SERPINE2 Overexpression Is Associated with Poor Prognosis of Urothelial Carcinoma

Pan-cancer analysis of SERPINE family genes as biomarkers of cancer prognosis and response to therapy

Background: Serine protease inhibitor E (SERPINE) family genes participate in the tumor growth, cancer cell survival and metastasis. However, the SERPINE family members role in the prognosis and their clinical therapeutic potentials in various human cancer types have not been elaborately explored. Methods: We preliminarily analyzed expression levels and prognostic values of SERPINE family genes, and investigated the correlation between SERPINEs expression and tumor microenvironment (TME), Stemness score, clinical characteristic, immune infiltration, tumor mutational burden (TMB), immune subtype, and drug sensitivity in pan-cancer, which based on updated public databases and integrated some bioinformatics analysis methods. In addition, we conducted the enrichment analysis of SERPINEs from DAVID and KOBAS databases. Results: SERPINE1, SERPINE2, and SERPINE3 expression were upregulated in nine cancers, twelve cancers, and six cancers, respectively. The expression of SERPINE family genes was associated with the prognosis in several cancers from The Cancer Genome Atlas (TCGA). Furthermore, SERPINE family genes expression also had a significant relation to stromal and immune scores, and RNA stemness score and DNA stemness score in pan-cancer. SERPINE1 and SERPINE2 expression significantly increased in tumor advanced stage in colon adenocarcinoma (COAD). Results showed that SERPINE1 and SERPINE2 expression were negatively related with B cells and Monocytes, respectively. SERPINE2 expression had a significantly positive relation with B cells and Macrophages. In terms of TMB, SERPINE1, SERPINE2, and SERPINE3 were found to associated with TMB in seven cancers, fourteen cancers, and four cancers, respectively. Moreover, all SERPINE gene family members were significantly correlated with immune subtypes. SERPINE1 expression had a significantly positive or negative correlation with drug sensitivity. Conclusion: The study indicated the great potential of SERPINE family genes as biomarkers for prognosis and provided valuable strategies for further investigation of SERPINE family genes as potential targets in cancer.

Serpin peptidase inhibitor, clade E, member 2 is associated with malignant progression and clinical prognosis in oral squamous cell carcinoma

Background/purpose

The serpin peptidase inhibitor, clade E, member 2 (SERPINE2), is upregulated in breast cancer, prostate cancer, and urothelial carcinoma; however, limited information exists regarding its expression in oral cancer. Therefore, this study aimed to analyze the association between SERPINE2 expression and oral squamous cell carcinoma (OSCC) outcomes.

Materials and methods

SERPINE2 mRNA and protein expression in patients with head and neck squamous cell carcinoma and OSCC were investigated using online databases and tissue-array analysis. Its relationship with clinicopathological characteristics, OSCC prognosis and its biological function in OSCC cells were explored.

Results

Analysis using online databases revealed higher SERPINE2 expression in tumor tissues and its role as a prognostic factor. High SERPINE2 protein levels were significantly correlated with adverse pathological parameters, including advanced clinical stage and tumor status (P < 0.001), lymph nodes (P = 0.014), and distant metastases (P = 0.013). High SERPINE2 expression was associated with worse overall survival (P < 0.001) and was identified as an independent prognostic factor for OSCC. In vitro studies revealed that SERPINE2 knockdown significantly reduced cell proliferation, migration, and invasion in OSCC cell lines.

Conclusion

This study suggests that SERPINE2 may serve as a prognostic biomarker and potential therapeutic target for oral cancer.

Differential Proteome Profiling Analysis under Pesticide Stress by the Use of a Nano-UHPLC-MS/MS Untargeted Proteomic-Based Approach on a 3D-Developed Neurospheroid Model: Identification of Protein Interactions, Prognostic Biomarkers, and Potential Therapeutic Targets in Human IDH Mutant High-Grade Gliomas

High-grade gliomas represent the most common group of infiltrative primary brain tumors in adults associated with high invasiveness, agressivity, and resistance to therapy, which highlights the need to develop potent drugs with novel mechanisms of action. The aim of this study is to reveal changes in proteome profiles under stressful conditions to identify prognostic biomarkers and altered apoptogenic pathways involved in the anticancer action of human isocitrate dehydrogenase (IDH) mutant high-grade gliomas. Our protocol consists first of a 3D in vitro developing neurospheroid model and then treatment by a pesticide mixture at relevant concentrations. Furthermore, we adopted an untargeted proteomic-based approach with high-resolution mass spectrometry for a comparative analysis of the differentially expressed proteins between treated and nontreated spheroids. Our analysis revealed that the majority of altered proteins were key members in glioma pathogenesis, implicated in the cellular metabolism, biological regulation, binding, and catalytic and structural activity and linked to many cascading regulatory pathways. Our finding revealed that grade-IV astrocytomas promote the downstream of the mitogen-activated-protein-kinases/extracellular-signal-regulated kinase (MAPK1/ERK2) pathway involving massive calcium influx. The gonadotrophin-releasing-hormone signaling enhances MAKP activity and may serve as a negative feedback compensating regulator. Thus, our study can pave the way for effective new therapeutic and diagnostic strategies to improve the overall survival.

Homologous recombination repair gene-based risk model predicts prognosis and immune microenvironment for primary lung cancer after previous malignancies

BACKGROUND

Homologous recombination repair (HRR) plays an important role in cancer development, drug resistance, and immune escape, but the role of HRR genes in primary lung cancer (PLC) after previous malignancies is unclear.

METHODS

We used HRR-related score constrcted by HRR genes to classify patients into two groups and compared clinical progression, differential genes, and their functions between them. Then, we constructed a prognostic risk model based on HRR-related score and screened key differentially expressed genes. We evaluated the potential roles, mutational information, and immune correlations of key genes. Finally, we compared the long-term prognosis and immune correlations of different prognostic risk subgroups.

RESULTS

We found that HRR-related score was associated with T-stage, immunotherapy sensitivity, and prognosis of PLC after previous malignancies. Differential genes between HRR-related low-score and high-score groups are mainly involved in DNA replication and repair processes, such as the cell cycle. We identified three key genes, ABO, SERPINE2, and MYC, by machine learning, and MYC had the highest amplification mutation frequency. We verified that the key gene-based prognostic model can better assess the prognosis of patients. The risk score of the prognostic model was associated with immune microenvironment and efficacy of immunotherapy.

CONCLUSIONS

Overall, we identified three key genes ABO, SERPINE2, and MYC associated with HRR status in PLC after previous malignancies. The risk model based on key genes is associated with immune microenvironment and can well predict the prognosis for PLC after previous malignancies.

Predicting Survival Signature of Bladder Cancer Related to Cancer-Associated Fibroblast (CAF) Constructed by Intersecting Genes in TCGA and GEO

Bladder cancer was one of the most common carcinomas around the world. However, the mechanism of the disease still remained to be investigated. We expected to establish a prognostic survival model with 9 prognostic genes to predict overall survival (OS) in patients of bladder cancer. The gene expression data of bladder cancer were obtained from TCGA and GEO datasets. TCGA and GEO datasets were used for screening prognostic genes along with developing and validating a 9-gene prognostic survival model by method of weighted gene co-expression network analysis (WGCNA) and LASSO with Cox regression. The relative analysis of evaluate tumor burden mutation (TBM), GO, KEGG, chemotherapy drug and functional pathway were also performed based on CAF-related mRNAs. 151 Overlapping CAF-related genes were distinguished after intersecting differentially expressed genes from 945 genes in TCGA and 491 genes in GEO dataset. 9 Prognostic genes (MSRB2, AGMAT, KLF6, DDAH2, GADD45B, SERPINE2, STMN3, TEAD2, and COMP) were used for construction of prognostic model after LASSO with Cox regression. Receiver operating characteristic (ROC) curves showed a good survival prediction by this model. Functional analysis indicated chemokine, cytokine, ECM interaction, oxidative stress and apoptosis were highly appeared. Potential drugs targeted different CAF-related genes like vemurafenib, irofulven, ghiotepa, and idarubicin were found as well. We constructed a novel 9 CAF-related mRNAs prognostic model and explored the gene expression and potential functional information of related genes, which might be worthy of clinical application. In addition, potential chemotherapy drugs could provide useful insights into the potential clinical treatment of bladder cancer.

A novel signature constructed by differential genes of muscle-invasive and non-muscle-invasive bladder cancer for the prediction of prognosis in bladder cancer

Background

Bladder cancer (BCa) is a malignant tumor that usually forms cancer cells in the inner lining of the bladder. Hundreds of thousands of people worldwide have BCa diagnosed each year. The purpose of this study was to construct a prognostic model by differential expression of genes between muscular and non-muscular invasive BCa, and to investigate the prognosis of BCa patients.

Methods

The data of BCa patients was sourced from the GEO and TCGA database. Single-cell sequencing data was obtained from three patients in the GSE135337 database, and microarray data for verification was obtained from GSE32894. Univariate, Lasso and multivariate cox regression analyses were performed to construct the prognostic model. The prognostic features, immune features and drug sensitivity of the model were further evaluated. Single-cell data and microarray data were used to validate the differential expression of model genes between muscle-invasive and non-muscle-invasive BCa. The invasion and migration of BCa cells were evaluated using the transwell assay and wound-healing assay. The cell proliferation capacity was simultaneously evaluated using Colony formation experiments. The protein expression of the specific gene was detected by western blot analysis.

Results

We identified 183 differentially expressed muscle-invasive-related differential genes (MIRDGs), among which four were selected to establish a prognostic model. Based on our signature, patients in different groups displayed varying levels of immune infiltration and immunotherapy profiles. Single-cell sequencing data and microarray data confirmed that four invasion-related genes were expressed at higher levels in muscle-invasive BCa. Given the critical role of S100A9 in the progression of BCa, we performed further analysis. The results showed that protein expression of S100A9 was high in muscle-invasive BCa, and S100A9 knockdown could inhibit the proliferation, migration and invasion of BCa.

Conclusion

These findings demonstrated that the prognostic model for BCa patients was reasonably accurate and valid, and it may prove to be of considerable value for the treatment and prognosis of BCa patients in the future. S100A9 may become a better prognostic marker and potential therapeutic target to further guide clinical treatment decisions.

New Hydronephrosis in the Native Kidney Is Associated with the Development of De Novo Urinary Bladder Urothelial Carcinoma in Patients with Post-Kidney Transplantation

Increased malignancy after kidney transplantation (KT) is by far the most troublesome issue. Among these malignancies, urothelial carcinoma (UC) incidence is uniquely high in Taiwan. We want to know whether routine sonography to detect native hydronephrosis is associated with the development of de novo urinary bladder urothelial carcinoma (UBUC) in post-KT recipients. From 2003 to 2018, we retrospectively analyzed 1005 KT patients, 58 of whom were subsequently diagnosed with UBUC. The association between new native hydronephrosis and post-KT UBUC was analyzed with univariate and multivariate logistic regression analyses and a Kaplan-Meier plot. We excluded cases of people who had upper urinary tract urothelial carcinoma (UTUC) and were diagnosed prior to UBUC. There were 612 males (60.9%) and 393 females (39.1%), with a mean age of 48.2 ± 12.0 years old at KT. The mean follow-up period was 118.6 ± 70.2 months, and the diagnosis of UBUC from KT to UBUC was 7.0 ± 5.1 years. New native kidney hydronephrosis occurred more frequently in the UBUC group (56.4% versus 6.4%, p < 0.001) than the non-UBUC group. Multivariate analysis disclosed that native hydronephrosis is the only statistically significant factor for UBUC, with an odds ratio of 16.03 (95% CI, 8.66-29.68; p < 0.001). UBUC in post-KT patients with native hydronephrosis also showed a tendency toward multifocal lesions upon presentation (47.8%). Post-KT UBUC is characterized by pathologically aggressive and multiple foci lesions. Native kidney hydronephrosis may be a deciding factor of post-KT UBUC.

Transcriptome analysis of newly established carboplatin-resistant ovarian cancer cell model reveals genes shared by drug resistance and drug-induced EMT

BACKGROUND

In ovarian cancer (OC) therapy, even initially responsive patients develop drug resistance.

METHODS

Here, we present an OC cell model composed of variants with differing degrees of acquired resistance to carboplatin (CBP), cross-resistance to paclitaxel, and CBP-induced metastatic properties (migration and invasion). Transcriptome data were analysed by two approaches identifying differentially expressed genes and CBP sensitivity-correlating genes. The impact of selected genes and signalling pathways on drug resistance and metastatic potential, along with their clinical relevance, was examined by in vitro and in silico approaches.

RESULTS

TMEM200A and PRKAR1B were recognised as potentially involved in both phenomena, also having high predictive and prognostic values for OC patients. CBP-resistant MES-OV CBP8 cells were more sensitive to PI3K/Akt/mTOR pathway inhibitors Rapamycin, Wortmannin, SB216763, and transcription inhibitor Triptolide compared with parental MES-OV cells. When combined with CBP, Rapamycin decreased the sensitivity of parental cells while Triptolide sensitised drug-resistant cells to CBP. Four PI3K/Akt/mTOR inhibitors reduced migration in both cell lines.

CONCLUSIONS

A newly established research model and two distinct transcriptome analysis approaches identified novel candidate genes enrolled in CBP resistance development and/or CBP-induced EMT and implied that one-gene targeting could be a better approach than signalling pathway inhibition for influencing both phenomena.

Construction of cancer- associated fibroblasts related risk signature based on single-cell RNA-seq and bulk RNA-seq data in bladder urothelial carcinoma

Background

The ability of cancer-associated fibroblasts (CAFs) to encourage angiogenesis, tumor cell spread, and increase treatment resistance makes them pro-tumorigenic. We aimed to investigate the CAF signature in Bladder urothelial carcinoma (BLCA) and, for clinical application, to build a CAF-based risk signature to decipher the immune landscape and screen for suitable treatment BLCA samples.

Methods

CAF-related genes were discovered by superimposing CAF marker genes discovered from single-cell RNA-seq (scRNA-seq) data taken from the GEO database with CAF module genes discovered by weighted gene co-expression network analysis (WGCNA) using bulk RNA-seq data from TCGA. After identifying prognostic genes related with CAF using univariate Cox regression, Lasso regression was used to build a risk signature. With microarray data from the GEO database, prognostic characteristics were externally verified. For high and low CAF-risk categories, immune cells and immunotherapy responses were analyzed. Finally, a nomogram model based on the risk signature and prospective chemotherapeutic drugs were examined.

Results

Combining scRNA-seq and bulk-seq data analysis yielded a total of 124 CAF-related genes. LRP1, ANXA5, SERPINE2, ECM1, RBP1, GJA1, and FKBP10 were the seven BLCA prognostic genes that remained after univariate Cox regression and LASSO regression analyses. Then, based on these genes, prognostic characteristics were created and validated to predict survival in BLCA patients. Additionally, risk signature had a strong correlation with known CAF scores, stromal scores, and certain immune cells. The CAF-risk signature was identified as an independent prognostic factor for BLCA using multifactorial analysis, and its usefulness in predicting immunotherapy response was confirmed. Based on risk classification, we projected six highly sensitive anticancer medicines for the high-risk group.

Conclusion

The prognosis of BLCA may be accurately predicted using CAF-based risk signature. With a thorough understanding of the BLCA CAF-signature, it might be able to explain the BLCA patients' response to immunotherapy and identify a potential target for BLCA treatment.

LHX2 Enhances the Malignant Phenotype of Esophageal Squamous Cell Carcinoma by Upregulating the Expression of SERPINE2

LHX2 dysregulations have been found to present in cancers, but the function of LHX2 in esophageal squamous cell carcinoma (ESCC) remains unknown. Here, we report that LHX2 was upregulated in ESCC tissues in comparison to the LHX2 levels in adjacent normal tissues. Loss- and gain-of-function experiments demonstrated that the knockdown of LHX2 markedly inhibited ESCC cells’ proliferation, migration, invasion, tumor growth and metastasis, whereas the overexpression of LHX2 had the opposite effects. A mechanistic investigation revealed that LHX2 bound to the promoter of SERPINE2 gene and transcriptionally regulated the expression of SERPINE2. Collectively, LHX2 facilitates ESCC tumor progression, and it could be a potential therapeutic target for ESCC.