Blood-based biomarkers for early detection of esophageal squamous cell carcinoma

Therapeutic implications of signaling pathways and tumor microenvironment interactions in esophageal cancer

Esophageal cancer (EC) is significantly influenced by the tumor microenvironment (TME) and altered signaling pathways. Downregulating these pathways in EC is essential for suppressing tumor development, preventing metastasis, and enhancing therapeutic outcomes. This approach can increase tumor sensitivity to treatments, enhance patient outcomes, and inhibit cancer cell proliferation and spread. The TME, comprising cellular and non-cellular elements surrounding the tumor, significantly influences EC's development, course, and treatment responsiveness. Understanding the complex relationships within the TME is crucial for developing successful EC treatments. Immunotherapy is a vital TME treatment for EC. However, the heterogeneity within the TME limits the application of anticancer drugs outside clinical settings. Therefore, identifying reliable microenvironmental biomarkers that can detect therapeutic responses before initiating therapy is crucial. Combining approaches focusing on EC signaling pathways with TME can enhance treatment outcomes. This integrated strategy aims to interfere with essential signaling pathways promoting cancer spread while disrupting factors encouraging tumor development. Unraveling aberrant signaling pathways and TME components can lead to more focused and efficient treatment approaches, identifying specific cellular targets for treatments. Targeting the TME and signaling pathways may reduce metastasis risk by interfering with mechanisms facilitating cancer cell invasion and dissemination. In conclusion, this integrative strategy has significant potential for improving patient outcomes and advancing EC research and therapy. This review discusses the altered signaling pathways and TME in EC, focusing on potential future therapeutics.

Expression of Interleukin-8, Interleukin-12 and Interleukin-13 in Esophageal Squamous Cell Carcinoma: Biomarker Potentiality and Prognostic Significance

PURPOSE

Interleukin-8 (IL8), Interleukin-12 (IL12) and Interleukin-13 (IL13) are cytokines that play regulatory role in cancer pathogenesis. We analysed their expression profile to evaluate as molecular biomarkers of esophageal squamous cell carcinoma (ESCC) and their association with different parameters and patient survival.

METHODS

Expression analysis was performed by Real time quantitative polymerase chain reaction and receiver operating characteristic (ROC) curve analysis was done. The expression profiles were associated with different clinicopathological and dietary factors. Survival and hazard analysis were also performed.

RESULTS

IL8 expression showed upregulation in tissue (p = 0.000) and blood samples (p = 0.481), IL12 expression showed downregulation in tissue samples (p = 0.064) and upregulation in blood samples (p = 0.689) and IL13 expression showed upregulation in tissue (p = 0.000) and blood samples (p = 0.006). IL13 expression in tissue showed the highest area under the curve (AUC) value (0.773) for ESCC diagnosis, followed by IL8 expression in tissue (0.704) and IL13 expression in blood (0.643). This study also reveals the correlation of studied cytokines in tissue and blood level. Different clinicopathological and dietary factors showed significant association (p < 0.05) with IL8, IL12 and IL13 expression and with survival of ESCC patients. IL8 expression in blood and IL12 expression in tissue and blood showed significant association (p < 0.05) with patient survival.

CONCLUSION

Altered expression of IL8, IL12 and IL13 may be associated with ESCC progression. Overexpression of IL8 and IL13 in tissue samples may be potential biomarkers for ESCC screening. Additionally, both survival and hazard analysis data indicate the effects of different parameters on the prognosis of ESCC patients.

Evaluation of Spectrum-Aided Visual Enhancer (SAVE) in Esophageal Cancer Detection Using YOLO Frameworks

The early detection of esophageal cancer presents a substantial difficulty, which contributes to its status as a primary cause of cancer-related fatalities. This study used You Only Look Once (YOLO) frameworks, specifically YOLOv5 and YOLOv8, to predict and detect early-stage EC by using a dataset sourced from the Division of Gastroenterology and Hepatology, Ditmanson Medical Foundation, Chia-Yi Christian Hospital. The dataset comprised 2741 white-light images (WLI) and 2741 hyperspectral narrowband images (HSI-NBI). They were divided into 60% training, 20% validation, and 20% test sets to facilitate robust detection. The images were produced using a conversion method called the spectrum-aided vision enhancer (SAVE). This algorithm can transform a WLI into an NBI without requiring a spectrometer or spectral head. The main goal was to identify dysplasia and squamous cell carcinoma (SCC). The model's performance was evaluated using five essential metrics: precision, recall, F1-score, mAP, and the confusion matrix. The experimental results demonstrated that the HSI model exhibited improved learning capabilities for SCC characteristics compared with the original RGB images. Within the YOLO framework, YOLOv5 outperformed YOLOv8, indicating that YOLOv5's design possessed superior feature-learning skills. The YOLOv5 model, when used in conjunction with HSI-NBI, demonstrated the best performance. It achieved a precision rate of 85.1% (CI95: 83.2-87.0%, p < 0.01) in diagnosing SCC and an F1-score of 52.5% (CI95: 50.1-54.9%, p < 0.01) in detecting dysplasia. The results of these figures were much better than those of YOLOv8. YOLOv8 achieved a precision rate of 81.7% (CI95: 79.6-83.8%, p < 0.01) and an F1-score of 49.4% (CI95: 47.0-51.8%, p < 0.05). The YOLOv5 model with HSI demonstrated greater performance than other models in multiple scenarios. This difference was statistically significant, suggesting that the YOLOv5 model with HSI significantly improved detection capabilities.

Latest insights into the global epidemiological features, screening, early diagnosis and prognosis prediction of esophageal squamous cell carcinoma

As a highly invasive carcinoma, esophageal cancer (EC) was the eighth most prevalent malignancy and the sixth leading cause of cancer-related death worldwide in 2020. Esophageal squamous cell carcinoma (ESCC) is the major histological subtype of EC, and its incidence and mortality rates are decreasing globally. Due to the lack of specific early symptoms, ESCC patients are usually diagnosed with advanced-stage disease with a poor prognosis, and the incidence and mortality rates are still high in many countries, especially in China. Therefore, enormous challenges still exist in the management of ESCC, and novel strategies are urgently needed to further decrease the incidence and mortality rates of ESCC. Although the key molecular mechanisms underlying ESCC pathogenesis have not been fully elucidated, certain promising biomarkers are being investigated to facilitate clinical decision-making. With the advent and advancement of high-throughput technologies, such as genomics, proteomics and metabolomics, valuable biomarkers with high sensitivity, specificity and stability could be identified for ESCC. Herein, we aimed to determine the epidemiological features of ESCC in different regions of the world, especially in China, and focused on novel molecular biomarkers associated with ESCC screening, early diagnosis and prognosis prediction.

Novel milestones for early esophageal carcinoma: From bench to bed

Esophageal cancer (EC) is the seventh most common cancer worldwide, and esophageal squamous cell carcinoma (ESCC) accounts for the majority of cases of EC. To effectively diagnose and treat ESCC and improve patient prognosis, timely diagnosis in the initial phase of the illness is necessary. This article offers a detailed summary of the latest advancements and emerging technologies in the timely identification of ECs. Molecular biology and epigenetics approaches involve the use of molecular mechanisms combined with fluorescence quantitative polymerase chain reaction (qPCR), high-throughput sequencing technology (next-generation sequencing), and digital PCR technology to study endogenous or exogenous biomolecular changes in the human body and provide a decision-making basis for the diagnosis, treatment, and prognosis of diseases. The investigation of the microbiome is a swiftly progressing area in human cancer research, and microorganisms with complex functions are potential components of the tumor microenvironment. The intratumoral microbiota was also found to be connected to tumor progression. The application of endoscopy as a crucial technique for the early identification of ESCC has been essential, and with ongoing advancements in technology, endoscopy has continuously improved. With the advancement of artificial intelligence (AI) technology, the utilization of AI in the detection of gastrointestinal tumors has become increasingly prevalent. The implementation of AI can effectively resolve the discrepancies among observers, improve the detection rate, assist in predicting the depth of invasion and differentiation status, guide the pericancerous margins, and aid in a more accurate diagnosis of ESCC.

AURKA knockdown inhibits esophageal squamous cell carcinoma progression through ferroptosis

Aurora kinase A, as a pro-carcinogenic in gastric cancer and glioma kinase, is enhanced in several human tumors. However, it's regulatory mechanism in esophageal squamous cell carcinoma (ESCC) remains unclear. Thus, this study aimed to investigate the expression status, functional roles, and molecular mechanisms of AURKA in ESCC development. AURKA expression was analyzed by the screening of the GEO database and detected using an immunohistochemical method. The biological function of AURKA on ESCC was evaluated in vitro and in vivo. Western blot assay, malondialdehyde (MDA), iron, and glutathione (GSH) kits were utilized to assess changes in ferroptosis. Database analysis results showed that AURKA was a differential gene in ESCC and was highly expressed in human ESCC tissues. Functionally, AURKA knockdown decreased ESCC cell proliferation, invasion, and metastasis both in vitro and in vivo. Moreover, when AURKA was knockdown, cells were more correctly blocked in the G2/M phase, and the ferroptosis-related MDA and Fe increased, whereas the GSH reduced. Consistently, Glutathione peroxidase 4 (GPX4) and solute carrier family 7a member 11 (SLC7A11) expression were downregulated by AURKA knockdown. However, ferroptosis inhibitor partially restore ESCC cell proliferation, invasion, and metastasis caused by AURKA knockdown. AURKA knockdown enhances ferroptosis and acts against cancer progression in ESCC. AURKA acts as a tumor-promoting gene and may serve as potential target for ESCC treatment.

Exploring Potential Biomarkers in Oesophageal Cancer: A Comprehensive Analysis

Oesophageal cancer (OC) is the sixth leading cause of cancer-related death worldwide. OC is highly aggressive, primarily due to its late stage of diagnosis and poor prognosis for patients' survival. Therefore, the establishment of new biomarkers that will be measured with non-invasive techniques at low cost is a critical issue in improving the diagnosis of OC. In this review, we summarize several original studies concerning the potential significance of selected chemokines and their receptors, including inflammatory proteins such as interleukin-6 (IL-6) and C-reactive protein (CRP), hematopoietic growth factors (HGFs), claudins (CLDNs), matrix metalloproteinases (MMPs) and their tissue inhibitors (TIMPs), adamalysines (ADAMs), as well as DNA- and RNA-based biomarkers, in OC. The presented results indicate the significant correlation between the CXCL12, CXCR4, CXCL8/CXCR2, M-CSF, MMP-2, MMP-9 ADAM17, ADAMTS-6, and CLDN7 levels and tumor stage, as well as the clinicopathological parameters of OC, such as the presence of lymph node and/or distant metastases. CXCL12, CXCL8/CXCR2, IL-6, TIMP-2, ADAM9, and ADAMTS-6 were prognostic factors for the overall survival of OC patients. Furthermore, IL-6, CXCR4, CXCL8, and MMP-9 indicate higher diagnostic utility based on the area under the ROC curve (AUC) than well-established OC tumor markers, whereas CLDN18.2 can be used in novel targeted therapies for OC patients.

A Case of Esophageal Cancer With Markedly Elevated Soluble Interleukin-2 Receptor: A Potential of Soluble Interleukin-2 Receptor as a Biomarker

We report an autopsy case of advanced esophageal cancer with multiple metastases that presented with a markedly high level of sIL-2R. An 83-year-old man was admitted to our hospital with a 1-week history of epigastric distress, appetite loss, and fatigue. Imaging examinations revealed a large liver tumor. Although the tumor markers for gastrointestinal and liver cancers were within normal limits, the sIL-2R level was extremely high (10,384 U/mL). The patient died immediately after admission due to the rapid course of the disease. An autopsy showed advanced esophageal cancer with multiple metastases, including the liver, lungs, and multiple lymph nodes. In histological examinations, esophageal cancer was a mixture of well- and poorly differentiated squamous cell carcinoma, in which poorly differentiated cancer cells expressed sIL-2R on immunohistochemical staining. However, we failed to detect positive staining for sIL-2R in the lymphocytes. Our findings revealed that solid tumors could express sIL-2R. Although sIL-2R is a tumor marker used for hematological malignancies, such as malignant lymphoma, this case report highlights the value of the measurement of sIL-2R levels in advanced solid tumors, including esophageal cancer. We concluded that sIL-2R has potential as a biomarker in advanced solid tumors for cancer staging and treatment response.

Non-endoscopic Screening for Esophageal Squamous Cell Carcinoma: Recent Advances

BACKGROUND

Esophageal squamous cell carcinoma (ESCC) is one of the most common tumors in the gastrointestinal tract, and China has a high incidence area with a high burden on the disease. As early symptoms of ESCC are not obvious, the mortality rate is high, and it is often diagnosed in the intermediate and advanced stages. However, early screening and treatment may reduce morbidity and mortality.

METHODS

Screening methods are divided into endoscopic and non-endoscopic screening.

RESULTS

Endoscopic screening cannot be widely used because of its invasive nature and high cost. Currently, non-endoscopic screening consists primarily of tumor biomarkers and cytology, and tumor biomarkers including autoantibodies, circulating tumor cells, circulating tumor DNA, exosomes and serum metabolomics are more likely to be effective. But the efficiency of early diagnosis of esophageal cancer is low and the accuracy of screening needs to be improved. The aim of this study is to summarize advances in non-endoscopic esophageal cancer screening and strategies to provide a scientific basis and research idea for esophageal cancer prevention and control.

CONCLUSIONS

Non-endoscopic screening is better than endoscopic screening. And the application of tumor biomarkers is much better than other non-endoscopic screening methods.

Prediction of Response to Chemoradiotherapy by Dynamic Changes of Circulating Exosome Levels in Patients with Esophageal Squamous Cell Carcinoma

Background

The exosomes-based liquid biopsy represents a prospective biomarker for tumor screening, prognosis prediction, and tumor regression. This study aimed to isolate circulating exosomes (CEs) from plasma of the esophageal squamous cell carcinoma (ESCC) patients who received chemoradiotherapy through exosome detection method via the ultrafast-isolation system (EXODUS) and investigated the association between the dynamic changes of CE levels and therapeutic effect.

Methods

We isolated and quantitatively analyzed CEs from plasma of locally advanced ESCC patients received chemoradiotherapy at 2 time points: baseline (pre-chemoradiotherapy) and 2 months after the chemoradiotherapy (post-chemoradiotherapy). We isolated exosomes from plasma by EXODUS platform and confirmed them through nanoparticle tracking analysis (NTA), transmission electron microscope (TEM), and Western blot. The associations of CE level with clinicopathological characteristics, tumor regression, and progression-free survival (PFS) were analyzed.

Results

The average diameter of CEs was 107.4±14.3 nm at baseline and 101.7±17.1 nm at post-chemoradiotherapy. The mean exosome concentration significantly decreased after chemoradiotherapy (7.3×1011 particles/mL vs 5.4×1011 particles/mL, P < 0.001). The patients with stage III-IVA and tumor length ≥5cm had obviously higher baseline CE levels. Dynamic changes in CE levels were successfully applied for evaluation of chemoradiotherapy response and PFS. Furthermore, through multivariate Cox regression analysis, it was revealed that dynamic changes of CE levels were an independent predictor of PFS in locally advanced ESCC patients who received chemoradiotherapy.

Conclusion

Here, we demonstrated EXODUS platform isolated and enriched CEs from plasma of ESCC patients with high-purity and high-yield. The EXODUS platform can facilitate liquid biopsy based on exosomes translation to the clinic. Baseline CE levels can reflect ESCC tumor burden. The dynamic changes of CE levels during chemoradiotherapy allow the prediction of treatment effect and PFS of ESCC patients, requiring further investigations in larger patient cohorts.

KLF5 promotes esophageal squamous cell cancer through the transcriptional activation of FGFBP1

Krüpple-like factor 5 (KLF5) is a zinc-finger-containing transcription factor implicated in several human malignancies, but its potential regulatory mechanisms implicated in esophageal squamous cell carcinoma (ESCC) remain elusive. Here, we show that KLF5 is upregulated in ESCC, where its level was significantly associated with tumor differentiation and lymph node metastasis status. Upregulated KLF5 expression promoted the proliferation, migration, and invasion of ESCC cells. Reduced KLF5 showed the opposite effects. Mechanistically, KLF5 exerts its tumor promotion effect by up-regulating fibroblast growth factor binding protein 1 (FGF-BP1) and snail family transcriptional repressor 2 (SNAIL2). KLF5 binds to the promoter regions of FGF-BP1 and transcriptionally activates its expression. Our study indicated that KLF5 could promote esophageal squamous cell cancer proliferation, migration, and invasion by upregulating FGF-BP1/SNAIL2 signaling. Our work suggests that KLF5 might be a proto-oncogene in ESCC and implicated in ESCC metastasis.

A novel autoantibody signatures for enhanced clinical diagnosis of pancreatic ductal adenocarcinoma

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease that requires precise diagnosis for effective treatment. However, the diagnostic value of carbohydrate antigen 19 - 9 (CA19-9) is limited. Therefore, this study aims to identify novel tumor-associated autoantibodies (TAAbs) for PDAC diagnosis.

METHODS

A three-phase strategy comprising discovery, test, and validation was implemented. HuProt™ Human Proteome Microarray v3.1 was used to screen potential TAAbs in 49 samples. Subsequently, the levels of potential TAAbs were evaluated in 477 samples via enzyme-linked immunosorbent assay (ELISA) in PDAC, benign pancreatic diseases (BPD), and normal control (NC), followed by the construction of a diagnostic model.

RESULTS

In the discovery phase, protein microarrays identified 167 candidate TAAbs. Based on bioinformatics analysis, fifteen tumor-associated antigens (TAAs) were selected for further validation using ELISA. Ten TAAbs exhibited differentially expressed in PDAC patients in the test phase (P < 0.05), with an area under the curve (AUC) ranging from 0.61 to 0.76. An immunodiagnostic model including three TAAbs (anti-HEXB, anti-TXLNA, anti-SLAMF6) was then developed, demonstrating AUCs of 0.81 (58.0% sensitivity, 86.0% specificity) and 0.78 (55.71% sensitivity, 87.14% specificity) for distinguishing PDAC from NC. Additionally, the model yielded AUCs of 0.80 (58.0% sensitivity, 86.25% specificity) and 0.83 (55.71% sensitivity, 100% specificity) for distinguishing PDAC from BPD in the test and validation phases, respectively. Notably, the combination of the immunodiagnostic model with CA19-9 resulted in an increased positive rate of PDAC to 92.91%.

CONCLUSION

The immunodiagnostic model may offer a novel serological detection method for PDAC diagnosis, providing valuable insights into the development of effective diagnostic biomarkers.

Giant Magnetoresistance Based Biosensors for Cancer Screening and Detection

Early-stage screening of cancer is critical in preventing its development and therefore can improve the prognosis of the disease. One accurate and effective method of cancer screening is using high sensitivity biosensors to detect optically, chemically, or magnetically labeled cancer biomarkers. Among a wide range of biosensors, giant magnetoresistance (GMR) based devices offer high sensitivity, low background noise, robustness, and low cost. With state-of-the-art micro- and nanofabrication techniques, tens to hundreds of independently working GMR biosensors can be integrated into fingernail-sized chips for the simultaneous detection of multiple cancer biomarkers (i.e., multiplexed assay). Meanwhile, the miniaturization of GMR chips makes them able to be integrated into point-of-care (POC) devices. In this review, we first introduce three types of GMR biosensors in terms of their structures and physics, followed by a discussion on fabrication techniques for those sensors. In order to achieve target cancer biomarker detection, the GMR biosensor surface needs to be subjected to biological decoration. Thus, commonly used methods for surface functionalization are also reviewed. The robustness of GMR-based biosensors in cancer detection has been demonstrated by multiple research groups worldwide and we review some representative examples. At the end of this review, the challenges and future development prospects of GMR biosensor platforms are commented on. With all their benefits and opportunities, it can be foreseen that GMR biosensor platforms will transition from a promising candidate to a robust product for cancer screening in the near future.

The role of microbiota in esophageal squamous cell carcinoma: A review of the literature

Esophageal squamous cell carcinoma (ESCC) exhibits high incidence with poor prognosis. Alcohol drinking, cigarette smoking, and betel nut chewing are well-known risk factors. Dysbiosis, an imbalance of the microbiota residing in a local environment, is known to be associated with human diseases, especially cancer. This article reviews the current evidence of esophageal microbiota in ESCC carcinogenesis, including initiation, progression, and drug resistance. Articles involving the esophageal microbiota, diagnosis, treatment, and the progression of esophageal cancer were acquired using a comprehensive literature search in PubMed in recent 10 years. Based on 16S rRNA sequencing of human samples, cell, and animal studies, current evidence suggests dysbiosis of the esophagus promotes ESCC progression and chemotherapy resistance, leading to a poor prognosis. Smoking and drinking are associated with esophageal dysbiosis. Specific bacteria have been reported to promote carcinogenesis, involving either progression or drug resistance in ESCC, for example Porphyromonas gingivalis and Fusobacterium nucleatum. These bacteria promote ESCC cell proliferation and migration via the TLR4/NF-κB and IL-6/STAT3 pathways. F. nucleatum induces cisplatin resistance via the enrichment of immunosuppressive myeloid-derived suppressor cells (MDSCs). Correcting the dysbiosis and reducing the abundance of specific esophageal pathogens may help in suppressing cancer progression. In conclusion, esophageal dysbiosis is associated with ESCC progression and chemoresistance. Screening the oral and esophageal microbiota is a potential diagnostic tool for predicting ESCC development or drug-resistance. Repairing esophageal dysbiosis is a novel treatment for ESCC. Clinical trials with probiotics in addition to current chemotherapy are warranted to study the therapeutic effects.

Development and Validation of the Oxidative Stress Related lncRNAs for Prognosis in Esophageal Squamous Cell Carcinoma

Esophageal squamous cell cancer (ESCC) is an aggressive disease associated with a poor prognosis. Long non-coding RNAs (lncRNAs) and oxidative stress play crucial roles in tumor progression. We aimed to identify an oxidative stress-related lncRNA signature that could predict the prognosis in ESCC. In the GSE53625 dataset, we identified 332 differentially expressed lncRNAs (DElncRNAs) between ESCC and control samples, out of which 174 were oxidative stress-related DElncRNAs. Subsequently, seven oxidative stress-related DElncRNAs (CCR5AS, LINC01749, PCDH9-AS1, TMEM220-AS1, KCNMA1-AS1, SNHG1, LINC01672) were selected based on univariate and LASSO Cox to build a prognostic risk model, and their expression was detected by RT-qPCR. The model exhibited an excellent ability for the prediction of overall survival (OS) and other clinicopathological traits using Kaplan-Meier (K-M) survival curves, receiver operating characteristic (ROC) curves, and the Wilcoxon test. Additionally, analysis of infiltrated immune cells and immune checkpoints indicated differences in immune status between the two risk groups. Finally, the in vitro experiments showed that PCDH9-AS1 overexpression inhibited proliferation ability and promoted apoptosis and oxidative stress levels in ESCC cells. In conclusion, our study demonstrated that a novel oxidative stress-related DElncRNA prognostic model performed favorably in predicting ESCC patient prognosis and benefits personalized clinical applications.

A novel diagnostic signature of circulating tsRNAs and miRNAs in esophageal squamous cell carcinoma detected with a microfluidic platform

Small non-coding RNAs (sncRNAs) consisting of tRNA-derived small RNAs (tsRNAs) and miRNAs can be released by cancer cells and detected in blood, offering great potential for diagnosis of malignant tumors such as squamous cell carcinoma of the esophagus (ESCC). One of the major challenges for the clinical application of blood-based sncRNAs biomarkers is the difficulty of detection because of their small sncRNA size and low abundance. The deferentially expressed tsRNAs and miRNAs in plasma were studied with high-throughput sequencing and polymerase chain reaction in ESCC cohorts. A novel signature containing tRF-55:74-chrM.Phe-GAA, tRF-56:75-Ala-CGC-1-M4 and miR-4488 was identified with diagnostic potential. The signature was further confirmed by an attomolar-level ultrasensitive and rapid microfluidic biochip, which can achieve a multiplex, simple and low-cost detection. Our results indicated that a combination of tsRNAs and miRNAs has high diagnostic efficiency and tremendous potential to act as specific biomarkers through a reliable, highly sensitive, fast, and economic microfluidic biochip for ESCC diagnosis.

Diagnostic value of circulating microRNAs for esophageal cancer: a meta-analysis based on Asian data

BACKGROUND AND OBJECTIVE

esophageal cancer (EC) is one of the most common gastrointestinal malignant diseases. We conducted a comprehensive meta-analysis to explore the clinical applicability of circulating microRNA for the diagnosis of EC.

METHODS

as of September 10, 2021, a comprehensive literature search was conducted on PubMed, Embase, Web of Science, Cochrane Library, Wanfang Database, and China National Knowledge Infrastructure (CNKI) to identify eligible studies. The sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the curve (AUC) were pooled to evaluate the test performance. The potential sources of heterogeneity were analyzed by subgroup analysis. Deeks' funnel plot was used to assess publication bias.

RESULTS

85 studies from 50 articles were included in the current meta-analysis. The overall pooled sensitivity was 0.82 (95 % CI, 0.79-0.84), specificity was 0.84 (95 % CI, 0.81-0.86), PLR was 4.9 (95 % CI, 4.2-5.9), NLR was 0.22 (95 % CI, 0.19-0.25), DOR was 22 (95 % CI, 17-29) and AUC was 0.89 (95 % CI, 0.86-0.92), respectively. Subgroup analysis suggested that miRNA clusters with a large sample size showed better diagnostic accuracy. Publication bias was not found.

CONCLUSIONS

circulating miRNAs can be used as a potential non-invasive biomarker for the diagnosis of EC in Asian populations.

Advances in targeted therapy and immunotherapy for esophageal cancer

ABSTRACT

Esophageal cancer (EC) is one of the most common aggressive malignant tumors in the digestive system with a severe epidemiological situation and poor prognosis. The early diagnostic rate of EC is low, and most EC patients are diagnosed at an advanced stage. Multiple multimodality treatments have gradually evolved into the main treatment for advanced EC, including surgery, chemotherapy, radiotherapy, targeted therapy, and immunotherapy. And the emergence of targeted therapy and immunotherapy has greatly improved the survival of EC patients. This review highlights the latest advances in targeted therapy and immunotherapy for EC, discusses the efficacy and safety of relevant drugs, summarizes related important clinical trials, and tries to provide references for therapeutic strategy of EC.

The interplay of signaling pathways and miRNAs in the pathogenesis and targeted therapy of esophageal cancer

Globally, esophageal cancer (EC) is the 6th leading cause of cancer-related deaths and the second deadliest gastrointestinal cancer. Multiple genetic and epigenetic factors, such as microRNAs (miRNAs), influence its onset and progression. miRNAs are short nucleic acid molecules that can regulate multiple cellular processes by regulating gene expression. Therefore, EC initiation, progression, apoptosis evasions, invasion capacity, promotion, angiogenesis, and epithelial-mesenchymal transition (EMT) enhancement are associated with miRNA expression dysregulation. Wnt/-catenin signaling, Mammalian target of rapamycin (mTOR)/P-gp, phosphoinositide-3-kinase (PI3K)/AKT/c-Myc, epidermal growth factor receptor (EGFR), and transforming growth factor (TGF)-β signaling are crucial pathways in EC that are controlled by miRNAs. This review was conducted to provide an up-to-date assessment of the role of microRNAs in EC pathogenesis and their modulatory effects on responses to various EC treatment modalities.

Long intergenic non-protein coding RNA 00858 participates in the occurrence and development of esophageal squamous cell carcinoma through the activation of the FTO-m6A-MYC axis by recruiting ZNF184

OBJECTIVES

We aimed at probing impact of LINC00858 on esophageal squamous cell carcinoma (ESCC) progression via ZNF184-FTO-m⁶A-MYC axis.

METHODS

Expression of related genes (LINC00858, ZNF184, FTO, and MYC) was detected in ESCC tissues or cells and their relationships were assessed. After expression alterations in ESCC cells, cell proliferation, invasion, migration, and apoptosis were detected. Tumor formation in nude mice was conducted.

RESULTS

LINC00858, ZNF184, FTO, and MYC were overexpressed in ESCC tissues and cells. LINC00858 enhanced ZNF184 expression to upregulate FTO, which augmented MYC expression. LINC00858 knockdown diminished ESCC cell proliferative, migratory, and invasive properties while elevating apoptosis, which was negated by FTO overexpression. FTO knockdown exerted similar functions of LINC00858 knockdown on ESCC cell movements, which was annulled by MYC upregulation. Silencing LINC00858 repressed tumor growth and related gene expression in nude mice.

CONCLUSIONS

LINC00858 modulated MYC m⁶A modification via FTO by recruiting ZNF184, thus facilitating ESCC progression.

Evolution of the scientific literature on esophageal cancer from 1945 to 2020: a bibliometric analysis

The aim of this study was to use bibliometric techniques to provide a longitudinal view of the evolution over more than 50 years of the literature on esophageal cancer without focusing on a specific area. The Web of Science Core Collection database was searched for published articles on esophageal neoplasm. Different aspects of the articles were analyzed - country, journal, authors, keywords, and topics. The search returned 24,215 articles - the journal Diseases of the Esophagus present the most number of manuscripts (n = 858), followed by Annals of Surgical Oncology (n = 475).The most cited article was one by van Hagen et al. (2012) (2,807 citations). The most prevalent topic was oncology (n = 10,448), followed by surgery (n = 4,944). Most articles were original research (n = 22,697), mainly with the basic science study design and published by institutions in China. The analysis of the variables chosen, identified China as the country with the highest number of articles and showed that authors and institutions in Asia stand out when it comes to production of scientific information on esophageal cancer.

Biomarkers for Early Detection, Prognosis, and Therapeutics of Esophageal Cancers

Esophageal cancer (EC) is the deadliest cancer worldwide, with a 92% annual mortality rate per incidence. Esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC) are the two major types of ECs, with EAC having one of the worst prognoses in oncology. Limited screening techniques and a lack of molecular analysis of diseased tissues have led to late-stage presentation and very low survival durations. The five-year survival rate of EC is less than 20%. Thus, early diagnosis of EC may prolong survival and improve clinical outcomes. Cellular and molecular biomarkers are used for diagnosis. At present, esophageal biopsy during upper endoscopy and histopathological analysis is the standard screening modality for both ESCC and EAC. However, this is an invasive method that fails to yield a molecular profile of the diseased compartment. To decrease the invasiveness of the procedures for diagnosis, researchers are proposing non-invasive biomarkers for early diagnosis and point-of-care screening options. Liquid biopsy involves the collection of body fluids (blood, urine, and saliva) non-invasively or with minimal invasiveness. In this review, we have critically discussed various biomarkers and specimen retrieval techniques for ESCC and EAC.

Current Status and Future Prospects for Esophageal Cancer

Esophageal cancer (EC) is the ninth most common cancer and the sixth leading cause of cancer deaths worldwide. Esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC) are the two main histological subtypes with distinct epidemiological and clinical features. While the global incidence of ESCC is declining, the incidence of EAC is increasing in many countries. Decades of epidemiologic research have identified distinct environmental exposures for ESCC and EAC subtypes. Recent advances in understanding the genomic aspects of EC have advanced our understanding of EC causes and led to using specific genomic alterations in EC tumors as biomarkers for early diagnosis, treatment, and prognosis of this cancer. Nevertheless, the prognosis of EC is still poor, with a five-year survival rate of less than 20%. Currently, there are significant challenges for early detection and secondary prevention for both ESCC and EAC subtypes, but Cytosponge™ is shifting this position for EAC. Primary prevention remains the preferred strategy for reducing the global burden of EC. In this review, we will summarize recent advances, current status, and future prospects of the studies related to epidemiology, time trends, environmental risk factors, prevention, early diagnosis, and treatment for both EC subtypes.

Genome-wide methylation profiling identify hypermethylated HOXL subclass genes as potential markers for esophageal squamous cell carcinoma detection

BACKGROUND

Numerous studies have revealed aberrant DNA methylation in esophageal squamous cell carcinoma (ESCC). However, they often focused on the partial genome, which resulted in an inadequate understanding of the shaped methylation features and the lack of available methylation markers for this disease.

METHODS

The current study investigated the methylation profiles between ESCC and paired normal samples using whole-genome bisulfite sequencing (WGBS) data and obtained a group of differentially methylated CpGs (DMC), differentially methylated regions (DMR), and differentially methylated genes (DMG). The DMGs were then verified in independent datasets and Sanger sequencing in our custom samples. Finally, we attempted to evaluate the performance of these genes as methylation markers for the classification of ESCC.

RESULTS

We obtained 438,558 DMCs, 15,462 DMRs, and 1568 DMGs. The four significantly enriched gene families of DMGs were CD molecules, NKL subclass, HOXL subclass, and Zinc finger C2H2-type. The HOXL subclass homeobox genes were observed extensively hypermethylated in ESCC. The HOXL-score estimated by HOXC10 and HOXD1 methylation, whose methylation status were then confirmed by sanger sequencing in our custom ESCC samples, showed good ability in discriminating ESCC from normal samples.

CONCLUSIONS

We observed widespread hypomethylation events in ESCC, and the hypermethylated HOXL subclass homeobox genes presented promising applications for the early detection of esophageal squamous cell carcinoma.

Investigating the predictive value of vascular endothelial growth factor in the evaluation of treatment efficacy and prognosis for patients with non-surgical esophageal squamous cell carcinoma

In this study, we aim to investigate the predictive value of serum vascular endothelial growth factor (VEGF) in evaluating treatment efficacy and long-term prognosis for patients with non-surgical esophageal squamous cell carcinoma (ESCC). The patients diagnosed with ESCC by histopathology who didn’t receive surgical treatment were retrospectively analyzed. Through follow-up and prognostic analysis, we explored the value of serum VEGF changes before, during, and after radiotherapy for predicting treatment efficacy, and identified important indicators to construct the predictive model. Eighty-four patients were enrolled in this study, and the objective response rate (ORR) after treatment was 75.0%. The serum VEGF before, during and after radiotherapy were 108.2 ± 38.4, 98.6 ± 20.3 and 96.9 ± 20.0pg/ml, respectively. Staging and serum VEGF during radiotherapy were the independent factors affecting the treatment efficacy of non-surgical ESCC patients (OR=0.182 and 0.959, P<0.05). The median overall survival (OS) and progression-free survival (PFS) were 24.4 and 15.8 months. The 3-year, 5-year, 10-year OS rates and PFS rates were 35.7%, 26.2%, 14.4%, and 26.2%, 22.6%, 12.3%, respectively. By performing COX regression analysis, we found that the TNM stage, changes of VEGF after radiotherapy (∆VEGF2), and endoscopic histopathological response were the independent prognostic factors for OS and PFS (P<0.05). The R² of the constructed prediction model was 0.328 and 0.362, and the C-index was 0.697 and 0.708, respectively. The follow-up time-dependent AUC showed that the predicted AUC was stable and greater than 0.7 as the follow-up time increased. For patients with non-surgical ESCC, those with low VEGF levels during radiotherapy had better treatment efficacy, and those with significant VEGF reduction after radiotherapy had a better prognosis. In summary, our results demonstrate that it is feasible to construct a model to evaluate and predict the efficacy and prognosis of patients with non-surgical ESCC based on serum VEGF measurement.

Machine Learning and Novel Biomarkers Associated with Immune Infiltration for the Diagnosis of Esophageal Squamous Cell Carcinoma

Esophageal squamous cell carcinoma (ESCC) accounts for the main esophageal cancer type, which is related to advanced stage and poor survivals. Therefore, novel diagnostic biomarkers are critically needed. In the current research, we aimed to screen novel diagnostic biomarkers based on machine learning. The expression profiles were obtained from GEO datasets (GSE20347, GSE38129, and GSE75241) and TCGA datasets. Differentially expressed genes (DEGs) were screened between 47 ESCC and 47 nontumor samples. The LASSO regression model and SVM-RFE analysis were carried out for the identification of potential markers. ROC analysis was carried out to assess discriminatory abilities. The expressions and diagnostic values of the candidates in ESCC were demonstrated in the GSE75241 datasets and TCGA datasets. We also explore the correlations between the critical genes and cancer immune infiltrates using CIBERSORT. In this study, we identified 27 DEGs in ESCC: 5 genes were significantly elevated, and 22 genes were significantly decreased. Based on the results of the SVM-RFE and LASSO regression model, we identified five potential diagnostic biomarkers for ESCC, including GPX3, COL11A1, EREG, MMP1, and MMP12. However, the diagnostic values of only GPX3, MMP1, and MMP12 were confirmed in GSE75241 datasets. Moreover, in TCGA datasets, we further confirmed that GPX3 expression was distinctly decreased in ESCC specimens, while the expression of MMP1 and MMP12 was noticeably increased in ESCC specimens. Immune cell infiltration analysis revealed that the expression of GPX3, MMP1, and MMP12 was associated with several immune, such as T cells CD8, macrophages M2, macrophages M0, and dendritic cells activated. Overall, our findings suggested GPX3, MMP1, and MMP12 as novel diagnostic marker and correlated with immune infiltrates in ESCC patients.

Performance of screening tests for esophageal squamous cell carcinoma: a systematic review and meta-analysis

BACKGROUND AND AIMS

This systematic review and meta-analysis aims to compare the pooled diagnostic accuracy of the currently available esophageal squamous cell carcinoma (ESCC) screening tests.

METHODS

A comprehensive literature search of Embase and Medline (up to October 31, 2020) was performed to identify eligible studies. We pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio for ESCC screening tools using a bivariate random-effects model. The summary receiver operating characteristic curves with area under the curve (AUC) were plotted for each screening test.

RESULTS

We included 161 studies conducted in 81 research articles involving 32,209 subjects. The pooled sensitivity, specificity, and AUC of the major screening tools were respectively as follows: endoscopy (peroral endoscopy): .94 (95% confidence interval [CI], .87-.97), .92 (95% CI, .87-.95), and .97 (95% CI, .96-.99); endoscopy (transnasal endoscopy): .85 (95% CI, .70-.93), .96 (95% CI, .91-.98), and .97 (95% CI, .95-.98); microRNA: .77 (95% CI, .75-.80), .78 (95% CI, .75-.80), and .85 (95% CI, .81-.87); autoantibody: .45 (95% CI, .36-.53), .91 (95% CI, .89-.93), and .84 (95% CI, .81-.87); and cytology: .82 (95% CI, .60-.93), .97 (95% CI, .88-.99), and .97 (95% CI, .95-.98). There was high heterogeneity.

CONCLUSIONS

The diagnostic accuracy seemed to be comparable between cytology and endoscopy, whereas autoantibody and microRNAs bear potential as future noninvasive screening tools for ESCC. To reduce ESCC-related death in high-risk populations, it is important to develop a more accurate and less-invasive screening test.

Identification of immunophenotypes in esophageal squamous cell carcinoma based on immune gene sets

PURPOSE

Esophageal squamous cell carcinoma (ESCC) is a malignant tumor with high heterogeneity. Research on molecular mechanisms involved in the process of tumor origination and progression is extremely limited to investigating mechanisms of molecular typing for ESCC.

METHODS

After comprehensively analyzing the gene expression profiles in The Cancer Genome Atlas and Gene Expression Omnibus databases, we identified four immunotypes of ESCC (referred to as C1-C4) based on the gene sets of 28 immune cell subpopulations. The discrepancies in prognostic value, clinical features, drug sensitivity, and tumor components between the immunotypes were individually analyzed.

RESULTS

The ranking of immune infiltration is C1 > C4 > C3 > C2. These subtypes are characterized by high and low expression of immune checkpoint proteins, enrichment and insufficiency of immune-related pathways, and differential distribution of immune cell subgroups. Poorer survival was observed in the C1 subtype, which we hypothesized could be caused by an immunosuppressive cell population. Fortunately, C1's susceptibility to anti-PD-1 therapy offers hope for patients with poor prognosis in advanced stages. On the other hand, C4 is sensitive to docetaxel, which may offer novel treatment strategies for ESCC in the future. It is worth noting that immunophenotyping is tightly bound to the abundance of stromal components and stem cells, which could explain the tumor immune escape to some extent. Ultimately, determination of hub genes based on the C1 subtypes provides a reference for the discovery of immunotarget drugs against ESCC.

CONCLUSION

The identification of immunophenotypes in our study provides new therapeutic strategies for patients with ESCC.

Tobacco Smoking and Gastrointestinal Cancer Risk

BACKGROUND

Smoking tobacco is the most preventable cause of gastrointestinal (GI) cancer disease in Germany. The more and the longer you smoke, the higher your risk of GI cancer. About 28% of 18-64 year-old Germans are current smokers; in addition, 11% of the population is regularly exposed to secondhand tobacco smoke.

SUMMARY

Tobacco use is causally associated with esophageal, gastric, pancreatic, biliary, hepatocellular, colorectal, and anal cancers. Combining smoking with alcohol use, excess body weight, diabetes, or chronic infections synergistically enhances GI cancer risk. Smoking cessation effectively reduces tobacco-associated GI cancer risk.

KEY MESSAGES

Smokers should be encouraged to stop smoking tobacco and join programs of risk-adaptive cancer screening.

Cancer-Secreted Exosomal MiR-620 Inhibits ESCC Aerobic Glycolysis via FOXM1/HER2 Pathway and Promotes Metastasis

Background

Esophageal squamous cell carcinoma (ESCC) is a leading cause of cancer death worldwide. MicroRNAs (MiRNAs) have been reported to regulate cell functions through exosomes. Through the Gene Expression Omnibus (GEO) database, miR-620 was selected as a serum miRNA highly expressed in ESCC, but its detailed role in ESCC has not been explored. Tumor-secreted miRNAs have been reported to promote cancer metastasis through reprogramming the aerobic glycolysis of lung fibroblasts. Therefore, we intended to verify whether exosomal miR-620 secreted in ESCC cells may regulate the aerobic glycolysis of lung fibroblasts.

Methods

The effect of miR-620 on the aerobic glycolysis of ESCC cells was firstly verified through bioinformatics prediction and mechanism assays. Exosomes secreted from ESCC cells was detected, and the influence of exosomal miR-620 in regulating the aerobic glycolysis of lung fibroblasts was then verified both in vitro and in vivo.

Results

MiR-620 inhibited ESCC malignancy and suppressed the aerobic glycolysis of ESCC cells via targeting Forkhead box M1 (FOXM1) and human epidermal growth factor receptor 2 (HER2). Moreover, exosomal miR-620 was highly secreted in ESCC and could regulate HFL1 aerobic glycolysis via FOXM1/HER2 signaling. Furthermore, exosomal miR-620 could promote ESCC metastasis by reprogramming the aerobic glycolysis of lung fibroblasts (HFL1).

Conclusion

Exosomal miR-620 secreted by ESCC cells inhibited the aerobic glycolysis via FOXM1/HER2 axis and promoted cancer metastasis.

RNA Sequencing of Tumor-Educated Platelets Reveals a Three-Gene Diagnostic Signature in Esophageal Squamous Cell Carcinoma

There is no cost-effective, accurate, and non-invasive method for the detection of esophageal squamous cell carcinoma (ESCC) in clinical practice. We aimed to investigate the diagnostic potential of tumor-educated platelets in ESCC. In this study, seventy-one ESCC patients and eighty healthy individuals were enrolled and divided into a training cohort (23 patients and 27 healthy individuals) and a validation cohort (48 patients and 53 healthy individuals). Next-generation RNA sequencing was performed on platelets isolated from peripheral blood of all participants, and a support vector machine/leave-one-out cross validation (SVM/LOOCV) approach was used for binary classification. A diagnostic signature composed of ARID1A, GTF2H2, and PRKRIR discriminated ESCC patients from healthy individuals with 91.3% sensitivity and 85.2% specificity in the training cohort and 87.5% sensitivity and 81.1% specificity in the validation cohort. The AUC was 0.924 (95% CI, 0.845–0.956) and 0.893 (95% CI, 0.821–0.966), respectively, in the training cohort and validation cohort. This 3-gene platelet RNA signature could effectively discriminate ESCC from healthy control. Our data highlighted the potential of tumor-educated platelets for the noninvasive diagnosis of ESCC. Moreover, we found that keratin and collagen protein families and ECM-related pathways might be involved in tumor progression and metastasis of ESCC, which might provide insights to understand ESCC pathobiology and advance novel therapeutics.

Liquid Biopsy in Squamous Cell Carcinoma of the Esophagus and of the Head and Neck

Squamous cell carcinomas of the esophagus (ESCC) and of the head and neck (HNSCC) are two neoplasms that share common risk factors and have the same embryological origin, but a very different prognosis, the 5-year survival of HNSCC being almost double (40–50%) compared to the 5-year survival of ESCC (20%). Current guidelines emphasize the importance of screening for ESCC in patients diagnosed with head and neck cancers. A liquid biopsy is a novel tool for diagnosis, prognostic stratification, and personalized therapy. Liquid biopsy biomarkers for these two malignancies could help both their early detection, facilitate residual disease identification, and provide prognosis information. The present systematic review of the literature was aimed at describing the liquid biopsy biomarkers present in these two malignancies, with an emphasis on potential clinical applications.

Investigation of serum markers of esophageal squamous cell carcinoma based on machine learning methods

Esophageal squamous cell carcinoma (ESCC) is one of the malignant tumors with high mortality in humans, and there is a lack of effective and convenient early diagnosis methods. By analyzing the serum miRNA expression data in ESCC tumor samples and normal samples, on the basis of the max-relevance and min-redundancy (mRMR) feature selection and the incremental feature selection (IFS) method, a random forest classifier constructed by 5 feature miRNAs was acquired in our study. The receiver operator characteristic (ROC) curve showed that the model was able to distinguish samples. Principal component analysis (PCA) and sample hierarchical cluster analysis showed that 5 feature miRNAs could well distinguish ESCC patients from healthy individuals. The expression levels of miR-663a, miR-5100 and miR-221-3p all showed a higher expression level in ESCC patients than those in healthy individuals. On the contrary, miR-6763-5p and miR-7111-5p both showed lower expression levels in ESCC patients than those in healthy individuals. In addition, the collected clinical serum samples were used for qRT-PCR analysis. It was uncovered that the expression trends of the 5 feature miRNAs followed a similar pattern with those in the training set. The above findings indicated that the 5 feature miRNAs may be serum tumor markers of ESCC. This study offers new insights for the early diagnosis of ESCC.

Circulating Long Non-Coding RNAs LINC00324 and LOC100507053 as Potential Liquid Biopsy Markers for Esophageal Squamous Cell Carcinoma: A Pilot Study

Background

Despite the availability of advanced technology to detect and treat esophageal squamous cell carcinoma (ESCC), the 5-year survival rate of ESCC patients is still meager. Recently, long non-coding RNAs (lncRNAs) have emerged as essential players in the diagnosis and prognosis of various cancers.

Objective

This pilot study focused on identifying circulating lncRNAs as liquid biopsy markers for the ESCC.

Methodology

We performed next-generation sequencing (NGS) to profile circulating lncRNAs in ESCC and healthy individuals’ blood samples. The expression of the top five upregulated and top five downregulated lncRNAs were validated through quantitative real-time PCR (qRT-PCR), including samples used for the NGS. Later, we explored the diagnostic/prognostic potential of lncRNAs and their impact on the clinicopathological parameters of patients. To unravel the molecular target and pathways of identified lncRNAs, we utilized various bioinformatics tools such as lncRnome, RAID v2.0, Starbase, miRDB, TargetScan, Gene Ontology, and KEGG pathways.

Results

Through NGS profiling, we obtained 159 upregulated, 137 downregulated, and 188 neutral lncRNAs in ESCC blood samples compared to healthy individuals. Among dysregulated lncRNAs, we observed LINC00324 significantly upregulated (2.11-fold; p-value = 0.0032) and LOC100507053 significantly downregulated (2.22-fold; p-value = 0.0001) in ESCC patients. Furthermore, we found LINC00324 and LOC100507053 could discriminate ESCC cancer patients’ from non-cancer individuals with higher accuracy of Area Under the ROC Curve (AUC) = 0.627 and 0.668, respectively. The Kaplan-Meier and log-rank analysis revealed higher expression levels of LINC00324 and lower expression levels of LOC100507053 well correlated with the poor prognosis of ESCC patients with a Hazard ratio of LINC00324 = 2.48 (95% CI: 1.055 to 5.835) and Hazard ratio of LOC100507053 = 4.75 (95% CI: 2.098 to 10.76)]. Moreover, we also observed lncRNAs expression well correlated with the age (>50 years), gender (Female), alcohol, tobacco, and hot beverages consumers. Using bioinformatics tools, we saw miR-493-5p as the direct molecular target of LINC00324 and interacted with the MAPK signaling pathway in ESCC pathogenesis.

Conclusion

This pilot study suggests that circulating LINC00324 and LOC100507053 can be used as a liquid biopsy marker of ESCC; however, multicentric studies are still warranted.

Bioinformatics Characterization of Candidate Genes Associated with Gene Network and miRNA Regulation in Esophageal Squamous Cell Carcinoma Patients

The present study aimed to identify potential therapeutic targets for esophageal squamous cell carcinoma (ESCC). The gene expression profile GSE161533 contained 84 samples, in that 28 tumor tissues and 28 normal tissues encoded as ESCC patients were retrieved from the Gene Expression Omnibus database. The obtained data were validated and screened for differentially expressed genes (DEGs) between normal and tumor tissues with the GEO2R tool. Next, the protein–protein network (PPI) was constructed using the (STRING 2.0) and reconstructed with Cytoscape 3.8.2, and the top ten hub genes (HGsT10) were predicted using the Maximal Clique Centrality (MCC) algorithm of the CytoHubba plugin. The identified hub genes were mapped in GSE161533, and their expression was determined and compared with The Cancer Genome Atlas (TCGA.) ESCC patient’s samples. The overall survival rate for HGsT10 wild and mutated types was analyzed with the Gene Expression Profiling Interactive Analysis2 (GEPIA2) server and UCSC Xena database. The functional and pathway enrichment analysis was performed using the WebGestalt database with the reference gene from lumina human ref 8.v3.0 version. The promoter methylation for the HGsT10 was identified using the UALCAN server. Additionally, the miRNA-HGsT10 regulatory network was constructed to identify the top ten hub miRNAs (miRT10). Finally, we identified the top ten novel driving genes from the DEGs of GSE161533 ESCC patient’s sample using a multi-omics approach. It may provide new insights into the diagnosis and treatment for the ESCC affected patients early in the future.

Suprabasin: Role in human cancers and other diseases

Suprabasin (SBSN), a gene with unknown function located in q13 region of chromosome 19, was first found to be expressed in the basal layer of the stratified epithelium in mouse and human tissues and was thought to be a potential precursor of keratinized capsules. However, in recent years, significant progress has been made in the study of SBSN in a variety of human diseases. One common theme appears to be the effect of SBSN on tumor progression, such as invasion, metastasis and resistance. However, the function and mechanism of action of SBSN is still elusive. In this study, we reviewed the literature on SBSN in the PubMed database to identify the basic characteristics, biological functions, and roles of SBSN in cancer and other diseases. In particular, we focused on the potential mechanisms of SBSN activity, to improve our understanding of the complex function of this protein and provide a theoretical basis for further research on the role of SBSN in cancer and other diseases.

Quantitative immunohistochemistry (IHC) analysis of biomarker combinations for human esophageal squamous cell carcinoma

Background

Esophageal squamous carcinoma (ESCC) is one of the most common cancers in developing countries. However, currently there are no specific biomarkers for ESCC. This study evaluated the expression of proliferating cell nuclear antigen (PCNA), tumor suppressor protein p53, epidermal growth factor receptor (EGFR), and vascular endothelial growth factor (VEGF) as biomarkers for ESCC.

Methods

This study included 60 clinical cases (30 ESCC and 30 non-ESCC cases that were confirmed pathologically). The expression of PCNA, p53, EGFR, and VEGF were investigated using a quantitative computerized immunohistochemistry (IHC) method. The expression level of each protein was indicated by a H-score from the quantitative analysis. Receiver operating characteristic curve (ROC) and area under curve (AUC) analyses were performed. The sensitivity and specificity of each individual protein and combinations of the proteins were calculated.

Results

The H-score analysis indicated that expressions of EGFR, PCNA, and VEGF were statistically significantly higher in ESCC than non-ESCC patients; however, p53 was not. The panels of combinations of these proteins were more sensitive than that of any single protein. In the triplicate combination, the AUC prediction probability increased to 0.86, while the single protein AUC prediction probabilities were 0.74 (EGFR), 0.80 (PCNA), and 0.70 (VEGF).

Conclusions

The high expression of PCNA, EGFR, and VEGF suggests that they are potential biomarkers for ESCC. The combination of these biomarkers may provide targets for molecular therapy and molecular imaging.

Identification of diagnostic markers and lipid dysregulation in oesophageal squamous cell carcinoma through lipidomic analysis and machine learning

BACKGROUND

Oesophageal cancer (EC) ranks high in both morbidity and mortality. A non-invasive and high-sensitivity diagnostic approach is necessary to improve the prognosis of EC patients.

METHODS

A total of 525 serum samples were subjected to lipidomic analysis. We combined serum lipidomics and machine-learning algorithms to select important metabolite features for the detection of oesophageal squamous cell carcinoma (ESCC), the major subtype of EC in developing countries. A diagnostic model using a panel of selected features was developed and evaluated. Integrative analyses of tissue transcriptome and serum lipidome were conducted to reveal the underlying mechanism of lipid dysregulation.

RESULTS

Our optimised diagnostic model with a panel of 12 lipid biomarkers together with age and gender reaches a sensitivity of 90.7%, 91.3% and 90.7% and an area under receiver-operating characteristic curve of 0.958, 0.966 and 0.818 in detecting ESCC for the training cohort, validation cohort and independent validation cohort, respectively. Integrative analysis revealed matched variation trend of genes encoding key enzymes in lipid metabolism.

CONCLUSIONS

We have identified a panel of 12 lipid biomarkers for diagnostic modelling and potential mechanisms of lipid dysregulation in the serum of ESCC patients. This is a reliable, rapid and non-invasive tumour-diagnostic approach for clinical application.

Modern Diagnosis of Early Esophageal Cancer: From Blood Biomarkers to Advanced Endoscopy and Artificial Intelligence

Simple Summary

Esophageal cancer (EC) has a poor prognosis when the diagnosis is delayed, but curative treatment is possible if the diagnosis is timely. The disease subtly progresses before symptoms prompt patients to seek medical attention. Effective pre-symptomatic screening strategies may improve the outcome of the disease. Recent evidence provided insights into early diagnosis of EC via blood tests, advanced endoscopic imaging, and artificial intelligence. Accordingly, we reviewed available strategies to diagnose early EC.

Abstract

Esophageal cancer (EC) is the seventh most common cancer and the sixth cause of cancer death worldwide. Histologically, esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC) account for up to 90% and 20% of all ECs, respectively. Clinical symptoms such as dysphagia, odynophagia, and bolus impaction occur late in the natural history of the disease, and the diagnosis is often delayed. The prognosis of ESCC and EAC is poor in advanced stages, being survival rates less than 20% at five years. However, when the diagnosis is achieved early, curative treatment is possible, and survival exceeds 80%. For these reasons, mass screening strategies for EC are highly desirable, and several options are currently under investigation. Blood biomarkers offer an inexpensive, non-invasive screening strategy for cancers, and novel technologies have allowed the identification of candidate markers for EC. The esophagus is easily accessible via endoscopy, and endoscopic imaging represents the gold standard for cancer surveillance. However, lesion recognition during endoscopic procedures is hampered by interobserver variability. To fill this gap, artificial intelligence (AI) has recently been explored and provided encouraging results. In this review, we provide a summary of currently available options to achieve early diagnosis of EC, focusing on blood biomarkers, advanced endoscopy, and AI.

Associations of circulating mediators of inflammation, cell regulation and immune response with esophageal squamous cell carcinoma

BACKGROUND

Esophageal squamous cell carcinoma (ESCC) is the most common histologic subtype of esophageal cancer globally. The development of squamous cell carcinoma has important inflammatory influences and effects. We, therefore, examined circulating levels of inflammation- and immune-related proteins for associations with ESCC.

METHODS

We used pre-treatment EDTA plasma from 80 ESCC patients (44% clinical stages I and II) and 80 cancer-free control individuals within the Hospital-based Epidemiologic Research Program at Aichi Cancer Center. Levels of 184 biomarkers were measured by high-throughput multiplexed proximity extension assays using Olink's Proseek Cell Regulation and Immuno-Oncology Panels. ESCC odds ratios (OR) per quantile (based on two to four categories) of each biomarker were calculated by unconditional logistic regression models, adjusted for age, sex, cigarette smoking and alcohol consumption. Correlations among continuous biomarker levels were assessed by Spearman's rank correlation. All statistical tests were two-sided with p values < 0.05 considered as significant. Given the exploratory nature of the study, we did not adjust for multiple comparisons.

RESULTS

Seven proteins were undetectable in nearly all samples. Of the remaining 177 evaluable biomarkers, levels of cluster of differentiation 40 (CD40, per quartile OR 1.64; p trend = 0.018), syntaxin 16 (STX16, per quartile OR 1.63; p trend = 0.008), heme oxygenase 1 (per quartile OR 1.59; p trend = 0.014), and γ-secretase activating protein (GSAP, per quartile OR 1.47; p trend = 0.036) were significantly associated with ESCC. Amongst these significant markers, levels of CD40, STX16, and GSPA were moderately correlated (Rho coefficients 0.46-0.55; p < 0.05).

CONCLUSION

Our case-control study expands the range of inflammation and immune molecules associated with ESCC. These novel findings warrant replication and functional characterization.