Development and validation of a Radiopathomics model based on CT scans and whole slide images for discriminating between Stage I-II and Stage III gastric cancer.

OBJECTIVE: This study aimed to develop and validate an artificial intelligence radiopathological model using preoperative CT scans and postoperative hematoxylin and eosin (HE) stained slides to predict the pathological staging of gastric cancer (stage I-II and stage III). METHODS: This study included a total of 202 gastric cancer patients with confirmed pathological staging (training cohort: n = 141; validation cohort: n = 61). Pathological histological features were extracted from HE slides, and pathological models were constructed using logistic regression (LR), support vector machine (SVM), and NaiveBayes. The optimal pathological model was selected through receiver operating characteristic (ROC) curve analysis. Machine learnin algorithms were employed to construct radiomic models and radiopathological models using the optimal pathological model. Model performance was evaluated using ROC curve analysis, and clinical utility was estimated using decision curve analysis (DCA). RESULTS: A total of 311 pathological histological features were extracted from the HE images, including 101 Term Frequency-Inverse Document Frequency (TF-IDF) features and 210 deep learning features. A pathological model was constructed using 19 selected pathological features through dimension reduction, with the SVM model demonstrating superior predictive performance (AUC, training cohort: 0.949; validation cohort: 0.777). Radiomic features were constructed using 6 selected features from 1834 radiomic features extracted from CT scans via SVM machine algorithm. Simultaneously, a radiopathomics model was built using 17 non-zero coefficient features obtained through dimension reduction from a total of 2145 features (combining both radiomics and pathomics features). The best discriminative ability was observed in the SVM_radiopathomics model (AUC, training cohort: 0.953; validation cohort: 0.851), and clinical decision curve analysis (DCA) demonstrated excellent clinical utility. CONCLUSION: The radiopathomics model, combining pathological and radiomic features, exhibited superior performance in distinguishing between stage I-II and stage III gastric cancer. This study is based on the prediction of pathological staging using pathological tissue slides from surgical specimens after gastric cancer curative surgery and preoperative CT images, highlighting the feasibility of conducting research on pathological staging using pathological slides and CT images.

Identify GADD45G as a potential target of 4-methoxydalbergione in treatment of liver cancer: bioinformatics analysis and in vivo experiment.

BACKGROUND: The growth arrest and DNA damage-inducible gene gamma (GADD45G), an important member of GADD45 family, has been connected to the development of certain human cancers. Our previous studies have confirmed that GADD45G expression could be upregulated by 4-methoxydalbergione (4MOD) in liver cancer cells, but its potential pathological role in hepatocellular carcinoma (HCC) has not been fully understood. This study aimed to determine potential role of GADD45G in HCC, and the effects of 4-methoxydalbergione (4MOD) on the regulation of GADD45G expression in vivo were also analyzed. METHODS: Publicly available data and in-house immunohistochemistry (IHC) experiments were utilized to explore the expression profiles and clinical significance of GADD45G in HCC samples. Functional enrichment analysis based on GADD45G co-expression genes was used to excavate the molecular mechanism of GADD45G in HCC. We also conducted in vivo experiment on BALB/c nude mice to excavate the inhibitory effect of 4MOD on HCC and to evaluate the differences in the expression of GADD45G in xenograft tissues between the 4MOD-treated and untreated groups. RESULTS: GADD45G displayed significant low expression in HCC tissues. Downregulated expression of GADD45G was positively correlated with some high risk factors in HCC patients and predicted worse prognosis of HCC patients. There was a close association of GADD45G mRNA expression and immune cells, including neutrophils, NK cells, CD8 T cells, and macrophages. Co-expressed genes of GADD45G were involved in several pathways including cell cycle, carbon metabolism, and peroxisome. 4MOD could significantly suppress the growth of HCC in vivo, and this inhibitory effect was dependent on the upregulation of GADD45G expression. CONCLUSION: GADD45G expression can be used as a new clinical biomarker for HCC and GADD45G may be a potential target for the anti-cancer effect of 4MOD in liver cancer.

Expression Landscape and Functional Roles of HOXA4 and HOXA5 in Lung Adenocarcinoma.

BACKGROUND: The role of HOXA family genes in the occurrence and progression of a variety of human cancers has been scatteredly reported. However, there is no systematic study on the differential expression, prognostic significance and potential molecular mechanism of HOXA4 and HOXA5 in LUAD. METHODS: In-house immunohistochemistry (IHC), multi-center microarrays, RT-qPCR and RNA-seq data were incorporated for comprehensively evaluating the expression and prognostic value of HOXA4 and HOXA5 in LUAD. The mechanism of HOXA4 and HOXA5 in the formation and development of LUAD was analyzed from multiple aspects of immune correlations, upstream transcriptional regulation, functional states of single cells and co-expressed gene network. The functional roles of HOXA4 and HOXA5 in LUAD were validated by in vitro experiments. RESULTS: As a result, in 3201 LUAD samples and 2494 non-cancer lung samples, HOXA4 and HOXA5 were significantly downexpressed (P < 0.05). The aberrant expression of HOXA5 was significantly correlated with the clinical progression of LUAD (P < 0.05). HOXA5 showed remarkable prognostic value for LUAD patients (P < 0.05). The expression of HOXA4 and HOXA5 in LUAD were negatively correlated with tumor purity and positively correlated with the infiltration of various immune cells such as B cells, T cells and macrophages. HOXA4 and HOXA5 overexpression had notable inhibitory effect on the proliferation, migration and invasion of LUAD cells. CONCLUSIONS: In conclusion, the identified downexpressed HOXA4 and HOXA5 had significant distinguishing ability for LUAD samples and affected the cellular functions of LUAD cells. The low expression of HOXA5 indicated worse overall survival of LUAD patients. Therefore, the two HOXA family genes especially HOXA5 may serve as potential biomarkers for LUAD.

Downregulation of zinc finger protein 71 in laryngeal squamous cell carcinoma tissues and its potential molecular mechanism and clinical significance: a study based on immunohistochemistry staining and data mining.

BACKGROUND: The molecular mechanism of laryngeal squamous cell carcinoma (LSCC) is not completely clear, which leads to poor prognosis and treatment difficulties for LSCC patients. To date, no study has reported the exact expression level of zinc finger protein 71 (ZNF71) and its molecular mechanism in LSCC. METHODS: In-house immunohistochemistry (IHC) staining (33 LSCC samples and 29 non-LSCC samples) was utilized in analyzing the protein expression level of ZNF71 in LSCC. Gene chips and high-throughput sequencing data collected from multiple public resources (313 LSCC samples and 192 non-LSCC samples) were utilized in analyzing the exact mRNA expression level of ZNF71 in LSCC. Single-cell RNA sequencing (scRNA-seq) data was used to explore the expression status of ZNF71 in different LSCC subpopulations. Enrichment analysis of ZNF71, its positively and differentially co-expressed genes (PDCEGs), and its downstream target genes was employed to detect the potential molecular mechanism of ZNF71 in LSCC. Moreover, we conducted correlation analysis between ZNF71 expression and immune infiltration. RESULTS: ZNF71 was downregulated at the protein level (area under the curve [AUC] = 0.93, p < 0.0001) and the mRNA level (AUC = 0.71, p = 0.023) in LSCC tissues. Patients with nodal metastasis had lower protein expression level of ZNF71 than patients without nodal metastasis (p < 0.05), and male LSCC patients had lower mRNA expression level of ZNF71 than female LSCC patients (p < 0.01). ZNF71 was absent in different LSCC subpopulations, including cancer cells, plasma cells, and tumor-infiltrated immune cells, based on scRNA-seq analysis. Enrichment analysis showed that ZNF71 and its PDCEGs may influence the progression of LSCC by regulating downstream target genes of ZNF71. These downstream target genes of ZNF71 were mainly enriched in tight junctions. Moreover, downregulation of ZNF71 may influence the development and even therapy of LSCC by reducing immune infiltration. CONCLUSION: Downregulation of ZNF71 may promote the progression of LSCC by reducing tight junctions and immune infiltration; this requires further study.

Clinical value and potential mechanisms of COL8A1 upregulation in breast cancer: a comprehensive analysis.

BACKGROUND: The situation faced by breast cancer patients, especially those with triple-negative breast cancer, is still grave. More effective therapeutic targets are needed to optimize the clinical management of breast cancer. Although collagen type VIII alpha 1 chain (COL8A1) has been shown to be downregulated in BRIP1-knockdown breast cancer cells, its clinical role in breast cancer remains unknown. METHODS: Gene microarrays and mRNA sequencing data were downloaded and integrated into larger matrices based on various platforms. Therefore, this is a multi-centered study, which contains 5048 breast cancer patients and 1161 controls. COL8A1 mRNA expression in breast cancer was compared between molecular subtypes. In-house immunohistochemistry staining was used to evaluate the protein expression of COL8A1 in breast cancer. A diagnostic test was performed to assess its clinical value. Furthermore, based on differentially expressed genes (DEGs) and co-expressed genes (CEGs) positively related to COL8A1, functional enrichment analyses were performed to explore the biological function and potential molecular mechanisms of COL8A1 underlying breast cancer. RESULTS: COL8A1 expression was higher in breast cancer patients than in control samples (standardized mean difference = 0.79; 95% confidence interval [CI] 0.55-1.03). Elevated expression was detected in various molecular subtypes of breast cancer. An area under a summary receiver operating characteristic curve of 0.80 (95% CI 0.76-0.83) with sensitivity of 0.77 (95% CI 0.69-0.83) and specificity of 0.70 (95% CI 0.61-0.78) showed moderate capacity of COL8A1 in distinguishing breast cancer patients from control samples. Worse overall survival was found in the higher than in the lower COL8A1 expression groups. Intersected DEGs and CEGs positively related to COL8A1 were significantly clustered in the proteoglycans in cancer and ECM-receptor interaction pathways. CONCLUSIONS: Elevated COL8A1 may promote the migration of breast cancer by mediating the ECM-receptor interaction and synergistically interplaying with DEGs and its positively related CEGs independently of molecular subtypes. Several genes clustered in the proteoglycans in cancer pathway are potential targets for developing effective agents for triple-negative breast cancer.

Downregulation of hsa-microRNA-204-5p and identification of its potential regulatory network in non-small cell lung cancer: RT-qPCR, bioinformatic- and meta-analyses.

BACKGROUND: Pulmonary malignant neoplasms have a high worldwide morbidity and mortality, so the study of these malignancies using microRNAs (miRNAs) has attracted great interest and enthusiasm. The aim of this study was to determine the clinical effect of hsa-microRNA-204-5p (miR-204-5p) and its underlying molecular mechanisms in non-small cell lung cancer (NSCLC). METHODS: Expression of miR-204-5p was investigated by real-time quantitative PCR (RT-qPCR). After data mining from public online repositories, several integrative assessment methods, including receiver operating characteristic (ROC) curves, hazard ratios (HR) with 95% confidence intervals (95% CI), and comprehensive meta-analyses, were conducted to explore the expression and clinical utility of miR-204-5p. The potential objects regulated and controlled by miR-204-5p in the course of NSCLC were identified by estimated target prediction and analysis. The regulatory network of miR-204-5p, with its target genes and transcription factors (TFs), was structured from database evidence and literature references. RESULTS: The expression of miR-204-5p was downregulated in NSCLC, and the downtrend was related to gender, histological type, vascular invasion, tumor size, clinicopathologic grade and lymph node metastasis (P<0.05). MiR-204-5p was useful in prognosis, but was deemed unsuitable at present as an auxiliary diagnostic or prognostic risk factor for NSCLC due to the lack of statistical significance in meta-analyses and absence of large-scale investigations. Gene enrichment and annotation analyses identified miR-204-5p candidate targets that took part in various genetic activities and biological functions. The predicted TFs, like MAX, MYC, and RUNX1, interfered in regulatory networks involving miR-204-5p and its predicted hub genes, though a modulatory loop or axis of the miRNA-TF-gene that was out of range with shortage in database prediction, experimental proof and literature confirmation. CONCLUSIONS: The frequently observed decrease in miR-204-5p was helpful for NSCLC diagnosis. The estimated target genes and TFs contributed to the anti-oncogene effects of miR-204-5p.

The clinical significance of endothelin receptor type B in hepatocellular carcinoma and its potential molecular mechanism.

OBJECTIVE: To explore the clinical significance and potential molecular mechanism of endothelin receptor type B (EDNRB) in hepatocellular carcinoma (HCC). METHODS: Immunohistochemistry was used to detect EDNRB protein expression level in 67 HCC paraffin embedded tissues and adjacent tissues. Correlations between EDNRB expression level and clinicopathologic parameters were analyzed in our study. The expression level and clinical significance of EDNRB in HCC were also evaluated from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. The cBioPortal for Cancer Genomics was employed to analyze the EDNRB related genes, and Gene Ontology (GO) annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and Protein-Protein Interaction (PPI) network were conducted for those EDNRB related genes. RESULTS: Lower expression level of EDNRB in HCC was verified by immunohistochemistry than adjacent tissues (P < 0.0001). The expression level of EDNRB in HCC tissues was lower than normal control liver tissues based on TCGA and GEO data (standard mean difference [SMD] = -1.48, 95% [confidence interval] CI: -1.63-(-1.33), Pheterogeneity = 0.116, I2 = 32.4%). Kaplan-Meier analysis showed that HCC patients with lower EDNRB expression were more prone to poor prognosis (P = .0041). The top terms of GO annotation in biological process, cellular component and molecular function were vasculature development, actin filament and transmembrane receptor protein kinase activity, respectively. The KEGG pathway enrichment analysis confirmed that EDNRB related genes mainly participated in Vascular smooth muscle contraction, cGMP-PKG signaling pathway and Focal adhesion pathways. The result of PPI network construction showed that KDR, VEGFC, FLT1, CDH5 and ADCY4 were possible to become the core genes of EDNRB related genes, which need further experiments to confirm. CONCLUSION: Our study provides novel findings and insights on the molecular pathogenesis of HCC from EDNRB view.

Biological Effect and Mechanism of the miR-23b-3p/ANXA2 Axis in Pancreatic Ductal Adenocarcinoma.

BACKGROUND/AIMS: Accumulating evidence strongly suggests that microRNAs (miRNAs) modulate the expression of known tumor suppressor genes and oncogenes. In the present study, we found that the proliferation and invasion ability of pancreatic ductal adenocarcinoma (PDAC) cells were significantly suppressed by the overexpression of miR-23b-3p. In addition, there are miR-23b-3p binding sites in annexin A2 (ANXA2). Here, we investigated whether miR-23b-3p had an impact on the progression and metastasis of PDAC by targeting ANXA2. METHODS: Cell proliferation, migration, and invasion, and cell cycle assays were performed to explore the effect of miR-23b-3p on various malignant phenotypes of pancreatic cancer cells. The size of tumors was observed following miR-23b-3p overexpression in an in vivo chick chorioallantoic membrane assay. Dual-luciferase reporter, quantitative real-time PCR, western blot, and immunohistochemical analyses were used to validate the relationship between miR-23b-3p and ANXA2 in vitro. RESULTS: We observed that miR-23b-3p could bind specifically to the 3' untranslated region of ANXA2 and inhibit its expression. MiR-23b-3p overexpression downregulated the expression of ANXA2 mRNA in PDAC cells and limited the size of tumors or even prevented tumor formation. In addition, there was a negative correlation between miR-23b-3p expression and ANXA2 protein expression in clinical specimens. CONCLUSION: MiR-23b-3p inhibits the development and progression of PDAC by regulating ANXA2 directly.

A circRNA-miRNA-mRNA network identification for exploring underlying pathogenesis and therapy strategy of hepatocellular carcinoma.

BACKGROUND: Circular RNAs (circRNAs) have received increasing attention in human tumor research. However, there are still a large number of unknown circRNAs that need to be deciphered. The aim of this study is to unearth novel circRNAs as well as their action mechanisms in hepatocellular carcinoma (HCC). METHODS: A combinative strategy of big data mining, reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and computational biology was employed to dig HCC-related circRNAs and to explore their potential action mechanisms. A connectivity map (CMap) analysis was conducted to identify potential therapeutic agents for HCC. RESULTS: Six differently expressed circRNAs were obtained from three Gene Expression Omnibus microarray datasets (GSE78520, GSE94508 and GSE97332) using the RobustRankAggreg method. Following the RT-qPCR corroboration, three circRNAs (hsa_circRNA_102166, hsa_circRNA_100291 and hsa_circRNA_104515) were selected for further analysis. miRNA response elements of the three circRNAs were predicted. Five circRNA-miRNA interactions including two circRNAs (hsa_circRNA_104515 and hsa_circRNA_100291) and five miRNAs (hsa-miR-1303, hsa-miR-142-5p, hsa-miR-877-5p, hsa-miR-583 and hsa-miR-1276) were identified. Then, 1424 target genes of the above five miRNAs and 3278 differently expressed genes (DEGs) on HCC were collected. By intersecting the miRNA target genes and the DEGs, we acquired 172 overlapped genes. A protein-protein interaction network based on the 172 genes was established, with seven hubgenes (JUN, MYCN, AR, ESR1, FOXO1, IGF1 and CD34) determined from the network. The Gene Oncology, Kyoto Encyclopedia of Genes and Genomes and Reactome enrichment analyses revealed that the seven hubgenes were linked with some cancer-related biological functions and pathways. Additionally, three bioactive chemicals (decitabine, BW-B70C and gefitinib) based on the seven hubgenes were identified as therapeutic options for HCC by the CMap analysis. CONCLUSIONS: Our study provides a novel insight into the pathogenesis and therapy of HCC from the circRNA-miRNA-mRNA network view.

Analysis of microarrays of miR-34a and its identification of prospective target gene signature in hepatocellular carcinoma.

BACKGROUND: Currently, some studies have demonstrated that miR-34a could serve as a suppressor of several cancers including hepatocellular carcinoma (HCC). Previously, we discovered that miR-34a was downregulated in HCC and involved in the tumorigenesis and progression of HCC; however, the mechanism remains unclear. The purpose of this study was to estimate the expression of miR-34a in HCC by applying the microarray profiles and analyzing the predicted targets of miR-34a and their related biological pathways of HCC. METHODS: Gene expression omnibus (GEO) datasets were conducted to identify the difference of miR-34a expression between HCC and corresponding normal tissues and to explore its relationship with HCC clinicopathologic features. The natural language processing (NLP), gene ontology (GO), pathway and network analyses were performed to analyze the genes associated with the carcinogenesis and progression of HCC and the targets of miR-34a predicted in silico. In addition, the integrative analysis was performed to explore the targets of miR-34a which were also relevant to HCC. RESULTS: The analysis of GEO datasets demonstrated that miR-34a was downregulated in HCC tissues, and no heterogeneity was observed (Std. Mean Difference(SMD) = 0.63, 95% confidence intervals(95%CI):[0.38, 0.88], P < 0.00001; Pheterogeneity = 0.08 I2 = 41%). However, no association was found between the expression value of miR-34a and any clinicopathologic characteristics. In the NLP analysis of HCC, we obtained 25 significant HCC-associated signaling pathways. Besides, we explored 1000 miR-34a-related genes and 5 significant signaling pathways in which CCND1 and Bcl-2 served as necessary hub genes. In the integrative analysis, we found 61 hub genes and 5 significant pathways, including cell cycle, cytokine-cytokine receptor interaction, notching pathway, p53 pathway and focal adhesion, which proposed the relevant functions of miR-34a in HCC. CONCLUSION: Our results may lead researchers to understand the molecular mechanism of miR-34a in the diagnosis, prognosis and therapy of HCC. Therefore, the interaction between miR-34a and its targets may promise better prediction and treatment for HCC. And the experiments in vivo and vitro will be conducted by our group to identify the specific mechanism of miR-34a in the progress and deterioration of HCC.

Evaluation of the HOXA11 level in patients with lung squamous cancer and insights into potential molecular pathways via bioinformatics analysis.

BACKGROUND: This study was carried out to discover the underlying role that HOXA11 plays in lung squamous cancer (LUSC) and uncover the potential corresponding molecular mechanisms and functions of HOXA11-related genes. METHODS: Twenty-three clinical paired LUSC and non-LUSC samples were utilized to examine the level of HOXA11 using quantitative real-time polymerase chain reaction (qRT-PCR). The clinical significance of HOXA11 was systematically analyzed based on 475 LUSC and 18 non-cancerous adjacent tissues from The Cancer Genome Atlas (TCGA) database. A total of 102 LUSC tissues and 121 non-cancerous tissues were available from Oncomine to explore the expressing profiles of HOXA11 in LUSC. A meta-analysis was carried out to further assess the differential expression of HOXA11 in LUSC, including in-house qRT-PCR data, expressing data extracted from TCGA and Oncomine databases. Moreover, the enrichment analysis and potential pathway annotations of HOXA11 in LUSC were accomplished via Gene Oncology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The expression of hub genes and according correlations with HOXA11 were assessed to further explore the biological role of HOXA11 in LUSC. RESULTS: HOXA11 expression in LUSC had a tendency to be upregulated in comparison to adjacent non-cancerous tissues by qRT-PCR. TCGA data displayed that HOXA11 was remarkably over-expressed in LUSC compared with that in non-LUSC samples, and the area under curves (AUC) was 0.955 (P < 0.001). A total of 1523 co-expressed genes were sifted for further analysis. The most significant term enriched in the KEGG pathway was focal adhesion. Among the six hub genes of HOXA11, including PARVA, ILK, COL4A1, COL4A2, ITGB1, and ITGA5, five (with the exception of COL4A1) were significantly decreased compared with the normal lung tissues. Moreover, the expression of ILK was negatively related to HOXA11 (r = - 0.141, P = 0.002). CONCLUSION: High HOXA11 expression may lead to carcinogenesis and the development of LUSC. Furthermore, co-expressed genes might affect the prognosis of LUSC.

Potential Targets and Clinical Value of MiR-224-5p in Cancers of the Digestive Tract.

BACKGROUND/AIMS: MicroRNAs participate in various biological processes in malignant tumors. However, the mechanisms of miR-224-5p in digestive system cancers are not fully understood. A comprehensive investigation of the clinical value and potential targets of miR-224-5p in cancers of the digestive tract is necessary. METHODS: Expression profiling data and related-prognostic data of miR-224-5p were acquired from Gene Expression Omnibus, The Cancer Genome Atlas, ArrayExpress, and published literature. The potential target mRNAs of miR-224-5p were predicted using bioinformatics methods and finally annotated using Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. RESULTS: MiR-224-5p is up-regulated in digestive system cancers (SMD=0.69, 95% CI: 0.43-0.96, P<0.0001) and exhibits a moderate diagnostic ability (AUC=0.84, 95% CI: 0.80-0.87). Our data also demonstrated that miR-224-5p is statistically significantly correlated with overall survival univariate analysis (HR=1.69, 95% CI: 1.15-2.49, P=0.007) and multivariate analysis (HR=2.39, 95% CI: 1.74-3.30, P<0.0001). In total, 388 potential miR-224-5p target mRNAs were predicted by bioinformatics methods. GO annotation analysis revealed that the top terms of miR-224-5p in biological process, cellular component and molecular function were system development, neuron part, and transcriptional activator activity, RNA polymerase II core promoter proximal region sequence-specific binding, respectively. Moreover, eight pathways were identified in KEGG pathway enrichment analysis. CONCLUSIONS: MiR-224-5p is up-regulated and has the potential to become a diagnostic and prognostic biomarker in digestive system cancers. MiR-224-5p might play vital roles in cancers of the digestive tract but the exact molecular mechanisms need further study and verification.

The clinicopathological significance of UBE2C in breast cancer: a study based on immunohistochemistry, microarray and RNA-sequencing data.

BACKGROUND: Ubiquitin-conjugating enzyme E2C (UBE2C) has been previously reported to correlate with the malignant progression of various human cancers, however, the exact molecular function of UBE2C in breast carcinoma (BRCA) remained elusive. We aimed to investigate UBE2C expression in BRCA and its clinical significance. METHODS: The expression of UBE2C in 209 BRCA tissue samples and 53 adjacent normal tissue samples was detected using immunohistochemistry. The clinical role of UBE2C was analyzed. Public databases including the human protein atlas and Oncomine were used to assess UBE2C expression in BRCA. Moreover, the cancer genome atlas (TCGA) database was employed to investigate the prognostic value of UBE2C in BRCA. RESULTS: The positive expression rate of UBE2C in BRCA was 70.8% (148/209), and UBE2C expression in the adjacent breast tissue was negative. The expression of UBE2C was positively correlated with tumor size (r = 0.32, P < 0.001), histological grade (r = 0.237, P = 0.001), clinical stage (r = 0.198, P = 0.004), lymph node metastasis (r = 0.155, P = 0.026), HER2 expression level (r = 0.356, P < 0.001), Ki-67 expression level (r = 0.504, P < 0.001), and P53 expression level (r = 0.32, P = 0.001). Negative correlations were found between UBE2C expression and the ER (r = - 0.403, P < 0.001) and PR (r = - 0.468, P < 0.001) status. UBE2C gene expression data from the public databases all proved that UBE2C was overexpressed in BRCA. According to the TCGA data analysis, a higher positive expression of UBE2C was associated with worse survival of BRCA patients (P = 0.0428), and data from cBioPortal indicated that 11% of all sequenced BRCA patients possessed a gene alteration of UBE2C, predominately gene amplification and mRNA regulation. CONCLUSION: Ubiquitin-conjugating enzyme E2C might pose an oncogenic effect on the progression of BRCA.

A comprehensive radiopathological nomogram for the prediction of pathological staging in gastric cancer using CT-derived and WSI-based features.

OBJECTIVE: This study aims to develop and validate an innovative radiopathomics model that combines radiomics and pathomics features to effectively differentiate between stages I-II and stage III gastric cancer (pathological staging). METHODS: Our study included 200 patients with well-defined stages of gastric cancer divided into a training cohort (n = 140) and a test cohort (n = 60). Radiomics features were extracted from contrast-enhanced CT images using PyRadiomics, while pathomics features were obtained from whole slide images of pathological specimens through a fine-tuned deep learning model (ResNet-18). After rigorous feature dimensionality reduction and selection, we constructed radiomics models (SVM_rad, LR_rad, and MLP_rad) and pathomics models (SVM_path, LR_path, and MLP_path) utilizing support vector machine (SVM), logistic regression (LR), and multilayer perceptron (MLP) algorithms. The optimal radiomics and pathomics models were chosen based on comprehensive evaluation criteria such as ROC curves, Hosmer‒Lemeshow tests, and calibration curve tests. Feature patterns extracted from the best-performing radiomics model (MLP_rad) and pathomics model (SVM_rad) were integrated to create a powerful radiopathomics nomogram. RESULTS: From a pool of 1834 radiomics features extracted from CT images, 14 were selected to construct radiomics models. Among these, the MLP_rad model exhibited the most robust predictive performance (AUC, training cohort: 0.843; test cohort: 0.797). Likewise, 10 pathomics features were chosen from 512 extracted from whole slide images to build pathomics models, with the SVM_path model demonstrating the highest predictive efficiency (AUC, training cohort: 0.937; test cohort: 0.792). The combined radiopathomics nomogram model exhibited optimal discriminative ability (AUC, training cohort: 0.951; test cohort: 0.837), as confirmed by decision curve analysis (DCA), which indicated superior clinical effectiveness. CONCLUSION: This study presents a cutting-edge radiopathomics nomogram model designed to predict pathological staging in gastric cancer, distinguishing between stages I-II and stage III. Our research leverages preoperative CT images and histopathological slides to forecast gastric cancer staging accurately, potentially facilitating the estimation of staging before radical gastric cancer surgery in the future.

Clinicopathological role of Cyclin A2 in uterine corpus endometrial carcinoma: Integration of tissue microarrays and ScRNA-Seq.

BACKGROUND: The comprehensive expression level and potential molecular role of Cyclin A2 (CCNA2) in uterine corpus endometrial carcinoma (UCEC) remains undiscovered. METHODS: UCEC and normal endometrium tissues from in-house and public databases were collected for investigating protein and messenger RNA expression of CCNA2. The transcription factors of CCNA2 were identified by the Cistrome database. The prognostic significance of CCNA2 in UCEC was evaluated through univariate and multivariate Cox regression as well as Kaplan-Meier curve analysis. Single-cell RNA-sequencing (scRNA-seq) analysis was performed to explore cell types in UCEC, and the AUCell algorithm was used to investigate the activity of CCNA2 in different cell types. RESULTS: A total of 32 in-house UCEC and 30 normal endometrial tissues as well as 720 UCEC and 165 control samples from public databases were eligible and collected. Integrated calculation showed that the CCNA2 expression was up-regulated in the UCEC tissues (SMD = 2.43, 95% confidence interval 2.23∼2.64). E2F1 and FOXM1 were identified as transcription factors due to the presence of binding peaks on transcription site of CCNA2. CCNA2 predicted worse prognosis in UCEC. However, CCNA2 was not an independent prognostic factor in UCEC. The scRNA-seq analysis disclosed five cell types: B cells, T cells, monocytes, natural killer cells, and epithelial cells in UCEC. The expression of CCNA2 was mainly located in B cells and T cells. Moreover, CCNA2 was active in T cells and B cells using the AUCell algorithm. CONCLUSION: CCNA2 was up-regulated and mainly located in T cells and B cells in UCEC. Overexpression of CCNA2 predicted unfavorable prognosis of UCEC.

4-Methoxydalbergione Elicits Anticancer Effects by Upregulation of GADD45G in Human Liver Cancer Cells.

Background: 4-Methoxydalbergione (4MOD) is a flavonoid isolated from the heartwood of Dalbergia. Studies have demonstrated that 4MOD exerts anticancer activities on bladder cancer and astrocytoma. However, the anticancer activity of 4MOD in hepatocellular carcinoma (HCC) remains unknown. This study aims to examine its anticancer activities and mechanisms in human liver cancer cells. Methods: CCK-8, colony forming, wound healing, transwell migration, and AnnexinV/PI assays were used to assess the anticancer effects of 4MOD in HCC cells. RNA sequencing (RNA-Seq) was selected to explore the possible mechanisms underlying the anti-HCC activity of 4MOD. The mRNA expression levels of target genes were verified through quantitative real-time PCR (qRT-PCR). A lentiviral shRNA interference technique was used to silence GADD45G expression. GADD45G knockdown was employed to confirm the crucial role of GADD45G in the 4MOD-mediatedanti-HCC effects. Results: 4MOD inhibited HCC cells' proliferation and migration and promoted tumor cell apoptosis. RNA-Seq and qRT-PCR analyses revealed that 4MOD treatment increased GADD45G expression. Silencing GADD45G reversed 4MOD-mediated inhibition of proliferation, migration, and promotion of apoptosis. Conclusions: Our findings show that 4MOD elicits anti-HCC effects by upregulating GADD45G expression and could be a valuable anticancer agent for liver cancer.

Clinicopathological features and prognostic significance of pulmonary adenocarcinoma with signet ring cell components: meta-analysis and SEER analysis.

Pulmonary adenocarcinoma is a common type of lung cancer that has been on the rise in recent years. Signet ring cell components (SRCC) can be present in various patterns of pulmonary adenocarcinoma, including papillary, acinar, and solid patterns. "Signet ring cell carcinoma" is a distinct subtype in the 2014 WHO classification of lung neoplasms, subsequent WHO classifications in 2015 and 2021 have deemed signet ring cells as accompanying morphological features with no clinical significance. The prognostic and clinical implications of SRCC in pulmonary adenocarcinoma remain controversial. Therefore, we conducted a meta-analysis to investigate the clinicopathological features and prognostic factors of SRCC in pulmonary adenocarcinoma. We conducted a comprehensive search in PubMed, EMBASE, and Web of Science to identify studies that examined the clinicopathological features and prognostic implications of pulmonary adenocarcinoma with SRCC. We used both fixed- and random-effects models to analyze the data and calculate the pooled hazard ratio (HR) and odds ratio (OR) with 95% confidence intervals (CIs). Additionally, we explored the prognostic significance of SRCC in pulmonary adenocarcinoma using the Surveillance, Epidemiology, and End Results (SEER) database. Our meta-analysis included 29 studies with pulmonary adenocarcinoma and SRCC components. The results showed that pulmonary adenocarcinoma with SRCC was associated with larger tumor size (OR = 1.99; 95% CI, 1.62-2.44, p < 0.001), advanced overall stage (OR = 5.18, 95% CI, 3.28-8.17, p < 0.00001) and lymph node stage (OR = 5.79, 95% CI, 1.96-17.09, p = 0.001), and worse overall survival (OS) compared to those without SRCC (HR = 1.80, 95% CI, 1.50-2.16, p < 0.00001). Analysis using the SEER dataset confirmed these findings. Our meta-analysis provides evidence that pulmonary adenocarcinoma with SRCC is associated with distinct clinicopathological features and a poorer prognosis. These findings have important implications for the management and treatment of patients. However, further studies are needed to validate these findings and explore the significance of SRCC in various subtypes of pulmonary adenocarcinoma.

Clinicopathological and prognostic significance of XPO1 in solid tumors: meta-analysis and TCGA analysis.

INTRODUCTION: Exportin 1 (XPO1) is overexpressed in several solid tumors, and is associated with poor prognosis. Here, we aimed to evaluate the implication of XPO1 expression in solid tumors through a meta-analysis. METHODS: PubMed, Web of Science, and Embase databases were searched for articles published until February 2023. Statistical data of the patients, odds ratios and hazard ratios (HRs), together with their corresponding 95% confidence intervals (CIs) were pooled to assess clinicopathological features and survival outcomes. Besides, the Cancer Genome Atlas (TCGA) was used to explore the prognostic significance of XPO1 in solid tumors. RESULTS: A total of 22 works, comprising 2595 patients were included in this study. The results suggested that increased XPO1 expression was associated with a higher tumor grade, more lymph node metastasis, advanced tumor stage, and progressively worse total clinical stage. Additionally, high XPO1 expression was associated with worse overall survival (OS) (HR = 1.43, 95% CI = 1.12-1.81, P = 0.004) and shorter progression-free survival (HR = 1.40, 95% CI = 1.07-1.84, P = 0.01). An analysis using the TCGA dataset showed that high XPO1 expression was associated with poor OS and disease-free survival. CONCLUSIONS: XPO1 is a promising prognostic biomarker and may constitute a therapeutic target for solid tumors.PROSPERO registration number: CRD42023399159.

High expression of centromere protein A and its molecular mechanism and clinical significance in prostate cancer: A study based on data mining and immunohistochemistry.

The progression of prostate cancer (PCa) leads to poor prognosis. However, the molecular mechanism of PCa is still not completely clear. This study aimed to elucidate the important role of centromere protein A (CENPA) in PCa. Large numbers of bulk RNA sequencing (RNA-seq) data and in-house immunohistochemistry data were used in analysing the expression level of CENPA in PCa and metastatic PCa (MPCa). Single-cell RNA-seq data was used to explore the expression status of CENPA in different prostate subpopulations. Enrichment analysis was employed to detect the function of CENPA in PCa. Clinicopathological parameters analysis was utilised in analysing the clinical value of CENPA. The results showed that CENPA was upregulated in PCa (standardised mean difference [SMD] = 0.83, p = 0.001) and MPCa (SMD = 0.61, p = 0.029). CENPA was overexpressed in prostate cancer stem cells (CSCs) with androgen receptor (AR) negative compared to epithelial cells with AR positive. CENPA may influence the development of PCa through affecting cell cycle. Patients with nodal metastasis had higher expression level of CENPA. And patients with high CENPA expression had poor disease-free survival. Taken together, Overexpression of CENPA may influence the development of PCa by regulating cell cycle and promoting metastasis.