SPP1, analyzed by bioinformatics methods, promotes the metastasis in colorectal cancer by activating EMT pathway

The crosstalk role of CDKN2A between tumor progression and cuproptosis resistance in colorectal cancer

BACKGROUND

Cuproptosis is a type of cell death characterized by excessive copper-lipid reactions in the tricarboxylic acid cycle, resulting in protein toxicity stress and cell death. Although known as a cuproptosis inhibitor through CRISPR-Cas9 screening, the role of cyclin-dependent kinase inhibitor 2A (CDKN2A) in cuproptosis resistance and its connection to tumor development remains unclear.

METHODS

In this study, we combined single-cell sequencing, spatial transcriptomics, pathological image analysis, TCGA multi-omics analysis and in vitro experimental validation to comprehensively investigate CDKN2A distribution, expression, epigenetic modification, regulation and genomic features in colorectal cancer cells. We further explored the associations between CDKN2A and cellular pathway, immune infiltration and spatial signal communication.

RESULTS

Our findings showed an increasing trend in cuproptosis in the trajectory of tumor progression, accompanied by an upward trend of CDKN2A. CDKN2A underwent transcriptional activation by MEF2D and via the SNHG7/miR-133b axis, upregulating glycolysis, copper metabolism and copper ion efflux. CDKN2A likely drives epithelial-mesenchymal transition (EMT) and progression by activating Wnt signaling. CDKN2A is associated with high genomic instability and sensitivity to radiation and chemotherapy. Tumor regions expressing CDKN2A exhibit distinctive SPP1+ tumor-associated macrophage (TAM) infiltration and MMP7 enrichment, along with unique signaling crosstalk with adjacent areas.

CONCLUSIONS

CDKN2A mediates cuproptosis resistance through regulating glycolysis and copper homeostasis, accompanied by a malignant phenotype and pro-tumor niche. Radiation and chemotherapy are expected to potentially serve as therapeutic approaches for cuproptosis-resistant colorectal cancer with high CDKN2A expression.

EXPRESSION OF SPP1 AND SPARC GENES IN TUMOR TISSUE OF PATIENTS WITH BREAST CANCER

BACKGROUND

Breast cancer (BCa) is one of the most common oncological diseases in women in Ukraine and worldwide, which determines the need to search for new diagnostic and prognostic markers. In this aspect, the study of multicellular proteins, in particular osteopontin (OPN) and osteonectin (ON), in BCа tissue is relevant. The aim of the work was to investigate the expression of SPP1 and SPARC at the mRNA and protein levels in BCa tissue and to assess their relationship with the main clinicopathological BCa characteristics and the survival rates of patients.

MATERIALS AND METHODS

The work was based on the analysis of the results of the examination and treatment of 60 patients with stage II-III BCa and 15 patients with breast fibroadenomas. SPP1 and SPARC mRNA levels were determined by real-time PCR. The study of the expression of protein products of the SPP1 and SPARC genes was carried out by the immunohistochemical method.

RESULTS

We have established that the BCa tissue was characterized by 3.5 (p < 0.05) and 7.4 (p < 0.05) lower levels of SPP1 and SPARC mRNA, respectively, compared to the tissue of benign neoplasms, while OPN and ON expression levels were 1.6 (p < 0.05) and 5.6 (p < 0.05) times higher, respectively, compared to fibroadenoma tissue. The analysis of the relationship between the expression of SPP1 and SPARC at the protein and mRNA levels in BCa tissue and the main clinicopathological BCa characteristics revealed its dependence on the presence of metastases in regional lymph nodes, differentiation grade, and the molecular BCa subtype. Also, high expression levels of SPP1 and OPN were associated with worse patient survival rates.

CONCLUSION

The obtained results indicate the perspective of using SPP1 and SPARC expression indices in BCa tissue to assess the aggressiveness of the cancer course and optimize the tactics of treating patients.

Distinct fibroblast subpopulations associated with bone, brain or intrapulmonary metastasis in advanced non-small-cell lung cancer

BACKGROUND

Bone or brain metastases may develop in 20-40% of individuals with late-stage non-small-cell lung cancer (NSCLC), resulting in a median overall survival of only 4-6 months. However, the primary lung cancer tissue's distinctions between bone, brain and intrapulmonary metastases of NSCLC at the single-cell level have not been underexplored.

METHODS

We conducted a comprehensive analysis of 14 tissue biopsy samples obtained from treatment-naïve advanced NSCLC patients with bone (n = 4), brain (n = 6) or intrapulmonary (n = 4) metastasis using single-cell sequencing originating from the lungs. Following quality control and the removal of doublets, a total of 80 084 cells were successfully captured.

RESULTS

The most significant inter-group differences were observed in the fraction and function of fibroblasts. We identified three distinct cancer-associated fibroblast (CAF) subpopulations: myofibroblastic CAF (myCAF), inflammatory CAF (iCAF) and antigen-presenting CAF (apCAF). Notably, apCAF was prevalent in NSCLC with bone metastasis, while iCAF dominated in NSCLC with brain metastasis. Intercellular signalling network analysis revealed that apCAF may play a role in bone metastasis by activating signalling pathways associated with cancer stemness, such as SPP1-CD44 and SPP1-PTGER4. Conversely, iCAF was found to promote brain metastasis by activating invasion and metastasis-related molecules, such as MET hepatocyte growth factor. Furthermore, the interaction between CAFs and tumour cells influenced T-cell exhaustion and signalling pathways within the tumour microenvironment.

CONCLUSIONS

This study unveils the direct interplay between tumour cells and CAFs in NSCLC with bone or brain metastasis and identifies potential therapeutic targets for inhibiting metastasis by disrupting these critical cell-cell interactions.

Overexpression of SPP1 is a prognostic indicator of immune infiltration in lung adenocarcinoma

OBJECTIVE

The extracellular phosphoprotein, secreted phosphoprotein 1 (SPP1), plays a crucial role in various tumors and regulating the immune system. This study aimed to evaluate its prognostic value and relationship to immune infiltration in lung adenocarcinoma (LUAD).

METHODS

In the TCGA and GEO datasets, the information on clinic and transcriptome analysis of SPP1 in non-small-cell lung cancer (NSCLC) was examined accordingly. The association of SPP1 expression with overall survival and clinicopathologic characteristics was investigated by univariate and multivariate analysis. CancerSEA database was utilized to investigate the role of SPP1 at the cellular level by single-cell analysis. Additionally, the CIBERSORT algorithm was utilized to assess the correlation among the immune cells that infiltrated.

RESULTS

NSCLC tissues exhibited a notable rise in SPP1 expression compared with that of normal tissues. Furthermore, the overexpression of SPP1 was substantially associated with clinicopathological features and unfavorable survival outcomes in individuals with LUAD, whereas no such correlation was observed in lung squamous cell carcinoma. Immune cells that infiltrate tumors and their corresponding genes were associated with SPP1 expression levels in LUAD.

CONCLUSIONS

SPP1 is a reliable indicator for assessing LUAD immune infiltration status and prognosis. With this approach, SPP1 can help earlier LUAD diagnosis and act as a possible immunotherapy target.

SPP1, a potential therapeutic target and biomarker for lung cancer: functional insights through computational studies

NIH reported 128 different types of cancer of which lung cancer is the leading cause of mortality. Globally, it is estimated that on average one in every seventeen hospitalized patients was deceased. There are plenty of studies that have been reported on lung cancer draggability and therapeutics, but yet a protein that plays a central specific to cure the disease remains unclear. So, this study is designed to identify the possible therapeutic targets and biomarkers that can be used for the potential treatment of lung cancers. In order to identify differentially expressed genes, 39 microarray datasets of lung cancer patients were obtained from various demographic regions of the GEO database available at NCBI. After annotating statistically, 6229 up-regulated genes and 10324 down-regulated genes were found. Out of 17 up-regulated genes and significant genes, we selected SPP1 (osteopontin) through virtual screening studies. We found functional interactions with the other cancer-associated genes such as VEGF, FGA, JUN, EGFR, and TGFB1. For the virtual screening studies,198 biological compounds were retrieved from the ACNPD database and docked with SPP1 protein (PDBID: 3DSF). In the results, two highly potential compounds secoisolariciresinol diglucoside (-12.9 kcal/mol), and Hesperidin (-12.0 kcal/mol) showed the highest binding affinity. The stability of the complex was accessed by 100 ns simulation in an SPC water model. From the functional insights obtained through these computational studies, we report that SPP1 could be a potential biomarker and successive therapeutic protein target for lung cancer treatment.

BRIX1 promotes ribosome synthesis and enhances glycolysis by selected translation of GLUT1 in colorectal cancer

BACKGROUND

Ribosome biogenesis protein BRX1 homolog (BRIX1) is critically required for the synthesis of the 60S ribosome subunit. However, the role and mechanism of BRIX1 in colorectal cancer (CRC) remain unclear.

METHODS

Kyoto Encyclopedia of Gene and Genome pathway and Gene Ontology analyses were used for bioinformatics analysis. The rRNA levels were detected in CRC tissues and cells. Nascent RNA synthesis was detected via cellular immunofluorescence. The correlation was analyzed between patient Positron Emission Tomography-Computed Tomography (PET-CT) values and their BRIX1 expression. The extracellular acidification rate (ECAR) and oxygen consumption rate were determined via live metabolic analyses. Polysome fractions were collected for BRIX1 mRNA used in translation. The orthotopic model and Cell Counting Kit-8 (CCK8) assay were used to assess BRIX1 function in CRC.

RESULTS

BRIX1 is a core protein involved in ribosome-related pathway changes in CRC. Gene Ontology analysis showed that BRIX1 was primarily enriched in ribosome assembly and ribosome biogenesis pathways. In fresh CRC tissue, rRNA levels (5S, 5.8S, 18S and 28S) were higher in the BRIX1 high-expression group than in the BRIX1 low-expression group. Similarly, BRIX1 knockdown significantly decreased rRNA levels for 5S, 5.8S, 18S and 28S in CRC cells, whereas overexpression of BRIX1 significantly increased these levels. In addition, BRIX1 knockdown inhibited nascent RNA synthesis in CRC cells. In clinical data analysis, BRIX1 expression was related to the glucose uptake in PET-CT. BRIX1 knockdown significantly decreased the ECAR value, glucose uptake and lactic acid production in CRC cells, whereas BRIX1 overexpression significantly increased these. Furthermore, BRIX1 knockdown significantly decreased the protein expression of GLUT1, whereas BRIX1 overexpression significantly increased this; however, expression of BRIX1 mRNA was unaffected in either case. Blocking glycolysis by si-GLUT1 or galactose reversed BRIX1 promotion of glycolysis and cell proliferation in CRC cells.

A pan-cancer analysis indicates long noncoding RNA HAND2-AS1 as a potential prognostic, immunomodulatory and therapeutic biomarker in various cancers including colorectal adenocarcinoma

The HAND2-AS1 (HAND2 Antisense RNA 1) Long noncoding RNA (lncRNA) has emerged as a participant in the initiation of various cancer types, underscoring its pivotal involvement in both oncological processes and immune responses. To gain deeper insights into the functional nuances of HAND2-AS1 and identify novel avenues for cancer immunotherapy, a comprehensive evaluation of this gene was undertaken. Here, based on the co-expression network analysis and construction of interacting lncRNA-mRNA genes, we introduce the HAND2-AS1 lncRNA, emphasizing its key roles in tumorigenesis and immune regulation. Our study spans across 33 distinct cancer types, revealing the HAND2-AS1's aberrant expression patterns, methylation variations, mutational signatures, and immune engagement. Across a majority of tumors, HAND2-AS1 exhibited a propensity for down-regulation, remarkably an association with poor survival outcomes. The outcomes of functional enrichment analyses strongly suggest HAND2-AS1's engagement in tumor progression and its association with various immune pathways across diverse tumor classifications. Additionally, a positive correlation emerged between HAND2-AS1 expression and the infiltration levels of key immune cells, encompassing not only immunosuppressive entities such as tumor-associated macrophages, cancer-associated fibroblasts, and Tregs, but also immune effector cells like NK cells and CD8+ T cells, spanning a pan-cancer context. Furthermore, the differential expression of HAND2-AS1 appears to have downstream consequences on various pathways, thus implicating it as a potential regulator in diverse cancer types. Finally, we have employed CRC tumor and normal samples to carry out clinical validation of HAND2-AS1. Our study unveils HAND2-AS1's potential as a pan-cancer tumor suppressor, and its essential role in the tumorigenesis and immune surveillance. The increased HAND2-AS1 expression emerges as a promising candidate for prognostic evaluation, therapeutic strategy, and a focal point for immunotherapeutic interventions.

ANGPTL2+cancer-associated fibroblasts and SPP1+macrophages are metastasis accelerators of colorectal cancer

Background

Liver metastasis (LM) is a leading cause of cancer-related deaths in CRC patients, whereas the associated mechanisms have not yet been fully elucidated. Therefore, it is urgently needed to deeply explore novel metastasis accelerators and therapeutic targets of LM-CRC.

Methods

The bulk RNA sequencing data and clinicopathological information of CRC patients were enrolled from the TCGA and GEO databases. The single-cell RNA sequencing (scRNA-seq) datasets of CRC were collected from and analyzed in the Tumor Immune Single-cell Hub (TISCH) database. The infiltration levels of cancer-associated fibroblasts (CAFs) and macrophages in CRC tissues were estimated by multiple immune deconvolution algorithms. The prognostic values of genes were identified by the Kaplan-Meier curve with a log-rank test. GSEA analysis was carried out to annotate the significantly enriched gene sets. The biological functions of cells were experimentally verified.

Results

In the present study, hundreds of differentially expressed genes (DEGs) were selected in LM-CRC compared to primary CRC, and these DEGs were significantly associated with the regulation of endopeptidase activity, blood coagulation, and metabolic processes. Then, SPP1, CAV1, ANGPTL2, and COLEC11 were identified as the characteristic DEGs of LM-CRC, and higher expression levels of SPP1 and ANGPTL2 were significantly associated with worse clinical outcomes of CRC patients. In addition, ANGPTL2 and SPP1 mainly distributed in the tumor microenvironment (TME) of CRC tissues. Subsequent scRNA-seq analysis demonstrated that ANGPTL2 and SPP1 were markedly enriched in the CAFs and macrophages of CRC tissues, respectively. Moreover, we identified the significantly enriched gene sets in LM-CRC, especially those in the SPP1+macrophages and ANGPTL2+CAFs, such as the HALLMARK_EPITHELIAL_MESENCHYMAL_TRANSITION and the HALLMARK_COMPLEMENT. Finally, our in vitro experiments proved that ANGPTL2+CAFs and SPP1+macrophages promote the metastasis of CRC cells.

Conclusion

Our study selected four characteristic genes of LM-CRC and identified ANGPTL2+CAFs and SPP1+macrophages subtypes as metastasis accelerators of CRC which provided a potential therapeutic target for LM-CRC.

A previously uncharacterized Factor Associated with Metabolism and Energy (FAME/C14orf105/CCDC198/1700011H14Rik) is related to evolutionary adaptation, energy balance, and kidney physiology

In this study we use comparative genomics to uncover a gene with uncharacterized function (1700011H14Rik/C14orf105/CCDC198), which we hereby name FAME (Factor Associated with Metabolism and Energy). We observe that FAME shows an unusually high evolutionary divergence in birds and mammals. Through the comparison of single nucleotide polymorphisms, we identify gene flow of FAME from Neandertals into modern humans. We conduct knockout experiments on animals and observe altered body weight and decreased energy expenditure in Fame knockout animals, corresponding to genome-wide association studies linking FAME with higher body mass index in humans. Gene expression and subcellular localization analyses reveal that FAME is a membrane-bound protein enriched in the kidneys. Although the gene knockout results in structurally normal kidneys, we detect higher albumin in urine and lowered ferritin in the blood. Through experimental validation, we confirm interactions between FAME and ferritin and show co-localization in vesicular and plasma membranes.

Metastatic colorectal cancer: mechanisms and emerging therapeutics

Metastatic colorectal cancer (mCRC) remains a lethal disease with an approximately 14% 5-year survival rate. While early-stage colorectal cancer (CRC) can be cured by surgery with or without adjuvant chemotherapy, mCRC cannot be eradicated due to a large burden of disseminated cancer cells comprising therapy-resistant metastasis-competent cells. To address this gap, recent studies have focused on further elucidating the molecular mechanisms underlying colorectal metastasis and recognizing the limitations of available therapeutic interventions. In this review, we discuss newfound factors that regulate CRC cell dissemination and colonization of distant organs, such as genetic mutations, identification of metastasis-initiating cells (MICs), epithelial-mesenchymal transition (EMT), and the tumor microenvironment (TME). We also review current treatments for mCRC, therapeutic regimens undergoing clinical trials, and trending preclinical studies being investigated to target treatment-resistant mCRC.

LncRNA TP73-AS1 enhances the malignant properties of colorectal cancer by increasing SPP-1 expression through miRNA-539-5p sponging

Colorectal cancer (CC) is one of the most aggressive cancers, with a high mortality rate worldwide. This study focuses on the mechanism of CC to explore the effective therapeutic targets. We determined that LncRNA TP73-AS1 (TP-73-AS1) expression was significantly increased in CC tissues. TP73-AS1 silencing dynamically inhibited the proliferation, migratory and invasive capacity in CC cells. Mechanistically, we found that TP73-AS1 targeted miR-539-5p and miR-539-5p silencing could promote the migratory and invasive capacity in CC cells. Further study also confirmed that SPP-1 expression significantly increased after co-transfection of miR-539-5p inhibitors. Knockdown the SPP-1 can reverse malignant properties of CC cells. Si-TP73-AS1 suppressed the tumor growth of CC cells in vivo. In a word, we found that TP73-AS1 enhances the malignant properties of colorectal cancer by increasing SPP-1 expression through miRNA-539-5p sponging. And our study provides a potential therapeutic target of CC.

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.

Identification of the six-hormone secretion-related gene signature as a prognostic biomarker for colon adenocarcinoma

BACKGROUND

Colon adenocarcinoma (COAD) is a globally prevalent cancer, with hormone secretion playing a crucial role in its progression. Despite this, there is limited understanding of the impact of hormone secretion on COAD prognosis. This study aimed to establish a prognostic signature based on hormone secretion-related genes and to elucidate the potential functional mechanisms of these genes in COAD.

METHODS

Using data from The Cancer Genome Atlas COAD cohort (TCGA-COAD), six hormone secretion-related genes were identified (CYP19A1, FOXD1, GRP, INHBB, SPP1, and UCN). These genes were used to develop a Hormone secretion score (HSS), which was then evaluated using the Kaplan-Meier curve and multivariable Cox analysis. The HSS model was further validated with external GEO cohorts (GSE41258, GSE39582, and GSE87211). Functional enrichment analyses were performed, and the CIBERSORT and TIDE algorithms were used to assess tumor infiltration.

RESULTS

The study developed a prognostic signature, dividing patients into HSS-high and HSS-low groups. The HSS-high group showed a notably worse prognosis within the TCGA-COAD dataset and in three independent datasets: GSE41258, GSE39582, and GSE87211. Moreover, the HSS-high group predicted a shorter overall survival rate in patients maintaining microsatellite stability (MSS). The functional analysis associated HSS-high with the hypoxic, epithelial-mesenchymal transition (EMT), and TGF-β signaling pathways and correlated with distant and lymph node metastases. The tumor immune microenvironment analysis revealed an elevated CIBERSORT score in the HSS-high group, suggesting an association with tumor metastasis. Further, the HSS-high group showed a higher TIDE score, indicating that patients with high HSS scores are less likely to benefit from Immune Checkpoint Inhibitor (ICI) therapy.

CONCLUSIONS

This study demonstrated the prognostic significance of a HSS signature based on six hormone secretion-related genes in COAD. The findings suggest that this gene signature may serve as a reliable biomarker for predicting survival outcomes in COAD patients.

Machine Learning Predicts the Oxidative Stress Subtypes Provide an Innovative Insight into Colorectal Cancer

So far, it has been reached the academic consensus that the molecular subtypes are via genomic heterogeneity and immune infiltration patterns. Considering that oxidative stress (OS) is involved in tumorigenesis and prognosis prediction, we propose an innovative classification of colorectal cancer- (CRC-) OS subtypes. We obtain three datasets from The Cancer Genome Atlas Program (TCGA) and Gene Expression Omnibus (GEO) online databases. 1399 OS-related genes were selected from the GeneCards database. We remove the batch effect before conducting differentially expressed genes (DEGs) analyses between normal and tumor samples. Nonnegative matrix factorization (NMF) was used to perform an unsupervised cluster. Lasso regression and Cox regression were used to construct the signature model. DEGs, robust rank aggregation, and protein-protein interaction networks were used to select hub genes, and then use hub genes to predict OS subtypes by random forest algorithms. NMF identifies two OS-related subtypes of CRC patients. Eight OS-related gene signatures were built to predict the outcome of patients, based on the DEGs between two subtypes. A total of 61 DEGs overlap each dataset, and the RRA analysis shows that 17 genes are important in these three datasets, and 15 genes are shared genes between the two methods. PPI network suggests that five hub genes are confirmed, they are SPP1, SERPINE1, CAV1, PDGFRB, and PLAU. These five hub genes could predict the OS-related subtype of CRC accurately with AUC equal to 0.771. In our study, we identify two OS-related subtypes, which will provide an innovative insight into colorectal cancer.

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.

Establishment of a Prognostic Model for Hepatocellular Carcinoma Based on Bioinformatics and the Role of NR6A1 in the Progression of HCC

BACKGROUND AND AIMS

Generally acceptable prognostic models for hepatocellular carcinoma (HCC) are not available. This study aimed to establish a prognostic model for HCC by identifying immune-related differentially expressed genes (IR-DEGs) and to investigate the potential role of NR6A1 in the progression of HCC.

METHODS

Bioinformatics analysis using The Cancer Genome Atlas and ImmPort databases was used to identify IR-DEGs. Lasso Cox regression and multivariate Cox regression analysis were used to establish a prognostic model of HCC. Kaplan-Meier analysis and the receiver operating characteristic (ROC) curves were used to evaluate the performance of the prognostic model, which was further verified in the International Cancer Genome Consortium (ICGC) database. Gene set enrichment analysis was used to explore the potential pathways of NR6A1. Cell counting kit 8, colony formation, wound healing, and Transwell migration assays using Huh7 cells, and tumor formation models in nude mice were conducted.

RESULTS

A prognostic model established based on ten identified IR-DEGs including HSPA4, FABP6, MAPT, NDRG1, APLN, IL17D, LHB, SPP1, GLP1R, and NR6A1, effectively predicted the prognosis of HCC patients, was confirmed by the ROC curves and verified in ICGC database. NR6A1 expression was significantly up-regulated in HCC patients, and NR6A1 was significantly associated with a low survival rate. Gene set enrichment analysis showed the enrichment of cell cycle, mTOR, WNT, and ERBB signaling pathways in patients with high NR6A1 expression. NR6A1 promoted cell proliferation, invasiveness, migration, and malignant tumor formation and growth in vitro and in vivo.

CONCLUSIONS

An effective prognostic model for HCC, based on a novel signature of 10 immune-related genes, was established. NR6A1 was up-regulated in HCC and was associated with a poor prognosis of HCC. NR6A1 promoted cell proliferation, migration, and growth of HCC, most likely through the cell cycle, mTOR, WNT, and ERBB signaling pathways.

SPP1 facilitates cell migration and invasion by targeting COL11A1 in lung adenocarcinoma

Background

Secreted phosphoprotein 1 (SPP1), an extracellular secreted glycol phosphoprotein, is closely related to tumor biologies, such as proliferation, migration, and invasion. However, the role and biological function of SPP1 in lung adenocarcinoma (LUAD) was still ambiguous.

Methods

SPP1 expression in LUAD tissues and its associations with clinical features and prognosis was investigated using meta-analysis, immunohistochemistry (IHC) staining methods, and quantitative real-time polymerase chain reaction (qRT-PCR). Moreover, the potential mechanism related to SPP1 was identified by using the Gene Set Enrichment Analysis (GSEA) method. A series of function assays were conducted to determine the biological role of SPP1 in LUAD cell migration and invasion in vitro and vivo. The co-expressed genes of SPP1 were obtained and verified by western blot assays. The influence of SPP1 on Collagen type XI alpha 1 (COL11A1) expression and epithelial-mesenchymal transition (EMT) markers was analyzed using western blot assays.

Results

The expression of SPP1 in LUAD tissues and cells was significantly higher than that in normal tissues and cells. And positively associations of SPP1 expression with TNM stage, lymph node metastasis, and invasion depth were observed. Patients with high SPP1 expression had unfavorable survival. The multivariable Cox regression analysis revealed that SPP1 expression was an independent prognostic factor of LUAD patients. Furthermore, downregulation of SPP1 could inhibit cell migration and invasion both in vitro and vivo, reduce the expression of epithelial marker (E-cadherin), and increase the expression of mesenchymal markers (N-cadherin and vimentin). Using bioinformatics and western blot assays, we confirmed that COL11A1 acted as the downstream of SPP1, and SPP1 knockdown could significantly downregulate the COL11A1 expression. Importantly, suppression of cell migration and invasion and the expression changes of EMT markers induced by SPP1 downregulation could be reversed by COL11A1 overexpression.

Conclusions

SPP1 facilitates cell migration and invasion by upregulating COL11A1 expression and that acts as a potential biomarker of metastasis and prognosis for LUAD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-022-02749-x.

Comprehensive analysis of potential cellular communication networks in advanced osteosarcoma using single-cell RNA sequencing data

Osteosarcoma (OS) is a common bone cancer in children and adolescents, and metastasis and recurrence are the major causes of poor treatment outcomes. A better understanding of the tumor microenvironment is required to develop an effective treatment for OS. In this paper, a single-cell RNA sequencing dataset was taken to a systematic genetic analysis, and potential signaling pathways linked with osteosarcoma development were explored. Our findings revealed 25 clusters across 11 osteosarcoma tissues, with 11 cell types including “Chondroblastic cells”, “Osteoblastic cells”, “Myeloid cells”, “Pericytes”, “Fibroblasts”, “Proliferating osteoblastic cells”, “Osteoclasts”, “TILs”, “Endothelial cells”, “Mesenchymal stem cells”, and “Myoblasts”. The results of Cell communication analysis showed 17 potential cellular communication networks including “COLLAGEN signaling pathway network”, “CD99 signaling pathway network”, “PTN signaling pathway network”, “MIF signaling pathway network”, “SPP1 signaling pathway network”, “FN1 signaling pathway network”, “LAMININ signaling pathway network”, “FGF signaling pathway network”, “VEGF signaling pathway network”, “GALECTIN signaling pathway network”, “PERIOSTIN signaling pathway network”, “VISFATIN signaling pathway network”, “ITGB2 signaling pathway network”, “NOTCH signaling pathway network”, “IGF signaling pathway network”, “VWF signaling pathway network”, “PDGF signaling pathway network”. This research may provide novel insights into the pathophysiology of OS’s molecular processes.

DDX39B drives colorectal cancer progression by promoting the stability and nuclear translocation of PKM2

Metastasis is a major cause of colorectal cancer (CRC) mortality, but its molecular mechanisms are still not fully understood. Here, we show that upregulated DDX39B correlates with liver metastases and aggressive phenotypes in CRC. DDX39B is an independent prognostic factor associated with poor clinical outcome in CRC patients. We demonstrate that Sp1 potently activates DDX39B transcription by directly binding to the GC box of the DDX39B promoter in CRC cells. DDX39B overexpression augments the proliferation, migration, and invasion of CRC cells, while the opposite results are obtained in DDX39B-deficient CRC cells. Mechanistically, DDX39B interacts directly with and stabilizes PKM2 by competitively suppressing STUB1-mediated PKM2 ubiquitination and degradation. Importantly, DDX39B recruits importin α5 to accelerate the nuclear translocation of PKM2 independent of ERK1/2-mediated phosphorylation of PKM2, leading to the transactivation of oncogenes and glycolysis-related genes. Consequently, DDX39B enhances glucose uptake and lactate production to activate Warburg effect in CRC. We identify that Arg319 of DDX39B is required for PKM2 binding as well as PKM2 nuclear accumulation and for DDX39B to promote CRC growth and metastasis. In addition, blocking PKM2 nuclear translocation or treatment with glycolytic inhibitor 2-deoxy-D-glucose efficiently abolishes DDX39B-triggered malignant development in CRC. Taken together, our findings uncover a key role for DDX39B in modulating glycolytic reprogramming and aggressive progression, and implicate DDX39B as a potential therapeutic target in CRC.

SPP1 is a biomarker of cervical cancer prognosis and involved in immune infiltration

Background: Cervical cancer is the fourth commonly occurred cancer in women around the world. However, it still lacks effective approaches to improve current prognosis of cervical cancer and prevent metastasis.

Objective: We aim to discover a promising biomarker for cervical cancer prognosis by utilizing bioinformatics analysis.

Methods: Gene expression was analyzed by the datasets from The Cancer Genome Atlas Program-Cervical squamous cell carcinoma and endocervical adenocarcinoma (TCGA-CESC) dataset and three independent patient cohort datasets. Biological process and pathway enrichment were performed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis. Immune infiltration was analyzed through TISIDB tool.

Results: SPP1 gene was highly expressed in cervical cancer tissues. In addition, SPP1 was positively correlated to advanced CESC stages and nodal metastasis status. SPP1 co-expressed genes are mainly enriched in immunological processes. Furthermore, SPP1 expression is involved in immune infiltration level, in which several tumour infiltrating lymphocytes are correlated with SPP1. SPP1 overexpression promotes a wide spectrum of chemokines and immunoinhibiors which contribute to CESC progression.

Conclusions: SPP1 is a promising biomarker and a prognostic factor of CESC. Tumour infiltrating lymphocytes are also possibly regulated by SPP1. Our study suggests that investigation on SPP1 is a new direction for CESC therapy.

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.

Alternative polyadenylation mechanism links secreted phosphoprotein 1 gene to glioblastoma

BACKGROUND

Secreted phosphoprotein 1 (SPP1), also known as osteopontin (OPN), is a multifunctional protein expressed in diverse normal tissues, and functionally is involved in cellular matrix and signaling processes. Many studies have linked SPP1 to pathophysiological conditions including cancer.

OBJECTIVE

The aim of this study is to evaluate the 3'UTR length of SPP1 gene in glioblastoma cell line.

METHODS

3' Rapid Amplification of cDNA End (3'-RACE) were used to determine the 3' end of SPP1 gene. APAatlas data base, GEPIA web server, and miRcode were also used to extract related information and bioinformatic analysis part.

RESULTS

In this study we show that SPP1 gene undergoes Alternative cleavage and Polyadenylation (APA) mechanism, by which it generates two 3' termini, longer isoform and shorter isoform, in glioblastoma derived cell line, U87-MG. Further bioinformatic analysis reveals that SPP1 alternative 3'UTR (aUTR), which is absent in shorter isoform, is targeted by two families of microRNAs-miR-181abcd/4262 and miR-154/872. These miRNAs also target and perhaps negatively regulate NAP1L1 and ENAH genes that are involved in cell proliferation and cell polarity, respectively. Relative expression difference (RED), obtained from RNA-seq data of diverse normal tissues, representing APA usage appears to be negatively correlated with expression of NAP1L1 and ENAH, emphasizing co-expression of SPP1 longer isoform with these two genes, indicating miRNA sponge function of aUTR (longer 3'UTR). Bioinformatic analysis also shows that in normal brain tissue longer APA isoform of SPP1 is expressed; however shorter isoform appears to be expressed in cancer condition.

CONCLUSION

Together, this study reveals that SPP1 APA isoforms have different pattern in normal and cancerous conditions, which can be considered as a diagnostic and prognostic marker in cancers.

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.

Integrative Analysis of DNA Methylation and Gene Expression Profiling Data Reveals Candidate Methylation-Regulated Genes in Hepatoblastoma

Purpose

This study aimed to identify novel methylation-regulated genes as diagnostic biomarkers and therapeutic targets for hepatoblastoma (HB).

Materials and Methods

The DNA methylation data of 19 HB tumor samples and 10 normal liver samples from the GSE78732 dataset and gene expression profiling data of 53 HB tumor samples and 14 normal liver samples from the GSE131329 dataset and 31 HB tumor samples and 32 normal liver samples from the GSE133039 dataset were downloaded form the Gene Expression Omnibus database. Next, differentially methylated genes (DMGs) and differentially expressed genes (DEGs) were identified. Venn diagrams were used to identify methylation-regulated genes. The VarElect online tool was selected to identify key methylation-regulated genes, and a protein–protein interaction (PPI) network was constructed to show the interactions among key methylation-regulated genes and DEGs. Finally, Gene Ontology annotation and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were performed to investigate the potential regulatory mechanisms of key methylation-regulated genes.

Results

A total of 457 DMGs and 1597 DEGs were identified between the HB and normal liver samples. After DMGs and DEGs overlapping, 22 hypomethylated and upregulated genes and 19 hypermethylated and downregulated genes in HB were screened. Survival analysis revealed that 13 methylation-regulated genes were associated with the prognosis of liver cancer. Moreover, SPP1, UHRF1, and HEY1 were selected as the key DNA methylation-regulated genes. The PPI network revealed that all of them could affect TP53, while both UHRF1 and HEY1 could influence BMP4. Enrichment analysis suggested that the DEGs were involved in TP53-related pathways, including the cell cycle and p53 signaling pathway. Finally, SPP1, UHRF1, and HEY1 were hypomethylated and upregulated in the HB samples compared with those in the normal liver samples.

Conclusion

SPP1, UHRE1, and HEY1 may play important roles in HB and be used as biomarkers for its diagnosis and treatment.

Comprehensive Analysis to Identify the Epithelial-Mesenchymal Transition-Related Immune Signatures as a Prognostic and Therapeutic Biomarkers in Hepatocellular Carcinoma

Background: Hepatocellular carcinoma (HCC) is a highly heterogeneous disease with the high rates of the morbidity and mortality due to the lack of the effective prognostic model for prediction.

Aim: To construct a risk model composed of the epithelial–mesenchymal transition (EMT)-related immune genes for the assessment of the prognosis, immune infiltration status, and chemosensitivity.

Methods: We obtained the transcriptome and clinical data of the HCC samples from The Cancer Genome Atlas (TCGA) and The International Cancer Genome Consortium (ICGC) databases. The Pearson correlation analysis was applied to identify the differentially expressed EMT-related immune genes (DE-EMTri-genes). Subsequently, the univariate Cox regression was introduced to screen out the prognostic gene sets and a risk model was constructed based on the least absolute shrinkage and selection operator-penalized Cox regression. Additionally, the receiver operating characteristic (ROC) curves were plotted to compare the prognostic value of the newly established model compared with the previous model. Furthermore, the correlation between the risk model and survival probability, immune characteristic, and efficacy of the chemotherapeutics were analyzed by the bioinformatics methods.

Results: Six DE-EMTri-genes were ultimately selected to construct the prognostic model. The area under the curve (AUC) values for 1-, 2-, and 3- year were 0.773, 0.721, and 0.673, respectively. Stratified survival analysis suggested that the prognosis of the low-score group was superior to the high-score group. Moreover, the univariate and multivariate analysis indicated that risk score [hazard ratio (HR) 5.071, 95% CI 3.050, 8.432; HR 4.396, 95% CI 2.624, 7.366; p < 0.001] and stage (HR 2.500, 95% CI 1.721, 3.632; HR 2.111, 95% CI 1.443, 3.089; p < 0.001) served as an independent predictive factors in HCC. In addition, the macrophages, natural killer (NK) cells, and regulatory T (Treg) cells were significantly enriched in the high-risk group. Finally, the patients with the high-risk score might be more sensitive to cisplatin, doxorubicin, etoposide, gemcitabine, and mitomycin C.

Conclusion: We established a reliable EMTri-genes-based prognostic signature, which may hold promise for the clinical prediction.

Insights into homeobox B9: a propeller for metastasis in dormant prostate cancer progenitor cells

BACKGROUND

Metastasis is the major cause of treatment failure and cancer-related deaths in prostate cancer (PCa) patients. Our previous study demonstrated that a CD44⁺ subpopulation isolated from PCa cells or tumours possesses both stem cell properties and metastatic potential, serving as metastatic prostate cancer stem cells (mPCSCs) in PCa metastasis. However, the underlying mechanisms remain unknown.

METHODS

In this study, we established PCa models via the orthotopic and subcutaneous implantation of different human PCa cancer cell lines, and compared the metastatic efficacy, after which process function analysis of target genes was pinpointed.

RESULTS

Several novel differentially expressed genes (DEGs) between orthotopic and ectopic tumours were identified. Among them, human homeobox B9 (HOXB9) transcription factor was found to be essential for PCa metastasis, as evidenced by the diminished number of lung metastatic foci derived from orthotopic implantation with HOXB9-deficient CWR22 cells, compared with the control. In addition, HOXB9 protein expression was upregulated in PCa tissues, compared with paracancer and benign prostate hyperplasia tissues. It was also positively correlated with Gleason scores. Gain- and loss-of-function assays showed that HOXB9 altered the expression of various tumour metastasis- and cancer stem cell (CSC) growth-related genes in a transforming growth factor beta (TGFβ)-dependent manner. Moreover, HOXB9 was overexpressed in an ALDH⁺CD44⁺CXCR4⁺CD24⁺ subpopulation of PCa cells that exhibited enhanced TGFβ-dependent tumorigenic and metastatic abilities, compared with other isogenic PCa cells. This suggests that HOXB9 may contribute to PCa tumorigenesis and metastasis via TGFβ signalling. Of note, ALDH⁺CD44⁺CXCR4⁺CD24⁺-PCa cells exhibited resistance to castration and antiandrogen therapy and were present in human PCa tissues.

CONCLUSION

Taken together, our study identified HOXB9 as a critical regulator of metastatic mPCSC behaviour. This occurs through altering the expression of a panel of CSC growth- and invasion/metastasis-related genes via TGFβ signalling. Thus, targeting HOXB9 is a potential novel therapeutic PCa treatment strategy.

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.

Identification of Hub Gene TIMP1 and Relative ceRNAs Regulatory Network in Colorectal Cancer

Objective

This study aimed to discover the ceRNAs network in the pathophysiological development of human colorectal cancer (CRC) and to screen biomarkers for target therapy and prognosis by using integrated bioinformatics analysis.

Methods

Data on gene expressions of mRNAs, miRNAs, and circRNAs and clinical information were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases, respectively. Differentially expressed mRNAs (DEmRNAs) were identified by using the DESeq2 package of R software. Functional enrichment analysis was conducted using the ClusterProfiler package of R software. The protein–protein interaction (PPI) network was shown by the STRING website. Survival analysis of hub genes was performed using the survival package in R software. Interactions among hub genes, differentially expressed miRNAs (DEmiRNAs), and differentially expressed circRNAs (DEcircRNAs) were used to construct the ceRNAs network.

Results

A total of 412 DEmRNAs including 82 upregulated and 330 downregulated genes were screened out between 473 CRC and 41 normal samples. Two hundred and sixty DEcircRNAs including 253 upregulated and 7 downregulated genes were altered between 23 CRC and 23 normal samples. One hundred and ninety DEmiRNAs including 82 upregulated and 108 downregulated genes were obtained between 450 CRC and 8 normal samples. A ceRNAs and PPI network were successfully constructed, and TIMP1 associated with prognosis was employed.

Conclusion

The present study identified a novel circRNAs-miRNAs-mRNA ceRNAs network, which implied that TIMP1 and related miRNAs, circRNAs were potential biomarkers underlying the development of CRC, providing new insights for survival predictions and therapeutic targets.

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.

Osteopontin as a Regulator of Colorectal Cancer Progression and Its Clinical Applications

Simple Summary

The mortality of colorectal cancer is principally related to metastatic disease at the time of diagnosis or to the growth of initially undetectable micro-metastasis. Current therapeutic strategies are efficient in patients with locally advanced cancer, but are rarely able to cure patients with metastatic disease. Therapeutic failure is mainly associated with drug resistance and an aggressive phenotype. The identification of new biomarkers for micro-metastasis and tumor progression remains an unmet clinical need that should allow for improved patient stratification for optimal treatment and may lead to the identification of novel therapeutic targets. Osteopontin (OPN), a multifunctional protein, has emerged as a potentially valuable biomarker in several cancer types. This review principally describes the molecular mechanisms of OPN that are associated with colorectal cancer (CRC) progression and metastasis, as well as the use of OPN as a clinical biomarker. This review identifies a role for OPN as a biomarker ready for extended clinical application and discusses its use as a therapeutic target.

Abstract

A high expression of the phosphoprotein osteopontin (OPN) has been associated with cancer progression in several tumor types, including breast cancer, hepatocarcinoma, ovarian cancer, and colorectal cancer (CRC). Interestingly, OPN is overexpressed in CRC and is associated with a poor prognosis linked to invasion and metastasis. Here, we review the regulation and functions of OPN with an emphasis on CRC. We examine how epigenetic and genetic regulators interact with the key signaling pathways involved in this disease. Then, we describe the role of OPN in cancer progression, including proliferation, survival, migration, invasion, and angiogenesis. Furthermore, we outline the interest of using OPN as a clinical biomarker, and discuss if and how osteopontin can be implemented as a routine assay in clinical laboratories for monitoring CRC patients. Finally, we discuss the use of OPN an attractive, but challenging, therapeutic target.

Identification of novel hub genes associated with gastric cancer using integrated bioinformatics analysis

Background

Gastric cancer (GC) is one of the most common solid malignant tumors worldwide with a high-recurrence-rate. Identifying the molecular signatures and specific biomarkers of GC might provide novel clues for GC prognosis and targeted therapy.

Methods

Gene expression profiles were obtained from the ArrayExpress and Gene Expression Omnibus database. Differentially expressed genes (DEGs) were picked out by R software. The hub genes were screened by cytohubba plugin. Their prognostic values were assessed by Kaplan–Meier survival analyses and the gene expression profiling interactive analysis (GEPIA). Finally, qRT-PCR in GC tissue samples was established to validate these DEGs.

Results

Total of 295 DEGs were identified between GC and their corresponding normal adjacent tissue samples in E-MTAB-1440, GSE79973, GSE19826, GSE13911, GSE27342, GSE33335 and GSE56807 datasets, including 117 up-regulated and 178 down-regulated genes. Among them, 7 vital upregulated genes (HMMR, SPP1, FN1, CCNB1, CXCL8, MAD2L1 and CCNA2) were selected. Most of them had a significantly worse prognosis except SPP1. Using qRT-PCR, we validated that their transcriptions in our GC tumor tissue were upregulated except SPP1 and FN1, which correlated with tumor relapse and predicts poorer prognosis in GC patients.

Conclusions

We have identified 5 upregulated DEGs (HMMR, CCNB1, CXCL8, MAD2L1, and CCNA2) in GC patients with poor prognosis using integrated bioinformatical methods, which could be potential biomarkers and therapeutic targets for GC treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08358-7.

SNX10 and PTGDS are associated with the progression and prognosis of cervical squamous cell carcinoma

Background

Cervical cancer (CC) is the primary cause of death in women. This study sought to investigate the potential mechanism and prognostic genes of CC.

Methods

We downloaded four gene expression profiles from GEO. The RRA method was used to integrate and screen differentially expressed genes (DEGs) between CC and normal samples. Functional analysis was performed by clusterprofiler. We built PPI network by Search Tool for the Retrieval of Interacting Genes Database (STRING) and selected hub modules via Molecular COmplex Detection (MCODE). CMap database was used to find molecules with therapeutic potential for CC. The hub genes were validated in GEO datasets, Gene Expession Profiling Interactive Analysis (GEPIA), immunohistochemistry, Cox regression analysis, TCGA methylation analysis and ONCOMINE were carried out. ROC curve analysis and GSEA were also performed to describe the prognostic significance of hub genes.

Results

Functional analysis revealed that 147 DEGs were significantly enriched in binding, cell proliferation, transcriptional activity and cell cycle regulation. PPI network screened 30 hub genes, with CDK1 having the strongest connectivity with CC. Cmap showed that apigenin, thioguanine and trichostatin A might be used to treat CC(P < 0.05). Eight genes (APOD, CXCL8, MMP1, MMP3, PLOD2, PTGDS, SNX10 and SPP1) were screened out through GEPIA. Of them, only PTGDS and SNX10 had not appeared in previous studies about CC. The validation in GEO showed that PTGDS showed low expression while SNX10 presented high expression in tumor tissues. Their expression profiles were consistent with the results in immunohistochemistry. ROC curve analysis indicated that the model had a good diagnostic efficiency (AUC = 0.738). GSEA analysis demonstrated that the two genes were correlated with the chemokine signaling pathway (P < 0.05). TCGA methylation analysis showed that patients with lowly-expressed and highly-methylated PTGDS had a worse prognosis than those with highly-expressed and lowly-methylated PTGDS (p = 0.037). Cox regression analysis showed that SNX10 and PTGDS were independent prognostic indicators for OS among CC patients (P = 0.007 and 0.003).

Conclusions

PTGDS and SNX10 showed abnormal expression and methylation in CC. Both genes might have high prognostic value of CC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08212-w.

CTHRC1 promotes liver metastasis by reshaping infiltrated macrophages through physical interactions with TGF-β receptors in colorectal cancer

Metastasis is a major cause of cancer-related deaths. Tumor-intrinsic properties can determine whether tumor metastasis occurs or not. Here, by comparing the gene expression patterns in primary colorectal cancer (CRC) patients with or without metastasis, we found that Collagen Triple Helix Repeat Containing 1 (CTHRC1) in primary CRC served as a metastasis-associated gene. Animal experiments verified that CTHRC1 secreted by CRC cells promoted hepatic metastasis, which was closely correlated with macrophage infiltration. Depletion of macrophages by liposomal clodronate largely abolished the promoting effect of CTHRC1 on CRC liver metastasis. Furthermore, we demonstrated that CTHRC1 modulated macrophage polarization to M2 phenotypes through TGF-β signaling. A mechanistic study revealed that CTHRC1 bound directly to TGF-β receptor II and TGF-β receptor III, stabilized the TGF-β receptor complex, and activated TGF-β signaling. The combination treatment of CTHRC1 monoclonal antibody and anti-PD-1 blocking antibody effectively suppressed CRC hepatic metastasis. Taken together, our data demonstrated that CTHRC1 is an intrinsic marker of CRC metastasis and further revealed that CTHRC1 promoted CRC liver metastasis by reshaping infiltrated macrophages through TGF-β signaling, suggesting that CTHRC1 could be a potential biomarker for the early prediction of and a therapeutic target of CRC hepatic metastasis.

Gene expression profile of epithelial-mesenchymal transition mediators in papillary thyroid cancer

PURPOSE

Platelet derived growth receptor alpha (PDGFRA) promotes the epithelial-mesenchymal transition (EMT) in thyroid follicular cells and is linked to lymphatic metastases in papillary thyroid cancer (PTC). We probed the regulatory network of genes linked to PDGFRA and EMT, comparing matched patient primary tumor and metastatic specimens, as well as engineered cell lines and ex vivo primary cultures with and without PDGFRA.

METHODS

Freshly isolated thyroid tumors with or without metastases, with matching neighboring benign or normal tissue, was isolated for comparative transcriptional analysis using a TaqMan Low Density array (TLDA) assay with genes representing important markers of EMT, cellular adhesion, apoptosis, differentiation, senescence, and signal transduction pathways in thyroid cancer. Transfected primary cultures and immortalized cell lines were also analyzed with respect to PDGFRA expression and cell phenotype.

RESULTS

We reveal the consistent upregulation of serine protease DPP4 and structural protein SPP1 with the progression of PTC to metastatic disease, as well as with PDGFRA expression. Conversely, epithelial integrity gene TFF3 and transcription factor SOX10 were strongly down-regulated. This gene network also includes important mediators of EMT including DSG1, MMP3, MMP9, and BECN. We observed similar genomic changes in ex vivo normal thyroid cells transfected with PDGFRA that also exhibited a partially dedifferentiated phenotype. In particular, we observed lamellopodia with induction of PDGFRA and illustrate that DPP4 and SPP1 were upregulated in this process, with decreased TFF3 and SOX10 as seen in tissue specimens. PDGFRA did decrease nuclear protein levels of differentiation factor TTF1, but not the transcription of TTF1 and PAX8.

CONCLUSIONS

We demonstrate that PDGFRA activates EMT pathways and decreases expression of genes favoring epithelial integrity, pushing follicular cells toward a dedifferentiated phenotype. SPP1 and DPP4, previously linked with adverse outcomes in thyroid cancer, appear to be regulated by PDGFRA. PDGFRA expression promotes metastatic disease through multiple EMT levers that favor formation of an invasive phenotype and increased metalloproteinase expression.

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.

Secreted phosphoprotein-1 accelerates the progression of human colorectal cancer through activating β-catenin signaling

Colorectal cancer (CRC) is a common malignant tumor of the digestive tract and one of the leading causes of cancer-associated mortality. Secreted phosphoprotein-1 (SPP-1) is overexpressed in CRC and promotes cancer progression, but the underlying mechanisms underlying SPP-1 function remain unclear. The present study aimed to explore the effects of Wnt/β-catenin signaling in SPP-1-induced CRC progression. The expression patterns of SPP-1 in CRC tissues were examined using reverse transcription-quantitative (RT-q)PCR, western blotting and immunohistochemistry. SPP-1 expression in cells was assessed using RT-qPCR and western blotting. Cell-Counting Kit-8, flow cytometry and tumor-burdened mice experiments were used to determine cell proliferation, apoptosis and in vivo tumor formation abilities. The results showed that SPP-1 expression was markedly elevated in CRC tissues and cells compared with that in normal colorectal tissues and cells. High expression of SPP-1 was associated with advanced clinical process and low overall survival rate in patients with CRC. Besides, SPP-1 could interact with β-catenin and positively regulated β-catenin protein expression, and enhanced its nuclear accumulation. Moreover, SPP-1-upregulation significantly enhanced cell proliferation and in vivo tumor formation ability, and reduced apoptosis, whereas these effects were all abolished when β-catenin was silenced. Overall, the present study revealed that SPP-1 promoted the progression of CRC in a β-catenin-dependent manner.

Machine Learning for Building Immune Genetic Model in Hepatocellular Carcinoma Patients

BACKGROUND

Hepatocellular carcinoma (HCC) is the leading liver cancer with special immune microenvironment, which played vital roles in tumor relapse and poor drug responses. In this study, we aimed to explore the prognostic immune signatures in HCC and tried to construct an immune-risk model for patient evaluation.

METHODS

RNA sequencing profiles of HCC patients were collected from the cancer genome Atlas (TCGA), international cancer genome consortium (ICGC), and gene expression omnibus (GEO) databases (GSE14520). Differentially expressed immune genes, derived from ImmPort database and MSigDB signaling pathway lists, between tumor and normal tissues were analyzed with Limma package in R environment. Univariate Cox regression was performed to find survival-related immune genes in TCGA dataset, and in further random forest algorithm analysis, significantly changed immune genes were used to generate a multivariate Cox model to calculate the corresponding immune-risk score. The model was examined in the other two datasets with recipient operation curve (ROC) and survival analysis. Risk effects of immune-risk score and clinical characteristics of patients were individually evaluated, and significant factors were then used to generate a nomogram.

RESULTS

There were 52 downregulated and 259 upregulated immune genes between tumor and relatively normal tissues, and the final immune-risk model (based on SPP1, BRD8, NDRG1, KITLG, HSPA4, TRAF3, ITGAV and MAP4K2) can better differentiate patients into high and low immune-risk subpopulations, in which high score patients showed worse outcomes after resection (p < 0.05). The differentially enriched pathways between the two groups were mainly about cell proliferation and cytokine production, and calculated immune-risk score was also highly correlated with immune infiltration levels. The nomogram, constructed with immune-risk score and tumor stages, showed high accuracy and clinical benefits in prediction of 1-, 3- and 5-year overall survival, which is useful in clinical practice.

CONCLUSION

The immune-risk model, based on expression of SPP1, BRD8, NDRG1, KITLG, HSPA4, TRAF3, ITGAV, and MAP4K2, can better differentiate patients into high and low immune-risk groups. Combined nomogram, using immune-risk score and tumor stages, could make accurate prediction of 1-, 3- and 5-year survival in HCC patients.

Identification and Validation of Potential Pathogenic Genes and Prognostic Markers in ESCC by Integrated Bioinformatics Analysis

Esophageal squamous cell carcinoma (ESCC) is one of the most fatal malignancies of the digestive tract, but its underlying molecular mechanisms are not known. We aim to identify the genes involved in ESCC carcinogenesis and discover potential prognostic markers using integrated bioinformatics analysis. Three pairs of ESCC tissues and paired normal tissues were sequenced by high-throughput RNA sequencing (RNA-seq). Integrated bioinformatics analysis was used to identify differentially expressed coding genes (DECGs) and differentially expressed long non-coding RNA (lncRNA) genes (DELGs). A protein-protein interaction (PPI) network of DECGs was established using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) website and visualized with Cytoscape. Survival analysis was conducted by log-rank tests to identify "hub" genes with potential prognostic value, and real-time reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was conducted to assess expression of these genes in ESCC tissues. Transwell^TM assays were employed to examine the migration ability of cells after knockdown of LINC01614 expression, followed by investigation of epithelial-mesenchymal transition (EMT) by western blotting (WB). A total of 106 upregulated genes and 42 downregulated genes were screened out from the ESCC data sets. Survival analysis showed two hub protein-coding genes with higher expression in module 1 of the PPI network (SPP1 and BGN) and another three upregulated lncRNAs (LINC01614, LINC01415, NKILA) that were associated with a poor prognosis. High expression of SPP1, BGN, LINC01614, and LINC01415 in tumor samples was validated further by RT-qPCR. In vitro experiments show that knockdown of LINC01614 expression could significantly inhibit the migration of ESCC cells by regulating EMT, which was confirmed by WB. These results indicate that BGN, SPP1, LINC01614, and LINC01415 might be critical genes in ESCC and potential prognostic biomarkers.

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.

Biomarker Discovery for the Carcinogenic Heterogeneity Between Colon and Rectal Cancers Based on lncRNA-Associated ceRNA Network Analysis

Background

Colorectal cancer (CRC) is one of the leading causes of cancer death worldwide. Emerging evidence has revealed that risk factors and metastatic patterns differ greatly between colon and rectal cancers. However, the molecular mechanism underlying their pathogenic differences remains unclear. Therefore, we here aimed to identify non-coding RNA biomarkers based on lncRNA-associated ceRNA network (LceNET) to elucidate the carcinogenic heterogeneity between colon and rectal cancers.

Methods

A global LceNET in human was constructed by employing experimental evidence-based miRNA-mRNA and miRNA-lncRNA interactions. Then, four context-specific ceRNA networks related to cancer initiation and metastasis were extracted by mapping differentially expressed lncRNAs, miRNAs and mRNAs to the global LceNET. Notably, a novel network-based bioinformatics model was proposed and applied to identify lncRNA/miRNA biomarkers and critical ceRNA triplets for understanding the carcinogenic heterogeneity between colon and rectal cancers. Moreover, the identified biomarkers were further validated by their diagnostic/prognostic performance, expression pattern and correlation analysis.

Results

Based on network modeling, lncRNA KCNQ1OT1 (AUC>0.85) and SNHG1 (AUC>0.94) were unveiled as common diagnostic biomarkers for the initiation and metastasis of colon and rectal cancers. qRT-PCR analysis uncovered that these lncRNAs had significantly higher expression level in CRC cell lines with high metastatic potential. In particular, KCNQ1OT1 and SNHG1 function in colon and rectal cancers via different ceRNA mechanisms. For example, KCNQ1OT1/miR-484/ANKRD36 axis was involved in the initiation of colon cancer, while KCNQ1OT1/miR-181a-5p/PCGF2 axis was implicated in the metastasis of rectal cancer; the SNHG1/miR-484/ORC6 axis played a role in colon cancer, while SNHG1/miR-423-5p/EZH2 and SNHG1/let-7b-5p/ATP6V1F axes participated in the initiation and metastasis of rectal cancer, respectively. In these ceRNA triplets, miR-484, miR-181a-5p, miR-423-5p and let-7b-5p were identified as miRNA biomarkers with excellent distinguishing ability between normal and tumor tissues, and ANKRD36, PCGF2, EZH2 and ATP6V1F were closely related to the prognosis of corresponding cancer.

Conclusion

The landscape of lncRNA-associated ceRNA network not only facilitates the exploration of non-coding RNA biomarkers, but also provides deep insights into the oncogenetic heterogeneity between colon and rectal cancers, thereby contributing to the optimization of diagnostic and therapeutic strategies of CRC.

SP8 Promotes an Aggressive Phenotype in Hepatoblastoma via FGF8 Activation

Hepatoblastoma (HB) is the most common malignant liver tumor in childhood and it generally has a good prognosis. However, if associated with aggressive metastatic disease, outcome is still poor. The molecular mechanisms leading to metastatic spread in HB patients are still unknown. By combining RNA-sequencing and a genome-wide methylome analysis, we identified the transcription factor SP8 and the growth factor FGF8 among the most strongly upregulated genes in metastatic HB cases, with a concomitant robust demethylation of the respective promoter regions. Of note, high expression of both candidates was associated with the aggressive C2 subtype of the 16-gene signature and poor survival. Chromatin immunoprecipitation revealed a direct transcriptional regulation of FGF8 through binding of SP8 to the FGF8 promoter. Gain- and loss-of-function experiments proved promoting effects of SP8 on motility, self-renewal, migration, and the invasive potential of HB cells. Moreover, stable overexpression of SP8 in Hep3B cells resulted in the acquisition of a mesenchymal phenotype and a strong upregulation of epithelial-mesenchymal transition-associated genes. Using KRAB-mediated CRISPR-dCas9 interference directed against FGF8, we could show that FGF8 is essential for the SP8-mediated aggressive tumor behavior. Treatment of HB cell lines with the pan SP family inhibitor mithramycin A resulted in a significant inhibition of their clonogenic growth. In summary, we identified SP8 and FGF8 as key players in aggressive traits of HB and propose SP8 inhibiting drugs as a new effective treatment strategy especially for metastatic tumors.

Analysis of Expression and Its Clinical Significance of the Secreted Phosphoprotein 1 in Lung Adenocarcinoma

Objective

To explore the expression of secreted phosphoprotein 1 (SPP1) in lung adenocarcinoma (LUAD), and evaluate its relationship with clinicopathological characteristics and prognosis of LUAD, and analyze the advantages of SPP1 as a potential prognostic marker in LUAD.

Methods

The expression of SPP1 in normal lung tissue and LUAD was analyzed from the Cancer Cell Line Encyclopedia (CCLE), Gene Expression Omnibus (GEO), and Human Protein Atlas (HPA) databases. GSE68465 was used to explore the relationship between the SPP1 expression and clinicopathological characteristics and the prognosis of LUAD patients. The relationship between SPP1 and immune infiltration in LUAD was analyzed by the Tumor Immune Estimation Resource (TIMER) database. Gene enrichment analysis was performed in GSEA. The Cancer Genome Atlas (TCGA)-LUAD data was used to verify the results.

Results

In the cell line level, non-small cell lung cancer ranked ninth among cancer cell lines based on SPP1 expression. In the messenger RNA (mRNA) and protein levels, SPP1 expression was higher in LUAD tissues than that in normal control. SPP1 expression was related to gender, N stage, histological grade, and progression or relapse. In men, SPP1 expression were higher compared to that in women. The higher the N stage, the higher the SPP1 expression level. As LUAD progresses or relapses, SPP1 expression could increase. In the pathological grade, the SPP1 expression was higher in LUAD samples with moderate differentiation. In addition, the overall 5-year survival rates of the SPP1 high and low expression groups were 50.574 and 59.181% [P = 0.008; hazard ratio (HR) = 0.7057; 95% CI, 0.5467-0.9109], indicating that SPP1 had an impact on overall survival for LUAD patients. The relationship between SPP1 expression and CD4⁺ T cell, macrophage, neutrophil, and dendritic cell infiltration was weak in LUAD. SPP1 could be considered as an independent prognostic marker in LUAD (P = 0.003; HR = 1.150; 95% CI, 1.048-1.261) by multivariate Cox regression analysis. The results of GSEA indicated that samples with high SPP1 expression were enriched in protein secretion, mTORC1 signaling, angiogenesis, and glycolysis pathway. The analysis results obtained by TCGA-LUAD data were basically consistent with the results obtained by GSE68465.

Conclusions

SPP1 can not only affect the occurrence and development of LUAD but also may be an independent prognostic marker of LUAD. SPP1 is expected to be a new target for molecular targeted therapy.

Deciphering Master Gene Regulators and Associated Networks of Human Mesenchymal Stromal Cells

Mesenchymal Stromal Cells (MSC) are multipotent cells characterized by self-renewal, multilineage differentiation, and immunomodulatory properties. To obtain a gene regulatory profile of human MSCs, we generated a compendium of more than two hundred cell samples with genome-wide expression data, including a homogeneous set of 93 samples of five related primary cell types: bone marrow mesenchymal stem cells (BM-MSC), hematopoietic stem cells (HSC), lymphocytes (LYM), fibroblasts (FIB), and osteoblasts (OSTB). All these samples were integrated to generate a regulatory gene network using the algorithm ARACNe (Algorithm for the Reconstruction of Accurate Cellular Networks; based on mutual information), that finds regulons (groups of target genes regulated by transcription factors) and regulators (i.e., transcription factors, TFs). Furtherly, the algorithm VIPER (Algorithm for Virtual Inference of Protein-activity by Enriched Regulon analysis) was used to inference protein activity and to identify the most significant TF regulators, which control the expression profile of the studied cells. Applying these algorithms, a footprint of candidate master regulators of BM-MSCs was defined, including the genes EPAS1, NFE2L1, SNAI2, STAB2, TEAD1, and TULP3, that presented consistent upregulation and hypomethylation in BM-MSCs. These TFs regulate the activation of the genes in the bone marrow MSC lineage and are involved in development, morphogenesis, cell differentiation, regulation of cell adhesion, and cell structure.

LncRNA AC093818.1 accelerates gastric cancer metastasis by epigenetically promoting PDK1 expression

Gastric cancer (GC) is a highly prevalent type of metastatic tumor. The mechanisms underlying GC metastasis are poorly understood. Some long noncoding RNAs (lncRNAs) reportedly play key roles in regulating metastasis of GC. However, the biological roles of five natural antisense lncRNAs (AC093818.1, CTD-2541M15.1, BC047644, RP11-597M12.1, and RP11-40A13.1) in GC metastasis remain unclear. In this study, the expression of these lncRNAs was measured by quantitative reverse transcription-polymerase chain reaction. Migration and invasion were evaluated by wound-healing and the Transwell assay, respectively. Stable cells were injected into the tail veins of nude mice. Sections of collected lung and liver tissues were stained using hematoxylin and eosin. Protein expression was analyzed by western blot. RNA immunoprecipitation (RIP) assay was used to verify whether the STAT3 and SP1 transcription factors bound to AC093818.1 in GC cells. Expression levels of the five lncRNAs, especially AC093818.1, were significantly upregulated in metastatic GC tissues relative to those in nonmetastatic GC tissues. AC093818.1 expression was correlated with invasion, lymphatic metastasis, distal metastasis, and tumor-node-metastasis stage. AC093818.1 expression was highly sensitive and specific in the diagnosis of metastatic or nonmetastatic GC. AC093818.1 overexpression promoted GC migration and invasion in vitro and in vivo. AC093818.1 overexpression increased PDK1, p-AKT1, and p-mTOR expression levels. AC093818.1 silencing decreased these expressions. AC093818.1 bound to transcription factors STAT3 and SP1, and SP1 or STAT3 silencing could alleviated the effect of AC093818.1 overexpression. The data demonstrate that lncRNA AC093818.1 accelerates gastric cancer metastasis by epigenetically promoting PDK1 expression. LncRNA AC093818.1 may be a potential therapeutic target for metastatic GC.

Actin-like protein 8 promotes cell proliferation, colony-formation, proangiogenesis, migration and invasion in lung adenocarcinoma cells

Background

Non‐small cell lung cancer (NSCLC) is the leading cause of cancer‐associated mortality worldwide of which lung adenocarcinoma (LUAD) is the most common. The identification of oncogenes and effective drug targets is the key to individualized LUAD treatment. Actin‐like protein 8 (ACTL8), a member of the cancer/testis antigen family, is associated with tumor growth and patient prognosis in various types of cancer. However, whether ACTL8 is involved in the development of LUAD remains unknown. The aim of the present study was to demonstrate the role of ACTL8 in human LUAD cells.

Methods

The expression of ACTL8 in LUAD tissues and cell lines was assessed using immunohistochemistry and western blotting. Additionally, plasmids expressing ACTL8‐specific short hairpin RNAs were used to generate lentiviruses which were subsequently used to infect A549 and NCI‐H1975 human LUAD cells. Cell proliferation, migration, invasion and apoptosis, as well as cell cycle progression and the expression of protein markers of epithelial to mesenchymal transition were investigated. A549 cell tumor growth in nude mice was also examined.

Results

The results showed that ACTL8 was highly expressed in A549 and NCI‐H1975 LUAD cell lines. Additionally, ACTL8‐knockdown inhibited proliferation, colony formation, cell cycle progression, migration and invasion, and increased apoptosis in both cell lines. Furthermore, in vivo experiments in nude mice revealed that ACTL8‐knockdown inhibited A549 cell tumor growth.

Conclusion

These results suggest that ACTL8 serves an oncogenic role in human LUAD cells, and that ACTL8 may represent a potential therapeutic target for LUAD.

Key points

Our results suggest that ACTL8 serves an oncogenic role in human LUAD cells, and that ACTL8 may represent a potential therapeutic target for LUAD.

Association between the expression of secreted phosphoprotein - related genes and prognosis of human cancer

Background

While many studies have assessed the predictive value of secreted phosphoprotein (SPP) genes in cancer, the findings have been inconsistent. To resolve these inconsistencies, we systematically analyzed the available data to determine whether SPP1 and SPP2 are prognostic markers in the context of human cancer.

Methods

The expression of SPP1 and SPP2 was assessed by Oncomine analysis. The PrognoScan database was used to assess the prognostic value of SPP1 and SPP2, with cBioPortal used to assess copy number variations. The STRING database was used to generate a Protein - Protein Interaction (PPI) network for SPP genes.

Results

SPP1 was more likely to be over-expressed in breast, bladder, colorectal, head, neck, liver, lung, and esophageal cancers. SPP2 was expressed at lower levels in colorectal cancer, leukemia, liver cancer and pancreatic cancer. In addition, SPP1 and SPP2 mutations mainly occurred in cutaneous melanoma and endometrial cancer.

Conclusions

Our results suggest that SPP1 and SPP2 may be effective therapeutic or diagnostic targets in certain cancers. Further research is required to confirm these results and verify the value of SPP1 and SPP2 as clinical markers of cancer prognosis.