Tumor cell-intrinsic MELK enhanced CCL2-dependent immunosuppression to exacerbate hepatocarcinogenesis and confer resistance of HCC to radiotherapy.

BACKGROUND: The outcome of hepatocellular carcinoma (HCC) is limited by its complex molecular characteristics and changeable tumor microenvironment (TME). Here we focused on elucidating the functional consequences of Maternal embryonic leucine zipper kinase (MELK) in the tumorigenesis, progression and metastasis of HCC, and exploring the effect of MELK on immune cell regulation in the TME, meanwhile clarifying the corresponding signaling networks. METHODS: Bioinformatic analysis was used to validate the prognostic value of MELK for HCC. Murine xenograft assays and HCC lung metastasis mouse model confirmed the role of MELK in tumorigenesis and metastasis in HCC. Luciferase assays, RNA sequencing, immunopurification-mass spectrometry (IP-MS) and coimmunoprecipitation (CoIP) were applied to explore the upstream regulators, downstream essential molecules and corresponding mechanisms of MELK in HCC. RESULTS: We confirmed MELK to be a reliable prognostic factor of HCC and identified MELK as an effective candidate in facilitating the tumorigenesis, progression, and metastasis of HCC; the effects of MELK depended on the targeted regulation of the upstream factor miR-505-3p and interaction with STAT3, which induced STAT3 phosphorylation and increased the expression of its target gene CCL2 in HCC. In addition, we confirmed that tumor cell-intrinsic MELK inhibition is beneficial in stimulating M1 macrophage polarization, hindering M2 macrophage polarization and inducing CD8 + T-cell recruitment, which are dependent on the alteration of CCL2 expression. Importantly, MELK inhibition amplified RT-related immune effects, thereby synergizing with RT to exert substantial antitumor effects. OTS167, an inhibitor of MELK, was also proven to effectively impair the growth and progression of HCC and exert a superior antitumor effect in combination with radiotherapy (RT). CONCLUSIONS: Altogether, our findings highlight the functional role of MELK as a promising target in molecular therapy and in the combination of RT therapy to improve antitumor effect for HCC.

Development and Validation of a Dual-Energy CT-Based Model for Predicting the Number of Central Lymph Node Metastases in Clinically Node-Negative Papillary Thyroid Carcinoma.

RATIONALE AND OBJECTIVES: This study aimed to develop and validate a dual-energy CT (DECT)-based model for preoperative prediction of the number of central lymph node metastases (CLNMs) in clinically node-negative (cN0) papillary thyroid carcinoma (PTC) patients. MATERIALS AND METHODS: Between January 2016 and January 2021, 490 patients who underwent lobectomy or thyroidectomy, CLN dissection, and preoperative DECT examinations were enrolled and randomly allocated into the training (N = 345) and validation cohorts (N = 145). The patients' clinical characteristics and quantitative DECT parameters obtained on primary tumors were collected. Independent predictors of> 5 CLNMs were identified and integrated to construct a DECT-based prediction model, for which the area under the curve (AUC), calibration, and clinical usefulness were assessed. Risk group stratification was performed to distinguish patients with different recurrence risks. RESULTS: More than 5 CLNMs were found in 75 (15.3%) cN0 PTC patients. Age, tumor size, normalized iodine concentration (NIC), normalized effective atomic number (nZeff) and the slope of the spectral Hounsfield unit curve (λHu) in the arterial phase were independently associated with> 5 CLNMs. The DECT-based nomogram that incorporated predictors demonstrated favorable performance in both cohorts (AUC: 0.842 and 0.848) and significantly outperformed the clinical model (AUC: 0.688 and 0.694). The nomogram showed good calibration and added clinical benefit for predicting> 5 CLNMs. The KaplanMeier curves for recurrence-free survival showed that the high- and low-risk groups stratified by the nomogram were significantly different. CONCLUSION: The nomogram based on DECT parameters and clinical factors could facilitate preoperative prediction of the number of CLNMs in cN0 PTC patients.

TACE responser NDRG1 acts as a guardian against ferroptosis to drive tumorgenesis and metastasis in HCC.

BACKGROUND: The treatment efficacy of transarterial chemoembolization (TACE) for hepatocellular carcinoma (HCC) varies widely between individuals. The aim of this study was to identify subtype landscapes and responser related to TACE, and further clarify the regulatory effect and corresponding mechanism of NDRG1 on HCC tumorgenesis and metastasis. METHODS: The principal component analysis (PCA) algorithm was used to construct a TACE response scoring (TRscore) system. The random forest algorithm was applied to identify the TACE response-related core gene NDRG1 of HCC, and its role in the prognosis of HCC was explored. The role of NDRG1 in the progression and metastasis of HCC and functional mechanism were confirmed using several experimental methods. RESULTS: Based on the GSE14520 and GSE104580 cohorts, we identified 2 TACE response-related molecular subtypes for HCC with significant differences in clinical features, and the TACE prognosis of Cluster A was significantly better than that of Cluster B (p < 0.0001). We then established the TRscore system and found that the low TRscore group showed a higher probability of survival and a lower rate of recurrence than the high TRscore group (p < 0.05) in both the HCC and TACE-treated HCC cohorts within the GSE14520 cohort. NDRG1 was determined to be the the hub gene associated with the TACE response of HCC and its high expression suggested a poor prognosis. Furthermore, The suppression of NDRG1 konckdown in tumorgenesis and metastasis of HCC was clarified in both vivo and vitro, which was importantly achieved through inducing ferroptosis in HCC cells, especially contributing to RLS3-induced ferroptosis. CONCLUSION: The constructed TACE response-related molecular subtypes and TRscores can specifically and accurately predict TACE prognosis for HCC. In addition, the TACE response-related hub gene NDRG1 may act as a guardian against ferroptosis to drive tumorgenesis and metastasis in HCC, which laid a new foundation for the development of new potential targeted therapy strategies to improve disease prognosis in HCC patients.

Precise prediction of the sensitivity of platinum chemotherapy in SCLC: Establishing and verifying the feasibility of a CT-based radiomics nomogram.

Objectives: To develop and validate a CT-based radiomics nomogram that can provide individualized pretreatment prediction of the response to platinum treatment in small cell lung cancer (SCLC). Materials: A total of 134 SCLC patients who were treated with platinum as a first-line therapy were eligible for this study, including 51 patients with platinum resistance (PR) and 83 patients with platinum sensitivity (PS). The variance threshold, SelectKBest, and least absolute shrinkage and selection operator (LASSO) were applied for feature selection and model construction. The selected texture features were calculated to obtain the radiomics score (Rad-score), and the predictive nomogram model was composed of the Rad-score and the clinical features selected by multivariate analysis. Receiver operating characteristic (ROC) curves, calibration curves, and decision curves were used to assess the performance of the nomogram. Results: The Rad-score was calculated using 10 radiomic features, and the resulting radiomics signature demonstrated good discrimination in both the training set (area under the curve [AUC], 0.727; 95% confidence interval [CI], 0.627-0.809) and the validation set (AUC, 0.723; 95% CI, 0.562-0.799). To improve diagnostic effectiveness, the Rad-score created a novel prediction nomogram by combining CA125 and CA72-4. The radiomics nomogram showed good calibration and discrimination in the training set (AUC, 0.900; 95% CI, 0.844-0.947) and the validation set (AUC, 0.838; 95% CI, 0.534-0.735). The radiomics nomogram proved to be clinically beneficial based on decision curve analysis. Conclusion: We developed and validated a radiomics nomogram model for predicting the response to platinum in SCLC patients. The outcomes of this model can provide useful suggestions for the development of tailored and customized second-line chemotherapy regimens.

Proteomic analysis of DZIP3 interactome and its role in proliferation and metastasis in gastric cancer cells.

Gastric cancer is a serious malignant tumor in the world, accounting for the third cause of cancer death worldwide. The pathogenesis of gastric cancer is very complex, in which epigenetic inheritance plays an important role. In our study, we found that DZIP3 was significantly up-regulated in gastric cancer tissues as compared to adjacent normal tissue, which suggested it may be play a crucial part in gastric cancer. To clarify the mechanism of it, we further analyzed the interacting proteome and transcriptome of DZIP3. An association between DZIP3 and some epigenetic regulators, such as CUL4B complex, was verified. We also present the first proteomic characterization of the protein-protein interaction (PPI) network of DZIP3. Then, the transcriptome analysis of DZIP3 demonstrated that knockdown DZIP3 increased a cohort of genes, including SETD7 and ZBTB4, which have essential role in tumors. We also revealed that DZIP3 promotes proliferation and metastasis of gastric cancer cells. And the higher expression of DZIP3 is positively associated with the poor prognosis of several cancers. In summary, our study revealed a mechanistic role of DZIP3 in promoting proliferation and metastasis in gastric cancer, supporting the pursuit of DZIP3 as a potential target for gastric cancer therapy.

MLL4 Regulates the Progression of Non-Small-Cell Lung Cancer by Regulating the PI3K/AKT/SOX2 Axis.

PURPOSE: Mixed-lineage leukemia protein 4 (MLL4/KMT2D) is a histone methyltransferase, and its mutation has been reported to be associated with a poor prognosis in many cancers, including lung cancer. We investigated the function of MLL4 in lung carcinogenesis. Materials and Methods: RNA sequencing (RNA-seq) in A549 cells transfected with control siRNA or MLL4 siRNA was performed. Also, we used EdU incorporation assay, colony formation assays, growth curve analysis, transwell invasion assays, immunohistochemical staining, and in vivo bioluminescence assay to investigate the function of MLL4 in lung carcinogenesis. RESULTS: We found that MLL4 expression was downregulated in non-small cell lung cancer (NSCLC) tissues compared to adjacent normal tissues and tended to decrease with disease stage progression. We analyzed the transcriptomes in control and MLL4- deficient cells using high-throughput RNA deep sequencing (RNA-seq) and identified a cohort of target genes, such as SOX2, ATF1, FOXP4, PIK3IP1, SIRT4, TENT5B, and LFNG, some of which are related to proliferation and metastasis. Our results showed that low expression of MLL4 promotes NSCLC cell proliferation and metastasis and is required for the maintenance of NSCLC stem cell properties. CONCLUSION: Our findings identify an important role of MLL4 in lung carcinogenesis through transcriptional regulation of PIK3IP1, affecting the PI3K/AKT/SOX2 axis, and suggest that MLL4 could be a potential prognostic indicator and target for NSCLC therapy.

Macrophage xCT deficiency drives immune activation and boosts responses to immune checkpoint blockade in lung cancer.

Tumor-associated macrophages (TAMs) play an important role in remodeling the tumor microenvironment (TME), which promotes tumor growth, immunosuppression and angiogenesis. Because of the high plasticity of macrophages and the extremely complex tumor microenvironment, the mechanism of TAMs in cancer progression is still largely unknown. In this study, we found that xCT (SLC7A11) was overexpressed in lung cancer-associated macrophages. Higher xCT in TAMs was associated with poor prognosis and was an independent predictive factor in lung cancer. In addition, lung cancer growth and progression was inhibited in xCT knockout mice, especially macrophage-specific xCT knockout mice. We also found that the deletion of macrophage xCT inhibited AKT/STAT6 signaling activation and reduced M2-type polarization of TAMs. Macrophage xCT deletion recruited more CD8+ T cells and activated the lung cancer cell-mediated and IFN-γ-induced JAK/STAT1 axis and increased the expression of its target genes, including CXCL10 and CD274. The combination of macrophage xCT deletion and anti-PDL1 antibody achieved better tumor inhibition. Finally, combining the xCT inhibitor erastin with an anti-PDL1 antibody was more potent in inhibiting lung cancer progression. Therefore, suppression of xCT may overcome resistance to cancer immunotherapy.

Targeted xCT-mediated Ferroptosis and Protumoral Polarization of Macrophages Is Effective against HCC and Enhances the Efficacy of the Anti-PD-1/L1 Response.

Tumor-associated macrophages (TAMs) play an essential role in tumor progression, metastasis, and antitumor immunity. Ferroptosis has attracted extensive attention for its lethal effect on tumor cells, but the role of ferroptosis in TAMs and its impact on tumor progression have not been clearly defined. Using transgenic mouse models, this study determines that xCT-specific knockout in macrophages is sufficient to limit tumorigenicity and metastasis in the mouse HCC models, achieved by reducing TAM recruitment and infiltration, inhibiting M2-type polarization, and activating and enhancing ferroptosis activity within TAMs. The SOCS3-STAT6-PPAR-γ signaling may be a crucial pathway in macrophage phenotypic shifting, and activation of intracellular ferroptosis is associated with GPX4/RRM2 signaling regulation. Furthermore, that xCT-mediated macrophage ferroptosis significantly increases PD-L1 expression in macrophages and improves the antitumor efficacy of anti-PD-L1 therapy is unveiled. The constructed Man@pSiNPs-erastin specifically targets macrophage ferroptosis and protumoral polarization and combining this treatment with anti-PD-L1 exerts substantial antitumor efficacy. xCT expression in tumor tissues, especially in CD68+ macrophages, can serve as a reliable factor to predict the prognosis of HCC patients. These findings provide further insight into targeting ferroptosis activation in TAMs and regulating TAM infiltration and functional expression to achieve precise tumor prevention and improve therapeutic efficacy.

SMYD3 associates with the NuRD (MTA1/2) complex to regulate transcription and promote proliferation and invasiveness in hepatocellular carcinoma cells.

BACKGROUND: SMYD3, a member of the SET and MYND domain-containing (SMYD) family, is a histone methyltransferase (HMT) and transcription factor that plays an important role in transcriptional regulation in human carcinogenesis. RESULTS: Using affinity purification and mass spectrometry assays to identify SMYD3-associated proteins in hepatocellular carcinoma (HCC) cells, we found several previously undiscovered SMYD3-interacting proteins, including the NuRD (MTA1/2) complex, the METTL family, and the CRL4B complex. Transcriptomic analysis of the consequences of knocking down SMYD3, MTA1, or MTA2 in HCC cells showed that SMYD3/NuRD complex targets a cohort of genes, some of which are critically involved in cell growth and migration. qChIP analyses showed that SMYD3 knockdown led to a significant reduction in the binding of MTA1 or MTA2 to the promoters of IGFBP4 and led to a significant decrease in H4K20me3 and a marked increase in H4Ac at the IGFBP4 promoter. In addition, we demonstrated that SMYD3 promotes cell proliferation, invasion, and tumorigenesis in vivo and in vitro and found that its expression is markedly upregulated in human liver cancer. Knockdown of MTA1 or MTA2 had the same effect as knockdown of SMYD3 on proliferation and invasion of hepatocellular carcinoma cells. Catalytic mutant SMYD3 could not rescue the phenotypic effects caused by knockdown of SMYD3. Inhibitors of SMYD3 effectively inhibited the proliferation and invasiveness of HCC cells. CONCLUSIONS: These findings revealed that SMYD3 could transcriptionally repress a cohort of target genes expression by associating with the NuRD (MTA1/2) complex, thereby promoting the proliferation and invasiveness of HCC cells. Our results support the case for pursuing SMYD3 as a practical prognostic marker or therapeutic target against HCC.

Intraplacental T2-hypointense bands may help predict placental invasion depth and postpartum hemorrhage in placenta accrete spectrum disorders in high-risk gravid patients.

INTRODUCTION: Accurate noninvasive prenatal diagnosis of placenta accreta spectrum (PAS) disorder is critical for delivery management. PURPOSE: To evaluate the diagnostic ability of MRI features in predicting the PAS, invasive depth and postpartum hemorrhage (PPH) in high-risk gravid patients. MATERIALS AND METHODS: Between February 2019 and November 2020, women with ultrasound (US)-suspected PAS were enrolled. With the exclusion criteria, 80 women were included in the study. Two experienced genitourinary radiologists reviewed and recorded the MRI features. The chi square test was used to compare the effectiveness of MRI features. Relative risk ratios were computed to test the association of intraplacental T2-hypointense bands with poor outcomes of cesarean section. Receiver operating characteristic (ROC) analyses based on the number and area of intraplacental T2-hypointense bands were used to predict PAS, invasion depth, and PPH. RESULTS: PAS was diagnosed in 56 of 80 women (70%). At delivery, 24 of 80 women (30%) experienced PPH (≥1000 mL). Intraplacental T2-hypointense bands were detected at MRI in 28 of 56 women with PAS (50%). The relative risk ratio of intraplacental T2-hypointense bands was 1.51 for PAS, 3.17 for depth of PAS invasiveness and 4.74 for PPH. The largest areas of intraplacental T2-hypointense bands for predicting PAS, invasion depth and PPH were 0.66 cm2, 1.68 cm2 and 1.99 cm2, respectively. DISCUSSION: The appearance of intraplacental T2-hypointense bands has important diagnostic value for PAS, its invasion depth and PPH. The area of the largest T2-hypointense band in the placenta can predict poor outcomes of cesarean section.

Corrigendum: Piperlongumine, a Novel TrxR1 Inhibitor, Induces Apoptosis in Hepatocellular Carcinoma Cells by ROS-Mediated ER Stress.

[This corrects the article DOI: 10.3389/fphar.2019.01180.].

Piperlongumine synergistically enhances the antitumour activity of sorafenib by mediating ROS-AMPK activation and targeting CPSF7 in liver cancer.

Sorafenib, a multikinase inhibitor, is the first-line agent for advanced liver cancer. Sorafenib strongly inhibits both cell proliferation and tumour angiogenesis. However, the development of drug resistance hampers its anticancer efficacy. To improve the antitumour activity of sorafenib, we demonstrate that piperlongumine (PL), an alkaloid isolated from the fruits and roots of Piper longum L., enhances the cytotoxicity of sorafenib in HCCLM3 and SMMC7721 cells using the cell counting kit-8 test. Flow cytometry analysis indicated that PL and sorafenib cotreatment induced robust reactive oxygen species (ROS) generation and mitochondrial dysfunction, thereby increasing the number of apoptotic cells and the ratio of G2/M phase cells in both HCCLM3 and SMMC7721 cells. Furthermore, AMP-protein kinase (AMPK) signalling was activated by excess ROS accumulation and mediated growth inhibition in response to PL and sorafenib cotreatment. RNA-sequencing analysis indicated that PL treatment disrupted RNA processing in HCCLM3 cells. In particular, PL treatment decreased the expression of cleavage and polyadenylation specificity factor 7 (CPSF7), a subunit of cleavage factor I, in a time- and concentration-dependent manner in HCCLM3 and SMMC7721 cells. CPSF7 knockdown using a gene interference strategy promoted growth inhibition of PL or sorafenib monotherapy, whereas CPSF7 overexpression alleviated the cytotoxicity of sorafenib in cultured liver cancer cells. Finally, PL and sorafenib coadministration significantly reduced the weight and volume of HCCLM3 cell xenografts in vivo. Taken together, our data indicate that PL displays potential synergistic antitumour activity in combination with sorafenib in liver cancer.

A role for the NPM1/PTPN14/YAP axis in mediating hypoxia-induced chemoresistance to sorafenib in hepatocellular carcinoma.

BACKGROUND: Tumor microenvironments are characterized by resistance to chemotherapeutic agents and radiotherapy. Hypoxia plays an important role in the development of tumor resistance, as well as the generation of metastatic potential. YAP also participates in the regulation of hypoxia-mediated chemoresistance, and is negatively regulated by protein tyrosine phosphatase non-receptor type 14 (PTPN14). METHODS: The PTPN14 expression in hepatocellular carcinoma (HCC) tissues were evaluated by qRT-PCR, western blot and tissue microarrays. The effect of PTPN14 on HCC progression was investigated in vitro and in vivo. RESULTS: Here, we report that PTPN14 expression was downregulated in HCC tissues and cell lines. Silencing PTPN14 significantly enhanced proliferation, migration, invasion of HepG2 cells in vitro and tumor growth and metastasis in vivo, whereas overexpression of PTPN14 significantly inhibited these abilities in SK-Hep1 cells. We also found that hypoxia-induced nuclear translocation and accumulation of PTPN14 led to resistance to sorafenib in HCC cells. Further mechanistic studies suggested that NPM1 regulates PTPN14 localization, and that NPM1 regulates YAP by retaining PTPN14 in the nucleus under hypoxic conditions. CONCLUSIONS: These data suggest that a therapeutic strategy against chemoresistant HCC may involve disruption of NPM1-mediated regulation of YAP by retaining PTPN14 in the nucleus under hypoxic conditions.

Identification of critical ferroptosis regulators in lung adenocarcinoma that RRM2 facilitates tumor immune infiltration by inhibiting ferroptotic death.

Ferroptosis is a novel form of cell death characterized by heavy iron accumulation and lipid peroxidation that plays a critical role in the tumor microenvironment. However, promising biomarkers associated with tumor immune cell infiltration and the immunotherapy response to ferroptosis regulators remain to be elucidated in lung adenocarcinoma (LUAD) patients. In this study, we defined ferroptosis regulators in LUAD through database analysis and experimental validation to determine the implementation of genes associated with clinical relevance, immunotherapy response and tumor microenvironment in LUAD patients. Multiomics data analysis was performed to explore the CNV features, molecular mechanisms and immunogenic characteristics of ferroptosis regulators in LUAD patients. Then, univariate and multivariate Cox regression analyses were used to identify three genes (DDIT4, RRM2, and SLC2A1) that were closely associated with the prognosis of LUAD patients. The prognostic model based on the determination of these three genes was an independent prognostic factor (p < 0.05, HR = 2.838), and patients with superior predictive performance and higher prognostic risk were more likely to have poor survival rates than those with lower prognostic risk in the training group (p < 0.001, HR = 3.19) and the test group (p < 0.001, HR = 2.94; p < 0.001, HR = 3.44). Activated immune cells, including T helper cells and activated CD8 T cells, were lower in the high-risk group, while type 2 T cells were higher (p < 0.05). Patients with higher prognostic risk were less likely to benefit from immunotherapy, partly due to low CTLA4 levels and an immunosuppressive microenvironment (p < 0.05). Combined with LUAD tissue samples and mouse trials, RRM2 was found to influence lung cancer progression and affect tumor immune cell infiltration. RRM2 inhibition effectively promoted M1 macrophage polarization and suppressed M2 macrophage polarization in vitro and in vivo. And ferroptosis inhibitor ferrostatin-1 treatment effectively re-blanced macrophage polarization mediated by RRM2 inhibition. Taken together, the results of the multiomics data analysis and experimental validation identified ferroptosis regulators as promising biomarkers and therapeutic targets associated with tumor immune infiltration in LUAD patients.

Construction of a novel radiomics nomogram for the prediction of aggressive intrasegmental recurrence of HCC after radiofrequency ablation.

OBJECTIVES: To construct a precise prediction model of preoperative magnetic resonance imaging (MRI)-based nomogram for aggressive intrasegmental recurrence (AIR) of hepatocellular carcinoma (HCC) patients treated with radiofrequency ablation (RFA). METHODS: Among 891 patients with HCC treated by RFA, 22 patients with AIR and 36 patients without AIR (non-AIR) were finally enrolled in our study, and each patient was followed up for more than 6 months to determine the occurrence of AIR. The laboratory indicators and MRI features were compared and assessed. Preoperative contrast-enhanced T1-weighted images (CE-T1WI) were used for radiomics analysis. The selected clinical indicators and texture features were finally screened out to generate the novel prediction nomogram. RESULTS: Tumor shape, ADC Value, DWI signal intensity and ΔSI were selected as the independent factors of AIR by univariate and multivariate logistic regression analysis. Meanwhile, two radiomics features were selected from 396 candidate features by LASSO (P < 0.05), which were further used to calculate the Rad-score. The selected clinical factors were further integrated with the Rad-score to construct the predictive model, and the AUCs were 0.941 (95% CI: 0.876-1.000) and 0.818 (95% CI: 0.576-1.000) in the training (15 AIR and 25 non-AIR) and validation cohorts (7 AIR and 11 non-AIR), respectively. The AIR predictive model was further converted into a novel radiomics nomogram, and decision curve analysis showed good agreement. CONCLUSIONS: The predictive nomogram integrated with clinical factors and CE-T1WI -based radiomics signature could accurately predict the occurrence of AIR after RFA, which could greatly help individualized evaluation before treatment.

Predictive Models for HCC Prognosis, Recurrence Risk, and Immune Infiltration Based on Two Exosomal Genes: MYL6B and THOC2.

INTRODUCTION: Hepatocellular carcinoma (HCC) is a heterogeneous molecular disease with complex molecular pathogenesis that influences the efficacy of therapies. Exosomes play a crucial role in tumorigenesis and poor disease outcomes in HCC. OBJECTIVE: The aim of this study was to identify the optimal gene set derived from exosomes in HCC with substantial predictive value to construct models for determining prognosis, recurrence risk and diagnosis and to identify candidates suitable for immunotherapy and chemotherapy, thereby providing new ideas for the individualized treatment of patients and for improving prognosis. METHODS: Weighted correlation network analysis (WGCNA) and univariate and multivariate Cox PH regression analyses were applied to identify exosome-related signatures in the TCGA and exoRbase databases associated with clinical relevance, immunogenic features and tumor progression in HCC. Cell experiments were performed to further confirm the oncogenic effect of MYL6B and THOC2. RESULTS: The models for prognosis and recurrence risk prediction were built based on two exosomal genes (MYL6B and THOC2) and were confirmed to be independent predictive factors with superior predictive performance. Patients with high prognostic risk had poorer prognosis than patients with low prognostic risk in all HCC datasets, namely, the TCGA cohort (HR=2.5, P<0.001), the ICGC cohort (HR=3.15, P<0.001) and the GSE14520 cohort (HR=1.85, P=0.004). A higher recurrence probability was found in HCC patients with high recurrence risk than in HCC patients with low recurrence risk in the TCGA cohort (HR=2.44, P<0.001) and the GSE14520 cohort (HR=1.54, P=0.025). High prognostic risk patients had higher expression of immune checkpoint genes, such as PD1, B7H3, B7H5, CTLA4 and TIM3 (P<0.05). Diagnostic models based on the same two genes were able to accurately distinguish HCC patients from normal individuals and HCC from dysplastic nodules. CONCLUSION: Our findings lay the foundation for identifying molecular markers to increase the early detection rate of HCC, improve disease outcomes, and determine more effective individualized treatment options for patients.

A Radiomics Signature-Based Nomogram to Predict the Progression-Free Survival of Patients With Hepatocellular Carcinoma After Transcatheter Arterial Chemoembolization Plus Radiofrequency Ablation.

Objective: The study aims to establish an magnetic resonance imaging radiomics signature-based nomogram for predicting the progression-free survival of intermediate and advanced hepatocellular carcinoma (HCC) patients treated with transcatheter arterial chemoembolization (TACE) plus radiofrequency ablation Materials and Methods: A total of 113 intermediate and advanced HCC patients treated with TACE and RFA were eligible for this study. Patients were classified into a training cohort (n = 78 cases) and a validation cohort (n = 35 cases). Radiomics features were extracted from contrast-enhanced T1W images by analysis kit software. Dimension reduction was conducted to select optimal features using the least absolute shrinkage and selection operator (LASSO). A rad-score was calculated and used to classify the patients into high-risk and low-risk groups and further integrated into multivariate Cox analysis. Two prediction models based on radiomics signature combined with or without clinical factors and a clinical model based on clinical factors were developed. A nomogram comcined radiomics signature and clinical factors were established and the concordance index (C-index) was used for measuring discrimination ability of the model, calibration curve was used for measuring calibration ability, and decision curve and clinical impact curve are used for measuring clinical utility. Results: Eight radiomics features were selected by LASSO, and the cut-off of the Rad-score was 1.62. The C-index of the radiomics signature for PFS was 0.646 (95%: 0.582-0.71) in the training cohort and 0.669 (95% CI:0.572-0.766) in validation cohort. The median PFS of the low-risk group [30.4 (95% CI: 19.41-41.38)] months was higher than that of the high-risk group [8.1 (95% CI: 4.41-11.79)] months in the training cohort (log rank test, z = 16.58, p < 0.001) and was verified in the validation cohort. Multivariate Cox analysis showed that BCLC stage [hazard ratio (HR): 2.52, 95% CI: 1.42-4.47, p = 0.002], AFP level (HR: 2.01, 95% CI: 1.01-3.99 p = 0.046), time interval (HR: 0.48, 95% CI: 0.26-0.87, p = 0.016) and radiomics signature (HR 2.98, 95% CI: 1.60-5.51, p = 0.001) were independent prognostic factors of PFS in the training cohort. The C-index of the combined model in the training cohort was higher than that of clinical model for PFS prediction [0.722 (95% CI: 0.657-0.786) vs. 0.669 (95% CI: 0.657-0.786), p＜0.001]. Similarly, The C-index of the combined model in the validation cohort, was higher than that of clinical model [0.821 (95% CI: 0.726-0.915) vs. 0.76 (95% CI: 0.667-0.851), p = 0.004]. The calibration curve, decision curve and clinical impact curve showed that the nomogram can be used to accurately predict the PFS of patients. Conclusion: The radiomics signature was a prognostic risk factor, and a nomogram combined radiomics and clinical factors acts as a new strategy for predicted the PFS of intermediate and advanced HCC treated with TACE plus RFA.

Radiomic Feature-Based Nomogram: A Novel Technique to Predict EGFR-Activating Mutations for EGFR Tyrosin Kinase Inhibitor Therapy.

OBJECTIVES: To develop and validate a radiomic feature-based nomogram for preoperative discriminating the epidermal growth factor receptor (EGFR) activating mutation from wild-type EGFR in non-small cell lung cancer (NSCLC) patients. MATERIAL: A group of 301 NSCLC patients were retrospectively reviewed. The EGFR mutation status was determined by ARMS PCR analysis. All patients underwent nonenhanced CT before surgery. Radiomic features were extracted (GE healthcare). The maximum relevance minimum redundancy (mRMR) and LASSO, were used to select features. We incorporated the independent clinical features into the radiomic feature model and formed a joint model (i.e., the radiomic feature-based nomogram). The performance of the joint model was compared with that of the other two models. RESULTS: In total, 396 radiomic features were extracted. A radiomic signature model comprising 9 selected features was established for discriminating patients with EGFR-activating mutations from wild-type EGFR. The radiomic score (Radscore) in the two groups was significantly different between patients with wild-type EGFR and EGFR-activating mutations (training cohort: P<0.0001; validation cohort: P=0.0061). Five clinical features were retained and contributed as the clinical feature model. Compared to the radiomic feature model alone, the nomogram incorporating the clinical features and Radscore exhibited improved sensitivity and discrimination for predicting EGFR-activating mutations (sensitivity: training cohort: 0.84, validation cohort: 0.76; AUC: training cohort: 0.81, validation cohort: 0.75). Decision curve analysis demonstrated that the nomogram was clinically useful and surpassed traditional clinical and radiomic features. CONCLUSIONS: The joint model showed favorable performance in the individualized, noninvasive prediction of EGFR-activating mutations in NSCLC patients.

Image-Guided Peri-Tumoral Radiofrequency Hyperthermia-Enhanced Direct Chemo-Destruction of Hepatic Tumor Margins.

PURPOSE: To validate the feasibility of using peri-tumoral radiofrequency hyperthermia (RFH)-enhanced chemotherapy to obliterate hepatic tumor margins. METHOD AND MATERIALS: This study included in vitro experiments with VX2 tumor cells and in vivo validation experiments using rabbit models of liver VX2 tumors. Both in vitro and in vivo experiments received different treatments in four groups (n=6/group): (i) RFH-enhanced chemotherapy consisting of peri-tumoral injection of doxorubicin plus RFH at 42°C; (ii) RFH alone; (iii) doxorubicin alone; and (iv) saline. Therapeutic effect on cells was evaluated using different laboratory examinations. For in vivo experiments, orthotopic hepatic VX2 tumors in 24 rabbits were treated by using a multipolar radiofrequency ablation electrode, enabling simultaneous delivery of both doxorubicin and RFH within the tumor margins. Ultrasound imaging was used to follow tumor growth overtime, correlated with subsequent histopathological analysis. RESULTS: In in vitro experiments, MTS assay demonstrated the lowest cell proliferation, and apoptosis analysis showed the highest apoptotic index with RFH-enhanced chemotherapy, compared with the other three groups (p<0.01). In in vivo experiments, ultrasound imaging detected the smallest relative tumor volume with RFH-enhanced chemotherapy (p<0.01). The TUNEL assay further confirmed the significantly increased apoptotic index and decreased cell proliferation in the RFH-enhanced therapy group (p<0.01). CONCLUSION: This study demonstrates that peri-tumoral RFH can specifically enhance the destruction of tumor margins in combination with peri-tumoral injection of a chemotherapeutic agent. This new interventional oncology technique may address the critical clinical problem of frequent marginal tumor recurrence/persistence following thermal ablation of large (>3 cm) hepatic cancers.

A radiomic nomogram based on arterial phase of CT for differential diagnosis of ovarian cancer.

PURPOSE: To develop and validate a radiomic nomogram based on arterial phase of CT to discriminate the primary ovarian cancers (POCs) and secondary ovarian cancers (SOCs). METHODS: A total of 110 ovarian cancer patients in our hospital were reviewed from January 2010 to December 2018. Radiomic features based on the arterial phase of CT were extracted by Artificial Intelligence Kit software (A.K. software). The least absolute shrinkage and selection operation regression (LASSO) was employed to select features and construct the radiomics score (Rad-score) for further radiomics signature calculation. Multivariable logistic regression analysis was used to develop the predicting model. The predictive nomogram model was composed of rad-score and clinical data. Nomogram discrimination and calibration were evaluated. RESULTS: Two radiomic features were selected to build the radiomics signature. The radiomics nomogram that incorporated 2 radiomics signature and 2 clinical factors (CA125 and CEA) showed good discrimination in training cohort (AUC 0.854), yielding the sensitivity of 78.8% and specificity of 90.7%, which outperformed the prediction model based on radiomics signature or clinical data alone. A visualized differential nomogram based on the radiomic score, CEA, and CA125 level was established. The calibration curve demonstrated the clinical usefulness of the proposed nomogram. CONCLUSION: The presented nomogram, which incorporated radiomic features of arterial phase of CT with clinical features, could be useful for differentiating the primary and secondary ovarian cancers.