A three-gene signature and clinical outcome in esophageal squamous cell carcinoma

Network pharmacology and molecular docking reveal the mechanisms of curcumin activity against esophageal squamous cell carcinoma

Background: Curcumin (CUR), an effective traditional Chinese medicinal extract, displays good anti-cancer activity against various cancers. Nevertheless, the impacts and fundamental mechanisms of CUR to treat esophageal squamous cell carcinoma (ESCC) yet to be comprehensively clarified. This study examined the suppressive impacts of CUR on ESCC. Methods: For a comprehensive understanding of the effect of CUR in ESCC. The CUR targets and ESCC-related genes were identified respectively, and the intersection targets between CUR and ESCC were acquired. Then, we examined the intersection targets and discovered genes that were expressed differently in ESCC. Using DAVID, enrichment analyses were conducted on the targets of CUR-ESCC. The STRING database and Cytoscape v.3.9.1 were utilized to build networks for protein-protein interaction (PPI) and drug-target-pathway. Furthermore, the interactions between CUR and its core targets were confirmed by molecular docking studies. To confirm the effects of CUR on ESCC cells, in vitro experiments were finally conducted. Results: Overall, 47 potential CUR targets for ESCC treatment were identified. The KEGG pathway enrichment analysis identified 61 signaling pathways, primarily associated with the FoxO signaling, the cell cycle, cellular senescence, the IL-17 signaling pathway which play important roles in ESCC progression. In the PPI network and the docking results identified CHEK1 and CDK6 as the core targets that positively associated with ESCC survival. CUR arrested ESCC cells at the G2/M and S phases, as shown by flow cytometry. Colony formation and CCK8 assays showed that CUR can inhibit the proliferative ability of ESCC cells. The Transwell invasion results validated that CUR can significantly inhibit the invasion rates of ESCC cells. Conclusion: Collectively, these findings indicate that CUR exhibits pharmacological effects on multiple targets and pathways in ESCC.

High NANOG expression correlates with worse patients' survival in esophageal adenocarcinoma

BACKGROUND

Patients diagnosed with esophageal cancer demonstrate a low overall survival even despite the established multimodal therapy as the current standard of care. Therefore, further biomarkers for patients with high-risk and additional therapy options are needed. NANOG is a transcription factor, which can be found in stem cells and is known to support tumorigenesis.

METHODS

Six hundred sixty patients with esophageal adenocarcinoma, who were operated at the University of Cologne with a curative intent, were included. Immunohistochemical stainings for NANOG were performed. The study population was divided into NANOG-positive and -negative subgroups.

RESULTS

Positive NANOG expression correlates significantly with worse overall survival (p = 0.002) and could be confirmed as an independent risk factor for worse patient survival in multivariate analysis (HR = 1.40, 95%CI = 1.09-1.80, p = 0.006). This effect could be detected in the subgroup of primarily operated patients, but not in patients after neoadjuvant therapy.

CONCLUSIONS

We describe a NANOG-positive subgroup of patients with esophageal cancer, who exhibit worse overall survival in a large patient cohort. This discovery suggests the potential use of NANOG as a biomarker for both intensified therapy and stricter follow-up regimes. Additionally, NANOG-positive stem cell-like cancer cells could be used as a new antitumoral treatment target if validated in mechanistic and clinical studies.

Spatial analysis of stromal signatures identifies invasive front carcinoma-associated fibroblasts as suppressors of anti-tumor immune response in esophageal cancer

BACKGROUND

Increasing evidence indicates that the tumor microenvironment (TME) is a crucial determinant of cancer progression. However, the clinical and pathobiological significance of stromal signatures in the TME, as a complex dynamic entity, is still unclear in esophageal squamous cell carcinoma (ESCC).

METHODS

Herein, we used single-cell transcriptome sequencing data, imaging mass cytometry (IMC) and multiplex immunofluorescence staining to characterize the stromal signatures in ESCC and evaluate their prognostic values in this aggressive disease. An automated quantitative pathology imaging system determined the locations of the lamina propria, stroma, and invasive front. Subsequently, IMC spatial analyses further uncovered spatial interaction and distribution. Additionally, bioinformatics analysis was performed to explore the TME remodeling mechanism in ESCC. To define a new molecular prognostic model, we calculated the risk score of each patient based on their TME signatures and pTNM stages.

RESULTS

We demonstrate that the presence of fibroblasts at the tumor invasive front was associated with the invasive depth and poor prognosis. Furthermore, the amount of α-smooth muscle actin (α-SMA)⁺ fibroblasts at the tumor invasive front positively correlated with the number of macrophages (MØs), but negatively correlated with that of tumor-infiltrating granzyme B⁺ immune cells, and CD4⁺ and CD8⁺ T cells. Spatial analyses uncovered a significant spatial interaction between α-SMA⁺ fibroblasts and CD163⁺ MØs in the TME, which resulted in spatially exclusive interactions to anti-tumor immune cells. We further validated the laminin and collagen signaling network contributions to TME remodeling. Moreover, compared with pTNM staging, a molecular prognostic model, based on expression of α-SMA⁺ fibroblasts at the invasive front, and CD163⁺ MØs, showed higher accuracy in predicting survival or recurrence in ESCC patients. Regression analysis confirmed this model is an independent predictor for survival, which also identifies a high-risk group of ESCC patients that can benefit from adjuvant therapy.

CONCLUSIONS

Our newly defined biomarker signature may serve as a complement for current clinical risk stratification approaches and provide potential therapeutic targets for reversing the fibroblast-mediated immunosuppressive microenvironment.

The combination of novel immune checkpoints HHLA2 and ICOSLG: A new system to predict survival and immune features in esophageal squamous cell carcinoma

Studies on immune checkpoint inhibitors targeting B7-CD28 family pathways in esophageal squamous cell carcinoma (ESCC) have shown promising results. However, a comprehensive understanding of B7-CD28 family members in ESCC is still limited. This study aimed to construct a novel B7-CD28 family-based prognosis system to predict survival in patients with ESCC. We collected 179 cases from our previously published microarray data and 86 cases with qPCR data. Specifically, 119 microarray data (GSE53624) were used as a training set, whereas the remaining 60 microarray data (GSE53622), all 179 microarray data (GSE53625) and an independent cohort with 86 qPCR data were used for validation. The underlying mechanism and immune landscape of the system were also explored using bioinformatics and immunofluorescence. We examined 13 well-defined B7-CD28 family members and identified 2 genes (ICSOLG and HHLA2) with the greatest prognostic value. A system based on the combination HHLA2 and ICOSLG (B7-CD28 signature) was constructed to distinguish patients as high- or low-risk of an unfavorable outcome, which was further confirmed as an independent prognostic factor. As expected, the signature was well validated in the entire cohort and in the independent cohort, as well as in different clinical subgroups. The signature was found to be closely related to immune-specific biological processes and pathways. Additionally, high-risk group samples demonstrated high infiltration of Tregs and fibroblasts and distinctive immune checkpoint panels. Collectively, we built the first, practical B7-CD28 signature for ESCC that could independently identify high-risk patients. Such information may help inform immunotherapy-based treatment decisions for patients with ESCC.

A Novel DNA Damage Repair-Related Gene Signature for Predicting Glioma Prognosis

Background

Glioma is one of the most prevalent tumors in the central nervous system of adults and shows a poor prognosis. This study aimed to develop a DNA damage repair (DDR)-related gene signature to evaluate the prognosis of glioma patients.

Methods

Differentially expressed genes (DEGs) were extracted based on 276 DDR genes. Then, a gene signature was developed for the survival prediction in glioma patients by means of univariate, multivariate Cox, and least absolute shrinkage and selector operation (Lasso) analyses. After analyzing the clinical parameters, a nomogram was constructed and assessed. A total of 693 gliomas from the Chinese Glioma Genome Atlas (CGGA) were used for external validation. In addition, we used glioma tumor tissues for qPCR experiment to verify.

Results

A 12-DDR-related gene signature was identified from the 75 DEGs to stratify the survival risk of glioma patients. The overall survival of high-risk group was significantly shorter than that of low-risk group (P < 0.001). Besides, according to the risk score assessment, patients in high- or low-risk group also had significant correlations with clinicopathological parameters, including age (P < 0.01), grade (P < 0.001), IDH status (P < 0.001) and 1p19q codeletion status (P < 0.001). The nomogram provided favorable C-index and calibration plots. The C-index of training set and verification set was 0.761 and 0.746, respectively, and the calibration curve also showed that both training set and verification set were close to the standard curve. The qPCR results showed that there were significant differences in the expression of some typical DDR-related genes in tumor tissues and paracancer tissues (P_(WEE1)=0.0002, P_(RECQL)=0.0117, P_(RPA1)=0.021, P_(RRM1)=0.0035, P_(PARP4)=0.0006, P_(ELOA)=0.0023).

Conclusion

Our study developed a novel 12 DDR-related gene signature as a practical prognostic predictor for glioma patients. A nomogram combining the signature and clinical parameters was established as an individual clinical prediction tool.

Development and Validation of a Prognostic Gene Signature Correlated With M2 Macrophage Infiltration in Esophageal Squamous Cell Carcinoma

Background

Esophageal squamous cell carcinoma (ESCC) is the most common type of esophageal cancer and the seventh most prevalent cause of cancer-related death worldwide. Tumor microenvironment (TME) has been confirmed to play an crucial role in ESCC progression, prognosis, and the response to immunotherapy. There is a need for predictive biomarkers of TME-related processes to better prognosticate ESCC outcomes.

Aim

To identify a novel gene signature linked with the TME to predict the prognosis of ESCC.

Methods

We calculated the immune/stromal scores of 95 ESCC samples from The Cancer Genome Atlas (TCGA) using the ESTIMATE algorithm, and identified differentially expressed genes (DEGs) between high and low immune/stromal score patients. The key prognostic genes were further analyzed by the intersection of protein–protein interaction (PPI) networks and univariate Cox regression analysis. Finally, a risk score model was constructed using multivariate Cox regression analysis. We evaluated the associations between the risk score model and immune infiltration via the CIBERSORT algorithm. Moreover, we validated the signature using the Gene Expression Omnibus (GEO) database. Within the ten gene signature, five rarely reported genes were further validated with quantitative real time polymerase chain reaction (qRT-PCR) using an ESCC tissue cDNA microarray.

Results

A total of 133 up-regulated genes were identified as DEGs. Ten prognostic genes were selected based on intersection analysis of univariate COX regression analysis and PPI, and consisted of C1QA, C1QB, C1QC, CD86, C3AR1, CSF1R, ITGB2, LCP2, SPI1, and TYROBP (HR>1, p<0.05). The expression of 9 of these genes in the tumor samples were significantly higher compared to matched adjacent normal tissue based on the GEO database (p<0.05). Next, we assessed the ability of the ten-gene signature to predict the overall survival of ESCC patients, and found that the high-risk group had significantly poorer outcomes compared to the low-risk group using univariate and multivariate analyses in the TCGA and GEO cohorts (HR=2.104, 95% confidence interval:1.343-3.295, p=0.001; HR=1.6915, 95% confidence interval:1.053-2.717, p=0.0297). Additionally, receiver operating characteristic (ROC) curve analysis demonstrated a relatively sensitive and specific profile for the signature (1-, 2-, 3-year AUC=0.672, 0.854, 0.81). To identify the basis for these differences in the TME, we performed correlation analyses and found a significant positive correlation with M1 and M2 macrophages and CD8+ T cells, as well as a strong correlation to M2 macrophage surface markers. A nomogram based on the risk score and select clinicopathologic characteristics was constructed to predict overall survival of ESCC patients. For validation, qRT-PCR of an ESCC patient cDNA microarray was performed, and demonstrated that C1QA, C3AR1, LCP2, SPI1, and TYROBP were up-regulated in tumor samples and predict poor prognosis.

Conclusion

This study established and validated a novel 10-gene signature linked with M2 macrophages and poor prognosis in ESCC patients. Importantly, we identified C1QA, C3AR1, LCP2, SPI1, and TYROBP as novel M2 macrophage-correlated survival biomarkers. These findings may identify potential targets for therapy in ESCC patients.

Nanog is a promising chemoresistant stemness marker and therapeutic target by iron chelators for esophageal cancer

Esophageal cancer is a disease showing poor prognosis. Although combination chemotherapy using cisplatin (CDDP) and 5-fluorouracil is standard for unresectable esophageal cancer, the response rate is 35%. Cancer stem cells (CSCs) and inflammation are reportedly responsible for the poor prognosis of esophageal cancer. However, comprehensive analyses have not been conducted and proposals for progress remain lacking. Iron is known to be a key factor in the stemness of CSCs. Our study focused on the therapeutic potential of iron control using iron chelators for CSCs in esophageal cancer. Among 134 immunohistochemically analyzed cases, Nanog expression was high in 98 cases and low in 36 cases. High Nanog expression correlated with low overall and disease-free survivals. The iron chelators deferasirox (DFX) and SP10 suppressed the proliferation and expression of stemness markers in TE8 and OE33 cells. DFX and SP10 did not induce compensatory interleukin (IL)-6 secretion, although CDDP did result in high induction. Moreover, BBI608 and SSZ, as other CSC-targeting drugs, could not suppress the expression of stemness markers. Overall, Nanog expression appears related to poor prognosis in esophageal cancer patients, and inhibition of stemness and compensatory IL-6 secretion by iron chelators may offer a novel therapeutic strategy for esophageal cancer.

STAT3β Enhances Sensitivity to Concurrent Chemoradiotherapy by Inducing Cellular Necroptosis in Esophageal Squamous Cell Carcinoma

Concurrent chemoradiotherapy (CCRT), especially platinum plus radiotherapy, is considered to be one of the most promising treatment modalities for patients with advanced esophageal cancer. STAT3β regulates specific target genes and inhibits the process of tumorigenesis and development. It is also a good prognostic marker and a potential marker for response to adjuvant chemoradiotherapy (ACRT). We aimed to investigate the relationship between STAT3β and CCRT. We examined the expression of STAT3α and STAT3β in pretreatment tumor biopsies of 105 ESCC patients who received CCRT by immunohistochemistry. The data showed that ESCC patients who demonstrate both high STAT3α expression and high STAT3β expression in the cytoplasm have a significantly better survival rate, and STAT3β expression is an independent protective factor (HR = 0.424, p = 0.003). Meanwhile, ESCC patients with high STAT3β expression demonstrated a complete response to CCRT in 65 patients who received platinum plus radiation therapy (p = 0.014). In ESCC cells, high STAT3β expression significantly inhibits the ability of colony formation and cell proliferation, suggesting that STAT3β enhances sensitivity to CCRT (platinum plus radiation therapy). Mechanistically, through RNA-seq analysis, we found that the TNF signaling pathway and necrotic cell death pathway were significantly upregulated in highly expressed STAT3β cells after CCRT treatment. Overall, our study highlights that STAT3β could potentially be used to predict the response to platinum plus radiation therapy, which may provide an important insight into the treatment of ESCC.

Identification of DNA repair-related genes predicting pathogenesis and prognosis for liver cancer

Background

Liver cancer (LC) is one of the most fatal cancers throughout the world. More efficient and sensitive gene signatures that could accurately predict survival in LC patients are vitally needed to promote a better individualized and effective treatment.

Material/methods

422 LC and adjacent normal tissues with both RNA-Seq and clinical data in TCGA were embedded in our study. Gene set enrichment analysis (GSEA) was applied to identify genes and hallmark gene sets that are more valuable for liver cancer therapy. Cox regression analysis was used to identify genes related to overall survival (OS) and build the prediction model. cBioPortal database was used to examine the alterations of the panel mRNA signature. ROC curves and Kaplan–Meier curves were used to validate the prediction model. Besides, the expression of the genes in the model were validated using quantitative real-time PCR in clinical tissue specimens.

Results

The panel of DNA repair-related mRNA signature consisted of seven mRNAs: RFC4 (replication factor C subunit 4), ZWINT (ZW10 interacting kinetochore protein), UPF3B (UPF3B regulator of nonsense mediated mRNA decay), NCBP2 (nuclear cap binding protein subunit 2), ADA (adenosine deaminase), SF3A3 (splicing factor 3a subunit 3) and GTF2H1 (general transcription factor IIH subunit 1). On-line analysis of cBioPortal database found that the expression of the panel mRNA has a wide variation ranging from 7 to 10%. All the mRNAs were significantly upregulated in LC tissues compared to normal tissues (P < 0.05). The risk model is closely related to the OS of LC patients. The hazard ratio (HR) is 2.184 [95% CI (confidence interval) 1.523–3.132] and log-rank P-value < 0.0001. For clinical specimen validation, we found that all of the genes in the model upregulated in liver cancer tissues versus normal liver tissues, which was consistent with the results predicted.

Conclusions

Our study demonstrated a mRNA signature including seven mRNA for prognosis prediction of LC. This panel gene signature provides a new criterion for accurate diagnosis and therapeutic target of LC.

Identification of a Ten-Gene Signature of DNA Damage Response Pathways with Prognostic Value in Esophageal Squamous Cell Carcinoma

Molecular prognostic signatures are critical for treatment decision-making in esophageal squamous cell cancer (ESCC), but the robustness of these signatures is limited. The aberrant DNA damage response (DDR) pathway may lead to the accumulation of mutations and thus accelerate tumor progression in ESCC. Given this, we applied the LASSO Cox regression to the transcriptomic data of DDR genes, and a prognostic DDR-related gene expression signature (DRGS) consisting of ten genes was constructed, including PARP3, POLB, XRCC5, MLH1, DMC1, GTF2H3, PER1, SMC5, TCEA1, and HERC2. The DRGS was independently associated with overall survival in both training and validation cohorts. The DRGS achieved higher accuracy than six previously reported multigene signatures for the prediction of prognosis in comparable cohorts. Furtherly, a nomogram incorporating DRGS and clinicopathological features showed improved predicting performance. Taken together, the DRGS was identified as a novel, robust, and effective prognostic indicator, which may refine the scheme of risk stratification and management in ESCC patients.

Identification of a Transcriptomic Prognostic Signature by Machine Learning Using a Combination of Small Cohorts of Prostate Cancer

Determining which treatment to provide to men with prostate cancer (PCa) is a major challenge for clinicians. Currently, the clinical risk-stratification for PCa is based on clinico-pathological variables such as Gleason grade, stage and prostate specific antigen (PSA) levels. But transcriptomic data have the potential to enable the development of more precise approaches to predict evolution of the disease. However, high quality RNA sequencing (RNA-seq) datasets along with clinical data with long follow-up allowing discovery of biochemical recurrence (BCR) biomarkers are small and rare. In this study, we propose a machine learning approach that is robust to batch effect and enables the discovery of highly predictive signatures despite using small datasets. Gene expression data were extracted from three RNA-Seq datasets cumulating a total of 171 PCa patients. Data were re-analyzed using a unique pipeline to ensure uniformity. Using a machine learning approach, a total of 14 classifiers were tested with various parameters to identify the best model and gene signature to predict BCR. Using a random forest model, we have identified a signature composed of only three genes (JUN, HES4, PPDPF) predicting BCR with better accuracy [74.2%, balanced error rate (BER) = 27%] than the clinico-pathological variables (69.2%, BER = 32%) currently in use to predict PCa evolution. This score is in the range of the studies that predicted BCR in single-cohort with a higher number of patients. We showed that it is possible to merge and analyze different small and heterogeneous datasets altogether to obtain a better signature than if they were analyzed individually, thus reducing the need for very large cohorts. This study demonstrates the feasibility to regroup different small datasets in one larger to identify a predictive genomic signature that would benefit PCa patients.

Prognostic significance of C-MYC dysregulation in esophageal squamous cell carcinoma: a meta-analysis

Aim: The clinicopathological and prognostic significance of C-MYC dysregulation (amplification or overexpression) in esophageal squamous cell carcinoma (ESCC) remains controversial. Therefore, we performed this meta-analysis to elucidate this relationship. Materials & methods: Available studies were retrieved from PubMed, Web of Science, EMBASE and the Cochrane Library, and ten studies with a total of 1432 patients were included in this meta-analysis. Results: Pooled results showed that C-MYC dysregulation was significantly associated with poor overall survival (hazard ratio: 1.405 [95% CI: 1.170-1.639]; p < 0.001) and lymph node metastasis (odds ratio: 1.798 [95% CI: 1.125-2.873]; p = 0.014). Subgroup analysis confirmed the results and more prominent predictive effects were observed in the C-MYC amplification group. Conclusion: C-MYC dysregulation is a promising biomarker for ESCC prognosis.

Prognostic value of stem cell markers in esophageal and esophagogastric junction cancer: a meta-analysis

Background: Esophageal cancer is an aggressive tumor, with poor prognosis and low survival rates. Although diagnosis and treatment have improved considerably, more efficient prognostic factors are urgently needed to prevent postoperative recurrence and metastasis. Cancer stem cells are key players in tumor progression and several studies have investigated the association between the expression of stemness genes and clinical outcome. However, the prognostic value of stemness markers in esophageal cancer remains controversial. We identified six factors involved in angiogenesis, anti-apoptosis and self-renewal that have been associated to poor prognosis in other types of cancer. We conducted a review of the literature and a meta-analysis to assess their potential prognostic role in this malignancy.

Material and Methods: The database of PMC, PubMed, Web of Science, Embase and The Cochrane Library were searched to investigate the association between CD34, CD133, Nucleostemin, OCT-4, NANOG and CD90, and the survival of patients affected by esophageal squamous cell carcinoma or esophageal adenocarcinoma. Among the 615 eligible studies, a total of 19 articles (including 1586 patients) met the inclusion criteria for the meta-analysis, and the pooled hazard ratio and 95% confidence intervals were calculated.

Results: Data showed that high expression of CD34 (HR 2.10; 95%CI 1.41-3.14; I²=56%; p=0.0003), CD133 (HR 1.91; 95%CI 1.15-3.19; I²=55%; p=0.01) and Nucleostemin (HR 2.97; 95%CI 1.11-7.98; I²=0%; p=0.03) were associated with poor prognosis in patients affected by esophageal cancer. The expression of NANOG and OCT-4 showed no significant association with survival of patients, whereas no study involving CD90 was included in this meta-analysis. Conclusion: CD34, CD133 and Nucleostemin might represent useful prognostic markers in patients affected by esophageal cancer.

Genome-wide analysis of lncRNAs, miRNAs, and mRNAs forming a prognostic scoring system in esophageal squamous cell carcinoma

Background

Esophageal squamous cell carcinoma (ESCC) is the main subtype of esophageal carcinoma. Protein coding genes and non-coding RNAs can be powerful prognostic factors in multiple cancers, including ESCC. However, there is currently no model that integrates multiple types of RNA expression signatures to predict clinical outcomes.

Methods

The sequencing data (RNA-sequencing and miRNA-sequencing) and clinical data of ESCC patients were obtained from The Cancer Genome Atlas (TCGA) database, and Differential gene expression analysis, Cox regression analysis and Spearman correlation analysis were used to construct prognosis-related lncRNA-mRNA co-expression network and scoring system with multiple types of RNA. The potential molecular mechanisms of prognostic mRNAs were explored by functional enrichment analysis.

Results

A total of 62 prognostic lncRNAs, eight prognostic miRNAs and 66 prognostic mRNAs were identified in ESCC (P-value < 0.05) and a prognosis-related lncRNA-mRNA co-expression network was created. Five prognosis-related hub RNAs (CDCA2, MTBP, CENPE, PBK, AL033384.1) were identified. Biological process analysis revealed that mRNAs in prognosis-related co-expression RNA network were mainly enriched in cell cycle, mitotic cell cycle and nuclear division. Additionally, we constructed a prognostic scoring system for ESCC using ten signature RNAs (MLIP, TNFSF10, SIK2, LINC01068, LINC00601, TTTY14, AC084262.1, LINC01415, miR-5699-3p, miR-552-5p). Using this system, patients in the low-risk group had better long-term survival than those in the high-risk group (log-rank, P-value < 0.0001). The area under the ROC curve (AUCs) revealed that the accuracy of the prediction model was higher than the accuracy of single type of RNA prediction model.

Conclusion

In brief, we constructed a prognostic scoring system based on multiple types of RNA for ESCC that showed high predicting prognosis performance, and deeply understood the regulatory mechanism of prognosis-related lncRNA-mRNA co-expression network.

Integrated analysis of genomic and transcriptomic profiles identified a prognostic immunohistochemistry panel for esophageal squamous cell cancer

Background

The poor outcome of patients with esophageal squamous cell carcinoma (ESCC) highlights the importance of the identification of novel effective prognostic biomarkers. We aimed to identify a clinically applicable prognostic immunohistochemistry (IHC) panel for ESCC.

Methods

An integrated analysis was performed to screen and establish a prognostic panel using exome sequencing profile from 81 pairs of ESCC samples and RNA expression microarray data from 119 ESCC subjects. Two independent ESCC cohorts were recruited as training and validation groups to test the prognostic value.

Results

Three genes were selected, namely, ANO1, GAL, and MMP3, which were aberrantly expressed in ESCC tumor tissues (P < .001). Among them, ANO1 and MMP3 were reserved for the construction of the prognostic panel due to their significant association with the prognosis of ESCC patients (P = .015 and P < .001). Patients with both ANO1+ and MMP3+ had a poorer prognosis than that with ANO1−/MMP3+, ANO1+/MMP3−, or ANO1−/MMP3 − in both the training set and validation set (P < .001). Receiver operating characteristic analysis showed that the combination of IHC panel and eighth American Joint Commission on Cancer staging yielded a better prognostic predictive efficacy compared with the two indexes alone (P < .001, area under curve: 0.752). Finally, a nomogram was created by integrating the IHC markers and clinicopathological risk factors to predict prognosis with a C‐index of 0.695 (95% confidence interval: 0.657‐0.734).

Conclusion

Using an integrated multistage screening strategy, we identified and validated a valuable prognostic IHC panel for ESCC.

Epigenetic Metalloenzymes

Epigenetics controls the expression of genes and is responsible for cellular phenotypes. The fundamental basis of these mechanisms involves in part the post-translational modifications (PTMs) of DNA and proteins, in particular, the nuclear histones. DNA can be methylated or demethylated on cytosine. Histones are marked by several modifications including acetylation and/or methylation, and of particular importance are the covalent modifications of lysine. There exists a balance between addition and removal of these PTMs, leading to three groups of enzymes involved in these processes: the writers adding marks, the erasers removing them, and the readers able to detect these marks and participating in the recruitment of transcription factors. The stimulation or the repression in the expression of genes is thus the result of a subtle equilibrium between all the possibilities coming from the combinations of these PTMs. Indeed, these mechanisms can be deregulated and then participate in the appearance, development and maintenance of various human diseases, including cancers, neurological and metabolic disorders. Some of the key players in epigenetics are metalloenzymes, belonging mostly to the group of erasers: the zinc-dependent histone deacetylases (HDACs), the iron-dependent lysine demethylases of the Jumonji family (JMJ or KDM) and for DNA the iron-dependent ten-eleven-translocation enzymes (TET) responsible for the oxidation of methylcytosine prior to the demethylation of DNA. This review presents these metalloenzymes, their importance in human disease and their inhibitors.

A genomewide transcriptomic approach identifies a novel gene expression signature for the detection of lymph node metastasis in patients with early stage gastric cancer

BACKGROUND

Although identification of lymph node (LN) metastasis is a well-recognized strategy for improving outcomes in patients with gastric cancer (GC), currently there is lack of availability of adequate molecular biomarkers that can identify such metastasis. Herein we have developed a robust gene-expression signature for detecting LN metastasis in early stage GC by using a transcriptome-wide biomarker discovery and subsequent validation in multiple clinical cohorts.

METHODS

A total of 532 patients with pathological T1 and T2 GC from 4 different cohorts were analyzed. Two independent datasets (n = 96, and n = 188) were used to establish a gene signature for the identification of LN metastasis in GC patients. The diagnostic performance of our gene-expression signature was subsequently assessed in two independent clinical cohorts using qRT-PCR assays (n = 101, and n = 147), and subsequently compared against conventional tumor markers and image-based diagnostics.

FINDINGS

We established a 15-gene signature by analyzing multiple high throughput datasets, which robustly distinguished LN status in both training (AUC = 0.765, 95% CI 0.667-0.863) and validation cohorts (AUC = 0.742, 95% CI 0.630-0.852). Notably, the 15-gene signature was significantly superior compared to the conventional tumor markers, CEA (P = .04) and CA19-9 (P = .005), as well as computed tomography-based imaging (P = .04).

INTERPRETATION

We have established and validated a 15-gene signature for detecting LN metastasis in GC patients, which offers a robust diagnostic tool for potentially improving treatment outcomes in gastric cancer patients. FUND: NIH: CA72851, CA181572, CA14792, CA202797, CA187956; CPRIT: RP140784: Baylor Sammons Cancer Center polot grants (AG), VPRT: 9610337, CityU 21101115, 11102317, 11103718; JCYJ20170307091256048 (XW).

Identification of a 6-gene signature predicting prognosis for colorectal cancer

BACKGROUND

An accurate and robust gene signature is of the utmost importance in assisting oncologists to make a more accurate evaluation in clinical practice. In our study, we extracted key mRNAs significantly related to colorectal cancer (CRC) prognosis and we constructed an expression-based gene signature to predict CRC patients' survival.

METHODS

mRNA expression profiles and clinicopathological data of colon adenocarcinoma (COAD) cases and rectum adenocarcinoma (READ) were collected from The Cancer Genome Atlas database to investigate gene expression alteration associated to the prognosis of CRC. Differentially expressed mRNAs (DEMs) were detected between COAD/READ and normal tissue samples. Relying on a univariate and multivariate Cox regression analyses, a mRNA panel signature was established and used for predicting the overall survival (OS) in CRC patients. Receiver operating characteristic curve was used to evaluate the prognosis performance of our model through calculating the AUC values corresponding to the 3-year and 5-year survival. To assess the performance of gene signature in the given cancer subgroups (CRC entire cohort, COAD cohort, and READ cohort), a stratified analysis was carried out according to clinical factors.

RESULTS

A total of 5341 and 5594 DEMs were collected from COAD vs. normal tissue samples, and READ vs. normal samples respectively. A univariate regression analysis for the common DEMs between COAD and READ cohorts resulted in 14 common mRNAs related to OS. The multivariate Cox regression analysis revealed that 6 of these mRNAs (EPHA6, TIMP1, IRX6, ART5, HIST3H2BB, and FOXD1) had significant prognostic value allowing the discrimination between high- and low-risk patients, implying poor and good outcomes, respectively. The stratified analysis identified 6-gene signature as an independent prognostic signature in predicting CRC patients' survival.

CONCLUSIONS

The 6-gene signature could act as an independent biomarker for survival prediction of CRC patients.

A Novel Three-Gene Model Predicts Prognosis and Therapeutic Sensitivity in Esophageal Squamous Cell Carcinoma

To precisely predict the clinical outcome and determine the optimal treatment options for patients with esophageal squamous cell carcinoma (ESCC) remains challenging. Prognostic models based on multiple molecular markers of tumors have been shown to have superiority over the use of single biomarkers. Our previous studies have identified the crucial role of ezrin in ESCC progression, which prompted us to hypothesize that ezrin-associated proteins contribute to the pathobiology of ESCC. Herein, we explored the clinical value of a molecular model constructed based on ezrin-associated proteins in ESCC patients. We revealed that the ezrin-associated proteins (MYC, PDIA3, and ITGA5B1) correlated with the overall survival (OS) and disease-free survival (DFS) of patients with ESCC. High expression of MYC was associated with advanced pTNM-stage (P=0.011), and PDIA3 and ITGA5B1 were correlated with both lymph node metastasis (PDIA3: P < 0.001; ITGA5B1: P=0.001) and pTNM-stage (PDIA3: P=0.001; ITGA5B1: P=0.009). Furthermore, we found that, compared with the current TNM staging system, the molecular model elicited from the expression of MYC, PDIA3, and ITGA5B1 shows higher accuracy in predicting OS (P < 0.001) or DFS (P < 0.001) in ESCC patients. Moreover, ROC and regression analysis demonstrated that this model was an independent predictor for OS and DFS, which could also help determine a subgroup of ESCC patients that may benefit from chemoradiotherapy. In conclusion, our study has identified a novel molecular prognosis model, which may serve as a complement for current clinical risk stratification approaches and provide potential therapeutic targets for ESCC treatment.

Autophagy Inhibitor (LY294002) and 5-fluorouracil (5-FU) Combination-Based Nanoliposome for Enhanced Efficacy Against Esophageal Squamous Cell Carcinoma

In this study, 5-fluorouracil (5-FU) and LY294002 (LY)-loaded PEGylated nanoliposome was prepared to target esophageal squamous cell carcinoma (ESCC). The particles were characterized in terms of physicochemical and biological parameters. The co-delivery of autophagy inhibitor and chemotherapeutic drug in a single carrier was successfully accomplished. The two components from 5-FU and LY-loaded PEGylated nanoliposome (FLNP) released in a controlled manner with LY relatively released faster compared to that of 5-FU. FLNP showed a receptor-mediated cellular uptake that will allow the gradual release of drug in the acidic environment. The cellular uptake of nanoparticles (NP) was further confirmed by FACS analysis. The combination of 5-FU and LY resulted in higher cytotoxic effect compared to that of individual drugs. Most importantly, FLNP exhibited a significantly higher anticancer effect in cancer cells compared to that of free cocktail combinations. The faster release of LY from FLNP leads to autophagy inhibition that improves the sensitivity of cancer cells towards 5-FU, resulting in more cell death. Consistently, FLNP induced a greater apoptosis (~ 48%) of cancer cells compared to that of any other groups. Western blot analysis clearly showed that 5-FU and LY individually increased the expression of caspase-3 and PARP, while as expected FLNP induced a remarkable expression of these protein markers indicating the superior anticancer effect. We believe that the programmed release of autophagy inhibitor and chemotherapeutic drug from a single nanocarrier will increase the prospect of anticancer therapy in ESCC.

Tissue-based quantitative proteomics to screen and identify the potential biomarkers for early recurrence/metastasis of esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is the eighth cause of cancer-related deaths worldwide. To screen potential biomarkers associated with early recurrence/metastasis (R/M) of ESCC patients after radical resection, ESCC patients were analyzed by a comparative proteomics analysis using iTRAQ with RPLC-MS to screen differential proteins among R/M groups and adjacent normal tissues. The proteins were identified by qRT-PCR, Western blotting, and tissue microarray. The protein and mRNA expression difference of PHB2 between tumor tissues of ESCC patients and adjacent normal tissues, ESCC patients with and without metastasis, four ESCC cell lines and normal esophageal epithelial cells were inspected using immunohistochemical staining, qRT-PCR, and Western blotting. The EC109 and TE1 cells were used to establish PHB2 knockdown cell models, and their cell proliferation and invasion ability were determined by cell counting method, Transwell® assay. Thirteen proteins were selected by cutoff value of 0.67 fold for underexpression and 1.5-fold for overexpression. Seven proteins were confirmed to be associated with R/M among the 13 proteins. The potential biomarker PHB2 for early recurrence/metastasis of ESCC was identified. PHB2 expression was related to the OS of ESCC patients (P = 0.032) and had high levels in the tumor tissues and human cell lines of ESCC (P = 0.0002). Also, the high PHB2 expression promoted the metastasis of ESCC (P = 0.0075), suggesting high PHB2 expression was a potential prognostic biomarker. Experiments showed that PHB2 could significantly promote the proliferation and cell invasion ability of human ESCC cell lines and the knockdown of PHB2 suppressed the phosphorylation level of AKT, as well as the expression of MMP9 and RAC1. PHB2 could predict the early metastasis of ESCC patients.

Survival prediction tools for esophageal and gastroesophageal junction cancer: A systematic review

BACKGROUND

Clinical, pathological, and molecular information combined with cancer stage in prognostication algorithms can offer more personalized estimates of survival, which might guide treatment choices. Our aim was to evaluate the quality of prognostication tools in esophageal cancer.

METHODS

We systematically searched MedLine and Embase from 2005 to 2017 for studies reporting development or validation of models predicting long-term survival in esophageal cancer. We evaluated tools using the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies guidelines and the American Joint Committee on Cancer acceptance criteria for risk models.

RESULTS

We identified 16 prognostication tools for patients treated with curative intent and 1 for patients with metastatic disease. These tools frequently excluded adenocarcinoma, contained outdated data, and were developed with a limited sample size. Nine tools were developed in China for squamous cell cancer, and 11 used data on patients diagnosed before 2010. Most tools excluded key prognostic factors such as age and sex. Tumor stage and grade were the most commonly, but not universally, included factors. Twelve tools were designed to predict overall survival; 5 predicted cancer-specific survival. Bootstrap internal validation was performed for most tools; c-statistics ranged from 0.63 to 0.77 and graphically evaluated calibration was "good." Five tools were externally validated; c-statistics ranged from 0.70 to 0.77.

CONCLUSIONS

Existing tools cannot be confidently used for esophageal cancer prognostication in current clinical practice. Better-quality tools might help to more individually and accurately estimate disease course, select further treatments, and risk-stratify for future clinical trials.

Protein-coding genes combined with long noncoding RNA as a novel transcriptome molecular staging model to predict the survival of patients with esophageal squamous cell carcinoma

BACKGROUND

Esophageal squamous cell carcinoma (ESCC) is the predominant subtype of esophageal carcinoma in China. This study was to develop a staging model to predict outcomes of patients with ESCC.

METHODS

Using Cox regression analysis, principal component analysis (PCA), partitioning clustering, Kaplan-Meier analysis, receiver operating characteristic (ROC) curve analysis, and classification and regression tree (CART) analysis, we mined the Gene Expression Omnibus database to determine the expression profiles of genes in 179 patients with ESCC from GSE63624 and GSE63622 dataset.

RESULTS

Univariate cox regression analysis of the GSE63624 dataset revealed that 2404 protein-coding genes (PCGs) and 635 long non-coding RNAs (lncRNAs) were associated with the survival of patients with ESCC. PCA categorized these PCGs and lncRNAs into three principal components (PCs), which were used to cluster the patients into three groups. ROC analysis demonstrated that the predictive ability of PCG-lncRNA PCs when applied to new patients was better than that of the tumor-node-metastasis staging (area under ROC curve [AUC]: 0.69 vs. 0.65, P < 0.05). Accordingly, we constructed a molecular disaggregated model comprising one lncRNA and two PCGs, which we designated as the LSB staging model using CART analysis in the GSE63624 dataset. This LSB staging model classified the GSE63622 dataset of patients into three different groups, and its effectiveness was validated by analysis of another cohort of 105 patients.

CONCLUSIONS

The LSB staging model has clinical significance for the prognosis prediction of patients with ESCC and may serve as a three-gene staging microarray.

The alterations of cytokeratin and vimentin protein expressions in primary esophageal spindle cell carcinoma

Background

The accumulated evidence has indicated the diagnostic role of cytokeratin (CK) and vimentin protein immunoassay in primary esophageal spindle cell carcinoma (PESC), which is a rare malignant tumor with epithelial and spindle components. However, it is largely unknown for the expression of CK and vimentin in pathological changes and prognosis of PESC.

Methods

Eighty-two PESC patients were identified from the esophageal and gastric cardia cancer database established by Henan Key Laboratory for Esophageal Cancer Research of Zhengzhou University. We retrospectively evaluated CK and vimentin protein expressions in PESC. Clinicopathological features were examined by means of univariate and multivariate survival analyses. Furthermore, the co-expression value of cytokeratin and vimentin was analyzed by receiver operating characteristic (ROC) curve.

Results

The positive pan-cytokeratins AE1/AE3 (AE1/AE3 for short) staining was chiefly observed in cytoplasm of epithelial component tumor cells, with a positive detection rate of 85.4% (70/82). Interestingly, 19 cases showed AE1/AE3 positive staining both in epithelial and spindle components (23.2%). However, AE1/AE3 expression was not observed with any significant association with age, gender, tumor location, gross appearance, lymph node metastasis and TNM stage. Furthermore, AE1/AE3 protein expression does not show any effect on survival. Similar results were observed for vimentin immunoassay. However, in comparison with a single protein, the predictive power of AE1/AE3 and vimentin proteins signature was increased apparently than with single signature [0.75 (95% CI = 0.68–0.82) with single protein v.s. 0.89 (95% CI = 0.85–0.94) with AE1/AE3 and vimentin proteins]. The 1-, 3-, 5- and 7-year survival rates for PESC patients in this study were 79.3%, 46.3%, 28.0% and 15.9%, respectively. Multivariate analysis demonstrated age and TNM stage were independent prognostic factors for overall survival (P = 0.036 and 0.003, respectively). It is noteworthy that only 17.1% patients had a PESC accurate diagnosis by biopsy pathology before surgery (14/82). 72.4% PESC patients with biopsy pathology before surgery had been diagnosed as squamous cell carcinoma.

Conclusion

The present study demonstrates that cytokeratin and vimentin protein immunoassay is a useful biomarker for PESC accurate diagnosis, but not prognosis. The co-expression of cytokeratin and vimentin in both epithelial and spindle components suggest the possibility of single clone origination for PESC.

A novel molecular and clinical staging model to predict survival for patients with esophageal squamous cell carcinoma

Current prognostic factors fail to accurately determine prognosis for patients with esophageal squamous cell carcinoma (ESCC) after surgery. Here, we constructed a survival prediction model for prognostication in patients with ESCC. Candidate molecular biomarkers were extracted from the Gene Expression Omnibus (GEO), and Cox regression analysis was performed to determine significant prognostic factors. The survival prediction model was constructed based on cluster and discriminant analyses in a training cohort (N=205), and validated in a test cohort (N=207). The survival prediction model consisting of two genes (UBE2C and MGP) and two clinicopathological factors (tumor stage and grade) was developed. This model could be used to accurately categorize patients into three groups in the test cohort. Both disease-free survival and overall survival differed among the diverse groups (P<0.05). In summary, we have developed and validated a predictive model that is based on two gene markers in conjunction with two clinicopathological variables, and which can accurately predict outcomes for ESCC patients after surgery.

A three-lncRNA signature predicts overall survival and disease-free survival in patients with esophageal squamous cell carcinoma

BACKGROUND

Increasing evidence shows that dysregulated long non-coding RNAs (lncRNAs) can serve as potential biomarkers for cancer prognosis. However, lncRNA signatures, as potential prognostic biomarkers for esophageal squamous cell carcinoma (ESCC), have been seldom reported.

METHODS

Based on our previous transcriptome RNA sequencing analysis from 15 paired ESCC tissues and adjacent normal tissues, we selected 10 lncRNAs with high score rank and characterized the expression of those lncRNAs, by qRT-PCR, in 138 ESCC and paired adjacent normal samples. These 138 patients were divided randomly into training (n = 77) and test (n = 59) groups. A prognostic signature of lncRNAs was identified in the training group and validated in the test group and in an independent cohort (n = 119). Multivariable Cox regression analysis evaluated the independence of the signature in overall survival (OS) and disease-free survival (DFS) prediction. GO and KEGG pathway analysis, combined with cell transwell and proliferation assays, are applied to explore the function of the three lncRNAs.

RESULTS

A novel three-lncRNA signature, comprised of RP11-366H4.1.1 (ENSG00000248370), LINC00460 (ENSG00000233532) and AC093850.2 (ENSG00000230838), was identified. The signature classified patients into high-risk and low-risk groups with different overall survival (OS) and disease-free survival (DFS). For the training group, median OS: 23.1 months vs. 39.1 months, P < 0.001; median DFS: 15.2 months vs. 33.3 months, P < 0.001. For the test group, median OS: 23 months vs. 59 months, P < 0.001; median DFS: 16.4 months vs. 50.8 months, P < 0.001. For the independent cohort, median OS: 22.4 months vs. 60.4 months, P < 0.001). The signature indicates that patients in the high-risk group show poor OS and DFS, whereas patients with a low-risk group show significantly better outcome. The independence of the signature was validated by multivariable Cox regression analysis. GO and KEGG pathway analysis for 588 protein-coding genes-associated with the three lncRNAs indicated that the three lncRNAs were involved in tumorigenesis. In vitro assays further demonstrated that the three lncRNAs promoted the migration and proliferation of ESCC cells.

CONCLUSIONS

The three-lncRNA signature is a novel and potential predictor of OS and DFS for patients with ESCC.

L1CAM drives oncogenicity in esophageal squamous cell carcinoma by stimulation of ezrin transcription

L1 cell adhesion molecule (L1CAM) is highly expressed in various types of human cancers, displaying yet unknown molecular mechanisms underlying their oncogenic potential. Here, we found that L1CAM expression was significantly increased in esophageal squamous cell carcinoma (ESCC; n = 157) lesions compared with non-cancerous tissues. High tumorous L1CAM expression significantly correlated with reduced overall survival. Experimentally, L1CAM knockdown led to decreased cell growth, migration, and invasiveness in vitro, whereas overexpression of L1CAM showed the opposite effect. In nude mice, L1CAM depletion attenuated tumorigenesis and ability to penetrate the tissues surrounding ESCC cells. Gene set enrichment analysis (GSEA) and SubpathwayMiner analysis on gene expression profiles (microarray data on ESCC tissues, GSE53625; cDNA microarray data on L1CAM-knockdown ESCC cell line, GSE86268) suggested that L1CAM-co-expression genes were related to cell motility, cell proliferation, and regulation of actin cytoskeleton, validating the above experimental findings. Further mechanistical analysis showed that L1CAM upregulated the expression of the cytoskeletal protein ezrin via activating integrin β1/MAPK/ERK/AP1 signaling and thus led to the malignant phenotypes of ESCC cells. Together, our findings suggest that L1CAM may be employed as a valuable prognosis marker and a therapeutic target for ESCC patients and that L1CAM promotes ESCC tumorigenicity by upregulating ezrin expression.

KEY MESSAGES

L1CAM promotes growth and invasiveness of ESCC cells in vitro and in vivo. L1CAM upregulates the expression of ezrin by integrin α5β1/MAPK/ERK/AP1 pathway. Ezrin is a key downstream effector in the L1CAM-promoted malignant phenotypes. High expression levels of both L1CAM and ezrin significantly correlated with reduced overall survival. Nuclear L1CAM is an independent prognosis marker for esophageal squamous cell carcinoma.

The Prognostic Value of Decreased KLF4 in Digestive System Cancers: A Meta-Analysis from 17 Studies

Background

The prognostic value of loss of Krüppel-like factor 4 (KLF4) expression in digestive system cancers has not reached a consensus. This study aimed for a comprehensive investigation of the internal associations between KLF4 expression loss and prognostic implications in patients with digestive system cancers.

Methods

We searched for all relevant literatures in the electronic databases until February 1, 2017. The degree of association between KLF4 and prognosis was evaluated by pooled hazard ratios (HRs) as well as relevant 95% confidence intervals (95% CIs).

Results

Seventeen eligible studies with 2118 patients revealed that loss of KLF4 expression was connected with poor prognosis, with the pooled HRs of 1.61 (95% CI: 1.17–2.20, P = 0.003) for the overall survival (OS) and 1.99 (95% CI: 1.12–3.52, P = 0.001) for the disease-free survival (DFS)/recurrence-free survival (RFS)/metastasis-free survival (MFS). Additionally, loss of KLF4 expression was also related to a worse disease-special survival (DSS) yielding a pooled HR of 1.73 (95% CI: 1.08–2.77, P = 0.022).

Conclusion

Our findings suggest that loss of KLF4 expression is correlated with a bad outcome in most digestive system cancers, apart from esophagus squamous cell carcinoma (ESCC).

Immunohistochemical prognostic markers of esophageal squamous cell carcinoma: a systematic review

Background

Esophageal squamous cell carcinoma (ESCC) is an aggressive malignancy, with a high incidence and poor prognosis. In the past several decades, hundreds of proteins have been reported to be associated with the prognosis of ESCC, but none has been widely accepted to guide clinical care. This study aimed to identify proteins with great potential for predicting prognosis of ESCC.

Methods

We conducted a systematic review on immunohistochemical (IHC) prognostic markers of ESCC according to the 2009 Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Guidelines. Literature related to IHC prognostic markers of ESCC were searched from PubMed, Embase, Web of Science, and Cochrane Library until January 30th, 2017. The risk of bias of these original studies was evaluated using the Quality in Prognosis Studies (QUIPS) tool.

Results

We identified 11 emerging IHC markers with reproducible results, including eight markers [epidermal growth factor receptor (EGFR), Cyclin D1, vascular endothelial growth factor (VEGF), Survivin, Podoplanin, Fascin, phosphorylated mammalian target of rapamycin (p-mTOR), and pyruvate kinase M2 (PKM2)] indicating unfavorable prognosis and 3 markers (P27, P16, and E-cadherin) indicating favorable prognosis of ESCC.

Conclusion

Strong evidence supports that these 11 emerging IHC markers or their combinations may be useful in predicting prognosis and aiding personalized therapy decision-making for ESCC patients.

Electronic supplementary material

The online version of this article (doi:10.1186/s40880-017-0232-5) contains supplementary material, which is available to authorized users.

食管鳞癌干细胞及其耐药机制的研究进展

食管癌(esophageal carcinoma, EC)的全球发病率在恶性肿瘤中位居第8位, 死亡率居第6位, 化疗是EC主要的治疗方法之一, 但化疗药物耐药严重影响了化疗效果, 甚至引起化疗失败, 导致肿瘤复发或远处转移. 肿瘤干细胞(cancer stem cells, CSCs)学说提出CSCs是引起肿瘤对化疗药物耐药的重要原因之一. 本文就食管鳞癌干细胞的生物学特性、分选及化疗耐药的相关机制作一综述.

Plasma Riboflavin Level is Associated with Risk, Relapse, and Survival of Esophageal Squamous Cell Carcinoma

Riboflavin is an essential micronutrient for normal cellular activity, and deficiency may result in disease, such as cancer. We performed a case-control study to explore the association of riboflavin levels with risk and prognosis of esophageal squamous cell carcinoma (ESCC). Plasma riboflavin levels, as measured by enzyme-linked immunosorbent assay (ELISA), in ESCC patients were significantly lower than in those of healthy controls (7.04 ± 6.34 ng/ml vs. 9.32 ± 12.40 ng/ml; P < 0.05). Moreover, there was an inverse relationship between riboflavin level and risk of ESCC (odds ratio (OR) = 0.97, 95% confidence interval (CI) = 0.95-0.99, P =  0.02). The 5-year relapse-free and overall survival rates were significantly lower when riboflavin levels were ≤0.8 ng/ml than >0.8 ng/ml (relapse-free survival rate: 29.4% vs. 54.8%; overall survival rate: 28.6% vs. 55.6%). Plasma riboflavin level was an independent protective factor for both relapse-free (hazard ratio (HR) = 0.325, 95% CI = 0.161-0.657, P = 0.002) and overall survival of ESCC patients (HR = 0.382, 95% CI = 0.190-0.768, P = 0.007). In conclusion, plasma riboflavin levels are significantly related to risk and prognosis of ESCC patients, suggesting that moderate supplementation of riboflavin will decrease risk and prevent recurrence of ESCC and also improve prognosis of ESCC patients.

Protein-coding genes combined with long non-coding RNAs predict prognosis in esophageal squamous cell carcinoma patients as a novel clinical multi-dimensional signature

Esophageal carcinoma is one of the most malignant gastrointestinal cancers worldwide, and has a high mortality rate. Both protein-coding genes (PCGs) and long non-coding RNAs (lncRNAs) have been shown to play an important role in the development of malignant tumors. However, the clinical significance of PCGs combined lncRNAs is yet to be investigated in esophageal squamous cell carcinoma (ESCC). Using probe re-annotation, univariable Cox regression and the random survival forest algorithm to identify PCG-lncRNA combinations predictive of the overall survival, we found a signature comprised of three PCGs (ANGPTL7, OBP2A, SLC27A5) and two lncRNAs (RP11-702B10.1, RP11-523H24.3) to have the highest accurate prediction, with an area under ROC curve (AUC) of 0.85 in the training group and 0.63 in the test group, and it was significantly associated with the survival of ESCC patients in the training group (median survival: 32.2 months > 60 months, P < 0.001). The application of the signature to the test group showed similar prognostic values (median survival: 39.3 months vs. >60 months, P = 0.03). The chi-square test and multivariable Cox regression analysis showed that the three-PCG, two-lncRNA signature was an independent prognostic factor for patients with ESCC. Stratified analysis suggested that the PCG-lncRNA signature combined with the TNM stage could more accurately categorize ESCC patients. Our study suggests that the three-PCG, two-lncRNA signature has clinical significance for the prognosis of patients with ESCC. This signature can serve as a potential auxiliary biomarker of the TNM stage to subdivide ESCC patients more precisely.

Jumonji histone demethylases as emerging therapeutic targets

The methylation status of lysine residues in histones determines the transcription of surrounding genes by modulating the chromatin architecture. Jumonji domain-containing histone-lysine demethylases (Jmj-KDMs) remove the methyl moiety from lysine residues in histones by utilizing Fe(2+) and α-ketoglutarate. Since genetic alterations in Jmj-KDMs occur in various human cancers, the roles of Jmj-KDMs in cancer development and progression have been investigated, but still controversial. The KDM7 subfamily, which belongs to the Jmj-KDM family, is an emerging class of transcriptional coactivators because its members erase the repressive marks H3K9me2/1, H3K27me2/1, and H4K20 me1. Recently, KDM7C (alternatively named PHF2) was discovered as a new KDM7 member and identified to play a tumor-suppressive role through the reinforcement of p53-driven growth arrest and apoptosis. In this article, we generally reviewed the roles of Jmj-KDMs in human cancers and more discussed the molecular functions and the clinical significances of KDM7C.

Integrin α5 promotes tumor progression and is an independent unfavorable prognostic factor in esophageal squamous cell carcinoma

The integrin family plays a major role in complex biological events such as differentiation, development, wound healing, and the altered adhesive and invasive properties of tumor cells. The expression and function of integrin α5 in esophageal squamous cell carcinoma (ESCC) are not clear. Here, by using tissue microarrays and immunohistochemical method, integrin α5 expression was retrospectively evaluated in 147 samples of human ESCC. Results showed that expression of integrin α5 was heterogeneous and varied from negative to intense expression in a membrane and cytoplasmic distribution manner. High expression of integrin α5 was significantly correlated with lymph node metastasis (P = .042) and tumor size (P = .042). Kaplan-Meier analysis revealed that high expression of integrin α5 was related to poor overall survival of ESCC patients (P = .018). Multivariate analysis suggested that integrin α5 expression status was an independent prognostic factor for ESCC (P = .003). Moreover, integrin α5 expression was associated with the survival of patients with lymph node metastasis (P = .020), but did not influence the survival of patients without lymph node metastasis. Finally, we found that RNAi-mediated knockdown of integrin α5 led to decreased growth, migration, and invasion of ESCC cells. Combined, integrin α5 might play important roles in the progression of ESCC. Integrin α5 is a novel biomarker to predict the prognosis of ESCC patients.

High sex determining region Y-box 2 (SOX2) expression correlates with absence of nodal metastasis in esophageal squamous cell carcinoma

Sex determining region Y-box 2 (SOX2) is a transcription factor involved in self-renewal and pluripotency. Dysregulation of SOX2 expression has been found in squamous cell carcinoma (SCC), including esophageal SCC. Recently, high SOX2 expression was found to be a negative predictor of occult lymph node metastasis in early oral SCC, but the clinical significance of SOX2 expression in esophageal SCC remains controversial. Here we investigated SOX2 expression by immunohistochemistry in 75 cases of surgically resected esophageal SCC. Similar to oral SCC, we found for the first time that high SOX2 expression correlates with absence of clinical nodal metastasis (P = 0.011). Podoplanin is a glycoprotein which is variably expressed by esophageal SCC. Since we previously found that podoplanin expression correlates with nodal metastasis in esophageal SCC, we also assessed podoplanin expression in these cases. Interestingly, SOX2 expression correlates negatively with podoplanin expression (P = 0.018). It is in contrast with a recent finding that SOX2 can up-regulate podoplanin expression in SCC of the skin. Our result suggests that SOX2 might suppress nodal metastasis through down-regulation of podoplanin in esophageal SCC. Further studies are needed to clarify the exact mechanism of regulation.

Cancer stem cells in oesophageal squamous cell carcinoma: Identification, prognostic and treatment perspectives

Cancer stem cells (CSCs) are a vital subpopulation of cells to target for the treatment of cancers. In oesophageal squamous cell carcinoma (ESCC), there are several markers such as CD44, ALDH, Pygo2, MAML1, Twist1, Musashi1, Side population (SP), CD271 and CD90 that have been proposed to identify the cancer stem cells in individual cancer masses. It has also been demonstrated that stem cell markers like ALDH1, HIWI, Oct3/4, ABCG2, SOX2, SALL4, BMI-1, NANOG, CD133 and podoplanin are associated with patient's prognosis, pathological stages, cancer recurrence and therapy resistance. Finding new cancer stem cell targets or designing drugs to manipulate the known molecular targets in CSCs could be useful for improvements in clinical outcomes of the disease. To conclude, data suggest that CSCs in oesophageal squamous cell carcinoma are related to resistance to therapy and poor prognosis of patients with ESCC. Therefore, innovative insights into CSC biology and CSC-targeted therapies will help to achieve more effective management of patients with oesophageal squamous cell carcinoma.