Noninvasive prediction of lymph node metastasis in pancreatic cancer using an ultrasound-based clinicoradiomics machine learning model.

OBJECTIVES: This study was designed to explore and validate the value of different machine learning models based on ultrasound image-omics features in the preoperative diagnosis of lymph node metastasis in pancreatic cancer (PC). METHODS: This research involved 189 individuals diagnosed with PC confirmed by surgical pathology (training cohort: n = 151; test cohort: n = 38), including 50 cases of lymph node metastasis. Image-omics features were extracted from ultrasound images. After dimensionality reduction and screening, eight machine learning algorithms, including logistic regression (LR), support vector machine (SVM), K-nearest neighbors (KNN), random forest (RF), extra trees (ET), extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), and multilayer perceptron (MLP), were used to establish image-omics models to predict lymph node metastasis in PC. The best omics prediction model was selected through ROC curve analysis. Machine learning models were used to analyze clinical features and determine variables to establish a clinical model. A combined model was constructed by combining ultrasound image-omics and clinical features. Decision curve analysis (DCA) and a nomogram were used to evaluate the clinical application value of the model. RESULTS: A total of 1561 image-omics features were extracted from ultrasound images. 15 valuable image-omics features were determined by regularization, dimension reduction, and algorithm selection. In the image-omics model, the LR model showed higher prediction efficiency and robustness, with an area under the ROC curve (AUC) of 0.773 in the training set and an AUC of 0.850 in the test set. The clinical model constructed by the boundary of lesions in ultrasound images and the clinical feature CA199 (AUC = 0.875). The combined model had the best prediction performance, with an AUC of 0.872 in the training set and 0.918 in the test set. The combined model showed better clinical benefit according to DCA, and the nomogram score provided clinical prediction solutions. CONCLUSION: The combined model established with clinical features has good diagnostic ability and can be used to predict lymph node metastasis in patients with PC. It is expected to provide an effective noninvasive method for clinical decision-making, thereby improving the diagnosis and treatment of PC.

Exploring the impact of insufficient thermal ablation on hepatocellular carcinoma: NDST2 overexpression mechanism and its role in facilitating growth and invasion of residual cancer cells.

OBJECTIVE: Incomplete thermal ablation (ITA) fosters the malignancy of residual cells in Hepatocellular carcinoma (HCC) with unclear mechanisms now. This study aims to investigate the expression changes of NDST2 following ITA of HCC and its impact on residual cancer cells. METHODS: An in vitro model of heat stress-induced liver cancer was constructed to measure the expression of NDST2 using Quantitative Real-Time PCR and Western blotting experiments. The sequencing data from nude mice were used for validation. The clinical significance of NDST2 in HCC was evaluated by integrating datasets. Gene ontology and pathway analysis were conducted to explore the potential signaling pathways regulated by NDST2. Additionally, NDST2 was knocked down in heat stress-induced HCC cells, and the effects of NDST2 on these cells were verified using Cell Counting Kit-8 assays, scratch assays, and Transwell assays. RESULTS: NDST2 expression levels are elevated in HCC, leading to a decrease in overall survival rates of HCC patients. Upregulation of immune checkpoint levels in high NDST2-expressing HCC may contribute to immune evasion by liver cancer cells. Additionally, the low mutation rate of NDST2 in HCC suggests a relatively stable expression of NDST2 in this disease. Importantly, animal and cell models treated with ITA demonstrate upregulated expression of NDST2. Knockdown of NDST2 in heat stress-induced liver cancer cells results in growth inhibition associated with gene downregulation. CONCLUSION: The upregulation of NDST2 can accelerate the progression of residual HCC after ITA, suggesting a potential role for NDST2 in the therapeutic efficacy and prognosis of residual HCC.

Proteomics profiling of nontumor liver tissues identifies prognostic biomarkers in hepatitis B-related hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) often occurs following chronic hepatitis B virus (HBV) infection, leading to high recurrence and a low 5-year survival rate. We developed an overall survival (OS) prediction model based on protein expression profiles in HBV-infected nontumor liver tissues. We aimed to demonstrate the feasibility of using protein expression profiles in nontumor liver tissues for survival prediction. A univariate Cox and differential expression analysis were performed to identify candidate prognostic factors. A multivariate Cox analysis was performed to develop the liver gene prognostic index (LGPI). The survival differences between the different risk groups in the training and validation cohorts were also estimated. A total of 363 patients, 159 in the training cohort, and 204 in the validation cohort were included. Of the 6478 proteins extracted from nontumor liver tissues, we identified 1275 proteins altered between HCC and nontumor liver tissues. A total of 1090 out of 6478 proteins were significantly related to OS. The prognostic values of the proteins in nontumor tissues were mostly positively related to those in the tumor tissues. Protective proteins were mainly enriched in the metabolism-related pathways. From the differentially expressed proteins, the top 10 most significant prognosis-related proteins were submitted for LGPI construction. In the training and validation cohorts, this LGPI showed a great ability for distinguishing patients' OS risk stratifications. After adjusting for clinicopathological features, the LGPI was an independent prognostic factor in the training and validation cohorts. We demonstrated the prognostic value of protein expression profiling in nontumor liver tissues. The proposed LGPI was a promising predictive model for estimating OS in HBV-related HCC.

Comparison of the Feasibility and Diagnostic Performance of ACR CEUS LI-RADS and a Modified CEUS LI-RADS for HCC in Examinations Using Sonazoid.

OBJECTIVES: The present study aimed to determine the feasibility of the American College of Radiology's (ACR) contrast-enhanced ultrasound (CEUS) Liver Imaging Reporting and Data System (LI-RADS) (version 2017) in examinations using Sonazoid and compare its diagnostic performance with that of modified LI-RADS in patients at high risk of hepatocellular carcinoma (HCC). METHODS: This retrospective study's sample population consisted of 137 participants with a total of 140 nodules who underwent CEUS with Sonazoid and pathological confirmation via surgery or biopsy from January 2020 to February 2022. The lesions were evaluated and classified based on the reference standards (ie, ACR CEUS LI-RADS and modified LI-RADS). The overall diagnostic capabilities of the two systems were evaluated in terms of accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) with 95% confidence intervals (CIs). RESULTS: The participants had a median age of 51 years and an interquartile range of 43-58 years. Regarding LR-5 as a predictor of HCC, the accuracy results of the ACR LI-RADS and modified LI-RADS algorithms were 72.9 and 71.4%, respectively (P = .50). The sensitivity of both systems was the same (69.7%; 95% CI: 60.7-77.8%). Regarding LR-M as a predictor of non-HCC malignancy, the diagnostic performance of the algorithms was the same, with accuracy and sensitivity results of 76.4 and 73.3%, respectively (95% CI: 44.9-92.2%). CONCLUSION: The findings indicate that modified LI-RADS had a moderate level of diagnostic performance for HCC in examinations using Sonazoid, which was comparable to ACR LI-RADS.

Investigation of Circular RNA Expression Profiles in Ultrasound-guided Incomplete Radiofrequency Ablation Transplanted Tumor Models of Human Liver Cancer.

BACKGROUND: Abnormally expressed circular RNAs (circRNAs) are associated with many diseases and have important biological effects on the regulation of gene expression. However, the circRNA expression profile in incomplete radiofrequency ablation (RFA)-treated liver cancer (LC) patients has not been characterized. This study investigated the potential biological effects of differentially expressed (DE) circRNAs in an incomplete RFA-treated transplantation tumor model of human LC. MATERIAL/METHODS: A circRNA microarray was utilized to analyze changes in the circRNA expression profiles. CircRNA host gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were also conducted using computational biology. Quantitative real-time PCR (qPCR) was also performed on the selected DE-circRNAs to verify the reliability of the microarray. The circRNA/miRNA interactions were predicted by Arraystar software and confirmed by a dual-luciferase assay. RESULTS: Following RFA incomplete ablation, 76 DE-circRNAs were detected (|fold change |>1.5, P-value < 0.05), 21 of which were upregulated and 55 of which were downregulated. Computational biological analysis revealed that the T-cell receptor signaling pathway was the most significantly enriched pathway of the genes related to altered expression, as indicated by enrichment of LCK, AKT3 and DLG1. PCR results for the upregulated hsa_circRNA_103595 and downregulated hsa_circRNA_001264 indicated that the circRNA microarray sequencing results were reliable. Double luciferase reporter assays confirmed that hsa-miR-185-3p was the target miRNA of hsa_circRNA_103595. CONCLUSIONS: The current study confirmed the changes in the expression profiles of circRNAs in tumor transplantation models after incomplete ablation, these changes may play a crucial role in the pathophysiological process of residual cancer transplantation tumors. These findings could lead to new directions for investigating the molecular biological mechanisms underlying RFA-treated LC as well as new ideas for treating LC by regulating circRNAs.

Identification of clear cell renal cell carcinoma subtypes by integrating radiomics and transcriptomics.

Objective: This study aimed to delineate the clear cell renal cell carcinoma (ccRCC) intrinsic subtypes through unsupervised clustering of radiomics and transcriptomics data and to evaluate their associations with clinicopathological features, prognosis, and molecular characteristics. Methods: Using a retrospective dual-center approach, we gathered transcriptomic and clinical data from ccRCC patients registered in The Cancer Genome Atlas and contrast-enhanced computed tomography images from The Cancer Imaging Archive and local databases. Following the segmentation of images, radiomics feature extraction, and feature preprocessing, we performed unsupervised clustering based on the "CancerSubtypes" package to identify distinct radiotranscriptomic subtypes, which were then correlated with clinical-pathological, prognostic, immune, and molecular characteristics. Results: Clustering identified three subtypes, C1, C2, and C3, each of which displayed unique clinicopathological, prognostic, immune, and molecular distinctions. Notably, subtypes C1 and C3 were associated with poorer survival outcomes than subtype C2. Pathway analysis highlighted immune pathway activation in C1 and metabolic pathway prominence in C2. Gene mutation analysis identified VHL and PBRM1 as the most commonly mutated genes, with more mutated genes observed in the C3 subtype. Despite similar tumor mutation burdens, microsatellite instability, and RNA interference across subtypes, C1 and C3 demonstrated greater tumor immune dysfunction and rejection. In the validation cohort, the various subtypes showed comparable results in terms of clinicopathological features and prognosis to those observed in the training cohort, thus confirming the efficacy of our algorithm. Conclusion: Unsupervised clustering based on radiotranscriptomics can identify the intrinsic subtypes of ccRCC, and radiotranscriptomic subtypes can characterize the prognosis and molecular features of tumors, enabling noninvasive tumor risk stratification.

Overexpression of PLK1 Molecule Following Incomplete Thermal Ablation Promotes the Proliferation and Invasion of Residual Hepatocellular Carcinoma.

TAT, a widely used treatment for HCC, can exacerbate the progression of residual HCC. The present study investigated the mechanism of action of PLK1 following ITA of HCC. The PLK1 levels in HCC were determined using qRT-PCR from clinical patient samples, IHC from tissue microarray, and data from globally high-throughput data and microarrays. The PLK1 levels and their effect on the biological phenotype of heat-stress HCC cells were evaluated through in vitro experiments. We detected PLK1 abnormal expression in HCC models of nude mice subjected to ITA. We detected the effects of different PLK1 expression levels on EMT pathway proteins. PLK1 exhibited an overexpression in HCC tissues with an SMD of 1.19 (3414 HCC and 3036 non-HCC tissues were included), distinguishing HCC from non-HCC effectively (AUC = 0.9). The qRT-PCR data from clinical HCC patient samples and IHC from HCC tissue microarray results also indicated an overexpressed level. In the incomplete ablation models, an increased PLK1 expression was found in both heat-stress cells and subcutaneous tumors. The upregulation of PLK1 following ITA was found to enhance the malignancy of HCC and exacerbate the proliferation, migration, and invasion of residual HCC cells, whereas PLK1 knockdown suppressed the biological malignancy of HCC cells. Meanwhile, PLK1 has different regulatory effects on various EMT pathway proteins. PLK1 promotes the progression of residual HCC by activating EMT pathway after ITA, which might provide a novel idea for the treatment and prognosis of residual HCC.

RAD21: A Key Transcriptional Regulator in the Development of Residual Liver Cancer.

Objective: Thermal ablation is a commonly used therapy for hepatocellular carcinoma (HCC). Nevertheless, inadequate ablation can lead to the survival of residual HCC, potentially causing rapid progression. The underlying mechanisms for this remain unclear. This study explores the molecular mechanism responsible for the rapid progression of residual HCC. Methods: We established an animal model of inadequate ablation in BALB/c nude mice and identified a key transcriptional regulator through high-throughput sequencing. Subsequently, we conducted further investigations on RAD21. We evaluated the expression and clinical significance of RAD21 in HCC and studied its impact on HCC cell function through various assays, including CCK-8, wound healing, Transwell migration and invasion. In vitro experiments established an incomplete ablation model verifying RAD21 expression and function. Using ChIP-seq, we determined potential molecules regulated by RAD21 and investigated how RAD21 influences residual tumor development. Results: High RAD21 expression in HCC was confirmed and correlated with low tumor cell differentiation, tumor growth, and portal vein thrombosis. Silencing RAD21 inhibited the migration, invasion, and proliferation significantly in liver cancer cells. Patients with high RAD21 levels showed elevated multiple inhibitory immune checkpoint levels and a lower response rate to immune drugs. Heat treatment intensified the malignant behavior of liver cancer cells, resulting in increased migration, invasion, and proliferation. After subjecting it to heat treatment, the results indicated elevated RAD21 levels in HCC. Differentially expressed molecules regulated by RAD21 following incomplete ablation were primarily associated with the VEGF signaling pathway, focal adhesion, angiogenesis, and hepatocyte growth factor receptor signaling pathway etc. Conclusion: The upregulation of RAD21 expression after incomplete ablation may play a crucial role in the rapid development of residual tumors and could serve as a novel therapeutic target.

Performance of current versus modified CEUS LI-RADS in the diagnosis of non-hepatocellular carcinoma malignancies.

PURPOSE: The high proportion of HCC in CEUS LR-M decreases the sensitivity of LR-5 for the diagnosis of HCC. However, when modifying LR-M criteria to further improve the sensitivity of LR-5, it is also important not to compromise the diagnostic performance (especially sensitivity) of LR-M for non-hepatocellular carcinoma malignancies (non-HCCMs). The purpose of this study was to evaluate the diagnostic performance of CEUS LI-RADS (2017 version) for non-HCCMs and to explore the impact of modified CEUS LI-RADS on the diagnostic performance of LR-M. METHODS: In this retrospective study, patients with pathologically confirmed non-HCCMs were evaluated. Two radiologists independently interpreted the major CEUS features and categorized the liver lesions. New LR-M criteria were applied: early washout (< 45 s) or marked washout (< 5 min). The sensitivity values of the current and modified CEUS LR-M were assessed and then compared using a paired χ2 test. Cohen's κ was used to compare the inter-reader agreement of the LI-RADS categories. RESULTS: A total of 131 non-HCCMs were ultimately selected, including 71 intrahepatic cholangiocarcinomas, 26 combined hepatocellular cholangiocarcinomas, 29 metastases, and 5 other non-HCCMs. The numbers of LR-M, LR-5, LR-4, and LR-3 in liver lesions were 111, 18, 1, and 1, respectively. The inter-reader agreement of the LI-RADS categories for non-HCCMs was 0.59. The sensitivity of the current CEUS LR-M in diagnosing non-HCCMs was 84.7%. By adjusting the early washout time to < 45 s, the sensitivity of LR-M was 80.9%. By adjusting the marked washout time within 5 min, the sensitivity of LR-M was 72.5%. CONCLUSION: CEUS LR-M has high sensitivity in diagnosing non-HCCMs. For LR-M nodules with nonrim arterial phase hyperenhancement and early washout, advancing the time of early washout to < 45 s has a minimal impact on the sensitivity of LR-M in diagnosing non-HCCMs compared to the condition of increasing the marked washout within 5 min.

Downregulation of MicroRNA-1 and Its Potential Molecular Mechanism in Nasopharyngeal Cancer: An Investigation Combined with In Silico and In-House Immunohistochemistry Validation.

BACKGROUND: This study was aimed at elucidating the molecular biological mechanisms of microRNA-1 (miR-1) in nasopharyngeal carcinoma (NPC). METHOD: In this study, we performed a pooled analysis of miR-1 expression data derived from public databases, such as GEO, ArrayExpress, TCGA, and GTEx. The miRWalk 2.0 database, combined with the mRNA microarray datasets, was used to screen the target genes, and the genes were then subjected to Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analysis using the DAVID 6.8 database. We then used the STRING 11.0 database and Cytoscape 3.80 software to construct a protein-protein interaction (PPI) network for screening hub genes. Immunohistochemistry (IHC) was further used to validate the expression of hub genes. Finally, potential therapeutic agents for NPC were screened by the Connectivity Map (cMap) database. RESULTS: Pooled analysis showed that miR-1 expression was significantly decreased in NPC (SMD = -0.57; P < 0.05). The summary receiver operating characteristic curve suggested that miR-1 had a good ability to distinguish cancerous tissues from noncancerous tissues (AUC = 0.78). The results of GO analysis focused on mitotic nuclear division, DNA replication, cell division, cell adhesion, extracellular space, kinesin complex, and extracellular matrix (ECM) structural constituent. The KEGG analysis suggested that the target genes played a role in key signaling pathways, such as cell cycle, focal adhesion, cytokine-cytokine receptor interaction, ECM-receptor interaction, and PI3K/Akt signaling pathway. The PPI network suggested that cyclin-dependent kinase 1 (CDK1) was the hub gene, and the CDK1 protein was subsequently confirmed to be significantly upregulated in NPC tissues by IHC. Finally, potential therapeutic drugs, such as masitinib, were obtained by the cMap database. CONCLUSION: miR-1 may play a vital part in NPC tumorigenesis and progression by regulating focal adhesion kinase to participate in cell mitosis, regulating ECM degradation, and affecting the PI3K/Akt signaling pathway. miR-1 has the potential to be a therapeutic target for NPC.

Expression, prognosis value, and immune infiltration of lncRNA ASB16-AS1 identified by pan-cancer analysis.

Long non-coding RNA known as ASB16 antisense RNA1 (ASB16-AS1) has been proven to be an oncogene, and the relationship between ASB16-AS1 and immunity is still under studied. This study aims to explore the expression and prognostic potential of ASB16-AS1, and to visualize the relationship between ASB16-AS1 expression and immune infiltration in pan-cancer analysis. We clarified ASB16-AS1 expression patterns and its relationship with prognosis through multi-platform and multi-database sources. We also verified the function of ASB16-AS1 in liver hepatocellular carcinoma (LIHC). A  variety of immune cell content evaluation methods were used to mutually verify the correlation between ASB16-AS1 and immune infiltration. Finally, the relationships between ASB16-AS1 and molecular characteristics were further explored. In terms of comprehensive analysis, compared with non-tumor tissues, ASB16-AS1 was highly expressed in tumor tissues, and indicated the value of poor prognosis in multiple cancer types. Functional assays, such as counting kit-8 assay, transwell assay and scratch-wound assay verified that high ASB16-AS1 expression promoted tumor progression in LIHC. ASB16-AS1 was positively correlated with B cells, T cells CD4+ and T cells CD8+ in most cancer types, and negatively correlated with macrophages, dendritic cells and neutrophils in some cancer types. In addition, there were different interaction modes between ASB16-AS1 and molecular features, such as the relationship with oncogenic signaling pathways, showing that the high ASB16-AS1 expression was related to alterations in oncogenic signaling pathways. Our study emphasizes that ASB16-AS1 is a potential pan-cancer prognostic marker, whichs is associated with the immune infiltration in multiple cancer types.

Increased infiltration of CD8 T cells in recurrent glioblastoma patients is a useful biomarker for assessing the response to combined bevacizumab and lomustine therapy.

PURPOSE: Treatment options for recurrent glioblastoma (rGBM) remain scarce, which may be due to the limited understanding of its molecular characteristics. METHODS: Based on gene expression profiling, the infiltration scores of 26 immune cell types were calculated using gene set variation analysis. The differences between rGBM and other cancer subtypes were estimated to characterize the specific immune characteristics of rGBM, and the prognostic value of immune cells in rGBM was estimated using univariate and multivariate Cox analysis. Subgroup analyses and Kaplan-Meier analyses were performed to identify whether CD8 T-cell infiltration could be useful in selecting treatment options for rGBM patients. RESULTS: We found that rGBM patients were associated with enrichment of activated CD8 T cells, and high CD8 T-cell infiltration was associated with superior overall survival. Patients exhibiting high CD8 T-cell infiltration who received treatment with bevacizumab and lomustine combination therapy experienced a significant benefit in overall survival and progression-free survival, whereas patients with low CD8 T-cell infiltration did not experience such a benefit. CD8 T cells remained an independent prognostic factor in multivariate analyses (cohort 1: hazard ratio [HR] = 0.546, 95% confidence interval [CI]: 0.316-0.945, P = 0.031; cohort 3: HR = 0.615, 95% CI: 0.387-0.978, P = 0.040) after adjusting for clinicopathological and molecular factors. CONCLUSIONS: Activated CD8 T-cells is a promising biomarker for predicting overall survival in rGBM patients and could be used for assisting treatment selection.

Integrated multi-omics analysis of the clinical relevance and potential regulatory mechanisms of splicing factors in hepatocellular carcinoma.

Splicing factors (SFs) have been increasingly documented to perturb the genome of cancers. However, little is known about the alterations of SFs in hepatocellular carcinoma (HCC). This study comprehensively delineated the genomic and epigenomic characteristics of 404 SFs in HCC based on the multi-omics data from the Cancer Genome Atlas database. The analysis revealed several clinically relevant SFs that could be effective biomarkers for monitoring the onset and prognosis of HCC (such as, HSPB1, DDX39A, and NELFE, which were the three most significant clinically relevant SFs). Functional enrichment analysis of these indicators showed the enrichment of pathways related to splicing and mRNA processes. Furthermore, the study found that SF copy number variation is common in HCC and could be a typical characteristic of hepato-carcinogenesis; the complex expression regulation of SFs was significantly affected by copy number variant and methylation. Several SFs with significant mutation patterns were identified (such as, RNF213, SF3B1, SPEN, NOVA1, and EEF1A1), and the potential regulatory network of SFs was constructed to identify their potential mechanisms for regulating clinically relevant alternative splicing events. Therefore, this study established a foundation to uncover the broad molecular spectrum of SFs for future functional and therapeutic studies of HCC.

A Comprehensive Evaluation of miR-144-3p Expression and Its Targets in Laryngeal Squamous Cell Carcinoma.

Laryngeal squamous cell carcinoma (LSCC) is an aggressive type of head and neck squamous cell carcinoma (HNSCC) with a relatively high rate of morbidity and mortality. An altered miR-144-3p level in LSCC with a small number of patients has been previously reported. However, the clinical implication of miR-144-3p and its involved mechanism underlying this disease is not clearly elucidated. In this work, we aimed to confirm the expression of miR-144-3p with larger samples and also to identify target genes for the investigation of the underlying mechanism of miR-144-3p in LSCC. The levels of miR-144-3p were downregulated in 155 samples of LSCC tissues as compared to 26 non-LSCC samples (SMD: -0.78; 95% confidence interval (CI): -1.23, -0.32). The AUC of 0.90 in the summarized ROC curve also indicated a potential ability to differentiate LSCC from non-LSCC tissues, with a sensitivity of 0.78 and a specificity of 0.88. With respect to the molecular mechanism, we predicted the potential targets from online-based prediction, peer-reviewed publications, and RNA-seq and microarray data. In particular, the genes influenced by transfection with miR-144-3p in the LSCC FaDu cell line were collected from the microarray GSE56243. Lastly, 12 novel targets for miR-144-3p in LSCC were obtained by different algorithms. In conclusion, our study confirmed the loss or downregulation of miR-144-3p in LSCC, which might contribute to the LSCC tumorigenesis and progression via regulation of the 12 novel targets, such as IL24, ITGA6, and CEP55. In the future, further investigations are required to validate the present results.

Down-Regulation of Activating Transcription Factor 3 (ATF3) in Hepatoblastoma and Its Relationship with Ferroptosis.

PURPOSE: The molecular mechanisms and signal pathways of ferroptosis in hepatoblastoma (HB) have not yet been clarified. In previous studies, activating transcription factor 3 (ATF3) was reported to be correlated with several tumors, but the clinical significance of ATF3 has never been determined. Herein, we investigated the clinicopathological value and mechanisms of ATF3 in regulating ferroptosis in HB. METHODS: The mRNA microarray and RNA-sequencing data of 402 samples from our hospital and public databases were used to estimate ATF3 expression and assess its clinical role in HB. The standard mean difference (SMD) and summary receiver operating characteristic curves were utilized to judge the discrimination ability of ATF3 between HB and non-HB liver tissues. We examined the expression variation of ATF3 in HB cells after the treatment with erastin. We also predicted the target genes of ATF3 as a transcriptional factor from public Chromatin Immunoprecipitation-sequencing data and selected the ferroptosis-related genes for a signaling pathway analysis. RESULTS: In ten series, the pooled SMD for ATF3 was -0.91, demonstrating that ATF3 expression was predominantly lower in HB than in non-HB liver tissues. ATF3 down-regulation showed moderate potential to distinguish HB from non-HB liver tissues (area under curves = 0.83, 95% confidence interval = 0.79-0.86). Altogether, 4855 putative targets of ATF3 as a transcriptional factor were collected, among which, 60 genes were ferroptosis-related. CONCLUSION: The down-regulated ATF3 expression may play a vital role in the occurrence of HB possible partially by regulating ferroptosis.

Incomplete thermal ablation-induced up-regulation of transcription factor nuclear receptor subfamily 2, group F, member 6 (NR2F6) contributes to the rapid progression of residual liver tumor in hepatoblastoma.

Hepatoblastoma is a kind of extreme malignancy frequently diagnosed in children. Although surgical resection is considered as the first-line treatment for hepatoblastoma, a relatively large population of patients have lost the preferred opportunity for surgery. Administration of locoregional ablation enables local tumor control but with the deficiency of insufficient ablation, residual tumor, and rapid progression. In this study, we integrated 219 hepatoblastoma and 121 non-cancer liver tissues to evaluate the expression of NR2F6, from which a higher NR2F6 level was found in hepatoblastoma compared with non-cancer livers with a standard mean difference (SMD) of 1.04 (95% CI: 0.79, 1.29). The overexpression of NR2F6 also appeared to be an efficient indicator in distinguishing hepatoblastoma tissues from non-cancer liver tissues from the indication of a summarized AUC of 0.90, with a pooled sensitivity of 0.76 and a pooled specificity of 0.89. Interestingly, nude mouse xenografts provided direct evidence that overexpressed NR2F6 was also detected in residual tumor compared to untreated hepatoblastoma. Chromatin immunoprecipitation-binding data in HepG2 cells and transcriptome analysis of HepG2 xenografts were combined to identify target genes regulated by NR2F6. We finally selected 150 novel target genes of NR2F6 in residual tumor of incomplete ablation, and these genes appeared to be associated with the biological regulation of lipid metabolism-related pathway. Accordingly, targeting NR2F6 holds a therapeutic promise in treating residual recurrent hepatoblastoma after incomplete ablation.

A novel alternative splicing-based prediction model for uteri corpus endometrial carcinoma.

Alternative splicing (AS) is crucial a mechanism by which the complexity of mammalian and viral proteom increased overwhelmingly. There lacks systematic and comprehensive analysis of the prognostic significance of AS profiling landscape for uteri corpus endometrial carcinoma (UCEC). In this study, univariate and multivariate Cox regression analyses were conducted to identify candidate survival-associated AS events curated from SpliceSeq for the construction of prognostic index (PI) models. A correlation network between splicing factor-related AS events and significant survival-associated AS events were constructed using Cytoscape 3.5. As consequence, 28281 AS events from 8137 genes were detected from 506 UCEC patients, including 2630 survival-associated AS events. Kaplan Meier survival analysis revealed that six of the seven PI models (AD, AP, AT, ME, RI and ALL) exhibited good performance in stratifying the prognosis of low risk and high risk group (P<0.05). Among the six PI models, PI-AT performed best with an area under curves (AUC) value of 0.758 from time-dependent receiver operating characteristic. Correlation network implicated potential regulatory mechanism of AS events in UCEC. PI models based on survival-associated AS events for UCEC in this study showed preferable prognosis-predicting ability and may be promising prognostic indicators for UCEC patients.Summary: This is the first study to systematically investigate the prognostic value of AS in UCEC. Findings in the presents study supported the clinical potential of AS for UCEC and shed light on the potential AS-associated molecular basis of UCEC.

The clinical significance of CHEK1 in breast cancer: a high-throughput data analysis and immunohistochemical study.

Breast cancer (BC) is a kind of malignant cancer that seriously threatens women's health. Research scientists have found that BC occurs as the result of multiple effects of the external environment and internal genetic changes. Cell cycle checkpoint kinase 1 (CHEK1) is a crucial speed limit point in the cell cycle. Alterations of CHEK1 have been found in various tumors but are rarely reported or verified in BC. By mining database information, a large amount of mRNA and protein data was collected and meta-analyzed. Also, in-house immunohistochemistry was carried out to validate the results of the CHEK1 expression levels. Relative clinical features of BC patients were calculated with the CHEK1 expression levels to determine their diagnostic value. The mRNA levels of CHEK1 were higher in 1,089 cases of BC tissues than in 291 cases of non-BC tissues. We observed that the mRNA levels of CHEK1 are related to the clinical stages of BC patients (P = 0.008) and are also significant for overall survival (HR = 1.6, P = 0.0081). Using the immunohistochemistry method, we calculated and confirmed, using Fisher's exact test (P < 0.001), that a high-level CHEK1 protein is exhibited in BC tissues. Overexpressed CHEK1 mRNA promotes the occurrence of BC. Also, up-regulated CHEK1 could serve as an independent risk biomarker in BC patients' prognoses.

The underlying molecular mechanism and potential drugs for treatment in papillary renal cell carcinoma: A study based on TCGA and Cmap datasets.

Papillary renal cell carcinoma (PRCC) accounts for 15­20% of all kidney neoplasms and continually attracts attention due to the increase in the incidents in which it occurs. The molecular mechanism of PRCC remains unclear and the efficacy of drugs that treat PRCC lacks sufficient evidence in clinical trials. Therefore, it is necessary to investigate the underlying mechanism in the development of PRCC and identify additional potential anti­PRCC drugs for its treatment. The differently expressed genes (DEGs) of PRCC were identified, followed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses for functional annotation. Then, potential drugs for PRCC treatment were predicted by Connectivity Map (Cmap) based on DEGs. Furthermore, the latent function of query drugs in PRCC was explored by integrating drug­target, drug­pathway and drug­protein interactions. In total, 627 genes were screened as DEGs, and these DEGs were annotated using KEGG pathway analyses and were clearly associated with the complement and coagulation cascades, amongst others. Then, 60 candidate drugs, as predicted based on DEGs, were obtained from the Cmap database. Vorinostat was considered as the most promising drug for detailed discussion. Following protein­protein interaction (PPI) analysis and molecular docking, vorinostat was observed to interact with C3 and ANXN1 proteins, which are the upregulated hub genes and may serve as oncologic therapeutic targets in PRCC. Among the top 20 metabolic pathways, several significant pathways, such as complement and coagulation cascades and cell adhesion molecules, may greatly contribute to the development and progression of PRCC. Following the performance of the PPI network and molecular docking tests, vorinostat exhibited a considerable and promising application in PRCC treatment by targeting C3 and ANXN1.

Identification of putative drugs for gastric adenocarcinoma utilizing differentially expressed genes and connectivity map.

Gastric adenocarcinoma (GAC) is a challenging disease with dim prognosis even after surgery; hence, novel treatments for GAC are in urgent need. The aim of the present study was to explore new potential compounds interfering with the key pathways related to GAC progression. The differentially expressed genes (DEGs) between GAC and adjacent tissues were identified from The Cancer Genome Atlas (TCGA) and Genotype­Tissue Expression (GTEx) database. Connectivity Map (CMap) was performed to screen candidate compounds for treating GAC. Subsequently, pathways affected by compounds were overlapped with those enriched by the DEGs to further identify compounds which had anti­GAC potential. A total of 843 DEGs of GAC were identified. Via Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, 13 pathways were significantly enriched. Moreover, 78 compounds with markedly negative correlations with DEGs were revealed in CMap database (P<0.05 and Enrichment <0). Subpathways of cell cycle and p53 signaling pathways, and core genes of these compounds, cyclin B1 (CCNB1) and CDC6, were identified. This study further revealed seven compounds that may be effective against GAC; in particular methylbenzethonium chloride and alexidine have never yet been reported for GAC treatment. In brief, the candidate drugs identified in this study may provide new options to improve the treatment of patients with GAC. However, the biological effects of these drugs need further investigation.