Gene expression analysis of pretreatment biopsies predicts the pathological response of esophageal squamous cell carcinomas to neo-chemoradiotherapy

Effects of myo-inositol on growth and biomarkers of environmental stress and metabolic regulation in Pacific white shrimp (Litopenaeus vannamei) reared at low salinity

This study explored the role of myo-inositol in alleviating the low salinity stress of White Shrimp (Litopenaeus vannamei). Juvenile shrimp (0.4 ± 0.02 g) in low salinity (salinity 3) water were fed diets with myo-inositol levels of 0, 272, 518, 1020 and 1950 mg/kg (crude protein is 36.82 %, crude lipid is 7.58 %), fed shrimp in seawater at a salinity of 25 were fed a 0 mg/kg myo-inositol diet as a control (Ctrl). The experiment was carried out in tanks (50 L) with satiety feeding, and the experiment lasted for 6 weeks. After sampling, the serum was used to measure immune function, the hepatopancreas homogenate was used to measure the antioxidant capacity and hepatopancreas damage state, the hepatopancreas was used for transcriptomics analysis, and the gills were used for qPCR to measure osmotic pressure regulation. The results showed that the final weight and survival of the shrimp in the 1020 mg/kg group increased significantly compared with those in the other low salinity groups, but the final weight and biomass increase were significantly lower than those in the Ctrl group. Dietary myo-inositol improved the antioxidant capacity of shrimp under low salinity. B-cell hyperplasia and hepatic duct damage were observed in the hepatopancreas in the 0 mg/kg group. The results of transcriptome analysis showed that myo-inositol could participate in the osmotic pressure regulation of shrimp by regulating carbohydrate metabolism, amino acid metabolism, lipid metabolism and other related genes. Myo-inositol significantly affected the expression of related genes in ion transporter and G protein-coupled receptor-mediated pathways. This study demonstrated that myo-inositol can not only act as an osmotic pressure effector and participate in the osmolar regulation of shrimp through the phosphatidylinositol signaling pathway mediated by G protein-coupled receptors but also relieve low salinity stress by mediating physiological pathways such as immunity, antioxidation, and metabolism in shrimp. The binomial regression analysis of biomass increases and survival showed that the appropriate amount of myo-inositol in the L. vannamei diet was 862.50-1275.00 mg/kg under low salinity.

Prognostic Risk Models Using Epithelial Cells Identify β-Sitosterol as a Potential Therapeutic Target Against Esophageal Squamous Cell Carcinoma

Background

Esophageal squamous cell carcinoma (ESCC) is an aggressive and fatal malignancy that leads to epithelial cancer. The association between epithelial cell heterogeneity, prognosis, and immune response in this cancer remains uncertain. This study aimed to investigate epithelial cell heterogeneity in ESCC and develop a predictive risk model using the identified cell types.

Methods

Single-cell RNA sequencing (scRNA-seq) and differential ESCC gene data were accessed from the Gene Expression Omnibus. Functional enrichment analysis, inferCNV, cell development trajectories, and intercellular communication were analyzed following epithelial cell characterization. Differentially expressed ESCC (n = 773) and epithelial cell marker genes (n = 3407) were intersected to obtain core genes, and epithelial cell-related prognostic genes were identified. LASSO regression analysis was used to construct a prognostic model. The external dataset GSE53624 was used to further validate the stability of the model. Drug sensitivity predictions, and immune cell infiltration were analyzed. Molecular docking clarified the possible therapeutic role of β-sitosterol in ESCC. Finally, wound healing assay, cell colony, and transwell assay were constructed to detect the effects of the core gene PDLIM2 on ESCC cell proliferation, invasion, and migration.

Results

Eight cell clusters were identified, and epithelial cells were categorized into tumor and paratumor groups. The tumor group possessed more chromosomal variants than the paratumor group. Epithelial cells were associated with multiple cell types and significantly correlated with the Wnt, transforming growth factor, and epidermal growth factor signaling pathways. From 231 intersected genes, five core genes were screened for use in the risk model: CTSL, LAPTM4B, MYO10, NCF2, and PDLIM2. These genes may contribute to the cancerous transformation of normal esophageal epithelial cells and thereby act as biomarkers and potential therapeutic targets in patients with ESCC. β-Sitosterol furthermore displayed excellent docking potential with these genes. Meanwhile, further experiments demonstrated that the gene PDLIM2 plays a major role in the progression of oesophageal squamous carcinoma.

Conclusion

We successfully developed a risk model for the prognosis of ESCC based on epithelial cells that addresses the response of ESCC to immunotherapy and offers novel cancer treatment options.

Multi-omics approaches for biomarker discovery in predicting the response of esophageal cancer to neoadjuvant therapy: A multidimensional perspective

Neoadjuvant chemoradiotherapy (NCRT) followed by surgery has been established as the standard treatment strategy for operable locally advanced esophageal cancer (EC). However, achieving pathologic complete response (pCR) or near pCR to NCRT is significantly associated with a considerable improvement in survival outcomes, while pCR patients may help organ preservation for patients by active surveillance to avoid planned surgery. Thus, there is an urgent need for improved biomarkers to predict EC chemoradiation response in research and clinical settings. Advances in multiple high-throughput technologies such as next-generation sequencing have facilitated the discovery of novel predictive biomarkers, specifically based on multi-omics data, including genomic/transcriptomic sequencings and proteomic/metabolomic mass spectra. The application of multi-omics data has shown the benefits in improving the understanding of underlying mechanisms of NCRT sensitivity/resistance in EC. Particularly, the prominent development of artificial intelligence (AI) has introduced a new direction in cancer research. The integration of multi-omics data has significantly advanced our knowledge of the disease and enabled the identification of valuable biomarkers for predicting treatment response from diverse dimension levels, especially with rapid advances in biotechnological and AI methodologies. Herein, we summarize the current status of research on the use of multi-omics technologies in predicting NCRT response for EC patients. Current limitations, challenges, and future perspectives of these multi-omics platforms will be addressed to assist in experimental designs and clinical use for further integrated analysis.

Regulation of Cellular-Signaling Pathways by Mammalian Proteins Containing Bacterial EPIYA or EPIYA-Like Motifs Predicted to be Phosphorylated

The effector proteins of several pathogenic bacteria contain the Glu-Pro-Ile-Tyr-Ala (EPIYA) motif or other similar motifs. The EPIYA motif is delivered into the host cells by type III and IV secretion systems, through which its tyrosine residue undergoes phosphorylation by host kinases. These motifs atypically interact with a wide range of Src homology 2 (SH2) domain-containing mammalian proteins through tyrosine phosphorylation, which leads to the perturbation of multiple signaling cascades, the spread of infection, and improved bacterial colonization. Interestingly, it has been reported that EPIYA (or EPIYA-like) motifs exist in mammalian proteomes and regulate mammalian cellular-signaling pathways, leading to homeostasis and disease pathophysiology. It is possible that pathogenic bacteria have exploited EPIYA (or EPIYA-like) motifs from mammalian proteins and that the mammalian EPIYA (or EPIYA-like) motifs have evolved to have highly specific interactions with SH2 domain-containing proteins. In this review, we focus on the regulation of mammalian cellular-signaling pathways by mammalian proteins containing these motifs.

Reducing Dietary Protein Content by Increasing Carbohydrates Is More Beneficial to the Growth, Antioxidative Capacity, Ion Transport, and Ammonia Excretion of Nile Tilapia (Oreochromis niloticus) under Long-Term Alkalinity Stress

Alkalinity stress is the main stress experienced by aquatic animals in saline-alkali water, which hinders the aquaculture development and the utilization of water resources. The two-factor (2 × 3) test was adopted to study the influence of dietary protein to carbohydrate ratios on the energy metabolism of Nile tilapia (Oreochromis niloticus) under different alkalinity stress levels. Three diets with different protein-carbohydrate ratios (P27/C35, P35/C25, and P42/C15) were fed to fish cultured in freshwater (FW, 1.3 mmol/L carbonate alkalinity) or alkaline water (AW, 35.7 mmol/L carbonate alkalinity) for 50 days. Ambient alkalinity decreased tilapia growth performance. Although ambient alkalinity caused oxidative stress and enhanced ion transport and ammonia metabolism in tilapia, tilapia fed the P27/C35 diet showed better adaptability than fish fed the other two diets in alkaline water. Further metabolomic analysis showed that tilapia upregulated all the pathways enriched in this study to cope with alkalinity stress. Under alkalinity stress, tilapia fed the P27/C35 diet exhibited enhanced pyruvate metabolism and purine metabolism compared with tilapia fed the P42/C15 diet. This study indicated that ambient alkalinity could significantly decrease growth performance and cause oxidative stress and osmotic regulation. However, reducing dietary protein content by increasing carbohydrates could weaken stress and improve growth performance, ion transport, and ammonia metabolism in tilapia under long-term hyperalkaline exposure.

Progenitor-like exhausted SPRY1+CD8+ T cells potentiate responsiveness to neoadjuvant PD-1 blockade in esophageal squamous cell carcinoma

Neoadjuvant immune checkpoint blockade (ICB) demonstrates promise in operable esophageal squamous cell carcinoma (ESCC), but lacks available efficacy biomarkers. Here, we perform single-cell RNA-sequencing of tumors from patients with ESCC undergoing neoadjuvant ICB, revealing a subset of exhausted CD8+ T cells expressing SPRY1 (CD8+ Tex-SPRY1) that displays a progenitor exhausted T cell (Tpex) phenotype and correlates with complete response to ICB. We validate CD8+ Tex-SPRY1 cells as an ICB-specific predictor of improved response and survival using independent ICB-/non-ICB cohorts and demonstrate that expression of SPRY1 in CD8+ T cells enforces Tpex phenotype and enhances ICB efficacy. Additionally, CD8+ Tex-SPRY1 cells contribute to proinflammatory phenotype of macrophages and functional state of B cells, which thereby promotes antitumor immunity by enhancing CD8+ T cell effector functions. Overall, our findings unravel progenitor-like CD8+ Tex-SPRY1 cells' role in effective responses to ICB for ESCC and inform mechanistic biomarkers for future individualized immunotherapy.

ESRRG-PKM2 axis reprograms metabolism to suppress esophageal squamous carcinoma progression and enhance anti-PD-1 therapy efficacy

BACKGROUND

Glycolysis under normoxic conditions, known as the Warburg effect, confers a selective advantage for the survival and proliferation of many tumors. In this study, we investigated the role of estrogen-related receptor gamma (ESRRG) in metabolic reprogramming in esophageal squamous cell carcinoma (ESCC).

METHODS

Bioinformatics analysis indicated that ESRRG expression was decreased in ESCC tissue and associated with poor clinical outcomes. We also examined the effects of altered ESRRG expression on the proliferation and metabolic reprogramming of ESCC cells. We explored the impact of ESRRG on Pyruvate kinase M2 (PKM2) expression and malignant behavior in ESCC.

RESULTS

Our study revealed the inhibitory effects of ESRRG on the growth, tumorigenesis, and glycolysis activity of ESCC cells, which were mediated by the downregulation of PKM2 expression. We further demonstrated that ESRRG directly interacts with the PKM2 promoter to inhibit its activity in ESCC. Notably, the ESRRG-specific agonist, DY131, inhibited ESCC cell proliferation and glycolysis activity by modulating genes in the glycolysis pathway. Moreover, we verified that DY131 exhibits enhanced activity as an immune checkpoint inhibitor, considering the significance of the ESRRG-PKM2 axis in the lactate regulation of ESCC cells.

CONCLUSION

Our findings provide novel insights into the role of ESRRG-PKM2 signaling in regulating ESCC cell metabolism and immune checkpoint regulation. Additionally, we suggest that DY131 holds promise as a promising therapeutic agent for ESCC treatment.

A novel immune-related prognostic signature based on Chemoradiotherapy sensitivity predicts long-term survival in patients with esophageal squamous cell carcinoma

Background

There is a heterogenous clinical response following chemoradiotherapy (CRT) in esophageal squamous cell carcinoma (ESCC). Therefore, we aimed to study signaling pathway genes that affect CRT sensitivity and prognosis.

Methods

Gene expression analyses were performed in the GEO and TCGA datasets. A immunohistochemistry (IHC) analysis was performed in pretreatment biopsies.

Results

MMP13 was found to be highly expressed in the "Pathologic Complete Response (pCR)" and "Complete Remission (CR)" and "Alive" groups. Th17 cells and MMP9/13 showed a negative correlation in immune infiltration analysis. In GSEA analysis, IL-4 and IL-13 signaling pathways were highly enriched in patients exhibiting high MMP expression in pCR and CR groups. IHC results suggested higher MMP13 & IL-4 and lower IL-17A & RORC expression in the CR group compared to the 0.70, and the model could well distinguish high-risk and low-risk subgroups.

Conclusion

The above results may provide guidance for developing novel treatment and prognostic strategies in ESCC patients.

The Molecular Characterization of Genetic Abnormalities in Esophageal Squamous Cell Carcinoma May Foster the Development of Targeted Therapies

Esophageal cancer is among the most common tumors in the world and is associated with poor outcomes, with a 5-year survival rate of about 10-20%. Two main histological subtypes are observed: esophageal squamous cell carcinoma (ESCC), more frequent among Asian populations, and esophageal adenocarcinoma (EAC), the predominant type in Western populations. The development of molecular analysis techniques has led to the definition of the molecular alterations observed in ESCC, consistently differing from those observed in EAC. The genetic alterations observed are complex and heterogeneous and involve gene mutations, gene deletions and gene amplifications. However, despite the consistent progress in the definition of the molecular basis of ESCC, precision oncology for these patients is still virtually absent. The recent identification of molecular subtypes of ESCC with clinical relevance may foster the development of new therapeutic strategies. It is estimated that about 40% of the genetic alterations observed in ESCC are actionable. Furthermore, the recent introduction of solid tumor immunotherapy with immune checkpoint inhibitors (ICIs) showed that a minority of ESCC patients are responsive, and the administration of ICIs, in combination with standard chemotherapy, significantly improves overall survival over chemotherapy in ESCC patients with advanced disease.

Impacts of neoadjuvant chemoradiotherapy on the immune landscape of esophageal squamous cell carcinoma

BACKGROUND

Neoadjuvant chemoradiotherapy (neoCRT) followed by surgery is the most common approach for locally advanced resectable esophageal squamous cell carcinoma (ESCC) patients. How neoCRT impacts ESCC tumor immune microenvironment (TIME) has not been fully understood.

METHODS

Single-cell RNA sequencing (scRNA-seq) was conducted to examine the neoCRT-driven cellular and molecular dynamics in 8 pre- and 7 post-neoCRT ESCC samples from 8 male patients.

FINDINGS

scRNA-seq data of about 112,000 cells were obtained. Expression programs of cell cycle, epithelium development, immune response, and extracellular structure in pre-treatment tumor cells were related to neoCRT response. Spearman correlation between CD8⁺ T cells' cytotoxicity and expression of checkpoint molecules was prominent in pre-neoCRT intermediate activated/exhausted CD8⁺ T cells. NeoCRT increased CD8⁺ T cells' infiltration but promoted their exhaustion in both major and minor responders. NeoCRT promoted differentiation of Th but demoted that of Treg cells in major responders. Maturation of cDC1s and expression of M2 macrophage markers increased while the number of cDC2s decreased after neoCRT. Higher activities of immune-related pathways in pre-neoCRT CD8⁺ T cells and macrophages, as well as a pronounced decrease of them after neoCRT, correlated with better neoCRT response. Interactions between intermediate activated/exhausted CD8⁺ T and macrophages, cDC1s, and LAMP3⁺ cDCs decreased after neoCRT.

INTERPRETATION

Our comprehensive picture of the neoCRT-related immune changes provides deeper insights into immunological mechanisms associated with ESCC response to neoCRT, which may aid in future development of immune-strategies for improving ESCC treatment.

FUNDING

This work was supported by the National Natural Science Foundation of China (82072607).

A tumor immune microenvironment-related integrated signature can predict the pathological response and prognosis of esophageal squamous cell carcinoma following neoadjuvant chemoradiotherapy: A multicenter study in China

BACKGROUND

Currently, there are insufficient indicators for the reliable assessment of treatment response following neoadjuvant chemoradiotherapy (nCRT) in patients with esophageal squamous cell carcinoma (ESCC). Considering the essential role of protein-coding and non-coding RNAs in gene regulation and cellular processes, we systematically explored the molecular features and clinical significance of mRNA and lncRNA in 249 pretreatment biopsies from four hospitals in three districts with a high incidence of ESCC patients in China.

METHODS

During the discovery phrase, 13 differentially expressed genes were identified and validated between samples with a complete pathological response (pCR) and those with an incomplete pathological response (<pCR). Subsequently, we constructed a predictive mRNA and lncRNA signature (SERPINE1, LINC00592, and PRKAG2-AS1) using Fisher's linear discriminant analysis (FLDA) with stepwise variant-selection, followed by validation of its predictive ability in both internal and external cohorts.

RESULTS

Our signature showed great value in predicting the response to nCRT among ESCC samples and acted as an independent predictive indicator, in addition to demonstrating great potential in estimating patient prognosis. Interestingly, we found that patients with a high signature score had lower PD-L1 and IDO1 expression levels but higher CD8⁺ T cells infiltration, suggesting that PD-L1 and IDO1 are negatively correlated with a high signature score and further associated with pCR and a better prognosis.

CONCLUSION

The present study identified a promising three-gene-based predictive signature that has powerful clinical implications for the identification of pCR and a good prognosis among patients with ESCC. Further immune-related exploration may provide an opportunity for future therapeutic combination.

A novel immune-related radioresistant lncRNAs signature based model for risk stratification and prognosis prediction in esophageal squamous cell carcinoma

Background and purpose: Radioresistance remains a major reason of radiotherapeutic failure in esophageal squamous cell carcinoma (ESCC). Our study is to screen the immune-related long non-coding RNA (ir-lncRNAs) of radiation-resistant ESCC (rr-ESCC) via Gene Expression Omnibus (GEO) database and to construct a prognostic risk model.

Methods: Microarray data (GSE45670) related to radioresistance of ESCC was downloaded from GEO. Based on pathologic responses after chemoradiotherapy, patients were divided into a non-responder (17 samples) and responder group (11 samples), and the difference in expression profiles of ir-lncRNAs were compared therein. Ir-lncRNA pairs were constructed for the differentially expressed lncRNAs as prognostic variables, and the microarray dataset (GSE53625) was downloaded from GEO to verify the effect of ir-lncRNA pairs on the long-term survival of ESCC. After modelling, patients are divided into high- and low-risk groups according to prognostic risk scores, and the outcomes were compared within groups based on the COX proportional hazards model. The different expression of ir-lncRNAs were validated using ECA 109 and ECA 109R cell lines via RT-qPCR.

Results: 26 ir-lncRNA genes were screened in the GSE45670 dataset with differential expression, and 180 ir-lncRNA pairs were constructed. After matching with ir-lncRNA pairs constructed by GSE53625, six ir-lncRNA pairs had a significant impact on the prognosis of ESCC from univariate analysis model, of which three ir-lncRNA pairs were significantly associated with prognosis in multivariate COX analysis. These three lncRNA pairs were used as prognostic indicators to construct a prognostic risk model, and the predicted risk scores were calculated. With a median value of 2.371, the patients were divided into two groups. The overall survival (OS) in the high-risk group was significantly worse than that in the low-risk group (p < 0.001). The 1-, 2-, and 3-year prediction performance of this risk-model was 0.666, 0.702, and 0.686, respectively. In the validation setting, three ir-lncRNAs were significantly up-regulated, while two ir-lncRNAs were obviouly down-regulated in the responder group.

Conclusion: Ir-lncRNAs may be involved in the biological regulation of radioresistance in patients with ESCC; and the prognostic risk-model, established by three ir-lncRNAs pairs has important clinical value in predicting the prognosis of patients with rr-ESCC.

Epithelial-Mesenchymal Transition Gene Signature Is Associated with Neoadjuvant Chemoradiotherapy Resistance and Prognosis of Esophageal Squamous Cell Carcinoma

Background

Neoadjuvant chemoradiotherapy (neo-CRT) in combination with surgery increases survival compared to surgery alone, as indicated by the esophageal squamous cell carcinoma (ESCC) treatment recommendations. However, the benefits of neo-CRT are diverse among patients. Consequently, the development of new biomarkers that correlate with neo-CRT might be important for the treatment of ESCC.

Methods

The differentially expressed genes (DEG) between responsive and resistant samples from the GSE45670 dataset were obtained. On the TCGA dataset, survival analysis was performed to identify prognosis-related-EMT-genes. For EMT score model construction, lasso regression analysis in the TCGA cohort was used to identify the genes. In the TCGA-ESCC cohort, age, stage, and EMT score were used to construct a nomogram.

Results

In total, 10 prognosis-related-EMT-genes were obtained. These 10 genes consisted of 6 risky genes and 4 protective genes. Based on the lasso analysis and univariate Cox regression, an EMT score model consisting of 7 genes (CLEC18A, PIR, KCNN4, MST1R, CAPG, ALDH5A1, and COX7B) was identified. ESCC patients with a high EMT score have a worse prognosis. These genes were differentially expressed between responsive and resistant patients and had a high accuracy for distinguishing resistant and responsive patients.

Conclusions

The identified genes have the potential to function as molecular biomarkers for predicting ESCC patients' resistance to neo-CRT. This research may aid in the elucidation of the molecular processes driving resistance and the identification of targets for improving the prognosis for ESCC.

SYNGR2 serves as a prognostic biomarker and correlates with immune infiltrates in esophageal squamous cell carcinoma

BACKGROUND

Synaptogyrin-2 (SYNGR2) plays an important role in regulating membrane traffic in nonneuronal cells. However, the role of SYNGR2 in esophageal squamous cell carcinoma (ESCC) remains unclear.

METHODS

All original data were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and integrated via R 3.5.3. SYNGR2 expression was explored in the TCGA and GEO databases. The correlations between SYNGR2 and cancer immune characteristics were analyzed via the TIMER and TISIDB databases.

RESULTS

In general, SYNGR2 was predominantly overexpressed and had reference value in the diagnosis and prognostic estimation of ESCC. Upregulated SYNGR2 was associated with poorer overall survival, poorer disease-specific survival and T stage in ESCC. Mechanistically, we identified hub genes that included a total of 38 SYNGR2-related genes, which were tightly associated with the protein polyubiquitination pathway in ESCC patients. SYNGR2 expression was negatively related to the infiltrating levels of T helper cells. SYNGR2 methylation was positively correlated with the expression of chemokines (CCL2 and CXCL12), chemokine receptors (CCR1 and CCR2), immunoinhibitors (CXCL12 and TNFRSF4) and immunostimulators (CSF1R and PDCD1LG2) in ESCC.

CONCLUSION

SYNGR2 may be used as a biomarker for determining prognosis and immune infiltration in ESCC.

A Transcriptomic Liquid Biopsy Assay for Predicting Resistance to Neoadjuvant Therapy in Esophageal Squamous Cell Carcinoma

OBJECTIVE

The aim of this study was to establish a liquid-biopsy assay to predict response to neoadjuvant therapy (NAT) in esophageal squamous cell carcinoma (ESCC) patients.

SUMMARY BACKGROUND DATA

Pretreatment prediction of resistance to NAT is of great significance for the selection of treatment options in ESCC patients. In this study, we comprehensively translated tissue-based microRNA (miRNA) and messenger RNA (mRNA) expression biomarkers into a liquid biopsy assay.

METHODS

We analyzed 186 clinical ESCC samples, which included 128 formalin-fixed paraffin-embedded and a matched subset of 58 serum samples, from 2 independent institutions. We performed quantitative reverse-transcription polymerase chain reaction, and developed a resistance-prediction model using the logistic regression analyses.

RESULTS

We first evaluated the potential of 4-miRNAs and 3-mRNAs panel, which robustly predicted resistance to NAT [area under the curve (AUC): 0.85]. Moreover, addition of tumor size to this panel increased predictive potential to establish a combination signature (AUC: 0.92). We successfully validated this signature performance in independent cohort, and our model was more accurate when the signature was combined with clinical predictors (AUC: 0.81) to establish a NAT resistance risk (NATRR) model. Finally, we successfully translated our NATRR model into a liquid biopsy assay (AUC: 0.78), and a multivariate regression analysis revealed this model as an independent predictor for response to NAT (odds ratio: 6.10; P < 0.01).

CONCLUSIONS

We successfully developed a liquid biopsy-based assay that allows robust prediction of response to NAT in ESCC patients, and our assay provides fundamentals of developing precision-medicine.

Discovery of Anticancer Activity of Amentoflavone on Esophageal Squamous Cell Carcinoma: Bioinformatics, Structure-Based Virtual Screening, and Biological Evaluation

Esophageal squamous cell carcinoma (ESCC) is the most common primary esophageal malignancy with poor prognosis. Here, due to the necessity for exploring potential therapies against ESCC, we obtained the gene expression data on ESCC from the TCGA and GEO databases. Venn diagram analysis was applied to identify common targets. The protein-protein interaction network was constructed by Cytoscape software, and the hub targets were extracted from the network via cytoHubba. The potential hub nodes as drug targets were found by pharmacophore-based virtual screening and molecular modeling, and the antitumor activity was evaluated through in vitro studies. A total of 364 differentially expressed genes (DEGs) in ESCC were identified. Pathway enrichment analyses suggested that most DEGs were mainly involved in the cell cycle. Three hub targets were retrieved, including CENPF, CCNA2 (cyclin A), and CCNB1 (cyclin B1), which were highly expressed in esophageal cancer and associated with prognosis. Moreover, amentoflavone, a promising drug candidate found by pharmacophore-based virtual screening, showed antiproliferative and proapoptotic effects and induced G1 in esophageal squamous carcinoma cells. Taken together, our findings suggested that amentoflavone could be a potential cell cycle inhibitor targeting cyclin B1, and is therefore expected to serve as a great therapeutic agent for treating esophageal squamous cell carcinoma.

LAMP2 as a Biomarker Related to Prognosis and Immune Infiltration in Esophageal Cancer and Other Cancers: A Comprehensive Pan-Cancer Analysis

Esophageal cancer (ESCA) is a common malignant tumor with poor prognosis. Accumulating evidence indicates an important role of lysosomal-associated membrane protein 2 (LAMP2) in the progression and development of various cancers. In this study, we obtained RNA-sequencing raw count data and the corresponding clinical information for ESCA samples from The Cancer Genome Atlas and Gene Expression Omnibus databases. We comprehensively investigated the expression and prognostic significance of LAMP2 and relationships between LAMP2 expression and prognosis, different clinicopathological parameters, and immune cell infiltration in ESCA. We also obtained the differentially expressed genes between the high LAMP2 expression and low LAMP2 expression groups in ESCA and performed a functional enrichment analysis of the 250 linked genes most positively related to LAMP2 expression. Moreover, we performed the pan-cancer analysis of LAMP2 to further analyze the role of LAMP2 in 25 commonly occurring types of human cancer. We also verified and compared the expression of LAMP2 in 40 samples of human ESCA tissue and adjacent tissues. The results indicated that LAMP2 expression was significantly upregulated in ESCA and various human cancers. In addition, LAMP2 expression was associated with certain clinicopathological parameters, prognosis, and immune infiltration in ESCA and the other types of cancer. Our study represents a comprehensive pan-cancer analysis of LAMP2 and supports the potential use of the modulation of LAMP2 in the management of ESCA and various cancers.

Transcriptome sequencing and lncRNA-miRNA-mRNA network construction in cardiac fibrosis and heart failure

Cardiac fibrosis (CF) and heart failure (HF) are common heart diseases, and severe CF can lead to HF. In this study, we tried to find their common potential molecular markers, which may help the diagnosis and treatment of CF and HF. RNA library construction and high-throughput sequencing were performed. The DESeq2 package in R was used to screen differentially expressed mRNAs (DEmRNAs), differentially expressed lncRNA (DElncRNAs) and differentially expressed miRNA (DEmiRNAs) between different samples. The common DEmRNAs, DElncRNAs and DEmiRNAs for the two diseases were obtained. The ConsensusPathDB (CPDB) was used to perform biological function enrichment for common DEmRNAs. Gene interaction network was constructed to screen out key genes. Subsequently, real-time polymerase chain reaction (RT-PCR) verification was performed. Lastly, GSE104150 and GSE21125 data sets were utilized for expression validation and diagnostic analysis. There were 1477 DEmRNAs, 502 DElncRNAs and 36 DEmiRNAs between CF and healthy control group. There were 607 DEmRNAs, 379DElncRNAs,s and 42 DEmiRNAs between HF and healthy control group. CH and FH shared 146 DEmRNAs, 80 DElncRNAs, and 6 DEmiRNAs. Hsa-miR-144-3p, CCNE2, C9orf72, MAP3K20-AS1, LEF1-AS1, AC243772.2, FLJ46284, and AC239798.2 were key molecules in lncRNA-miRNA-mRNA network. In addition, hsa-miR-144-3p and CCNE2 may be considered as potential diagnostic gene biomarkers in HF. In this study, the identification of common biomarkers of CF and HF may help prevent CF to HF transition as early as possible.

A single-nucleotide-polymorphism in the 5′-flanking region of MSX1 gene as a predictive marker candidate for platinum-based therapy of esophageal carcinoma

Background:

Platinum derivatives are important treatment options for patients with esophageal carcinoma (EC), and a predictive marker for platinum-based therapy is needed for precision medicine.

Patients and methods:

This study contained two cohorts consisting of EC patients treated using platinum-based chemoradiation therapy (CRT) as the first-line and another external cohort of nationwide clinicogenomic data from the BioBank Japan (BBJ).

Results:

Genome-wide association study (GWAS) of therapeutic outcomes, refractory disease or not, following platinum-based CRT as first-line in 94 patients in the first cohort suggested the association of 89 SNPs using p < 0.0001. The top 10 SNPs selected from each chromosomal region by odds ratio were evaluated for progression-free survival (PFS) and overall survival (OS) hazard ratios in the first cohort, resulting in four candidates (p < 0.0025). The four selected candidates were re-evaluated in another cohort of 24 EC patients, which included patients prospectively enrolled in this study to fulfill the sample size statistically suggested by the results of the first cohort, and of the four, only rs3815544 was replicated (p < 0.0125). Furthermore, this candidate genotype of rs3815544 proceeded to the re-evaluation study in an external cohort consisting of EC patients treated with platinum derivatives and/or by radiation therapy as the first-line treatment in BBJ, which confirmed that the alternative allele (G) of rs3815544 was statistically associated with non-response (SD or PD) to platinum-based therapy in EC patients (odds ratio = 1.801, p = 0.048). The methylation QTL database as well as online clinicogenomic databases suggested that the region including rs3815544 may regulate MSX1 expression through CpG methylation, and this down-regulation was statistically associated with poor prognosis after platinum-based therapies for EC.

Conclusion:

rs3815544 is a novel candidate predictive marker for platinum-based EC therapy.

Biomarkers for the prediction of esophageal cancer neoadjuvant chemoradiotherapy response: A systemic review

Neoadjuvant chemoradiotherapy followed by surgery has been established as the standard treatment for locally advanced esophageal cancer. For patients with complete regression after neoadjuvant chemotherapy, active surveillance rather than planned surgery has been proposed as an organ preservation strategy. Reliable biomarkers to predict chemoradiation response is needed. We first summarized the previous reports of biomarkers with the potential to predict the treatment response of esophageal cancer neoadjuvant chemoradiotherapy. These traditional biomarkers are classified into three groups: genetic biomarkers, RNA biomarkers, and protein biomarkers. We then summarized some special types of biomarkers, including metabolites biomarkers, immune and tumor microenvironment biomarkers, and microbiome biomarkers.

The Functionalities and Clinical Significance of Tumor-Infiltrating Immune Cells in Esophageal Squamous Cell Carcinoma

Tumor-infiltrating immune cells have been implicated in the tumorigenesis and progression of esophageal squamous cell carcinoma (ESCC). However, the functionalities and clinical significance of immune cells remain largely unveiled. In this study, the gene expression data from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were extracted. The relative infiltrating levels were estimated by single-sample gene set enrichment analysis. Some cytotoxic immune cells were attenuated, and resting cytotoxic immune cells were accumulated in ESCC. Remarkably, we also observed that infiltrating levels of macrophage M2 and resting natural killer (NK) cells were increased in nonresponders of CRT, and T cells that had anticancer activities such as activated memory CD4 and T helper 2 (Th2) cells were significantly reduced in ESCC tissues of the nonresponders. Moreover, the high infiltrations of the resting natural killer (NK) and dendritic cell (DC) were observed to result in a shorter overall survival in ESCC. Consistently, high expression of immune checkpoint genes, CTLA4 and HAVCR2, was associated with poor prognosis. Furthermore, STAT5B, a key transcription factor, as well as its target genes, involved in the regulation of T cells, was significantly downregulated in ESCC, especially subgroup I, indicating that downregulation of STAT5B might be associated with reduced T cell-mediated anticancer activity. In conclusion, the present study significantly improved our understanding of the regulatory roles of immune cells in ESCC.

Epigenetic Study of Esophageal Carcinoma Based on Methylation, Gene Integration and Weighted Correlation Network Analysis

Purpose

Esophageal carcinoma is a common and highly metastatic malignant tumor of the digestive tract. The aim of the present study was to identify potential molecular markers of esophageal carcinoma that may help its diagnosis and treatment.

Materials and Methods

First, mRNA and DNA methylation data were downloaded from The Cancer Genome Atlas (TCGA) database for the identification of differentially expressed genes (DEGs) and DNA methylation analysis. Secondly, Weighted Gene Co-Expression Network Analysis (WGCNA) was used to identify important modules and hub genes. In addition, correlation analysis between DNA methylation genes and DEGs was performed. Thirdly, the GSE45670 dataset was used to validate the expression of the diagnostic and survival ability analysis of genes in TCGA data. Finally, reverse transcription-quantitative PCR and immunohistochemical analysis of genes were performed.

Results

A total of 2408 DEGs and 5134 differentially methylated sites were obtained. In the WGCNA analysis, the royal blue module was found to be the optimal module. In addition, hub genes in the module, including ESRRG, MFSD4, CCKBR, ATP4B, ESRRB, ATP4A, CCKAR and B3GAT1, were also differentially methylated genes and DEGs. It was found that CCKAR, MFSD4 and ESRRG may be diagnostic gene biomarkers for esophageal carcinoma. In addition, the high expression of MFSD4 was significantly correlated with patient survival. Immunohistochemistry analysis results showed that the gene expression levels of ATP4B, B3GAT1, CCKBR and ESRRG were decreased in esophageal carcinoma tissues, which was in line with the bioinformatics results.

Conclusion

Therefore, these identified molecular markers may be helpful in the diagnosis and treatment of esophageal carcinoma.

Transcriptomic and microRNA Expression Profiles Identify Biomarkers for Predicting Neo-Chemoradiotherapy Response in Esophageal Squamous Cell Carcinomas (ESCC)

Neo-chemoradiotherapy (nCRT) before surgery is a standard treatment for locally advanced esophageal cancers. However, the treatment outcome of nCRT varied with different patients. This study aimed to identify potential biomarkers for prediction of nCRT-response in patients with esophageal squamous cell carcinoma (ESCC). Microarray datasets of nCRT responder and non-responder samples (access number GSE45670 and GSE59974) of patients with ESCC were downloaded from Gene Expression Omnibus (GEO) database. The mRNA expression profiles of cancer biopsies from four ESCC patients were analyzed before and after nCRT. Differentially expressed genes (DEGs) and miRNAs were screened between nCRT responder and non-responder ESCC samples. Functional enrichment analysis was conducted for these DEGs followed by construction of protein-protein interaction (PPI) network and miRNA-mRNA regulatory network. Finally, univariate survival analysis was performed to identify candidate biomarkers with prognostic values in ESCC. We identified numerous DEGs and differentially expressed miRNAs from nCRT responder group. GO and KEGG analysis showed that the dysregulated genes were mainly involved in biological processes and pathways, including "response to stimulus", "cellular response to organic substance", "regulation of signal transduction", "AGE-RAGE signaling pathway in diabetic complications", and "steroid hormone biosynthesis". After integration of PPI network and miRNA-mRNA network analysis, we found eight genes, TNF, AKR1C1, AKR1C2, ICAM1, GPR68, GNB4, SERPINE1 and MMP12, could be candidate genes associated with disease progression. Univariate cox regression analysis showed that there was no significant correlation between dysregulated miRNAs (such as hsa-miR-34b-3p, hsa-miR-127-5p, hsa-miR-144-3p, and hsa-miR-486-5p, et al.) and overall survival of ESCC patients. Moreover, abnormal expression of MMP12 was significantly correlated with pathological degree, TNM stage, lymph nodes metastasis, and overall survival of ESCC patients (p < 0.05). Taken together, our study identified that MMP12 might be a useful tumor biomarker and therapeutic target for ESCC.

Prognostic Value of a Four-miRNA Signature in Patients With Lymph Node Positive Locoregional Esophageal Squamous Cell Carcinoma Undergoing Complete Surgical Resection

OBJECTIVE

This study was intended to identify prognostic biomarkers for lymph node (LN)-positive locoregional esophageal squamous cell carcinoma (ESCC) patients.

SUMMARY OF BACKGROUND DATA

Surgery is a major treatment for LN-positive locoregional ESCC patients in China. However, patient outcomes are poor and heterogeneous.

METHODS

ESCC-associated miRNAs were identified by microarray and validated by quantitative real-time polymerase chain reaction analyses in ESCC and normal esophageal epithelial samples. A multi-miRNA based classifier was established using a least absolute shrinkage and selection operator model in a training set of 145 LN-positive locoregional ESCCs, and further assessed in internal testing and independent validation sets of 145 and 243 patients, respectively.

RESULTS

Twenty ESCC-associated miRNAs were identified and validated. A 4-miRNA based classifier (miR-135b-5p, miR-139-5p, miR-29c-5p, and miR-338-3p) was generated to classify LN-positive locoregional ESCC patients into high and low-risk groups. Patients with high-risk scores in the training set had a lower 5-year overall survival rate [8.7%, 95% confidence interval (CI): 0-20.3] than those with low-risk scores (50.3%, 95% CI: 40.0-60.7; P < 0.0001). The prognostic accuracy of the classifier was validated in the internal testing (P < 0.0001) and independent validation sets (P = 0.00073). Multivariate survival analyses showed that the 4-miRNA based classifier was an independent prognostic factor, and the combination of the 4-miRNA based classifier and clinicopathological prognostic factors significantly improved the prognostic accuracy of clinicopathological prognostic factors alone.

CONCLUSION

Our 4-miRNA based classifier is a reliable prognostic prediction tool for overall survival in LN-positive locoregional ESCC patients and might offer a novel probability of ESCC treatment individualization.

Phenotypic profiling and prognostic significance of immune infiltrates in esophageal squamous cell carcinoma

The tumor microenvironment (TME) of esophageal squamous cell carcinoma (ESCC) impacts tumor progression but is poorly understood. We obtained tumor tissues from 279 patients after esophagectomy and characterized the TME in intraepithelial and stromal regions using multiplex fluorescent immunohistochemistry (mfIHC). A heterogeneous immune population infiltrating tumor and the uninvolved esophageal tissue were observed. The infiltration of intraepithelial programmed death ligand 1 (PD-L1)-positive tumor-associated macrophages (TAMs) and stromal granzyme B⁺ activated cytotoxic T cells (aCTLs) correlated with both prolonged overall survival (OS) and disease-free survival (DFS). The intraepithelial memory T cell infiltration predicted longer OS, while intraepithelial and stromal regulatory T cell (Treg) infiltration was associated with shortened OS and DFS, respectively. Multivariate models combining immune infiltrates and clinicopathological factors outperformed tumor-node-metastasis (TNM) stage in predicting OS and DFS at 3 and 5 years. The infiltration of Treg inversely correlated with that of the antitumor effectors including CTLs, aCTLs, and natural killer (NK) cells. Intraepithelial memory T cell infiltration also negatively correlated with PD-L1 expression. In spatial analysis, intraepithelial dendritic cell (DC)-memory T cell engagement increased in high PD-L1⁺ TAM infiltration group. The characterization of the TME revealed a complex interplay between immune populations and may be employed to stratify patient for prognosis prediction and immunotherapy.

Long non‑coding RNA LINC00491 promotes proliferation and inhibits apoptosis in esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is a common malignant tumor in the human digestive system, which affects the physical and mental health of the patient. Long non-coding (lnc)RNAs have been revealed to play an important role in human malignant tumors. Moreover, long intergenic non-protein coding RNA 491 (LINC00491) is a newly discovered lncRNA that can affect the prognosis of cancer. The present study aimed to explore the expression of LINC00491 in ESCC tissues and cells. The reverse transcription-quantitative PCR results suggested that LINC00491 was upregulated in ESCC tissues and cells. LINC00491 expression in esophageal squamous cell carcinoma cells were knocked down. Cell Counting Kit-8, wound healing, Transwell and apoptosis assays were performed to detect the effects of LINC00491 knockdown on cell biological behavior. The results showed that lower expression of LINC00491 resulted in decreased cell proliferation and migration and increased the apoptosis rate. Therefore, the present results indicated that lncRNA LINC00491 promoted the biological processes of ESCC, and thus LINC00491 may be a potential therapeutic target for ESCC.

Low GSTM3 expression is associated with poor disease-free survival in resected esophageal squamous cell carcinoma

Background

Glutathione S-transferase mu 3 (GSTM3) plays a crucial role in tumor progression in various cancers. However, the relationship between GSTM3 expression and the clinical prognosis of esophageal squamous cell carcinoma (ESCC) has not been studied to date. We aimed to characterize the role of GSTM3 in predicting postoperative prognosis of ESCC patients.

Methods

In the retrospective study, GSTM3 mRNA levels in 184 ESCC tissues and matched 43 adjacent nontumorous tissues were measured by quantitative real-time PCR. GSTM3 protein levels in 247 ESCC tissues were measured by immunohistochemistry.

Results

Downregulation of GSTM3 occurred in 62.8 % of primary ESCC tissues compared with their nontumor counterparts. Patients with low GSTM3 expression tended to exhibit an increased rate of poor differentiation in both the mRNA cohort (p = 0.024) and protein cohort (p = 0.004). In the mRNA cohort, low GSTM3 expression was associated with unfavorable 3-year disease-free survival (DFS) (39.2 % vs. 57.4 %) and 5-year DFS (26.8 % vs. 45.1 %) (p = 0.023). The result was confirmed in the protein cohort. Patients with low GSTM3 expression had unfavorable 3-year disease-free survival (DFS) (18.7 % vs. 33.5 %) and 5-year DFS (5.3 % vs. 30.5 %) (p = 0.006). Cox multivariate analysis revealed that GSTM3 expression was an independent prognostic factor.

Conclusions

The findings of the present study provide evidence that GSTM3 may function as a tumor suppressor in ESCC and represents a potential novel prognostic biomarker for disease-free survival for resected ESCC patients.

Computed tomography-based deep-learning prediction of neoadjuvant chemoradiotherapy treatment response in esophageal squamous cell carcinoma

BACKGROUND

Deep learning is promising to predict treatment response. We aimed to evaluate and validate the predictive performance of the CT-based model using deep learning features for predicting pathologic complete response to neoadjuvant chemoradiotherapy (nCRT) in esophageal squamous cell carcinoma (ESCC).

MATERIALS AND METHODS

Patients were retrospectively enrolled between April 2007 and December 2018 from two institutions. We extracted deep learning features of six pre-trained convolutional neural networks, respectively, from pretreatment CT images in the training cohort (n = 161). Support vector machine was adopted as the classifier. Validation was performed in an external testing cohort (n = 70). We assessed the performance using the area under the receiver operating characteristics curve (AUC) and selected an optimal model, which was compared with a radiomics model developed from the training cohort. A clinical model consisting of clinical factors only was also built for baseline comparison. We further conducted a radiogenomics analysis using gene expression profiles to reveal underlying biology associated with radiological prediction.

RESULTS

The optimal model with features extracted from ResNet50 achieved an AUC and accuracy of 0.805 (95% CI, 0.696-0.913) and 77.1% (65.6%-86.3%) in the testing cohort, compared with 0.725 (0.605-0.846)) and 67.1% (54.9%-77.9%) for the radiomics model. All the radiological models showed better predictive performance than the clinical model. Radiogenomics analysis suggested a potential association mainly with WNT signaling pathway and tumor microenvironment.

CONCLUSIONS

The novel and noninvasive deep learning approach could provide efficient and accurate prediction of treatment response to nCRT in ESCC, and benefit clinical decision making of therapeutic strategy.

Identification of the Prognostic Value of Tumor Microenvironment-Related Genes in Esophageal Squamous Cell Carcinoma

Background: Esophageal squamous cell carcinoma (ESCC) is the most prevalent histological type of esophageal cancer, but there is a lack of definite prognostic markers for this cancer. Methods: We used the ESTIMATE algorithm to access the tumor microenvironment (TME) of ESCC cases deposited in the TCGA database, and identified TME-related prognostic genes using Cox regression analysis. A least absolute shrinkage and selector operation or LASSO algorithm was used to identify key prognostic genes. Risk scores were calculated, and a clinical predictive model was constructed to evaluate the prognostic value of TME-related genes. Results: We found that high immune and stromal scores were significantly associated with poor overall survival (p < 0.05). We identified a total of 1,151 TME-related differently expression genes, among which 67 were prognosis-related genes. Through the LASSO method, 13 key prognostic genes were selected, namely, ADAMTS16, LOC51089, CH25H, CORO2B, DLGAP1, GYS2, HAL, MXRA8, NPTX1, OTX1, RET, SLC24A2, and SPI1, and a 13-gene risk score was constructed. A higher score was indicative of a poorer prognosis than a lower risk score (hazard ratio = 8.21, 95% confidence interval: 2.56-26.31; P < 0.001). The risk score was significantly correlated with immune/stromal scores and various types of infiltrating immune cells, including CD8 cells, regulatory T cells, and resting macrophages. Conclusion: We characterized the tumor microenvironment in ESCC, and identified the key prognosis genes. The risk score based on the expression profiles of these genes is proposed as an indicator of TME status and is instrumental in predicting patient prognosis.

Transcriptomic biomarkers for predicting response to neoadjuvant treatment in oesophageal cancer

Oesophageal cancer is a devastating disease with poor outcomes and is the sixth leading cause of cancer death worldwide. In the setting of resectable disease, there is clear evidence that neoadjuvant chemotherapy and chemoradiotherapy result in improved survival. Disappointingly, only 15%-30% of patients obtain a histopathological response to neoadjuvant therapy, often at the expense of significant toxicity. There are no predictive biomarkers in routine clinical use in this setting and the ability to stratify patients for treatment could dramatically improve outcomes. In this review, we aim to outline current progress in evaluating predictive transcriptomic biomarkers for neoadjuvant therapy in oesophageal cancer and discuss the challenges facing biomarker development in this setting. We place these issues in the wider context of recommendations for biomarker development and reporting. The majority of studies focus on messenger RNA (mRNA) and microRNA (miRNA) biomarkers. These studies report a range of different genes involved in a wide variety of pathways and biological processes, and this is explained to a large extent by the different platforms and analysis methods used. Many studies are also vastly underpowered so are not suitable for identifying a candidate biomarker. Multiple molecular subtypes of oesophageal cancer have been proposed, although little is known about how these relate to clinical outcomes. We anticipate that the accumulating wealth of genomic and transcriptomic data and clinical trial collaborations in the coming years will provide unique opportunities to stratify patients in this poor-prognosis disease and recommend that future biomarker development incorporates well-designed retrospective and prospective analyses.

Links among extracellular enzymes, lignin degradation and cell growth establish the models to identify marine lignin-utilizing bacteria

A major conundrum in the isolation of prokaryotes from open environments is stochasticity. It is especially difficult to study low abundance groups where very little biological information exists, although single-cell genomics and metagenomics have alleviated some of this bottleneck. Here, we report an approach to capture lignin-utilizing bacteria by linking a physical model to actual organisms. Extracellular enzymes, lignin degradation and cell growth are crucial phenotypes of lignin-utilizing bacteria, but their interrelationships remain poorly understood. In this study, the phenotypes of bacteria isolated from in situ lignocellulose enrichment samples in coastal waters were traced and statistically analysed. It suggested cell growth, dye-decolorizing peroxidase (DyP) and reactive oxygen species (ROS) were significantly correlated with lignin degradation, exhibiting a genus-specific property. The established models enabled us to efficiently capture lignin-utilizing bacteria and rapidly evaluate lignin degradation for Bacillus and Vibrio strains. Through the model, we identified several previously unrecognized marine bacterial lignin degraders. Moreover, it demonstrated that the isolated marine lignin-utilizing bacteria employ a DyP-based system and ROS for lignin depolymerization, providing insights into the mechanism of marine bacterial lignin degradation. Our findings should have implications beyond the capture of lignin-utilizing bacteria, in the isolation of other microorganisms with as-yet-unknown molecular biomarkers.

An individualized immune signature of pretreatment biopsies predicts pathological complete response to neoadjuvant chemoradiotherapy and outcomes in patients with esophageal squamous cell carcinoma

No clinically available biomarkers can predict pathological complete response (pCR) for esophageal squamous cell carcinomas (ESCCs) with neoadjuvant chemoradiotherapy (nCRT). Considering that antitumor immunity status is an important determinant for nCRT, we performed an integrative analysis of immune-related gene profiles from pretreatment biopsies and constructed the first individualized immune signature for pCR and outcome prediction of ESCCs through a multicenter analysis. During the discovery phase, 14 differentially expressed immune-related genes (DEIGs) with greater than a twofold change between pCRs and less than pCRs (<pCRs) were revealed from 28 pretreatment tumors in a Guangzhou cohort using microarray data. Ten DEIGs were verified by qPCR from 30 cases in a Beijing discovery cohort. Then, a four-gene-based immune signature (SERPINE1, MMP12, PLAUR, and EPS8) was built based on the verified DEIGs from 71 cases in a Beijing training cohort, and achieved a high accuracy with an area under the receiver operating characteristic curve (AUC) of 0.970. The signature was further validated in an internal validation cohort and an integrated external cohort (Zhengzhou and Anyang cohorts) with AUCs of 0.890 and 0.859, respectively. Importantly, a multivariate analysis showed that the signature was the only independent predictor for pCR. In addition, patients with high predictive scores showed significantly longer overall and relapse-free survival across multiple centers (P < 0.05). This is the first, validated, and clinically applicable individualized immune signature of pCR and outcome prediction for ESCCs with nCRT. Further prospective validation may facilitate the combination of nCRT and immunotherapy.

Identification and Characterization of Copy Number-Associated Driver Genes in Esophageal Squamous Cell Carcinoma

Background

Esophageal squamous cell carcinoma (ESCC) is a leading malignancy with both high incidence and mortality worldwide. However, the molecular mechanisms of the poor prognosis in ESCC are still unclear.

Methods

We conducted differential expression analysis between ESCC and normal tissues and between ESCC samples with and without CNAs in a given gene. Overrepresentation enrichment and gene set enrichment analyses were used to identify the oncogenic pathways and abnormal transcription factors (TFs). The survival analysis was employed to identify the genes associated with overall survival.

Results

In this study, we aimed to identify and interpret the driver genes triggered by the copy number alterations (CNAs), including CCND1, TEAD4, EIF4EBP1, EGFR, FGFR3, and FZD6. Furthermore, we identified oncogenic pathways, including RTK-RAS, WNT, PI3K, Hippo, and cell cycle, and key TFs including TEAD4, a transcription factor in the Hippo signaling pathway, and LEF1 in the WNT signaling pathway. Furthermore, we observed that upregulations of FGFR3 and EIF4EBP1 were significantly associated with shorter overall survival in ESCC.

Conclusion

In conclusion, the driver genes triggered by CNAs not only exhibited critical functionality but also were clinically relevant in ESCC, which greatly improved our understanding of the molecular mechanisms in ESCC.

High Mean Corpuscular Volume as a Predictor of Poor Overall Survival in Patients with Esophageal Cancer Receiving Concurrent Chemoradiotherapy

Background

Increasing numbers of recent studies have demonstrated that high mean corpuscular volume (MCV) is a predictor of poor overall survival (OS) and therapeutic response in patients with solid tumors. The aim of the present study was to explore the association between high MCV and OS in patients with advanced esophageal cancer (EC) undergoing concurrent chemoradiotherapy.

Patients and Methods

Enrolled in this study were 249 patients with advanced EC who underwent concurrent chemoradiotherapy. Pre-treatment MCV values were collected in all patients and their correlations with OS and pathophysiological characteristics were analyzed. The chi-square test was used to explore the correlation between MCV and various clinical pathophysiological characteristics, and the prognostic significance of high MCV using Kaplan–Meier curves and the Cox proportional hazards model. All P-values were two-tailed and a P-value <0.05 was considered statistically significant.

Results

According to ROC curve analysis, the optimal cut-off value of MCV was 93.6 fL. The mean OS was 14.7 months in all 249 EC patients, 10.9 months in patients with MCV >93.6 fL, and 18.8 months in patients with MCV <93.6 fL; the difference is statistically significant (P<0.05). Chi-square test showed that the MCV value was correlated with the N stage of the tumor and the therapeutic effect, indicating that the higher the MCV was, the higher the T stage of the tumor and the worse the therapeutic effect would be (p=0.012 and p <0.01). Multivariate analysis showed that MCV (OR = 1.864, 95% CI: 1.439–2.415) was an independent prognostic factor for OS in EC patients.

Conclusion

High MCV is a poor predictor of OS in patients with advanced EC receiving concurrent chemoradiotherapy.

A three-lncRNA signature of pretreatment biopsies predicts pathological response and outcome in esophageal squamous cell carcinoma with neoadjuvant chemoradiotherapy

BACKGROUND

Current strategies are insufficient to predict pathologically complete response (pCR) for esophageal squamous cell carcinomas (ESCCs) before treatment. Here, we aim to develop a novel long noncoding RNA (lncRNA) signature for pCR and outcome prediction of ESCCs through a multicenter analysis for a Chinese population.

METHODS

Differentially expressed lncRNAs (DELs) between pCRs and less than pCR (

RESULTS

Twelve DELs were identified from Guangzhou cohort and six lncRNAs were verified. Then, a classifier of three lncRNAs (SCAT1, PRKAG2-AS1, and FLG-AS1) was established and achieved a high accuracy with an area under the receiver operating characteristic curve (AUC) of 0.952 in the training cohort, which was well validated in the internal validation cohort and external cohort with the AUCs of 0.856 and 0.817, respectively. Furthermore, the predictive score was identified as the only independent predictor for pCR. Patients with high discriminant score showed a significantly longer overall and relapse-free survival (P < .05).

CONCLUSIONS

We developed the first and applicable three-lncRNA signature of pCR and outcome prediction, which is robust and reproducible in multicenter cohorts for ESCCs with nCRT.

Collapse

Key Words

• esophageal squamous cell carcinoma
• individualized medicine
• lncRNAs
• neoadjuvant chemoradiotherapy
• pathologically complete response

Collapse

MESH Headings Collapse

Grants

• 2017-I2M-1-005 CAMS Innovation Fund for Medical Sciences
• 2016-I2M-1-001 CAMS Innovation Fund for Medical Sciences
• 2016YFC1303201 National Key R&D Program of China
• 81802299 National Natural Science Foundation of China
• 81502514 National Natural Science Foundation of China
• 3332018070 Fundamental Research Funds for the Central Universities
• 2018YFC1312105 National Key Basic Research Development Plan
• 7204291 Beijing Natural Science Foundation
• LC2019B18 Beijing Hope Run Special Fund of Cancer Foundation of China
• National Natural Science Foundation of China
• Fundamental Research Funds for the Central Universities
• Beijing Natural Science Foundation

Collapse

Affiliation(s)

Chaoqi Zhang Department of Thoracic SurgeryNational Cancer CenterNational Clinical Research Center for CancerCancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
Zhihui Zhang Department of Thoracic SurgeryNational Cancer CenterNational Clinical Research Center for CancerCancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
Guochao Zhang Department of Thoracic SurgeryNational Cancer CenterNational Clinical Research Center for CancerCancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
Liyan Xue Department of PathologyNational Cancer CenterNational Clinical Research Center for CancerCancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
Haijun Yang Department of PathologyAnyang Cancer HospitalThe Fourth Affiliated Hospital of Henan University of Science and TechnologyAnyangHenanChina
Yuejun Luo Department of Thoracic SurgeryNational Cancer CenterNational Clinical Research Center for CancerCancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
Xiaoli Zheng Department of radiotherapyThe Affiliated Cancer hospital of Zhengzhou UniversityZhengzhouHenanChina
Yonglei Zhang Department of General SurgeryThe Affiliated Cancer Hospital of Zhengzhou UniversityZhengzhouHenanChina
Yufen Yuan Department of PathologyAnyang Cancer HospitalThe Fourth Affiliated Hospital of Henan University of Science and TechnologyAnyangHenanChina
Ruixue Lei Department of PathologyAnyang Cancer HospitalThe Fourth Affiliated Hospital of Henan University of Science and TechnologyAnyangHenanChina
Zhaoyang Yang Department of PathologyNational Cancer CenterNational Clinical Research Center for CancerCancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
Bo Zheng Department of PathologyNational Cancer CenterNational Clinical Research Center for CancerCancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
Zhen Zhang Biotherapy CenterThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouHenanChina
Le Wang Department of OtologyThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouHenanChina
Yun Che Department of Thoracic SurgeryNational Cancer CenterNational Clinical Research Center for CancerCancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
Sihui Wang Department of Thoracic SurgeryNational Cancer CenterNational Clinical Research Center for CancerCancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
Feng Wang Department of Thoracic SurgeryNational Cancer CenterNational Clinical Research Center for CancerCancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
Lingling Fang Department of Thoracic SurgeryNational Cancer CenterNational Clinical Research Center for CancerCancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
Qingpeng Zeng Department of Thoracic SurgeryNational Cancer CenterNational Clinical Research Center for CancerCancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
Jiagen Li Department of Thoracic SurgeryNational Cancer CenterNational Clinical Research Center for CancerCancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
Shugeng Gao Department of Thoracic SurgeryNational Cancer CenterNational Clinical Research Center for CancerCancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
Qi Xue Department of Thoracic SurgeryNational Cancer CenterNational Clinical Research Center for CancerCancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
Nan Sun Department of Thoracic SurgeryNational Cancer CenterNational Clinical Research Center for CancerCancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
Jie He Department of Thoracic SurgeryNational Cancer CenterNational Clinical Research Center for CancerCancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina

Collapse

RACGAP1 is transcriptionally regulated by E2F3, and its depletion leads to mitotic catastrophe in esophageal squamous cell carcinoma

Background

RACGAP1 has significant involvement in tumorigenesis of cancers, including liver cancer, stomach cancer, and colon cancer. However, the role and the exact mechanism of RACGAP1 in esophageal squamous cell carcinoma (ESCC) has not been explored.

Methods

QPCR and Western blots analysis was performed to analyze the expression of RACGAP1 in ESCC. MTT assays and colony formation assays were performed to explore the functional role of RACGAP1 in ESCC. Cell cycle analysis and immunofluorescence assays were used to investigate the function of RACGAP1 involvement in mitotic catastrophe. At last, we conducted the public datasets mining to explore the expression status and prognosis value of RACGAP1 as well as the correlation between RACGAP1 and E2F3 in various cancers.

Results

The high abnormal expression of RACGAP1 is observed in ESCC and associated with worse clinical outcomes of patients with ESCC. RACGAP1, a novel cell cycle associated gene regulated by E2F3, acts as an oncogenic driver in ESCC cell lines. Notably, for the first time, RACGAP1 depletion induced severe mitotic catastrophe, followed by massive cell death.

Conclusions

Our findings showed the essential role of RACGAP1 in ESCC cancer cell survival and the therapeutic potential of RACGAP1 as a molecular target for ESCC.

A Gene-Expression Predictor for Efficacy of Induction Chemotherapy in Locoregionally Advanced Nasopharyngeal Carcinoma

BACKGROUND

Induction chemotherapy (IC) followed by concurrent chemoradiotherapy is the mainstay treatment for patients with locoregionally advanced nasopharyngeal carcinoma. However, some patients obtain little benefit and experience unnecessary toxicities from IC. We intended to develop a gene-expression signature that can identify beneficiaries of IC.

METHODS

We screened chemosensitivity-related genes by comparing gene-expression profiles of patients with short-term tumor response or nonresponse to IC (n = 95) using microarray analysis. Chemosensitivity-related genes were quantified by digital expression profiling in a training cohort (n = 342) to obtain a gene signature. We then validated this gene signature in the clinical trial cohort (n = 187) and an external independent cohort (n = 240). Tests of statistical significance are 2-sided.

RESULTS

We identified 43 chemosensitivity-related genes associated with the short-term tumor response to IC. In the training cohort, a 6-gene signature was developed that was highly accurate at predicting the short-term tumor response to IC (area under the curve [AUC] = 0.87, sensitivity = 87.5%, specificity = 75.6%). We further found that IC conferred failure-free survival benefits only in patients in the benefit group (hazard ratio [HR] = 0.54, 95% confidence interval [CI] = 0.34 to 0.87; P = .01) and not on those in the no-benefit group (HR = 1.25, 95% CI = 0.62 to 2.51; P = .53). In the clinical trial cohort, the 6-gene signature was also highly accurate at predicting the tumor response (AUC = 0.82, sensitivity = 87.5%, specificity = 71.8%) and indicated failure-free survival benefits. In the external independent cohort, similar results were observed.

CONCLUSIONS

The 6-gene signature can help select beneficiaries of IC and lay a foundation for a more individualized therapeutic strategy for locoregionally advanced nasopharyngeal carcinoma patients.

Clinical Factors to Predict the Response to Concurrent Chemoradiotherapy and Survival in Esophageal Cancer Patients

Background/Aims

Several clinical factors have been used to predict the response for concurrent chemoradiotherapy (CCRT); however, these factors are insufficient for prognostic predictions. We investigated clinical factors to assess whether they could be used to predict the response to CCRT and the survival of patients with esophageal cancer.

Methods

Patients with esophageal cancer underwent CCRT from January 2005 to December 2015. Response to CCRT was classified as progressive disease (PD), stationary disease (SD), partial remission (PR), or complete remission (CR). Factors to predict the response to CCRT and patient survival were subsequently investigated.

Results

A total of 535 esophageal cancer patients underwent CCRT. Four hundred ninety-three patients were followed up, and patient outcomes were investigated. In the adjusted analysis, patients with advanced stage disease (relative risk [RR], 0.28 in stage III and 0.12 in stage IV compared to stage I), poor performance status, circumferential involvement (RR, 0.61), and male sex (RR, 0.31) were less likely to achieve CR. Advanced stage disease (hazard ratio [HR], 1.71 in stage III/IV), poor CCRT response (HR, 2.82 in PR, 4.47 in SD, 4.77 in PD compared to CR), and poor performance status (HR, 1.38 in ECOG 2–4) were found to increase mortality.

Conclusions

Advanced stage disease, poor performance status, male sex, and circumferential involvement were independent predictive factors for a poor response to CCRT. Advanced stage, poor performance status, and poor CCRT response were independent factors for decreased survival.

Sodium hydrogen exchanger 9 NHE9 (SLC9A9) and its emerging roles in neuropsychiatric comorbidity

Variations in SLC9A9 gene expression and protein function are associated with multiple human diseases, which range from Attention-deficit/hyperactivity disorder (ADHD) to glioblastoma multiforme. In an effort to determine the full spectrum of human disease associations with SLC9A9, we performed a systematic review of the literature. We also review SLC9A9's biochemistry, protein structure, and function, as well as its interacting partners with the goal of identifying mechanisms of disease and druggable targets. We report gaps in the literature regarding the genes function along with consistent trends in disease associations that can be used to further research into treating the respective diseases. We report that SLC9A9 has strong associations with neuropsychiatric diseases and various cancers. Interestingly, we find strong overlap in SLC9A9 disease associations and propose a novel role for SLC9A9 in neuropsychiatric comorbidity. In conclusion, SLC9A9 is a multifunctional protein that, through both its endosome regulatory function and its protein-protein interaction network, has the ability to modulate signaling axes, such as the PI3K pathway, among others.

Development and validation of a radiomics signature on differentially expressed features of 18F-FDG PET to predict treatment response of concurrent chemoradiotherapy in thoracic esophagus squamous cell carcinoma

BACKGROUND AND PURPOSE

To investigate potential image markers for early prediction of treatment response on thoracic esophagus squamous cell carcinoma (ESCC) treated with concurrent chemoradiotherapy (CCRT).

MATERIALS AND METHODS

159 thoracic ESCC patients enrolled from two institutions were divided into training and validation sets. A total of 944 radiomics features were extracted from pretreatment ¹⁸F-FDG PET images. We first performed the inter-observer reproducibility test in 10 pairs of patients (responders vs. nonresponders), and the limma package was used to identify differentially expressed features (DEFs). Then the least absolute shrinkage and selection operator (LASSO) logistic regression model with 10-fold cross-validation was used to construct a treatment response related radiomics signature. Finally, the performance was assessed in both sets with receiver operating characteristic (ROC) curves and Kaplan-Meier analysis.

RESULTS

After the inter-observer test, 691 features were considered reproducible and been retained (ICC > 0.9). 61 DEFs were selected from limma and entered into the LASSO logistic regression model. The radiomics signature was significantly associated with treatment response in the training (p < 0.001) and validation set (p = 0.026), which achieved area under curve (AUC) values of 0.844 and 0.835, respectively. Delong test results of two ROCs showed no significant difference (p = 0.918). The cut-off value of the radiomics signature could successfully divide patients into high-risk and low-risk groups in both sets.

CONCLUSION

This study indicated that the proposed radiomics signature could be a useful image marker to predict the therapeutic response of thoracic ESCC patients treated with CCRT.

The prognostic role of FZD6 in esophageal squamous cell carcinoma patients

BACKGROUND

Esophageal squamous cell carcinoma (ESCC) is a kind of cancer with heterogeneous biological characteristics, which is affected by a complex network of gene interactions. Identification of molecular biomarkers paves the way for individualized therapy based on gene expression profiles, which can overcome the heterogeneity of ESCC.

METHODS

In this study, GSE20347, GSE23400 and GSE45670 datasets were retrieved from Gene Expression Omnibus (GEO) database, and the overlapping differentially expressed genes (DEGs) in three datasets were screened. Then the overlapping DEGs function was annotated by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway-enrichment analysis. The prognostic value of the top five KEGG pathway-related genes were further validated in The Cancer Genome Atlas (TCGA) database. After extensive statistical analysis, four genes (CDC25B, CXCL8, FZD6 and MCM4) were identified as potential prognostic markers. Among the four candidate genes, the prognostic value of FZD6 in ESCC patients has not been evaluated. Therefore, we finally used immunohistochemistry method to evaluate the effect of FZD6 on the prognosis of patients with ESCC. Additionally, we detected the expression level of FZD6 in ESCC cell line and normal esophageal epithelial cell line, and observed the cell viability of ESCC cell line after FZD6 knockdown.

RESULTS

The results showed that the overexpression of FZD6 predicted poor overall survival (OS) (P = 0.005) and progression-free survival (PFS) (P = 0.004) in ESCC patients. COX regression analysis showed that N stage (P = 0.026) and FZD6 expression level (P = 0.001) were independent prognostic factors of OS for ESCC patients. Furthermore, compared with normal esophageal epithelial cell line, the up-regulation of FZD6 was detected in ESCC cell line. Knockdown of FZD6 could significantly inhibit the proliferation of ESCC cells (P < 0.001).

CONCLUSION

CDC25B, CXCL8, FZD6 and MCM4 were screened as candidate genes for prognosis assessment of patients with ESCC. The prognostic role of FZD6 in ESCC patients was confirmed in current study.

Integrated analysis highlights multiple long non‑coding RNAs and their potential roles in the progression of human esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is a prevalent aggressive malignant tumor with poor prognosis. Investigations into the molecular changes that occur as a result of the disease, as well as identification of novel biomarkers for its diagnosis and prognosis, are urgently required. Long non‑coding RNAs (lncRNAs) have been reported to play a critical role in tumor progression. The present study performed data mining analyses for ESCC via an integrated study of accumulated datasets and identification of the differentially expressed lncRNAs from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. The identified intersection of differentially expressed genes (lncRNAs, miRNAs and mRNAs) in ESCC tissues between the GEO and TCGA datasets was investigated. Based on these intersected lncRNAs, the present study constructed a competitive endogenous RNA (ceRNA) network of lncRNAs in ESCC. A total of 81 intersection lncRNAs were identified; 67 of these were included in the ceRNA network. Functional analyses revealed that these 67 key lncRNAs primarily dominated cellular biological processes. The present study then analyzed the associations between the expression levels of these 67 key lncRNAs and the clinicopathological characteristics of the ESCC patients, as well as their survival time using TCGA. The results revealed that 31 of these lncRNAs were associated with tumor grade, tumor‑node‑metastasis (TNM) stage and lymphatic metastasis status (P<0.05). In addition, 15 key lncRNAs were demonstrated to be associated with survival time (P<0.05). Finally, 5 key lncRNAs were selected for validation of their expression levels in 30 patients newly diagnosed with ESCC via reverse transcription‑quantitative PCR (RT‑qPCR). The results suggested that the fold changes in the trends of up‑ and downregulation between GEO, TCGA and RT‑qPCR were consistent. In addition, it was also demonstrated that a select few of these 5 key lncRNAs were significantly associated with TNM stage and lymph node metastasis (P<0.05). The results of the clinically relevant analysis and the aforementioned bioinformatics were similar, hence proving that the bioinformatics analysis used in the present study is credible. Overall, the results from the present study may provide further insight into the functional characteristics of lncRNAs in ESCC through bioinformatics integrative analysis of the GEO and TCGA datasets, and reveal potential diagnostic and prognostic biomarkers for ESCC.

CACNA2D3 Enhances the Chemosensitivity of Esophageal Squamous Cell Carcinoma to Cisplatin via Inducing Ca2+-Mediated Apoptosis and Suppressing PI3K/Akt Pathways

Resistance to platinum-based combination chemotherapy is the main cause of poor prognosis in patients with advanced esophageal squamous cell carcinoma (ESCC). Previously, we showed that CACNA2D3 (voltage-dependent subunit alpha 2 delta 3 of a calcium channel complex) was significantly downregulated and functioned as a tumor suppressor in ESCC, but its role in the chemosensitivity of ESCC to cisplatin remained unknown. Here, we found that the expression of CACNA2D3 was significantly associated with poor platinum response in ESCC patients from the Gene Expression Omnibus database. Overexpression of CACNA2D3 increased sensitivity to cisplatin in ESCC in vitro, whereas knockdown of CACNA2D3 increased cisplatin resistance. CACNA2D3 promoted cisplatin-induced apoptosis by modulating intracellular Ca²⁺ stores. In vivo experiments further showed that overexpression of CACNA2D3 enhanced cisplatin anti-tumor effects in a xenograft mouse model. CACNA2D3 overexpression also resulted in the attenuation of PI3K and Akt phosphorylation. Treatment with the PI3K/Akt inhibitor LY294002 restored the chemosensitivity of CACAN2D3-knockdown cells to cisplatin. In conclusion, the results of the current study indicate that CACAN2D3 enhances the chemosensitivity of ESCC to cisplatin via inducing Ca²⁺-mediated apoptosis and suppressing PI3K/Akt pathways. Therefore, regulating the expression of CACNA2D3 is a potential new strategy to increase the efficacy of cisplatin in ESCC patients.

Batch adjustment by reference alignment (BARA): Improved prediction performance in biological test sets with batch effects

Many biological data acquisition platforms suffer from inadvertent inclusion of biologically irrelevant variance in analyzed data, collectively termed batch effects. Batch effects can lead to difficulties in downstream analysis by lowering the power to detect biologically interesting differences and can in certain instances lead to false discoveries. They are especially troublesome in predictive modelling where samples in training sets and test sets are often completely correlated with batches. In this article, we present BARA, a normalization method for adjusting batch effects in predictive modelling. BARA utilizes a few reference samples to adjust for batch effects in a compressed data space spanned by the training set. We evaluate BARA using a collection of publicly available datasets and three different prediction models, and compare its performance to already existing methods developed for similar purposes. The results show that data normalized with BARA generates high and consistent prediction performances. Further, they suggest that BARA produces reliable performances independent of the examined classifiers. We therefore conclude that BARA has great potential to facilitate the development of predictive assays where test sets and training sets are correlated with batch.

miR-424 coordinates multilayered regulation of cell cycle progression to promote esophageal squamous cell carcinoma cell proliferation

BACKGROUND

Dysregulation of the cell cycle has been implicated in esophageal squamous cell carcinoma (ESCC) progression. This study aimed to evaluate the role of miR-424 in cell cycle regulation and ESCC proliferation.

METHODS

The role of miR-424 in cell proliferation was evaluated in vitro and in vivo. Transcriptional activation of miR-424 was determined using chromatin immunoprecipitation, and binding of miR-424 to targets was verified using miRNA ribonucleoprotein complex immunoprecipitation.

FINDINGS

miR-424 was upregulated and correlated with poor survival in ESCC patients. Repression or overexpression of miR-424 respectively decreased or increased ESCC cell proliferation in vitro and in vivo. miR-424 expression is transcriptionally regulated by E2F1 and increased during G1/S transition. Knockdown or overexpression of miR-424 respectively inhibited or promoted both G1/S and G2/M cell cycle transitions in ESCC cells, and these effects were mediated by two newly identified miR-424 targets, PRKCD and WEE1, respectively. Consequently, elevation of PRKCD by miR-424 knockdown led to enhanced stability of the p21Cip1 protein via increased activation of PRKCD and downstream p38 MAPK and JNK signaling to block CDK2 activation and G1/S transition, while elevated WEE1 maintained CDC2 in an inactive state to block G2/M transition. However, circLARP4 could sponge the binding of miR-424 to PRKCD, thus compromising the regulation of G1/S progression by miR-424.

INTERPRETATION

miR-424 coordinates a previously unknown, multilayered regulation of ESCC cell cycle progression to promote ESCC proliferation, and may be used as a novel prognostic marker and an effective therapeutic target for ESCCs. FUND: National Natural Science Foundation of China.

Evaluation of Prognostic Factors for Esophageal Squamous Cell Carcinoma Treated with Neoadjuvant Chemoradiotherapy Followed by Surgery

BACKGROUND

Intensive trimodality therapy is needed for locally advanced esophageal squamous cell carcinoma (ESCC). However, some patients develop recurrence and die of cancer even after trimodality therapy.

METHODS

We evaluated prognostic factors based on data from 125 patients with ESCC who underwent neoadjuvant chemoradiotherapy (NCRT) comprising concurrent chemotherapy and 40 Gy of radiation, followed by curative-intent esophagectomy.

RESULTS

Thirty-four (27.2%) patients achieved a pathological complete response (pCR) after NCRT. The 5-year recurrence-free (RFS) and overall survival (OS) rates of all patients were 49.2 and 52.9%, respectively, and were significantly better for patients with pCR than without pCR (p = 0.01 and 0.02, respectively). Univariate and multivariate analyses selected performance status [PS 0 vs. 1: hazard ratio (HR) 2.05; 95% confidence interval (CI) 1.30-4.84; p = 0.01] and ypN (0 vs. 1: HR 2.33; 95% CI 1.12-4.84; p = 0.02; 0 vs. 2/3: HR 3.73; 95% CI 1.68-8.28; p = 0.001) as independent covariates for RFS. Furthermore, PS (0 vs. 1; HR 2.94; 95% CI 1.51-5.72; p = 0.002) and ypN (0 vs. 1; HR 2.26; 95% CI 1.09-4.69; p = 0.03; 0 vs. 2/3: HR 3.90; 95% CI 1.79-8.48; p = 0.001) were also independent covariates for OS.

CONCLUSIONS

Performance status 1 and ypN+ were significantly associated with a poor prognosis after trimodality therapy for ESCC.

A genome-wide analysis of long noncoding RNA profile identifies differentially expressed lncRNAs associated with Esophageal cancer

Esophageal cancer is one of the most common cancers and a leading cause of cancer‐related death worldwide. However, the mechanism of esophageal cancer pathogenesis remains poorly understood. Long noncoding RNAs (lncRNAs) dysregulation have been reported to involve in various human cancers, which highlights the potential of lncRNAs used as novel biomarkers for cancer diagnosis. Although more efforts have been made to identify novel lncRNAs signature in esophageal cancer, the expression pattern, prognostic value, and biological function of most lncRNAs in esophageal cancer still need to be systematically investigated. In this study, we comprehensively analyzed the expression profile of lncRNAs in more than 200 esophageal cancer patients tissue samples from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). We identified thousands of lncRNAs are differentially expressed in esophageal cancer tissues, and many of those lncRNAs expression are associated with patients overall survival or recurrence‐free survival time. Moreover, copy number variation analyses revealed that genomic loci copy number amplification or deletion might contribute to these lncRNAs dysregulation. Among these lncRNAs, DUXAP8 and LINC00460 were significantly upregulated, and GO enrichment analyses indicated that the two lncRNAs associated protein‐coding genes involve with many known biological processes, such as cell cycle and cell‐cell adherens junction. Further experimental validation revealed that knockdown of DUXAP8 could impair esophageal cancer cells proliferation and invasion in vitro. Taken together, our findings identified more aberrantly expressed lncRNAs in esophageal cancer that may provide a useful resource for identifying novel esophageal cancer associated lncRNAs.

Prognostic gene expression profiling in esophageal cancer: a systematic review

Background

Individual variability in prognosis of esophageal cancer highlights the need for advances in personalized therapy. This systematic review aimed at elucidating the prognostic role of gene expression profiles and at identifying gene signatures to predict clinical outcome.

Methods

A systematic search of the Medline, Embase and the Cochrane library databases (2000-2015) was performed. Articles associating gene expression profiles in patients with esophageal adenocarcinoma or squamous cell carcinoma to survival, response to chemo(radio)therapy and/or lymph node metastasis were identified. Differentially expressed genes and gene signatures were extracted from each study and combined to construct a list of prognostic genes per outcome and histological tumor type.

Results

This review includes a total of 22 studies. Gene expression profiles were related to survival in 9 studies, to response to chemo(radio)therapy in 7 studies, and to lymph node metastasis in 9 studies. The studies proposed many differentially expressed genes. However, the findings were heterogeneous and only 12 (ALDH1A3, ATR, BIN1, CSPG2, DOK1, IFIT1, IFIT3, MAL, PCP4, PHB, SPP1) of the 1.112 reported genes were identified in more than 1 study. Overall, 16 studies reported a prognostic gene signature, which was externally validated in 10 studies.

Conclusion

This systematic review shows heterogeneous findings in associating gene expression with clinical outcome in esophageal cancer. Larger validated studies employing RNA next-generation sequencing are required to establish gene expression profiles to predict clinical outcome and to select optimal personalized therapy.

Prediction of pathologic responders to neoadjuvant chemoradiotherapy by diffusion-weighted magnetic resonance imaging in locally advanced esophageal squamous cell carcinoma: a prospective study

This study aims to investigate the role of diffusion-weighted magnetic resonance imaging (DW-MRI) in ESCC patients receiving neoadjuvant concurrent chemoradiotherapy (CCRT), and the efficacy of apparent diffusion coefficient (ADC) values in predicting pathologic response to neoadjuvant CCRT. Twenty-eight locally advanced ESCC patients treated with neoadjuvant CCRT followed by radical resection were prospectively enrolled. DW-MRI was recommended to be performed within 2 weeks before and 4-6 weeks after neoadjuvant CCRT. The calculated ADCs pre- (ADC1) and post- (ADC2) neoadjuvant CCRT, the definite (ΔADC) and percentage changes (ΔADC%) were analyzed for the efficacy of predicting pathologic response to neoadjuvant CCRT. Twenty patients had been identified as responders (tumor regression grade 1-2). Among them, ADC2 (3.02 ± 0.84 vs. 2.12 ± 0.44 × 10-3 mm2/s, P = 0.001) and ΔADC (1.22 ± 0.78 vs 0.64 ± 0.26 × 10-3 mm2/s, P = 0.007) were significantly higher than those of nonresponders (tumor regression grade: 3-5). Receiver operating characteristic analysis revealed that ADC2 exhibited an overall accuracy of in 71.4% in predicting pathologic response, with a sensitivity of 60.0%, a specificity of 100%, a positive predictive value of 100%, and a negative predictive value of 50.0%, when 3.04 × 10-3 mm2/s was used as the cutoff value. ADC value could be useful in predicting pathologic response to neoadjuvant CCRT in ESCC patients. High postneoadjuvant CCRT ADC is a predictive indicator for good response.

Construction of an oesophageal cancer-specific ceRNA network based on miRNA, lncRNA, and mRNA expression data

AIM

To explore the expression profiles of microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and mRNAs in oesophageal squamous cell carcinoma (ESCC) in order to construct an oesophageal cancer-specific competing endogenous RNA (ceRNA) network.

METHODS

In this work, the expression data of miRNAs, lncRNAs, and mRNAs in ESCC were obtained. An oesophageal cancer-specific ceRNA network was then constructed and investigated.

RESULTS

CeRNAs have the ability to reduce the targeting activity of miRNAs, leading to the de-repression of specific mRNAs with common miRNA response elements. CeRNA interactions have a critical effect in gene regulation and cancer development.

CONCLUSION

This study suggests a novel perspective on potential oesophageal cancer mechanisms as well as novel pathways for modulating ceRNA networks for treating cancers.