BACKGROUND Hepatocellular carcinoma is the third leading cause of cancer-related deaths worldwide. In the heterogeneous group of hepatocellular carcinomas, those with characteristics of embryonic stem-cell and progenitor-cell gene expression are associated with the worst prognosis. The oncofetal gene SALL4, a marker of a subtype of hepatocellular carcinoma with progenitor-like features, is associated with a poor prognosis and is a potential target for treatment. METHODS We screened specimens obtained from patients with primary hepatocellular carcinoma for the expression of SALL4 and carried out a clinicopathological analysis. Loss-of-function studies were then performed to evaluate the role of SALL4 in hepatocarcinogenesis and its potential as a molecular target for therapy. To assess the therapeutic effects of a peptide that targets SALL4, we used in vitro functional and in vivo xenograft assays. RESULTS SALL4 is an oncofetal protein that is expressed in the human fetal liver and silenced in the adult liver, but it is reexpressed in a subgroup of patients who have hepatocellular carcinoma and an unfavorable prognosis. Gene-expression analysis showed the enrichment of progenitor-like gene signatures with overexpression of proliferative and metastatic genes in SALL4-positive hepatocellular carcinomas. Loss-of-function studies confirmed the critical role of SALL4 in cell survival and tumorigenicity. Blocking SALL4–corepressor interactions released suppression of PTEN (the phosphatase and tensin homologue protein) and inhibited tumor formation in xenograft models in vivo. CONCLUSIONS SALL4 is a marker for a progenitor subclass of hepatocellular carcinoma with an aggressive phenotype. The absence of SALL4 expression in the healthy adult liver enhances the potential of SALL4 as a treatment target in hepatocellular carcinoma. (Funded by the Singapore National Medical Research Council and others.)

As a promising method in artificial intelligence, deep learning has been proven successful in several domains ranging from acoustics and images to natural language processing. With medical imaging becoming an important part of disease screening and diagnosis, deep learning-based approaches have emerged as powerful techniques in medical image areas. In this process, feature representations are learned directly and automatically from data, leading to remarkable breakthroughs in the medical field. Deep learning has been widely applied in medical imaging for improved image analysis. This paper reviews the major deep learning techniques in this time of rapid evolution and summarizes some of its key contributions and state-of-the-art outcomes. The topics include classification, detection, and segmentation tasks on medical image analysis with respect to pulmonary medical images, datasets, and benchmarks. A comprehensive overview of these methods implemented on various lung diseases consisting of pulmonary nodule diseases, pulmonary embolism, pneumonia, and interstitial lung disease is also provided. Lastly, the application of deep learning techniques to the medical image and an analysis of their future challenges and potential directions are discussed.

Viruses in the order Picornavirales infect eukaryotes, and are widely distributed in coastal waters. Amplicon deep-sequencing of the RNA dependent RNA polymerase (RdRp) revealed diverse and highly uneven communities of picorna-like viruses in the coastal waters of British Columbia (BC), Canada. Almost 300 000 pyrosequence reads revealed 145 operational taxonomic units (OTUs) based on 95% sequence similarity at the amino-acid level. Each sample had between 24 and 71 OTUs and there was little overlap among samples. Phylogenetic analysis revealed that some clades of OTUs were only found at one site; whereas, other clades included OTUs from all sites. Since most of these OTUs are likely from viruses that infect eukaryotic phytoplankton, and viral isolates infecting phytoplankton are strain-specific; each OTU probably arose from the lysis of a specific phytoplankton taxon. Moreover, the patchiness in OTU distribution, and the high turnover of viruses in the mixed layer, implies continuous infection and lysis by RNA viruses of a diverse array of eukaryotic phytoplankton taxa. Hence, these viruses are likely important elements structuring the phytoplankton community, and play a significant role in nutrient cycling and energy transfer.

Purpose: This study aimed to identify the potential prognostic role of HK3 and provide clues about glycolysis and the microenvironmental characteristics of ccRCC. Methods: Based on the Cancer Genome Atlas (TCGA, n = 533) and Gene expression omnibus (GEO) (n = 127) databases, real-world (n = 377) ccRCC cohorts, and approximately 15,000 cancer samples, the prognostic value and immune implications of HK3 were identified. The functional effects of HK3 in ccRCC were analyzed in silico and in vitro . Results: The large-scale findings suggested a significantly higher HK3 expression in ccRCC tissues and the predictive efficacy of HK3 for tumor progression and a poor prognosis. Next, the subgroup survival and Cox regression analyses showed that HK3 serves as a promising and independent predictive marker for the prognosis and survival of patients with ccRCC from bioinformatic databases and real-world cohorts. Subsequently, we found that HK3 could be used to modulate glycolysis and the malignant behaviors of ccRCC cells. The comprehensive results suggested that HK3 is highly correlated with the abundance of immune cells, and specifically stimulates the infiltration of monocytes/macrophages presenting surface markers, regulates the immune checkpoint molecules PD-1 and CTLA-4 of exhaustive T cells, restrains the immune escape of tumor cells, and prompts the immune-rejection microenvironment of ccRCC. Conclusion: In conclusion, the large-scale data first revealed that HK3 could affect glycolysis, promote malignant biologic processes, and predict the aggressive progression of ccRCC. HK3 may stimulate the abundance of infiltrating monocytes/macrophages presenting surface markers and regulate the key molecular subgroups of immune checkpoint molecules of exhaustive T cells, thus inducing the microenvironmental characteristics of active anti-tumor immune responses.

Objective: The purpose of this study was to explore the composition of tumor-infiltrating immune cells (TIIC) and prognostic significance of tumor-infiltrating mast cells (TIMC) in adrenocortical carcinoma (ACC). Methods: The gene expression profiles of ACC were downloaded from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GSE90713, GSE12368). The abundance of TIICs in ACC samples was calculated by CIBERSORT algorithm and immunohistochemistry was used to identify mast cells of 39 tumor samples from Fudan University Shanghai Cancer Center (FUSCC). Differentially expressed genes (DEGs) were analyzed by LIMMA package using R software. Survival analysis was analyzed by Kaplan-Meier method and Cox regression models. Results: The abundance of mast cells (p = .008) was positively correlated with ACC patients' outcome in TCGA cohort and was also positively correlated with both overall survival (p < .05) and progression-free survival (p < .05) in FUSCC cohort. Different TIMC infiltrations showed significant changes in signaling pathways including DNA replication, nuclear chromosome segregation, and meiotic cell cycle process of ACC. In addition, elevated expression of eight hub genes (KIF18A, CDCA8, SKA1, CEP55, BUB1, CDK1, SGOL1, SGOL2) related to the abundance of TIMC in ACC was significantly correlated with the poor prognosis of the patients. Conclusion: In conclusion, higher TIMC infiltration was positively correlated with ACC patients' outcome in both TCGA and FUSCC cohort. Lower TIMC infiltration and elevated expression of hub genes (KIF18A,

Clear cell renal cell carcinoma (ccRCC) is the most common and highly malignant pathological type of kidney cancer. We sought to establish a metabolic signature to improve post‐operative risk stratification and identify novel targets in the prediction models for ccRCC patients. A total of 58 metabolic differential expressed genes (MDEGs) were identified with significant prognostic value. LASSO regression analysis constructed 20‐mRNA signatures models, metabolic prediction models (MPMs), in ccRCC patients from two cohorts. Risk score of MPMs significantly predicts prognosis for ccRCC patients in TCGA ( P < 0.001, HR = 3.131, AUC = 0.768) and CPTAC cohorts ( P = 0.046, HR = 2.893, AUC = 0.777). In addition, G6PC , a hub gene in PPI network of MPMs, shows significantly prognostic value in 718 ccRCC patients from multiply cohorts. Next, G6Pase was detected high expressed in normal kidney tissues than ccRCC tissues. It suggested that low G6Pase expression significantly correlated with poor prognosis ( P < 0.0001, HR = 0.316) and aggressive progression ( P < 0.0001, HR = 0.414) in 322 ccRCC patients from FUSCC cohort. Meanwhile, promoter methylation level of G6PC was significantly higher in ccRCC samples with aggressive progression status. G6PC significantly participates in abnormal immune infiltration of ccRCC microenvironment, showing significantly negative association with check‐point immune signatures, dendritic cells, Th1 cells, etc. In conclusion, this study first provided the opportunity to comprehensively elucidate the prognostic MDEGs landscape, established novel prognostic model MPMs using large‐scale ccRCC transcriptome data and identified G6PC as potential prognostic target in 1,040 ccRCC patients from multiply cohorts. These finding could assist in managing risk assessment and shed valuable insights into treatment strategies of ccRCC.

Bladder cancer (BLCA) is the most common urinary malignancy in the United States, and approximately 814,00 new cases and 17,980 deaths have been recorded in the 2020s. 1 There are two major subtypes: non-muscle-invasive bladder cancer (NMIBC) and muscleinvasive bladder cancer (MIBC). Currently, clinicians prefer to undertake transurethral resection of the bladder tumour followed by intravesical instillations of chemotherapy or immunotherapy as the therapeutic approach for NMIBC. 2,3 Radical cystectomy remains

Purpose: Lipid metabolism reprogramming is a major pathway in tumor evolution. This study investigated fatty acid synthase (FASN) mRNA expression in anthropometric adipose tissue and elucidated the prognostic value and potential mechanism of clear cell renal cell carcinoma (ccRCC).Materials and Methods: Transcription profiles were obtained from 533 ccRCC samples in The Cancer Genome Atlas (TCGA) cohorts. Real-time quantitative PCR (RT-qPCR) and immunohistochemistry were performed to detect FASN expression in 380 paired ccRCC and normal tissues from the Fudan University Shanghai Cancer Center (FUSCC). Visceral adipose tissue (VAT) and subcutaneous adipose tissue were at the level of the umbilicus as measured by magnetic resonance imaging (MRI). Non-targeted metabolomics and in vitro experiments were used to reveal the biological functions of FASN.Results: Increased FASN expression was significantly relevant to advanced T, N, and American Joint Committee on Cancer (AJCC) stages (p &lt; 0.01) and significantly correlated to poor progression-free survival (PFS) and overall survival (OS) of 913 ccRCC patients in FUSCC and TCGA cohorts. Pearson's correlation coefficient indicated that FASN amplification was positively correlated to VAT% (r = 0.772, p &lt; 0.001), which significantly correlated to poor PFS (HR = 2.066, p = 0.028) and OS (HR = 2.773, p = 0.023) in the FUSCC cohort. Transient inhibition or overexpression of FASN significantly regulated A498 and 786O cell proliferation and migration by regulating epithelial–mesenchymal transition. Inhibition of FASN led to a higher apoptotic rate and decreased lipid droplet formation compared with normal control in ccRCC cells. Non-targeted metabolomics showed that decreased de novo lipogenesis might be required to sustain an elevation of glycolytic activity in 786O cells by regulating galactinol, dl-lactate, N-acetylaspartylglutamate, and sucrose, thereby participating in carcinogenesis and progression of ccRCC.Conclusion: This study demonstrated that FASN expression is positively related to aggressive cell proliferation, migration, apoptosis, and lipid droplet formation and regulates metabolic disorders of the ccRCC microenvironment. Additionally, elevated FASN mRNA expression is significantly correlated to the abdominal obesity distribution, especially VAT%, which is a significant predictor of a poor prognosis for ccRCC patients.