Development and Evaluation of Serum CST1 Detection for Early Diagnosis of Esophageal Squamous Cell Carcinoma

Clinical application of serum CST4 combined with tumor markers in the diagnosis of digestive system malignant tumors

The aim of the present study was to evaluate the diagnostic value of plasma human cystatin-S (CST4) in patients with digestive system malignant tumors. CST4 and tumor markers, such as α-fetoprotein (AFP), carcinoembryonic antigen (CEA), carbohydrate antigen (CA)199, CA125, CA153 and CA724, were detected in blood samples from 100 patients with a digestive system malignant tumor and 100 patients with benign digestive system diseases. The tumor markers AFP, CEA, CA199, CA125, CA153 and CA724 were detected using an electrochemiluminescence immunoassay, and CST4 levels were detected using a human CST4 ELISA kit. The results demonstrated that the sensitivities of AFP and CA153 (both 5.00%) were significantly lower than that of CST4 (38.00%) in the diagnosis of digestive system malignancy (P<0.001), and CA724 (18.00%) was also less sensitive than CST4 (P<0.05). The sensitivities of CA199 (26.00%), CEA (31.00%) and CA125 (25.00%) were similar to that of CST4 (P>0.05). There was no significant difference in the CEA, CA125, CA724 and CST4 specificities (P>0.05), which were 91.00, 95.00, 94.00 and 83.00%, respectively. The specificities of AFP (99.00%), CA199 (98.00%) and CA153 (100.00%) were significantly higher than that of CST4 (P<0.01). By constructing a receiver operating characteristic curve and comparing the area under the curve as well as sensitivity, the findings of the present study demonstrated that combining CST4 with AFP, CEA, CA199, CA125, CA153 and CA724 can significantly enhance the diagnostic sensitivity for malignancies of the digestive system. However, the introduction of CST4 into the traditional diagnostic groups (CEA + AFP, CA199 + CA125 + CA153 + CA724 and AFP + CEA + CA199 + CA125 + CA153 + CA724) resulted in an increased sensitivity and loss of specificity, thereby not offering significant advantages in terms of comprehensive diagnostic efficiency compared with the traditional diagnostic groups. In conclusion, CST4 detection may be a promising diagnostic tool. Nonetheless, the potential false positive results in tumor diagnosis should be taken into consideration when developing new diagnostic groups involving CST4.

Salivary metabolomic biomarkers for esophageal and gastric cancers by liquid chromatography-mass spectrometry

Early detection of esophageal and gastric cancers is essential for patients' prognosis; however, optimal noninvasive screening tests are currently not available. Saliva is a biofluid that is readily available, allowing for frequent screening tests. Thus, we explored salivary diagnostic biomarkers for esophageal and gastric cancers using metabolomic analyses. Saliva samples were collected from patients with esophageal (n = 50) and gastric cancer (n = 63), and patients without cancer as controls (n = 20). Salivary metabolites were analyzed by liquid chromatography-mass spectrometry to identify salivary biomarkers. We also examined the metabolic profiles of gastric cancer tissues and compared them with the salivary biomarkers. The sensitivity of the diagnostic models based on salivary biomarkers was assessed by comparing it with that of serum tumor markers. Additionally, using postoperative saliva samples collected from patients with gastric cancer, we analyzed the changes in the biomarkers' concentrations before and after surgery. Cytosine was detected as a salivary biomarker for gastric cancer, and cytosine, 2-oxoglutarate, and arginine were detected as salivary biomarkers for esophageal cancer. Cytidine, a cytosine nucleotide, showed decreased concentrations in gastric cancer tissues. The sensitivity of the diagnostic models for esophageal and gastric cancers was 66.0% and 47.6%, respectively, while that of serum tumor markers was 40%. Salivary cytosine concentration increased significantly postoperatively relative to the preoperative value. In summary, we identified salivary biomarkers for esophageal and gastric cancers, which showed diagnostic sensitivity at least comparable to that of serum tumor markers. Salivary metabolomic tests could be promising screening tests for these types of cancer.

Cysteine protease inhibitor 1 promotes metastasis by mediating an oxidative phosphorylation/MEK/ERK axis in esophageal squamous carcinoma cancer

Cysteine protease inhibitor 1 (CST1) is a cystatin superfamily protein that inhibits cysteine protease activity and is reported to be involved in the development of many malignancies. Mitochondrial oxidative phosphorylation (OXPHOS) also plays an important role in cancer cell growth regulation. However, the relationship and roles of CST1 and OXPHOS in esophageal squamous cell carcinoma (ESCC) remains unclear. In our pilot study, CST1 was shown the potential of promoting ESCC migration and invasion by the activation of MEK/ERK pathway. Transcriptome sequencing analysis revealed that CST1 is closely associated with OXPHOS. Based on a real-time ATP rate assay, mitochondrial complex I enzyme activity assay, immunofluorescence, co-immunoprecipitation, and addition of the OXPHOS inhibitor Rotenone and MEK/ERK inhibitor PD98059, we determined that CST1 affects mitochondrial complex I enzyme activity by interacting with the GRIM19 protein to elevate OXPHOS levels, and a reciprocal regulatory relationship exists between OXPHOS and the MEK/ERK pathway in ESCC cells. Finally, an in vivo study demonstrated the potential of CST1 in ESCC metastasis through regulation of the OXPHOS and MEK/ERK pathways. This study is the first to reveal the oncogenic role of CST1 in ESCC development by enhancing mitochondrial respiratory chain complex I activity to activate the OXPHOS/MEK/ERK axis, and then promote ESCC metastasis, suggesting that CST1/OXPHOS is a promising target for ESCC treatment.

Validation of serum cystatin SN detection for diagnosis and poor prognosis of esophageal squamous cell carcinoma

Background

The identification of effective tumor markers is of paramount importance for the early diagnosis, treatment, and prognosis of esophageal squamous cell carcinoma (ESCC). The present study endeavors to identify efficacious serological markers that can differentiate patients with early-stage ESCC from those with benign esophageal lesions and healthy controls (HC). Cystatin-SN (CST1), an active cysteine protease inhibitor belonging to the Cystatin (CST) superfamily, is implicated in the pathogenesis of inflammation and tumorigenesis. The objective of this investigation is to assess the diagnostic, therapeutic, and prognostic potential of serum CST1 in ESCC.

Methods

In our prior RNA sequencing and screening endeavors, we have identified ten genes that are up-regulated in relation to esophageal cancer. Subsequently, we have verified the gene CST1 from the transcriptome data of the The Cancer Genome Atlas Program (TCGA) and Gene Expression Profiling Interactive Analysis (GEPIA) database. Following this, we conducted an enzyme-linked immunosorbent assay (ELISA) to ascertain the expression levels of CST1 in serum samples from clinical cohorts.

Results

The study revealed a significant elevation in serum CST1 levels among patients with early-stage esophageal squamous cell carcinoma (ESCC) (7.41 ± 4.32 ng/ml) compared to those with esophageal benign lesions (4.67 ± 2.43 ng/ml) (p < 0.0001) and healthy controls (4.87 ± 2.77 ng/ml) (p < 0.0001). The diagnostic sensitivity of CST1 for ESCC was 75.68% (specificity 70.83%, AUC 0.775). Combination of CST1 and SCC-Ag exhibited the AUC up to 0.819. Additionally, serum CST1 levels exhibited a significant decrease at 1-2 weeks post-surgery (4.49 ± 3.31 ng/ml) compared to pre-surgery levels (7.68 ± 3.71 ng/ml) (p<0.0001). Survival analysis demonstrated a strong association between high (844/415-1543 d) or low (1490/645-1710 d) serum CST1 levels at diagnosis and overall survival time (p < 0.001). Furthermore, multivariate regression analysis confirmed CST1 (p=0.024, HR=2.023, 95%CI 1.099-3.725) as an independent prognostic factor.

Conclusion

Serum CST1 has the potential to function as a diagnostic indicator for distinguishing early-stage esophageal squamous cell carcinoma (ESCC) from individuals with benign esophageal lesions and healthy individuals. Additionally, it could serve as a prognostic predictor and therapeutic efficacy indicator for patients with ESCC.

Diagnosis of Esophageal Squamous Cell Carcinoma by High-Performance Serum Metabolic Fingerprints: A Retrospective Study

Esophageal squamous cell carcinoma (ESCC) is a highly prevalent and aggressive malignancy, and timely diagnosis of ESCC contributes to an increased cancer survival rate. However, current detection methods for ESCC mainly rely on endoscopic examination, limited by a relatively low participation rate. Herein, ferric-particle-enhanced laser desorption/ionization mass spectrometry (FPELDI MS) is utilized to record the serum metabolic fingerprints (SMFs) from a retrospective cohort (523 non-ESCC participants and 462 ESCC patients) to build diagnostic models toward ESCC. The PFELDI MS achieved high speed (≈30 s per sample), desirable reproducibility (coefficients of variation < 15%), and high throughput (985 samples with ≈124 200 data points for each spectrum). Desirable diagnostic performance with area-under-the-curves (AUCs) of 0.925-0.966 is obtained through machine learning of SMFs. Further, a metabolic biomarker panel is constructed, exhibiting superior diagnostic sensitivity (72.2-79.4%, p < 0.05) as compared with clinical protein biomarker tests (4.3-22.9%). Notably, the biomarker panel afforded an AUC of 0.844 (95% confidence interval [CI]: 0.806-0.880) toward early ESCC diagnosis. This work highlighted the potential of metabolic analysis for accurate screening and early detection of ESCC and offered insights into the metabolic characterization of diseases including but not limited to ESCC.

Ensembled CNN with artificial bee colony optimization method for esophageal cancer stage classification using SVM classifier

BACKGROUND

Esophageal cancer (EC) is aggressive cancer with a high fatality rate and a rapid rise of the incidence globally. However, early diagnosis of EC remains a challenging task for clinicians.

OBJECTIVE

To help address and overcome this challenge, this study aims to develop and test a new computer-aided diagnosis (CAD) network that combines several machine learning models and optimization methods to detect EC and classify cancer stages.

METHODS

The study develops a new deep learning network for the classification of the various stages of EC and the premalignant stage, Barrett's Esophagus from endoscopic images. The proposed model uses a multi-convolution neural network (CNN) model combined with Xception, Mobilenetv2, GoogLeNet, and Darknet53 for feature extraction. The extracted features are blended and are then applied on to wrapper based Artificial Bee Colony (ABC) optimization technique to grade the most accurate and relevant attributes. A multi-class support vector machine (SVM) classifies the selected feature set into the various stages. A study dataset involving 523 Barrett's Esophagus images, 217 ESCC images and 288 EAC images is used to train the proposed network and test its classification performance.

RESULTS

The proposed network combining Xception, mobilenetv2, GoogLeNet, and Darknet53 outperforms all the existing methods with an overall classification accuracy of 97.76% using a 3-fold cross-validation method.

CONCLUSION

This study demonstrates that a new deep learning network that combines a multi-CNN model with ABC and a multi-SVM is more efficient than those with individual pre-trained networks for the EC analysis and stage classification.

Combination of serum CST1 and HE4 for early diagnosis of endometrial cancer

Purpose

Optimal serological biomarkers have been absent for the early diagnosis of endometrial cancer, to date. In this study, we aimed to define the diagnostic performances of individual and combined detection of serum cysteine protease inhibitor 1 (CST1) with traditional tumor markers, including glycated antigen 125 (CA125) and human epididymis protein 4 (HE4), in patients with early-stage endometrial cancer (EC).

Methods

The performances of individual and combined detection of serum CST1, HE4, and CA125 were evaluated by enzyme-linked immunosorbent assay (ELISA) and chemiluminescent immunoassay, respectively. A training data set of 67 patients with early EC, 67 patients with endometrial benign lesion (EBL), and 67 healthy controls (HC) was used to develop a predictive model for early EC diagnosis, which was validated by an independent validation data set.

Results

In the training data set, serum CST1 and HE4 levels in the early EC group were significantly higher than in EBL/HC groups (P < 0.05), while there was no significant difference of serum CA125 level between the early EC and EBL/HC groups (P > 0.05). Serum CST1 and HE4 exhibited areas under the curve (AUC) of 0.715 with 31.3% sensitivity at 90.3% specificity, and 0.706 with 23.9% sensitivity at 95.5% specificity, respectively. Combined detection of serum CST1 and HE4 exhibited an AUC of 0.788 with 49.3% sensitivity at 92.5% specificity. The combination of serum CST1 and HE4 showed promise in diagnosis.

Conclusion

CST1 is a prospective serological biomarker for early EC diagnosis, and the combination of CST1 and HE4 contributes to the further improvement in the diagnosis of patients with early-stage EC.

MiR-942-5p inhibits tumor migration and invasion through targeting CST1 in esophageal squamous cell carcinoma

INTRODUCTION

Cysteine Protease Inhibitor 1 (CST1), a cystatin superfamily protein with the effect on the inhibition of cysteine protease activity, is reported to be involved in the development of many malignancies. MiR-942-5p has been demonstrated its regulatory effects on some malignancies. However, the roles of CST1 and miR-942-5p on esophageal squamous cell carcinoma (ESCC) are still unknown up to now.

METHODS

The expression of CST1 in ESCC tissues was analyzed by TCGA database, immunohistochemistry, and RT-qPCR, respectively. Matrigel-uncoated or-coated transwell assay was used to determine the effect of CST1 on migration and invasion of ESCC cells. Regulatory effect of miR-942-5p on CST1 was detected by dual luciferase assay.

RESULTS

CST1 was ectopically highly expressed in ESCC tissues, and had the effect on promoting the migration and invasion of ESCC cells by upregulating phosphorylated levels of key effectors including MEK1/2, ERK1/2, and CREB in MEK/ERK/CREB pathway. Dual-luciferase assay results showed that miR-942-5p had a regulatory effect on targeting CST1.

CONCLUSIONS

CST1 plays a carcinogenic role on ESCC, and miR-942-5p can regulate the migration and invasion of ESCC cells by targeting CST1 to downregulate MEK/ERK/CREB signaling pathway, suggesting that miR-942-5p/CST1 axis might be a promising target for diagnosis and treatment of ESCC.

MicroRNA-375 inhibits laryngeal squamous cell carcinoma progression via targeting CST1

OBJECTIVE

This study aims to explore the effect and mechanism of miR-375 in Laryngeal Squamous Cell Carcinoma (LSCC) cell progression.

METHODS

LSCC cells (LSC-1 and TU177) were transfected with miR-375-mimic, miR-375-inhibitor or miR-375-mimic+oe-CST1. The expression of miR-375, CST1, MMP-2, and MMP-9 was measured. The effect of miR-375-mimic, miR-375-inhibitor or miR-375-mimic+oe-CST1 on cell biological functions, including cell proliferation, migration, invasion, and apoptosis, was also assessed. The potential relationship between CST1 and miR-375 was predicted by Jefferson software and validated by dual luciferase reporter gene assay.

RESULTS

Downregulated miR-375 expression was found in LSCC cells. Overexpression of miR-375 inhibited the viability and migration and promoted apoptosis of LSCC cells. Jefferson database and dual luciferase reporter gene assay confirmed that miR-375 directly targeted CST1. Overexpression of CST1 could reverse the anti-cancer effect of miR-375 overexpression in LSCC cells.

CONCLUSION

Collected evidence showed that miR-375/CST1 axis was implicated in LSCC progression.

LEVEL OF EVIDENCE

Level 3.

Urinary protein biomarker panel predicts esophageal squamous carcinoma from control cases and other tumors

PURPOSE

Discovery of noninvasive urinary biomarkers for the early diagnosis of esophageal squamous carcinoma (ESCC).

METHODS

We conducted proteomic analyses of 499 human urine samples obtained from healthy individuals (n = 321) and ESCC (n = 83), bladder cancer (n = 17), breast cancer (n = 12), colorectal cancer (n = 16), lung cancer (n = 33) and thyroid cancer (n = 17) patients from multiple medical centers. Those samples were divided into a discovery set (n = 247) and an independent validation set (n = 157).

RESULTS

Among urinary proteins identified in the comprehensive quantitative proteomics analysis, we selected a panel of three urinary biomarkers (ANXA1, S100A8, TMEM256), and established a logistic regression model in the discovery set that can correctly classify the majority of ESCC cases in the validation sets with the area under the curve (AUC) values of 0.825. This urinary biomarker panel not only discriminates ESCC patients from healthy individuals but also differentiates ESCC from other common tumors. Notably, the panel distinguishes stage I ESCC patients from healthy individuals with AUC values of 0.886. On the analysis of stage-specific biomarkers, another combination panel of protein (ANXA1, S100A8, SOD3, TMEM256) demonstrated a good AUC value of 0.792 for stage I ESCC.

CONCLUSIONS

Urinary biomarker panel represents a promising auxiliary diagnostic tool for ESCC, including early-stage ESCC.

Cystatin SN promotes epithelial-mesenchymal transition and serves as a prognostic biomarker in lung adenocarcinoma

Background

Cystatins are a class of proteins that can inhibit cysteine protease and are widely distributed in human bodily fluids and secretions. Cystatin SN (CST1), a member of the CST superfamily, is abnormally expressed in a variety of tumors. However, its effect on the occurrence and development of lung adenocarcinoma (LUAD) remains unclear.

Methods

We obtained transcriptome analysis data of CST1 from The Cancer Genome Atlas (TCGA) and GSE31210 databases. The association of CST1 expression with prognosis, gene mutations and tumor immune microenvironment was analyzed using public databases. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) were performed to investigate the potential mechanisms of CST1.

Results

In this study, we found that CST1 was highly expressed in lung adenocarcinoma and was associated with prognosis and tumor immune microenvironment. Genetic mutations of CST1 were shown to be related to disease-free survival (DFS) by using the c-BioPortal tool. Potential proteins binding to CST1 were identified by constructing a protein-protein interaction (PPI) network. Gene set enrichment analysis (GSEA) of CST1 revealed that CST1 was notably enriched in epithelial-mesenchymal transition (EMT). Cell experiments confirmed that overexpression of CST1 promoted lung adenocarcinoma cells migration and invasion, while knockdown of CST1 significantly inhibited lung adenocarcinoma cells migration and invasion.

Conclusions

Our comprehensive bioinformatics analyses revealed that CST1 may be a novel prognostic biomarker in LUAD. Experiments confirmed that CST1 promotes epithelial-mesenchymal transition in LUAD cells. These findings will help to better understand the distinct role of CST1 in LUAD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09685-z.