Upregulation of the adipokine genes ADIPOR1 and SPP1 is related to poor survival outcomes in colorectal cancer

Targeting adipocyte ESRRA promotes osteogenesis and vascular formation in adipocyte-rich bone marrow

Excessive bone marrow adipocytes (BMAds) accumulation often occurs under diverse pathophysiological conditions associated with bone deterioration. Estrogen-related receptor α (ESRRA) is a key regulator responding to metabolic stress. Here, we show that adipocyte-specific ESRRA deficiency preserves osteogenesis and vascular formation in adipocyte-rich bone marrow upon estrogen deficiency or obesity. Mechanistically, adipocyte ESRRA interferes with E2/ESR1 signaling resulting in transcriptional repression of secreted phosphoprotein 1 (Spp1); yet positively modulates leptin expression by binding to its promoter. ESRRA abrogation results in enhanced SPP1 and decreased leptin secretion from both visceral adipocytes and BMAds, concertedly dictating bone marrow stromal stem cell fate commitment and restoring type H vessel formation, constituting a feed-forward loop for bone formation. Pharmacological inhibition of ESRRA protects obese mice against bone loss and high marrow adiposity. Thus, our findings highlight a therapeutic approach via targeting adipocyte ESRRA to preserve bone formation especially in detrimental adipocyte-rich bone milieu.

SPP1 represents a therapeutic target that promotes the progression of oesophageal squamous cell carcinoma by driving M2 macrophage infiltration

BACKGROUND

Tumour-associated macrophages (TAMs) are an important component of the tumour microenvironment (TME). However, the crosstalk between oesophageal squamous cell carcinoma (ESCC) cells and TAMs remains largely unexplored.

METHODS

Clinical samples and the TCGA database were used to evaluate the relevance of SPP1 and TAM infiltration in ESCC. Mouse models were constructed to investigate the roles of macrophages educated by SPP1 in ESCC. Macrophage phenotypes were determined using qRT‒PCR and immunohistochemical staining. RNA sequencing was performed to elucidate the mechanism.

RESULTS

Increasing expression of SPP1 correlated with M2-like TAM accumulation in ESCC, and they both predicted poor prognosis in the ESCC cohort. Knockdown of SPP1 significantly inhibited the infiltration of M2 TAMs in xenograft tumours. In vivo mouse model experiments showed that SPP1-mediated education of macrophages plays an essential role in the progression of ESCC. Mechanistically, SPP1 recruited macrophages and promoted M2 polarisation via CD44/PI3K/AKT signalling activation and then induced VEGFA and IL6 secretion to sustain ESCC progression. Finally, blockade of SPP1 with RNA aptamer significantly inhibited tumour growth and M2 TAM infiltration in xenograft mouse models.

CONCLUSIONS

This study highlights SPP1-mediated crosstalk between ESCC cells and TAMs in ESCC. SPP1 could serve as a potential target in ESCC therapy.

Beyond Body Size: Adiponectin as a Key Player in Obesity-Driven Cancers

Obesity, a complex and multifactorial disease influenced by genetic, environmental, and psychological factors, has reached epidemic proportions globally, posing a significant health challenge. In addition to its established association with cardiovascular disease and type II diabetes, obesity has been implicated as a risk factor for various cancers. However, the precise biological mechanisms linking obesity and cancer remain largely understood. Adipose tissue, an active endocrine organ, produces numerous hormones and bioactive molecules known as adipokines, which play a crucial role in metabolism, immune responses, and systemic inflammation. Notably, adiponectin (APN), the principal adipocyte secretory protein, exhibits reduced expression levels in obesity. In this scoping review, we explore and discuss the role of APN in influencing cancer in common malignancies, including lung, breast, colorectal, prostate, gastric, and endometrial cancers. Our review aims to emphasize the critical significance of investigating this field, as it holds great potential for the development of innovative treatment strategies that specifically target obesity-related malignancies. Furthermore, the implementation of more rigorous and comprehensive prevention and treatment policies for obesity is imperative in order to effectively mitigate the risk of associated diseases, such as cancer.

The inhibitory effect of Gremlin-2 on adipogenesis suppresses breast cancer cell growth and metastasis

BACKGROUND

Gremlin-1 (GREM1) and Gremlin-2 (GREM2) are bone morphogenetic protein antagonists that play important roles in organogenesis, tissue differentiation, and tissue homeostasis. Although GREM1 has been reported to be involved in promoting various cancers, little has been reported about effects of GREM2 on cancer. Recently, it has been reported that GREM2 can inhibit adipogenesis in adipose-derived stromal/stem cells. However, as an inhibitor of adipogenesis, the role of GREM2 in cancer progression is not well understood yet.

METHODS

Pre-adipocyte 3T3-L1 cells overexpressing mock or Grem2 were established using a lentiviral transduction system and differentiated into adipocytes-mock and adipocytes-Grem2, respectively. To investigate the effect of adipocyte-Grem2 on breast cancer cells, we analyzed the proliferative and invasion abilities of spheroids using a 3D co-culture system of breast cancer cells and adipocytes or conditioned medium (CM) of adipocytes. An orthotopic breast cancer mouse model was used to examine the role of adipocytes-Grem2 in breast cancer progression.

RESULTS

Grem2 overexpression suppressed adipogenesis of 3T3-L1 cells. Proliferative and invasion abilities of spheroids formed by co-culturing MTV/TM-011 breast cancer cells and adipocytes-Grem2 were significantly reduced compared to those of spheroids formed by co-culturing MTV/TM-011 cells and adipocytes-mock. Compared to adipocytes-mock, adipocytes-Grem2 showed decreased mRNA expression of several adipokines, notably IL-6. The concentration of IL-6 in the CM of these cells was also decreased. Proliferative and invasive abilities of breast cancer cells reduced by adipocytes-Grem2 were restored by IL-6 treatment. Expression levels of vimentin, slug, and twist1 in breast cancer cells were decreased by treatment with CM of adipocytes-Grem2 but increased by IL-6 treatment. In orthotopic breast cancer mouse model, mice injected with both MTV/TM-011 cells and adipocytes-Grem2 showed smaller primary tumors and lower lung metastasis than controls. However, IL-6 administration increased both the size of primary tumor and the number of metastatic lung lesions, which were reduced by adipocytes-Grem2.

CONCLUSIONS

Our study suggests that GREM2 overexpression in adipocytes can inhibit adipogenesis, reduce the expression and secretion of several adipokines, including IL-6, and ultimately inhibit breast cancer progression.

Multi-Faceted Role of Cancer-Associated Adipocytes in Colorectal Cancer

Colorectal cancer (CRC) is one of the most commonly diagnosed types of cancer, especially in obese patients, and the second cause of cancer-related death worldwide. Based on these data, extensive research has been performed over the last decades to decipher the pivotal role of the tumor microenvironment (TME) and its cellular and molecular components in CRC development and progression. In this regard, substantial progress has been made in the identification of cancer-associated adipocytes' (CAAs) characteristics, considering their active role in the CCR tumor niche, by releasing a panel of metabolites, growth factors, and inflammatory adipokines, which assist the cancer cells' development. Disposed in the tumor invasion front, CAAs exhibit a fibroblastic-like phenotype and establish a bidirectional molecular dialogue with colorectal tumor cells, which leads to functional changes in both cell types and contributes to tumor progression. CAAs also modulate the antitumor immune cells' response and promote metabolic reprogramming and chemotherapeutic resistance in colon cancer cells. This review aims to report recent cumulative data regarding the molecular mechanisms of CAAs' differentiation and their activity spectrum in the TME of CRC. A better understanding of CAAs and the molecular interplay between CAAs and tumor cells will provide insights into tumor biology and may open the perspective of new therapeutic opportunities in CRC patients.

Angiogenesis regulators S100A4, SPARC and SPP1 correlate with macrophage infiltration and are prognostic biomarkers in colon and rectal cancers

Introduction

Increasing evidence suggests that it is necessary to find effective and robust clinically validated prognostic biomarkers that can identify "high-risk" colorectal cancer (CRC) patients. Currently, available prognostic factors largely include clinical-pathological parameters and focus on the cancer stage at the time of diagnosis. Among cells of tumor microenvironment (TME) only Immunoscore classifier based on T lymphocytes showed high predictive value.

Methods

In the present study, we performed the complex analysis of mRNA and protein expression of crucial regulators of tumor angiogenesis and tumor progression, expressed by tumor-associated macrophages (TAMs): S100A4, SPP1 and SPARC. Colon and rectal cancer patients were investigated independently and in a combined cohort (CRC). For mRNA expression, we analyzed RNA sequencing data obtained from TCGA (N=417) and GEO (N=92) cohorts of colorectal cancer patients. For protein expression, we performed IHC digital quantification of tumor tissues obtained from 197 patients with CRC treated in the Department of abdominal oncology in Clinics of Tomsk NRMC.

Results

High S100A4 mRNA expression accurately predicted poor survival for patients with CRC independently of cancer type. SPARC mRNA level was independent prognostic factors for survival in colon but not in rectal cancer. SPP1 mRNA level had significant predictive value for survival in both rectal and colon cancers. Analysis of human CRC tissues revealed that S100A4, SPP1 and SPARC are expressed by stromal compartments, in particular by TAMs, and have a strong correlation with macrophage infiltration. Finally, our results indicate that chemotherapy-based treatment can change the predictive direction of S100A4 for rectal cancer patients. We found that S100A4 stromal levels were higher in patients with better response to neoadjuvant chemotherapy/chemoradiotherapy, and S100A4 mRNA levels predicted better DFS among non-responders.

Discussion

These findings can help improve the prognosis of patients with CRC based on S100A4, SPP1 and SPARC expression levels.

Integrated bioinformatics analysis of microarray data from the GEO database to identify the candidate genes linked to poor prognosis in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is one of the most common cancers with high morbidity and mortality and remains a crucial factor endangering human health.

OBJECTIVE

This study aimed to elucidate the potential treatment target and prognostic biomarker in patients with LUAD through a comprehensive bioinformatics analysis.

METHODS

The three public microarray datasets of GSE118370, GSE116959, and GSE43767 were obtained from the GEO data resource. The DEGs were explored between LUAD and non-malignant samples using GEO2R online tool in GEO data resource. GO along with KEGG analysis of DEGs were examined using WebGestalt tool. The STRING web resource was employed to develop the PPI network of DEGs, whereas Cytoscape software was employed to perform module analysis. Finally, the mRNA, protein expression along with survival analysis of hub genes were explored via GEPIA, HPA along with Kaplan-Meier plotter web resource, respectively.

RESULTS

Only 82 upregulated and 105 downregulated DEGs were found among the three datasets. Further, GO analysis illustrated that 187 DEGs were primary enriched in extracellular structure organization, tube development along with cell adhesion. The KEGG enrichments showed that these DEGs were primary linked to leukocyte transendothelial migration, vascular smooth muscle contraction along with ECM-receptor interaction. Among the 187 DEGs, the 10 hub genes (P4HB, SPP1, CP, GOLM1, COL1A1, MMP9, COL10A1, APOA1, COL4A6, and TIMP1) were identified. The mRNA along with protein levels of hub genes in LUAD tissues were further verified by Oncomine, UCSC Xena, GEPIA and HPA databases. Additionally, overall survival curves illustrated that LUAD patients with the higher levels of P4HB, SPP1, COL1A1, and MMP9 were dramatically linked to shorter overall survival.

CONCLUSIONS

The current study identified DEGs candidate genes (P4HB, SPP1, COL1A1, and MMP9) and pathways in LUAD using bioinformatics analysis, which could enhance our understanding of pathogenesis along with underlying molecular events in LUAD, and these hub genes and pathways may help provide candidate treatment targets for LUAD.

A Five-LLPS Gene Risk Score Prognostic Signature Predicts Survival in Hepatocellular Carcinoma

Background

Primary liver cancer, dominated by hepatocellular carcinoma (HCC), is one of the most common cancer types and the third leading cause of cancer death in 2020. Previous studies have shown that liquid-liquid phase separation (LLPS) plays an important role in the occurrence and development of cancer including HCC, but its influence on the patient prognosis is still unknown. It is necessary to explore the effect of LLPS genes on prognosis to accurately forecast the prognosis of HCC patients and identify relevant targeted therapeutic sites.

Methods

Using The Cancer Genome Atlas dataset and PhaSepDB dataset, we identified LLPS genes linked to the overall survival (OS) of HCC patients. We applied Least Absolute Shrinkage and Selection Operator (LASSO) Cox penalized regression analysis to choose the best genes for the risk score prognostic signature. We then analysed the validation dataset and evaluated the effectiveness of the risk score prognostic signature. Finally, we performed quantitative real-time PCR experiments to validate the genes in the prognostic signature.

Results

We identified 43 differentially expressed LLPS genes that were associated with the OS of HCC patients. Five of these genes (BMX, FYN, KPNA2, PFKFB4, and SPP1) were selected to generate a prognostic risk score signature. Patients in the low-risk group were associated with better OS than those in the high-risk group in both the training dataset and the validation dataset. We found that BMX and FYN had lower expression levels in HCC tumour tissues, whereas KPNA2, PFKFB4, and SPP1 had higher expression levels in HCC tumour tissues. The validation demonstrated that the five-LLPS gene risk score signature has the capability of predicting the OS of HCC patients.

Conclusion

Our study constructed a five-LLPS gene risk score signature that can be applied as an effective and convenient prognostic tool. These five genes might serve as potential targets for therapy and the treatment of HCC.

Distinct roles of ADIPOR1 and ADIPOR2: A pan-cancer analysis

INTRODUCTION

AdipoR1 and AdipoR2 proteins, encoded by ADIPOR1 and ADIPOR2 genes respectively, are the receptors of adiponectin secrected by adipose tissue. Increasing studies have identified the vital role of adipose tissue in various diseases, including cancers. Hence, there is an urgent need to explore the roles of AdipoR1 and AdipoR2 in cancers.

METHODS

We conducted a comprehensive pan-cancer analysis for the roles of AdipoR1 and AdipoR2 via several public databases, including expression differences, prognostic value, and the correlations with tumor microenvironment, epigenetic modification, and drug sensitivity.

RESULTS

Both ADIPOR1 and ADIPOR2 genes are dysregulated in most cancers, but their genomic alteration frequencies are low. In addition, they are also correlated with the prognosis of some cancers. Although they are not strongly correlated with tumor mutation burden (TMB) or microsatellite instability (MSI), ADIPOR1/2 genes display a significant association with cancer stemness, tumor immune microenvironment, immune checkpoint genes (especially CD274 and NRP1), and drug sensitivity.

DISCUSSION

ADIPOR1 and ADIPOR2 play critical roles in diverse cancers, and it is a potential strategy to treat tumors through targeting ADIPOR1 and ADIPOR2.

A novel prognostic model based on urea cycle-related gene signature for colorectal cancer

Background

Colorectal cancer (CRC) is the second leading cause of cancer-related deaths in the world. This study aimed to develop a urea cycle (UC)-related gene signature that provides a theoretical foundation for the prognosis and treatment of patients with CRC.

Methods

Differentially expressed UC-related genes in CRC were confirmed using differential analysis and Venn diagrams. Univariate Cox and least absolute shrinkage and selection operator regression analyses were performed to identify UC-related prognostic genes. A UC-related signature was created and confirmed using distinct datasets. Independent prognostic predictors were authenticated using Cox analysis. The Cell-type Identification by Estimating Relative Subsets of RNA Transcripts algorithm and Spearman method were applied to probe the linkage between UC-related prognostic genes and tumor immune-infiltrating cells. The Human Protein Atlas database was used to determine the protein expression levels of prognostic genes in CRC and normal tissues. Verification of the expression levels of UC-related prognostic genes in clinical tissue samples was performed using real-time quantitative polymerase chain reaction (qPCR).

Results

A total of 49 DEUCRGs in CRC were mined. Eight prognostic genes (TIMP1, FABP4, MMP3, MMP1, CD177, CA2, S100P, and SPP1) were identified to construct a UC-related gene signature. The signature was then affirmed using an external validation set. The risk score was demonstrated to be a credible independent prognostic predictor using Cox regression analysis. Functional enrichment analysis revealed that focal adhesion, ECM-receptor interaction, IL-17 signaling pathway, and nitrogen metabolism were associated with the UC-related gene signature. Immune infiltration and correlation analyses revealed a significant correlation between UC-related prognostic genes and differential immune cells between the two risk subgroups. Finally, the qPCR results of clinical samples further confirmed the results of the public database.

Conclusion

Taken together, this study authenticated UC-related prognostic genes and developed a gene signature for the prognosis of CRC, which will be of great significance in the identification of prognostic molecular biomarkers, clinical prognosis prediction, and development of treatment strategies for patients with CRC.

Serum anti-SPP1 autoantibody as a potential novel biomarker in detection of esophageal squamous cell carcinoma

Background

Esophageal squamous cell carcinoma (ESCC) has poor prognosis mainly due to lacking of effective diagnostic biomarkers. Aberrant expression of secreted phosphoprotein 1 (SPP1) protein has been observed in several cancers. The purpose of this study is to assess the feasibility of serum autoantibody to SPP1 in detection of ESCC.

Methods

The SPP1 protein levels in 108 ESCC tissues and 72 adjacent normal tissues were analyzed by immunohistochemistry. Discovery group containing 62 serum samples from ESCC patients and 62 serum samples from normal controls (NC) were used to detect the levels of anti-SPP1 autoantibody by enzyme-linked immunosorbent assay (ELISA). Validation group containing another 100 ESCC and 100 NC serum samples were tested to confirm the levels of autoantibody to SPP1. Western blotting was performed to further confirm the results of ELISA.

Results

SPP1 protein was significantly overexpressed in ESCC tissues compared to adjacent normal tissues. ELISA results showed that serum autoantibody to SPP1 was significantly increased in ESCC compared to NC in both discovery and validation groups. Autoantibody to SPP1 could discriminate patients with ESCC from NC with the area under curve (AUC) values of 0.653 and 0.739 in discovery and validation group, respectively. The results of ELISA and the occurrence of immunoreactivity to SPP1 in ESCC sera were confirmed by western blotting.

Conclusion

Our study indicated the potential significance of anti-SPP1 autoantibody as a novel biomarker for detection of ESCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-10012-9.

Immune-Related Biomarkers Associated with Lung Metastasis from the Colorectal Cancer Microenvironment

Immune-associated biomarkers can predict lung metastases from colorectal cancer. Differentially expressed genes (DEGs) were screened from sample data extracted from gene expression omnibus (GEO) database. The DEGs were screened from the lung metastasis (LM) and primary cancer (PC) groups of the Moffitt Cancer Center cohort dataset. Then, the tumor immune microenvironment and abundance of immune cell infiltration analyses were performed, and the immune-related DEGs were retrieved. In addition, the transcription factor (TF)-miRNA-mRNA network was constructed and enrichment analyses of the immune-related DEGs and upregulated and downregulated DEGs were carried out. Then, the protein-protein interaction (PPI) network was conducted and the drug-gene interaction was predicted. A total of 268 DEGs were screened. The Immune_Score of samples in the LM group was significantly higher compared with the PC group. The infiltration ratio of M0 macrophages and M2 macrophages of samples was higher than others. A total of 54 immune-related DEGs in M0 macrophages were screened. Moreover, the TF-miRNA-mRNA network was constructed among 8 miRNA-mRNA and 50 TF-mRNA, and the secreted phosphoprotein 1 was regulated by 12 TFs, and the oxidized low-density lipoprotein receptor 1 was regulated by 3 miRNAs and 3 TFs. The TF SAM pointed domain containing ETS TF was also a downregulated DEG. The Kyoto Encyclopedia of Genes and Genomes pathway analysis showed that the DEGs in the TF-miRNA-mRNA network were mainly involved in the interleukin-7 signaling pathway and cell adhesion molecules. In total, 23 protein interactions in this PPI network of M0 macrophage cells were involved in 27 mRNAs. There were 38 drug-gene interactions of immune-related DEGs of M0 macrophage cells predicted to contain 34 small molecule drugs and 8 mRNAs. Finally, the CON cohort dataset verified that the infiltration ratio of M0 and M2 macrophages of the samples was higher.

Identification of Key Pathways and Establishment of a Seven-Gene Prognostic Signature in Cervical Cancer

Cervical cancer (CC) remains high morbidity and mortality. We aimed to identify critical pathways underlying cervical carcinogenesis and establish a prognostic signature. Six datasets from the gene expression omnibus (GEO) database were used to screen the differentially expressed genes (DEGs) between CC and normal tissues. We used the unions of the DEGs to perform functional analysis. The 108 overlapped DEGs were analyzed to determine a prognostic signature by Cox regression and Lasso analysis based on The Cancer Genome Atlas (TCGA) database. Gene Set Enrichment Analysis (GSEA) and Immune Cell Abundance Identifier (ImmuCellAI) were used to determine the relationships between the signature and biological functions. The PI3K-Akt signaling pathway, the Ras signaling pathway, and the viral carcinogenesis pathway may be critical for CC development. We identified seven genes (PLOD2, DSG2, SPP1, CXCL8, MCM5, HLTF, and KLF4) to construct a risk score formula. Survival analysis showed that the high-risk group indicated a worse prognosis than the low-risk group $\left(p<0.0001\right)$ . The AUC of the prognostic signature was 0.7449, 0.7641, and 0.8146 at 1, 3, and 5 years. We also identified that the signature is an independent prognostic factor. GSEA showed five pathways were relevant to the signature, such as the adherens junction pathway. The signature also affected the abundances of various types of immune cells, such as B cell, CD4+ T cell, and CD8+ T cell. Further, we found that SPP1 was co-expressed with HK3, CD163, CCL3, CLEC5A, MMP8, TREM1, OLR1, and TREM2. The results of Gene Ontology analysis showed that SPP1 and its co-expressed related proteins mainly affected metabolic process, multicellular organismal process, cell communication, cell proliferation, protein binding, and transporter activity. In conclusion, the present study explored the key pathways for CC development and the seven-gene signature can effectively make the prognosis evaluation of CC patients.

Comprehensive Analysis to Identify SPP1 as a Prognostic Biomarker in Cervical Cancer

Background: SPP1, secreted phosphoprotein 1, is a member of the small integrin-binding ligand N-linked glycoprotein (SIBLING) family. Previous studies have proven SPP1 overexpressed in a variety of cancers and can be identified as a prognostic factor, while no study has explored the function and carcinogenic mechanism of SPP1 in cervical cancer. Methods: We aimed to demonstrate the relationship between SPP1 expression and pan-cancer using The Cancer Genome Atlas (TCGA) database. Next, we validated SPP1 expression of cervical cancer in the Gene Expression Omnibus (GEO) database, including GSE7803, GSE63514, and GSE9750. The receiver operating characteristic (ROC) curve was used to evaluate the feasibility of SPP1 as a differentiating factor by the area under curve (AUC) score. Cox regression and logistic regression were performed to evaluate factors associated with prognosis. The SPP1-binding protein network was built by the STRING tool. Enrichment analysis by the R package clusterProfiler was used to explore potential function of SPP1. The single-sample GSEA (ssGSEA) method from the R package GSVA and TIMER database were used to investigate the association between the immune infiltration level and SPP1 expression in cervical cancer. Results: Pan-cancer data analysis showed that SPP1 expression was higher in most cancer types, including cervical cancer, and we got the same result in the GEO database. The ROC curve suggested that SPP1 could be a potential diagnostic biomarker (AUC = 0.877). High SPP1 expression was associated with poorer overall survival (OS) (P = 0.032). Further enrichment and immune infiltration analysis revealed that high SPP1 expression was correlated with regulating the infiltration level of neutrophil cells and some immune cell types, including macrophage and DC. Conclusion: SPP1 expression was higher in cervical cancer tissues than in normal cervical epithelial tissues. It was significantly associated with poor prognosis and immune cell infiltration. Thus, SPP1 may become a promising prognostic biomarker for cervical cancer patients.

Prognostic Matrisomal Gene Panel and Its Association with Immune Cell Infiltration in Head and Neck Carcinomas

Simple Summary

Squamous cell carcinoma of the head and neck (SCCHN) is a heterogeneous group of tumors arising from squamous cells lining different anatomic sites. This type of malignancy has been mainly investigated by focusing primarily on tumor cells, but recent evidence highlighted the importance of the tumor microenvironment (TME) in cancer growth, progression and metastasis. Hence, we hypothesized that dysregulated matrisomal components could have a common association with patient survival, irrespective of the subsite of origin of the SCCHN. Using bioinformatic methods and public datasets, we successfully identified a gene panel with prognostic value in HPV-negative and non-metastatic node-negative tumors and demonstrated its association with immune cell infiltration.

Abstract

Squamous cell carcinoma of the head and neck (SCCHN) is common worldwide and related to several risk factors including smoking, alcohol consumption, poor dentition and human papillomavirus (HPV) infection. Different etiological factors may influence the tumor microenvironment and play a role in dictating response to therapeutics. Here, we sought to investigate whether an early-stage SCCHN-specific prognostic matrisome-derived gene signature could be identified for HPV-negative SCCHN patients (n = 168), by applying a bioinformatics pipeline to the publicly available SCCHN-TCGA dataset. We identified six matrisome-derived genes with high association with prognostic outcomes in SCCHN. A six-gene risk score, the SCCHN TMI (SCCHN-tumor matrisome index: composed of MASP1, EGFL6, SFRP5, SPP1, MMP8 and P4HA1) was constructed and used to stratify patients into risk groups. Using machine learning-based deconvolution methods, we found that the risk groups were characterized by a differing abundance of infiltrating immune cells. This work highlights the key role of immune infiltration cells in the overall survival of patients affected by HPV-negative SCCHN. The identified SCCHN TMI represents a genomic tool that could potentially aid patient stratification and selection for therapy in these patients.

A methylation-based prognostic model predicts survival in patients with colorectal cancer

Background

To construct a model that could effectively predict the prognosis of colorectal cancer (CRC) by searching for methylated-differentially expressed genes (MDEGs).

Methods

We identified MDEGs through four databases from Gene Expression Omnibus (GEO) and annotated their functions via bioinformatics analysis. Subsequently, after adjusting for gender, age, and grading, multivariate Cox hazard analysis was utilized to select MDEGs interrelated with the prognosis of CRC, and LASSO analysis was utilized to fit the prediction model in the training set. Furthermore, another independent dataset was harnessed to verify the effectiveness of the model in predicting prognosis.

Results

In total, 252 hypomethylated and up-regulated genes and 132 hypermethylated and down-regulated genes were identified, 27 of which were correlated with the prognosis of CRC, and a 10-gene prognostic model was established after LASSO analysis. The overall survival rate could be effectively grouped into different risks by the median score of this model in the training set [risk ratio (HR) =2.27, confidence interval (95% CI), 1.69-3.13, P=8.15×10^-8], and the validity of its effect in predicting prognosis in CRC was verified in the validation dataset (HR =1.75, 95% CI, 1.15-2.70, P=9.32×10^-3).

Conclusions

Our model could effectively predict the overall survival rate of patients with CRC and provides potential application guidelines for its clinically personalized treatment.

SPP1 and FN1 are significant gene biomarkers of tongue squamous cell carcinoma

Tongue squamous cell carcinoma (TSCC) is one of the most common malignant tumor types in the oral and maxillofacial region. The etiology and pathogenesis behind TSCC is complicated. In the present study, three gene expression profiles, namely GSE31056, GSE13601 and GSE78060, were downloaded from the Gene Expression Omnibus (GEO). The GEO2R online tool was utilized to identify differentially expressed genes (DEGs) between TSCC and normal tissue samples. Furthermore, a protein-protein interaction (PPI) network was constructed and hub genes were validated and analyzed. A total of 83 common DEGs were obtained in three datasets, including 48 upregulated and 35 downregulated genes. Pathway enrichment analysis indicated that DEGs were primarily enriched in cell adhesion, extracellular matrix (ECM) organization, and proteolysis. A total of 63 nodes and 218 edges were included in the PPI network. The top 11 candidate hub genes were acquired, namely plasminogen activator urokinase (PLAU), signal transducer and activator of transcription 1, C-X-C motif chemokine ligand 12, matrix metallopeptidase (MMP) 13, secreted phosphoprotein 1 (SPP1), periostin, MMP1, MMP3, fibronectin 1 (FN1), serpin family E member 1 and snail family transcriptional repressor 2. Overall, 83 DEGs and 11 hub genes were screened from TSCC and normal individuals using bioinformatics and microarray technology. These genes may be used as diagnostic and therapeutic biomarkers for TSCC. In addition, SPP1 and FNl were identified as potential biomarkers for the progression of TSCC.

Identification of gene biomarkers and immune cell infiltration characteristics in rectal cancer

Background

Compared with colon cancer, the increase of morbidity is more significant for rectal cancer. The current study set out to identify novel and critical biomarkers or features that may be used as promising targets for early diagnosis and treatment monitoring of rectal cancer.

Methods

Microarray datasets of rectal cancer with a minimum sample size of 30 and RNA-sequencing datasets of rectal adenocarcinoma (READ) were downloaded from the Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA) database. The method of robust rank aggregation was utilized to integrate differentially expressed genes (DEGs). The protein-protein interaction (PPI) network of the DEGs was structured using the STRING platform, and hub genes were identified using the Cytoscape plugin cytoHubba and an UpSet diagram. R software was employed to perform functional enrichment analysis. Receiver operating characteristic (ROC) curves based on the GEO data and Kaplan-Meier curves based on the TCGA data were drawn to assess the diagnostic and prognostic values of the hub genes. Immune cell infiltration analysis was conducted with CIBERSORT, and the diagnostic value and correlations between prognostic genes and infiltrated immune cells were analyzed by principal component analysis (PCA), ROC curves, and correlation scatter plots.

Results

A total of 137 robust DEGs were obtained by integrating datasets in GEO. Twenty-four hub genes, including CHGA, TTR, SAA1, SPP1, MMP1, TGFBI, COL1A1, and PCK1, were identified as a diagnostic gene biomarker group for rectal cancer, and SAA1, SPP1, and SI were identified as potential novel prognostic biomarkers. Functionally, the hub genes were mainly involved in the rectal cancer related interleukin (IL)-17 and proximal tubule bicarbonate reclamation pathways. Twelve sensitive infiltrated immune cells were identified, and were correlated with prognostic genes.

Conclusions

The integrated gene biomarker group combined with immune cell infiltration can effectively indicate rectal cancer.

Prognostic biomarkers and therapeutic targets in oral squamous cell carcinoma: a study based on cross-database analysis

Background

Oral squamous cell carcinoma (OSCC) is a malignant cancer, the survival rate of patients is disappointing. Therefore, it is necessary to identify the driven-genes and prognostic biomarkers in OSCC.

Methods

Four Gene Expression Omnibus (GEO) datasets were integratedly analyzed using bioinformatics approaches, including identification of differentially expressed genes (DEGs), GO and KEGG analysis, construction of protein-protein interaction (PPI) network, selection of hub genes, analysis of prognostic information and genetic alterations of hub genes. ONCOMINE, The Cancer Genome Atlas (TCGA) and Human Protein Atlas databases were used to evaluate the expression and prognostic value of hub genes. Tumor immunity was assessed to investigate the functions of hub genes. Finally, Cox regression model was performed to construct a multiple-gene prognostic signature.

Results

Totally 261 genes were found to be dysregulated. 10 genes were considered to be the hub genes. The Kaplan-Meier analysis showed that upregulated SPP1, FN1, CXCL8, BIRC5, PLAUR, and AURKA were related to poor outcomes in OSCC patients. FOXM1 and TPX2 were considered as the potential immunotherapeutic targets with future clinical significance. Moreover, we constructed a nine-gene signature (TEX101, DSG2, SCG5, ADA, BOC, SCARA5, FST, SOCS1, and STC2), which can be utilized to predict prognosis of OSCC patients effectively.

Conclusion

These findings may provide new clues for exploring the molecular mechanisms and targeted therapy in OSCC. The hub genes and risk gene signature are helpful to the personalized treatment and prognostic judgement.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41065-021-00181-1.

Identification of VWF as a Novel Biomarker in Lung Adenocarcinoma by Comprehensive Analysis

Lung adenocarcinoma (LUAD) is one of the most malignant tumors with high morbidity and mortality worldwide due to the lack of reliable methods for early diagnosis and effective treatment. It’s imperative to study the mechanism of its development and explore new biomarkers for early detection of LUAD. In this study, the Gene Expression Omnibus (GEO) dataset GSE43458 and The Cancer Genome Atlas (TCGA) were used to explore the differential co-expressed genes between LUAD and normal samples. Three hundred sixity-six co-expressed genes were identified by differential gene expression analysis and Weighted Gene Co-expression Network Analysis (WGCNA) method. Those genes were mainly enriched in ameboidal-type cell migration (biological process), collagen-containing extracellular matrix (cell component), and extracellular matrix structure constituent (molecular function). The protein-protein network (PPI) was constructed and 10 hub genes were identified, including IL6, VWF, CDH5, PECAM1, EDN1, BDNF, CAV1, SPP1, TEK, and SELE. The expression level of hub genes was validated in the GEPIA database, compared with normal tissues, VWF is lowly expressed and SPP1 is upregulated in LUAD tissues. The survival analysis showed increased expression of SPP1 indicated unfavorable prognosis whereas high expression of VWF suggested favorable prognosis in LUAD (p < 0.05). Based on the immune infiltration analysis, the relationship between SPP1 and VWF expression and macrophage, neutrophil, and dendritic cell infiltration was weak in LUAD. Quantitative real-time PCR (qRT-PCR) and western blotting were used to validate the expression of VWF and SPP1 in normal human bronchial epithelial (HBE) cell and three LUAD cell lines, H1299, H1975, and A549. Immunohistochemistry (IHC) was further performed to detect the expression of VWF in 10 cases LUAD samples and matched normal tissues. In summary, the data suggest that VWF is a potential novel biomarker for prognosis of LUAD.

The clinical relevance of gene expression based prognostic signatures in colorectal cancer

Colorectal cancer (CRC) is one of the most prevalent cancers, with more than one million new cases every year. In the last few decades, several advancements in therapeutic and preventative levels have reduced the mortality rate, but new biomarkers are required for improved prognosis. The alterations at the genetic and epigenetic level have been recognized as major players in tumorigenesis. The products of gene expression in the form of mRNA, microRNA, and long-noncoding RNA, have started to emerge as important regulatory molecules, playing an important role in cancer. Gene-expression based prognostic risk scores, which quantify and compare their expression, have emerged as promising biomarkers with enormous clinical value. These composite multi-gene models in which more than one gene is used to predict prognosis have been shown to be significantly effective in identifying patients with multiple clinico-pathological risks like overall mortality, response to chemotherapy, risk of metastasis, etc. The advent of microarray and advanced sequencing technologies have led to the generation of large datasets like TCGA (The Cancer Genome Atlas) and GEO (Gene Expression Omnibus), which have fueled the search for new biomarkers. Continuous evaluation of these candidate biomarkers in clinical settings is promising to improve the management of CRC. These composite gene signatures provide potential in identifying high-risk patients, which might help clinicians to better manage these patients and design appropriate personalized therapeutic interventions. In this review, we emphasize on composite prognostic scores from diverse resources with clinical utility in CRC.

Network Pharmacology-Based Study on the Mechanism of Gegen Qinlian Decoction against Colorectal Cancer

Purpose

Gegen Qinlian decoction (GQD) has been used to treat gastrointestinal diseases, such as diarrhea and ulcerative colitis (UC). A recent study demonstrated that GQD enhanced the effect of PD-1 blockade in colorectal cancer (CRC). This study used network pharmacology analysis to investigate the mechanisms of GQD as a potential therapeutic approach against CRC.

Materials and Methods

Bioactive chemical ingredients (BCIs) of GQD were collected from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. CRC-specific genes were obtained using the gene expression profile GSE110224 from the Gene Expression Omnibus (GEO) database. Target genes related to BCIs of GQD were then screened out. The GQD-CRC ingredient-target pharmacology network was constructed and visualized using Cytoscape software. A protein-protein interaction (PPI) network was subsequently constructed and analyzed with BisoGenet and CytoNCA plug-in in Cytoscape. Gene Ontology (GO) functional and the Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analysis for target genes were then performed using the R package of clusterProfiler.

Results

One hundred and eighteen BCIs were determined to be effective on CRC, including quercetin, wogonin, and baicalein. Twenty corresponding target genes were screened out including PTGS2, CCNB1, and SPP1. Among these genes, CCNB1 and SPP1 were identified as crucial to the PPI network. A total of 212 GO terms and 6 KEGG pathways were enriched for target genes. Functional analysis indicated that these targets were closely related to pathophysiological processes and pathways such as biosynthetic and metabolic processes of prostaglandins and prostanoids, cytokine and chemokine activities, and the IL-17, TNF, Toll-like receptor, and nuclear factor-kappa B (NF-κB) signaling pathways.

Conclusion

The study elucidated the “multiingredient, multitarget, and multipathway” mechanisms of GQD against CRC from a systemic perspective, indicating GQD to be a candidate therapy for CRC treatment.

A Novel Four-Gene Signature Associated With Immune Checkpoint for Predicting Prognosis in Lower-Grade Glioma

The overall survival of patients with lower grade glioma (LGG) varies greatly, but the current histopathological classification has limitations in predicting patients’ prognosis. Therefore, this study aims to find potential therapeutic target genes and establish a gene signature for predicting the prognosis of LGG. CD44 is a marker of tumor stem cells and has prognostic value in various tumors, but its role in LGG is unclear. By analyzing three glioma datasets from Gene Expression Omnibus (GEO) database, CD44 was upregulated in LGG. We screened 10 CD44-related genes via protein–protein interaction (PPI) network; function enrichment analysis demonstrated that these genes were associated with biological processes and signaling pathways of the tumor; survival analysis showed that four genes (CD44, HYAL2, SPP1, MMP2) were associated with the overall survival (OS) and disease-free survival (DFS)of LGG; a novel four-gene signature was constructed. The prediction model showed good predictive value over 2-, 5-, 8-, and 10-year survival probability in both the development and validation sets. The risk score effectively divided patients into high- and low- risk groups with a distinct outcome. Multivariate analysis confirmed that the risk score and status of IDH were independent prognostic predictors of LGG. Among three LGG subgroups based on the presence of molecular parameters, IDH-mutant gliomas have a favorable OS, especially if combined with 1p/19q codeletion, which further confirmed the distinct biological pattern between three LGG subgroups, and the gene signature is able to divide LGG patients with the same IDH status into high- and low- risk groups. The high-risk group possessed a higher expression of immune checkpoints and was related to the activation of immunosuppressive pathways. Finally, this study provided a convenient tool for predicting patient survival. In summary, the four prognostic genes may be therapeutic targets and prognostic predictors for LGG; this four-gene signature has good prognostic prediction ability and can effectively distinguish high- and low-risk patients. High-risk patients are associated with higher immune checkpoint expression and activation of the immunosuppressive pathway, providing help for screening immunotherapy-sensitive patients.

Identification and verification of three key genes associated with survival and prognosis of COAD patients via integrated bioinformatics analysis

BACKGROUND

Colorectal cancer (CRC) is the third most lethal malignancy in the world, wherein colon adenocarcinoma (COAD) is the most prevalent type of CRC. Exploring biomarkers is important for the diagnosis, treatment, and prevention of COAD.

METHODS

We used GEO2R and Venn online software for differential gene screening analysis. Hub genes were screened via Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and Cytoscape, following Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Finally, survival analysis and RNA expression validation were performed via UALCAN online software and real-time PCR. Immunohistochemistry (IHC) was performed to verify the protein expression level of hub genes from tissues of COAD patients.

RESULTS

In the present study, we screened 323 common differentially expressed genes (DEGs) from four GSE datasets. Furthermore, four hub genes were selected for survival correlation analysis and expression level verification, three of which were shown to be statistically significant.

CONCLUSION

Our study suggests that Serpin Family E Member 1 (SERPINE1), secreted phosphoprotein 1 (SPP1) and tissue inhibitor of metalloproteinase 1 (TIMP1) may be biomarkers closely related to the prognosis of CRC patients.

Adipocytokines: Are they the Theory of Everything?

INTRODUCTION

Adipose tissue secretes various bioactive peptides/proteins, immune molecules and inflammatory mediators which are known as adipokines or adipocytokines. Adipokines play important roles in the maintenance of energy homeostasis, appetite, glucose and lipid metabolism, insulin sensitivity, angiogenesis, immunity and inflammation. Enormous number of studies from all over the world proved that adipocytokines are involved in the pathogenesis of diseases affecting nearly all body systems, which raises the question whether we can always blame adipocytokines as the triggering factor of every disease that may hit the body.

OBJECTIVE

Our review targeted the role played by adipocytokines in the pathogenesis of different diseases affecting different body systems including diabetes mellitus, kidney diseases, gynecological diseases, rheumatologic disorders, cancers, Alzheimer's, depression, muscle disorders, liver diseases, cardiovascular and lung diseases.

METHODOLOGY

We cited more than 33 recent literature reviews that discussed the role played by adipocytokines in the pathogenesis of different diseases affecting different body systems.

CONCLUSION

More evidence is being discovered to date about the role played by adipocytokines in more diseases and extra research is needed to explore hidden roles played by adipokine imbalance on disease pathogenesis.

Estimation of Hub Genes and Infiltrating Immune Cells in Non-Smoking Females with Lung Adenocarcinoma by Integrated Bioinformatic Analysis

BACKGROUND In recent years, the morbidity and mortality rates of lung adenocarcinoma in non-smoking females have been increasing dramatically. Although much research has been done with some progress, the molecular mechanism remains unclear. In this study we aimed to estimate hub genes and infiltrating immune cells in non-smoking females with lung adenocarcinoma. MATERIAL AND METHODS Firstly, we obtained differentially expressed genes (DEGs) by GEO2R analysis based on 3 independent mRNA microarray datasets of GSE10072, GSE31547, and GSE32863. The DAVID database was utilized for functional enrichment analysis of DEGs. Moreover, we identified hub genes with prognostic value by STRING, Cytoscape, and Kaplan Meier plotter. Subsequently, these genes were further analyzed by Gene Expression Profiling Interactive Analysis, Oncomine, Tumor Immune Estimation Resource, and Human Protein Atlas. Finally, the immune infiltration analysis was performed by CIBERSORT and The Cancer Genome Atlas with R packages. RESULTS We found 315 DEGs enriching in the extracellular matrix organization, cell adhesion, integrin binding, angiogenesis, and hypoxic response. And among these DEGs, we identified 10 hub genes (SPP1, ENG, ATF3, TOP2A, COL1A1, PAICS, CAV1, CAT, TGFBR2, and ANGPT1) of significant prognostic value. Simultaneously, we illustrated the distribution and differential expressions of 22 immune cell subtypes. and dendritic cells resting and macrophages M1 were identified with prognostic significance. CONCLUSIONS The results indicated that 10 hub genes and 2 immune cell subtypes might be promising biomarkers for lung adenocarcinoma in non-smoking females. This finding needs to be further evaluated.

Identification of key genes associated with progression and prognosis for lung squamous cell carcinoma

Background

Lung squamous cell carcinoma (LUSC) is a major subtype of lung cancer with limited therapeutic options and poor clinical prognosis.

Methods

Three datasets (GSE19188, GSE33532 and GSE33479) were obtained from the gene expression omnibus (GEO) database. Differentially expressed genes (DEGs) between LUSC and normal tissues were identified by GEO2R, and functional analysis was employed using the Database for Annotation, Visualization and Integrated Discovery (DAVID) online tool. Protein-protein interaction (PPI) and hub genes were identified via the Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape software. Hub genes were further validated in The Cancer Genome Atlas (TCGA) database. Subsequently, survival analysis was performed using the Kapla-Meier curve and Cox progression analysis. Based on univariate and multivariate Cox progression analysis, a gene signature was established to predict overall survival. Receiver operating characteristic curve was used to evaluate the prognostic value of the model.

Results

A total of 116 up-regulated genes and 84 down-regulated genes were identified. These DEGs were mainly enriched in the two pathways: cell cycle and p53 signaling way. According to the degree of protein nodes in the PPI network, 10 hub genes were identified. The mRNA expression levels of the 10 hub genes in LUSC were also significantly up-regulated in the TCGA database. Furthermore, a novel seven-gene signature (FLRT3, PPP2R2C, MMP3, MMP12, CAPN8, FILIP1 and SPP1) from the DEGs was constructed and acted as a significant and independent prognostic signature for LUSC.

Conclusions

The 10 hub genes might be tightly correlated with LUSC progression. The seven-gene signature might be an independent biomarker with a significant predictive value in LUSC overall survival.

A Case-Control Study of the Association Between the SPP1 Gene SNPs and the Susceptibility to Breast Cancer in Guangxi, China

Secreted phosphoprotein-1 (SPP1) has been reported to be involved in the pathogenesis of breast cancer (BRC), but the influence of SPP1 single nucleotide polymorphisms on the BRC susceptibility has been rarely reported. In this study, we explored the association between rs11730582, rs2853750, and rs35893069 in the SPP1 gene and the BRC susceptibility. We used Snapshot assay to detect SPP1 single nucleotide polymorphisms in 471 BRC patients and 471 controls. The plasma SPP1 level was measured by ELISA. We found that the CC genotype and C allele of rs11730582 were associated with a significantly decreased BRC risk compared with the TT genotype and T allele, respectively [CC vs. TT: odds ratio (OR) = 0.59, 95% CI = 0.37–0.94, P = 0.026; C vs. T: OR = 0.79, 95% CI = 0.65–0.96, P = 0.022]. In addition, BRC patients and controls with the rs11730582 CC genotype had a lower plasma SPP1 level than did BRC patients and controls with TT genotype (P = 0.007 and P = 0.011, respectively). Moreover, the proportions of rs11730582 CC genotype and C allele were decreased in BRC patients with clinical stages I–III compared with those with clinical stage IV (P = 0.012 and P = 0.003, respectively). Besides, the C-G-T haplotype was associated with a significantly decreased BRC risk compared with the T-A-T haplotype (OR = 0.69, 95% CI = 0.52–0.93, P = 0.015). However, there was no significant association between rs2853750 or rs35893069 and the BRC risk. In summary, our study found the association between rs11730582 and the risk of BRC and suggested that rs11730582 may promote the occurrence and development of BRC by regulating SPP1 expression.

CXC chemokine ligand 1 mediates adiponectin-induced angiogenesis in ovarian cancer

OBJECTIVES

Adiponectin is a cytokine secreted from adipose tissue that regulates energy homeostasis, inflammation, and cell proliferation. Obesity is associated with increased risk of various cancers, including ovarian cancer. Adipokines, including adiponectin, have been implicated as a factor linking obesity and carcinogenesis. The oncogenic role of adiponectin is not known with regard to various cancer types. We sought to determine the role of adiponectin in angiogenesis in ovarian cancer in vitro.

METHODS

We transfected SKOV3 cells with vascular endothelial growth factor small interfering RNA in order to identify the independent angiogenic role of adiponectin in ovarian cancer. The vascular endothelial growth factor knockdown SKOV3 cell lines were treated with adiponectin for 48 h. The cytokines involved in adiponectin-mediated angiogenesis were explored using the human angiogenesis cytokine array and were verified with the enzyme-linked immunosorbent assay. The angiogenic effect of adiponectin was evaluated using the human umbilical vein endothelial cell tube formation assay. We also investigated the effects of adiponectin treatment on the migration and invasion of SKOV3 cells.

RESULTS

The number of tubes formed by human umbilical vein endothelial cell decreased significantly after knockdown of vascular endothelial growth factor (via transfection of vascular endothelial growth factor small interfering RNA into SKOV3 cells). When these vascular endothelial growth factor knockdown SKOV3 cells were treated with adiponectin, there was an increase in the number of tubes in a tube formation assay. Following adiponectin treatment, the CXC chemokine ligand 1 secretion increased in a cytokine array. This was confirmed by both enzyme-linked immunosorbent assay and Western blot. The increased secretion of CXC chemokine ligand 1 by adiponectin occurred regardless of vascular endothelial growth factor knockdown. In addition, the induction of migration and invasion of SKOV3 cells were significantly stronger with adiponectin treatment than they were without.

CONCLUSION

Adiponectin treatment of ovarian cancer cells induces angiogenesis via CXC chemokine ligand 1 independently of vascular endothelial growth factor. These findings suggest that adiponectin may serve as a novel therapeutic target for ovarian cancer.

Identification of key candidate genes and pathways in oral squamous cell carcinoma by integrated Bioinformatics analysis

Oral squamous cell carcinoma (OSCC) is one of the most common types of malignant head and neck tumor, which poses a serious threat to human health. In recent years, the incidence of OSCC has been increasing, while the prognosis has not significantly improved. Elucidation of the molecular mechanisms underlying the development of OSCC may provide novel therapeutic strategies. In the present study, the gene expression profiles from 4 datasets, including 244 OSCC and 95 normal oral mucosa samples, were subjected to statistical and Bioinformatics analysis. A total of 34 differentially expressed genes (DEGs) were identified, among which 14 were upregulated and 20 were downregulated in OSCC compared with normal oral mucosa tissues. Gene Ontology enrichment analysis indicated that the DEGs were mainly involved in regulation of the immune response, cell adhesion and cell proliferative processes. The Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that the DEGs were mainly associated with the phosphoinositide-3 kinase Akt and Toll-like receptor signaling pathway. The key candidate DEGs were identified from the complex protein-protein interaction network, and secreted phosphoprotein 1 (SPP1), integrin subunit α 3 and plasminogen activator, urokinase (PLAU) were confirmed to be significantly associated with the survival rate. Cell Counting Kit-8 and Transwell assays demonstrated that SPP1 and PLAU regulate cell proliferation, migration and invasion. The candidate genes/pathways identified in the present study may include promising diagnostic biomarkers or therapeutic targets for OSCC.

Adiponectin as Link Factor between Adipose Tissue and Cancer

Adipose tissue is a key regulator of energy balance playing an active role in lipid storage as well as in synthesizing several hormones directly involved in the pathogenesis of obesity. Obesity represents a peculiar risk factor for a growing list of cancers and is frequently associated to poor clinical outcome. The mechanism linking obesity and cancer is not completely understood, but, amongst the major players, there are both chronic low-grade inflammation and deregulation of adipokines secretion. In obesity, the adipose tissue is pervaded by an abnormal number of immune cells that create an inflammatory environment supporting tumor cell proliferation and invasion. Adiponectin (APN), the most abundant adipokine, shows anti-inflammatory, anti-proliferative and pro-apoptotic properties. Circulating levels of APN are drastically decreased in obesity, suggesting that APN may represent the link factor between obesity and cancer risk. The present review describes the recent advances on the involvement of APN and its receptors in the etiology of different types of cancer.

The prognostic and therapeutic role of hormones in colorectal cancer: a review

Colorectal cancer (CRC) is one of the commonest cancers in Western society with a poor prognosis in patients with advanced disease. Targeted therapy is of increasing interest and already, targeted hormone treatment for breast and prostate cancer has improved survival. The aim of this literature review is to summarise the role of hormones in CRC prognosis and treatment. A literature review of all human and animal in vivo and in vitro studies in the last 20 years, which assessed the role of hormones in CRC treatment or prognosis, was carried out. The hormones described in this review have been subdivided according to their secretion origin. Most of the studies are based on in vitro or animal models. The main findings point to adipokines, insulin and the insulin growth factor axis as key players in the link between obesity, type 2 diabetes mellitus and a subset of CRC. Gut-derived hormones, especially uroguanylin and guanylin are being increasingly investigated as therapeutic targets, with promising results. Using hormones as prognostic and therapeutic markers in CRC is still in the preliminary stages for only a fraction of the hormones affecting the GIT. In light of the increasing interest in tailoring treatment strategies, hormones are an important area of focus in the future of CRC management.