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Background Liver cancer remains the leading cause of cancer death globally, and the treatment strategies are distinct for each type of malignant hepatic tumors. However, the differential diagnosis before surgery is challenging and subjective. This study aims to build an automatic diagnostic model for differentiating malignant hepatic tumors based on patients’ multimodal medical data including multi-phase contrast-enhanced computed tomography and clinical features. Methods Our study consisted of 723 patients from two centers, who were pathologically diagnosed with HCC, ICC or metastatic liver cancer. The training set and the test set consisted of 499 and 113 patients from center 1, respectively. The external test set consisted of 111 patients from center 2. We proposed a deep learning model with the modular design of SpatialExtractor-TemporalEncoder-Integration-Classifier (STIC), which take the advantage of deep CNN and gated RNN to effectively extract and integrate the diagnosis-related radiological and clinical features of patients. The code is publicly available at https://github.com/ruitian-olivia/STIC-model. Results The STIC model achieved an accuracy of 86.2% and AUC of 0.893 for classifying HCC and ICC on the test set. When extended to differential diagnosis of malignant hepatic tumors, the STIC model achieved an accuracy of 72.6% on the test set, comparable with the diagnostic level of doctors’ consensus (70.8%). With the assistance of the STIC model, doctors achieved better performance than doctors’ consensus diagnosis, with an increase of 8.3% in accuracy and 26.9% in sensitivity for ICC diagnosis on average. On the external test set from center 2, the STIC model achieved an accuracy of 82.9%, which verify the model’s generalization ability. Conclusions We incorporated deep CNN and gated RNN in the STIC model design for differentiating malignant hepatic tumors based on multi-phase CECT and clinical features. Our model can assist doctors to achieve better diagnostic performance, which is expected to serve as an AI assistance system and promote the precise treatment of liver cancer.

Classically activated M1 macrophages and alternatively activated M2 macrophages are two polarized subsets of macrophages at the extreme ends of a constructed continuum. In the field of cancer research, M2 macrophage reprogramming is defined as the repolarization of pro-tumoral M2 to anti-tumoral M1 macrophages. It is known that colony-stimulating factor 1 (CSF1)/CSF1 receptor (CSF1R) and CSF2/CSF2R signaling play important roles in macrophage polarization. Targeting CSF1/CSF1R for M2 macrophage reprogramming has been widely performed in clinical trials for cancer therapy. Other targets for M2 macrophage reprogramming include Toll-like receptor 7 (TLR7), TLR8, TLR9, CD40, histone deacetylase (HDAC), and PI3Kγ. Although macrophages are involved in innate and adaptive immune responses, M1 macrophages are less effective at phagocytosis and antigen presenting, which are required properties for the activation of T cells and eradication of cancer cells. Similar to T and dendritic cells, the “functionally exhausted” status might be attributed to the high expression of programmed death-ligand 1 (PD-L1) or programmed cell death protein 1 (PD-1). PD-L1 is expressed on both M1 and M2 macrophages. Macrophage reprogramming from M2 to M1 might increase the expression of PD-L1, which can be transcriptionally activated by STAT3. Macrophage reprogramming or PD-L1/PD-1 blockade alone is less effective in the treatment of most cancers. Since PD-L1/PD-1 blockade could make up for the defect in macrophage reprogramming, the combination of macrophage reprogramming and PD-L1/PD-1 blockade might be a novel treatment strategy for cancer therapy.

BackgroundPrevious nomograms for intrahepatic cholangiocarcinoma (ICC) were conducted to predict overall survival, which could be influenced by various factors. Herein, we conducted our nomogram to predict recurrence of the tumor only after hepatic resection.MethodsThe nomogram was established with prognostic factors for the relapse-free survival (RFS) analyzed from our single center cohort and was evaluated by comparing with the American Joint Committee on Cancer (AJCC) staging system for the predictive accuracy.ResultsSeropositivity of hepatitis B surface antigen (hazard ratio [HR], 0.505; 95% confidence interval [CI], 0.279 to 0.914; P = 0.024), tumor size of larger than 5 cm (HR, 1.947; 95% CI, 1.177 to 3.219; P = 0.009), Child-Pugh score of B (HR, 3.067; 95% CI, 1.293 to 7.275; P = 0.011), and lymph node metastasis (HR, 2.790; 95% CI, 1.628 to 4.781; P < 0.001) were found to be independent prognostic factors that significantly affected RFS. The calibration curve for the prediction revealed excellent agreement between estimation by our stratification system and actual RFS. The concordance C index of the nomogram (0.71; 95% CI, 0.65 to 0.77) revealed to be significantly higher than the AJCC staging system (0.66; 95% CI, 0.60 to 0.72). In the validation cohort, our risk stratification system (C-index 0.65; 95% CI, 0.59 to 0.71) also revealed more precise prediction than the AJCC staging system (C-index, 0.57; 95% CI, 0.50 to 0.64).ConclusionsOur nomogram could more accurately predict recurrence of ICC after hepatic resection than the AJCC staging system.

Pyroptosis, a proinflammatory form of programmed cell death, plays important roles in the pathogenesis of many diseases. Inflammasome activation, which has been shown in hepatic ischemia-reperfusion injury (IRI), is demonstrated to be closely associated with pyroptosis, indicating that pyroptosis may occur and perform functions in hepatic IRI. However, there is no direct evidence showing the function of pyroptosis in hepatic IRI. In this study, by detecting the pyroptosis markers, we showed that pyroptosis may be induced during hepatic IRI. Furthermore, by adopting caspase-1 inhibitors, we showed that inhibition of pyroptosis could significantly ameliorate liver injury and suppress inflammatory response during hepatic IRI. Interestingly, caspase-1 inhibitors have no protective effects on in vitro hepatocytes under hypoxic reoxygenation condition. To investigate pyroptosis induced in which specific cell types may affect hepatic IRI, we generated hepatocyte-specific Gsdmd-knockout (Hep-Gsdmd −/−) and myeloidspecific Gsdmd-knockout (LysmCre + Gsdmd f/f) mice. Functional experiments showed that compared to control mice (Gsdmd f/f), there were alleviated liver injury and inflammation in LysmCre + Gsdmd f/f mice, but not in AlbCre + Gsdmd f/f mice. In parallel in vitro studies, cytokine expression and production decreased in bone-marrow-derived macrophages and Kupffer cells from LysmCre + Gsdmd f/f mice compared to their controls. Our findings demonstrated that pyroptosis in innate immune cells aggravates hepatic IRI and implied that hepatic IRI could be protected by blocking pyroptosis, which may become a potential therapeutic target in the clinic.

Cancer stem cells contribute to a high rate of recurrence and chemotherapeutic resistance in many types of cancer, including intrahepatic cholangiocarcinoma (ICC). Inhibitor of differentiation 3 (ID3) has been reported to promote cancer stem cells, but its role in ICC is obscure. In this study, we identified that ID3 is highly expressed in human ICC tissues compared with matched normal tissues and correlates with poor prognosis. Functional studies demonstrate that ID3 is required for stemness maintenance in cholangiocarcinoma both in vitro and in vivo . Consistent with the regulation of cancer stem cell features by ID3, transgenic expression of ID3 enhances chemoresistance of cholangiocarcinoma cells. Moreover, we found that ICC patients with low ID3 levels benefited from postoperative transarterial chemoembolization, whereas patients with high ID3 levels did not, indicating the significance of ID3 in individualized ICC therapy. Mechanistically, ID3 could interact with E47 and block E47 recruitment to the promoter of β-catenin, which leads to activation of Wnt/β-catenin signaling. Conclusion: Our results show that ID3 could promote the stemness of ICC by increasing the transcriptional activity of β-catenin and could serve as a biomarker in predicting ICC patients' response to adjuvant chemotherapeutics.

Liver fibrosis is a global health problem and previous studies have demonstrated that reactive oxygen species (ROS) play important roles in fibrogenesis. Parkinson disease (autosomal recessive, early onset) 7 (Park7) also called DJ-1 has an essential role in modulating cellular ROS levels. DJ-1 therefore may play functions in liver fibrogenesis and modulation of DJ-1 may be a promising therapeutic approach. Here, wild-type (WT) and DJ-1 knockout (DJ-1 KO) mice were administrated with carbon tetrachloride (CCl4) to induce liver fibrosis or acute liver injury. Results showed that DJ-1 depletion significantly blunted liver fibrosis, accompanied by marked reductions in liver injury and ROS production. In the acute CCl4 model, deficiency of DJ-1 showed hepatic protective functions as evidenced by decreased hepatic damage, reduced ROS levels, diminished hepatic inflammation and hepatocyte proliferation compared to WT mice. In vitro hepatic stellate cells (HSCs) activation assays indicated that DJ-1 has no direct effect on the activation of HSCs in the context of with or without TGFβ treatment. Thus our present study demonstrates that in CCl4-induced liver fibrosis, DJ-1 deficiency attenuates mice fibrosis by inhibiting ROS production and liver injury, and further indirectly affecting the activation of HSCs. These results are in line with previous studies that ROS promote HSC activation and fibrosis development, and suggest the therapeutic value of DJ-1 in treatment of liver fibrosis.

Hepatitis B virus (HBV) infection has been reported to be associated with non‐Hodgkin lymphoma (NHL). However, the evidence is limited to the seroepidemiological study. There is a lack of evidence showing the HBV infection and integration in NHL cells. Here, we reported that in the Shanghai area, the positive rates of serum HBsAg (OR: 3.11; 95% CI: 2.20‐4.41) and HBeAg (OR: 3.99; 95% CI: 1.73‐9.91) were significantly higher in patients with NHL. HBsAg, HBcAg and HBV DNA were detected in 34.4%, 45.2% and 47.0% of the NHL tissues, respectively. Furthermore, by using a high‐throughput viral integration detection approach (HIVID), integrated HBV DNA was identified from 50% (6/12) HBV‐related NHL tissues. There were a total of 313 HBV integration sites isolated from the NHL tissues, among which four protein‐coding genes (FAT2, SETX, ITGA10 and CD63) were interrupted by HBV DNA in their exons. Seven HBV preferential target genes (ANKS1B, HDAC4, EGFLAM, MAN1C1, XKR6, ZBTB38 and CCDC91) showed significantly altered expression levels in NHL, suggesting a potential role of these genes in NHL development. Taken together, HBV integration is a common phenomenon in NHL. This finding opens up a new direction of research into the mechanistic link between HBV infection and NHL.