Identification of Potential Diagnostic and Prognostic Values of P4HA1 Expression in Lung Cancer, Breast Cancer, and Head and Neck Cancer

P4HA1 expression and function in esophageal squamous cell carcinoma

This study aimed to explore the effect of P4HA1 (prolyl 4-hydroxylase subunit α1) and its ratio on the prognosis of esophageal squamous cell carcinoma. The expression data of P4HA1 in esophageal cancer in The Cancer Genome Atlas and Genotype-Tissue Expression were collected using the public database gene expression profiling interactive analysis. The expression levels of P4HA1 were examined by immunohistochemistry. The relationship between P4HA1 expression and clinicopathological parameters was analyzed the χ2 test. Survival analysis was performed to investigate the effect of P4HA1 and its ratio on prognosis. Compared with normal esophageal mucosal epithelium, there was higher P4HA1 gene mRNA in esophageal cancer tissue. Regarding the expression level, no significant difference was observed in patients with stage I-IV esophageal cancer. Immunohistochemistry showed that P4HA1 was highly expressed in esophageal squamous cell carcinoma (68.7%), while it was negatively expressed in paracancerous tissues. There was a significant difference in expression between cancer and adjacent tissues. The expression of P4HA1 associated with the degree of tumor differentiation, site, lymph node metastasis, and tumor node metastasis stage. The prognostic factors that affected the OS (overall survival) of esophageal cancer patients were the degree of differentiation, lymph node metastasis, and P4HA1 expression. Multivariate analysis of the OS results of patients showed that lymph node metastases and P4HA1 expression were independent prognostic factors that affected the OS of esophageal cancer patients. The prognostic factors affecting the PFS (progression-free survival) of esophageal cancer patients in the univariate survival analysis were as follows: degree of differentiation, lymph node metastasis, and P4HA1 expression. In addition, multivariate analysis of the PFS results of patients showed that lymph node metastasis and P4HA1 expression were independent prognostic factors that affected the PFS of esophageal cancer patients. P4HA1 may be a novel potential biomarker for the early diagnosis, prognosis, and targeted therapy of esophageal cancer.

A novel tumor microenvironment-related gene signature with immune features for prognosis of lung squamous cell carcinoma

PURPOSE

Lung squamous cell carcinoma (LUSC) is an aggressive subset of non-small-cell lung cancer (NSCLC). The tumor microenvironment (TME) plays an important role in the development of LUSC. We aim to identify potential therapeutic targets and a TME-related prognostic signature and for LUSC.

METHODS

TME-related genes were obtained from TCGA-LUSC dataset. LUSC samples were clustered by the non-negative matrix clustering algorithm (NMF). The prognostic signature was constructed through univariate Cox regression, multivariate Cox regression, and the least absolute shrinkage and selection operator (LASSO) analyses. Gene set enrichment analysis (GSEA) was carried out to explore the enrichment pathways.

RESULTS

This study constructed a prognostic signature which contained 12 genes: HHIPL2, PLK4, SLC6A4, LSM1, TSLP, P4HA1, AMH, CLDN5, NRTN, CDH2, PTGIS, and STX1A. Patients were classified into high-risk and low-risk groups according to the median risk score of this signature. Compared with low-risk group patients, patients in high-risk group patients had poorer overall survival, which demonstrated this signature was an independent prognostic factor. Besides, correlation analysis and GSEA results revealed that genes of this signature were correlated with immune cells and drug response.

CONCLUSION

Our novel signature based on 12 TME-related genes might be applied as an independent prognostic indicator. Importantly, the signature could be a promising biomarker and accurately predict the prognosis of LUSC patients.

PLODs: Novel prognostic biomarkers and potential immunotherapy targets for head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) comprise a group of malignant tumors arising from the squamous epithelium of the oral cavity, pharynx, and larynx. HNSCC is the 6th most common cancer in the world, with approximately 650,000 new cases and 400,000 deaths annually. Although survival rates have improved, HNSCC therapy may result in short - or long-term morbidity in approximately 50% of cases. Previous studies have also indicated that the overexpression of procollagen-Lysine, 2-Oxoglutarate 5-Dioxygenases (PLOD) family proteins could lead to certain diseases or even tumors. However, there has been no dedicated evaluation of the relationship between PLOD family members and HNSCC. Here we used data from the Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Human Protein Atlas (HPA) databases to explore the potential role of PLOD family proteins in HNSCC. Our evaluations suggest that increased expression of PLOD family proteins may be associated with poorer prognosis and increased immune infiltration in HNSCC, making these proteins a potential biomarker for personalized treatment of HNSCC.

P4HA1, transcriptionally activated by STAT1, promotes esophageal cancer progression

Esophageal cancer (EC) is one of the most frequent cancers with a higher mortality worldwide. Although prolyl 4-hydroxylase alpha polypeptide I (P4HA1) is involved in various human malignancies, the function of P4HA1 in EC remains unclear. The mRNA and protein expressions were assessed by quantitative real-time polymerase chain reaction, western blot and immunohistochemistry. CCK8 assay was used to detect EC cell viability. Cell proliferation was analyzed by colony formation and ethynyl-2'-deoxyuridine assays. In addition, flow cytometry and TdT-mediated dUTP nick-end labeling staining were performed to detect cell apoptosis. Masson's trichrome staining was used to assess the collagen fiber level in tumor tissues. The interaction between STAT1 and P4HA4 was analyzed using ChIP, dual-luciferase reporter gene and Y1H assays. P4HA1 was overexpressed in EC, and its knockdown suppressed EC cell proliferation and collagen synthesis and increased cell apoptosis. Meanwhile, P4HA1 knockdown could repress EC tumor growth in vivo. Our further research displayed that STAT1 promoted P4HA1 expression by interacting with P4HA1 promoter. As expected, P4HA1 overexpression abolished STAT1 knockdown's repression on EC cell malignant behaviors. Our research proved that P4HA1 was transcriptionally activated by STAT1, thereby promoting EC progression.

Cancer stem cell-like cells-derived exosomal lncRNA CDKN2B-AS1 promotes biological characteristics in thyroid cancer via miR-122-5p/P4HA1 axis

Introduction

Here, the discussion focused on the function and possible mechanism of cancer stem cell-like cells (CSCs)-derived exosomal CDKN2B-AS1 in thyroid cancer.

Methods

Specifically, the bioinformatics analysis, dual-luciferase reporter assay and RT-qPCR were conducted to obtain the expression and regulation of CDKN2B-AS1, and the downstream miR-122-5p/P4HA1 axis. Exosomes were identified by transmission electron microscopy. The uptake of exosome by recipient cells was observed by PKH67 labeling. Functional experiments and western blot were adopted to detect the effects of exosomal CDKN2B-AS1/miR-122-5p/P4HA1 axis on thyroid cancer cells. Tumor xenograft and in vivo metastasis model combined with RT-qPCR, western blot and hematoxylin-eosin staining verified the role of CDKN2B-AS1.

Results

Exosomal CDKN2B-AS1 up-regulated P4HA1 expression through miR-122-5p. CDKN2B-AS1 and P4HA1 expressions were up-regulated, and miR-122-5p expression was down-regulated in thyroid cancer. Silent CDKN2B-AS1 reduced cell viability and stemness. CDKN2B-AS1 was found to be abundant in CSCs and CSCs-derived exosomes. Exosomal CDKN2B-AS1 silencing could transfer to thyroid cancer cells to elevate E-cadherin level, and diminish P4HA1, N-cadherin and Vimentin levels, thus impeding cell migration and invasion. MiR-122-5p inhibitor reversed the function of exosomal CDKN2B-AS1, while P4HA1 silencing attenuated the effect of miR-122-5p inhibitor. Exosomal CDKN2B-AS1 affected the growth and metastasis of thyroid cancer through the miR-122-5p/P4HA1 axis.

Conclusion

CSCs-derived exosomal CDKN2B-AS1 acts as an oncogene in thyroid cancer through miR-122-5p/P4HA1 axis.

Potential Diagnostic and Prognostic Values of CBX8 Expression in Liver Hepatocellular Carcinoma, Kidney Renal Clear Cell Carcinoma, and Ovarian Cancer: A Study Based on TCGA Data Mining

Background

Chromobox protein homolog 8 (CBX8), a transcriptional repressor, participates in many biological processes in various carcinomas. Cell differentiation, aging, and cell cycle progression are examples of such processes. It is critical to investigate CBX8 expression and its relationship with clinicopathological characteristics in liver hepatocellular carcinoma (LIHC), kidney renal clear cell carcinoma (KIRC), and ovarian cancer (OV) to investigate CBX8's potential diagnostic and prognostic values.

Methods

TCGA and CPTAC databases were used to compare the data between cancer and matched normal tissues on RNA and protein expression profiles and their relevant clinical information to determine the relationship between CBX8 and clinicopathological features. Kaplan–Meier analyses were used to assess CBX8 relationship's with disease-free survival (DFS), relapse-free survival (RFS), and overall survival (OS). The multivariate Cox regression analysis was used to identify independent risk factors which affect prognosis. DNA methylation and genetic changes and their impact on prognoses were evaluated by cBioPortal and MethSurv websites. Spearman's correlation was used to determine the relationship of CBX8 expression with somatic mutation. Tumor immune estimation resource (TIMER) was adopted to investigate the relationship between CBX8 and immune cell infiltration (ICI). CBX8-relevant genes and proteins are analyzed by EnhancedVolcano and STRING databases. The gene set enrichment analysis (GSEA) was performed to investigate the potential functions of CBX8.

Results

CBX8 RNA and protein overexpression were confirmed in LIHC, KIRC, and OV (p < 0.05). High CBX8 was significantly related to the clinical features and poor prognoses. The CBX8 genetic alteration rate was 3%. DNA methylation was also associated with prognoses. CBX8 closely interacted with ICI, TMB, MSI, purity, and ploidy. GO analyses revealed that CBX8-associated genes were enriched in biological processes, cell cycle regulation, and molecular functions. KEGG analyses exhibited that CBX8 was gathered in signaling pathway regulation. GSEA revealed that cell cycle, DNA replication, and Wnt signaling pathways were differentially enriched in the high CBX8 expression group.

Conclusions

CBX8 could be a potential diagnostic and prognostic biomarker for LIHC, KIRC, and OV cancers.

Identification of a metabolic reprogramming-related signature associated with prognosis and immune microenvironment of head and neck squamous cell carcinoma by in silico analysis

Background

Metabolic reprogramming is one of the essential features of tumorigenesis. Herein, this study aimed to develop a novel metabolism‐related gene signature for head and neck squamous cell carcinoma (HNSCC) patients.

Methods

The transcriptomic and clinical data of HNSCC samples were collected from The Cancer Genome Atlas (TCGA) and GSE65858 datasets. The metabolism‐related gene‐based prognostic signature (MRGPS) was constructed by the Least Absolute Shrinkage and Selection Operator (LASSO) regression model. The time‐dependent receiver operating characteristic (ROC) and Kaplan‐Meier (K‐M) survival curves were plotted for evaluating its predicting performance. At the same time, univariate along with multivariate analysis was carried out to explore its correlation with clinicopathologic factors. Furthermore, GSEA analysis was performed to explore the signaling pathways affected by MRGPS. We also analyzed the associations of MRGPS with the tumor immune microenvironment (TIME), as well as identified potential compounds via Connectivity Map (CMap) and molecular docking.

Results

A total of 12 differentially expressed metabolism‐related genes were identified and selected to construct the MRGPS. Notably, this signature performed well in predicting HNSCC patients’ survival and could serve as an independent prognostic factor in multiple datasets. In addition to the metabolism‐related pathway, this signature could also affect some immune‐related pathways. The results indicated that MRGPS is correlated with immune cells infiltration and anti‐cancer immune response. Furthermore, we identified cephaeline as a potential therapeutic compound for HNSCC.

Conclusion

Taken together, we established an MRGs‐based signature that has the potential to predict the clinical outcome and immune microenvironment, which help to search for potential combination immunotherapy compounds and provide a promising therapeutic strategy for treating HNSCC patients.

Identification of a novel glycolysis-related gene signature for predicting the survival of patients with colon adenocarcinoma

BACKGROUND

The most frequent histologic subtype of colon cancer is colon adenocarcinoma (COAD). A major problem in the diagnosis and treatment of COAD is that there is lack of new biomarkers to indicate the early stage of COAD. Compared with normally differentiated cells, the glycolytic pathways of tumor cells are more active, thus making them more adaptable to the hypoxic environment of solid tumors, which is known as the Warburg effect. Therefore, establishing a diagnostic and prognostic model based on glycolysis-related genes may provide guidance for the precise treatment of colon cancer.

METHODS

The Cancer Genome Atlas (TCGA) mRNA data were used to identify differentially expressed genes (DEGs). The glycolysis-related DEGs were identified using Gene Set Enrichment Analysis (GSEA) with HALLMARK gene sets. Combined with clinical data, we identified prognostic genes in glycolysis-related DEGs based on Cox regression analysis. Four glycolysis-related genes were identified and a predictive model was developed using univariate and multivariate Cox regression analysis. cBioPortal investigated the chromosomal variations of these genes. Following that, survival analysis and receiver operating characteristic (ROC) curve validation were carried out. The correlations between glycolysis-related gene signatures and molecular features and cancer subtypes were analyzed.

RESULTS

We discovered five genes (SPAG4, P4HA1, STC2, ENO3, and GPC1) that are associated with COAD patients' prognosis. The risk score was more accurate in predicting prognosis when based on this gene signature in COAD patients. Furthermore, multivariate Cox regression analysis demonstrated that the glycolysis-related gene signature's predictive value was independent of clinical variables.

CONCLUSION

We identified a glycolysis-related five-gene signature and developed a risk staging model potentially valuable for the clinical management of COAD patients. Our results suggest that prognostic markers based on glycolysis-related genes may be a reliable predictive tool for the prognosis of COAD patients.

A Novel Glycolysis and Hypoxia Combined Gene Signature Predicts the Prognosis and Affects Immune Infiltration of Patients with Colon Cancer

Purpose

We aimed to characterize the expression patterns of glycolysis and hypoxia genes in colon cancers as well as their value in prognosis and immune microenvironment.

Methods

The expression profiles were acquired from the Cancer Genome Atlas database. Enrichment of hypoxia and glycolysis gene sets in colon cancer was identified by gene set enrichment analysis. Then, a prognostic signature was built up after Cox regression analyses, and overall survival analysis validated the predictive ability. Immune status and infiltration in cancer tissues were explored using the single sample gene set enrichment analysis and CIBERSORT algorithm. A nomogram model integrating clinical variables and the gene signature was established and assessed.

Results

Altogether, 378 cancer and 39 control cases were enrolled. Three glycolysis gene sets and two hypoxia gene sets were enriched in colon cancer (P < 0.05). Five independent genes (ENO3, GPC1, P4HA1, SPAG4, and STC2) were significantly correlated with prognosis of colon cancer patients. Patients with higher risks had significantly better prognosis than those with lower risks (P = 0.002 and AUC = 0.750), which was also observed in the elderly, female and stage I–II subgroups (P < 0.05). In high-risk cases, proportion of NK cells resting increased (P < 0.05) while that of dendritic cells activated (P < 0.05), dendritic cells resting (P < 0.01) and monocytes (P < 0.01) decreased. Besides, expressions of 22 checkpoint genes were found abnormal in groups with different risks (P < 0.05). The predictive nomogram presented satisfactory performance with C-index of 0.771 (0.712–0.830). The area under ROC curve was 0.796 and 0.803 for 3- and 5-year survival prediction, respectively.

Conclusion

A glycolysis and hypoxia combined gene signature was a promising method to evaluate the prognosis and immune infiltration of colon cancer patients, which may provide a new tool for cancer management.

P4HA1, a Prognostic Biomarker that Correlates With Immune Infiltrates in Lung Adenocarcinoma and Pan-Cancer

Objective: Prolyl 4-hydroxylase, alpha polypeptide I (P4HA1), a key enzyme in collagen synthesis, comprises two identical alpha subunits and two beta subunits. However, the immunomodulatory role of P4HA1 in tumor immune microenvironment (TIME) remains unclear. This study aimed to evaluate the prognostic value of P4HA1 in pan-cancer and explore the relationship between P4HA1 expression and TIME.

Methods: P4HA1 expression, clinical features, mutations, DNA methylation, copy number alteration, and prognostic value in pan-cancer were investigated using the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression data. Pathway enrichment analysis of P4HA1 was performed using R package “clusterProfiler.” The correlation between immune cell infiltration level and P4HA1 expression was analyzed using three sources of immune cell infiltration data, including ImmuCellAI database, TIMER2 database, and a published work.

Results: P4HA1 was substantially overexpressed in most cancer types. P4HA1 overexpression was associated with poor survival in patients. Additionally, we discovered that P4HA1 expression was positively associated with infiltration levels of immunosuppressive cells, such as tumor-associated macrophages, cancer-associated fibroblasts, nTregs, and iTregs, and negatively correlated with CD8⁺ T and NK cells in pan-cancer.

Conclusions: Our results highlighted that P4HA1 might serve as a potential prognostic biomarker in pan-cancer. P4HA1 overexpression is indicative of an immunosuppressive microenvironment. P4HA1 may be a potential target of immunotherapy.

Constructe a novel 5 hypoxia genes signature for cervical cancer

Background

Hypoxia, which affects the development, metastasis and prognosis of cancer, represents a key feature of cancer. This study describe a hypoxia risk factor model, with predicting the prognosis of cervical cancer.

Methods

Based on hypoxia pathway related genes, we divided cervical cancer samples into high and low expression groups. A cox analysis was then performed. Genes from these cervical cancer samples showing a significant impact on OS were selected for cluster analysis to obtain two subtypes. The TPM dataset of TCGA was divided into training and validation sets. For the training set, a lasso analysis was conducted as based on cox analysis of meaningful genes and a risk factor model was constructed. The constructed model was verified in internal and external data sets. Finally, RT-PCR, immunohistochemistry were used to detect the expression of relative genes or proteins and functional assays were used to evaluate the biological function of signature genes.

Results

Two molecular subtypes were obtained, Cluster2 vs Cluster1.These subtypes were obtained by clustering with a total of 149 DEGs (Differential expressed genes) being in line with this standard, of which 27 were up-regulated and 122 were down-regulated. The five genes with lambda = 0.0571 were selected to construct the model, the RiskScore = AK4*0.042 + HK2*0.021 + P4HA1*0.22 + TGFBI*0.1 + VEGFA*0.077. Further, in order to verify the signature, we used TCGA-test and GSE44001 chip datasets to test, and finally got a good risk prediction effect in those datasets. Moreover, the result of RT-PCR and immunohistochemistry demonstrated that AK4, HK2, P4HA1, TGFBI and VEGFA were all highly expressed in these cervical cancer tissue samples. The functional study shown that expression of AK4, HK2, P4HA1, TGFBI and VEGFA can regulate the proliferation, migration, and invasion ability of cervical cancer cells in vitro.

Conclusions

In summary, we developed a 5-gene signature prognostic hierarchical system based on the hypoxic pathway of cervical cancer, which is independent of clinical characteristics. And also conducted experimental verifications on these signature gene. Therefore, we propose that use of this classifier as a molecular diagnostic test can provide an effective means for evaluating the prognostic risk of cervical cancer patients, and provide potential targets for the treatment of cervical cancer patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02050-3.

Collagen modifying enzyme P4HA1 is overexpressed and plays a role in lung adenocarcinoma

Lung cancer is the leading cause of cancer-related deaths globally and is histologically defined as either small cell lung cancer (SCLC) or non-small cell lung cancer (NSCLC), with the latter accounting for 80% of all lung cancers. The 5-year overall survival rate for lung cancer patients is low as it is often discovered at advanced stages when potential cure by surgical resection is no longer an option. To identify a biomarker and target for lung cancer, we performed analysis of multiple datasets of lung cancer gene expression data. Our analyses indicated that the collagen-modifying enzyme Prolyl 4-Hydroxylase Subunit Alpha 1 (P4HA1) is overexpressed in NSCLC. Furthermore, our investigation found that overexpression of enzymes involved in this pathway predicts poor outcome for patients with lung adenocarcinoma. Our functional studies using knockdown strategies in lung cancer cell lines in vitro indicated that P4HA1 is critical for lung cancer growth, migration, and invasion. Additionally, diethyl pythiDC (PythiDC), a small molecule inhibitor, decreased the malignant phenotypes of lung cancer cells. Moreover, we found that miR-124 regulates and targets P4HA1 in lung cancer cells. Thus, our study suggests that collagen-modifying enzymes play an important role in lung cancer aggressiveness. Furthermore, our studies showed that P4HA1 is required for lung cancer cell growth and invasion, suggesting its potential as a valid therapeutic target in lung adenocarcinoma.

Genetic Drivers of Head and Neck Squamous Cell Carcinoma: Aberrant Splicing Events, Mutational Burden, HPV Infection and Future Targets

Head and neck cancers include cancers that originate from a variety of locations. These include the mouth, nasal cavity, throat, sinuses, and salivary glands. These cancers are the sixth most diagnosed cancers worldwide. Due to the tissues they arise from, they are collectively named head and neck squamous cell carcinomas (HNSCC). The most important risk factors for head and neck cancers are infection with human papillomavirus (HPV), tobacco use and alcohol consumption. The genetic basis behind the development and progression of HNSCC includes aberrant non-coding RNA levels. However, one of the most important differences between healthy tissue and HNSCC tissue is changes in the alternative splicing of genes that play a vital role in processes that can be described as the hallmarks of cancer. These changes in the expression profile of alternately spliced mRNA give rise to various protein isoforms. These protein isoforms, alternate methylation of proteins, and changes in the transcription of non-coding RNAs (ncRNA) can be used as diagnostic or prognostic markers and as targets for the development of new therapeutic agents. This review aims to describe changes in alternative splicing and ncRNA patterns that contribute to the development and progression of HNSCC. It will also review the use of the changes in gene expression as biomarkers or as the basis for the development of new therapies.

A Recurrence-Specific Gene-Based Prognosis Prediction Model for Lung Adenocarcinoma through Machine Learning Algorithm

Background

After curative surgical resection, about 30-75% lung adenocarcinoma (LUAD) patients suffer from recurrence with dismal survival outcomes. Identification of patients with high risk of recurrence to impose intense therapy is urgently needed.

Materials and Methods

Gene expression data of LUAD were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Differentially expressed genes (DEGs) were calculated by comparing the recurrent and primary tissues. Prognostic genes associated with the recurrence-free survival (RFS) of LUAD patients were identified using univariate analysis. LASSO Cox regression and multivariate Cox analysis were applied to extract key genes and establish the prediction model.

Results

We detected 37 DEGs between primary and recurrent LUAD tumors. Using univariate analysis, 31 DEGs were found to be significantly associated with RFS. We established the RFS prediction model including thirteen genes using the LASSO Cox regression. In the training cohort, we classified patients into high- and low-risk groups and found that patients in the high-risk group suffered from worse RFS compared to those in the low-risk group (P < 0.01). Concordant results were confirmed in the internal and external validation cohort. The efficiency of the prediction model was also confirmed under different clinical subgroups. The high-risk group was significantly identified as the risk factor of recurrence in LUAD by the multivariate Cox analysis (HR = 13.37, P = 0.01). Compared to clinicopathological features, our prediction model possessed higher accuracy to identify patients with high risk of recurrence (AUC = 96.3%). Finally, we found that the G2M checkpoint pathway was enriched both in recurrent tumors and primary tumors of high-risk patients.

Conclusions

Our recurrence-specific gene-based prognostic prediction model provides extra information about the risk of recurrence in LUAD, which is conducive for clinicians to conduct individualized therapy in clinic.

Systematic Characterization of the Expression and Prognostic Values of Formin-Like Gene Family in Gastric Cancer

Formin-like genes (FMNLs) are members of formins family and have been implicated to the development and progression of multiple cancers. This research aims to analyze the expression profiles, prognostic values, and immune infiltrating associations of FMNLs in gastric cancer (GC) using multiple online bioinformatics website, including Oncomine, UALCAN, Kaplan-Meier Plotter, TIMER, GeneMANIA, DAVID, and LinkedOmics databases. The mRNA levels of FMNL1/2/3 were higher in GC tissues than normal. Meanwhile, FMNLs expressions tend to be upregulated in advanced and poorly differentiated GC. Prognostic value analysis suggested that high transcription levels of FMNL1/3 were associated with poor overall survival in GC patients. Correlation analysis between FMNLs expressions and immune infiltrating GC revealed that the expressions of FMNLs were significantly associated with immune infiltrating. Protein-protein interaction network and enrichment analysis of FMNLs in GC showed that FMNLs coexpressed genes mainly participated in organizing actin cytoskeleton through affecting small G proteins activity. Moreover, Gene Set Enrichment Analysis (GSEA) analysis uncovered FMNLs and their coexpressed genes was tightly associated with immune-related cellular functions. These findings demonstrate that FMNLs might play significant immunomodulatory roles in tumor immunity and could be novel therapeutic targets and potential prognostic biomarkers in GC.

Identification of Candidate Genes Associated with Breast Cancer Prognosis

Breast cancer (BC) is the most malignant tumor in women. The molecular mechanisms underlying tumorigenesis still need to be further elucidated. It is necessary to investigate novel candidate genes involved in breast cancer progression and prognosis. In this study, we commit to explore candidate genes that associate with prognosis and therapy in BC by a comprehensive bioinformatic analysis. Four GEO datasets (GSE5764, GSE7904, GSE20711, and GSE29431) and the BC-related transcriptome data in TCGA database were downloaded and used to identify the differently expressed genes (DEGs). The function of DEGs was analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analysis. The protein-protein interaction (PPI) network of DEGs was constructed to identify hub genes. Prognostic candidate genes were identified through survival analysis. In addition, potential therapeutic targets were identified by constructed gene-drug interaction network through Comparative Toxicogenomics Database. A total of 547 DEGs (302 up and 245 down) were identified. Three core-subnetwork and 25 hub genes were identified in PPI network. Seven genes (namely COL12A1, QPRT, MRPL13, KRT14, KRT15, LAMB3, and MYBPC1) were identified as crucial prognostic candidate genes, which significantly associated with breast cancer overall survival. Furthermore, two representative candidate genes (COL12A1 and LAMB3) were optionally chosen for verification by reverse transcription and quantitative real-time polymerase chain reaction (RT-PCR). What's more, the gene-drugs interaction analysis indicates several antitumor drugs that could affect the expression of these prognostic markers, such as doxorubicin, cisplatin, and tamoxifen. These results identified seven crucial candidate genes that may serve as prognosis biomarkers and novel therapeutic targets of breast cancer, which may facilitate further understanding the molecular pathogenesis and providing potential therapeutic strategies for BC.