carcinoma (HCC). However, considering the unsatisfactory efficacy, biomarkers are urgently needed to identify the patients most likely to benefit from ICI-based combination therapy. Methods: A total of 194 patients undergoing ICI-based combination therapy for unresectable HCC were retrospectively enrolled and divided into a training cohort (n = 129) and a validation cohort (n = 65) randomly. A novel circulating immune index (CII) defined as the ratio of white blood cell count (×109/L) to lymphocyte proportion (%) was constructed and its prognostic value was determined and validated. Results: Patients with CII ≤ 43.1 reported prolonged overall survival (OS) compared to those with CII > 43.1 (median OS: 24.7 vs 15.1 months; 6-, 12-, 18-month OS: 94.2%, 76.7%, 66.1% vs 86.4%, 68.2%, 22.8%, P = 0.019), and CII was identified as an independent prognostic factor for OS (hazard ratio, 2.24; 95% confidence interval, 1.17-4.31; P = 0.015). These results were subsequently verified in the validation cohort. Additionally, patients with low CII levels had improved best radiological tumor response (complete response, partial response, stable disease, progressive disease: 3%, 36%, 50%, 11% vs 0%, 27%, 46%, 27%; P = 0.037) and disease control rate (89% vs 73%; P = 0.031) in the pooled cohort and better pathologic response (pathologic complete response, major pathologic response, partial pathologic response, no pathologic response: 20%, 44%, 28%, 8% vs 0%, 0%, 40%, 60%; P = 0.005) in the neoadjuvant cohort. Detection of lymphocyte subsets revealed that an elevated proportion of CD4+ T cells was related to better OS, while the proportion of CD8+ T cells was not. Conclusions: We constructed a novel circulating immune biomarker that was capable of predicting OS and therapeutic efficacy for HCC patients undergoing ICI and lenvatinib combination therapy.

Prognostic model for predicting outcome and guiding treatment decision for unresectable hepatocellular carcinoma treated with lenvatinib monotherapy or lenvatinib plus immunotherapy.

Background: Lenvatinib monotherapy and combination therapy with immune checkpoint inhibitors (ICI) were widely applied for unresectable hepatocellular carcinoma (uHCC). However, many patients failed to benefit from the treatments. A prognostic model was needed to predict the treatment outcomes and guide clinical decisions. Methods: 304 patients receiving lenvatinib monotherapy or lenvatinib plus ICI for uHCC were retrospectively included. The risk factors derived from the multivariate analysis were used to construct the predictive model. The C-index and area under the receiver-operating characteristic curve (AUC) were calculated to assess the predictive efficiency. Results: Multivariate analysis revealed that protein induced by vitamin K absence or antagonist-II (PIVKA-II) (HR, 2.05; P=0.001) and metastasis (HR, 2.07; P<0.001) were independent risk factors of overall survival (OS) in the training cohort. Herein, we constructed a prognostic model called PIMET score and stratified patients into the PIMET-low group (without metastasis and PIVKA-II<600 mAU/mL), PIMET-int group (with metastasis or PIVKA-II>600 mAU/mL) and PIMET-high group (with metastasis and PIVKA-II>600 mAU/mL). The C-index of PIMET score for the survival prediction was 0.63 and 0.67 in the training and validation cohort, respectively. In the training cohort, the AUC of 12-, 18-, and 24-month OS was 0.661, 0.682, and 0.744, respectively. The prognostic performances of the model were subsequently validated. The AUC of 12-, 18-, and 24-month OS was 0.724, 0.726, and 0.762 in the validation cohort. Subgroup analyses showed consistent predictive value for patients receiving lenvatinib monotherapy and patients receiving lenvatinib plus ICI. The PIMET score could also distinguish patients with different treatment responses. Notably, the combination of lenvatinib and ICI conferred survival benefits to patients with PIMET-int or PIMET-high, instead of patients with PIMET-low. Conclusion: The PIMET score comprising metastasis and PIVKA-II could serve as a helpful prognostic model for uHCC receiving lenvatinib monotherapy or lenvatinib plus ICI. The PIMET score could guide the treatment decision and facilitate precision medicine for uHCC patients.

Efficacy and safety of lenvatinib for preventing tumor recurrence after liver transplantation in hepatocellular carcinoma beyond the Milan criteria.

Background: Lenvatinib is one of the first-line treatments for unresectable hepatocellular carcinoma (HCC). However, data are lacking on lenvatinib in the postoperative setting. Methods: This retrospective analysis enrolled 242 patients with HCC who underwent liver transplantation (LTx). Eligible patients were divided into 2 groups according to their use of adjuvant lenvatinib following LTx (lenvatinib, n=42; control, n=200). The primary outcome measures were overall survival (OS), time to recurrence (TTR), and safety. Kaplan-Meier analysis was applied to calculate the OS, while a competing risk model was used to estimate the cumulative incidence of recurrence. Results: The lenvatinib group showed more advanced tumors and a higher proportion of HCC beyond the Milan criteria (P<0.001) than the control group. There were no significant differences in both the OS and TTR between the 2 groups. After focusing on the patients with HCC beyond the Milan criteria, baseline characteristics were similar in the lenvatinib group (n=38) and the control group (n=102). Competing risk analysis showed lenvatinib significantly prolonged TTR after LTx versus the control group [sub-hazard ratio (sHR), 0.40; 95% confidence interval (CI): 0.17 to 0.93; P=0.031]. In the multivariate competing risk model, adjuvant lenvatinib was an independent protective factor for tumor recurrence after LTx in patients with HCC beyond the Milan criteria (sHR, 0.33; 95% CI: 0.13 to 0.83; P=0.018). The rate of early recurrence within t2 years after LTx was also significantly decreased in the lenvatinib group (15.8% vs. 33.3%, P=0.041). However, the lenvatinib group exhibited comparable OS with the control group in patients with HCC beyond the Milan criteria. Treatment-related adverse events (TRAEs) and Grade ≥3 TRAEs occurred in 40 (95.2%) and 13 (31%) patients who received adjuvant lenvatinib, respectively. No treatment-related death was reported. Conclusions: Postoperative lenvatinib administration may provide clinical benefits and is well tolerated in patients with HCC beyond the Milan criteria who undergo LTx.

Sorafenib-Loaded Cu2-xSe Nanoparticles Boost Photothermal-Synergistic Targeted Therapy against Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) accounts for the predominant form of liver malignancy and presents a leading cause of cancer-related death globally. Sorafenib (SOR), a first-line targeted drug for advanced HCC treatment, has a battery of untoward side effects. Photothermal therapy (PTT) has been utilized as an effective adjuvant in synergy with other approaches. However, little is known about the tumoricidal efficacy of combining SOR with PTT for HCC. Herein, a novel versatile nanoparticle, Cu2-xSe@SOR@PEG (CSP), that is based on a photothermal Cu2-xSe core and SOR for simultaneously reinforcing PTT and reducing the adverse effects of SOR was constructed. The synthesized CSP exhibited a remarkably enhanced therapeutic effect upon 808 nm laser irradiation via dampening HCC cell propagation and metastasis and propelling cell apoptosis. The intravenous administration of CSP substantially suppressed tumor growth in a xenograft tumor mouse model. It was noted that the CSP manifested low toxicity and excellent biocompatibility. Together, this work indicates a promising and versatile tool that is based on synergistic PTT and molecular-targeted therapy for HCC management.

Integration of Inflammation-Immune Factors to Build Prognostic Model Predictive of Prognosis and Minimal Residual Disease for Hepatocellular Carcinoma.

Background: Tumor recurrence after hepatectomy is high for hepatocellular carcinoma (HCC), and minimal residual disease (MRD) could be the underlying mechanism. A predictive model for recurrence and presence of MRD is needed. Methods: Common inflammation-immune factors were reviewed and selected to construct novel models. The model consisting of preoperative aspartate aminotransferase, C-reactive protein, and lymphocyte count, named ACLR, was selected and evaluated for clinical significance. Results: Among the nine novel inflammation-immune models, ACLR showed the highest accuracy for overall survival (OS) and time to recurrence (TTR). At the optimal cutoff value of 80, patients with high ACLR (> 80) had larger tumor size, higher Edmondson's grade, more vascular invasion, advanced tumor stage, and poorer survival than those with low ACLR (≤ 80) in the training cohort (5-year OS: 43.3% vs. 80.1%, P < 0.0001; 5-year TTR: 74.9% vs. 45.3%, P < 0.0001). Multivariate Cox analysis identified ACLR as an independent risk factor for OS [hazard ratio (HR) = 2.22, P < 0.001] and TTR (HR = 2.36, P < 0.001). Such clinical significance and prognostic value were verified in validation cohort. ACLR outperformed extant models, showing the highest area under receiver operating characteristics curve for 1-, 3-, and 5-year OS (0.737, 0.719, and 0.708) and 1-, 3-, and 5-year TTR (0.696, 0.650, and 0.629). High ACLR correlated with early recurrence (P < 0.001) and extremely early recurrence (P < 0.001). In patients with high ACLR, wide resection margin might confer survival benefit by decreasing recurrence (median TTR, 25.5 vs. 11.4 months; P = 0.037). Conclusions: The novel inflammation-immune model, ACLR, could effectively predict prognosis, and the presence of MRD before hepatectomy and might guide the decision on resection margin for patients with HCC.

The molecular biology of pancreatic adenocarcinoma: translational challenges and clinical perspectives.

Pancreatic cancer is an increasingly common cause of cancer mortality with a tight correspondence between disease mortality and incidence. Furthermore, it is usually diagnosed at an advanced stage with a very dismal prognosis. Due to the high heterogeneity, metabolic reprogramming, and dense stromal environment associated with pancreatic cancer, patients benefit little from current conventional therapy. Recent insight into the biology and genetics of pancreatic cancer has supported its molecular classification, thus expanding clinical therapeutic options. In this review, we summarize how the biological features of pancreatic cancer and its metabolic reprogramming as well as the tumor microenvironment regulate its development and progression. We further discuss potential biomarkers for pancreatic cancer diagnosis, prediction, and surveillance based on novel liquid biopsies. We also outline recent advances in defining pancreatic cancer subtypes and subtype-specific therapeutic responses and current preclinical therapeutic models. Finally, we discuss prospects and challenges in the clinical development of pancreatic cancer therapeutics.

[Syntheses and luminescence investigation of CaAl12O19:xMn(4+) red phosphors].

CaAl12O19:xMn(4+) (x=0.0~0.00184 mol) red phosphors were prepared by high-temperature solid state method. Different influencing factors, i. e. the doping amount of Mn(4+), and sintering temperature, were investigated by the orthogonal experiment design. The optimum conditions for preparing CaAl12O19:xMn(4+) phosphors are: sintering temperature 1500 °C, and x=0.0147 mol. It emits strong deep red light with emission maximal peak at 656 nm, and two shoulder peaks (643 and 666 nm), the corresponding excitation peak is located at 470 nm. The 656 nm emission peak is ascribed to the (2)E-->(4)A2 transition, and the shoulder peaks (643 and 666 nm) are attributed to phonon sideband transitions. The 470 nm excitation peak is ascribed to the ligand-field (4)A2-->(4)T2 transition (d-->d band). Owing to the fact that the excitation peak (470 nm) is near the emission (460 nm) of commercial LED chips, it is quite suitable for red light candidate for LED light resources.