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.

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.

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.

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.

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.

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.

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.

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.

Identification and validation of an individualized autophagy-clinical prognostic index in bladder cancer patients.

Purpose: Autophagy is a major catabolic system by which eukaryotic cells undergo self-degradation of damaged, defective, or unwanted intracellular components. An abnormal autophagic level is implicated in the pathogenesis of multiple diseases, including cancers. The aim of this study is to explore the prognostic value of autophagy in bladder cancer (BC), which is a major cause of cancer-related death globally. Patients and methods: First, 27 differentially expressed autophagy-related genes (ARGs) were identified in BC patients based on The Cancer Genome Atlas (TCGA) database. Functional enrichment analyses hinted that autophagy may act in a tumor-suppressive role in the initiation of BC. Then, the Cox proportional hazard regression model were employed to identify three key prognostic ARGs (JUN, MYC, and ITGA3), which were related with overall survival (OS) significantly in BC. The three genes represented important clinical significance and prognostic value in BC. Then a prognostic index (PI) was constructed. Results: The PI was constructed based on the three genes, and significantly stratified BC patients into high- and low-risk groups in terms of OS (HR=1.610, 95% CI=1.200-2.160, P=0.002). PI remained as an independent prognostic factor in multivariate analyses (HR=2.355, 95% CI=1.483-3.739, P<0.001). When integrated with clinical characteristics of age and stage, an autophagy-clinical prognostic index (ACPI) was finally validated, which had improved performance in predicting OS of BC patients (HR=2.669, 95% CI=1.986-3.587, P<0.001). The ACPI was confirmed in datasets of GSE13507 (HR=7.389, 95% CI=3.645-14.980, P<0.001) and GSE31684 (HR=1.665, 95% CI=0.872-3.179, P=0.122). Conclusion: This study provides a potential prognostic signature for predicting prognosis of BC patients and molecular insights of autophagy in BC.

Prospective molecular mechanism of COL5A1 in breast cancer based on a microarray, RNA sequencing and immunohistochemistry.

Breast cancer (BC) has a complex etiology and pathogenesis, and is the most common malignant tumor type in females, in USA in 2018, yet its relevant molecular mechanisms remain largely unknown. The collagen type V α­1 chain (COL5A1) gene is differentially expressed in renal and ovarian cancer. Using bioinformatics methods, COL5A1 was determined to also be a significant gene in BC, but its association with BC has not been sufficiently reported. COL5A1 microarray and relevant clinical data were collected from the Gene Expression Omnibus, The Cancer Genome Atlas and other databases to summarize COL5A1 expression in BC and its subtypes at the mRNA and protein levels. All associated information was comprehensively analyzed by various software. The clinical significance of the mutation was obtained via the cBioPortal. Furthermore, Gene Ontology functional annotation and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were also performed to investigate the mechanism of COL5A1 in BC. Immunohistochemistry was also conducted to detect and confirm COL5A1 expression. It was determined that COL5A1 was highly expressed in BC tissues, compared with normal tissues at the mRNA level [standard mean difference, 0.84; 95% confidence interval (CI), 0.60­1.07; P=0.108]. The area under the summary receiver operator characteristic curve for COL5A1 was 0.87 (95% CI, 0.84­0.90). COL5A1 expression was altered in 32/817 (4%) sequenced samples. KEGG analysis confirmed the most notable pathways, including focal adhesion, extracellular matrix­receptor interaction and regulation of the actin cytoskeleton. Immunohistochemical detection was used to verify the expression of COL5A1 in 136 selected cases of invasive BC tissues and 55 cases of adjacent normal tissues, while the rate of high expression of COL5A1 in BC was up to 90.4%. These results indicated that COL5A1 is highly expressed at the mRNA and protein levels in BC, and the prognosis of patients with BC with high COL5A1 expression may be reduced; therefore, COL5A1 may be used independently or combined with other detection factors in BC diagnosis.

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.

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.

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.

The expression and biological information analysis of miR-375-3p in head and neck squamous cell carcinoma based on 1825 samples from GEO, TCGA, and peer-reviewed publications.

BACKGROUND: The specific expression level and clinical significance of miR-375-3p in HNSCC had not been fully stated, as well as the overall biological function and molecular mechanisms. Therefore, we purpose to carry out a comprehensive meta-analysis to further explore the clinical significance and potential function mechanism of miR-375-3p in HNSCC. METHODS: HNSCC-related data was gained from Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), and peer-reviewed journals. A meta-analysis was carried out to comprehensively explore the relationship between miR-375-3p expression level and clinicopathological features of HNSCC. And summary receiver operating characteristic (SROC) curve analysis was applied for evaluating disease diagnosis value of miR-375-3p. In addition, a biological pathway analysis was also performed to assess the possible molecular mechanism of miR-375-3p in HNSCC. RESULTS: A total of 24 available records and references were added into analysis. The overall pooled meta-analysis outcome revealed a relatively lower expression level of miR-375-3p in HNSCC specimens than that in non-cancerous controls (P < 0.001). And SROC curve analysis showed that the pooled area under the SROC curve (AUC) was 0.90 (95%CI: 0.88-0.93). In addition, biological pathway analysis indicated that LAMC1, EDIL3, FN1, VEGFA, IGF2BP2, and IGF2BP3 maybe the latent target genes of miR-375-3p, which were greatly enriched in the pathways of beta3 integrin cell surface interactions and the binding of RNA via the insulin-like growth factor-2 mRNA-binding protein (IGF2BPs/IMPs/VICKZs). CONCLUSION: MiR-375-3p expression clearly decreased in HNSCC samples compared with non-cancerous controls. Meanwhile, miR-375-3p may serve as a tumor suppressor via regulating tumor-related genes LAMC1, EDIL3, FN1, VEGFA, IGF2BP2, and IGF2BP3 in HNSCC.

Clinical value of survivin and its underlying mechanism in ovarian cancer: A bioinformatics study based on GEO and TCGA data mining.

OBJECTIVE: An increasing number of studies have confirmed that survivin (BIRC5) plays essential roles in ovarian cancer. Nevertheless, inconsistent or controversial results exist in some studies. In the present study, we sought to determine the clinical significance of survivin and its potential molecular pathways. METHODS: The correlation between survivin (BIRC5) expression and diagnostic value, prognostic value and clinicopathological features was assessed by meta-analysis with more than 4000 patients from literature, GEO and TCGA. In addition, the potential molecular mechanism of survivin in ovarian cancer was also determined. RESULTS: The pooled sensitivity and specificity were 0.71 (95%CI: 0.68-0.74) and 0.97 (95%CI: 0.94-0.98), respectively. The AUC of sROC was 0.8765. The results showed that there was also a significant relationship between survivin expression and poor overall survival (HR: 1.24, 95%CI: 1.14-1.35, p < 0.001), disease-free survival (HR: 1.53, 95%CI: 0.57-4.09, p < 0.001), as well as higher recurrence rate (HR: 1.11, 95%CI: 0.97-1.27). Moreover, survivin expression was also associated with tumor progression (cancerous vs. benign, OR: 11.29, 95%CI: 8.96-14.24, p < 0.001), TNM stage (III + IV vs. I + II, OR: 5.38, 95%CI: 4.16-6.97, p < 0.001), histological grades (G3 vs. G1 ∼ G2, OR: 4.36, 95%CI: 3.29-5.77, p < 0.001), and lymphatic metastasis (metastasis vs. non-metastasis, 3.35, 95%CI 2.36-4.75, p < 0.001). Bioinformatics analysis revealed the 50 most frequently altered neighboring genes of survivin in OC, and then Gene Oncology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were conducted. GO analysis showed that these genes were related to signal conduction, cell cycle, apoptosis, and metabolism. KEGG pathways analysis indicated that these genes were primarily enriched in mitotic prometaphase, PLK1 signaling events and the regulation of glucokinase by the glucokinase regulatory protein. CONCLUSION: Survivin (BIRC5) expression might become a specific but low-sensitivity biomarker in ovarian cancer patients, and its presence indicated poor prognosis and worse TNM stages. This protein might function as an oncoprotein by influencing specific pathways involving the 50 genes identified herein. Additional studies are needed to confirm these results.