Detection of ANO1 mRNA in PBMCs is a promising method for GISTs diagnosis

Intelligent identification system of gastric stromal tumors based on blood biopsy indicators

BACKGROUND

The most prevalent mesenchymal-derived gastrointestinal cancers are gastric stromal tumors (GSTs), which have the highest incidence (60-70%) of all gastrointestinal stromal tumors (GISTs). However, simple and effective diagnostic and screening methods for GST remain a great challenge at home and abroad. This study aimed to build a GST early warning system based on a combination of machine learning algorithms and routine blood, biochemical and tumour marker indicators.

METHODS

In total, 697 complete samples were collected from four hospitals in Gansu Province, including 42 blood indicators from 318 pretreatment GST patients, 180 samples of gastric polyps and 199 healthy individuals. In this study, three algorithms, gradient boosting machine (GBM), random forest (RF), and logistic regression (LR), were chosen to build GST prediction models for comparison. The performance and stability of the models were evaluated using two different validation techniques: 5-fold cross-validation and external validation. The DeLong test assesses significant differences in AUC values by comparing different ROC curves, the variance and covariance of the AUC value.

RESULTS

The AUC values of both the GBM and RF models were higher than those of the LR model, and this difference was statistically significant (P < 0.05). The GBM model was considered to be the optimal model, as a larger area was enclosed by the ROC curve, and the axes indicated robust model classification performance according to the accepted model discriminant. Finally, the integration of 8 top-ranked blood indices was proven to be able to distinguish GST from gastric polyps and healthy people with sensitivity, specificity and area under the curve of 0.941, 0.807 and 0.951 for the cross-validation set, respectively.

CONCLUSION

The GBM demonstrated powerful classification performance and was able to rapidly distinguish GST patients from gastric polyps and healthy individuals. This identification system not only provides an innovative strategy for the diagnosis of GST but also enables the exploration of hidden associations between blood parameters and GST for subsequent studies on the prevention and disease surveillance management of GST. The GST discrimination system is available online for free testing of doctors and high-risk groups at https://jzlyc.gsyy.cn/bear/mobile/index.html .

Role of ANO1 in tumors and tumor immunity

Dysregulation of gene amplification, cell-signaling-pathway transduction, epigenetic and transcriptional regulation, and protein interactions drives tumor-cell proliferation and invasion, while ion channels also play an important role in the generation and development of tumor cells. Overexpression of Ca²⁺-activated Cl- channel anoctamin 1 (ANO1) is shown in numerous cancer types and correlates with poor prognosis. However, the mechanisms involved in ANO1-mediated malignant cellular transformation and the role of ANO1 in tumor immunity remain unknown. In this review, we discuss recent studies to determine the role of ANO1 in tumorigenesis and provide novel insights into the role of ANO1 in the context of tumor immunity. Furthermore, we analyze the roles and potential mechanisms of ANO1 in different types of cancers, and provide novel notions for the role of ANO1 in the tumor microenvironment and for potential use of ANO1 in clinical applications. Our review shows that ANO1 is involved in tumor immunity and microenvironment, and may, therefore, be an effective biomarker and therapeutic drug target.

The Ca2+-activated chloride channel ANO1/TMEM16A: An emerging therapeutic target for epithelium-originated diseases?

Anoctamin 1 (ANO1) or TMEM16A gene encodes a member of Ca²⁺ activated Cl^– channels (CaCCs) that are critical for physiological functions, such as epithelial secretion, smooth muscle contraction and sensory signal transduction. The attraction and interest in ANO1/TMEM16A arise from a decade long investigations that abnormal expression or dysfunction of ANO1 is involved in many pathological phenotypes and diseases, including asthma, neuropathic pain, hypertension and cancer. However, the lack of specific modulators of ANO1 has impeded the efforts to validate ANO1 as a therapeutic target. This review focuses on the recent progress made in understanding of the pathophysiological functions of CaCC ANO1 and the current modulators used as pharmacological tools, hopefully illustrating a broad spectrum of ANO1 channelopathy and a path forward for this target validation.

Prognostic significance of ANO1 expression in cancers

BACKGROUND

Anoctamin-1 (ANO1) plays a pivotal role in cancer progression. A meta-analysis was conducted to assess the potential prognostic role of ANO1 in cancers.

METHODS

A total of 1760 patients from 7 eligible studies were included into the analysis. Pooled hazard ratios or odds ratios were extracted and calculated with a random-effects model, and analyses of heterogeneity bias were conducted.

RESULTS

Our results showed that over expression of ANO1 was significantly correlated with poor overall survival in all cancers (HR = 1.52; 95% CI: 1.19-1.92; P = .0006). Subgroup analysis indicated that there was a significant association between over expression of ANO1 and poor prognosis breast cancer (HR = 3.24; 95% CI: 1.74-6.04), head and neck squamous cell carcinoma (HR = 1.14; 95% CI: 1.00-1.30), esophageal squamous cell carcinoma (HR = 1.93; 95% CI: 1.07-3.50), gastric cancer (HR = 1.62; 95% CI: 1.12-2.34) and colorectal cancer (HR = 1.38; 95% CI: 1.03-1.85). In addition, over expression of ANO1 was not associated with TNM stage, histological grade, lymph node metastasis, tumor size, age and gender. However, ANO1 was significantly associated with human epidermal growth factor receptor 2, but not associated with progesterone receptor or estrogen receptor in breast cancer.

CONCLUSIONS

Our results indicate that ANO1 can be a predictive factor for prognosis of cancer.

Expression and serum levels of the neural cell adhesion molecule L1-like protein (CHL1) in gastrointestinal stroma tumors (GIST) and its prognostic power

INTRODUCTION

Diagnosis of gastrointestinal stroma tumors (GIST) is based on the histological evaluation of tissue specimens. Reliable systemic biomarkers are lacking. We investigated the local expression of the neural cell adhesion molecule L1-like protein (CHL1) in GIST and determined whether soluble CHL1 proteoforms could serve as systemic biomarkers.

MATERIAL AND METHODS

Expression of CHL1 was analyzed in primary tumor specimens and metastases. 58 GIST specimens were immunohistochemically stained for CHL1 on a tissue microarray (TMA). Systemic CHL1 levels were measured in sera derived from 102 GIST patients and 91 healthy controls by ELISA. Results were statistically correlated with clinicopathological parameters.

RESULTS

CHL1 expression was detected in GIST specimens. Reduced tissue expression was significantly associated with advanced UICC stages (p = 0.036) and unfavorable tumor localization (p = 0.001). CHL1 serum levels are significantly elevated in GIST patients (p < 0.010). Elevated CHL1 levels were significantly associated with larger tumors (p = 0.023), advanced UICC stage (p = 0.021), and an increased Fletcher score (p = 0.041). Moreover, patients with a higher CHL1 serum levels displayed a significantly shortened recurrence free survival independent of other clinicopathological variables.

CONCLUSION

Local CHL1 expression and serum CHL1 levels show a reverse prognostic behavior, highlighting the relevance of proteolytic shedding of the molecule. The results of the study indicate a potential role of serum CHL1 as a diagnostic and prognostic marker in GIST.