Landscape of expression profiles in esophageal carcinoma by The Cancer Genome Atlas data

Prognostic modeling and Emerging therapeutic targets Unveiled through single-cell sequencing in esophageal squamous Cell carcinoma

ESCC presents a significant global health challenge due to its high mortality rates and varying responses to treatment. This underscores the critical need for novel diagnostic and predictive biomarkers to improve treatment outcomes. Initially, we conducted single-cell transcriptome sequencing on a total of 128,688 cells obtained from 10 patients as part of our research. Utilizing machine learning and cross-validation techniques, we developed a model incorporating 12 genes that distinguish malignant cells from non-malignant ones. In vitro, we explored the effects of IGFBP2 knockdown on the proliferation, invasion, and migration of ESCC cells. The clinical relevance of IGFBP2 was confirmed through IHC and Kaplan-Meier survival analyses. Furthermore, using bioinformatics tools such as GSVA and xCell on public databases, we discovered that high expression of IGFBP2 is associated with an immunosuppressive tumor microenvironment in ESCC, characterized by reduced CD8+ T cell infiltration. This was validated then through IHC. In summary, our study integrates single-cell sequencing and sophisticated computational techniques to highlight IGFBP2 as a promising biomarker and therapeutic target in ESCC.

miRNA profiling of esophageal adenocarcinoma using transcriptome analysis

Esophageal adenocarcinoma (EAC) occurs following a series of histological changes through epithelial-mesenchymal transition (EMT). A variable expression of normal and aberrant genes in the tissue can contribute to the development of EAC through the activation or inhibition of critical molecular signaling pathways. Gene expression is regulated by various regulatory factors, including transcription factors and microRNAs (miRs). The exact profile of miRs associated with the pathogenesis of EAC is largely unknown, though some candidate miRNAs have been reported in the literature. To identify the unique miR profile associated with EAC, we compared normal esophageal tissue to EAC tissue using bulk RNA sequencing. RNA sequence data was verified using qPCR of 18 selected genes. Fourteen were confirmed as being upregulated, which include CDH11, PCOLCE, SULF1, GJA4, LUM, CDH6, GNA12, F2RL2, CTSZ, TYROBP, and KDELR3 as well as the downregulation of UGT1A1. We then conducted Ingenuity Pathway Analysis (IPA) to analyze for novel miR-gene relationships through Causal Network Analysis and Upstream Regulator Analysis. We identified 46 miRs that were aberrantly expressed in EAC compared to control tissues. In EAC tissues, seven miRs were associated with activated networks, while 39 miRs were associated with inhibited networks. The miR-gene relationships identified provide novel insights into potentially oncogenic molecular pathways and genes associated with carcinogenesis in esophageal tissue. Our results revealed a distinct miR profile associated with dysregulated genes. The miRs and genes identified in this study may be used in the future as biomarkers and serve as potential therapeutic targets in EAC.

Research Progress on the Predicting Factors and Coping Strategies for Postoperative Recurrence of Esophageal Cancer

Esophageal cancer is one of the malignant tumors with poor prognosis in China. Currently, the treatment of esophageal cancer is still based on surgery, especially in early and mid-stage patients, to achieve the goal of radical cure. However, esophageal cancer is a kind of tumor with a high risk of recurrence and metastasis, and locoregional recurrence and distant metastasis are the leading causes of death after surgery. Although multimodal comprehensive treatment has advanced in recent years, the prediction, prevention and treatment of postoperative recurrence and metastasis of esophageal cancer are still unsatisfactory. How to reduce recurrence and metastasis in patients after surgery remains an urgent problem to be solved. Given the clinical demand for early detection of postoperative recurrence of esophageal cancer, clinical and basic research aiming to meet this demand has been a hot topic, and progress has been observed in recent years. Therefore, this article reviews the research progress on the factors that influence and predict postoperative recurrence of esophageal cancer, hoping to provide new research directions and treatment strategies for clinical practice.

Prognostic Value of SPOCD1 in Esophageal Squamous Cell Carcinoma: A Comprehensive Study Based on Bioinformatics and Validation

In the study, we aimed to explore and analyze the potential function of SPOC Domain Containing 1 (SPOCD1) in esophageal squamous cell carcinoma (ESCC). We performed a comprehensive analysis of gene expression of SPOCD1 and its corresponding clinicopathological features in ESCC. In particular, the correlation between SPOCD1 and ESCC was evaluated using a wide range of analysis tools and databases, including TCGA, GTEx, GenePattern, CellMiner, GDSC, and STRING datasets. Different bioinformatics analyses, including differential expression analysis, mutation analysis, drug sensitivity analysis, function analysis, pathway analysis, co-expression network analysis, immune cell infiltration analysis, and survival analysis, were carried out to comprehensively explore the potential molecular mechanisms and functional effects of SPOCD1 on the initiation and progression of ESCC. The expression of SPOCD1 was upregulated in ESCC tissues compared to those in normal tissues. In the high SPOCD1 expression group, we found apparent mutations in TP53, TTN, and MUC16 genes, which were 92, 36, and 18%, respectively. GO and KEGG enrichment analysis of SPOCD1 and its co-expressed genes demonstrated that it may serve as an ESCC oncogene by regulating the genes expression in the essential functions and pathways of tumorigenesis, such as glycosaminoglycan binding, Cytokine-cytokine receptor interaction, and Ras signaling pathway. Besides, the immune cell infiltration results revealed that SPOCD1 expression was positively correlated with Macrophages M0 and Mast cells activated cells, and negatively correlated with plasma cells and T cells follicular helper cell infiltration. Finally, ESCC patients with high expression of SPOCD1 indicated poor overall survival. qRT-PCR demonstrated that the SPOCD1 expression in ESCC tissues was significantly higher than adjacent tissues (p < 0.001). Our study indicated that SPOCD1 was increased in ESCC tissues. The current data support the oncogenic role of SPOCD1 in the occurrence and development of ESCC. Most importantly, SPOCD1 might be an independent prognostic factor for ESCC patients.

Identification of Candidate Therapeutic Genes for More Precise Treatment of Esophageal Squamous Cell Carcinoma and Adenocarcinoma

The standard therapy administered to patients with advanced esophageal cancer remains uniform, despite its two main histological subtypes, namely esophageal squamous cell carcinoma (SCC) and esophageal adenocarcinoma (AC), are being increasingly considered to be different. The identification of potential drug target genes between SCC and AC is crucial for more effective treatment of these diseases, given the high toxicity of chemotherapy and resistance to administered medications. Herein we attempted to identify and rank differentially expressed genes (DEGs) in SCC vs. AC using ensemble feature selection methods. RNA-seq data from The Cancer Genome Atlas and the Fudan-Taizhou Institute of Health Sciences (China). Six feature filters algorithms were used to identify DEGs. We built robust predictive models for histological subtypes with the random forest (RF) classification algorithm. Pathway analysis also be performed to investigate the functional role of genes. 294 informative DEGs (87 of them are newly discovered) have been identified. The areas under receiver operator curve (AUC) were higher than 99.5% for all feature selection (FS) methods. Nine genes (i.e., ERBB3, ATP7B, ABCC3, GALNT14, CLDN18, GUCY2C, FGFR4, KCNQ5, and CACNA1B) may play a key role in the development of more directed anticancer therapy for SCC and AC patients. The first four of them are drug targets for chemotherapy and immunotherapy of esophageal cancer and involved in pharmacokinetics and pharmacodynamics pathways. Research identified novel DEGs in SCC and AC, and detected four potential drug targeted genes (ERBB3, ATP7B, ABCC3, and GALNT14) and five drug-related genes.

Development and Validation of a Ferroptosis-Related Gene Signature and Nomogram for Predicting the Prognosis of Esophageal Squamous Cell Carcinoma

Esophageal squamous cell carcinoma (ESCC) is a common malignant tumor with high mortality and poor prognosis. Ferroptosis is a newly discovered form of cell death induced by iron-catalyzed excessive peroxidation of polyunsaturated fatty acids (PUFAs). However, the prognostic value of ferroptosis-related genes (FRGs) for ESCC remains unclear. Based on the ESCC dataset from the Gene Expression Omnibus (GEO) database, we identified 39 prognostic FRGs through univariate Cox regression analysis. After LASSO regression and multivariate Cox regression analyses, a multigene signature based on 10 prognostic FRGs was constructed and successfully divided ESCC patients into two risk groups. Patients in the low-risk group showed a significantly better prognosis than patients in the high-risk group. In addition, we combined the risk score with clinical predictors to construct a nomogram for ESCC. The predictive ability of the nomogram was further verified by ROC curves and calibration plots in both the training and validation sets. The predictive power of the nomogram was demonstrated to be better than that of either the risk score or clinical variable alone. Furthermore, functional analysis revealed that the 10-FRG signature was mainly associated with ferroptosis, differentiation and immune response. Connectivity map analysis identified potential compounds capable of targeting FRGs in ESCC. Finally, we demonstrated the prognostic value of SRC gene in ESCC using the clinical samples and found that SRC inhibition sensitized ESCC cells to ferroptosis inducers by in vitro experiments. In conclusion, we identified and verified a 10-FRG prognostic signature and a nomogram, which provide individualized prognosis prediction and provide insight into potential therapeutic targets for ESCC.

Immune-Related Long Non-coding RNA Signature and Clinical Nomogram to Evaluate Survival of Patients Suffering Esophageal Squamous Cell Carcinoma

Esophageal squamous cell carcinoma (ESCC) turns out to be one of the most prevalent cancer types, leading to a relatively high mortality among worldwide sufferers. In this study, gene microarray data of ESCC patients were obtained from the GEO database, with the samples involved divided into a training set and a validation set. Based on the immune-related differential long non-coding RNAs (lncRNAs) we identified, a prognostic eight-lncRNA-based risk signature was constructed following regression analyses. Then, the predictive capacity of the model was evaluated in the training set and validation set using survival curves and receiver operation characteristic curves. In addition, univariate and multivariate regression analyses based on clinical information and the model-based risk score also demonstrated the ability of the risk score in independently determining the prognosis of patients. Besides, based on the CIBERSORT tool, the abundance of immune infiltrates in tumor samples was scored, and a significant difference was presented between the high- and low- risk groups. Correlation analysis with immune checkpoints (PD1, PDL1, and CTLA4) indicated that the eight-lncRNA signature–based risk score was negatively correlated with PD1 expression, suggesting that the eight-lncRNA signature may have an effect in immunotherapy for ESCC. Finally, GO annotation was performed for the differential mRNAs that were co-expressed with the eight lncRNAs, and it was uncovered that they were remarkably enriched in immune-related biological functions. These results suggested that the eight-lncRNA signature–based risk model could be employed as an independent biomarker for ESCC prognosis and might play a part in evaluating the response of ESCC to immunotherapy with immune checkpoint blockade.

Relationship between cervical esophageal squamous cell carcinoma and human papilloma virus infection and gene mutations

Cervical esophageal squamous cell carcinoma (CESCC) is rare, accounting for 5% of all esophageal carcinomas. Several diagnostic and predictive markers have been studied. However, to the best of our knowledge, no biomarker is known to determine patient management except the clinical stage. The present study aimed to evaluate whether human papilloma virus (HPV) infection, epidermal growth factor receptor (EGFR) and its pathway-related gene mutations, known to be sensitive biomarkers of oropharyngeal carcinomas, could be used as biomarkers for the prediction of the prognosis of patients with CESCC. The present retrospective study included patients with CESCC who received chemoradiotherapy or surgery. HPV infection and the genomic status of EGFR, KRAS, BRAF, NRAS and PIK3CA of each tumor sample from patients with CESCC were analyzed by in situ hybridizations (ISH) and PCR methods, respectively. The present study included 33 patients with CESCC (male/female, 29/4; median age, 62 years; age range, 41-86 years; clinical stage I/II/III/IV, 2/6/10/15). The present study detected HPV in one patient (3.0%) by ISH and PCR. Concerning the investigation of EGFR and its pathway-related gene mutations, the present study detected 15.1% of EGFR, 6.0% of NRAS, 3.5% of BRAF, 3.0% of KRAS and 3.0% for PIK3CA mutations, with no significant relationship between any gene mutations and the clinical prognostic factors. The HPV-infected patient did not exhibit any gene mutations. The present study indicated that HPV infection, EGFR and its pathway-related gene mutations rarely exist in patients with CESCC. The relationship between these biomarkers and the prognosis in patients with CESCC is still unclear.

Meta-analysis of prognostic factors of overall survival in patients undergoing oesophagectomy for oesophageal cancer

INTRODUCTION

Currently, the American Joint Commission on Cancer (AJCC) staging system is used for prognostication for oesophageal cancer. However, several prognostically important factors have been reported but not incorporated. This meta-analysis aimed to characterize the impact of preoperative, operative, and oncological factors on the prognosis of patients undergoing curative resection for oesophageal cancer.

METHODS

This systematic review was performed according to PRISMA guidelines and eligible studies were identified through a search of PubMed, Scopus, and Cochrane CENTRAL databases up to 31 December 2018. A meta-analysis was conducted with the use of random-effects modeling to determine pooled univariable hazard ratios (HRs). The study was prospectively registered with the PROSPERO database (Registration: CRD42018157966).

RESULTS

One-hundred and seventy-one articles including 73,629 patients were assessed quantitatively. Of the 122 factors associated with survival, 39 were significant on pooled analysis. Of these. the strongly associated prognostic factors were 'pathological' T stage (HR: 2.07, CI95%: 1.77-2.43, P < 0.001), 'pathological' N stage (HR: 2.24, CI95%: 1.95-2.59, P < 0.001), perineural invasion (HR: 1.54, CI95%: 1.36-1.74, P < 0.001), circumferential resection margin (HR: 2.17, CI95%: 1.82-2.59, P < 0.001), poor tumor grade (HR: 1.53, CI95%: 1.34-1.74, P < 0.001), and high neutrophil:lymphocyte ratio (HR: 1.47, CI95%: 1.30-1.66, P < 0.001).

CONCLUSION

Several tumor biological variables not included in the AJCC 8th edition classification can impact on overall survival. Incorporation and validation of these factors into prognostic models and next edition of the AJCC system will enable personalized approach to prognostication and treatment.

Down-Regulation of miR-2053 Inhibits the Development and Progression of Esophageal Carcinoma by Targeting Fyn-Related Kinase (FRK)

BACKGROUND

MicroRNAs (miRNAs) play essential roles in the regulation and pathophysiology of various types of cancers including esophageal carcinoma (ESCA). Increasing numbers of miRNAs have been identified to be important regulators in the progression of ESCA by regulating gene expression. However, functional miRNAs and the underlying mechanisms involved in ESCA need sufficient elucidation.

AIMS

In the present study, the function of miR-2053 was investigated in ESCA cells.

METHODS

The expression of miR-2053 was detected in four different ESCA cell lines (Eca109, Ec9706, KYSE30, and TE-1 cells) and normal cell line (HEEC) by qRT-PCR. Cell proliferation, migration, and invasion abilities after knockdown of miR-2053 were assessed by CCK-8 assay, scratch assay, and transwell assay, respectively. Cell cycle of ESCA cells was detected by flow cytometric analysis. Expression of proteins in ESCA cells was detected by Western blot analysis.

RESULTS

The results showed that the expression of miR-2053 was remarkably up-regulated in ESCA tissues and cells lines. Down-regulation of miR-2053 markedly inhibited cell proliferation, migration, and invasion and markedly induced cell cycle arrest and cell apoptosis in ESCA cell lines. Fyn-related kinase (FRK) was a target gene of miR-2053. Moreover, down-regulation of miR-2053 mediated the protein kinase B (AKT)/mammalian target of rapamycin and Wnt3a/β-catenin signaling pathway in ESCA cell lines.

CONCLUSIONS

Our results together suggest the potential of regulating miR-2053 expression against development and progression of esophageal carcinoma by targeting FRK.

Identification of a RNA-seq-based signature to improve prognostics for uterine sarcoma

OBJECTIVE

Uterine sarcoma (US) is a highly malignant cancer with poor prognosis and high mortality. This study focused on the identification of a RNA-Seq expression signature for prognosis prediction in uterine sarcoma.

METHODS

We obtained RNA-Seq expression profiles from The Cancer Genome Atlas database, and differentially expressed genes were identified between US tissues and normal tissues. Univariate Cox proportional hazards regression analysis and LASSO Cox model were performed to identify and construct the prognostic gene signature. Time-dependent receiver operating characteristic, Kaplan-Meier curve and multivariate Cox regression analysis were used to assess the prognostic capacity of the six-gene signature. The nomogram was developed including prognostic signature and independent clinical factors to predict the overall survival (OS) of US patients. The functional enrichment and somatic mutation analysis were also analyzed by bioinformatics to understand the molecular mechanisms.

RESULTS

This study identified a prognostic signature based on 6 genes: FGF23, TLX2, TIFAB, RNF223, HIST1H3A and AADACL4. In the training group, the median OS in the high- and low-risk groups was 19.6 vs 88.1 months (HR, 0.1412, 95% CI: 0.03295 - 0.6054; P = 0.002), respectively. In the testing group, the median OS in the high- and low-risk groups were 30 vs NR (not reach) months (HR, <0.0001, 95% CI: 0 - inf; P = 0.03). In all of patients, the low-risk group showed significant better survival compared with the high-risk group in OS, PFI, DSS and DFI. The nomogram based on the gene signature and radiation therapy was developed and successfully predicted the OS of US patients. The patients in the high-risk group displayed distinct mutation signatures comparing to patients in the low-risk group. Functional enrichment analysis indicated that the signature can play a vital role in cancer-related biological processes.

CONCLUSION

Our study established a novel 6-gene signature and nomogram which could improve prognosis prediction in patients with US.

MicroRNA expression profiling in the colorectal normal-adenoma-carcinoma transition

Colorectal adenoma is a major precursor to colorectal cancer. Investigating the alteration of microRNA (miRNA/miR) expression during the progression from normal colorectal tissue to adenoma, and finally to colorectal carcinoma may aid our understanding of the biological mechanisms of colorectal tumorigenesis. In the present study, the miRNA expression profiles of normal colorectal tissue, adenoma and colorectal carcinoma from 6 patients were evaluated using miRNA-sequencing. A total of 334 miRNAs were identified as differentially expressed. It was revealed that 34 miRNAs were upregulated in all 6 patients, including miR-135b-5p, miR-18a-5p and miR-29b-3p, and 28 miRNAs were downregulated, including miR-1-3p, miR-338-3p and miR-218-5p. Using bioinformatic analysis, the potential target genes of these 62 miRNAs were predicted and found to be enriched in 'transcription, DNA-dependent (GO:0006351)', 'signal transduction (GO:0007165)', 'small molecule metabolic process (GO:0044281)' 'PI3K/AKT signaling pathway (path ID:04151)' and 'MAPK signaling pathway (path ID:04010)'. The miRNA expression profiles identified in the present study may extend our understanding of the molecular mechanisms underlying colorectal tumorigenesis and promote novel perspectives for prevention, diagnosis and treatment.

Prediction of Recurrence in Cervical Cancer Using a Nine-lncRNA Signature

Background and Objective

As a common cancer type in women, cervical cancer remains one of the leading causes of cancer-associated mortalities word wide. Recent evidence has demonstrated the regulatory role of a large number of long non-coding RNAs (lncRNAs) in cervical cancer. Here, we aimed to identify new biomarkers that related with the recurrence through comprehensive bioinformatics analysis.

Methods

Firstly, we collected online lncRNA expression data of cervical cancer patients which were divided into training, validation, and test set. Then we developed a nine-lncRNA signature from training set by conducting LASSO Cox regression model along with 10-fold cross validation. The prognostic value of this risk score was validated in all the three sets using Kaplan–Meier analysis, C-index, time-dependent ROC curves and dynamic AUC. Biological function of these lncRNAs in cervical cancer cells were evaluated by performing gene ontology biological process enrichment and Kyoto Encyclopedia of Genes and Genomes signaling pathways analysis.

Results

According to the results, a higher predict accuracy was observed in the nine-lncRNA signature than that of FIGO stage in all the three sets. Stratified analysis also demonstrated that the nine-lncRNA signature can predict the recurrence of cervical cancer within FIGO stage. The potential mechanisms underlying the nine-lncRNAs from the signature were also identified according to the gene enrichment analysis.

Conclusion

In the present article, we provided a reliable prognostic tool to facilitate the individual management of patients with cervical cancer after treatment.

Identification of a 26-lncRNAs Risk Model for Predicting Overall Survival of Cervical Squamous Cell Carcinoma Based on Integrated Bioinformatics Analysis

As a common malignancy in women, cervical squamous cell carcinoma is a major cause of cancer-related mortality globally. Recent studies have demonstrated that long non-coding RNA (lncRNA) can function as potential biomarkers in cancer prognosis; however, little is known about its role in cervical cancer. In this study, we downloaded the gene expression profiles along with the clinical data of patients with cervical squamous cell carcinoma from The Cancer Genome Atlas. By applying bioinformatics analysis including random forest selection and Least Absolute Shrinkage and Selection Operator (LASSO) cox regression model along with 10-fold cross-validation, we constructed a 26-lncRNAs risk model that can be used to predict the overall survival of cervical squamous cell carcinoma. After that, Kaplan-Meier analysis combined with log-rank p test was applied to assess the predictive accuracy of the 26-lncRNAs risk model. Further analysis showed that the prognostic value of 26-lncRNAs risk model was independent of other clinicopathological factors. At last, lncRNAs in the model were put into gene ontology biological process enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathways analysis, which suggested that these lncRNAs might contribute to cancer-associated processes such as cell cycle and apoptosis. This study indicated that lncRNAs signature could be a useful marker to predict the prognosis of cervical squamous cell carcinoma.

Elevated microRNA-520d-5p in the serum of patients with Parkinson's disease, possibly through regulation of cereloplasmin expression

Iron metabolism dysfunction and redox-active iron-induced oxidative stress in the brain may contribute to the pathogenesis of Parkinson's disease. We have previously demonstrated that reduced serum ceruloplasmin level exacerbates nigral iron deposition in Parkinson's disease, although the underlying cause of the low serum ceruloplasmin level in Parkinson's disease remains unknown. Fluorescent quantitative real-time polymerase chain reaction analysis revealed that patients with Parkinson's disease had higher serum levels of microRNA (miR)-520d-5p than controls (p = 0.0011). Patients with Alzheimer's disease or multiple system atrophy did not have significantly elevated miR-520d-5p levels. Expression of miR-520d-5p did not correlate with disease severity or the motor phenotype of Parkinson's disease. Luciferase assays confirmed that miR-520d-5p was associated with ceruloplasmin gene expression, as predicted by the TargetScan tool and miRBase. In vitro experiments showed that miR-520d-5p reduced ceruloplasmin gene expression in the U251 astrocyte cell line. Our data suggest that miR-520d-5p may be a potential regulator of ceruloplasmin gene expression in vitro.

Label‑free quantitative proteomics and bioinformatics analyses of alcoholic liver disease in a chronic and binge mouse model

As a significant cause of mortality and morbidity, alcoholic liver disease (ALD) has been widely investigated. However, little is known about the underlying metabolic mechanisms involved in the complicated pathological processes of ALD. The present study used label‑free quantitative proteomics and bioinformatics analyses to investigate the differentially expressed proteins (DEPs) and their functions in the livers of alcohol‑feed (AF) and control pair‑feed (PF) mice. As a result, 87 upregulated DEPs and 133 downregulated DEPs were identified in AF liver tissues compared with PF livers. Gene ontology and Kyoto encyclopedia of genes and genomes bioinformatics analyses demonstrated that the DEPs were significantly enriched in 'protein binding', 'metabolism', 'signal conduction' and 'immune response'. The expression of several core proteins including thyroid hormone receptor interactor 12 (TRIP12), NADH dehydrogenase (ubiquinone)1 α subcomplex, assembly factor 3 (NDUFAF3) and guanine monophosphate synthetase (GMPS) was validated by reverse transcription‑quantitative polymerase chain reaction (RT‑qPCR) in a larger series of samples. The RT‑qPCR results confirmed that TRIP12, NDUFAF3 and GMPS genes were significantly differentially expressed in between the AF and PF samples. These results extend our understanding of the molecular mechanisms underlying the occurrence and development of ALD. The present study indicated that the majority of DEPs serve vital roles in multiple metabolic pathways and this extends our knowledge of the molecular mechanisms involved in the occurrence and progression of ALD.

A seven-lncRNA signature predicts overall survival in esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is one of the most common types of cancer and the leading causes of cancer-related mortality worldwide, especially in Eastern Asia. Here, we downloaded the microarray data of lncRNA expression profiles of ESCC patients from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) data sets and divided into training, validation and test set. The random survival forest (RSF) algorithm and Cox regression analysis were applied to identify a seven-lncRNA signature. Then the predictive ability of the seven-lncRNA signature was evaluated in the validation and test set using Kaplan-Meier test, time-dependent receiver operating characteristic (ROC) curves and dynamic area under curve (AUC). Stratified analysis and multivariate Cox regression also demonstrated the independence of the signature in prognosis prediction from other clinical factors. Besides, the predict accuracy of lncRNA signature was much better than that of tumor-node-metastasis (TNM) stage in all the three sets. LncRNA combined with TNM displayed better prognostic predict ability than either alone. The role of LINC00173 from the signature in modulating the proliferation and cell cycle of ESCC cells was also observed. These results indicated that this seven-lncRNA signature could be used as an independent prognostic biomarker for prognosis prediction of patients with ESCC.

Identification of molecular targets for esophageal carcinoma diagnosis using miRNA-seq and RNA-seq data from The Cancer Genome Atlas: a study of 187 cases

Esophageal carcinoma (ESCA) is one of the most common malignancies worldwide, and its pathogenesis is complex. In this study, we identified differentially expressed miRNAs (DEMs) and genes (DEGs) of ESCA from The Cancer Genome Atlas (TCGA) database. The diagnostic values of DEMs were determined by receiver operating characteristic (ROC) analyses and validated based on data from Gene Expression Omnibus (GEO). The top five DEMs with the best diagnostic values were selected, and their potential targets were predicted by various in silico methods. These target genes were then identified among the DEGs from TCGA. Furthermore, the overlapping genes were subjected to protein-protein interaction (PPI) analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. The miRNA-transcription factor (TF) regulatory relations were determined using CircuitsDB and TransmiR. Finally, the regulatory networks of miRNA-TF and miRNA-gene were constructed and analyzed. A total of 136 DEMs and 3541 DEGs were identified in ESCA. The top five DEMs with the highest area under the receiver operating characteristic curve (AUC) values were miRNA-93 (0.953), miRNA-21 (0.928), miRNA-4746 (0.915), miRNA-196a-1 (0.906) and miRNA-196a-2 (0.906). The combined AUC of these five DEMs was 0.985. The KEGG analysis with 349 overlapping genes showed that the calcium signaling pathway and the neuroactive ligand-receptor interaction were the most relevant pathways. The regulatory networks of miRNA-TF and miRNA-gene, including 38 miRNA-TF and 560 miRNA-gene pairs, were successfully established. Our findings may provide new insights into the molecular mechanisms of ESCA pathogenesis. Future research will aim to explore the role of novel miRNAs in the pathogenesis and improve the early diagnosis of ESCA.

Bioinformatics analyses of the differences between lung adenocarcinoma and squamous cell carcinoma using The Cancer Genome Atlas expression data

The present study aimed to explore gene and microRNA (miRNA) expression differences between lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). Differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) were identified by analyzing mRNA and miRNA expression data in normal and cancerous lung tissues that were obtained from The Cancer Genome Atlas database. A total of 778 DEGs and 7 DEMs were identified. Altered gene functions and signaling pathways were investigated using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses, which revealed that DEGs were significantly enriched in extracellular matrix organization, cell differentiation, negative regulation of toll signaling pathway, and several other terms and pathways. Transcription factor (TF)-miRNA-gene networks in LUAD and LUSC were predicted using the TargetScan, Miranda, and TRANSFAC databases, which revealed the regulatory links among the TFs, DEMs, and DEGs. The central TFs, i.e., the TFs in the middle of the TF-miRNA-gene network, of LUAD and LUSC were similar. Although LUAD and LUSC shared similar miRNAs in the predicted networks, miR-29b-3p was demonstrated to be upregulated only in LUAD, whereas miR-1, miR-105-5p, and miR-193b-5p were altered in LUSC. These findings may improve our understanding of the different molecular mechanisms in non-small cell lung cancers and may promote new and accurate strategies for prevention, diagnosis, and treatment.

Comprehensive bioinformatics analyses of Crohn's disease

Crohn's disease (CD) is a chronic, relapsing inflammatory disease with increasing incidence and prevalence worldwide. In previous years, the accumulation of microarray data has provided us an approach to obtain further insight into CD. In the present study, the microarray data of CD was comprehensively analyzed using multiple bioinformatics methods, and the pathobiological process of the disease was examined. Gene expression data from colon tissues of patients with CD were obtained from the Gene Expression Omnibus database; following which differentially expressed genes were identified between CD and control sample groups. Subsequently, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were performed to investigate which functions and pathways in which the differentially expressed genes enriched. TargetScan and miRDB databases were then used to predict which microRNAs (miRNAs) regulated the differentially expressed genes. As a result, a total of 432 differentially expressed genes, including 229 upregulated and 203 downregulated genes, including matrix metallopeptidase 3 and glutathione S‑transferase α1, were identified in CD samples. These differentially expressed genes were significantly involved in regulation of the inflammatory response, innate immune response, cell migration, extracellular matrix organization, Janus kinase/signal transducers and activators of transcription signaling pathway, and cytokine‑cytokine receptor interaction. The miRNA-gene network showed that miR‑149‑3p and miR‑4447 regulated the most differentially expressed genes. These findings extend current understanding of the mechanisms underlying CD, and the differentially expressed genes and regulator miRNAs identified may be used as potential biomarkers and therapeutic targets for CD.

SEOM Clinical Guideline for the diagnosis and treatment of esophageal cancer (2016)

Esophageal cancer (EC) is an aggressive tumor that represents the 6th most common cause of cancer death worldwide. The estimated incidence in Spain is 2090 cases/year. Two main pathological subtypes exist, squamous cell carcinoma and adenocarcinoma. The main differences between them are localization and underlying factors which are the principal cause of the recent incidence changes observed in west countries. Staging techniques and treatment options which combine surgery, chemotherapy and radiotherapy, reflected the high complexity of the EC management. An undeniably multidisciplinary approach is, therefore, required. In this guide, we review the status of current diagnosis and treatment, define evidence and propose recommendations.

The expression of microRNA 574-3p as a predictor of postoperative outcome in patients with esophageal squamous cell carcinoma

BACKGROUND

Despite advances in radical esophagectomies and adjuvant therapy, the postoperative prognosis in esophageal squamous cell carcinoma (ESCC) patients remains poor. The aim of this study was to identify a molecular signature to predict postoperative favorable outcomes in patients with ESCC.

METHODS

As a training data set, total RNA was extracted from formalin-fixed paraffin-embedded samples of surgically removed specimens from 19 ESCC patients who underwent curative esophagectomy. The expression of microRNA (miRNA) was detected using a miRNA oligo chip on which 885 genes were mounted. As a validation data set, we obtained frozen samples of surgically resected tumors from 12 independent ESCC patients and the expression of miR-574-3p was detected by quantitative real-time PCR.

RESULTS

Our microarray analysis in the training set patients identified three miRNAs (miR-574-3p, miR-106b, and miR-1303) and five miRNAs (miR-1203, miR-1909, miR-204, miR-371-3p, miR-886-3p) which were differentially expressed between the patients with (n = 14) and without (n = 5) postoperative tumor relapse (p < 0.01 and p < 0.05, respectively). Higher expression of miR-574-3p, which showed the most significant association with non-relapse (p = 0.001), was associated with favorable overall survival (p = 0.016). Real-time PCR experiments on the validation set patients confirmed that higher expression of miR-574-3p was associated with non-tumor relapse (p = 0.029) and better overall survival (p = 0.004).

CONCLUSIONS

Our results suggest that the aberrant expression of the miRNAs identified in this study plays key roles in the progression of ESCC. miR-574-3p was suggested to have a tumor suppressor effect, and thus, to be a predictor of postoperative outcome in patients with ESCC.