Intrahepatic cholangiocarcinoma (ICC) is a liver tumor featured by challenges of non-invasive early diagnosis and a higher prevalence rate in Asian countries. These characteristics necessitate the development of liquid biopsy and immunotherapy methods to improve the prognosis of patients with ICC. Herein, we conducted a pilot study on the transcriptome of tumor tissues, adjacent normal tissues, and plasma exosomes of Asian patients with ICC from northern and southern China. We identified a subgroup of immunogenic Asian ICC, which is different from Caucasian ICC and is characterized by T cell exhaustion and neutrophil extracellular traps. The levels of circ-PTPN22 (hsa_circ_0110529) and circ-ADAMTS6 (hsa_circ_0072688), potential circRNA biomarkers, were elevated in the ICC tumor tissues and plasma exosomes of this subgroup than in the other subgroups and normal controls. These circRNAs were derived from post-transcriptional backsplicing of PTPN22 and ADAMTS6 that were expressed in T cells and endothelial cells, respectively, in the ICC microenvironment. Our results revealed a subgroup of Asian ICC characterized by T cell exhaustion and neutrophil extracellular traps and marked by elevated levels of circ-PTPN22 and circ-ADAMTS6 in tumor tissues and plasma exosomes. This subgroup is potentially detectable by plasma exosomal circRNAs and treatable with immune checkpoint blockade.

Background: Dynamic PET with kinetic modeling was reported to be potentially helpful in the assessment of hepatic malignancy. In this study, a kinetic modeling analysis was performed on hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) from dynamic FDG positron emission tomography/computer tomography (PET/CT) scans. Methods: A reversible two-tissue compartment model with dual blood input function, which takes into consideration the blood supply from both hepatic artery and portal vein, was used for accurate kinetic modeling of liver dynamic ¹⁸F-FDG PET imaging. The blood input functions were directly measured as the mean values over the VOIs on descending aorta and portal vein respectively. And the contribution of hepatic artery to the blood input function was optimization-derived in the process of model fitting. The kinetic model was evaluated using dynamic PET data acquired on 24 patients with identified hepatobiliary malignancy. 38 HCC or ICC identified lesions and 24 healthy liver regions were analyzed. Results: Results showed significant differences in kinetic parameters $${K}_{1}-{k}_{4}$$K 1 - k 4 , blood supplying fraction $${f}_{A}$$f A , and metabolic rate constant $${K}_{i}$$K i between malignant lesions and healthy liver tissue. And significant differences were also observed in $${K}_{1}$$K 1 , $${k}_{3}$$k 3 , $${f}_{A}$$f A and $${K}_{i}$$K i between HCC and ICC lesions. Further investigations of the effect of SUV measurements on the derived kinetic parameters were conducted. And results showed comparable effectiveness of the kinetic modeling using either SUVmean or SUVmax measurements. Conclusions: Dynamic 18F-FDG PET imaging with optimization-derived hepatic artery blood supply fraction dual-blood input function kinetic modeling can effectively distinguish malignant lesions from healthy liver tissue, as well as HCC and ICC lesions.

Single-cell sequencing technology refers to the sequencing of the genome, transcriptome and epigenome in one single cell. Comparing to traditional histology, single-cell sequencing can reveal the genetic heterogeneity among different cells. Due to the complex pathogenesis and various pathological types of hepatocellular carcinoma (HCC), studies on the heterogeneity of tumor cells confer improvement for its clinical diagnosis, treatment and prognosis. This article summarizes the principal basis and development of single-cell sequencing technology, as well as its increasing application in the field of HCC.

Background: This study was designed to investigate the prognostic value of the lymphocyte to monocyte ratio (LMR) in patients with gallbladder carcinoma (GBC). Patients and Methods: We retrospectively enrolled 154 consecutive GBC patients from 2005 to 2017 in this study. The LMR of preoperative blood samples was calculated by dividing the lymphocyte count by the monocyte count. A receiver operating characteristic (ROC) curve was employed to identify the optimal cut-off value of the LMR in the determination of overall survival (OS). The Kaplan–Meier method was utilized to assess OS, and the Log rank test was employed to compare survival differences. Univariate and multivariate Cox regression analyses were conducted to detect independent prognostic indicators. Results: The optimal cut-off point for the LMR was 4.76 according to the ROC curve. Patients ≤ 60 years old with an LMR ≤ 4.76 experienced significantly worse OS than those with an LMR > 4.76 (hazard ratio (HR): 0.399, 95% confidence interval (CI): 0.265– 0.602, P< 0.001); however, the prognostic value of the LMR was not determined in patients > 60 years old or among the entire study cohort (both P> 0.05). Significantly poorer OS was observed in patients > 60 years with an LMR ≤ 4.21 compared to those with an LMR > 4.21 (HR: 1.830, 95% CI: 1.129– 2.967, P=0.014). Multivariate Cox regression analysis indicated that both the high and low LMR cut-off values were independent risk factors for OS (HR: 0.272, 95% CI: 0.105– 0.704, P=0.007; HR: 0.544, 95% CI: 0.330– 0.895, P=0.017). Conclusion: The LMR is an independent prognostic indicator for GBC patients, the cut-off value of which is age dependent.

Although KIAA0101 is involved in many diseases, its expression and prognostic value in HCC remain undefined. According to CCLE, KIAA0101 is highly expressed in HCC, with a weak positive correlation between copy number and gene expression. Four studies involving 760 samples in ONCOMINE report elevated KIAA0101 expression in HCC (p=3.11E-22). The KM plotter revealed high KIAA0101 expression to be associated with worse overall survival in HCC (HR=2.09, p=4.1e-05); this prognostic power was stronger for male than female, early-stage than advanced-stage, and Asian than Caucasian patients. RNA sequencing data for 8 pairs of HCC and adjacent tissue samples validated the significantly high KIAA0101 level (p=0.00497). Moreover, functional annotations of 31 KIAA0101-coexpressed genes show enrichment of terms associated with mitosis, cytoskeleton construction, and chromosome segregation. Among 9 genes having STRING-validated protein-protein interactions with KIAA0101, two are involved in virus-related pathways. Alternative splicing analysis indicated higher expression of variant 1 and variant 2 in HCC and no significant differences in exon usage of KIAA0101 between cancer and normal tissues. These findings support that KIAA0101 is a potential prognostic biomarker for HCC and highlight the association between virus infection and the mechanism underlying the process by which KIAA0101 contributes to poor prognosis of patients.