Down-regulation of focal adhesion signaling in response to cyclophilin A knockdown in human endometrial cancer cells, implicated by cDNA microarray analysis

Establishing and Validating an Innovative Focal Adhesion-Linked Gene Signature for Enhanced Prognostic Assessment in Endometrial Cancer

Studies have highlighted the significant role of focal adhesion signaling in cancer. Nevertheless, its specific involvement in the pathogenesis of endometrial cancer and its clinical significance remains uncertain. We analyzed TCGA-UCEC and GSE119041 datasets with corresponding clinical data to investigate focal adhesion-related gene expression and their clinical significance. A signature, "FA-riskScore," was developed using LASSO regression in the TCGA cohort and validated in the GSE dataset. The FA-riskScore was compared with four existing models in terms of their prediction performance. We employed univariate and multivariate Cox regression analyses towards FA-riskScore to assess its independent prognostic value. A prognostic evaluation nomogram based on our model and clinical indexes was established subsequently. Biological and immune differences between high- and low-risk groups were explored through functional enrichment, PPI network analysis, mutation mining, TME evaluation, and single-cell analysis. Sensitivity tests on commonly targeted drugs were performed on both groups, and Connectivity MAP identified potentially effective molecules for high-risk patients. qRT-PCR validated the expressions of FA-riskScore genes. FA-riskScore, based on FN1, RELN, PARVG, and PTEN, indicated a poorer prognosis for high-risk patients. Compared with published models, FA-riskScore achieved better and more stable performance. High-risk groups exhibited a more challenging TME and suppressive immune status. qRT-PCR showed differential expression in FN1, RELN, and PTEN. Connectivity MAP analysis suggested that BU-239, potassium-canrenoate, and tubocurarine are effective for high-risk patients. This study introduces a novel prognostic model for endometrial cancer and offers insights into focal adhesion's role in cancer pathogenesis.

CypA: A Potential Target of Tumor Radiotherapy and/or Chemotherapy

Cyclophilin A (CypA) is a ubiquitous and highly conserved protein. CypA, the intracellular target protein for the immunosuppressant cyclosporine A (CsA), plays important cellular roles through peptidyl-prolyl cis-trans isomerase (PPIase). Increasing evidence shows that CypA is up-regulated in a variety of human cancers. In addition to being involved in the occurrence and development of multiple tumors, overexpression of CypA has also been shown to be strongly associated with malignant transformation. Surgery, chemotherapy and radiotherapy are the three main treatments for cancer. Chemotherapy and radiotherapy are often used as direct or adjuvant treatments for cancer. However, various side effects and resistance to both chemotherapy and radiotherapy bring great challenges to these two forms of treatment. According to recent reports, CypA can improve the chemosensitivity and/or radiosensitivity of cancers, possibly by affecting the expression of drug-resistant related proteins, cell cycle arrest and activation of the mitogen-activated protein kinase (MAPK) signaling pathways. In this review, we focus on the role of CypA in cancer, its impact on cancer chemotherapeutic and radiotherapy sensitivity, and the mechanism of action. It is suggested that CypA may be a novel potential therapeutic target for cancer chemotherapy and/or radiotherapy.

CeModule: an integrative framework for discovering regulatory patterns from genomic data in cancer

BACKGROUND

Non-coding RNAs (ncRNAs) are emerging as key regulators and play critical roles in a wide range of tumorigenesis. Recent studies have suggested that long non-coding RNAs (lncRNAs) could interact with microRNAs (miRNAs) and indirectly regulate miRNA targets through competing interactions. Therefore, uncovering the competing endogenous RNA (ceRNA) regulatory mechanism of lncRNAs, miRNAs and mRNAs in post-transcriptional level will aid in deciphering the underlying pathogenesis of human polygenic diseases and may unveil new diagnostic and therapeutic opportunities. However, the functional roles of vast majority of cancer specific ncRNAs and their combinational regulation patterns are still insufficiently understood.

RESULTS

Here we develop an integrative framework called CeModule to discover lncRNA, miRNA and mRNA-associated regulatory modules. We fully utilize the matched expression profiles of lncRNAs, miRNAs and mRNAs and establish a model based on joint orthogonality non-negative matrix factorization for identifying modules. Meanwhile, we impose the experimentally verified miRNA-lncRNA interactions, the validated miRNA-mRNA interactions and the weighted gene-gene network into this framework to improve the module accuracy through the network-based penalties. The sparse regularizations are also used to help this model obtain modular sparse solutions. Finally, an iterative multiplicative updating algorithm is adopted to solve the optimization problem.

CONCLUSIONS

We applied CeModule to two cancer datasets including ovarian cancer (OV) and uterine corpus endometrial carcinoma (UCEC) obtained from TCGA. The modular analysis indicated that the identified modules involving lncRNAs, miRNAs and mRNAs are significantly associated and functionally enriched in cancer-related biological processes and pathways, which may provide new insights into the complex regulatory mechanism of human diseases at the system level.

Selected reaction monitoring approach for validating peptide biomarkers

We here describe a selected reaction monitoring (SRM)-based approach for the discovery and validation of peptide biomarkers for cancer. The first stage of this approach is the direct identification of candidate peptides through comparison of proteolytic peptides derived from the plasma of cancer patients or healthy individuals. Several hundred candidate peptides were identified through this method, providing challenges for choosing and validating the small number of peptides that might prove diagnostically useful. To accomplish this validation, we used 2D chromatography coupled with SRM of candidate peptides. We applied this approach, called sequential analysis of fractionated eluates by SRM (SAFE-SRM), to plasma from cancer patients and discovered two peptides encoded by the peptidyl-prolyl cis-trans isomerase A (PPIA) gene whose abundance was increased in the plasma of ovarian cancer patients. At optimal thresholds, elevated levels of at least one of these two peptides was detected in 43 (68.3%) of 63 women with ovarian cancer but in none of 50 healthy controls. In addition to providing a potential biomarker for ovarian cancer, this approach is generally applicable to the discovery of peptides characteristic of various disease states.

miR-34c plays a role of tumor suppressor in HEC‑1-B cells by targeting E2F3 protein

Endometrial carcinoma (EC) is a common malignancy of the female genital tract with a poor prognosis. It has been reported that miR-34c is significantly reduced in EC, but research concerning its function in EC is rare. In the present study, the expression of miR-34c was upregulated in the EC cell line, HEC-1-B, by transfecting the cells with hsa-miR-34c-5p mimics. Then, after determining the transfection efficiency by RT-qPCR, we analyzed the effects of miR-34c on the HEC-1-B cells. We found that overexpression of miR-34c significantly inhibited cell proliferation, colony formation, migration and invasion and induced cell cycle arrest and apoptosis. Finally, western blot analysis demonstrated that the expression of E2F3 was reduced after upregulation of the expression of miR-34c in the HEC-1-B cells, and the effects of miR-34c are likely associated with the reduction in E2F3 protein. In conclusion, our study demonstrated that miR-34c plays a role of tumor suppressor in HEC-1-B cells, and E2F3 protein may be a target of miR-34c.

Clinical significance of cyclophilin a expression in esophageal squamous cell carcinoma

OBJECTIVE

To explore the expression of cyclophilin A (CypA) in esophageal tissues and its clinical significance.

METHOD

Expression of CypA was detected in 236 esophageal cancer tissues and 236 normal tissues by using an immunohistochemical method, and the relationship between CypA expression and clinical outcomes was observed.

RESULTS

There were 166 patients with high expression of CypA (70.23%) and a higher expression in 69.3% of males and 73.3% in females. The CypA expression was irrelevant to age, tumor location, lymph node metastasis, and tumor differentiation degree. The Kaplan-Meier survival curve analysis showed that the expression of CypA was associated with the prognosis of patients with esophageal squamous cell carcinoma.

CONCLUSION

The poor prognosis of esophageal cancer patients was associated with high expression of CypA.

Construction of pancreatic cancer double-factor regulatory network based on chip data on the transcriptional level

Transcription factor (TF) and microRNA (miRNA) have been discovered playing crucial roles in cancer development. However, the effect of TFs and miRNAs in pancreatic cancer pathogenesis remains vague. We attempted to reveal the possible mechanism of pancreatic cancer based on transcription level. Using GSE16515 datasets downloaded from gene expression omnibus database, we first identified the differentially expressed genes (DEGs) in pancreatic cancer by the limma package in R. Then the DEGs were mapped into DAVID to conduct the kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis. TFs and miRNAs that DEGs significantly enriched were identified by Fisher's test, and then the pancreatic cancer double-factor regulatory network was constructed. In our study, total 1117 DEGs were identified and they significantly enriched in 4 KEGG pathways. A double-factor regulatory network was established, including 29 DEGs, 24 TFs, 25 miRNAs. In the network, LAMC2, BRIP1 and miR155 were identified which may be involved in pancreatic cancer development. In conclusion, the double-factor regulatory network was found to play an important role in pancreatic cancer progression and our results shed new light on the molecular mechanism of pancreatic cancer.