Predicting human epidermal growth factor receptor 2 status of patients with gastric cancer by computed tomography and clinical features.

Background: There have been no studies on predicting human epidermal growth factor receptor 2 (HER2) status in patients with resectable gastric cancer (GC) in the neoadjuvant and perioperative settings. We aimed to investigate the use of preoperative contrast-enhanced computed tomography (CECT) imaging features combined with clinical characteristics for predicting HER2 expression in GC. Methods: We retrospectively enrolled 301 patients with GC who underwent curative resection and preoperative CECT. HER2 status was confirmed by postoperative immunohistochemical analysis with or without fluorescence in situ hybridization. A prediction model was developed using CECT imaging features and clinical characteristics that were independently associated with HER2 status using multivariate logistic regression analysis. Receiver operating characteristic curves were constructed and the performance of the prediction model was evaluated. The bootstrap method was used for internal validation. Results: Three CECT imaging features and one serum tumor marker were independently associated with HER2 status in GC: enhancement ratio in the arterial phase (odds ratio [OR] = 4.535; 95% confidence interval [CI], 2.220-9.264), intratumoral necrosis (OR = 2.64; 95% CI, 1.180-5.258), tumor margin (OR = 3.773; 95% CI, 1.968-7.235), and cancer antigen 125 (CA125) level (OR = 5.551; 95% CI, 1.361-22.651). A prediction model derived from these variables showed an area under the receiver operating characteristic curve of 0.802 (95% CI, 0.740-0.864) for predicting HER2 status in GC. The established model was stable, and the parameters were accurately estimated. Conclusions: Enhancement ratio in the arterial phase, intratumoral necrosis, tumor margin, and CA125 levels were independently associated with HER2 status in GC. The prediction model derived from these factors may be used preoperatively to estimate HER2 status in GC and guide clinical treatment.

The association between education and premature mortality in the Chinese population: a 10-year cohort study.

Background: Recent studies have shown significant associations between education and premature mortality. However, the relationship differs across countries. We aimed to present the latest evidence on the educational inequalities in premature mortality in the Chinese population. Methods: We linked two databases, to establish a population-based, ten-year cohort spanning 2010 to 2020. Cox proportional hazard regression analyses adjusting for age, sex and urbanicity were conducted for all-cause mortality, and competing risk models were fitted for cause-specific mortality. We calculated population attributable fraction (PAF) using the hazard ratios (HRs) obtained by regression analyses. Additionally, we fitted models adjusting for risk factors and investigated the mediating effect of income, smoking, alcohol consumption and diets. Findings: Compared with individuals with upper secondary and above education, the HR for premature all-cause mortality for those with less than primary education was 1.93 (95% CI: 1.72-2.19). The HRs were the highest for deaths from respiratory diseases (HR = 3.09, 95% CI 1.82-5.27). The excess risk of premature mortality associated with low education was higher among women and urban population. The association of education remained significant after accounting for risk factors, and income was the main mediator, which accounted for 23.0% of mediation in men and 11.1% in women. Interpretation: The study's findings support the increased risk of premature mortality associated with low education, particularly in women and urban populations. The considerable number of deaths attributed to educational inequality underscores the necessity for more effective and targeted public health interventions. Funding: Chinese Central Government.

Terf2ip deficiency accelerates non-alcoholic steatohepatitis through regulating lipophagy and fatty acid oxidation via Sirt1/AMPK pathway.

BACKGROUND & AIMS: Our previous study has demonstrated that Telomeric repeat-binding factor 2-interacting protein 1(Terf2ip), played an important role in hepatic ischemia reperfusion injury. This study is aimed to explore the function and mechanism of Terf2ip in non-alcoholic steatohepatitis (NASH). METHODS: The expression of Terf2ip was detected in liver tissue samples obtained from patients diagnosed with NASH. Mice NASH models were constructed by fed with high-fat diet (HFD) or methionine/choline deficient diet (MCD) in Terf2ip knockout and wild type (WT) mice. To further investigate the role of Terf2ip in NASH, adeno-associated viruses (AAV)-Terf2ip was administrated to mice. RESULTS: We observed a significant down-regulation of Terf2ip levels in the livers of NASH patients and mice NASH models. Terf2ip deficiency was associated with an exacerbation of hepatic steatosis in mice under HFD or MCD. Additionally, Terf2ip deficiency impaired lipophagy and fatty acid oxidation (FAO) in NASH models. Mechanically, we discovered that Terf2ip bound to the promoter region of Sirt1 to regulate Sirt1/AMPK pathway activation. As a result, Terf2ip deficiency was shown to inhibit lipophagy through the AMPK pathway, while the activation of Sirt1 alleviated steatohepatitis in the livers of mice. Finally, re-expression of Terf2ip in hepatocyes alleviated liver steatosis, inflammation, and restored lipophagy. CONCLUSIONS: These results revealed that Terf2ip played a protective role in the progression of NASH through regulating lipophagy and FAO by binding to Sirt1 promoter. Our findings provided a potential therapeutic target for the treatment of NASH.

Prediction of breast cancer and axillary positive-node response to neoadjuvant chemotherapy based on multi-parametric magnetic resonance imaging radiomics models.

PURPOSE: Accurate identification of primary breast cancer and axillary positive-node response to neoadjuvant chemotherapy (NAC) is important for determining appropriate surgery strategies. We aimed to develop combining models based on breast multi-parametric magnetic resonance imaging and clinicopathologic characteristics for predicting therapeutic response of primary tumor and axillary positive-node prior to treatment. MATERIALS AND METHODS: A total of 268 breast cancer patients who completed NAC and underwent surgery were enrolled. Radiomics features and clinicopathologic characteristics were analyzed through the analysis of variance and the least absolute shrinkage and selection operator algorithm. Finally, 24 and 28 optimal features were selected to construct machine learning models based on 6 algorithms for predicting each clinical outcome, respectively. The diagnostic performances of models were evaluated in the testing set by the area under the curve (AUC), sensitivity, specificity, and accuracy. RESULTS: Of the 268 patients, 94 (35.1 %) achieved breast cancer pathological complete response (bpCR) and of the 240 patients with clinical positive-node, 120 (50.0 %) achieved axillary lymph node pathological complete response (apCR). The multi-layer perception (MLP) algorithm yielded the best diagnostic performances in predicting apCR with an AUC of 0.825 (95 % CI, 0.764-0.886) and an accuracy of 77.1 %. And MLP also outperformed other models in predicting bpCR with an AUC of 0.852 (95 % CI, 0.798-0.906) and an accuracy of 81.3 %. CONCLUSIONS: Our study established non-invasive combining models to predict the therapeutic response of primary breast cancer and axillary positive-node prior to NAC, which may help to modify preoperative treatment and determine post-NAC surgery strategy.

Mobile iodides capture for highly photolysis- and reverse-bias-stable perovskite solar cells.

For halide perovskites that are susceptible to photolysis and ion migration, iodide-related defects, such as iodine (I2) and iodine vacancies, are inevitable. Even a small number of these defects can trigger self-accelerating chemical reactions, posing serious challenges to the durability of perovskite solar cells. Fortunately, before I2 can damage the perovskites under illumination, they generally diffuse over a long distance. Therefore, detrimental I2 can be captured by interfacial materials with strong iodide/polyiodide (Ix-) affinities, such as fullerenes and perfluorodecyl iodide. However, fullerenes in direct contact with perovskites fail to confine Ix- ions within the perovskite layer but cause detrimental iodine vacancies. Perfluorodecyl iodide, with its directional Ix- affinity through halogen bonding, can both capture and confine Ix-. Therefore, inverted perovskite solar cells with over 10 times improved ultraviolet irradiation and thermal-light stabilities (under 85 °C and 1 sun illumination), and 1,000 times improved reverse-bias stability (under ISOS-V ageing tests) have been developed.

One Stone Several Birds: Self-Localizing Submicrocages With Dual Loading Points for Multifunctional Drug Delivery.

As the core index, how to improve bioavailability of loaded cargoes is a hot topic of drug carriers. In this study, aminated ß-cyclodextrin (ß-CD) as a cross-linking points is first integrated into 3D poly(acrylamide-co-acrylonitrile) (P(AAm-co-AN)) network to build up a unique submicrocage (466.2 ± 47.6 nm), featuring upper critical solution temperature (UCST; ≈40 °C), high volume expansion coefficient, and excellent biocompatibility. Hereinto, hydrophobic ß-elemene (ELE) is locally loaded in ß-CD with high loading efficiency (8.72%) and encapsulation efficiency (78.60%) through hydrophobic desolvation and host-guest interaction. Above UCST, the release of the loaded ELE is accelerated to 72.87% in 24 h, together with the enhanced sensitization effect of synergized radiotherapy. Given spontaneous long-lasting delivery, targeted embolization, and post-treatment removal of such UCST-type submicrocage, it is anticipated to provide a novel, facile, efficient, and versatile strategy of comprehensive anticancer treatments for high drug bioavailability.

NUF2 regulated the progression of hepatocellular carcinoma through modulating the PI3K/AKT pathway via stabilizing ERBB3.

Hepatocellular carcinoma (HCC) is among the most prevalent and lethal cancers worldwide. The NDC80 kinetochore complex component NUF2 has been previously identified as up-regulating in HCC and associated with patient prognosis. However, the pathophysiological effects and molecular mechanisms of NUF2 in tumorigenesis remain unclear. In this study, we confirmed a significant increase in NUF2 expression in HCC tissues and established a correlation between high NUF2 expression and adverse outcomes in HCC patients. Through in vitro and in vivo experiments, we demonstrated that genetic inhibition of NUF2 suppressed the proliferation of HCC cells and disrupted the cell cycle. Further investigation into the molecular mechanisms revealed that NUF2 interacted with ERBB3, inhibiting its ubiquitination degradation, thus activating the PI3K/AKT signaling pathway and influencing cell cycle regulation. Overall, this study revealed the crucial role of NUF2 in promoting the malignant progression of HCC, suggesting its potential as both a prognostic biomarker and a therapeutic target for HCC.

Predicting One-year Recurrence of HCC based on Gadoxetic Acid-enhanced MRI by Machine Learning Models.

OBJECTIVE: Accurate prediction of recurrence risk after resction in patients with Hepatocellular Carcinoma (HCC) may help to individualize therapy strategies. This study aimed to develop machine learning models based on preoperative clinical factors and multiparameter Magnetic Resonance Imaging (MRI) characteristics to predict the 1-year recurrence after HCC resection. METHODS: Eighty-two patients with single HCC who underwent surgery were retrospectively analyzed. All patients underwent preoperative gadoxetic acidenhanced MRI examination. Preoperative clinical factors and MRI characteristics were collected for feature selection. Least Absolute Shrinkage and Selection Operator (LASSO) was applied to select the optimal features for predicting postoperative 1-year recurrence of HCC. Four machine learning algorithms, Multilayer Perception (MLP), random forest, support vector machine, and k-nearest neighbor, were used to construct the predictive models based on the selected features. A Receiver Operating Characteristic (ROC) curve was used to assess the performance of each model. RESULTS: Among the enrolled patients, 32 patients experienced recurrences within one year, while 50 did not. Tumor size, peritumoral hypointensity, decreasing ratio of liver parenchyma T1 value (ΔT1), and α-fetoprotein (AFP) levels were selected by using LASSO to develop the machine learning models. The area under the curve (AUC) of each model exceeded 0.72. Among the models, the MLP model showed the best performance with an AUC, accuracy, sensitivity, and specificity of 0.813, 0.742, 0.570, and 0.853, respectively. CONCLUSION: Machine learning models can accurately predict postoperative 1-year recurrence in patients with HCC, which may help to provide individualized treatment.

USP21 deubiquitinates and stabilizes HSP90 and ENO1 to promote aerobic glycolysis and proliferation in cholangiocarcinoma.

Deubiquitylating enzymes (DUBs) play an essential role in targeted protein degradation and represent an emerging therapeutic paradigm in cancer. However, their therapeutic potential in cholangiocarcinoma (CCA) has not been explored. Herein, based on The Cancer Genome Atlas (TCGA) and The Gene Expression Omnibus (GEO) databases, we found that ubiquitin-specific protease 21 (USP21) was upregulated in CCA, high USP21 level was associated with poor prognosis. In vivo and in vitro, we identified USP21 as a master regulator of CCA growth and maintenance, which directly interacted with deubiquitinates and stabilized the heat shock protein 90 (HSP90) through K48-linked deubiquitination, and in turn, this stabilization increased HIF1A expression, thus upregulating key glycolytic enzyme genes ENO2, ENO3, ALDOC, ACSS2, and then promoted aerobic glycolysis, which provided energy for CCA cell proliferation. In addition, USP21 could directly stabilize alpha-Enolase 1 (ENO1) to promote aerobic glycolysis. Furthermore, increased USP21 level enhanced chemotherapy resistance to the gemcitabine-based regimen. Taken together, we identify a USP21-regulated aerobic glycolysis mechanism that involves the USP21/HSP90/HIF1A axis and USP21/ENO1 axis in CCA tumorigenesis, which could serve as a potential target for the treatment of CCA.

PIN1 promotes the metastasis of cholangiocarcinoma cells by RACK1-mediated phosphorylation of ANXA2.

BACKGROUND: Cholangiocarcinoma (CCA), a primary hepatobiliary malignancy, is characterized by a poor prognosis and a lack of effective treatments. Therefore, the need to explore novel therapeutic approaches is urgent. While the role of Peptidylprolyl Cis/Trans Isomerase, NIMA-Interacting 1 (PIN1) has been extensively studied in various tumor types, its involvement in CCA remains poorly understood. METHODS: In this study, we employed tissue microarray (TMA), reverse transcription-polymerase chain reaction (RT-PCR), and The Cancer Genome Atlas (TCGA) database to assess the expression of PIN1. Through in vitro and in vivo functional experiments, we investigated the impact of PIN1 on the adhesion and metastasis of CCA. Additionally, we explored downstream molecular pathways using RNA-seq, western blotting, co-immunoprecipitation, immunofluorescence, and mass spectrometry techniques. RESULTS: Our findings revealed a negative correlation between PIN1 overexpression and prognosis in CCA tissues. Furthermore, high PIN1 expression promoted CCA cell proliferation and migration. Mechanistically, PIN1 functioned as an oncogene by regulating ANXA2 phosphorylation, thereby promoting CCA adhesion. Notably, the interaction between PIN1 and ANXA2 was facilitated by RACK1. Importantly, pharmacological inhibition of PIN1 using the FDA-approved drug all-trans retinoic acid (ATRA) effectively suppressed the metastatic potential of CCA cells in a nude mouse lung metastasis model. CONCLUSION: Overall, our study emphasizes the critical role of the PIN1/RACK1/ANXA2 complex in CCA growth and functionality, highlighting the potential of targeting PIN1 as a promising therapeutic strategy for CCA.

Hepatic Pecoma versus Hepatocellular Carcinoma In The Noncirrhotic Liver on Gd-EOB-DTPA-Enhanced MRI: A Diagnostic Challenge.

AIM: Hepatic perivascular epithelioid cell tumors (PEComa) often mimic hepatocellular carcinoma (HCC) in patients without cirrhosis. This study aimed to develop a nomogram using imaging characteristics on Gd-EOB-DTPA-enhanced MRI and to distinguish PEComa from HCC in a noncirrhotic liver. METHODS: Forty patients with non-cirrhotic Gd-EOB-DTPA-enhanced magnetic resonance imaging(MRI) were included in our study. A multivariate logistic regression model was used to select significant variables to distinguish PEComa from HCC. A nomogram was developed based on the regression model. The performance of the nomogram was assessed with respect to the ROC curve and calibration curve. Decision curve analysis (DCA) was performed to evaluate the clinical usefulness of the nomogram. RESULTS: Two significant predictors were identified: the appearance of an early draining vein and the T1D value of tumors. The ROC curve showed that the area under the curve (AUC) of the model to predict the risk of PEComa was 0.91 (95% CI: 0.80~1) and showed that the model had high specificity (92.3%) and sensitivity (88.9%). The nomogram incorporating these two predictors showed favorable calibration, which was validated using 1000 resampling procedures, and the corrected C-index of this model was 0.90. Furthermore, DCA analysis showed that the model had clinical practicability. CONCLUSION: In conclusion, the nomogram model showed favorable predictive accuracy for distinguishing PEComa from HCC in non-cirrhotic patients and may aid in clinical decision-making.

CircPCNXL2 promotes tumor growth and metastasis by interacting with STRAP to regulate ERK signaling in intrahepatic cholangiocarcinoma.

BACKGROUND: circular RNAs (circRNAs) have been reported to exert important effects in the progression of numerous cancers. However, the functions of circRNAs in intrahepatic cholangiocarcinoma (ICC) are still unclear. METHODS: circPCNXL2 (has_circ_0016956) were identified in paired ICC by circRNA microarray. Then, we assessed the biological functions of circPCNXL2 by CCK8, EdU, clone formation, transwell, wound healing assays, and xenograft models. RNA pull-down, mass spectrometry, and RNA immunoprecipitation (RIP) were applied to explore the interaction between cirrcPCNXL2 and serine-threonine kinase receptor-associated protein (STRAP). RNA pull-down, RIP and luciferase reporter assays were used to investigate the sponge functions of circPCNXL2. In the end, we explore the effects of circPCNXL2 and trametinib (a MEK1/2 inhibitor) in vivo. RESULTS: circPCNXL2 was upregulated in ICC tissues and cell lines, which promoted the proliferation and metastasis of ICC in vitro and in vivo. In terms of the mechanisms, circPCNXL2 could directly bind to STRAP and induce the interaction between STRAP and MEK1/2, resulting in the tumor promotion in ICC by activation of ERK/MAPK pathways. Besides, circPCNXL2 could regulate the expression of SRSF1 by sponging miR-766-3p and subsequently facilitated the growth of ICC. Finally, circPCNXL2 could partially inhibit the anti-tumor activity of trametinib in vivo. CONCLUSION: circPCNXL2 played a crucial role in the progression of ICC by interacting with STRAP to activate the ERK signaling pathway, as well as by modulating the miR-766-3p/SRSF1 axis. These findings suggest that circPCNXL2 may be a promising biomarker and therapeutic target for ICC.

Pseudo-targeted metabolic profile differences between emergency patients with type 1 and type 2 myocardial infarction diagnosed by optical coherence tomography.

BACKGROUND: It is difficult to distinguish type 2 myocardial infarction (T2MI) from type 1 myocardial infarction (T1MI), although their management varies. OBJECTIVES: Using optical coherence tomography (OCT) and pseudo-targeted metabolomics to identify biomarkers, investigate metabolic differences, and establish a T2MI subclassification. METHODS: Among 1519 patients with MI, 97 T2MI patients are identified who are 1:1 matched with 97 T1MI patients after considering age, gender, ST-segment elevation, time from onset to coronary angiography, and hs-cTnI on admission by propensity score matching. Plasma pseudo-targeted metabolomics at baseline was determined. RESULTS: The clinical characteristics of the two groups were comparable, while the T1MI showed more severe coronary lesions than T2MI according to OCT imaging. 90 differential metabolites were identified between the two groups, among 1027 endogenous metabolites in 20 classes. N-Acetyl-L-Leucine, free fatty acid (15:1), Thymidine-5'-triphosphate, Mevalonic acid 5-pyrophosphate, and five oligopeptides were candidate biomarkers (AUC ≥ 0.85) distinguishing T2MI from T1MI. 12 KEGG pathways showed significant differences, mainly involving amino acid, nucleotide, and their derivatives metabolism, and signaling pathways such as mTOR, cGMP-PKG, and cAMP. Other differences were observed in TCA cycle (P = 0.08) and ROS (P = 0.05). Proteolysis and coronary heart disease risk lipid level were lower in T2MI. T2MI had a decrease of differential abundance score in almost all the KEGG enrichment pathways. Furthermore, T2MI can be subdivided into three subtypes by hierarchical cluster analysis of AUCs with causes/triggers of T2MI. CONCLUSIONS: There are significant metabolic profile differences between T1MI and T2MI. Several candidate metabolic biomarkers can effectively distinguish the two groups. CLINICAL TRIAL REGISTRATION: ClinicalTrials. gov NCT03297164.

Exosome-derived miR-182-5p promoted cholangiocarcinoma progression and vasculogenesis by regulating ADK/SEMA5a/PI3K pathway.

BACKGROUND AND AIMS: Increasing evidence suggested that miRNAs regulated the expression of pivotal genes involved in oncogenesis and malignant phenotype. In this project, the purpose was to make an inquiry to the effect and mechanism of miR-182-5p in the progression of cholangiocarcinoma. METHODS: By analysing TCGA and GEO databases, combined with tissue expression levels, miR-182-5p was identified as one of the most valuable miRNAs for research. The function and relationships between miR-182-5p and downstream target genes were both verified by in vitro and in vivo experiments. Methylation-specific PCR and bisulphite sequencing were used to detect the methylation level changes of downstream gene promoter. RESULTS: We found that miR-182-5p could be taken up by exosomes secreted from cholangiocarcinoma. Moreover, exosomal derived miR-182-5p promoted vascular endothelial cell proliferation and migration and induced angiogenesis by targeting ADK/SEMA5a. Subsequently, the PI3K/AKT/mTOR signalling pathway was activated and ultimately caused resistance to gemcitabine and cisplatin. CONCLUSIONS: Our findings suggested that the miR-182-5p/ADK/SEMA5a axis might serve as a potential therapeutic target for cholangiocarcinoma.

Computed tomography imaging phenotypes of hepatoblastoma identified from radiomics signatures are associated with the efficacy of neoadjuvant chemotherapy.

BACKGROUND: Though neoadjuvant chemotherapy has been widely used in the treatment of hepatoblastoma, there still lacks an effective way to predict its effect. OBJECTIVE: To characterize hepatoblastoma based on radiomics image features and identify radiomics-based lesion phenotypes by unsupervised machine learning, intended to build a classifier to predict the response to neoadjuvant chemotherapy. MATERIALS AND METHODS: In this retrospective study, we segmented the arterial phase images of 137 cases of pediatric hepatoblastoma and extracted the radiomics features using PyRadiomics. Then unsupervised k-means clustering was applied to cluster the tumors, whose result was verified by t-distributed stochastic neighbor embedding (t-SNE). The least absolute shrinkage and selection operator (LASSO) regression was used for feature selection, and the clusters were visually analyzed by radiologists. The correlations between the clusters, clinical and pathological parameters, and qualitative radiological features were analyzed. RESULTS: Hepatoblastoma was clustered into three phenotypes (homogenous type, heterogenous type, and nodulated type) based on radiomics features. The clustering results had a high correlation with response to neoadjuvant chemotherapy (P=0.02). The epithelial ratio and cystic components in radiological features were also associated with the clusters (P=0.029 and 0.008, respectively). CONCLUSIONS: This radiomics-based cluster system may have the potential to facilitate the precise treatment of hepatoblastoma. In addition, this study further demonstrated the feasibility of using unsupervised machine learning in a disease without a proper imaging classification system.

Preoperative assessment of peripheral vascular invasion of pancreatic ductal adenocarcinoma based on high-resolution MRI.

OBJECTIVES: Preoperative imaging of vascular invasion is important for surgical resection of pancreatic ductal adenocarcinoma (PDAC). However, whether MRI and CT share the same evaluation criteria remains unclear. This study aimed to compare the diagnostic accuracy of high-resolution MRI (HR-MRI), conventional MRI (non-HR-MRI) and CT for PDAC vascular invasion. METHODS: Pathologically proven PDAC with preoperative HR-MRI (79 cases, 58 with CT) and non-HR-MRI (77 cases, 59 with CT) were retrospectively collected. Vascular invasion was confirmed surgically or pathologically. The degree of tumour-vascular contact, vessel narrowing and contour irregularity were reviewed respectively. Diagnostic criteria 1 (C1) was the presence of all three characteristics, and criteria 2 (C2) was the presence of any one of them. The diagnostic efficacies of different examination methods and criteria were evaluated and compared. RESULTS: HR-MRI showed satisfactory performance in assessing vascular invasion (AUC: 0.87-0.92), especially better sensitivity (0.79-0.86 vs. 0.40-0.79) than that with non-HR-MRI and CT. HR-MRI was superior to non-HR-MRI. C2 was superior to C1 on CT evaluation (0.85 vs. 0.79, P = 0.03). C1 was superior to C2 in the venous assessment using HR-MRI (0.90 vs. 0.87, P = 0.04) and in the arterial assessment using non-HR-MRI (0.69 vs. 0.68, P = 0.04). The combination of C1-assessed HR-MRI and C2-assessed CT was significantly better than that of CT alone (0.96 vs. 0.86, P = 0.04). CONCLUSIONS: HR-MRI more accurately assessed PDAC vascular invasion than conventional MRI and may contribute to operative decision-making. C1 was more applicable to MRI scans, and C2 to CT scans. The combination of C1-assessed HR-MRI and C2-assessed CT outperformed CT alone and showed the best efficacy in preoperative examination of PDAC.

Hypoxia-induced SKA3 promoted cholangiocarcinoma progression and chemoresistance by enhancing fatty acid synthesis via the regulation of PAR-dependent HIF-1a deubiquitylation.

BACKGROUND: Spindle and kinetochore-associated complex subunit 3 (SKA3) plays an important role in cell proliferation by regulating the separation of chromosomes and their division into daughter cells. Previous studies demonstrated that SKA3 was strongly implicated in tumor development and progression. However, the roles of SKA3 in cholangiocarcinoma (CCA) and the underlying mechanisms remain unclear. METHODS: Next-generation sequencing (NGS) was performed with paired CCA tissues and normal adjacent tissues (NATs). SKA3 was chose to be the target gene because of its remarkably upregulation and unknown function in cholangiocarcinoma in TCGA datasets, GSE107943 datasets and our sequencing results. RT-PCR and immunohistochemistry staining were used to detect the expression of SKA3 in paired CCA tissues and normal adjacent tissues. The SKA3 knockdown and overexpression cell line were constructed by small interfering RNA and lentivirus vector transfection. The effect of SKA3 on the proliferation of cholangiocarcinoma under hypoxic conditions was detected by experiments in vitro and in vivo. RNA-seq was used to find out the differentially expressed pathways in cholangiocarcinoma proliferation under hypoxia regulated by SKA3. IP/MS analysis and Western blot assays were used to explore the specific mechanism of SKA3 in regulating the expression of HIF-1a under hypoxia. RESULTS: SKA3 was up-regulated in NGS, TCGA and GSE107943 databases and was associated with poor prognosis. Functional experiments in vitro and in vivo showed that hypoxia-induced SKA3 promoted cholangiocarcinoma cell proliferation. RNA-sequencing was performed and verified that SKA3 enhanced fatty acid synthesis by up-regulating the expression of key fatty acid synthase, thus promoting cholangiocarcinoma cell proliferation under hypoxic conditions. Further studies indicated that under hypoxic conditions, SKA3 recruited PARP1 to bind to HIF-1a, thus enhancing the poly ADP-ribosylation (PARylation) of HIF-1a. This PARylation enhanced the binding between HIF-1a and USP7, which triggered the deubiquitylation of HIF-1a under hypoxic conditions. Additionally, PARP1 and HIF-1a were upregulated in CCA and promoted CCA cell proliferation. SKA3 promoted CCA cell proliferation and fatty acid synthesis via the PARP1/HIF-1a axis under hypoxic conditions. High SKA3 and HIF-1a expression levels were associated with poor prognosis after surgery. CONCLUSION: Hypoxia-induced SKA3 promoted CCA progression by enhancing fatty acid synthesis via the regulation of PARylation-dependent HIF-1a deubiquitylation. Furthermore, increased SKA3 level enhanced chemotherapy-resistance to gemcitabine-based regimen under hypoxic conditions. SKA3 and HIF-1a could be potential oncogenes and significant biomarkers for the analysis of CCA patient prognosis.

MAD2 activates IGF1R/PI3K/AKT pathway and promotes cholangiocarcinoma progression by interfering USP44/LIMA1 complex.

Spindle assembly checkpoint (SAC) plays an essential part in facilitating normal cell division. However, the clinicopathological and biological significance of mitotic arrest deficient 2 like 1 (MAD2/MAD2L1), a highly conserved member of SAC in cholangiocarcinoma (CCA) remain unclear. We aim to determine the role and mechanism of MAD2 in CCA progression. In the study, we found up-regulated MAD2 facilitated CCA progression and induced lymphatic metastasis dependent on USP44/LIMA1/PI3K/AKT pathway. MAD2 interfered the binding of USP44 to LIMA1 by sequestrating more USP44 in nuclei, causing impaired formation of USP44/LIMA1 complex and enhanced LIMA1 K48 (Lys48)-linked ubiquitination. In therapeutic perspective, the data combined eleven cases of CCA PDTX model showed that high-MAD2 inhibits tumor necrosis and diminishes the inhibition of cell viability after treated with gemcitabine-based regimens. Immunohistochemistry (IHC) analysis of tissue microarray (TMA) for CCA patients revealed that high-MAD2, low-USP44 or low-LIMA1 level are correlated with worse survival for patients. Together, MAD2 activates PI3K/AKT pathway, promotes cancer progression and induces gemcitabine chemo-resistance in CCA. These findings suggest that MAD2 might be an excellent indicator in prognosis analysis and chemotherapy guidance for CCA patients.

Clinical Interpretability of Deep Learning for Predicting Microvascular Invasion in Hepatocellular Carcinoma by Using Attention Mechanism.

Preoperative prediction of microvascular invasion (MVI) is essential for management decision in hepatocellular carcinoma (HCC). Deep learning-based prediction models of MVI are numerous but lack clinical interpretation due to their "black-box" nature. Consequently, we aimed to use an attention-guided feature fusion network, including intra- and inter-attention modules, to solve this problem. This retrospective study recruited 210 HCC patients who underwent gadoxetate-enhanced MRI examination before surgery. The MRIs on pre-contrast, arterial, portal, and hepatobiliary phases (hepatobiliary phase: HBP) were used to develop single-phase and multi-phase models. Attention weights provided by attention modules were used to obtain visual explanations of predictive decisions. The four-phase fusion model achieved the highest area under the curve (AUC) of 0.92 (95% CI: 0.84-1.00), and the other models proposed AUCs of 0.75-0.91. Attention heatmaps of collaborative-attention layers revealed that tumor margins in all phases and peritumoral areas in the arterial phase and HBP were salient regions for MVI prediction. Heatmaps of weights in fully connected layers showed that the HBP contributed the most to MVI prediction. Our study firstly implemented self-attention and collaborative-attention to reveal the relationship between deep features and MVI, improving the clinical interpretation of prediction models. The clinical interpretability offers radiologists and clinicians more confidence to apply deep learning models in clinical practice, helping HCC patients formulate personalized therapies.

NUF2 Drives Cholangiocarcinoma Progression and Migration via Inhibiting Autophagic Degradation of TFR1.

Cholangiocarcinoma (CCA) is the second most common primary hepatic malignancy and associated with poor prognosis. Lack of therapeutic methods for CCA and insensitivity of targeted therapy and immunotherapy make its treatment challenging. NUF2, a component of Ndc80 kinetochore complex, is implicated in the initiation and development of multiple cancers. However, the role and mechanism of NUF2 in CCA is still unclear. In this research, we investigated the biological processes and underlying mechanisms of NUF2 in CCA. We discovered that the expression of NUF2 was upregulated in CCA and negatively correlated with prognosis. Changes in NUF2 levels had an impact on cell proliferation and migration. Moreover, NUF2 functioned as an oncogene to promote the progression of CCA through p38/MAPK signaling by inhibiting p62 binding of TFR1 and affecting its autophagic degradation. In addition, TFR1 promoted CCA progression and Kaplan-Meier analyses uncovered patients with high expression of TFR1 was associated with the poor survival. In conclusion, our study demonstrated that NUF2 promoted CCA progression by regulating TFR1 protein degradation, and the NUF2/TFR1/MAPK axis could be an excellent therapeutic target for CCA.