Plakophilin-2 Promotes Lung Adenocarcinoma Development via Enhancing Focal Adhesion and Epithelial-Mesenchymal Transition

PKP2 induced by YAP/TEAD4 promotes malignant progression of gastric cancer

Gastric cancer (GC) exhibits significant heterogeneity and its prognosis remains dismal. Therefore, it is essential to investigate new approaches for diagnosing and treating GC. Desmosome proteins are crucial for the advancement and growth of cancer. Plakophilin-2 (PKP2), a member of the desmosome protein family, frequently exhibits aberrant expression and is strongly associated with many tumor types' progression. In this study, we found upregulation of PKP2 in GC. Further correlation analysis showed a notable association between increased PKP2 expression and both tumor stage and poor prognosis in individuals diagnosed with gastric adenocarcinoma. In addition, our research revealed that the Yes-associated protein1 (YAP1)/TEAD4 complex could stimulate the transcriptional expression of PKP2 in GC. Elevated PKP2 levels facilitate activation of the AKT/mammalian target of rapamycin signaling pathway, thereby promoting the malignant progression of GC. By constructing a mouse model, we ultimately validated the molecular mechanism and function of PKP2 in GC. Taken together, these discoveries suggest that PKP2, as a direct gene target of YAP/TEAD4 regulation, has the potential to be used as an indication of GC progression and prognosis. PKP2 is expected to be a promising therapeutic target for GC.

TM6SF1 suppresses the progression of lung adenocarcinoma and M2 macrophage polarization by inactivating the PI3K/AKT/mtor pathway

Transmembrane 6 superfamily 1 (TM6SF1) is lowly expressed in lung adenocarcinoma (LUAD), but the function and mechanisms of TM6SF1 remain unclear. Thus, we attempt to explore the function of TM6SF1 and its underlying mechanisms in LUAD. qRT-PCR was used for detecting TM6SF1 mRNA expression. Immunohistochemistry staining was used for detecting the expression of MMP-2, TM6SF1, Ki67, MMP-9, and CD163 proteins. E-cadherin, p-PI3K, Vimentin, AKT, N-cadherin, PI3K, p-AKT, mTOR, p-mTOR, and marker proteins of M2 macrophages were evaluated using Western blot. CD206 protein expression was examined via immunofluorescence. The IL-10 concentration was measured via enzyme-linked immunosorbent assay (ELISA). Using CCK-8, colony formation and transwell assays, cell proliferation, migration, and invasion were assessed. A549 cells were injected into the mice's flank for establishing a mouse tumor model and into the tail vein for establishing the lung metastasis model. HE staining was performed to detect pathological changes in lung tissues. Decreased TM6SF1 expression was found in LUAD tissues and cells. TM6SF1 overexpression inhibited cell viability, proliferation, invasion, migration, EMT, and polarization of M2 macrophages in LUAD cells, along with tumor growth and metastasis in xenograft mice. Bioinformatics analysis demonstrated that TM6SF1 was correlated with the tumor microenvironment. TM6SF1 overexpression reduced expression levels of p-mTOR, p-PI3K, p-AKT, mTOR, and AKT. TM6SF1-caused inhibition of proliferation, migration, invasion and EMT, as M2 macrophage polarization was reversed by the PI3K activator in LUAD cells. TM6SF1 inactivated the PI3K/AKT/mTOR pathway to suppress LUAD malignancy and polarization of M2 macrophages, providing insight for developing new LUAD treatments.

Downregulated expression of plakophilin-2 gene in patients with colon adenocarcinoma predicts an unfavorable prognosis and immune infiltrate

BACKGROUND

Plakophilin 2 gene (PKP2) has been revealed to be differentially expressed in various cancer types and is correlated with prognosis. However, the role of PKP2 in colon adenocarcinoma remains indistinct.

METHODS

Differences in transcriptional expression of PKP2 between colon adenocarcinoma tissues and normal adjacent tissues were acquired from the publicly available dataset-the Cancer Genome Atlas. A receiver operating curve (ROC) was constructed to differentiate colon adenocarcinoma tissues from adjacent normal tissues. The Kaplan-Meier plot method was performed to evaluate the effect of PKP2 on survival. The correlation between mRNA expression of PKP2 and immune infiltrating was determined by the Tumor Immune Estimation Resource and Tumor-Immune System Interaction databases.

RESULTS

The expression of PKP2 in colon adenocarcinoma tissues was significantly downregulated compared with corresponding adjacent normal tissues. Decreased PKP2 mRNA expression was associated with lymph node metastases and advanced pathological stage. The ROC curve analysis indicated that with a cutoff value of 6.034, the sensitivity and specificity for PKP2 differentiating the colon adenocarcinoma tissues from the adjacent normal tissues were 90.2 and 66.5% respectively. Kaplan-Meier plot survival analysis revealed that colon adenocarcinoma patients with low-PKP2 had a worse prognosis than those with high-PKP2 (68.2 vs. 101.4 months, p = 0.028). Correlation analysis showed that mRNA expression of PKP2 was correlative with immune infiltrates.

CONCLUSIONS

Downregulated PKP2 is significantly correlated with unfavorable immune infiltrating and survival in colon adenocarcinoma. This research indicates that PKP2 can be selected as a novel biomarker of potential immunotherapy targets and unfavorable prognosis in colon adenocarcinoma.

Impaired Plakophilin-2 in obesity breaks cell cycle dynamics to breed adipocyte senescence

Plakophilin-2 (PKP2) is a key component of desmosomes, which, when defective, is known to promote the fibro-fatty infiltration of heart muscle. Less attention has been given to its role in adipose tissue. We report here that levels of PKP2 steadily increase during fat cell differentiation, and are compromised if adipocytes are exposed to a pro-inflammatory milieu. Accordingly, expression of PKP2 in subcutaneous adipose tissue diminishes in patients with obesity, and normalizes upon mild-to-intense weight loss. We further show defective PKP2 in adipocytes to break cell cycle dynamics and yield premature senescence, a key rheostat for stress-induced adipose tissue dysfunction. Conversely, restoring PKP2 in inflamed adipocytes rewires E2F signaling towards the re-activation of cell cycle and decreased senescence. Our findings connect the expression of PKP2 in fat cells to the physiopathology of obesity, as well as uncover a previously unknown defect in cell cycle and adipocyte senescence due to impaired PKP2.

Novel human lymph node-derived matrix supports the adhesion of metastatic oral carcinoma cells

BACKGROUND

3D culture is increasingly used in cancer research, as it allows the growth of cells in an environment that mimics in vivo conditions. Metastases are the primary cause of morbidity and mortality in cancer patients, and solid tumour metastases are mostly located in lymph nodes. Currently, there are no techniques that model the pre-metastatic lymph node microenvironment in vitro. In this study, we prepared a novel extracellular matrix, Lymphogel, which is derived from lymph nodes, mimicking the tumour microenvironment (TME) of metastatic carcinoma cells. We tested the suitability of the new matrix in various functional experiments and compared the results with those obtained using existing matrices.

METHODS

We used both commercial and patient-derived primary and metastatic oral tongue squamous cell carcinoma (OTSCC) cell lines. We characterized the functional differences of these cells using three different matrices (human uterine leiomyoma-derived Myogel, human pre-metastatic neck lymph node-derived Lymphogel (h-LG), porcine normal neck lymph node-derived Lymphogel (p-LG) in proliferation, adhesion, migration and invasion assays. We also performed proteomic analyses to compare the different matrices in relation to their functional properties.

RESULTS

OTSCC cells exhibited different adhesion and invasion patterns depending on the matrix. Metastatic cell lines showed improved ability to adhere to h-LG, but the effects of the matrices on cell invasion fluctuated non-significantly between the cell lines. Proteomic analyses showed that the protein composition between matrices was highly variable; Myogel contained 618, p-LG 1823 and h-LG 1520 different proteins. The comparison of all three matrices revealed only 120 common proteins. Analysis of cellular pathways and processes associated with proteomes of each matrix revealed similarities of Myogel with h-LG but less with p-LG. Similarly, p-LG contained the least adhesion-related proteins compared with Myogel and h-LG. The highest number of unique adhesion-related proteins was present in h-LG.

CONCLUSIONS

We demonstrated that human pre-metastatic neck lymph node-derived matrix is suitable for studying metastatic OTSCC cells. As a whole-protein extract, h-LG provides new opportunities for in vitro carcinoma cell culture experiments.

Identification of novel gene signature for lung adenocarcinoma by machine learning to predict immunotherapy and prognosis

Background

Lung adenocarcinoma (LUAD) as a frequent type of lung cancer has a 5-year overall survival rate of lower than 20% among patients with advanced lung cancer. This study aims to construct a risk model to guide immunotherapy in LUAD patients effectively.

Materials and methods

LUAD Bulk RNA-seq data for the construction of a model, single-cell RNA sequencing (scRNA-seq) data (GSE203360) for cell cluster analysis, and microarray data (GSE31210) for validation were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. We used the Seurat R package to filter and process scRNA-seq data. Sample clustering was performed in the ConsensusClusterPlus R package. Differentially expressed genes (DEGs) between two groups were mined by the Limma R package. MCP-counter, CIBERSORT, ssGSEA, and ESTIMATE were employed to evaluate immune characteristics. Stepwise multivariate analysis, Univariate Cox analysis, and Lasso regression analysis were conducted to identify key prognostic genes and were used to construct the risk model. Key prognostic gene expressions were explored by RT-qPCR and Western blot assay.

Results

A total of 27 immune cell marker genes associated with prognosis were identified for subtyping LUAD samples into clusters C3, C2, and C1. C1 had the longest overall survival and highest immune infiltration among them, followed by C2 and C3. Oncogenic pathways such as VEGF, EFGR, and MAPK were more activated in C3 compared to the other two clusters. Based on the DEGs among clusters, we confirmed seven key prognostic genes including CPA3, S100P, PTTG1, LOXL2, MELTF, PKP2, and TMPRSS11E. Two risk groups defined by the seven-gene risk model presented distinct responses to immunotherapy and chemotherapy, immune infiltration, and prognosis. The mRNA and protein level of CPA3 was decreased, while the remaining six gene levels were increased in clinical tumor tissues.

Conclusion

Immune cell markers are effective in clustering LUAD samples into different subtypes, and they play important roles in regulating the immune microenvironment and cancer development. In addition, the seven-gene risk model may serve as a guide for assisting in personalized treatment in LUAD patients.

Endoplasmic reticulum stress-related gene model predicts prognosis and guides therapies in lung adenocarcinoma

BACKGROUND

The prognosis and survival of lung adenocarcinoma (LUAD) patients are still not promising despite recent breakthroughs in treatment. Endoplasmic reticulum stress (ERS) is a self-protective mechanism resulting from an imbalance in quality control of unfolded proteins when cells are stressed, which plays an active role in lung cancer development, but the relationship between ERS and the pathological characteristics and clinical prognosis of LUAD patients remains unclear.

METHODS

LASSO and Cox regression were applied based on sequencing information to construct the model, which was validated to be robust. The risk scores of the patients were calculated using the formula provided by the model, and the patients were divided into high and low-risk groups according to the median cut-off of risk scores. Cox regression analysis identifies independent prognostic factors for these patients, and enrichment analysis of prognosis-related genes was also performed. The relationship between risk scores and tumor mutation burden (TMB), cancer stem cell index, and drug sensitivity was explored.

RESULTS

We constructed a 13-gene prognostic model for LUAD patients. Patients in the high-risk group had worse overall survival, lower immune score and ESTIMATE score, higher TMB, higher cancer stem cell index, and higher sensitivity to conventional chemotherapeutic agents. In addition, we constructed a nomogram that predicts 5-year survival in LUAD patients, which helps clinicians to foresee the prognosis from a new perspective.

CONCLUSIONS

Our results highlight the association of ERS with LUAD and the potential use of ERS in guiding treatment.

Identification and validation of novel lung adenocarcinoma subtypes and construction of prognostic models: based on cuprotosis-related genes

Cuprotosis is a novel and unique form of cell death that is of great value in a variety of cancers. However, the prognostic role of cuprotosis-related genes (CRGs) in lung cancer remains undetermined. We compared the expression profile of CRGs in lung adenocarcinoma (LUAD) patients, revealing the genetic alterations and inter-gene correlations of CRGs. Based on 13 CRGs, LUAD patients could be well differentiated into two molecular subgroups, and the differentially expressed genes (DEGs) in these molecular subtypes were identified. Furthermore, 10 cuprotosis pattern-related DEGs with a significant prognostic value were obtained for constructing a prognostic model. Through validation in an external validation set, the prognostic model based on the CRGs-risk score showed the robust and effective predictive ability and served as an independent prognostic indicator for LUAD patients. Therefore, combining the CRGs-risk score with multiple factors such as clinicopathological characteristics, a quantitative nomogram was developed to predict the survival and prognosis of LUAD patients, improving the clinical application value of the CRGs-risk score. In the low CRGs-risk score group, the related immune cell infiltration was increased and the immune function was activated in LUAD patients. This study may add to the knowledge of CRGs in LUAD, partly contribute to evaluating the prognosis of LUAD patients, and provide direction for the development of targeted therapy and immunotherapy.

Pyroptosis-based risk score predicts prognosis and drug sensitivity in lung adenocarcinoma

Pyroptosis is a recently identified form of programmed cell death; however, its role in lung adenocarcinoma (LUAD) remains unclear. Therefore, we set out to explore the prognostic potential of pyroptosis-related genes in LUAD. The pyroptosis-related risk score (PRRS) was developed by least absolute shrinkage and selection operator Cox regression and multivariate Cox regression. We found that PRRS was an independent prognostic factor for LUAD. LUAD patients in the high-PRRS group showed a significantly shorter overall survival (OS) and enriched in cell proliferation-related pathways. Then pathway enrichment analyses, mutation profile, tumor microenvironment, and drug sensitivity analysis were further studied in PRRS stratified LUAD patients. Tumor purity (TP) analyses revealed that L-PRRS LUAD patients had a lower TP, and patients in L-TP + L-PRRS subgroup had the most prolonged OS. Mutation analyses suggested that the L-PRRS LUAD patients had a lower tumor mutation burden (TMB), and patients in H-TMB + L-PRRS subgroup had the most prolonged OS. Drug sensitivity analyses showed that PRRS was significantly negatively correlated with the sensitivity of cisplatin, besarotene, etc., while it was significantly positively correlated with the sensitivity of kin001-135. Eventually, a nomogram was constructed based on PRRS and clinical characters of LUAD. Overall, the pyroptosis-related signature is helpful for prognostic prediction and in guiding treatment for LUAD patients.

Identifying a lactic acid metabolism-related gene signature contributes to predicting prognosis, immunotherapy efficacy, and tumor microenvironment of lung adenocarcinoma

Lactic acid, once considered as an endpoint or a waste metabolite of glycolysis, has emerged as a major regulator of cancer development, maintenance, and progression. However, studies about lactic acid metabolism-related genes (LRGs) in lung adenocarcinoma (LUAD) remain unclear. Two distinct molecular subtypes were identified on basis of 24 LRGs and found the significant enrichment of subtype A in metabolism-related pathways and had better overall survival (OS). Subsequently, a prognostic signature based on 5 OS-related LRGs was generated using Lasso Cox hazards regression analysis in TCGA dataset and was validated in two external cohorts. Then, a highly accurate nomogram was cosntructed to improve the clinical application of the LRG_score. By further analyzing the LRG_score, higher immune score and lower stromal score were found in the low LRG_score group, which presented a better prognosis. Patients with low LRG_score also exhibited lower somatic mutation rate, tumor mutation burden (TMB), and cancer stem cell (CSC) index. Three more independent cohorts (GSE126044: anti-PD-1, GSE135222: anti-PD-1, and IMvigor210: anti-PD-L1) were analyzed, and the results showed that patients in the low LRG_score category were more responsive to anti-PD-1/PD-L1 medication and had longer survival times. It was also determined that gefitinib, etoposide, erlotinib, and gemcitabine were more sensitive to the low LRG_score group. Finally, we validated the stability and reliability of LRG_score in cell lines, clinical tissue samples and HPA databases. Overall, the LRG_score may improve prognostic information and provide directions for current research on drug treatment strategies for LUAD patients.

Epigenetic Alterations of DNA Methylation and miRNA Contribution to Lung Adenocarcinoma

This study focused on the epigenetic alterations of DNA methylation and miRNAs for lung adenocarcinoma (LUAD) diagnosis and treatment using bioinformatics analyses. DNA methylation data and mRNA and miRNA expression microarray data were obtained from The Cancer Genome Atlas (TCGA) database. The differentially methylated genes (DMGs), differentially expressed genes (DEGs), and differentially expressed miRNAs were analyzed by using the limma package. The DAVID database performed GO and KEGG pathway enrichment analyses. Using STRING and Cytoscape, we constructed the protein-protein interaction (PPI) network and achieved visualization. The online analysis tool CMap was used to identify potential small-molecule drugs for LUAD. In LUAD, 607 high miRNA-targeting downregulated genes and 925 low miRNA-targeting upregulated genes, as well as 284 hypermethylated low-expression genes and 315 hypomethylated high-expression genes, were obtained. They were mainly enriched in terms of pathways in cancer, neuroactive ligand-receptor interaction, cAMP signaling pathway, and cytosolic DNA-sensing pathway. In addition, 40 upregulated and 84 downregulated genes were regulated by both aberrant alternations of DNA methylation and miRNAs. Five small-molecule drugs were identified as a potential treatment for LUAD, and five hub genes (SLC2A1, PAX6, LEP, KLF4, and FGF10) were found in PPI, and two of them (SLC2A1 and KLF4) may be related to the prognosis of LUAD. In summary, our study identified a series of differentially expressed genes associated with epigenetic alterations of DNA methylation and miRNA in LUAD. Five small-molecule drugs and five hub genes may be promising drugs and targets for LUAD treatment.

Development of a 5-Gene Signature to Evaluate Lung Adenocarcinoma Prognosis Based on the Features of Cancer Stem Cells

Cancer stem cells (CSCs) can induce recurrence and chemotherapy resistance of lung adenocarcinoma (LUAD). Reliable markers identified based on CSC characteristic of LUAD may improve patients' chemotherapy response and prognosis. OCLR was used to calculate mRNA expression-based stemness index (mRNAsi) of LUAD patients' data in TCGA. Association analysis of mRNAsi was performed with clinical features, somatic mutation, and tumor immunity. A prognostic prediction model was established with LASSO Cox regression. Kaplan-Meier Plotter (KM-plotter) and time-dependent ROC were applied to assess signature performance. For LUAD, univariate and multivariate Cox analysis was performed to identify independent prognostic factors. LUAD tissues showed a noticeably higher mRNAsi in than nontumor tissues, and it showed significant differences in T, N, M, AJCC stages, and smoking history. The most frequently mutated gene was TP53, with a higher mRNAsi relating to more frequent mutation of TP53. The mRNAsi was significantly negatively correlated with immune score, stromal score, and ESTIMATE score in LUAD. The blue module was associated with mRNAsi. The 5-gene signature was confirmed as an independent indicator of LUAD prognosis that could promote personalized treatment of LUAD and accurately predict overall survival (OS) of LUAD patients.

miR-126-5p enhances radiosensitivity of lung adenocarcinoma cells by inhibiting EZH2 via the KLF2/BIRC axis

Radiotherapy is a common method for the treatment of lung adenocarcinoma, but it often fails due to the relative non‐susceptibility of lung adenocarcinoma cells to radiation. We aimed to discuss the related mechanisms by which miR‐126‐5p might mediate radiosensitivity of lung adenocarcinoma cells. The binding affinity between miR‐126‐5p and EZH2 and between KLF2 and BIRC5 was identified using multiple assays. A549 and H1650 cells treated with X‐ray were transfected with miR‐126‐5p mimic/inhibitor, oe‐EZH2, or si‐KLF2 to detect cell biological functions and radiosensitivity. Finally, lung adenocarcinoma nude mouse models were established. miR‐126‐5p and KLF2 were poorly expressed, while EZH2 and BIRC5 were upregulated in lung adenocarcinoma tissues and cells. miR‐126‐5p targeted EZH2 to promote the KLF2 expression so as to inhibit BIRC5 activation. Both in vitro and in vivo experiments verified that elevated miR‐126‐5p inhibited cell migration and promoted apoptosis to enhance the sensitivity of lung adenocarcinoma cells to radiotherapy via the EZH2/KLF2/BIRC5 axis. Collectively, miR‐126‐5p downregulated EZH2 to facilitate the sensitivity of lung adenocarcinoma cells to radiotherapy via KLF2/BIRC5.

Genomics and Prognosis Analysis of N6-Methyladenosine Regulators in Lung Adenocarcinoma

Objective: N⁶-methyladenosine (m⁶A) modification is involved in modulating various biological processes in human cancers. But the implication of m⁶A modification in lung adenocarcinoma (LUAD) is still unclear. Hence, this study conducted a comprehensive analysis of the expression and clinical implication of m⁶A regulators in LUAD.

Methods: Consensus clustering analysis of 502 LUAD samples in the TCGA dataset was presented based on the expression profiles of 20 m⁶A regulators using ConsensusClusterPlus package. Overall survival (OS), activation of signaling pathways and tumor immunity (immune/stromal score, tumor purity, expression of HLA and immune checkpoints, and immune cell infiltration) were compared between m⁶A modification patterns. The m⁶A-related genes between patterns were identified and prognostic m⁶A-related genes were imported into LASSO-cox regression analysis. The m⁶A risk score was developed and its prognostic implication was evaluated and externally verified in the GSE30219 and GSE72094 dataset. Furthermore, a nomogram that contained independent prognostic indicators was established, followed by external verification.

Results: Two m⁶A modification patterns were clustered across LUAD based on the expression similarity of the m⁶A regulators via consensus clustering analysis, with distinct OS, activation of signaling pathways and tumor immunity. Totally, 213 m⁶A-related genes that were identified by comparing two patterns were significantly related to LUAD prognosis. By LASSO method, we constructed the m⁶A risk score that was a reliable and independent prognostic factor for LUAD. Patients with low m⁶A risk score displayed a prominent survival advantage. After incorporating independent clinical features, we developed the prognostic nomogram that exhibited high predictive accuracy and the best clinical net benefit for OS.

Conclusion: Collectively, our study may provide a clinically useful tool for precise prognostic management and optimization of immunotherapeutic strategies for LUAD patients.

Long non-coding RNA HCG11 enhances osteosarcoma phenotypes by sponging miR-1245b-5p that directly inhibits plakophilin 2

Long non-coding RNA (lncRNA) HCG11 can regulate various cancers through the ceRNA network. However, its role in osteosarcoma (OS) remains unknown. The HOS and Saos-2 cell lines were used for in vitro analyses. HCG11 and plakophilin 2 (PKP2) silencers, a miR-1245b-5p mimic, and a miR-1245b-5p inhibitor were utilized for the regulation analysis of lncRNA HCG11, miR-1245b-5p, and PKP2. Cell Counting Kit-8, wound healing, and transwell assays were used for cell proliferation, migration, and invasion analyses, and caspase-3 activity assay was used to measure cell apoptosis. The expression levels of lncRNA HCG11, miR-1245b-5p, and PKP2 were evaluated by quantitative real-time PCR and Western blotting. The distribution of lncRNA HCG11 was assessed using the RNA-FISH assay. The sponging and targeting roles of HCG11 and PKP2 on miR-1245b-5p were confirmed by dual-luciferase reporter analysis. An RNA immunoprecipitation assay was used to assess the binding between lncRNA HCG11 and miRNA-1245b-5p. We found that the lncRNA HCG11 was significantly upregulated in OS. LncRNA HCG11 silencing inhibits OS progression by repressing cell proliferation, migration, and invasion, and promoting cell apoptosis. RNA-FISH analysis indicated that lncRNA HCG11 was located in the cytoplasm. Mechanistic experiments showed that lncRNA HCG11 sponges miR-1245b-5p and negatively regulates miR-1245b-5p expression. Upregulated lncRNA HCG11 promotes proliferation, migration, and invasion, and inhibits apoptosis by inhibiting miR-1245b-5p in OS cells. PKP2 was verified as a target gene of miR-1245b-5p. Upregulated PKP2 promotes proliferation, migration, and invasion, and inhibits apoptosis by inhibiting miR-1245b-5p in OS. In conclusion, the HCG11/miR-1245b-5p/PKP2 axis promotes OS expression by promoting cell proliferation, migration, and invasion, and inhibiting apoptosis.

Desmosomes as Signaling Hubs in the Regulation of Cell Behavior

Desmosomes are intercellular junctions, which preserve tissue integrity during homeostatic and stress conditions. These functions rely on their unique structural properties, which enable them to respond to context-dependent signals and transmit them to change cell behavior. Desmosome composition and size vary depending on tissue specific expression and differentiation state. Their constituent proteins are highly regulated by posttranslational modifications that control their function in the desmosome itself and in addition regulate a multitude of desmosome-independent functions. This review will summarize our current knowledge how signaling pathways that control epithelial shape, polarity and function regulate desmosomes and how desmosomal proteins transduce these signals to modulate cell behavior.

Identification of CDK2-Related Immune Forecast Model and ceRNA in Lung Adenocarcinoma, a Pan-Cancer Analysis

Background

Tumor microenvironment (TME) plays important roles in different cancers. Our study aimed to identify molecules with significant prognostic values and construct a relevant Nomogram, immune model, competing endogenous RNA (ceRNA) in lung adenocarcinoma (LUAD).

Methods

“GEO2R,” “limma” R packages were used to identify all differentially expressed mRNAs from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Genes with P-value <0.01, LogFC>2 or <-2 were included for further analyses. The function analysis of 250 overlapping mRNAs was shown by DAVID and Metascape software. By UALCAN, Oncomine and R packages, we explored the expression levels, survival analyses of CDK2 in 33 cancers. “Survival,” “survminer,” “rms” R packages were used to construct a Nomogram model of age, gender, stage, T, M, N. Univariate and multivariate Cox regression were used to establish prognosis-related immune forecast model in LUAD. CeRNA network was constructed by various online databases. The Genomics of Drug Sensitivity in Cancer (GDSC) database was used to explore correlations between CDK2 expression and IC50 of anti-tumor drugs.

Results

A total of 250 differentially expressed genes (DEGs) were identified to participate in many cancer-related pathways, such as activation of immune response, cell adhesion, migration, P13K-AKT signaling pathway. The target molecule CDK2 had prognostic value for the survival of patients in LUAD (P = 5.8e-15). Through Oncomine, TIMER, UALCAN, PrognoScan databases, the expression level of CDK2 in LUAD was higher than normal tissues. Pan-cancer analysis revealed that the expression, stage and survival of CDK2 in 33 cancers, which were statistically significant. Through TISIDB database, we selected 13 immunodepressants, 21 immunostimulants associated with CDK2 and explored 48 genes related to these 34 immunomodulators in cBioProtal database (P < 0.05). Gene Set Enrichment Analysis (GSEA) and Metascape indicated that 49 mRNAs were involved in PUJANA ATM PCC NETWORK (ES = 0.557, P = 0, FDR = 0), SIGNAL TRANSDUCTION (ES = –0.459, P = 0, FDR = 0), immune system process, cell proliferation. Forest map and Nomogram model showed the prognosis of patients with LUAD (Log-Rank = 1.399e-08, Concordance Index = 0.7). Cox regression showed that four mRNAs (SIT1, SNAI3, ASB2, and CDK2) were used to construct the forecast model to predict the prognosis of patients (P < 0.05). LUAD patients were divided into two different risk groups (low and high) had a statistical significance (P = 6.223e-04). By “survival ROC” R package, the total risk score of this prognostic model was AUC = 0.729 (SIT1 = 0.484, SNAI3 = 0.485, ASB2 = 0.267, CDK2 = 0.579). CytoHubba selected ceRNA mechanism medicated by potential biomarkers, 6 lncRNAs-7miRNAs-CDK2. The expression of CDK2 was associated with IC50 of 89 antitumor drugs, and we showed the top 20 drugs with P < 0.05.

Conclusion

In conclusion, our study identified CDK2 related immune forecast model, Nomogram model, forest map, ceRNA network, IC50 of anti-tumor drugs, to predict the prognosis and guide targeted therapy for LUAD patients.