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IntroductionImmune checkpoint inhibitors (ICIs) are important systemic therapeutic agents for hepatocellular carcinoma (HCC), among which T-cell immunoglobulin and mucin-domain containing protein 3 (Tim-3) is considered an emerging target for ICI therapy. This study aims to evaluate the prognostic value of Tim-3 expression and develop a predictive model for Tim-3 infiltration in HCC.MethodsWe collected data from 424 HCC patients in The Cancer Genome Atlas (TCGA) and data from 102 pathologically confirmed HCC patients from our center for prognostic analysis. Multivariate Cox regression analyses were performed on both datasets to determine the prognostic significance of Tim-3 expression. In radiomics analysis, we used the K-means algorithm to cluster regions of interest in arterial phase enhancement and venous phase enhancement images from patients at our center. Radiomic features were extracted from three subregions as well as the entire tumor using pyradiomics. Five machine learning methods were employed to construct Habitat models based on habitat features and Rad models based on traditional radiomic features. The predictive performance of the models was compared using ROC curves, DCA curves, and calibration curves.ResultsMultivariate Cox analyses from both our center and the TCGA database indicated that high Tim-3 expression is an independent risk factor for poor prognosis in HCC patients. Higher levels of Tim-3 expression were significantly associated with worse prognosis. Among the ten models evaluated, the Habitat model constructed using the LightGBM algorithm showed the best performance in predicting Tim-3 expression status (training set vs. test set AUC 0.866 vs. 0.824).DiscussionThis study confirmed the importance of Tim-3 as a prognostic marker in HCC. The habitat radiomics model we developed effectively predicted intratumoral Tim-3 infiltration, providing valuable insights for the evaluation of ICI therapy in HCC patients.

ObjectiveTo assess the positional reproducibility of sedated and non-sedated pediatric tumor patients during radiotherapy through a retrospective analysis of cone-beam computed tomography (CBCT) and planned computed tomography (CT) scan data.MethodsThe positional reproducibility of 40 pediatric tumor patients, aged 2 to 17 years with a median age of 4.5 years, who received radiotherapy under sedated and non-sedated states was retrospectively compared. The first CBCT images obtained during CT-based treatment planning were analyzed. The analysis encompassed six-dimensional positional changes, including vertical (Vrt), longitudinal (Lng), lateral (Lat), rotational (Rtn), pitch, and roll directions. Kolmogorov-Smirnov Z nonparametric rank-sum testing was employed to evaluate the positional deviations, considering absolute values regardless of directionality. Data were further stratified based on different fixation methods used during treatment.ResultsSedated patients exhibited significantly smaller positional deviations in Vrt, Lng, Lat, and Rtn directions in the body membrane group compared with their non-sedated counterparts (P

We reported an 85-year-old patient with malignant glomus tumor (GT) of the prostate. He presented with urinary frequency for more than 2 years and gross hematuria for 7 days. Computed tomography scan showed that the prostate was markedly irregularly enlarged, and the boundary between the prostate and the posterior wall of the bladder was unclear. Bilateral kidneys and ureters were dilated. Biochemical examinations showed that the serum potassium was 7.24 mmol/L and the serum creatinine was 974.6 μmol/L. Transurethral diagnostic resection was performed after restoring homeostasis through several times of bedside blood filtration. The pathological diagnosis was malignant GT. The patient’s renal function recovered after bilateral nephrostomy, and he refused further treatment and was out of contact after 9 months. We summarize the clinical and histopathological features of malignant GT of the prostate in order to improve the early recognition of the disease by clinicians.

The poly (ADP-ribose) polymerase (PARP) inhibitor (PARPi) Olaparib is a widely used targeted therapy for a variety of solid tumors with homologous recombination deficiency (HRD) caused by mutation of BRCA1/2 or other DNA repair genes. The anti-tumor activity of Olaparib has been largely attributed to its ability to inhibit PARP enzymes and block DNA single-strand break (SSB) repair, which eventually leads to the most detrimental DNA damage, double-strand breaks (DSB), in HRD cells. Although PARPi was found to induce p53-dependent cell death, the underlying molecular mechanism remains incompletely understood. Here, we report that Olaparib treatment leads to p53 stabilization and activation of its downstream target genes in a dose- and time-dependent manner. Mechanistically, Olaparib triggers nucleolar stress by inhibiting biosynthesis of the precursor of ribosomal RNAs (pre-rRNA), resulting in enhanced interaction between ribosomal proteins (RPs), RPL5 and RPL11, and MDM2. Consistently, knockdown of RPL5 and RPL11 prevents Olaparib-induced p53 activation. More importantly, Olaparib efficiently suppresses breast and colorectal cancer cell survival and proliferation through activation of p53. Altogether, our study demonstrates that Olaparib activates the nucleolar stress-RPs-p53 pathway, suggesting rRNA biogenesis as a novel target for PARPi.

Bladder cancer is a highly complex and heterogeneous malignancy. Tumor heterogeneity is a barrier to effective diagnosis and treatment of bladder cancer. Human carcinogenesis is closely related to abnormal gene expression, and DNA methylation is an important regulatory factor of gene expression. Therefore, it is of great significance for bladder cancer research to characterize tumor heterogeneity by integrating genetic and epigenetic characteristics. This study explored specific molecular subtypes based on DNA methylation status and identified subtype-specific characteristics using patient samples from the TCGA database with DNA methylation and gene expression were measured simultaneously. The results were validated using an independent cohort from GEO database. Four DNA methylation molecular subtypes of bladder cancer were obtained with different prognostic states. In addition, subtype-specific DNA methylation markers were identified using an information entropy-based algorithm to represent the unique molecular characteristics of the subtype and verified in the test set. The results of this study can provide an important reference for clinicians to make treatment decisions.

Two histone methyltransferases, enhancer of zeste homolog 2 (EZH2) and nuclear SET domain-containing 2 (NSD2), are aberrantly expressed in several types of human cancers. However, the regulatory relationship between EZH2 and NSD2 and their prognostic values in breast cancer (BC) have not been fully elucidated. In this study, we demonstrated that EZH2 and NSD2 were overexpressed in BC compared with benign lesions and normal tissues using tissue microarray, immunohistochemistry, and bioinformatic databases. Both EZH2 and NSD2 expression were associated with pathological grade of tumor and lymph node metastasis. A comprehensive survival analysis using Kaplan-Meier Plotter database indicated that EZH2 expression was negatively correlated with relapse-free survival (RFS), overall survival (OS), distant metastasis-free survival (DMFS), and postprogression survival (PPS) in 3951 BC patients, and NSD2 expression was negatively correlated with RFS and DMFS. Notably, EZH2 and NSD2 expression were coordinately higher in triple-negative breast cancer (TNBC) than that in other subtypes. Stable knockdown of EZH2 using lentiviral shRNA vector significantly reduced the proliferation, migration and invasion abilities of TNBC cell line MDA-MB-231 and MDA-MB-468, and downregulated NSD2 expression as well as the levels of H3K27me3 and H3K36me2, two histone methylation markers catalyzed by EZH2 and NSD2, respectively. By contrast, overexpression of EZH2 using adenovirus vector displayed an inverse phenotype. Furthermore, knockdown of NSD2 in EZH2-overexpressing cells could dramatically attenuate EZH2-mediated oncogenic effects. Bioinformatic analysis further revealed the function and pathway enrichments of co-expressed genes and interactive genes of EZH2/NSD2 axis, suggesting that EZH2/NSD2 axis was associated with cell division, mitotic nuclear division and transition of mitotic cell cycle in TNBC. Taken together, EZH2/NSD2 axis may act as a predictive marker for poor prognosis and accelerate the progression of TNBC.

Objective: To evaluate the value of CT radiomics in predicting the epidermal growth factor receptor (EGFR) mutation of patients with non-small cell lung cancer (NSCLC), and combing with the clinical characteristic to construct the prediction model.Methods: Sixty-seven cases of NSCLC confirmed by pathology were enrolled. The pre-treatment chest CT enhanced images were used in Radiomics analysis. Two experienced radiologists delineated the region of interest (ROI) on open source software 3D-Slicer. The feature of ROI was extracted by Pyradiomics software package and a total of 849 features were extracted. By calculating Pearson correlation coefficient between pair-wise features and LASSO method for feature screening. The prediction model was constructed by logical regression, diagnostic efficacy of the model by the area under the receiver operating characteristic (ROC) curve was calculated.Results: Based on clinical model and the radiomics model, the AUC under the ROC was 0.8387 and 0.8815, respectively. The model combining clinical and radiomics features perfect best, the AUC under the ROC was 0.9724, the sensitivity and specificity were 85.3 and 90.9%, respectively.Conclusions: Compared with clinical features or radiomics features alone, the model constructed by combining clinical and pre-treatment chest enhanced CT features may show more utility for improved patient stratification in EGFR mutation and EGFR wild.

Purpose: To investigate the associations of MRI radiological features and prognosis of glioma with the status of isocitrate dehydrogenase 1 (IDH1).Material and Methods: A total of 116 patients with gliomas were retrospectively recruited from January 2013 to December 2015. All patients were undergone routine MRI (T1WI, T2WI, T2-FLAIR) scanning and contrast-enhanced MRI T1WI before surgery. The following imaging features were included: tumor location, diameter, the pattern of growth, boundary, the degree of enhancement, mass effect, edema, cross the middle line, under the ependyma. χ2 and Fisher's exact probability tests were used to determine the significance of associations between MRI features and IDH1 mutation of glioma. The survival distributions were estimated using Kaplan-Meier compared by Log-rank test. Univariate and multivariate analyses were performed using Cox regression.Results: Gliomas with IDH1 mutant were significantly more likely to exhibit homogeneous signal intensity (p = 0.009) on non-contrast MRI protocols and less contrast enhancement (p = 0.000) on contrast enhanced T1WI. IDH1 mutant type glioma was more inclined to cross the midline to invade contralateral hemisphere (p = 0.001). The overall survival between IDH1 mutated and wild type glioma were significantly different (p = 0.000), age ≤ 40 (p = 0.003), KPS scores > 80 before operation (p = 0.000) and low grade glioma (p = 0.000).Conclusions: Our results suggest IDH1 mutant in gliomas is more likely to exhibit homogeneous signal intensity, less contrast enhancement and more inclined to cross the midline. Patients with IDH1 mutated, age ≤ 40, KPS scores > 80 before operation and low-grade glioma may have a longer life and better prognosis.

Objective: Neutrophil lymphocyte ratio (NLR), Lymphocyte mononuclear cell ratio (LMR), and Platelet lymphocyte ratio (PLR) can be used as various prognostic factors for malignant tumors, but the value of prognosis for patients with adenocarcinoma of the esophagogastric junction (AEG) has not been determined. This study used meta-analysis to assess the value of these indicators in the evaluation of AEG prognosis.Methods: Relevant literatures on the prognostic relationship between NLR, LMR, PLR, and AEG was retrieved from PubMed, Web of Science, Embase, Cochrane Library, Cochrane Central Register of Controlled Trials, Wanfang data, and Chinese National Knowledge Infrastructure. The search time from database establishment to June 30, 2019. The language is limited to English and Chinese. Data was analyzed using Stata 15.0 software.Result: Six retrospective studies were included, five of them involved NLR and six of them involved PLR. No LMR literature that adequately satisfied the conditions was retrieved. Increased NLR was significantly associated with a significant reduction in overall survival (OS), cancer-specific survival (CSS), or disease specific survival (DSS) in patients with AEG [hazard ratio (HR) = 1.545, 95% CI: 1.096–2.179, P < 0.05]. Subgroup analysis showed that NLR had significant value in the prognosis of both Chinese and Non-Chinese patients (P = 0.009 vs. P = 0.000). NLR had significant prognostic value for ≥3 and 0.05). PLR had no significant prognostic value for both Chinese and UK patients (P = 0.282 vs. P = 0.429). PLR had no significant prognostic value for ≥150 group and

Purpose: The present study aimed to investigate the clinical prognostic significance of radiomics signature (R-signature) in patients with gastric neuroendocrine neoplasm (GNEN). Methods and Materials: A retrospective study of 182 patients with GNEN who underwent dual-phase enhanced computed tomography (CT) scanning was conducted. LASSO-Cox regression analysis was used to screen the features and establish the arterial, venous and the arteriovenous phase combined Rsignature, respectively. The association between the optimal R-signature with the best prognostic performance and overall survival (OS) was assessed in the training cohort and verified in the validation cohort. Univariate and multivariate Cox regression analysis were used to identify the significant factors of clinicopathological characteristics for OS. Furthermore, the performance of a combined radiomics-clinical nomogram integrating the R-signature and independent clinicopathological risk factors was evaluated. Results: The arteriovenous phase combined R-signature had the best performance in predicting OS, and its C-index value was better than the independent arterial and venous phase R-signature (0.803 vs 0.784 and 0.803 vs 0.756, P<0.001, respectively). The optimal R-signature was significantly associated with OS in the training cohort and validation cohort. GNEN patients could be successfully divided into high and low prognostic risk groups with radiomics score median. The combined radiomics-clinical nomogram combining this R-signature and independent clinicopathological risk factors (sex, age, treatment methods, T stage, N stage, M stage, tumor boundary, Ki67, CD56) exhibited significant prognostic superiority over clinical nomogram, Rsignature alone, and traditional TNM staging system (C-index, 0.882 vs 0.861, 882 vs 0.803, and 0.882 vs 0.870 respectively, P<0.001). All calibration curves showed remarkable consistency between predicted and actual survival, and decision curve analysis verified the usefulness of the combined radiomicsclinical nomogram for clinical practice. Conclusions: The R-signature could be used to stratify patients with GNEN into high and low risk groups. Furthermore, the combined radiomics-clinical nomogram provided better predictive accuracy than other predictive models and might aid clinicians with therapeutic decision-making and patient counseling. [ABSTRACT FROM AUTHOR]

Background: Hepatocellular carcinoma (HCC) is the sixth leading type of cancer worldwide. We aimed to develop a preoperative predictive model of the risk of early tumor recurrence after HCC treatment based on radiomic features of the peritumoral region and evaluate the performance of this model against postoperative pathology. Method: Our model was developed using a retrospective analysis of imaging and clinicopathological data of 175 patients with an isolated HCC =5 cm in diameter; 117 patients were used for model training and 58 for model validation. The peritumoral area was delineated layer-by-layer for the arterial and portal vein phase on preoperative dynamic enhanced computed tomography images. The volume area of interest was expanded by 5 and 10 mm and the radiomic features of these areas extracted. Lasso was used to select the most stable features. Results: The radiomic features of the 5-mm area were sufficient for prediction of early tumor recurrence, with an area under the curve (AUC) value of 0.706 for the validation set and 0.837 for the training set using combined images. The AUC of the model using clinicopathological information alone was 0.753 compared with 0.786 for the preoperative radiomics model (P >0.05). Conclusions: Radiomic features of a 5-mm peritumoral region may provide a non-invasive biomarker for the preoperative prediction of the risk of early tumor recurrence for patients with a solitary HCC =5 cm in diameter. A fusion model that combines the radiomic features of the peritumoral region and postoperative pathology could contribute to individualized treatment of HCC. [ABSTRACT FROM AUTHOR]

BackgroundHepatocellular carcinoma (HCC) is the sixth leading type of cancer worldwide. We aimed to develop a preoperative predictive model of the risk of early tumor recurrence after HCC treatment based on radiomic features of the peritumoral region and evaluate the performance of this model against postoperative pathology.MethodOur model was developed using a retrospective analysis of imaging and clinicopathological data of 175 patients with an isolated HCC ≤5 cm in diameter; 117 patients were used for model training and 58 for model validation. The peritumoral area was delineated layer-by-layer for the arterial and portal vein phase on preoperative dynamic enhanced computed tomography images. The volume area of interest was expanded by 5 and 10 mm and the radiomic features of these areas extracted. Lasso was used to select the most stable features.ResultsThe radiomic features of the 5-mm area were sufficient for prediction of early tumor recurrence, with an area under the curve (AUC) value of 0.706 for the validation set and 0.837 for the training set using combined images. The AUC of the model using clinicopathological information alone was 0.753 compared with 0.786 for the preoperative radiomics model (P >0.05).ConclusionsRadiomic features of a 5-mm peritumoral region may provide a non-invasive biomarker for the preoperative prediction of the risk of early tumor recurrence for patients with a solitary HCC ≤5 cm in diameter. A fusion model that combines the radiomic features of the peritumoral region and postoperative pathology could contribute to individualized treatment of HCC.

Rationale and ObjectivesPrimary spinal epithelioid hemangioendothelioma (SEHE) is an extremely rare angiocentric vascular neoplasm with inherent metastatic potential, which pursues a clinical course intermediate between hemangioma and angiosarcoma. The present study sought to present computed tomography (CT) and magnetic resonance imaging (MRI) findings and clinical features of primary SEHE and review the literature.Materials and MethodsClinical data of four patients with primary SEHE confirmed by pathology from January 2011 to May 2020 were analyzed retrospectively. Two cases underwent CT scan, while 3 cases underwent MRI scan. Image observation included the tumor location, bone changes, morphology, density/signal characteristics, and enhanced features.ResultsThe four patients were all women who ranged in age from 25 to 74 years. Four cases of the lesions were in the vertebral body; among them, two cases involved the accessory of the vertebra. Soap bubble appearance was detected in 2 cases, honeycomb osteolytic appearance in 2 cases, a sclerotic margin in 3 cases, and accompanying vertebral compression fracture in 1 case. CT showed a slightly inhomogeneous low density with punctate high-density foci. MRI showed an inhomogeneous low signal on T1-weighted image (T1WI) and a high signal on T2WI. Contrast-enhanced CT/MRI demonstrated moderate to intensive inhomogeneous enhancement of the lesions. The discs were normal. In one case, lesions presented a dural tail sign.ConclusionsPrimary SEHE is so rare in the clinic as an aggressive vascular tumor. The relatively typical clinical features and radiographic findings can help in preoperative diagnosis.

PurposeIt is challenging for traditional CT signs to predict invasiveness of pancreatic solid pseudopapillary neoplasm (pSPN). We aim to develop and evaluate CT-based radiomics signature to preoperatively predict invasive behavior in pSPN.MethodsEighty-five patients who had pathologically confirmed pSPN and preoperative contrasted-enhanced CT imaging in our hospital were retrospectively analyzed (invasive: 24; non-invasive: 61). 1316 radiomics features were separately extracted from delineated 2D or 3D ROIs in arterial and venous phases. 200% (SMOTE) was used to generate balanced dataset (invasive: 72, non-invasive: 96) for each phase, which was for feature selection and modeling. The model was internally validated in the original dataset. Inter-observer consistency analysis, spearman correlation, univariate analysis, LASSO regression and backward stepwise logical regression were mainly applied to screen the features, and 6 logistic regression models were established based on multi-phase features from 2D or 3D segmentations. The ROC analysis and Delong’s test were mainly used for model assessment and AUC comparison.ResultsIt retained 11, 8, 7 and 7 features to construct 3D-arterial, 3D-venous, 2D-arterial and 2D-venous model. Based on 3D ROIs, the arterial model (AUC: 0.914) performed better than venous (AUC: 0.815) and the arterial-venous combined model was slightly improved (AUC: 0.918). Based on 2D ROIs, the arterial model (AUC: 0.814) performed better than venous (AUC:0.768), while the arterial-venous combined model (AUC:0.893) performed better than any single-phase model. In addition, the 3D arterial model performed better than the best combined 2D model. The Delong’s test showed that the significant difference of model AUC existed in arterial models in original dataset (p = 0.019) while not in arterial-venous combined model (p=0.49) as comparing 2D and 3D ROIs.ConclusionThe arterial radiomics model constructed by 3D-ROI feature is potential to predict the invasiveness of pSPN preoperatively.

PurposeGastric sarcomatoid carcinoma (GSC) is a very rare malignant tumor. The purpose of this study is to describe the clinical, computed tomography (CT), and pathologic features of GSC to increase awareness of this entity.MethodsThe CT features and clinical data of five patients with pathologically documented GSC were retrospectively analyzed and compared with the corresponding data of gastric adenocarcinoma and lymphoma.ResultsAmong the 5 patients, 4 were male, and 1 was female. The median age was 59 years. Of the 5 cases of GSC, 3 were in the gastric fundus and cardia, 1 was in the gastric body, and 1 was in the gastric fundus. The gastric wall had local thickening in 4 cases and mass formation in 1 case, with stenosis and deformation of the adjacent gastric cavity. The long-axis diameter of the lesions ranged from 1.4 to 10.2 cm (mean, 4.97 cm) and was 10 cm in 1 case. The tumor showed predominantly inhomogeneous density, with radiodensity values ranging from 30 to 53 HU. In addition, ulcers with an irregular base and slightly raised borders were observed in 4 of 5 cases. After an injection of contrast material, heterogeneous (n = 4) or homogeneous (n = 1) enhancement was observed. After contrast medium injection, obvious enhancement was seen in 2 cases, and moderate enhancement was seen in 3 cases; the peak tumor signal was observed in the portal phase. Two of the patients demonstrated evidence of lymph node involvement, and in one patient, the boundary between the lesion and the left lobe of the liver was unclear, with low attenuation in the right lobe of the liver with circular enhancement. The remaining two patients showed no evidence of metastasis.ConclusionAlthough GSC is extremely rare, it should be considered in the differential diagnosis of gastric adenocarcinoma and lymphoma. CT findings, combined with patient age and sex, can provide support for the diagnosis of GSC. However, the final diagnosis must be confirmed with histopathology.