Integrated Single-cell and Transcriptome Sequencing Analyses Identified PREX1 as an Immune-related Prognostic Biomarker for Liver Hepatocellular Carcinoma.

Background: PtdIns (3,4,5) P3-dependent Rac exchanger 1 (PREX1), also known as PREX1, a member of the Rac guanine nucleotide exchange factors (Rac-GEF) family. Studies have suggested that PREX1 plays a role in mediating oncogenic pathway activation and controlling various biological mechanisms in different types of cancer, including liver hepatocellular carcinoma (LIHC). However, the function of PREX1 in the pathogenesis of LIHC and its potential role on immunological regulation is not clearly elucidated. Methods: The expression level and the clinical role of PREX1 in LIHC was analyzed based on database from the Cancer Genome Atlas (TCGA), TNM plotter and University of Alabama Cancer Database (UALCAN). We investigated the relationship between PREX1 and immunity in LIHC by TISIDB, CIBERSORT and single cell analysis. Immunotherapy responses were assessed by the immunophenoscores (IPS). Moreover, biological functional assays were performed to further investigate the roles of PREX1 in liver cancer cell lines. Results: Higher expression of PREX1 in LIHC tissues than in normal liver tissues was found based on public datasets. Further analysis revealed that PREX1 was associated with worse clinical characteristics and dismal prognosis. Pathway enrichment analysis indicated that PREX1 participated in immune-related pathways. Through CIBERSORT and single cell analysis, we found a remarkable correlation between the expression of PREX1 and various immune cells, especially macrophages. In addition, high PREX1 expression was found to be associated with a stronger response to immunotherapy. Furthermore, in vitro assays indicated that depletion of PREX1 can suppress invasion and proliferation of LIHC cells. Conclusion: Elevated expression of PREX1 indicates poor prognosis, influences immune modulation and predicts sensitivity of immunosuppression therapy in LIHC. Our results suggested that PREX1 may be a prognostic biomarker and therapeutic target, offering new treatment options for LIHC.

AI detection of mild COVID-19 pneumonia from chest CT scans.

OBJECTIVES: An artificial intelligence model was adopted to identify mild COVID-19 pneumonia from computed tomography (CT) volumes, and its diagnostic performance was then evaluated. METHODS: In this retrospective multicenter study, an atrous convolution-based deep learning model was established for the computer-assisted diagnosis of mild COVID-19 pneumonia. The dataset included 2087 chest CT exams collected from four hospitals between 1 January 2019 and 31 May 2020. The true positive rate, true negative rate, receiver operating characteristic curve, area under the curve (AUC) and convolutional feature map were used to evaluate the model. RESULTS: The proposed deep learning model was trained on 1538 patients and tested on an independent testing cohort of 549 patients. The overall sensitivity was 91.5% (195/213; p < 0.001, 95% CI: 89.2-93.9%), the overall specificity was 90.5% (304/336; p < 0.001, 95% CI: 88.0-92.9%) and the general AUC value was 0.955 (p < 0.001). CONCLUSIONS: A deep learning model can accurately detect COVID-19 and serve as an important supplement to the COVID-19 reverse transcription-polymerase chain reaction (RT-PCR) test. KEY POINTS: • The implementation of a deep learning model to identify mild COVID-19 pneumonia was confirmed to be effective and feasible. • The strategy of using a binary code instead of the region of interest label to identify mild COVID-19 pneumonia was verified. • This AI model can assist in the early screening of COVID-19 without interfering with normal clinical examinations.

Contribution of ultrasound-guided fine-needle aspiration cell blocks of metastatic supraclavicular lymph nodes to the diagnosis of lung cancer.

PURPOSES: Routine smears of fine-needle aspiration (FNA) specimens of supraclavicular lymph nodes with ultrasound (US) real-time guidance have proven useful in lung cancer staging, but the clinical value of additional information from cell-block of FNA samples has been little researched. This study mainly focused on the contribution of cell block analysis to the diagnosis and staging in lung cancer. MATERIALS AND METHODS: Clinical data about 211 lung cancer patients with supraclavicular lymph node enlargement admitted to ultrasonography in the Zhejiang Cancer Hospital and recommended a needle biopsy under US-guided, the adequacy of the specimens for preparing cell blocks was acquireded, and the additional immunohistochemistry or genetic information provided from cell block analysis was examined. RESULTS: In 211 lung cancer patients referred for US-guided FNA (median age 61.8 ± 10.0 years, range 30-88) 279 aspirations were performed. Conventional smears could be obtained from 185 aspirates (66.3%) and contained 176 (95.1%) diagnostic smears. Cell blocks could be obtained from 94 aspirates (33.7%) and contained diagnostic material in 88 (93.6%) aspirates. Above all, cell blocks also made epithelial growth factor receptor gene mutation analysis in 17 patients with FNA samples, and the positive rate was 70.6%. Overall, cell blocks provided clinically significant information for 51 of the 211 patients participating in the study (24.2%). CONCLUSION: Cell-block samples from US-guided FNA is a promising, relatively noninvasive technique to provide additional information in lung cancer diagnosis. Analysis of cell blocks allows for genetic analysis of the patients with supraclavicular lymph nodes metastasis.

[Value of ultrasono-portography using SonoVue in selective portal vein embolization].

OBJECTIVE: To explore the value of ultrasono-portography using SonoVue in selective portal vein embolization (SPVE). METHODS: Twenty-eight patients with malignant liver tumors underwent percutaneous ultrasound-guided SPVE. The procedure was performed under color Doppler ultrasound guidance in 11 cases (conventional group) and under guidance with ultrasono-portography using SonoVue in 17 cases (contrast group). Contrast-enhanced CT was performed 2-4 weeks after SPVE to evaluate the effect of embolization. RESULTS: The procedure of SPVE was aborted in 3 cases in which ultrasono-portography showed contraindications. Postoperative contrast-enhanced CT showed ectopic embolization in 2 cases in the conventional group, and none of the cases in the contrast group showed ectopic embolization. CONCLUSION: Ultrasono-portography using SonoVue can provide important assistance for SPVE.