Identification of COL1A1 and COL1A2 as candidate prognostic factors in gastric cancer

l-Carnitine relieves cachexia-related skeletal muscle fibrosis by inducing deltex E3 ubiquitin ligase 3L to negatively regulate the Runx2/COL1A1 axis

BACKGROUND

Cancer cachexia-induced skeletal muscle fibrosis (SMF) impairs muscle regeneration, alters the muscle structure and function, reduces the efficacy of anticancer drugs, diminishes the patient's quality of life and shortens overall survival. RUNX family transcription factor 2 (Runx2), a transcription factor, and collagen type I alpha 1 chain (COL1A1), the principal constituent of SMF, have been linked previously, with Runx2 shown to directly modulate COL1A1 mRNA levels. l-Carnitine, a marker of cancer cachexia, can alleviate fibrosis in liver and kidney models; however, its role in cancer cachexia-associated fibrosis and the involvement of Runx2 in the process remain unexplored.

METHODS

Female C57 mice (48 weeks old) were inoculated subcutaneously with MC38 cells to establish a cancer cachexia model. A 5 mg/kg dose of l-carnitine or an equivalent volume of water was administered for 14 days via oral gavage, followed by assessments of muscle function (grip strength) and fibrosis. To elucidate the interplay between the deltex E3 ubiquitin ligase 3L(DTX3L)/Runx2/COL1A1 axis and fibrosis in transforming growth factor beta 1-stimulated NIH/3T3 cells, a suite of molecular techniques, including quantitative real-time PCR, western blot analysis, co-immunoprecipitation, molecular docking, immunofluorescence and Duolink assays, were used. The relevance of the DTX3L/Runx2/COL1A1 axis in the gastrocnemius was also explored in the in vivo model.

RESULTS

l-Carnitine supplementation reduced cancer cachexia-induced declines in grip strength (>88.2%, P < 0.05) and the collagen fibre area within the gastrocnemius (>57.9%, P < 0.05). At the 5 mg/kg dose, l-carnitine also suppressed COL1A1 and alpha-smooth muscle actin (α-SMA) protein expression, which are markers of SMF and myofibroblasts. Analyses of the TRRUST database indicated that Runx2 regulates both COL1A1 and COL1A2. In vitro, l-carnitine diminished Runx2 protein levels and promoted its ubiquitination. Overexpression of Runx2 abolished the effects of l-carnitine on COL1A1 and α-SMA. Co-immunoprecipitation, molecular docking, immunofluorescence and Duolink assays confirmed an interaction between DTX3L and Runx2, with l-carnitine enhancing this interaction to promote Runx2 ubiquitination. l-Carnitine supplementation restored DTX3L levels to those observed under non-cachectic conditions, both in vitro and in vivo. Knockdown of DTX3L abolished the effects of l-carnitine on Runx2, COL1A1 and α-SMA in vitro. The expression of DTX3L was negatively correlated with the levels of Runx2 and COL1A1 in untreated NIH/3T3 cells.

CONCLUSIONS

This study revealed a previously unrecognized link between Runx2 and DTX3L in SMF and demonstrated that l-carnitine exerted a significant therapeutic impact on cancer cachexia-associated SMF, potentially through the upregulation of DTX3L.

Association of COL4A2 indel polymorphism with the development of stomach adenocarcinoma in Chinese populations

OBJECTIVE

The objective of the study was to assess the potential association between the indel polymorphism (rs34802628) located within the intron of the collagen type ⅳ alpha 2 gene (COL4A2) and the susceptibility to stomach adenocarcinoma (STAD) within a Chinese population.

METHODS

Peripheral venous blood samples were collected from a total of 497 STAD patients and 804 healthy control individuals to extract genomic DNA. The genotyping of the COL4A2 rs34802628 polymorphism was carried out using a polymerase chain reaction assay. Additionally, statistical analyses were conducted on the expression levels of COL4A2 mRNA using the GEPIA database. Meanwhile, the expression of COL4A2 mRNA was also validated by Real-time PCR using STAD tissue samples. Then, based on an analysis of patient tumor RNA seq data available from the Cancer Genome Atlas (TCGA), we assessed the prognostic value of mRNA expression of the COL4A2 gene in STAD patients using K-M plotter.

RESULTS

The study presented compelling evidence supporting an association between the rs34802628 polymorphism in the COL4A2 gene and susceptibility to STAD. Logistic regression analysis revealed that both the heterozygote and homozygote 4-bp del/del genotypes were significantly associated with a decreased risk of STAD, even after controlling for other variables (adjusted odds ratio [OR] = 0.663, 95% confidence interval [CI] 0.519-0.848, p = 0.037; OR = 0.422, 95% CI 0.290-0.614, p = 0.000005, respectively). Importantly, individuals carrying the 4-bp deletion allele demonstrated a notably lower risk of developing the disease (OR = 0.696, 95% CI 0.591-0.820, p = 0.000014). Furthermore, Genotype-phenotype correlation studies in human STAD tissue samples demonstrated that the higher mRNA expression levels of COL4A2 were associated with the ins allele of rs34802628. Bioinformatics analysis revealed that higher expression of the COL4A2 gene was significant with development and poor prognosis of STAD.

CONCLUSION

The results of our study provide strong evidence indicating a potential involvement of genetic variants in the COL4A2 gene in the development of STAD. Nonetheless, to validate and consolidate these findings, additional investigations incorporating larger sample sizes and functional experiments are necessary.

Nearby and non-nested genes in the human genome have more similar genotype tissue expression

Neighboring genes within a shared promoter arrangement (i.e. opposite direction with the neighboring ends as the transcriptional start sites) are expected to have a high similarity in genotype tissue expression due to the potential overlap in the promoter region. This raises the question of whether similarity in expression profiles depends on orientation of the neighboring genes and whether there exist thresholds of locality where the similarity diminishes. Thus, in this work, we compared genotype tissue expression profiles at different genomic orientations and localities. Interestingly, there exist gene pairs in the human genome with very high or low expression similarity. Shorter chromosomes tend to have more similarly expressed genes. Also, a cluster of 3 adjacent genes within the average range of 20 to 60 kilobase pairs can have very similar expression profiles regardless of their orientations. However, when genes are nested and in opposite orientations, a lower than expected similarity was observed. Lastly, in cases where genotype tissue expression data does not exist or have low read counts (e.g. non-coding RNA), our identified influencing range can be a first estimate of the genotype tissue expression.

The Spatial Extracellular Proteomic Tumor Microenvironment Distinguishes Molecular Subtypes of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) mortality rates continue to increase faster than those of other cancer types due to high heterogeneity, which limits diagnosis and treatment. Pathological and molecular subtyping have identified that HCC tumors with poor outcomes are characterized by intratumoral collagenous accumulation. However, the translational and post-translational regulation of tumor collagen, which is critical to the outcome, remains largely unknown. Here, we investigate the spatial extracellular proteome to understand the differences associated with HCC tumors defined by Hoshida transcriptomic subtypes of poor outcome (Subtype 1; S1; n = 12) and better outcome (Subtype 3; S3; n = 24) that show differential stroma-regulated pathways. Collagen-targeted mass spectrometry imaging (MSI) with the same-tissue reference libraries, built from untargeted and targeted LC-MS/MS was used to spatially define the extracellular microenvironment from clinically-characterized, formalin-fixed, paraffin-embedded tissue sections. Collagen α-1(I) chain domains for discoidin-domain receptor and integrin binding showed distinctive spatial distribution within the tumor microenvironment. Hydroxylated proline (HYP)-containing peptides from the triple helical regions of fibrillar collagens distinguished S1 from S3 tumors. Exploratory machine learning on multiple peptides extracted from the tumor regions could distinguish S1 and S3 tumors (with an area under the receiver operating curve of ≥0.98; 95% confidence intervals between 0.976 and 1.00; and accuracies above 94%). An overall finding was that the extracellular microenvironment has a high potential to predict clinically relevant outcomes in HCC.

Simultaneous Detection of Collagen I Alpha II and Cytokeratin 19 mRNA by Multiplex qPCR in Liquid Biopsy in Diagnosis of Patients with Resectable Solid Tumors

The early detection of tumors is one of the key factors in increasing overall survival in cancer patients. A wide range of cancers still do not have a system of early diagnosis; therefore, the development of new non-invasive tools in this line is essential. Accordingly, the objective of our work was to develop a non-invasive screening method for the early detection of various carcinomas in plasma using a panel that combines two markers using RT-qPCR. A retrospective case-control study was conducted to develop a cancer screening test based on the detection of stromal and epithelial biomarkers (COL1A2 and KRT19) in plasma. The expression of biomarkers was evaluated using multiplex quantitative PCR applied to 47 cases with non-metastatic tumors and 13 control participants. For both biomarkers, a cut-off value was stablished using Youden's J index through ROC curve analysis and areas under the curve (AUC) were calculated. The plasma mRNA expression level of both biomarkers was significantly higher in diseased versus healthy patients. Moreover, ROC curve analysis showed an AUC value of 0.897 for the combined model. This model also resulted in a cutoff value of 0.664, as well as a sensitivity of 83% and a specificity of 84.6%. These results suggest that the plasma expression levels of COL1A2 and KRT19 could a have potential role in detecting various types of cancer at the early stages. The combined analysis of both stromal and epithelial biomarkers would provide a non-invasive screening method that would allow us to differentiate patients with an active neoplastic process.

ENG is a Biomarker of Prognosis and Angiogenesis in Liver Cancer, and Promotes the Differentiation of Tumor Cells into Vascular ECs

BACKGROUND

Liver cancer is a highly lethal malignancy with frequent recurrence, widespread metastasis, and low survival rates. The aim of this study was to explore the role of Endoglin (ENG) in liver cancer progression, as well as its impacts on angiogenesis, immune cell infiltration, and the therapeutic efficacy of sorafenib.

METHODS

A comprehensive evaluation was conducted using online databases Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA), 76 pairs of clinical specimens of tumor and adjacent non-tumor liver tissue, and tissue samples from 32 hepatocellular carcinoma (HCC) patients treated with sorafenib. ENG expression levels were evaluated using quantitative Reverse Transcription Polymerase Chain Reaction (qRT-PCR), Western blot, and immunohistochemical analysis. Cox regression analysis, Spearman rank correlation analysis, and survival analysis were used to assess the results. Functional experiments included Transwell migration assays and tube formation assays with Human Umbilical Vein Endothelial Cells (HUVECs).

RESULTS

Tumor cells exhibited retro-differentiation into endothelial-like cells, with a significant increase in ENG expression in these tumor-derived endothelial cells (TDECs). High expression of ENG was associated with more aggressive cancer characteristics and worse patient prognosis. Pathway enrichment and functional analyses identified ENG as a key regulator of immune responses and angiogenesis in liver cancer. Further studies confirmed that ENG increases the expression of Collagen type Iα1 (COL1A1), thereby promoting angiogenesis in liver cancer. Additionally, HCC patients with elevated ENG levels responded well to sorafenib treatment.

CONCLUSIONS

This study found that ENG is an important biomarker of prognosis in liver cancer. Moreover, ENG is associated with endothelial cell differentiation in liver cancer and plays a crucial role in formation of the tumor vasculature. The assessment of ENG expression could be a promising strategy to identify liver cancer patients who might benefit from targeted immunotherapies.

Characterize molecular signatures and establish a prognostic signature of gastric cancer by integrating single-cell RNA sequencing and bulk RNA sequencing

Gastric cancer is a significant global health concern with complex molecular underpinnings influencing disease progression and patient outcomes. Various molecular drivers were reported, and these studies offered potential avenues for targeted therapies, biomarker discovery, and the development of precision medicine strategies. However, it was posed that the heterogeneity of the disease and the complexity of the molecular interactions are still challenging. By seamlessly integrating data from single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (bulk RNA-seq), we embarked on characterizing molecular signatures and establishing a prognostic signature for this complex malignancy. We offered a holistic view of gene expression landscapes in gastric cancer, identified 226 candidate marker genes from 3 different dimensions, and unraveled key players' risk stratification and treatment decision-making. The convergence of molecular insights in gastric cancer progression occurs at multiple biological scales simultaneously. The focal point of this study lies in developing a prognostic model, and we amalgamated four molecular signatures (COL4A1, FKBP10, RNASE1, SNCG) and three clinical parameters using advanced machine-learning techniques. The model showed high predictive accuracy, with the potential to revolutionize patient care by using clinical variables. This will strengthen the reliability of the model and enable personalized therapeutic strategies based on each patient's unique molecular profile. In summary, our research sheds light on the molecular underpinnings of gastric cancer, culminating in a powerful prognostic tool for gastric cancer. With a firm foundation in biological insights and clinical implications, our study paves the way for future validations and underscores the potential of integrated molecular analysis in advancing precision oncology.

Effects of COL1A1 and SYTL2 on inflammatory cell infiltration and poor extracellular matrix remodeling of the vascular wall in thoracic aortic aneurysm

BACKGROUND

Thoracic aortic aneurysm (TAA) is a fatal cardiovascular disease, the pathogenesis of which has not yet been clarified. This study aimed to identify and validate the diagnostic markers of TAA to provide a strong theoretical basis for developing new methods to prevent and treat this disease.

METHODS

Gene expression profiles of the GSE9106, GSE26155, and GSE155468 datasets were acquired from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified using the "limma" package in R. Least absolute shrinkage and selection operator (LASSO), support vector machine-recursive feature elimination (SVM-RFE), random forest, and binary logistic regression analyses were used to screen the diagnostic marker genes. Single-sample gene set enrichment analysis (ssGSEA) was used to estimate immune cell infiltration in TAA.

RESULTS

A total of 16 DEGs were identified. The enrichment and functional correlation analyses showed that DEGs were mainly associated with inflammatory response pathways and collagen-related diseases. Collagen type I alpha 1 chain ( COL1A1 ) and synaptotagmin like 2 ( SYTL2 ) were identified as diagnostic marker genes with a high diagnostic value for TAA. The expression of COL1A1 and SYTL2 was considerably higher in TAA vascular wall tissues than in the corresponding normal tissues, and there were significant differences in the infiltration of immune cells between TAA and normal vascular wall tissues. Additionally, COL1A1 and SYTL2 expression were associated with the infiltration of immune cells in the vascular wall tissue. Single-cell analysis showed that COL1A1 in TAA was mainly derived from fibroblasts and SYTL2 mainly from cluster of differentiation (CD)8 + T cells. In addition, single-cell analysis indicated that fibroblasts and CD8 + T cells in TAA were significantly higher than those in normal arterial wall tissue.

CONCLUSIONS

COL1A1 and SYTL2 may serve as diagnostic marker genes for TAA. The upregulation of SYTL2 and COL1A1 may be involved in the inflammatory infiltration of the vessel wall and poor extracellular matrix remodeling, promoting the progression of TAA.

Unveiling Collagen's Role in Breast Cancer: Insights into Expression Patterns, Functions and Clinical Implications

Collagen, the predominant protein constituent of the mammalian extracellular matrix (ECM), comprises a diverse family of 28 members (I-XXVIII). Beyond its structural significance, collagen is implicated in various diseases or cancers, notably breast cancer, where it influences crucial cellular processes including proliferation, metastasis, apoptosis, and drug resistance, intricately shaping cancer progression and prognosis. In breast cancer, distinct collagens exhibit differential expression profiles, with some showing heightened or diminished levels in cancerous tissues or cells compared to normal counterparts, suggesting specific and pivotal biological functions. In this review, we meticulously analyze the expression of individual collagen members in breast cancer, utilizing Transcripts Per Million (TPM) data sourced from the GEPIA2 database. Through this analysis, we identify collagens that deviate from normal expression patterns in breast cancer, providing a comprehensive overview of their expression dynamics, functional roles, and underlying mechanisms. Our findings shed light on recent advancements in understanding the intricate interplay between these aberrantly expressed collagens and breast cancer. This exploration aims to offer valuable insights for the identification of potential biomarkers and therapeutic targets, thereby advancing the prospects of more effective interventions in breast cancer treatment.

Collagen 1A1 (COL1A1) and Collagen11A1(COL11A1) as diagnostic biomarkers in Breast, colorectal and gastric cancers

PURPOSE

Collagen family genes (CFGs) play a significant role in the pathogenesis of cancers. This study aimed to evaluate changes in the expression levels (Els) of CFGs related to epithelial-mesenchymal transition (EMT) and metastasis in gastric (GC), breast (BC), and colorectal (CRC) cancers to introduce these genes as potential diagnostic biomarkers for these three types of cancer.

METHODS

The Cancer Genome Atlas (TCGA) examined ELS changes in CFGs associated with EMT and metastasis to determine their diagnostic value for GC, BC, and CRC. InteractiVenn was used to find genes shared by these three cancers. The biomarker role of CFGs was determined using the receiver operating characteristic (ROC) analysis. GC, BC, and CRC samples were analyzed using the RT-qPCR method to verify the bioinformatics results and evaluate the EL of the selected genes as biomarkers for these cancers.

RESULTS

The in-silico results showed a significant increase in the EL of several CFGs involved in EMT and metastasis in GC, BC, and CRC samples compared to healthy samples. Six common genes (COL11A1, COL12A1, COL1A1, COL1A2, COL5A1, and COL5A2) showed significantly increased in these three cancers, therebysupporting their oncogenic role. Furthermore, the biomarker-related analyses indicated that COL11A1 and COL1A1 were common diagnostic biomarkers for the three cancers. The RT-qPCR method confirmed that the ELs of COL11A1 and COL1A1 in the GC, BC, and CRC samples increased significantly compared to the adjacent normal samples.

CONCLUSION

CFGs in EMT and metastasis of GC, BC, and CRC are strong common diagnostic biomarkers for these cancers.

Single-cell sequencing of head and neck carcinoma: Transcriptional landscape and prognostic model based on malignant epithelial cell features

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common malignancy worldwide, and the development of novel therapeutic strategies for HNSCC requires a profound understanding of tumor cells and the tumor microenvironment (TME). Additionally, HNSCC has a poor prognosis, necessitating the use of genetic markers for predicting clinical outcomes in HNSCC. In this study, we performed single-cell sequencing analysis on tumor tissues from seven HNSCC patients, along with one adjacent normal tissue. Firstly, the analysis of epithelial cell clusters revealed two clusters of malignant epithelial cells, characterized by unique gene expression patterns and dysregulated signaling pathways compared to normal epithelial cells. Secondly, the examination of the TME unveiled extensive crosstalk between fibroblasts and malignant epithelial cells, potentially mediated through ligand-receptor interactions such as COL1A1-SDC1, COL1A1-CD44, and COL1A2-SDC1. Furthermore, transcriptional heterogeneity was observed in immune cells present in the TME, including macrophages and dendritic cells. Finally, leveraging the gene expression profiles of malignant epithelial cells, we developed a prognostic model comprising six genes, which we validated using two independent datasets. These findings shed light on the heterogeneity within HNSCC tumors and the intricate interplay between malignant cells and the TME. Importantly, the developed prognostic model demonstrates high efficacy in predicting the survival outcomes of HNSCC patients.

Identification of differentially expressed genes associated with the pathogenesis of gastric cancer by bioinformatics analysis

AIM

Gastric cancer (GC) is one of the most diagnosed cancers worldwide. GC is a heterogeneous disease whose pathogenesis has not been entirely understood. Besides, the GC prognosis for patients remains poor. Hence, finding reliable biomarkers and therapeutic targets for GC patients is urgently needed.

METHODS

GSE54129 and GSE26942 datasets were downloaded from Gene Expression Omnibus (GEO) database to detect differentially expressed genes (DEGs). Then, gene set enrichment analyses and protein-protein interactions were investigated. Afterward, ten hub genes were identified from the constructed network of DEGs. Then, the expression of hub genes in GC was validated. Performing survival analysis, the prognostic value of each hub gene in GC samples was investigated. Finally, the databases were used to predict microRNAs that could regulate the hub genes. Eventually, top miRNAs with more interactions with the list of hub genes were introduced.

RESULTS

In total, 203 overlapping DEGs were identified between both datasets. The main enriched KEGG pathway was "Protein digestion and absorption." The most significant identified GO terms included "primary alcohol metabolic process," "basal part of cell," and "extracellular matrix structural constituent conferring tensile strength." Identified hub modules were COL1A1, COL1A2, TIMP1, SPP1, COL5A2, THBS2, COL4A1, MUC6, CXCL8, and BGN. The overexpression of seven hub genes was associated with overall survival. Moreover, among the list of selected miRNAs, hsa-miR-27a-3, hsa-miR-941, hsa-miR-129-2-3p, and hsa-miR-1-3p, were introduced as top miRNAs targeting more than five hub genes.

CONCLUSIONS

The present study identified ten genes associated with GC, which may help discover novel prognostic and diagnostic biomarkers as well as therapeutic targets for GC. Our results may advance the understanding of GC occurrence and progression.

Identification and validation of key genes associated with pathogenesis and prognosis of gastric cancer

Background

Gastric cancer (GC) is the fourth leading cause of cancer-related death worldwide. However, the precise mechanisms and specific biomarkers of GC have not been fully elucidated. We therefore sought to identify and validate the genes associated with GC.

Methods

RNA sequencing was performed on gastric tissue specimens from 10 cases each of non-atrophic gastritis (NAG), intestinal metaplasia (IM), and GC. Validation of gene expression was conducted through immunohistochemistry (IHC) staining. The Kaplan-Meier Plotter database was utilized to screen genes associated with prognosis, while protein-protein interaction analysis was conducted to identify hub genes.

Results

In GC-IM, the differentially expressed genes (DEGs) were predominantly enriched in pathways related to ECM-receptor interaction, focal adhesion, PI3K-Akt pathway, and pathways in cancer. Conversely, in IM-NAG, the DEGs were primarily enriched in pathways associated with fat digestion and absorption, pancreatic secretion, and retinol metabolism. IHC staining revealed elevated expression levels of KLK7 and KLK10 in GC. Specifically, KLK7 expression was found to be correlated with differentiation (P = 0.025) and depth of invasion (P = 0.007) in GC, while both KLK7 and KLK10 were associated with the overall survival (P < 0.05). Furthermore, a total of ten hub genes from DEGs in GC-NAG (COL6A2, COL1A1, COL4A1, COL1A2, SPARC, COL4A2, FN1, PCOLCE, SERPINH1, LAMB1) and five hub genes in IM-NAG (SI, DPP4, CLCA1, MEP1A, OLFM4) were demonstrated to have a significant correlation with the prognosis of GC.

Conclusions

The present study successfully identified and validated crucial genes associated with GC, providing valuable insights into the underlying mechanisms of this disease. The findings of this study have the potential to inform clinical practice.

ceRNA network-regulated COL1A2 high expression correlates with poor prognosis and immune infiltration in colon adenocarcinoma

Collagen type I α 2 (COL1A2) is a major component of collagen type I. Recently, abnormal COL1A2 expression has been reported in human cancers. However, the specific role and mechanism of COL1A2 in colon adenocarcinoma (COAD) remain unclear. We performed the pan-cancer analysis of COL1A2 expression in 33 types of human cancers from TIMER database and integrated data combined TCGA with GTEx. The prognostic values of COL1A2 for 17 cancer types of interest were estimated from GEPIA database. The results showed that COL1A2 was significantly upregulated in COAD tissues and that higher COL1A2 expression predicted unfavorable prognosis for patients with COAD. Next, COL1A2-related functional pathways in COAD were analyzed with TCGA data using R package. Additionally, we constructed a ceRNA network that LINC00638/hsa-miR-552-3p axis served as a potential regulatory pathway of COL1A2 in COAD. Furthermore, our findings showed that COL1A2 positively associated with immune infiltration and that tumor immune escape might be involved in COL1A2-mediated carcinogenesis in COAD. For the first time, we constructed a ceRNA prediction network of COL1A2 and explored the association of COL1A2 with tumor immune microenvironment remodeling. The findings may advance our understanding of the pathogenesis mechanism in COAD and paves the way for further cancer therapeutics.

Regulatory role of Chitinase 3-like 1 gene in papillary thyroid carcinoma proved by integration analyses of single-cell sequencing with cohort and experimental validations

Papillary thyroid carcinoma (PTC) is one of the most common thyroid carcinomas. The gross extrathyroidal extension and extensive metastases of PTC lead to high rates of recurrence and poor clinical outcomes. However, the mechanisms underlying PTC development are poorly understood. In this study, using single-cell RNA sequencing, the transcriptome profiles of two PTC patients were addressed, including PTC1 with low malignancy and good prognosis and PTC2 with high malignancy and poor prognosis. We found that epithelial subcluster Epi02 was the most associated with the malignant development of PTC cells, with which the fold change of Chitinase 3-like 1 (CHI3L1) is on the top of the differentially expressed genes between PTC1 and PTC2 (P < 0.001). However CHI3L1 is rarely investigated in PTC as far. We then studied its role in PTC with a series of experiments. Firstly, qRT-PCR analysis of 14 PTC patients showed that the expression of CHI3L1 was positively correlated with malignancy. In addition, overexpression or silencing of CHI3L1 in TPC-1 cells, a PTC cell line, cultured in vitro showed that the proliferation, invasion, and metastasis of the cells were promoted or alleviated by CHI3L1. Further, immunohistochemistry analysis of 110 PTC cases revealed a significant relationship between CHI3L1 protein expression and PTC progression, especially the T (P < 0.001), N (P < 0.001), M stages (P = 0.007) and gross ETE (P < 0.001). Together, our results prove that CHI3L1 is a positive regulator of malignant development of PTC, and it promotes proliferation, invasion, and metastasis of PTC cells. Our study improves understanding of the molecular mechanisms underlying the progression of PTC and provides new insights for the clinical diagnosis and treatment of PTC.

Therapeutic Modulation of Cell Morphology and Phenotype of Diseased Human Cells towards a Healthier Cell State Using Lignin

Despite lignin's global abundance and its use in biomedical studies, our understanding of how lignin regulates disease through modulation of cell morphology and associated phenotype of human cells is unknown. We combined an automated high-throughput image cell segmentation technique for quantitatively measuring a panel of cell shape descriptors, droplet digital Polymerase Chain Reaction for absolute quantification of gene expression and multivariate data analyses to determine whether lignin could therapeutically modulate the cell morphology and phenotype of inflamed, degenerating diseased human cells (osteoarthritic (OA) chondrocytes) towards a healthier cell morphology and phenotype. Lignin dose-dependently modified all aspects of cell morphology and ameliorated the diseased shape of OA chondrocytes by inducing a less fibroblastic healthier cell shape, which correlated with the downregulation of collagen 1A2 (COL1A2, a major fibrosis-inducing gene), upregulation of collagen 2A1 (COL2A1, a healthy extracellular matrix-inducing gene) and downregulation of interleukin-6 (IL-6, a chronic inflammatory cytokine). This is the first study to show that lignin can therapeutically target cell morphology and change a diseased cells' function towards a healthier cell shape and phenotype. This opens up novel opportunities for exploiting lignin in modulation of disease, tissue degeneration, fibrosis, inflammation and regenerative medical implants for therapeutically targeting cell function and outcome.

Liquid biopsy: an examination of platelet RNA obtained from head and neck squamous cell carcinoma patients for predictive molecular tumor markers

Aim

Recently, a tumor cell-platelet interaction was identified in different tumor entities, resulting in a transfer of tumor-derived RNA into platelets, named further "tumor-educated platelets (TEP)". The present pilot study aims to investigate whether such a tumor-platelet transfer of RNA occurs also in patients suffering from head and neck squamous cell carcinoma (HNSCC).

Methods

Sequencing analysis of RNA derived from platelets of tumor patients (TPs) and healthy donors (HDs) were performed. Subsequently, quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was used for verification of differentially expressed genes in platelets from TPs and HDs in a second cohort of patients and HDs. Data were analyzed by applying bioinformatic tools.

Results

Sequencing of RNA derived from the tumor as well as from platelets of TPs and HDs revealed 426 significantly differentially existing RNA, at which 406 RNA were more and 20 RNA less abundant in platelets from TPs in comparison to that of HDs. In TPs' platelets, abundantly existing RNA coding for 49 genes were detected, characteristically expressed in epithelial cells and RNA, the products of which are involved in tumor progression. Applying bioinformatic tools and verification on a second TP/HD cohort, collagen type I alpha 1 chain (COL1A1) and zinc finger protein 750 (ZNF750) were identified as the strongest potentially platelet-RNA-sequencing (RNA-seq)-based biomarkers for HNSCC.

Conclusions

These results indicate a transfer of tumor-derived messenger RNA (mRNA) into platelets of HNSCC patients. Therefore, analyses of a patient's platelet RNA could be an efficient option for liquid biopsy in order to diagnose HNSCC or to monitor tumorigenesis as well as therapeutic responses at any time and in real time.

Galectin-1 promotes gastric cancer peritoneal metastasis through peritoneal fibrosis

BACKGROUND

Peritoneal metastasis is one of the main causes of death in patients with gastric cancer (GC). Galectin-1 regulates various undesirable biological behaviors in GC and may be key in GC peritoneal metastasis.

METHODS

In this study, we elucidated the regulatory role of galectin-1 in GC cell peritoneal metastasis. GC and peritoneal tissues underwent hematoxylin-eosin (HE), immunohistochemical (IHC), and Masson trichrome staining to analyze the difference in galectin-1 expression and peritoneal collagen deposition in different GC clinical stages. The regulatory role of galectin-1 in GC cell adhesion to mesenchymal cells and in collagen expression was determined using HMrSV5 human peritoneal mesothelial cells (HPMCs). Collagen and corresponding mRNA expression were detected with western blotting and reverse transcription PCR, respectively. The promoting effect of galectin-1 on GC peritoneal metastasis was verified in vivo. Collagen deposition and collagen I, collagen III, and fibronectin 1 (FN1) expression in the peritoneum of the animal models were detected by Masson trichrome and IHC staining.

RESULTS

Galectin-1 and collagen deposition in the peritoneal tissues was correlated with GC clinical staging and were positively correlated. Galectin-1 enhanced the ability of GC cells to adhere to the HMrSV5 cells by promoting collagen I, collagen III, and FN1 expression. The in vivo experiments confirmed that galectin-1 promoted GC peritoneal metastasis by promoting peritoneal collagen deposition.

CONCLUSION

Galectin-1-induced peritoneal fibrosis may create a favorable environment for GC cell peritoneal metastasis.

Bioinformatics and pathway enrichment analysis identified hub genes and potential biomarker for gastric cancer prognosis

Introduction

Gastric cancer is one of the most common cancers in the world. This study aimed to identify genes, biomarkers, and metabolic pathways affecting gastric cancer using bioinformatic analysis and meta-analysis.

Methods

Datasets containing gene expression profiles of tumor lesions and adjacent non-tumor mucosa samples were downloaded. Common differentially expressed genes between data sets were selected to identify hub genes and further analysis. Gene Expression Profiling and Interactive Analyses (GEPIA) and the Kaplan-Meier method were used to further validate the expression level of genes and plot the overall survivalcurve, respectively.

Results and disscussion

KEGG pathway analysis showed that the most important pathway was enriched in ECM-receptor interaction. Hub genes includingCOL1A2, FN1, BGN, THBS2, COL5A2, COL6A3, SPARC and COL12A1 wereidentified. The top interactive miRNAs including miR-29a-3p, miR-101-3p,miR-183-5p, and miR-15a-5p targeted the most hub genes. The survival chart showed an increase in mortality in patients with gastric cancer, which shows the importance of the role of these genes in the development of the disease and can be considered candidate genes in the prevention and early diagnosis of gastric cancer.

LncRNA BBOX1-AS1 targets miR-361-3p/COL1A1 axis to drive the progression of oesophageal carcinoma

BACKGROUND

Oesophageal carcinoma (EC) is one of the types of prevalent malignant cancer in the globe. Many researchers reported the vital role played by long-coding RNAs in EC. In the current research, we investigated the mechanisms of the action of lncRNA BBOX1-AS1 in EC progression.

METHODS

In EC tissues and EC cells, the expression levels of miR-361-3p along with COL1A1 and BBOX1-AS1 were detected through RT-qPCR or western blotting. MiR-361-3p interactions with BBOX1-AS1 or COL1A1 were verified through Luciferase reporter and RIP tests. Loss of function combined with caspase-3 activity, CCK-8 and Transwell assays was performed to investigate cell apoptosis, proliferation and migration, respectively. Knockdown of BBOX1-AS1 was used for evaluating BBOX1-AS1 effects on tumour development in vivo.

RESULTS

BBOX1-AS1 was remarkably elevated in EC tissues and cells. In addition, the silencing of BBOX1-AS1 attenuated the cell viability, cell migration and enhanced cell apoptosis of EC, as well as suppressed EC tumour formation in vivo. Moreover, BBOX1-AS1 was found to be a sponge of miR-361-3p, which downregulated miR-361-3p expression. MiR-361-3p inhibitor rescued the anti-tumour effect of BBOX1-AS1 knockdown on the progression of EC. Furthermore, we discovered that miR-361-3p specially bound to COL1A1 3'UTR and downregulated COL1A1 and COL1A1 reduction declined the promoting effect of silencing miR-361-3p on EC cell malignant phenotypes.

CONCLUSION

BBOX1-AS1 facilitated the EC development and malignancy via miR-361-3p/COL1A1 axis, indicating BBOX1-AS1 could be a novel therapy target for the diagnostic of EC.

COL1A2 inhibition suppresses glioblastoma cell proliferation and invasion

OBJECTIVE

An extracellular matrix such as collagen is an essential component of the tumor microenvironment. Collagen alpha-2(I) chain (COL1A2) is a chain of type I collagen whose triple helix comprises two alpha-1 chains and one alpha-2 chain. The authors' proteomics data showed that COL1A2 is significantly higher in the blood of patients with glioblastoma (GBM) compared with healthy controls. COL1A2 has many different functions in various types of cancers. However, the functions of COL1A2 in GBM are poorly understood. In this study, the authors analyzed the functions of COL1A2 and its signaling pathways in GBM.

METHODS

Surgical specimens and GBM cell lines (T98, U87, and U251) were used. The expression level of COL1A2 was examined using GBM tissues and normal brain tissues by quantitative real-time polymerase chain reaction. The clinical significance of these levels was evaluated using Kaplan-Meier analysis. Small interfering RNA (siRNA) and small hairpin RNA of COL1A2 were transfected into GBM cell lines to investigate the function of COL1A2 in vitro and in vivo. Flow cytometry was introduced to analyze the alteration of cell cycles. Western blot and immunohistochemistry were performed to analyze the underlying mechanisms.

RESULTS

The expression level of COL1A2 was upregulated in GBM compared with normal brain tissues. A higher expression of COL1A2 was correlated with poor progression-free survival and overall survival. COL1A2 inhibition significantly suppressed cell proliferation in vitro and in vivo, likely due to G1 arrest. The invasion ability was notably deteriorated by inhibiting COL1A2. Cyclin D1, cyclin-dependent kinase 1, and cyclin-dependent kinase 4, which are involved in the cell cycle, were all downregulated after blockade of COL1A2 in vitro and in vivo. Phosphoinositide 3-kinase inhibitor reduced the expression of COL1A2. Although downregulation of COL1A2 decreased the protein kinase B (Akt) phosphorylation, Akt activator can phosphorylate Akt in siRNA-treated cells. This finding suggests that Akt phosphorylation is partially dependent on COL1A2.

CONCLUSIONS

COL1A2 plays an important role in driving GBM progression. COL1A2 inhibition attenuated GBM proliferation by promoting cell cycle arrest, indicating that COL1A2 could be a promising therapeutic target for GBM treatment.

Core genes in lung adenocarcinoma identified by integrated bioinformatic analysis

This study aims to identify potential core genes of lung adenocarcinoma (LUAD). Three datasets (GSE32863, GSE43458, and GSE116959) were retrieved from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between LUAD and normal tissues were filtrated by GEO2R tool. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed via Metascape database. The protein-protein interaction (PPI) network was constructed and core genes were identified using STRING and Cytoscape. Core genes expressions and their relevant clinical characteristics were performed via Oncomine and UALCAN databases respectively. The correlation between core genes and immune infiltrates was investigated by TIMER database. Kaplan-Meier plotter was performed for survival analysis. The signal pathway network of core genes was mapped by KEGG Mapper analysis tool. In this study, ten core genes were significantly related to overall survival (OS) of LUAD patients, which can provide clues for prognosis of LUAD.

The Regulatory Network of Gastric Cancer Pathogenesis and Its Potential Therapeutic Active Ingredients of Traditional Chinese Medicine Based on Bioinformatics, Molecular Docking, and Molecular Dynamics Simulation

Objective. This study aims to investigate the functional gene network in gastric carcinogenesis by using bioinformatics; besides, the diagnostic utility of key genes and potential active ingredients of traditional Chinese medicine (TCM) for treatment in gastric cancer have been explored. Methods. The Cancer Genome Atlas and Gene Expression Omnibus databases have been applied to analyze the differentially expressed genes (DEGs) between gastric cancer and normal gastric tissues. Then, the DEGs underwent Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses using the Metascape database. The STRING database and the Cytoscape software were utilized for the protein-protein interaction network of DEGs and hub genes screening. Furthermore, survival and expression analyses of hub genes were conducted using Gene Expression Profiling Interactive Analysis and Human Protein Atlas databases. By using the Comparative Toxicogenomics Database, the hub genes interconnected with active ingredients of TCM were analyzed to provide potential information for the treatment of gastric cancer. After the molecular docking of the active ingredients of TCM to specific hub gene receptor proteins, the molecular dynamics simulation GROMACS was applied to validate the conformation of the strongest binding ability in the molecular docking. Results. A total of 291 significant DEGs were found, from which 12 hub genes were screened out. Among these hub genes, the expressions of five hub genes including COL1A1, COL5A2, MMP12, SERPINE1, and VCAN were significantly correlated with the overall survival. Furthermore, four potential therapeutic active ingredients of TCM were acquired, including quercetin, resveratrol, emodin, and schizandrin B. In addition, the molecular docking results exhibited that the active ingredients of TCM formed stable binding with the hub gene targets. SERPINE1 (3UT3)-Emodin and COL1A1 (7DV6)-Quercetin were subjected to molecular dynamics simulations as conformations of continuing research significance, and both were found to be stably bound as a result of the interaction of van der Waals potentials, electrostatic, and hydrogen bonding. Conclusion. Our findings may provide novel insights and references for the screening of biomarkers, the prognostic evaluation, and the identification of potential active ingredients of TCM for gastric cancer treatment.

Transcriptomic discovery of a theranostic signature (SERPINE1/MMP3/COL1A1/SPP1) for head and neck squamous cell carcinomas and identification of antrocinol as a candidate drug

Head and neck squamous cell carcinomas (HNSCC) are prevalent malignancies with a disappointing prognosis, necessitating the search for theranostic biomarkers for better management. Based on a meta-analysis of transcriptomic data containing ten clinical datasets of HNSCC and matched nonmalignant samples, we identified SERPINE1/MMP3/COL1A1/SPP1 as essential hub genes as the potential theranostic biomarkers. Our analysis suggests these hub genes are associated with the extracellular matrix, peptidoglycans, cell migration, wound-healing processes, complement and coagulation cascades, and the AGE-RAGE signaling pathway within the tumor microenvironment. Also, these hub genes were associated with tumor-immune infiltrating cells and immunosuppressive phenotypes of HNSCC. Further investigation of The Cancer Genome Atlas (TCGA) cohorts revealed that these hub genes were associated with staging, metastasis, and poor survival in HNSCC patients. Molecular docking simulations were performed to evaluate binding activities between the hub genes and antrocinol, a novel small-molecule derivative of an anticancer phytochemical antrocin previously discovered by our group. Antrocinol showed high affinities to MMP3 and COL1A1. Notably, antrocinol presented satisfactory drug-like and ADMET properties for therapeutic applications. These results hinted at the potential of antrocinol as an anti-HNSCC candidate via targeting MMP3 and COL1A1. In conclusion, we identified hub genes: SERPINE1/MMP3/COL1A1/SPP1 as potential diagnostic biomarkers and antrocinol as a potential new drug for HNSCC.

Identification of potential hub genes of gastric cancer

BACKGROUND

Gastric cancer (GC) is a malignant tumor originated from gastric mucosa epithelium. It is the third leading cause of cancer mortality in China. The early symptoms are not obvious. When it is discovered, it has developed to the advanced stage, and the prognosis is poor. In order to screen for potential genes for GC development, this study obtained GSE118916 and GSE109476 from the gene expression omnibus (GEO) database for bioinformatics analysis.

METHODS

First, GEO2R was used to identify differentially expressed genes (DEG) and the functional annotation of DEGs was performed by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The Search Tool for the Retrieval of Interacting Genes (STRING) tool was used to construct protein-protein interaction (PPI) network and the most important modules and hub genes were mined. Real time quantitative polymerase chain reaction assay was performed to verify the expression level of hub genes.

RESULTS

A total of 139 DEGs were identified. The functional changes of DEGs are mainly concentrated in the cytoskeleton, extracellular matrix and collagen synthesis. Eleven genes were identified as core genes. Bioinformatics analysis shows that the core genes are mainly enriched in many processes related to cell adhesion and collagen.

CONCLUSION

In summary, the DEGs and hub genes found in this study may be potential diagnostic and therapeutic targets.

A comparative analysis of differentially expressed genes in rostral and caudal regions after spinal cord injury in rats

The initial mechanical damage of a spinal cord injury (SCI) triggers a progressive secondary injury cascade, which is a complicated process integrating multiple systems and cells. It is crucial to explore the molecular and biological process alterations that occur after SCI for therapy development. The differences between the rostral and caudal regions around an SCI lesion have received little attention. Here, we analyzed the differentially expressed genes between rostral and caudal sites after injury to determine the biological processes in these two segments after SCI. We identified a set of differentially expressed genes, including Col3a1, Col1a1, Dcn, Fn1, Kcnk3, and Nrg1, between rostral and caudal regions at different time points following SCI. Functional enrichment analysis indicated that these genes were involved in response to mechanical stimulus, blood vessel development, and brain development. We then chose Col3a1, Col1a1, Dcn, Fn1, Kcnk3, and Nrg1 for quantitative real-time PCR and Fn1 for immunostaining validation. Our results indicate alterations in different biological events enriched in the rostral and caudal lesion areas, providing new insights into the pathology of SCI.

RhoBTB3 Regulates Proliferation and Invasion of Breast Cancer Cells via Col1a1

Breast cancer is the leading cause of cancer-related death in women worldwide, despite medical and technological advancements. The RhoBTB family consists of three isoforms: RhoBTB1, RhoBTB2, and RhoBTB3. RhoBTB1 and RhoBTB2 have been proposed as tumor suppressors in breast cancer. However, the roles of RhoBTB3 proteins are unknown in breast cancer. Bioinformatics analysis, including Oncomine, cBioportal, was used to evaluate the potential functions and prognostic values of RhoBTB3 and Col1a1 in breast cancer. qRT-PCR analysis and immunoblotting assay were performed to investigate relevant expression. Functional experiments including proliferation assay, invasion assay, and flow cytometry assay were conducted to determine the role of RhoBTB3 and Col1a1 in breast cancer cells. RhoBTB3 mRNA levels were significantly up-regulated in breast cancer tissues as compared to in adjacent normal tissues. Moreover, RhoBTB3 expression was found to be associated with Col1a1 expression. Decreasing RhoBTB3 expression may lead to decreases in the proliferative and invasive properties of breast cancer cells. Further, Col1a1 knockdown in breast cancer cells limited the proliferative and invasive ability of cancer cells. Knockdown of RhoBTB3 may exert inhibit the proliferation, migration, and metastasis of breast cancer cells by repressing the expression of Col1a1, providing a novel therapeutic strategy for treating breast cancer.

Analysis of gene expression profile of peripheral blood in alveolar and cystic echinococcosis

RNA-sequencing (RNA-seq) is a versatile, high-throughput technology that is being widely employed for screening differentially expressed genes (DEGs) in various diseases. Echinococcosis, a globally distributed zoonosis, has been reported to impose a heavy disease burden in pastoral areas of China. Herein we aimed to explore the molecular mechanisms underlying echinococcosis. In this study, peripheral blood samples were collected from six patients with alveolar echinococcosis (AE), six patients with cystic echinococcosis (CE), and six healthy controls. RNA-Seq (mRNA) was performed to detect gene transcript and expression levels, and DEGs were subjected to bioinformatic analyses. In comparison with healthy controls, 492 DEGs (270 upregulated, 222 downregulated) were found in the AE group and 424 DEGs (170 upregulated, 254 downregulated) were found in the CE group (|log₂ (fold change)| > 1 and P < 0.05). Further, 60 genes were upregulated and 39 were downregulated in both the AE and CE groups. Gene ontology enrichment analysis indicated that DEGs were mainly involved in molecular functions, including extracellular space, extracellular region, organ and system development, and anatomical structure development. Protein–protein interaction (PPI) networks were constructed to depict the complex relationship between DEGs and interacting proteins.

COL1A1: A novel oncogenic gene and therapeutic target in malignancies

Collagen type I alpha 1 (COL1A1), a member of the collagen family, is involved in epithelial-mesenchymal transition, which is closely linked to malignant tumorigenesis. COL1A1 is highly expressed in various cancers and regulates various cellular processes, including cell proliferation, metastasis, apoptosis, and cisplatin resistance. COL1A1 is also associated with cancer progression and prognosis; elevated COL1A1 expression is associated with poor prognosis in cancer patients. However, the main role of COL1A as a cancer-promoting factor in specific tumors has not been reported. Additionally, the protein levels and mechanisms of action of this protein differ among tumor types. This review discusses current research progress concerning COL1A1 in different tumor types, and then summarizes its contributions to cancer progression, thus providing a basis for follow-up research and potential targets for cancer treatment.

Aptamer-conjugated nanoliposomes containing COL1A1 siRNA sensitize CRC cells to conventional chemotherapeutic drugs

COL1A1 is an important extracellular matrix component that is associated with poor prognosis in cancers. In this study, As1411 aptamer-conjugated liposomes were used for targeted siRNA delivery against the COL1A1 gene in colorectal cancer (CRC) cells. Cationic liposomes were synthesized and siRNA loading and conjugation of aptamer were confirmed by gel shift assay and spectrophotometry method. Release of siRNA from liposomes was assessed using dialysis method. Binding and uptake of aptamer-conjugated liposomes to and into cancer cells was assessed by fluorescence microscopy and flowcytometry. Gene expression was evaluated using qRT-PCR. Cell viability, chemosensitivity and apoptosis were determined by MTT assay and Annexin/PI kit. Cellular studies showed that liposomal transfer of COL1A1 siRNA into HCT116 and HEK293 cells significantly reduced the expression level of corresponding gen and cell viability, and significantly increased the sensitivity to chemotherapy drugs while free siRNA had no such effects. Aptamer conjugation was associated with increased cellular effects in HCT116 cells, but not in HEK293 cells. Our study revealed that delivery of COL1A1 siRNA via AS1411-targeted liposomes is a promising therapeutic approach to overcome treatment resistance in CRC.

Prune homolog 2 with BCH domain (PRUNE2) gene expression is associated with feed efficiency-related traits in Nelore steers

Animal feeding is a critical factor in increasing producer profitability. Improving feed efficiency can help reduce feeding costs and reduce the environmental impact of beef production. Candidate genes previously identified for this trait in differential gene expression studies (e.g., case-control studies) have not examined continuous gene-phenotype variation, which is a limitation. The aim of this study was to investigate the association between the expression of five candidate genes in the liver, measured by quantitative real-time PCR and feed-related traits. We adopted a linear mixed model to associate liver gene expression from 52 Nelore steers with the following production traits: average daily gain (ADG), body weight (BW), dry matter intake (DMI), feed conversion ratio (FCR), feed efficiency (FE), Kleiber index (KI), metabolic body weight (MBW), residual feed intake (RFI), and relative growth ratio (RGR). The total expression of the prune homolog 2 (PRUNE2) gene was significantly associated with DMI, FCR, FE, and RFI (P < 0.05). Furthermore, we have identified a new transcript of PRUNE2 (TCONS_00027692, GenBank MZ041267) that was inversely correlated with FCR and FE (P < 0.05), in contrast to the originally identified PRUNE2 transcript. The cytochrome P450 subfamily 2B (CYP2B6), early growth response protein 1 (EGR1), collagen type I alpha 1 chain (COL1A1), and connective tissue growth factor (CTGF) genes were not associated with any feed efficiency-related traits (P > 0.05). The findings reported herein suggest that PRUNE2 expression levels affects feed efficiency-related traits variation in Nelore steers.

Identification of COL1A1 associated with immune infiltration in brain lower grade glioma

Brain low grade gliomas (LGG) often give serious clinical symptoms due to the invasion towards nervous system, affecting the life quality of patients. Collagen type I alpha 1(COL1A1) is the main component of type I collagen. Although there are many reports about abnormal expression of COL1A1 in various tumors, specific role and clinical significance of COL1A1 in LGG have not yet been elucidated. In this work, Tumor Immune Estimation Resource database was used for detecting the expression level of COL1A1 in cancer and normal tissues, and aimed to explore the relationship between COL1A1 and tumor immune infiltration. We applied Kaplan-Meier to analyze the role of COL1A1 in clinical prognosis. Univariate survival rate and multivariate Cox analysis were used to compare clinical characteristics and survival rate. The relativity between the expression of COL1A1 and the tumor microenvironment was evaluated using ESTIMATE algorithm. Finally, the relationship between expression level of COL1A1 and gene marker sets of immune cell infiltration was investigated via TIMER. According to TCGA, COL1A1 overexpression was correlated with overall survival (OS), progression free interval (PFI) and disease specific survival (DSS) of multiple tumors, especially in LGG. Multivariate analysis showed that COL1A1 expression was an independent prognostic factor for LGG. The expression of COL1A1 was positively correlated with the infiltration of CD4 + T and CD8 + T cells, neutrophils, macrophages and dendritic cells in LGG. In addition, there was a strong correlation between expression of COL1A1 and different immune marker sets in LGG. The results suggest that COL1A1 is related with tumor immune infiltration of LGG.

Comprehensive bioinformatic analysis reveals a cancer-associated fibroblast gene signature as a poor prognostic factor and potential therapeutic target in gastric cancer

BACKGROUND

Gastric cancer is one of the deadliest cancers, currently available therapies have limited success. Cancer-associated fibroblasts (CAFs) are pivotal cells in the stroma of gastric tumors posing a great risk for progression and chemoresistance. The poor prognostic signature for CAFs is not clear in gastric cancer, and drugs that target CAFs are lacking in the clinic. In this study, we aim to identify a poor prognostic gene signature for CAFs, targeting which may increase the therapeutic success in gastric cancer.

METHODS

We analyzed four GEO datasets with a network-based approach and validated key CAF markers in The Cancer Genome Atlas (TCGA) and The Asian Cancer Research Group (ACRG) cohorts. We implemented stepwise multivariate Cox regression guided by a pan-cancer analysis in TCGA to identify a poor prognostic gene signature for CAF infiltration in gastric cancer. Lastly, we conducted a database search for drugs targeting the signature genes.

RESULTS

Our study revealed the COL1A1, COL1A2, COL3A1, COL5A1, FN1, and SPARC as the key CAF markers in gastric cancer. Analysis of the TCGA and ACRG cohorts validated their upregulation and poor prognostic significance. The stepwise multivariate Cox regression elucidated COL1A1 and COL5A1, together with ITGA4, Emilin1, and TSPAN9 as poor prognostic signature genes for CAF infiltration. The search on drug databases revealed collagenase clostridium histolyticum, ocriplasmin, halofuginone, natalizumab, firategrast, and BIO-1211 as the potential drugs for further investigation.

CONCLUSIONS

Our study demonstrated the central role of extracellular matrix components secreted and remodeled by CAFs in gastric cancer. The gene signature we identified in this study carries high potential as a predictive tool for poor prognosis in gastric cancer patients. Elucidating the mechanisms by which the signature genes contribute to poor patient outcomes can lead to the discovery of more potent molecular-targeted agents and increase the therapeutic success in gastric cancer.

The Analysis of Potential Diagnostic and Therapeutic Targets for the Occurrence and Development of Gastric Cancer Based on Bioinformatics

Objective

Gastric cancer is among the most common malignant tumors of the digestive system. This study explored the molecular mechanisms and potential therapeutic targets for gastric cancer occurrence and progression using bioinformatics.

Methods

The gastric cancer microarray dataset was downloaded from the Gene Expression Omnibus (GEO) database. The R package was used for data mining and screening differentially expressed genes (DEGs). Gene Ontology (GO) analysis and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analysis were performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). Based on the protein-protein interaction (PPI) network analysis, core targets and core subsets were screened. Then, the relationship between the expression level of the core genes and the prognosis of gastric cancer patients was analyzed using the Gene Expression Profiling Interactive Analysis (GEPIA) database.

Results

Using the GSE19826 and GSE54129 datasets, a total of 550 DEGs were identified, including 248 upregulated and 302 downregulated genes. GO and KEGG analyses showed that the upregulated DEGs were mainly enriched in the extracellular matrix (ECM) organization of the biological process (BP), the collagen-containing ECM of cellular component (CC), and the ECM structural constituent of molecular function (MF). DEGs were also enriched in human papillomavirus infections, the focal adhesion pathway, PI3K-Akt signaling pathway, and among others. The downregulated DEGs were mainly enriched in digestion, basal part of the cell, and aldo-keto reductase (NADP) activity. And the above pathways were enriched primarily in the metabolism of xenobiotics by cytochrome P450, drug metabolism-cytochrome P450, and retinol metabolism. Five core genes, including COL1A2, COL3A1, BGN, FN1, and VCAN, were significantly highly expressed in gastric cancer patients and were associated with poor prognosis.

Conclusion

This study identified new potential molecular targets closely related to gastric cancer occurrence and development via mining public data using bioinformatics analysis methods.

Carboxypeptidase N2 as a Novel Diagnostic and Prognostic Biomarker for Lung Adenocarcinoma

Carboxypeptidase N2 (CPN2) is a plasma metallo-protease that cleaves basic amino acids from the C-terminal of peptides and proteins. Emerging evidence showed that carboxypeptidases perform many diverse functions in the body and play key roles in tumorigenesis. However, the clinical significance and biological functions of CPN2 in lung adenocarcinoma remain unclear. Our study aimed to explore the potential role and functions of CPN2 in lung adenocarcinoma. The results showed that the transcription level of CPN2 was significantly increased in the tumor tissues of lung adenocarcinoma patients compared to the adjacent normal tissues in The Cancer Genome Atlas cohort (P < 0.05). The survival plots showed that the overall survival of patients with a high expression of CPN2 was significantly lower than that of patients with a low expression of CPN2, both in the Kaplan-Meier database and the clinical sample cohort (P < 0.05). The tissue microarray analysis found that CPN2 protein expression was significantly positively correlated with node status and tumor stage as well as tumor malignancy (P < 0.05). Further univariate and multivariate Cox regression analyses showed that CPN2 may act as an independent prognostic factor in patients with lung adenocarcinoma (P < 0.05). In addition, the analysis of co-expression genes from LinkedOmics showed that CPN2 was positively associated with many genes of fibrillar collagen family members and the PI3K-Akt pathway. The gene set enrichment analysis showed that a higher expression of CPN2 may participate in mTOR, TGF-BETA, NOTCH, TOLL-like-receptor, WNT, and MAPK signaling pathway in lung adenocarcinoma. Notably, the knockdown of CPN2 significantly inhibited the ability of cell proliferation, clone formation, invasion, and migration. Our findings suggested that the upregulation of CPN2 is associated with a worse clinical outcome in lung adenocarcinoma and cancer-related pathways, which laid the foundation for further research on CPN2 during carcinogenesis.

Identification of a Cancer Stem Cells Signature of Head and Neck Squamous Cell Carcinoma

Background: Head and neck squamous cell carcinoma (HNSCC) ranks as the sixth most widespread and deadly cancer. In recent times, it has been determined that undifferentiated cell populations with stem cell-like properties in HNSCC are major factors influencing recurrence and progression.

Method: In this study, we determine key genes related to stemness by merging WGCNA with HNSCC mRNAsi based on the online database.

Results: We first download the mRNA expression-based stemness index (mRNAsi) data and contrast the expression levels of mRNAsi in cancers and control samples; we found significantly elevated mRNAsi expressions in HNSCC tissues (p = 0.002). Moreover, the brown module showed a relatively high negative correlation with mRNAsi (cor = -0.8). Thus, we selected the brown module as the interesting module and used it for following analysis. We screened 20 key genes (PDGFRB, PLPP4, CALU, ADAMTS14, COL5A3, KCNE4, LOXL1, CLEC11A, PODN,BGN, AEBP1, COL1A2, LAMA4, LOXL2, LRRC15, THY1, SPON2, COL1A1, NID2, and AC134312.5) including and as to decide the neighbor genes biological interaction network of these 20 stemness-related genes in HNSCC. The top 10 frequent alterations were PIK3CA, FGF3, FGF19, FGF4, DVL3, P3H2, GNB4, COL22A1, COL14A1, and PLOD2.

Conclusion: This study showed the critical role of stemness-related genes in HNSCC. However, more related studies are needed to confirm these results.

Circular RNAs With Efficacy in Preclinical In Vitro and In Vivo Models of Esophageal Squamous Cell Carcinoma

Esophageal cancer is associated with a dismal prognosis. The armamentarium of approved drugs is focused on chemotherapy with modest therapeutic benefit. Recently, checkpoint inhibitory monoclonal antibody Pembrolizumab was approved. In order to identify new targets and modalities for the treatment of esophagus squamous cell carcinoma (ESCC) we searched the literature for circRNAs involved in the pathogenesis of ESCC. We identified two down-regulated and 17 up-regulated circRNAs as well as a synthetic circRNA with efficacy in preclinical in vivo systems. Down-regulated circRNAs sponge microRNAs directed against tumor suppressor genes. Up-regulated circRNAs sponge microRNAs directed against mRNAs, which encode proteins with pro-tumoral functions. We discuss issues such as reconstitution of down-regulated circRNAs and inhibition of up-regulated circRNAs with short interfering RNA (siRNA)- related entities. Also, we address druggability issues of the identified targets.

Identification of Potential Diagnostic and Prognostic Biomarkers for Gastric Cancer Based on Bioinformatic Analysis

Background: Gastric cancer (GC) is one of the most prevalent cancers all over the world. The molecular mechanisms of GC remain unclear and not well understood. GC cases are majorly diagnosed at the late stage, resulting in a poor prognosis. Advances in molecular biology techniques allow us to get a better understanding of precise molecular mechanisms and enable us to identify the key genes in the carcinogenesis and progression of GC.

Methods: The present study used datasets from the GEO database to screen differentially expressed genes (DEGs) between GC and normal gastric tissues. GO and KEGG enrichments were utilized to analyze the function of DEGs. The STRING database and Cytoscape software were applied to generate protein–protein network and find hub genes. The expression levels of hub genes were evaluated using data from the TCGA database. Survival analysis was conducted to evaluate the prognostic value of hub genes. The GEPIA database was involved to correlate key gene expressions with the pathological stage. Also, ROC curves were constructed to assess the diagnostic value of key genes.

Results: A total of 607 DEGs were identified using three GEO datasets. GO analysis showed that the DEGs were mainly enriched in extracellular structure and matrix organization, collagen fibril organization, extracellular matrix (ECM), and integrin binding. KEGG enrichment was mainly enriched in protein digestion and absorption, ECM-receptor interaction, and focal adhesion. Fifteen genes were identified as hub genes, one of which was excluded for no significant expression between tumor and normal tissues. COL1A1, COL5A2, P4HA3, and SPARC showed high values in prognosis and diagnosis of GC.

Conclusion: We suggest COL1A1, COL5A2, P4HA3, and SPARC as biomarkers for the diagnosis and prognosis of GC.

Collagen XI Alpha 1 (COL11A1) Expression in the Tumor Microenvironment Drives Neuroblastoma Dissemination

BACKGROUND

Neuroblastoma (NB) is among the most common cancers in children. A highly aggressive form of cancer, NB relies on cells in the microenvironment for dissemination particularly cancer associated fibroblast (CAFs). CAFs synthesise the extracellular matrix to create a scaffold for tumor growth thus enabling the carcinogenesis of NB, Collagen, an abundant scaffold protein produced by CAFs, has been implicated in the creation of an optimal tumor microenvironment, however, the expression profile of collagen within NB is not yet known.

METHODS

We characterised collagen expression within the tumor-stroma boundary by microarray and confirmed by qRT-PCR and immunohistochemistry.

RESULTS

The collagen marker, COL11A1, was also upregulated in NB CD45+ cells and SMA+ CAFs. Furthermore, SMA+ CAFs led to neuroblastoma cell invasion in an in vitro co-culture system which was subsequently attenuated by gene silencing COL11A1. Immunohistochemical staining of clinical tumor samples revealed that high COL11A1 expression in the stroma adjacent to tumour site, significantly associated with advanced cancer stages, age ≥18 months, undifferentiated tumor status, relapse and poor overall survival.

CONCLUSION

Collectively, these results suggest that a COL11A1 signature in the NB microenvironment could represent a novel target for therapeutic intervention.

Targeting Type I Collagen for Cancer Treatment

Collagen is the most abundant protein in animals. Interactions between tumor cells and collagen influence every step of tumor development. Type I collagen is the main fibrillar collagen in the extracellular matrix and is frequently up-regulated during tumorigenesis. The binding of type I collagen to its receptors on tumor cells promotes tumor cell proliferation, epithelial-mesenchymal transition, and metastasis. Type I collagen also regulates the efficacy of tumor therapies, such as chemotherapy, radiotherapy, and immunotherapy. Furthermore, type I collagen fragments are diagnostic markers of metastatic tumors and have prognostic value. Inhibition of type I collagen synthesis has been reported to have anti-tumor effects in animal models. However, collagen has also been shown to possess anti-tumor activity. Therefore, the roles that type I collagen plays in tumor biology are complex and tumor type-dependent. In this review, we discuss the expression and regulation of synthesis of type I collagen, as well as the role up-regulated type I collagen plays in various stages of cancer progression. We also discuss the role of collagen in tumor therapy. Finally, we highlight several recent approaches targeting type I collagen for cancer treatment. This article is protected by copyright. All rights reserved.

The Circular RNA CircCOL1A1 Functions as a miR-149-5p Sponge to Regulate the Formation of Superior-Quality Brush Hair via the CMTM3/AR Axis

Superior-quality brush hair, also called Type III hair, can be obtained only from the cervical spine region of skin tissues of Yangtze River Delta white goats. The formation of superior-quality brush hair is controlled by a series of critical genes and related signaling pathways. Circular RNAs (circRNAs) are ubiquitous endogenous noncoding RNAs that regulate many biological and physiological processes in mammals. However, little is known about the potential regulatory role of circRNAs in superior-quality brush hair formation. Here, we analyzed circRNA sequencing data from cervical spine region skin tissues of normal-quality brush hair goats and superior-quality brush hair goats and then selected and identified the differentially expressed circRNA circCOL1A1. To investigate the regulatory role and mechanism of action of circCOL1A1, goat hair follicle stem cells (gHFSCs) were cultured and treated with a circCOL1A1 overexpression plasmid and small-interfering RNAs (siRNAs). Functional assays showed that circCOL1A1 knockdown promoted the proliferation and differentiation of gHFSCs cultured in vitro but inhibited stem cell apoptosis, whereas overexpression of circCOL1A1 suppressed stem cell proliferation and differentiation and induced apoptosis. Bioinformatics analysis combined with dual-luciferase reporter assays and RNA binding protein immunoprecipitation (RIP) verified that, mechanistically, circCOL1A1 could bind miR-149-5p directly and then relieve its inhibitory effect on CMTM3 to further control the CMTM3/AR axis. Collectively, our results reveal a novel regulatory pathway for the formation of superior-quality brush hair and indicate that circCOL1A1 plays a role in gHFSC growth and superior-quality brush hair formation by targeting the miR-149-5p/CMTM3/AR axis.

Identification of key genes associated with papillary thyroid microcarcinoma characteristics by integrating transcriptome sequencing and weighted gene co-expression network analysis

OBJECTIVE

Papillary thyroid microcarcinoma (PTMC) is the most prevalent histological type of thyroid carcinoma. Despite the overall favorable prognosis of PTMC, some cases exhibit aggressive phenotypes. The identification of robust biomarkers may improve early PTMC diagnosis. In this study, we integrated high-throughput transcriptome sequencing, bioinformatic analyses and experimental validation to identify key genes associated with the malignant characteristics of PTMC.

METHODS

Total RNA was extracted from 24 PTMC samples and 7 non-malignant thyroid tissue samples, followed by RNA sequencing. The differentially expressed genes (DEGs) were identified and used to construct co-expression networks by weighted gene co-expression network analysis (WGCNA). Gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed, and protein-protein interaction networks were constructed. Key modules and hub genes showing a strong correlation with the malignant characteristics of PTMC were identified and validated.

RESULTS

The green-yellow and turquoise modules generated by WGCNA were strongly associated with the malignant characteristics of PTMC. Functional enrichment analysis revealed that genes in the green-yellow module participated in cell motility and metabolism, whereas those in the turquoise module participated in several oncogenic biological processes. Nine real hub genes (FHL1, NDRG2, NEXN, SYNM, COL1A1, FN1, LAMC2, POSTN, and TGFBI) were identified and validated at the transcriptional and translational levels. Our preliminary results indicated their diagnostic potentials in PTMC.

CONCLUSIONS

In this study, we identified key co-expression modules and nine malignancy-related genes with potential diagnostic value in PTMC.

Identification of Potential Prognostic Biomarkers Associated With Macrophage M2 Infiltration in Gastric Cancer

Gastric cancer is a common cancer afflicting people worldwide. Although incremental progress has been achieved in gastric cancer research, the molecular mechanisms underlying remain unclear. In this study, we conducted bioinformatics methods to identify prognostic marker genes associated with gastric cancer progression. Three hundred and twenty-seven overlapping DEGs were identified from three GEO microarray datasets. Functional enrichment analysis revealed that these DEGs are involved in extracellular matrix organization, tissue development, extracellular matrix–receptor interaction, ECM-receptor interaction, PI3K-Akt signaling pathway, focal adhesion, and protein digestion and absorption. A protein–protein interaction network (PPI) was constructed for the DEGs in which 25 hub genes were obtained. Furthermore, the turquoise module was identified to be significantly positively coexpressed with macrophage M2 infiltration by weighted gene coexpression network analysis (WGCNA). Hub genes of COL1A1, COL4A1, COL12A1, and PDGFRB were overlapped in both PPI hub gene list and the turquoise module with significant association with the prognosis in gastric cancer. Moreover, functional analysis demonstrated that these hub genes play pivotal roles in cancer cell proliferation and invasion. The investigation of the gene markers can help deepen our understanding of the molecular mechanisms of gastric cancer. In addition, these genes may serve as potential prognostic biomarkers for gastric cancer diagnosis.

COL1A1 Gene Expression in Hepatitis B Virus (HBV) Related Hepatocellular Carcinoma (HCC) Egyptian's Patients

Introduction:

Collagens are the most abundant proteins in the human body, accounting for one-third of total proteins. Over the last few years, accumulated evidence have indicated that some collagens are differentially expressed in cancer. The aim of the study was to assess COL1A1 gene expression as a novel marker for the progression of hepatitis B cirrhosis into hepatocellular carcinoma.

Methods:

This cohort study included 348 subjects and was conducted between May 2018 and June 2019. Subjects were divided into 4 groups: group1 included HBV positive hepatocellular carcinoma patients “HCC” (n= 87), group II included HBV positive patients with liver cirrhosis “LC” (n = 87), group III included chronic hepatitis B patients with neither HCC nor cirrhosis “ C-HBV” (n = 87) and group IV consisted of healthy volunteers as controls (n = 87). Fasting venous blood samples (10 ml) were collected from each participant in this study and were used for assessment of aspartate aminotransferase (AST), alanine aminotransferase (ALT), total bilirubin, albumin and alfa-fetoprotein (AFP). Another portion of blood was collected in 2 vacutainer tubes containing EDTA, one for Complete blood count and the other for gene expression of COL1A1.

Results:

The gene expression of collagen was 6.9 ± 8.8 in group 1 (HBV positive hepatocellular carcinoma patients) and this was a significant increase in comparison with the other groups. In group 2 (HBV positive patients with liver cirrhosis), the gene expression (collagen) was 3.7±1.5 and it was significantly increased when compared with group 4 (healthy volunteers).

Conclusion:

COL1A1 gene expression can be used as an indicator of the progression of hepatitis B cirrhosis into hepatocellular carcinoma.

Aspects of the Epigenetic Regulation of EMT Related to Cancer Metastasis

Epithelial to mesenchymal transition (EMT) occurs during the pathological process associated with tumor progression and is considered to influence and promote the metastatic cascade. Characterized by loss of cell adhesion and apex base polarity, EMT enhances cell motility and metastasis. The key markers of the epithelial to mesenchymal transition are proteins characteristic of the epithelial phenotype, e.g., E-cadherin, cytokeratins, occludin, or desmoplakin, the concentration and activity of which are reduced during this process. On the other hand, as a result of acquiring the characteristics of mesenchymal cells, an increased amount of N-cadherin, vimentin, fibronectin, or vitronectin is observed. Importantly, epithelial cells undergo partial EMT where some of the cells show both epithelial and mesenchymal characteristics. The significant influence of epigenetic regulatory mechanisms is observed in the gene expression involved in EMT. Among the epigenetic modifications accompanying incorrect genetic reprogramming in cancer are changes in the level of DNA methylation within the CpG islands and posttranslational covalent changes of histone proteins. All observed modifications, which are stable but reversible changes, affect the level of gene expression leading to the development and progression of the disease, and consequently affect the uncontrolled growth of the population of cancer cells.

MRPS31 loss is a key driver of mitochondrial deregulation and hepatocellular carcinoma aggressiveness

Deregulated mitochondrial energetics is a metabolic hallmark of cancer cells. However, the causative mechanism of the bioenergetic deregulation is not clear. In this study, we show that somatic copy number alteration (SCNA) of mitoribosomal protein (MRP) genes is a key mechanism of bioenergetic deregulation in hepatocellular carcinoma (HCC). Association analysis between the genomic and transcriptomic profiles of 82 MRPs using The Cancer Genome Atlas-Liver HCC database identified eight key SCNA-dependent MRPs: MRPS31, MRPL10, MRPL21, MRPL15, MRPL13, MRPL55, and DAP3. MRPS31 was the only downregulated MRP harboring a DNA copy number (DCN) loss. MRPS31 loss was associated specifically with the DCN losses of many genes on chromosome 13q. Survival analysis revealed a unique dependency of HCC on the MRPS31 deficiency, showing poor clinical outcome. Subclass prediction analysis using several public classifiers indicated that MRPS31 loss is linked to aggressive HCC phenotypes. By employing hepatoma cell lines with SCNA-dependent MRPS31 expression (JHH5, HepG2, Hep3B, and SNU449), we demonstrated that MRPS31 deficiency is the key mechanism, disturbing the whole mitoribosome assembly. MRPS31 suppression enhanced hepatoma cell invasiveness by augmenting MMP7 and COL1A1 expression. Unlike the action of MMP7 on extracellular matrix destruction, COL1A1 modulated invasiveness via the ZEB1-mediated epithelial-to-mesenchymal transition. Finally, MRPS31 expression further stratified the high COL1A1/DDR1-expressing HCC groups into high and low overall survival, indicating that MRPS31 loss is a promising prognostic marker. SIGNIFICANCE: Our results provide new mechanistic insight for mitochondrial deregulation in HCC and present MRPS31 as a novel biomarker of HCC malignancy.

Bioinformatic and experimental analyses of key biomarkers in pancreatic cancer

The present study aimed to screen the key genes in pancreatic cancer and to explore the pathogenesis of pancreatic cancer. A total of three expression profiling datasets (GSE28735, GSE16515 and GSE15471) associated with pancreatic cancer were retrieved from the public gene chip database. The differentially expressed genes (DEGs) were screened by GEO2R and subjected to Gene Ontology (GO) and signaling pathway enrichment analysis. Furthermore, a protein interaction network was constructed. The GEPIA online database was used to screen for genes that affect the prognosis of pancreatic cancer. Finally, cell functional experiments were performed on the selected key genes. A total of 72 DEGs were identified, including 52 upregulated and 20 downregulated genes. Enrichment analysis revealed roles of the DEGs in endodermal cell differentiation, cell adhesion, extracellular matrix-receptor interaction and PI3K-Akt signaling pathway. In total, 10 key nodal genes were identified, including integrin subunit α 2 (ITGA2), ITGB6 and collagen α 1 chain 1. Through survival analysis, two genes with an impact on the prognosis of pancreatic cancer were identified, namely ITGA2 and ITGB6. Silencing of ITGB6 in a pancreatic cancer cell line significantly suppressed cell proliferation and induced cell cycle arrest at G2/M phase. The identified key genes and signaling pathways may help to deepen the understanding of the molecular mechanisms involved in pancreatic cancer and provide a theoretical basis to develop novel therapies.

A construction and comprehensive analysis of ceRNA networks and infiltrating immune cells in papillary renal cell carcinoma

Background

As the second most common malignancy in adults, papillary renal cell carcinoma (PRCC) has shown an increasing trend in both incidence and mortality. Effective treatment for advanced metastatic PRCC is still lacking. In this study, we aimed to establish competitive endogenous RNA (ceRNA) networks related to PRCC tumorigenesis, and analyze the specific role of differentially expressed ceRNA components and infiltrating immune cells in tumorigenesis.

Methods

CeRNA networks were established to identify the key ceRNAs related to PRCC tumorigenesis based on the 318 samples from The Cancer Genome Atlas database (TCGA), including 285 PRCC and 33 normal control samples. The R package, “CIBERSORT,” was used to evaluate the infiltration of 22 types of immune cells. Then we identified the significant ceRNAs and immune cells, based on which two nomograms were obtained for predicting the prognosis in PRCC patients. Finally, we investigated the co‐expression of PRCC‐specific immune cells and core ceRNAs via Pearson correlation test.

Results

COL1A1, H19, ITPKB, LDLR, TCF4, and WNK3 were identified as hub genes in ceRNA networks. Four prognostic‐related tumor‐infiltrating immune cells, including T cells CD4 memory resting, Macrophages M1, and Macrophages M2 were revealed. Pearson correlation test indicated that Macrophage M1 was negatively related with COL1A1 (p < 0.01) and LDLR (p < 0.01), while Macrophage M2 was positively related with COL1A1 (p < 0.01), TCF4 (p < 0.01), and H19 (p = 0.032). Two nomograms were conducted with favorable accuracies (area under curve of 1‐year survival: 0.935 and 0.877; 3‐year survival: 0.849 and 0.841; and 5‐year survival: 0.818 and 0.775, respectively).

Conclusion

The study constructed two nomograms suited for PRCC prognosis predicting. Moreover, we concluded that H19‐miR‐29c‐3p‐COL1A1 axis might promote the polarization of M2 macrophages and inhibit M1 macrophage activation through Wnt signaling pathway, collaborating to promote PRCC tumorigenesis and lead to poor overall survival of PRCC patients.