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Abstract Background Gastric cancer (GC), a molecularly heterogeneous disease, is the third leading cause of cancer death worldwide. The majority of GC cases worldwide occur in East Asia, predominantly China. Mutational Signature Framework offers an elegant approach to identify mutational processes present in tumors. Methods To identify mutational signature patterns, we conducted whole exome sequencing (WES) analysis in Chinese patients with GC. Mutect2 and MutsigCV were used to identify significantly mutated genes in 175 Chinese GC cases using paired tumor-normal tissues. We investigated mutational signatures using Catalogue of Somatic Mutations in Cancer (COSMIC) Version 2 (V2) and Version 3 (V3). Results We identified 104 mutated genes with P

Abstract Background The progression of gallbladder cancer (GBC) is accompanied by abnormal fatty acid β-oxidation (FAO) metabolism. Different types of lipids perform various biological functions. This study aimed to determine the role of acyl carnitines in the molecular mechanisms of GBC progression. Methods Distribution of lipids in GBC was described by LC–MS-based lipidomics. Cellular localization, expression level and full-length of lncBCL2L11 were detected using fluorescence in situ hybridization (FISH) assays, subcellular fractionation assay and 5′ and 3′ rapid amplification of the cDNA ends (RACE), respectively. In vitro and in vivo experiments were used to verify the biological function of lncBCL2L11 in GBC cells. Methylated RNA Immunoprecipitation (MeRIP) was performed to detect the methylation levels of lncBCL2L11. RNA pull-down assay and RNA immunoprecipitation (RIP) assay were used to identify lncBCL2L11 interacting proteins. Co-Immunoprecipitation (Co-IP) and Western blot assay were performed to validate the regulatory mechanism of lncBCL2L11 and THO complex. Results Acylcarnitines were significantly up-regulated in GBC tissues. High serum triglycerides correlated to decreased survival in GBC patients and promoted tumor migration. LncBCL2L11 was identified in the joint analysis of highly metastatic cells and RNA sequencing data. LncBCl2L11 prevented the binding of THOC6 and THOC5 and causes the degradation of THOC5, thus promoting the accumulation of acylcarnitines in GBC cells, leading to the malignant progression of cancer cells. In addition, highly expressed acylcarnitines stabilized the expression of lncBCL2L11 through N6-methyladenosine methylation (m6A), forming a positive feedback regulation in tumor dissemination. Conclusions LncBCL2L11 is involved in gallbladder cancer metastasis through FAO metabolism. High lipid intake is associated with poor prognosis of GBC. Therefore, targeting lncBCL2L11 and its pathway-related proteins or reducing lipid intake may be significant for the treatment of GBC patients.

Abstract Background Gallbladder cancer (GBC) is the most prevalent and invasive biliary tract malignancy. As a GTPase-activating protein, Neurofibromin 1 (NF1) is a tumor suppressor that negatively regulates the RAS signaling pathway, and its abnormality leads to neurofibromatosis type 1 (NF-1) disease. However, the role of NF1 playing in GBC and the underlying molecular mechanism has not been defined yet. Methods A combination of NOZ and EH-GB1 cell lines as well as nude mice, were utilized in this study. mRNA expression and protein levels of NF1 and YAP1 were evaluated by quantitative real-time PCR (qRT-PCR), western blot (WB), and immunohistochemistry (IHC). In vitro and in vivo assays were performed to explore the biological effects of NF1 in NOZ and EH-GB1 cells via siRNA or lv-shRNA mediated knockdown. Direct interaction between NF1 and YAP1 was detected by confocal microscopy and co-immunoprecipitation (Co-IP), and further confirmed by GST pull-down assay and isothermal titration calorimetry assay (ITC). The stability of proteins was measured by western blot (WB) in the presence of cycloheximide. Results This study showed that a higher level of NF1 and YAP1 was found in GBC samples than in normal tissues and associated with worse prognoses. The NF1 knockdown impaired the proliferation and migration of NOZ in vivo and in vitro by downregulating YAP1 expression. Moreover, NF1 co-localized with YAP1 in NOZ and EH-GB1 cells, and the WW domains of YAP1 specifically recognized the PPQY motif of NF1. The structural modeling also indicated the hydrophobic interactions between YAP1 and NF1. On the other hand, YAP1 knockdown also impaired the proliferation of NOZ in vitro, phenocopying the effects of NF1 knockdown. Overexpression of YAP1 can partially rescue the impaired proliferation in NF1 stably knockdown cells. In mechanism, NF1 interacted with YAP1 and increased the stability of YAP1 by preventing ubiquitination. Conclusions Our findings discovered a novel oncogenic function of NF1 by directly interacting with YAP1 protein and stabilizing YAP1 to protect it from proteasome degradation in NOZ cells. NF1 may serve as a potential therapeutic target in GBC.

Abstract Background tRNA-derived fragments (tRFs) are newly discovered noncoding RNAs and regulate tumor progression via diverse molecular mechanisms. However, the expression and biofunction of tRFs in gallbladder cancer (GBC) have not been reported yet. Methods The expression of tRFs in GBC was detected by tRF and tiRNA sequencing in GBC tissues and adjacent tissues. The biological function of tRFs was investigated by cell proliferation assay, clonal formation assay, cell cycle assay, and xenotransplantation model in GBC cell lines. The molecular mechanism was discovered and verified by transcriptome sequencing, fluorescence in situ hybridization (FISH), target gene site prediction, and RNA binding protein immunoprecipitation (RIP). Results tRF-3013b was significantly downregulated in GBC compared with para-cancer tissues. Decreased expression of tRF-3013b in GBC patients was correlated with poor overall survival. Dicer regulated the production of tRF-3013b, and its expression was positively correlated with tRF-3013b in GBC tissues. Functional experiments demonstrated that tRF-3013b inhibited GBC cell proliferation and induced cell-cycle arrest. Mechanically, tRF-3013b exerted RNA silencing effect on TPRG1L by binding to AGO3, and then inhibited NF-κB. TPRG1L overexpression could rescue the effects of tRF-3013b on GBC cell proliferation. Conclusions This study indicated that Dicer-induced tRF-3013b inhibited GBC proliferation by targeting TPRG1L and repressed NF-κB, pointing to tRF-3013b as a novel potential therapeutic target of GBC.

Abstract 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.

Abstract Background Gemcitabine plus platinum as the first-line chemotherapy for cholangiocarcinoma (CCA) has limited efficacy. The aim of this study was to evaluate the effectiveness of modified FOLFIRINOX (mFOLFIRINOX) compared to that of gemcitabine plus oxaliplatin (Gemox) for patients with locally advanced or metastatic CCA. Methods From January 2016 to December 2019, consecutive patients who were diagnosed with locally advanced or metastatic CCA were treated with either mFOLFIRINOX or Gemox as a first-line chemotherapy. The main endpoint was Progression free survival (PFS). The second endpoints were Overall survival (OS), Disease control rate (DCR) and incidence of severe toxicity (grade 3–4). Tumors were evaluated at baseline and thence every 4–6 weeks. The study was designed and carried out in accordance with the principles of the declaration of Helsinki, approved by the Ethics Committee of Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine (XHEC-D-2020-154) and registered with ClinicalTrials.gov , number NCT04305288 (registration date: 12/03/2020). Results Of 49 patients in this study, 27 were in the FOLFIRINOX regimen group and 22 in the Gemox regimen group. There were no significant differences between groups in baseline characteristics. The DCR was 77.8% in the mFOLFIRINOX group and 63.5% in the Gemox group. The corresponding median PFS was 9.9 months (95% confidence interval [CI], 7.3–12.4) in the mFOLFIRINOX group versus 6.4 months (95% CI,3.6–9.2, p = 0.040) in the Gemox group. The corresponding median OS was 15.7 months (95% CI, 12.5–19.0) versus 12.0 months (95% CI, 9.3–14.8, p = 0.099). Significantly more grade 3–4 vomiting occurred in the mFOLFIRINOX than the Gemox groups (7 (25.9%) vs 1 (4.5%), p = 0.044). Conclusions First-line mFOLFIRINOX offered more promising results in patients with advanced or metastatic CCA.

Abstract Background Patients with metastatic or relapsed gallbladder cancer generally have a poor prognosis. Therefore, targeting metastasis is one arm of therapeutic strategies to treat gallbladder cancer. Methods Levels of translationally controlled tumor protein (TCTP) were measured in samples of gallbladder cancer by immunohistochemical staining. Wound healing, migration and invasion assays were used to investigate the motility of cells. Western blot assay was used to investigate the levels of TCTP and other proteins. Liver metastasis models and lung metastasis models were established to investigate the inhibitory effect of Dihydroartemisinin on gallbladder cancer metastasis. Results TCTP is aberrantly expressed in gallbladder cancer patients and associated with metastasis and a poor prognosis. Depleting TCTP significantly inhibited gallbladder cancer cell migration and invasion. We found that Dihydroartemisinin as a potent inhibitor of TCTP inhibited TCTP-dependent cell migration and invasion by reducing cell division control protein 42 homolog (Cdc42) activation. In addition, in mice with xenografted tumors, treatment with Dihydroartemisinin decreased gallbladder cancer cell metastases and improved survival. Conclusions These findings provide new insights into the therapeutic activity of Dihydroartemisinin as a treatment for gallbladder cancer metastasis.

In the original publication of this article [1], there are mistakes in Fig. 3A and Fig. 3D.