SRPX2 knockdown inhibits cell proliferation and metastasis and promotes chemosensitivity in esophageal squamous cell carcinoma

CPA4 as a biomarker promotes the proliferation, migration and metastasis of clear cell renal cell carcinoma cells

Clear cell renal cell carcinoma (ccRCC) is a commonly occurring and highly aggressive urological malignancy characterized by a significant mortality rate. Current therapeutic options for advanced ccRCC are limited, necessitating the discovery of novel biomarkers and therapeutic targets. Carboxypeptidase A4 (CPA4) is a zinc-containing metallocarboxypeptidase with implications in various cancer types, but its role in ccRCC remains unexplored. The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were utilized in order to investigate the differential expression patterns of CPA4. The expression of CPA4 in ccRCC patients was further verified using immunohistochemical (IHC) examination of 24 clinical specimens. A network of protein-protein interactions (PPI) was established, incorporating CPA4 and its genes that were expressed differentially. Functional enrichment analyses were conducted to anticipate the contribution of CPA4 in the development of ccRCC. To validate our earlier study, we conducted real-time PCR and cell functional tests on ccRCC cell lines. Our findings revealed that CPA4 is overexpressed in ccRCC, and the higher the expression of CPA4, the worse the clinical outcomes such as TNM stage, pathological stage, histological grade, etc. Moreover, patients with high CPA4 expression had worse overall survival, disease-specific survival and progress-free interval than patients with low expression. The PPI network analysis highlighted potential interactions contributing to ccRCC progression. Functional enrichment analysis indicated the involvement of CPA4 in the regulation of key pathways associated with ccRCC development. Additionally, immune infiltration analysis suggested a potential link between CPA4 expression and immune response in the tumour microenvironment. Finally, cell functional studies in ccRCC cell lines shed light on the molecular mechanisms underlying the role of CPA4 in promoting ccRCC formation. Overall, our study unveils CPA4 as a promising biomarker with prognostic potential in ccRCC. The identified interactions and pathways provide valuable insights into its implications in ccRCC development and offer a foundation for future research on targeted therapies. Further investigation of CPA4's involvement in immune responses may contribute to the development of immunotherapeutic strategies for ccRCC treatment.

Potential markers of cancer stem-like cells in ESCC: a review of the current knowledge

In patients with esophageal squamous cell carcinoma (ESCC), the incidence and mortality rate of ESCC in our country are also higher than those in the rest of the world. Despite advances in the treatment department method, patient survival rates have not obviously improved, which often leads to treatment obstruction and cancer repeat. ESCC has special cells called cancer stem-like cells (CSLCs) with self-renewal and differentiation ability, which reflect the development process and prognosis of cancer. In this review, we evaluated CSLCs, which are identified from the expression of cell surface markers in ESCC. By inciting EMTs to participate in tumor migration and invasion, stem cells promote tumor redifferentiation. Some factors can inhibit the migration and invasion of ESCC via the EMT-related pathway. We here summarize the research progress on the surface markers of CSLCs, EMT pathway, and the microenvironment in the process of tumor growth. Thus, these data may be more valuable for clinical applications.

TAPI-1 Exhibits Anti-tumor Efficacy in Human Esophageal Squamous Cell Carcinoma Cells via Suppression of NF-κB Signaling Pathway

BACKGROUND

TNF-α processing inhibitor-1 (TAPI-1) is a known metalloproteinase inhibitor with potential anti-inflammatory effects. However, its anti-cancer effects on esophageal squamous cell carcinoma (ESCC) have not been uncovered.

AIM

In the present study, the effects of TAPI-1 on ESCC cell viability, migration, invasion, and cisplatin resistance and the underlying molecular mechanisms were investigated in TE-1 and Eca109 cells.

METHODS

To this end, TE-1 and Eca109 cells were exposed to TAPI-1 for indicated time intervals. Cell viability was assessed using cell counting kit-8 assay and apoptosis was evaluated using flow cytometry assay. Migration and invasion were assessed using Transwell assays. Gene expressions were analyzed using quantitative reverse transcription polymerase chain reaction. The activation of NF-κB signaling pathway was elucidated via Western blot and chromatin immunoprecipitation assay.

RESULTS

We observed that higher doses (10, 20 μM) of TAPI-1 inhibited ESCC cell viability, while a lower dose (5 μM) of TAPI-1 inhibited ESCC cell migration and invasion and enhanced the chemosensitivity of ESCC cells to cisplatin. Moreover, TAPI-1 suppressed the activation of NF-κB signaling and the target genes expression in the stage of transcription initiation. Furthermore, blocking NF-κB signaling in advance could abolish all the effects of TAPI-1 on ESCC cells.

CONCLUSION

Overall, these results indicated that TAPI-1 impairs ESCC cell viability, migration, and invasion and facilitates cisplatin-induced apoptosis via suppression of NF-κB signaling pathway. TAPI-1 may serve as a potential adjuvant agent with cisplatin for ESCC therapy.

SRPX2 promotes cancer cell proliferation and migration of papillary thyroid cancer

Thyroid cancer is the endocrine tumor with the highest incidence at present. It originates from the thyroid follicular epithelium or follicular paraepithelial cells. There is an increasing incidence of thyroid cancer all over the world. We found that SRPX2 expression level was higher in papillary thyroid tumors than in normal thyroid tissues, and SRPX2 expression was closely related to tumor grade and clinical prognosis. Previous reports showed that SRPX2 could function by activating PI3K/AKT signaling pathway. In addition, in vitro experiments showed that SRPX2 promoted the proliferation and migration of papillary thyroid cancer (PTC). In conclusion, SRPX2 could promote the malignant development of PTC. This may be a potential treatment target for PTC.

Lymphangiogenesis in gastric cancer: function and mechanism

Increased lymphangiogenesis and lymph node (LN) metastasis are thought to be important steps in cancer metastasis, and are associated with patient's poor prognosis. There is increasing evidence that the lymphatic system may play a crucial role in regulating tumor immune response and limiting tumor metastasis, since tumor lymphangiogenesis is more prominent in tumor metastasis and diffusion. Lymphangiogenesis takes place in embryonic development, wound healing, and a variety of pathological conditions, including tumors. Tumor cells and tumor microenvironment cells generate growth factors (such as lymphangiogenesis factor VEGF-C/D), which can promote lymphangiogenesis, thereby inducing the metastasis and diffusion of tumor cells. Nevertheless, the current research on lymphangiogenesis in gastric cancer is relatively scattered and lacks a comprehensive understanding. Therefore, in this review, we aim to provide a detailed perspective on molecules and signal transduction pathways that regulate gastric cancer lymphogenesis, which may provide new insights for the diagnosis and treatment of cancer.

SRPX2 attenuated oxygen–glucose deprivation and reperfusion-induced injury in cardiomyocytes via alleviating endoplasmic reticulum stress-induced apoptosis through targeting PI3K/Akt/mTOR axis

Myocardial infraction (MI) is the leading cause of high morbidity and mortality worldwide. It was still urgently needed to find new and effective drugs for MI treatment by the use of myocardial ischemia/reperfusion (I/R) model. Sushi repeats contain the protein X-Linked 2 (SRPX2), which regulates a variety of important cell functions. However, its possible role in myocardial I/R and the progression of MI is still unclear. In this study, we investigated the role of SRPX2 in myocardial I/R. SRPX2 showed low expression in IR rats and H9C2 cells induced by oxygen–glucose deprivation/reperfusion (OGD/R). SRPX2 could increase OGD/R-induced H9C2 cell survival. In addition, SRPX2 suppressed the apoptosis of OGD/R-induced H9C2 cells. Furthermore, we found that SRPX2 could inhibit ER stress induced by OGD/R in H9C2 cells. Mechanically, we found that SRPX2 suppressed the PI3K/Akt/mTOR pathway, thus attenuating OGD/R -induced injury in H9C2 cells. Therefore, SRPX2 has the potential to serve as a target for MI treatment.

SRPX2 Promotes Tumor Proliferation and Migration via the FAK Pathway in Papillary Thyroid Carcinoma

Thyroid cancer is the most common form of endocrine cancer around the world, and among which papillary thyroid carcinoma (PTC) is the most ubiquitous pathological sub-kind. Sushi repeat-containing protein X-linked 2 (SRPX2) was reported to be an independent prognostic factor and significantly overexpressed in advanced PTC patients. However, the biological functions of SRPX2 remain ambiguous in PTC. Here, we explored SRPX2 expression profiles and functions in PTC, finding that SRPX2 expression was remarkably upregulated in PTC tissues and cell lines. Further colony formation, CCK-8, as well as transwell assay, suggested that SRPX2 silencing remarkably dampened PTC growth and migration. Mouse xenograft models were established to find that SRPX2 silence remarkably suppressed PTC proliferation and migration in vivo. Following mechanism studies revealed that SRPX2 realized its functions in the PTC process partially through activating the Focal adhesion kinase (FAK) phosphorylation. In conclusion, this study investigated the functions and mechanisms of the SRPX2/FAK pathway in PTC progression. SRPX2 could act as a prospective biologic signature and therapeutic target molecule for PTC.

Sushi-Repeat-Containing Protein X-Linked 2: A Potential Therapeutic Target for Inflammation and Cancer Therapy

Accumulating evidence has showed that sushi-repeat-containing protein X-linked 2 (SRPX2) is an abnormal expression in a variety of cancers and involved in cancer carcinogenesis, chemosensitivity, and prognosis, which mainly promote cancer cell metastasis, invasion, and migration by regulating the uPAR/integrins/FAK signaling pathway, epithelial-mesenchymal transition (EMT), angiogenesis, and glycosylation. Inflammation has been regarded as a key role in regulating cancer initiation, progression, EMT, and therapeutics. Furthermore, SRPX2 exhibited excellent antifibrosis effect via the TGFβR1/SMAD3/SRPX2/AP1/SMAD7 signaling pathway. Therefore, this review provides compelling evidence that SRPX2 might be a therapeutic target for inflammation and cancer-related inflammation for future cancer therapeutics.

A Deep Learning Radiomics Analysis for Survival Prediction in Esophageal Cancer

The purpose of this study was to explore the deep learning radiomics (DLR) nomogram to predict the overall 3-year survival after chemoradiotherapy in patients with esophageal cancer. The 154 patients' data were used in this study, which was randomly split into training (116) and validation (38) data. Deep learning and handcrafted features were obtained via the preprocessing diagnostic computed tomography images. The selected features were used to construct radiomics signatures through the least absolute shrinkage and selection operator (LASSO) regression, maximizing relevance while minimizing redundancy. The DLR signature, handcrafted features' radiomics (HCR) signature, and clinical factors were incorporated to develop a DLR nomogram. The DLR nomogram was evaluated in terms of discrimination and calibration with comparison to the HCR signature-based radiomics model. The experimental results showed the outperforming discrimination ability of the proposed DLR over the HCR model in terms of Harrel's concordance index, 0.76 and 0.784, for training and validation sets, respectively. Also, the proposed DLR nomogram calibrates and classifies better than the HCR model in terms of AUC, 0.984 (vs. 0.797) and 0.942 (vs. 0.665) for training and validation sets, respectively. Furthermore, the nomogram-predicted Kaplan–Meier survival (KMS) curves differed significantly from the nonsurvival groups in the log-rank test (p value <0.05). The proposed DLR model based on conventional CT images showed the outperforming performance over the HCR signature model in noninvasively individualized prediction of the 3-year survival rate in esophageal cancer patients. The proposed model can potentially provide prognostic information that guides and helps the clinical decisions between observation and treatment.

Molecular mechanisms associated with chemoresistance in esophageal cancer

Esophageal cancer (EC) is one of the most incident and lethal tumors worldwide. Although surgical resection is an important approach in EC treatment, late diagnosis, metastasis and recurrence after surgery have led to the management of adjuvant and neoadjuvant therapies over the past few decades. In this scenario, 5-fluorouracil (5-FU) and cisplatin (CISP), and more recently paclitaxel (PTX) and carboplatin (CBP), have been traditionally used in EC treatment. However, chemoresistance to these agents along EC therapeutic management represents the main obstacle to successfully treat this malignancy. In this sense, despite the fact that most of chemotherapy drugs were discovered several decades ago, in many cases, including EC, they still represent the most affordable and widely employed treatment approach for these tumors. Therefore, this review summarizes the main mechanisms through which the response to the most widely chemotherapeutic agents used in EC treatment is impaired, such as drug metabolism, apoptosis resistance, cancer stem cells (CSCs), cell cycle, autophagy, energetic metabolism deregulation, tumor microenvironment and epigenetic modifications.

Tumor Nonimmune-Microenvironment-Related Gene Expression Signature Predicts Brain Metastasis in Lung Adenocarcinoma Patients after Surgery: A Machine Learning Approach Using Gene Expression Profiling

Simple Summary

It is important to be able to predict brain metastasis in lung adenocarcinoma patients; however, research in this area is still lacking. Much of the previous work on tumor microenvironments in lung adenocarcinoma with brain metastasis concerns the tumor immune microenvironment. The importance of the tumor nonimmune microenvironment (extracellular matrix (ECM), epithelial–mesenchymal transition (EMT) feature, and angiogenesis) has been overlooked with regard to brain metastasis. We evaluated tumor nonimmune-microenvironment-related gene expression signatures that could predict brain metastasis after the surgical resection of lung adenocarcinoma using a machine learning approach. We identified a tumor nonimmune-microenvironment-related 17-gene expression signature, and this signature showed high brain metastasis predictive power in four machine learning classifiers. The immunohistochemical expression of the top three genes of the 17-gene expression signature yielded similar results to NanoString tests. Our tumor nonimmune-microenvironment-related gene expression signatures are important biological markers that can predict brain metastasis and provide patient-specific treatment options.

Abstract

Using a machine learning approach with a gene expression profile, we discovered a tumor nonimmune-microenvironment-related gene expression signature, including extracellular matrix (ECM) remodeling, epithelial–mesenchymal transition (EMT), and angiogenesis, that could predict brain metastasis (BM) after the surgical resection of 64 lung adenocarcinomas (LUAD). Gene expression profiling identified a tumor nonimmune-microenvironment-related 17-gene expression signature that significantly correlated with BM. Of the 17 genes, 11 were ECM-remodeling-related genes. The 17-gene expression signature showed high BM predictive power in four machine learning classifiers (areas under the receiver operating characteristic curve = 0.845 for naïve Bayes, 0.849 for support vector machine, 0.858 for random forest, and 0.839 for neural network). Subgroup analysis revealed that the BM predictive power of the 17-gene signature was higher in the early-stage LUAD than in the late-stage LUAD. Pathway enrichment analysis showed that the upregulated differentially expressed genes were mainly enriched in the ECM–receptor interaction pathway. The immunohistochemical expression of the top three genes of the 17-gene expression signature yielded similar results to NanoString tests. The tumor nonimmune-microenvironment-related gene expression signatures found in this study are important biological markers that can predict BM and provide patient-specific treatment options.

Identifying the tumor-progressive gene expression profile in high-risk papillary thyroid cancer

PURPOSE

Papillary thyroid cancer (PTC) is generally associated with a favorable prognosis. However, some patients have fatal disease, with locally infiltrating tumors or progressive distant metastases; yet few studies have investigated the characteristics of the tumor-progressive gene expression profile in advanced PTC. We conducted this study to clarify the gene expression status in advanced PTC and identify candidate molecules for prognostic biomarkers.

METHODS

We analyzed 740 tumor-progressive gene expression levels from formalin-fixed paraffin-embedded blocks of samples from six patients with low-risk PTC and six patients with high-risk PTC, using the nCounter PanCancer Progression panel. Then, we investigated the association between the expression levels of focused genes and pathological factors in PTC patients in The Cancer Genome Atlas (TCGA) database.

RESULTS

The expression levels of 14 genes in the high-risk PTC specimens were more than two-fold those in the low-risk PTC specimens. In the TCGA database, expression levels of four genes (CCL11, COL6A3, INHBA, and SRPX2) were significantly higher in patients with advanced PTC. Among the patients with advanced PTC, those with high SRPX2 expression levels had poor disease-free survival. Univariate and multivariate analyses revealed that high SRPX2 expression was an independent prognostic factor.

CONCLUSION

Based on the findings of this study, CCL11, COL6A3, INHBA, and SRPX2 are potential biomarkers that indicate advanced PTC. SRPX2, in particular, is considered a prognostic biomarker.

FOXA2-Interacting FOXP2 Prevents Epithelial-Mesenchymal Transition of Breast Cancer Cells by Stimulating E-Cadherin and PHF2 Transcription

FOXP2, a member of forkhead box transcription factor family, was first identified as a language-related gene that played an important role in language learning and facial movement. In addition, FOXP2 was also suggested regulating the progression of cancer cells. In previous studies, we found that FOXA2 inhibited epithelial-mesenchymal transition (EMT) in breast cancer cells. In this study, by identifying FOXA2-interacting proteins from FOXA2-pull-down cell lysates with Mass Spectrometry Analysis, we found that FOXP2 interacted with FOXA2. After confirming the interaction between FOXP2 and FOXA2 through Co-IP and immunofluorescence assays, we showed a correlated expression of FOXP2 and FOXA2 existing in clinical breast cancer samples. The overexpression of FOXP2 attenuated the mesenchymal phenotype whereas the stable knockdown of FOXP2 promoted EMT in breast cancer cells. Even though FOXP2 was believed to act as a transcriptional repressor in most cases, we found that FOXP2 could activate the expression of tumor suppressor PHF2. Meanwhile, we also found that FOXP2 could endogenously bind to the promoter of E-cadherin and activate its transcription. This transcriptional activity of FOXP2 relied on its interaction with FOXA2. Furthermore, the stable knockdown of FOXP2 enhanced the metastatic capacity of breast cancer cells in vivo. Together, the results suggested that FOXP2 could inhibit EMT by activating the transcription of certain genes, such as E-cadherin and PHF2, in concert with FOXA2 in breast cancer cells.

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

BACKGROUND

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSIONS

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

SRPX2 boosts pancreatic cancer chemoresistance by activating PI3K/AKT axis

Background and aim

This investigation was aimed at disclosing whether SRPX2 affected pancreatic cancer (PC) chemoresistance by regulating PI3K/Akt/mTOR signaling.

Methods

Totally 243 PC patients were recruited, and they were incorporated into partial remission (PR) group, stable disease (SD) group and progressive disease (PD) group in accordance with their chemotherapeutic response. PC cell lines (i.e. AsPC1, Capan2, VFPAC-1, HPAC, PANC-1, BxPC-3 and SW1990) and human pancreatic ductal epithelial cell lines (hTERT-HPNE) were also collected.

Results

PC patients of SD + PD group were associated with higher post-chemotherapeutic SRPX2 level than PR group, and their post-chemotherapeutic SRPX2 level was above the pretherapeutic SRPX2 level (P < 0.05). PR population showed lower SRPX2 level after chemotherapy than before chemotherapy (P < 0.05). Besides high serum SRPX2 level and SRPX2 level change before and after chemotherapy were independent predictors of poor PC prognosis. Additionally, si-SRPX2 enhanced chemosensitivity of PC cell lines, and expressions of p-PI3K, p-AKT and p-mTOR were suppressed by si-SRPX2 (P < 0.05). IGF-1 treatment could changeover the impact of si-SRPX2 on proliferation, migration, invasion and chemoresistance of PC cells (P < 0.05).

Conclusion

The SRPX2-PI3K/AKT/mTOR axis could play a role in modifying progression and chemoresistance of PC cells, which might help to improve PC prognosis.

Sushi Repeat Containing Protein X-linked 2 Is a Downstream Signal of LEM Domain Containing 1 and Acts as a Tumor-Promoting Factor in Oral Squamous Cell Carcinoma

Because oral squamous cell carcinomas (OSCCs) have a high potential for locoregional invasion and nodal metastasis, early detection and treatment are essential. A LAP2, emerin, MAN1 (LEM) domain containing 1 (LEMD1) is associated with local progression, clinical stage, nodal metastasis, poor prognosis, angiogenesis, and lymphangiogenesis in OSCC. Although LEMD is a cancer-testis antigen, the cancer-related signals related to LEMD1 remain unknown. In this study, we used a microarray analysis of OSCC cells to identify sushi repeat containing protein X-linked 2 (SRPX2) as a LEMD1-related downstream signal. LEMD1 expression was correlated with lymph node metastasis of OSCC according to the immunohistochemistry analysis. Furthermore, patients expressing SRPX2 had a significantly worse prognosis than those without SRPX2 expression. The concentration of SRPX2 in OSCC was positively correlated with the concentrations of LEMD1, urokinase plasminogen activator receptor (uPAR), and hepatocyte growth factor (HGF). In OSCC cells, SRPX2 secretion levels were elevated by interactions with uPAR and HGF. We also found that SRPX2 promotes endothelial cell proliferation and adhesion between endothelial cells and OSCC cells. These results suggest that SRPX2 might be a useful tumor marker for OSCC.

Emetine Synergizes with Cisplatin to Enhance Anti-Cancer Efficacy against Lung Cancer Cells

Cisplatin is still the primary therapeutic choice for advanced lung cancers without driver mutations. The occurrence of cisplatin resistance is a major clinical problem in lung cancer treatment. The natural extracted agent emetine reportedly has anticancer effects. This study aimed to explore the possible role of emetine in cisplatin resistance. We used cell viability, Western blot, and Wnt reporter assays to show that emetine suppresses proliferation, β-catenin expression, and Wnt/β-catenin signaling in non-small cell lung cancer (NSCLC). The synergism of emetine and cisplatin was assessed by constructing isobolograms and calculating combination index (CI) values using the Chou-Talalay method. Emetine effectively synergized with cisplatin to suppress the proliferation of cancer cells. Furthermore, nuclear β-catenin and cancer stem cell-related markers were upregulated in the cisplatin-resistant subpopulation of CL1-0 cells. Emetine enhanced the anticancer efficacy of cisplatin and synergized with cisplatin in the cisplatin-resistant subpopulation of CL1-0 cells. Taken together, these data suggest that emetine could suppress the growth of NSCLC cells through the Wnt/β-catenin pathway and contribute to a synergistic effect in combination with cisplatin.

Mortalin is a distinct bio-marker and prognostic factor in serous ovarian carcinoma

This study focused on mortalin expression and its relevance to the prognosis in serous ovarian carcinoma, mortalin modulated cell malignant proliferation and EMT progression via Wnt/β-Catenin signaling pathway. In this study, data obtained from Oncomine database, Cancer Cell Line Encyclopedia (CCLE) analysis and Immunohistochemical (IHC) staining was used to assess the expression of mortalin in serous ovarian carcinoma. The prognostic value of mortalin was analyzed using Meier plotter database and Kaplan-Meier. MTT (3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide) assay, immunofluorescence (IF) staining, and colony formation assay were used to detect cell reproductive capacity. SK-OV-3 cell motility and epithelial-mesenchymal transition (EMT) were measured by wound-healing, migration and western-blot assays. Data from Oncomine showed that mortalin was highly expressed in serous ovarian carcinomas compared with corresponding normal controls. Similar results were found in CCLE analysis and in clinical specimens. High mortalin expression was associated with high histological grade and worse overall survival (OS) rate. The results of MTT analyses, IF staining, and colony formation assay indicated that MKT-077 (1-Ethyl-2-[[3-ethyl-5-(3-methyl-2(3H)-benzothiazolylidene)-4-oxo-2-thiazolidinylidene] methyl]-pyridinium chloride) suppressed the viability of SK-OV-3 cells. Besides, mortalin suppression restrained cell EMT progression by Wnt/β-Catenin signaling pathway. Taken together, mortalin is over-expressed in serous ovarian carcinoma. High mortalin expression could be a candidate for the prognostic indicator and a biomarker in serous ovarian carcinoma.