Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Kidney cancer usually requires multidisciplinary individualized treatments. No matter what kind of treatment, drugs are essential. According to the "six-step process" (prescription legitimacy review, patient basic information evaluation review, treatment protocol review, organ function and laboratory index review, pretreatment review, and unconventional prescription review) in prescription review proposed by the anti-tumor drug prescription review expert group and referring to domestic and foreign kidney cancer guidelines and drug instructions in recent years, this consensus selects 9 targeted drugs and 4 immunotherapeutic drugs that are currently commonly used in China and elaborates the key review points in patient basic information evaluation review, treatment protocol review, and organ function and laboratory index review of kidney cancer drug treatment, in order to provide reference for clinical front-line pharmacists to review prescriptions of kidney cancer patients and promote rational drug use in clinic.

Kidney cancer usually requires multidisciplinary individualized treatments. No matter what kind of treatment, drugs are essential. According to the "six-step process" (prescription legitimacy review, patient basic information evaluation review, treatment protocol review, organ function and laboratory index review, pretreatment review, and unconventional prescription review) in prescription review proposed by the anti-tumor drug prescription review expert group and referring to domestic and foreign kidney cancer guidelines and drug instructions in recent years, this consensus selects 9 targeted drugs and 4 immunotherapeutic drugs that are currently commonly used in China and elaborates the key review points in patient basic information evaluation review, treatment protocol review, and organ function and laboratory index review of kidney cancer drug treatment, in order to provide reference for clinical front-line pharmacists to review prescriptions of kidney cancer patients and promote rational drug use in clinic.

Radiogenomics explores the relationship between imaging features and gene expression patterns using radiomics, which is non-invasive and can present the overall information of tumors. The application of radiomics, somewhat effective in predicting gene mutations in non-small cell lung cancer (NSCLC), has recently become a research focus. Radiomic features, combined with conventional imaging, clinical and other features, can provide multi-directional information on tumors and play an increasingly important role in the prediction and precise treatment of NSCLC-driving gene phenotypes.

Radiogenomics aims at investigating the relationship between radiomics features and genomic features, which has certain practical value in the individualized molecular targeted therapy. Meanwhile, it is noninvasive, repeatable and inexpensive. In recent years, a large number of studies have shown that radiomics features have certain predictive values for the mutation status of driver genes of lung cancer. The application of radiogenomics is insufficient at present, but with its continuous improvement and development, it will play an increasingly important role in the precise therapy of lung cancer in the future.

Objective To synthesize a molecular probe targeted to human hepatoma HepG2 cells with high expression of integrin αvβ3 (RGD-PEG-VSOP) and evaluate its MRI efficacy in vitro.Methods RGD-PEG-VSOP was characterized and analyzed by 1H NMR and TEM.MTT test was used to evaluate its biological safety.In vitro experiments at the cellular level,the targeting effect of RGD-PEG-VSOP to integrin was assessed,meanwhile the nontargeted nanoparticles were used as controls.Results TEM showed that the nanoparticles were spherical and uniform in size,with a relatively high r1 relaxivity of 1.37 mM-1S-1.MRI showed the signal intensity of the HepG2 cells treated with RGD-PEG--VSOP was significantly higher than that of the HepG2 cells treated with PEG-VSOP (P＜0.05).Conclusion RGD-PEG-VSOP has positive T1 contrast effect.At the cellular level,the RGD-PEG-VSOP nanoparticles have the characteristics targeted to integrin αvβ3.

Objective To observe the targeting function of high affinity anti-EGFR monoclonal antibody (Cetuximab)conjugated superparamagnetic iron oxide-dopamine (anti-EGFR-PEG-SPIO) lung cancer cells via epidermal growth factor receptor (EGFR),as well as the feasibility for surveillance of tumor targeting with MRI.Methods Nanoparticles (NPs)of anti-EGFR-PEG-SPIO and PEG-SPIO were prepared,and the morphology of nanoparticles was observed with transmission electron microscope (TEM).The hydrodynamic diameter and R2 values of nanoparticles before and after conjugation with anti-EGFR were performed with dynamic light scattering (DLS) and MRI.MRI was performed in incubation with anti-EGFR-PEG-SPIO and PEG-SPIO after 2 h in vitro.The cellular uptake of anti-EGFR-PEG-SPIO and PEG-SPIO was further evaluated using Prussian blue staining and TEM.Results Anti-EGFR-PEG-SPIO and PEG-SPIO showed signal intensity of H460 cells on T2WI,decreased significantly compared with PEG-SPIO.The rate of signal intensity change was -58.2％,-82.7％,-94.4％ and-98.3％,respectively,at iron concentrations of (0,10,20,40,80 μg/ml) of antiEGFR-PEG-SPIO.Prussian blue staining and TEM showed that a lot of intracellular irons of anti-EGFR-PEG-SPIO were observed in H460 cells,but few of PEG-SPIO.Conclusion The effect of active targeting via anti-EGFR in EGFR overexpressed cells can be achieved with anti-EGFR-PEG-SPIO in H460 cells in vitro,and the targeting delivery process could be monitored with 3.0T MRI.

Objective To summary the experience of laparoscopic cystectomy ileal conduit (Bricker) and orthotopic ileal neo‐bladder (Hautmann) and compare the short‐term efficacy of the two types of urinary diversion for invasive bladder cancer . Methods Retorspective analysis of the patients in our hospital who accepted laparoscopic radical cystectomy from 2010 to 2014 was performed ,74 of them accepted ileal conduit ,and 30 of them accepted orthotopic ileal neobladder .The general clinical data ,postop‐erative recovery ,postoperative complications and Oncology feature were analyzed and compared between the two groups .Results There was no demonstrable difference was found in operation time ,blood loss ,intraoperative blood transfusion rate ,the number of removed lymph node ,average hospital stay ,specimens positive margin rate and postoperative pathology results between the two groups (P>0 .05) .But there were significant difference in postoperative intestinal function recovery time[(4 .2 ± 1 .4)d ,(5 .3 ± 2 .2)d] ,(P=0 .002) ,and the complication rates 31 .9% (23 cases)vs .53 .3% (16 case) ,P=0 .043 .After 6 months ,the daytime and nighttime urinary control were 76 .9% ,57 .7% ,after 12 months ,the daytime and nighttime urinary control increased to 90 .9% , 81 .8% .2 cases(7 .7% ) were diagnosed with recurrence or metastasis during follow‐up in Hautmann group ,while 9 cases(14 .1% ) were diagnosed with recurrence or metastasis in Bricker group .Conclusion Two kinds of surgical procedures both have the similar therapeutic effect ,but the postoperative quality of life is better for Hautmann orthotopic neobladder patients .