Systematic profiling identifies PDLIM2 as a novel prognostic predictor for oesophageal squamous cell carcinoma (ESCC)

Tumor promoting effect of PDLIM2 downregulation involves mitochondrial ROS, oncometabolite accumulations and HIF-1α activation

BACKGROUND

Cancer is characterized by dysregulated cellular metabolism. Thus, understanding the mechanisms underlying these metabolic alterations is important for developing targeted therapies. In this study, we investigated the pro-tumoral effect of PDZ and LIM domain 2 (PDLIM2) downregulation in lung cancer growth and its association with the accumulation of mitochondrial ROS, oncometabolites and the activation of hypoxia-inducible factor-1 (HIF-1) α in the process.

METHODS

Databases and human cancer tissue samples were analyzed to investigate the roles of PDLIM2 and HIF-1α in cancer growth. DNA microarray and gene ontology enrichment analyses were performed to determine the cellular functions of PDLIM2. Seahorse assay, flow cytometric analysis, and confocal microscopic analysis were employed to study mitochondrial functions. Oncometabolites were analyzed using liquid chromatography-mass spectrometry (LC-MS). A Lewis lung carcinoma (LLC) mouse model was established to assess the in vivo function of PDLIM2 and HIF-1α.

RESULTS

The expression of PDLIM2 was downregulated in lung cancer, and this downregulation correlated with poor prognosis in patients. PDLIM2 highly regulated genes associated with mitochondrial functions. Mechanistically, PDLIM2 downregulation resulted in NF-κB activation, impaired expression of tricarboxylic acid (TCA) cycle genes particularly the succinate dehydrogenase (SDH) genes, and mitochondrial dysfunction. This disturbance contributed to the accumulation of succinate and other oncometabolites, as well as the buildup of mitochondrial reactive oxygen species (mtROS), leading to the activation of hypoxia-inducible factor 1α (HIF-1α). Furthermore, the expression of HIF-1α was increased in all stages of lung cancer. The expression of PDLIM2 and HIF-1α was reversely correlated in lung cancer patients. In the animal study, the orally administered HIF-1α inhibitor, PX-478, significantly reduces PDLIM2 knockdown-promoted tumor growth.

CONCLUSION

These findings shed light on the complex action of PDLIM2 on mitochondria and HIF-1α activities in lung cancer, emphasizing the role of HIF-1α in the tumor-promoting effect of PDLIM2 downregulation. Additionally, they provide new insights into a strategy for precise targeted treatment by suggesting that HIF-1α inhibitors may serve as therapy for lung cancer patients with PDLIM2 downregulation.

Prognostic Risk Models Using Epithelial Cells Identify β-Sitosterol as a Potential Therapeutic Target Against Esophageal Squamous Cell Carcinoma

Background

Esophageal squamous cell carcinoma (ESCC) is an aggressive and fatal malignancy that leads to epithelial cancer. The association between epithelial cell heterogeneity, prognosis, and immune response in this cancer remains uncertain. This study aimed to investigate epithelial cell heterogeneity in ESCC and develop a predictive risk model using the identified cell types.

Methods

Single-cell RNA sequencing (scRNA-seq) and differential ESCC gene data were accessed from the Gene Expression Omnibus. Functional enrichment analysis, inferCNV, cell development trajectories, and intercellular communication were analyzed following epithelial cell characterization. Differentially expressed ESCC (n = 773) and epithelial cell marker genes (n = 3407) were intersected to obtain core genes, and epithelial cell-related prognostic genes were identified. LASSO regression analysis was used to construct a prognostic model. The external dataset GSE53624 was used to further validate the stability of the model. Drug sensitivity predictions, and immune cell infiltration were analyzed. Molecular docking clarified the possible therapeutic role of β-sitosterol in ESCC. Finally, wound healing assay, cell colony, and transwell assay were constructed to detect the effects of the core gene PDLIM2 on ESCC cell proliferation, invasion, and migration.

Results

Eight cell clusters were identified, and epithelial cells were categorized into tumor and paratumor groups. The tumor group possessed more chromosomal variants than the paratumor group. Epithelial cells were associated with multiple cell types and significantly correlated with the Wnt, transforming growth factor, and epidermal growth factor signaling pathways. From 231 intersected genes, five core genes were screened for use in the risk model: CTSL, LAPTM4B, MYO10, NCF2, and PDLIM2. These genes may contribute to the cancerous transformation of normal esophageal epithelial cells and thereby act as biomarkers and potential therapeutic targets in patients with ESCC. β-Sitosterol furthermore displayed excellent docking potential with these genes. Meanwhile, further experiments demonstrated that the gene PDLIM2 plays a major role in the progression of oesophageal squamous carcinoma.

Conclusion

We successfully developed a risk model for the prognosis of ESCC based on epithelial cells that addresses the response of ESCC to immunotherapy and offers novel cancer treatment options.

PDZ and LIM Domain-Encoding Genes: Their Role in Cancer Development

PDZ-LIM family proteins (PDLIMs) are a kind of scaffolding proteins that contain PDZ and LIM interaction domains. As protein-protein interacting molecules, PDZ and LIM domains function as scaffolds to bind to a variety of proteins. The PDLIMs are composed of evolutionarily conserved proteins found throughout different species. They can participate in cell signal transduction by mediating the interaction of signal molecules. They are involved in many important physiological processes, such as cell differentiation, proliferation, migration, and the maintenance of cellular structural integrity. Studies have shown that dysregulation of the PDLIMs leads to tumor formation and development. In this paper, we review and integrate the current knowledge on PDLIMs. The structure and function of the PDZ and LIM structural domains and the role of the PDLIMs in tumor development are described.

Effect of SARS-CoV-2 infection on asthma patients

Background

SARS-CoV-2 causes coronavirus disease 2019 (COVID-19), a new coronavirus pneumonia, and containing such an international pandemic catastrophe remains exceedingly difficult. Asthma is a severe chronic inflammatory airway disease that is becoming more common around the world. However, the link between asthma and COVID-19 remains unknown. Through bioinformatics analysis, this study attempted to understand the molecular pathways and discover potential medicines for treating COVID-19 and asthma.

Methods

To investigate the relationship between SARS-CoV-2 and asthma patients, a transcriptome analysis was used to discover shared pathways and molecular signatures in asthma and COVID-19. Here, two RNA-seq data (GSE147507 and GSE74986) from the Gene Expression Omnibus were used to detect differentially expressed genes (DEGs) in asthma and COVID-19 patients to find the shared pathways and the potential drug candidates.

Results

There were 66 DEGs in all that were classified as common DEGs. Using a protein-protein interaction (PPI) network created using various bioinformatics techniques, five hub genes were found. We found that asthma has some shared links with the progression of COVID-19. Additionally, protein-drug interactions with common DEGs were also identified in the datasets.

Conclusion

We investigated possible links between COVID-19 and asthma using bioinformatics databases, which might be useful in treating COVID-19 patients. More studies on populations affected by these diseases are needed to elucidate the molecular mechanism behind their association.

High Expression of PDLIM2 Predicts a Poor Prognosis in Prostate Cancer and Is Correlated with Epithelial-Mesenchymal Transition and Immune Cell Infiltration

Purpose

To elucidate the clinical and prognostic role of PDZ and LIM domain protein (PDLIM) genes and the association to epithelial-mesenchymal transition (EMT) and immune cell infiltration in patients with prostate cancer (PRAD).

Methods

The data of RNA-seq, DNA methylation, and clinical features of PRAD patients were collected from The Cancer Genome Atlas (TCGA) database to define the prognostic value of PDLIM gene expression and the association with EMT and immune cell infiltration. A tissue microarray including 134 radical prostatectomy specimens was served as validation by immunohistochemistry (IHC) staining analysis.

Results

The mRNA levels of PDLIM1/2/3/4/6/7 were significantly downregulated, while PDLIM5 was upregulated in PRAD (P < 0.05). High expression of PDLIM2 mRNA suggests poor progression free interval in PRAD patients. DNA methylation of PDLIM2 was correlated with its mRNA expression level, and that the cg22973076 methylation site in PDLIM2 was associated with shorter PFI (P < 0.05) in PRAD. Single-sample gene-set enrichment and gene functional enrichment results showed that PDLIM2 was correlated with EMT and immune processes. Spearman's test showed a significant correlation with six reported EMT signatures and several EMT signature-related genes. Tumor microenvironment analysis revealed that the PDLIM2 mRNA expression was positively correlated with the immune score, stromal score, and various tumor infiltrating immune cells. Additionally, the results showed that patients in the high-PDLIM2 mRNA expression group may be more sensitive to immune checkpoint blockade therapy. Finally, IHC analysis further implicated the protein level of PDLIM2 was upregulated in PRAD and acts as a novel potential biomarker in predicting tumor progression.

Conclusion

Our study suggests that PDLIM family genes might be significantly correlated with oncogenesis and the progression of PRAD. PDLIM2 correlated with EMT and immune cell infiltration by acting as an oncogene in PRAD, which may serve as a potential prognostic biomarker for PRAD patients.

Six Novel Biomarkers for Diagnosis and Prognosis of Esophageal squamous cell carcinoma: validated by scRNA-seq and qPCR

Esophageal squamous cell carcinoma (ESCC) is one of the most common cancers worldwide. ESCC has a generally poor prognosis and there is a lack of available biomarkers for diagnosis and prognosis. The aim of the study was to identify novel biomarkers for ESCC. We screened the overlapping differentially expressed genes (DEGs) acquired from six Gene Expression Omnibus (GEO) ESCC datasets and The Cancer Genome Atlas (TCGA) ESCC datasets. Subsequently, protein-protein interaction network analysis was performed to identify the key hub genes. Then, Kaplan Meier survival and receiver operating curve (ROC) analysis were utilized to clarify the diagnostic and prognostic role of these hub genes. The UALCAN database, single cell RNA sequencing (scRNA-seq) and real-time quantitative PCR (qPCR) were performed to confirm the expression levels of identified hub genes. Finally, immune infiltration analysis was conducted to investigate the role of these genes in the pathogenesis of ESCC. The results showed that PBK, KIF2C, NUF2, KIF20A, RAD51AP1, and DEPDC1 effectively distinguish ESCC tissues from normal samples, and all of them were significantly correlated with overall survival. The results of scRNA-seq and qPCR indicated that the expression levels of hub genes in ESCC were significantly higher than in normal cells or tissues. Further immune infiltration analysis showed that infiltration of dendritic cells was significantly negatively correlated with PBK, KIF2C, NUF2, RAD51AP1, and DEPDC1 expression levels. In conclusion, our results suggest that PBK, KIF2C, NUF2, KIF20A, RAD51AP1 and DEPDC1 are all potential biomarkers for ESCC diagnosis and prognosis may also be potential therapeutic targets for ESCC.

A model for predicting prognosis in patients with esophageal squamous cell carcinoma based on joint representation learning

Esophageal squamous cell carcinoma (ESCC) is one of the deadliest cancer types with a poor prognosis due to the lack of symptoms in the early stages and a delayed diagnosis. The present study aimed to identify the risk factors significantly associated with prognosis and to search for novel effective diagnostic modalities for patients with early-stage ESCC. mRNA and methylation data of patients with ESCC and the corresponding clinical information were downloaded from The Cancer Genome Atlas (TCGA) database, and the representation features were screened using deep learning autoencoder. The univariate Cox regression model was used to select the prognosis-related features from the representation features. K-means clustering was used to cluster the TCGA samples. Support vector machine classifier was constructed based on the top 75 features mostly associated with the risk subgroups obtained from K-means clustering. Two ArrayExpress datasets were used to verify the reliability of the obtained risk subgroups. The differentially expressed genes and methylation genes (DEGs and DMGs) between the risk subgroups were analyzed, and pathway enrichment analysis was performed. A total of 500 representation features were produced. Using K-means clustering, the TCGA samples were clustered into two risk subgroups with significantly different overall survival rates. Joint multimodal representation strategy, which showed a good model fitness (C-index=0.760), outperformed early-fusion autoencoder strategy. The joint representation learning-based classification model had good robustness. A total of 1,107 DEGs and 199 DMGs were screened out between the two risk subgroups. The DEGs were involved in 70 pathways, the majority of which were correlated with metastasis and proliferation of various cancer types, including cytokine-cytokine receptor interaction, cell adhesion molecules PPAR signaling pathway, pathways in cancer, transcriptional misregulation in cancer and ECM-receptor interaction pathways. The two survival subgroups obtained via the joint representation learning-based model had good robustness, and had prognostic significance for patients with ESCC.

PDLIM2 protects articular chondrocytes from lipopolysaccharide-induced apoptosis, degeneration and inflammatory injury through down-regulation of nuclear factor (NF)-κB signaling

Excessive inflammatory response-induced apoptosis and the degeneration of articular chondrocytes contribute to the development and progression of osteoarthritis. PDZ and LIM domain containing protein 2 (PDLIM2) has emerged as one of the pivotal regulators in orchestrating an inflammatory response through regulating the activity of transcription factor nuclear factor (NF)-κB. However, whether PDLIM2 participates in the articular chondrocyte-associated inflammatory response in osteoarthritis remains unknown. In the current study, we aimed to explore the biological function of PDLIM2 in lipopolysaccharide (LPS)-stimulated articular chondrocytes, an in vitro model of osteoarthritis. Herein, we found that PDLIM2 expression was significantly down-regulated in chondrocytes in response to LPS exposure. Functional experiments revealed that PDLIM2 overexpression increased the viability and decreased the apoptosis of chondrocytes following LPS treatment. Moreover, PDLIM2 overexpression attenuated LPS-induced degeneration of chondrocytes via the down-regulation of matrix metalloproteinase (MMP)-3 and MMP-13 and the up-regulation of COL2A1 and ACAN. In addition, the overexpression of PDLIM2 decreased LPS-induced production of interleukin (IL)-1β, IL-6 and TNF-α. In contrast, depletion of PDLIM2 exhibited the opposite effect. Mechanism research elucidated that PDLIM2 repressed the activation of NF-κB signaling associated with the down-regulation of NF-κB p65 protein expression. PDLIM2 depletion-exacerbated LPS-induced injury was significantly reversed by NF-κB inhibition. Taken together, these results demonstrate that PDLIM2 overexpression attenuates LPS-induced injury of articular chondrocytes through the inactivation of NF-κB signaling.

PDLIM2 acts as a cancer suppressor gene in non-small cell lung cancer via the down regulation of NF-κB signaling

PDZ and LIM domain containing protein 2 (PDLIM2) has been identified as a vital tumor-associated gene that is aberrantly expressed in various types of tumors. Yet, the involvement of PDLIM2 in non-small cell lung cancer (NSCLC) is currently undetermined. The design of the current study was to evaluate whether PDLIM2 plays a role in NSCLC. We found that PDLIM2 expression was commonly decreased in NSCLC tissues. Moreover, low expression of PDLIM2 was also detected in NSCLC cell lines and demethylation treatment restored PDLIM2 expression. The re-expression of PDLIM2 impeded the proliferative, colony-forming, and invasive capabilities of NCLCL cells. In contrast, depletion of PDLIM2 markedly enhanced the malignant behaviors of NSCLC cells. Notably, PDLIM2 overexpression downregulated the expression of nuclear factor (NF)-κB p65 subunit and repressed NF-κB transcription reporter activity in NSCLC cells. The overexpression of p65 significantly reversed PDLIM2-mediated antitumor effects in NSCLC cells. Additionally, the Xenograft tumor formation assay revealed that the overexpression of PDLIM2 markedly restricted the tumor growth of NSCLC in vivo. Overall, our study confirms that PDLIM2 acts as a tumor-inhibitor in NSCLC through the inactivation of NF-κB, suggesting PDLIM2 as a candidate therapeutic target for NSCLC.

Sexual Dimorphism in Cellular and Molecular Features in Human ACTH-Secreting Pituitary Adenomas

(1) Background. Cushing's disease presents gender disparities in prevalence and clinical course. Little is known, however, about sexual dimorphism at the level of the corticotrope adenoma itself. The aim of the present study was to evaluate molecular features of ACTH-secreting pituitary adenomas collected from female and male patients with Cushing's disease. (2) Methods. We analyzed 153 ACTH-secreting adenomas collected from 31 men and 122 women. Adenomas were established in culture and ACTH synthesis and secretion assessed in basal conditions as well as during incubation with CRH or dexamethasone. Concurrently, microarray analysis was performed on formalin-fixed specimens and differences in the expression profiles between specimens from male and female patients identified. (3) Results. ACTH medium concentrations in adenomas obtained from male patients were significantly lower than those observed in adenomas from female patients. This could be observed for baseline as well as modulated secretion. Analysis of corticotrope transcriptomes revealed considerable similarities with few, selected differences in functional annotations. Differentially expressed genes comprised genes with known sexual dimorphism, genes involved in tumour development and genes relevant to pituitary pathophysiology. (4) Conclusions. Our study shows for the first time that human corticotrope adenomas present sexual dimorphism and underlines the need for a gender-dependent analysis of these tumours. Differentially expressed genes may represent the basis for gender-tailored target therapy.

Systematic profiling identifies PDLIM2 as a novel prognostic predictor for oesophageal squamous cell carcinoma (ESCC)

Till now, no appropriate biomarkers for high‐risk population screening and prognosis prediction have been identified for patients with oesophageal squamous cell carcinoma (ESCC). In this study, by the combined use of data from the Gene Expression Omnibus (GEO) datasets and The Cancer Genome Atlas (TCGA)‐oesophageal carcinoma (ESCA), we aimed to screen dysregulated genes with prognostic value in ESCC and the genetic and epigenetic alterations underlying the dysregulation. About 222 genes that had at least fourfold change in ESCC compared with adjacent normal tissues were identified using the microarray data in GDS3838. Among these genes, only PDLIM2 was associated with nodal invasion and overall survival (OS) at the same time. The high PDLIM2 expression group had significantly longer OS and its expression was independently associated with better OS (HR: 0.64, 95% CI: 0.43‐0.95, P = 0.03), after adjustment for gender and pathologic stages. The expression of its exon 7/8/9/10 had the highest AUC value (0.724) and better prognostic value (HR: 0.43, 95% CI: 0.22‐0.83, P = 0.01) than total PDLIM2 expression. PDLIM2 DNA copy deletion was common in ESCC and was associated with decreased gene expression. The methylation status of two CpG sites (cg23696886 and cg20449614) in the proximal promoter region of PDLIM2 showed a moderate negative correlation with the gene expression in PDLIM2 copy neutral/amplification group. In conclusion, we infer that PDLIM2 expression might be a novel prognostic indicator for ESCC patients. Its exon 7/8/9/10 expression had the best prognostic value. Its down‐regulation might be associated with gene‐level copy deletion and promoter hypermethylation.