A Candidate Prognostic Biomarker Complement Factor I Promotes Malignant Progression in Glioma

Proteomic and In Silico Analyses Highlight Complement System's Role in Bladder Cancer Immune Regulation

Background and Objectives: Bladder cancer (BLCA), intimately associated with the immune system, represents a substantial global health burden due to its high recurrence rates and limited therapeutic effectiveness. Although immunotherapy shows promise, challenges persist due to the lack of reliable therapeutic targets. This study aims to investigate potential immune-related biomarkers that could influence the tumor microenvironment in BLCA, using proteomic and in silico approaches. Materials and Methods: Tissue samples from BLCA patients (n = 27) and controls (n = 27) were collected from Şişli Hamidiye Etfal Training and Research Hospital. Proteomic analysis was performed by liquid chromatography/mass spectrometry (LC-MS)/MS to reveal the identities of differentially regulated proteins. Protein network analysis and hub protein detection were performed using Cytoscape (v.3.10.3), while functional annotation was carried out using EnrichR. The immunological analysis of hub proteins was performed in Sangerbox platform, and prognostic associations were evaluated through the Kaplan-Meier Plotter tool. Results: LC-MS/MS analysis identified 120 differentially regulated immune-related proteins. STRING analysis, using an immune response dataset (GO:0006955), highlighted the complement cascade as a significantly enriched pathway (p < 0.05). Proteins, namely C4A, CFB, C4B, C8B, CFH, CFI, C5, C4BPA, C3, and C2, that are known to play key roles in the complement system were identified. Immunological analysis with these proteins revealed the phenomena of immune infiltration and immune checkpoint gene associations (p < 0.05). Four hub genes-CFB, C4B, CFI, and C2-demonstrated a significant prognostic value for BLCA (p < 0.05). Conclusions: This study highlights the pivotal role of the complement system in the immune regulation of BLCA. CFI, C4A, and C4B emerged as potential target proteins for BLCA treatment, particularly in immunotherapy, for enhancing survival. Future research on these proteins and the complement system specifically focusing on BLCA may facilitate the development of targeted immunotherapies, ultimately improving treatment outcomes.

The Role of Coagulation-Related Genes in Glioblastoma: A Comprehensive Analysis of the Tumor Microenvironment, Prognosis, and Treatment

The influence of coagulation on glioma biology has not been comprehensively elucidated. This study explores the role of coagulation-related genes (CRGs) in glioblastoma (GBM) from the perspectives of the tumor microenvironment (TME), differences in coagulation function among GBM patients, treatment, and prognosis. Somatic mutation analysis was performed on single nucleotide polymorphism (SNP) and copy number variation data from GBM patients in the TCGA cohort. Publicly available single-cell RNA sequencing data were used to analyze the role of coagulation in the GBM TME and its underlying biological mechanisms. Unsupervised clustering of GBM patients from the CGGA693 cohort was conducted, and coagulation function for each patient was assessed using ssGSEA scoring. Prognosis was assessed with Kaplan-Meier survival analysis, and immune infiltration was analyzed through ESTIMATE. A risk signature based on five CRGs (CFI, GNG12, MMP2, LEFTY2, and SERPINC1) was constructed and validated using LASSO regression and random survival forest analyses to predict responses to immunotherapy and identify potential sensitive drugs. Finally, the roles of LEFTY2 and SERPINC1 in GBM progression was verified by immunohistochemistry, cell counting kit-8 (CCK8) assay and wound healing assay, and the anti-GBM effect of the drug PLX4720 was verified by CCK8 assay, wound healing assay, and colony formation assay. Somatic mutation analysis revealed SNP events of CRG mutations in 117 out of 461 GBM cases (25.38%). Single-cell analysis of the GBM TME revealed significant activation of the coagulation pathway in endothelial cells, with intercellular communication mediated via the SPP1-integrin pathway (p < 0.01). Clustering analysis and ssGSEA identified two coagulation-related subtypes in GBM: coagulation-activated and coagulation-inhibited subtypes. Patients in the coagulation-activated subtype exhibited shorter overall survival and poorer prognosis compared to those in the coagulation-inhibited subtype (p = 0.0085). Immune infiltration analysis showed lower tumor purity and higher levels of immune-suppressive cells in the coagulation-activated subtype (p < 0.001). The CRG-based risk signature accurately predicted prognosis (p < 0.0001) and responses to immunotherapy in the IMvigor210 cohort (p = 0.0062). Based on the risk model, PLX4720 was identified as a potential sensitive drug (p < 0.001), and drug validation experiments demonstrated that PLX4720 inhibited the proliferation and migration of glioma cells (p < 0.0001). In vitro experiments demonstrated that LEFTY2 and SERPINC1 were significantly overexpressed in GBM compared to normal brain tissue, and knockdown of LEFTY2 and SERPINC1 inhibited glioma cell proliferation and migration (p < 0.05). The CRG-based risk signature model effectively predicts the prognosis of GBM patients and aids in assessing the efficacy of ICI therapy and chemotherapy. Furthermore, the genes LEFTY2, SERPINC1 and the drug PLX4720 offer potential directions for the development of novel therapeutic strategies for GBM.

Identification of a coagulation-related gene signature for predicting prognosis in recurrent glioma

BACKGROUND

Recurrent gliomas rapidly progress and have high mortality and poor prognosis in the central nervous system. Therefore, further investigation of prognostic and therapeutic markers is needed.

METHODS

The mRNA expression, clinical data, and coagulation-related genes (CRGs) associated with recurrent glioma were obtained and calculated from the Chinese Glioma Genome Atlas and Kyoto Encyclopedia of Genes and Genomes databases. The significant CRGs were calculated by Weighted gene co-expression network analysis and PPI network. A prediction model was constructed using the least absolute shrinkage and selection operator regression analysis. Recurrent gliomas were stratified into high and low-risk groups based on the median risk score (RS). The Kaplan-Meier curve was used to analyze the difference in overall survival (OS) between these groups, while the receiver operating characteristic (ROC) curve was used to evaluate the accuracy of the gene model at 1-, 3-, and 5-years. Clinical factors, including age, gender, MGMT methylation status, radiotherapy, chemotherapy, and RS, were included in the univariate and multivariate regression analysis. A prognostic nomogram and calibration curve were established based on these factors.

RESULTS

Overall, seven CRGs associated with the prognosis were identified, including BTK, ITGB1, GNAI3, CFH, LYN, CFI, and F3. OS and survival rates were lower in the high-risk group compared with the low-risk group. The ROC curve demonstrated the area under the curve values >0.65 at 1-, 3-, and 5-years, confirming the reliability of the prognostic model. The univariate regression analysis indicated that tumor grade (grades 2, 3, and 4), histopathology (GBM or not), chemotherapy, IDH mutation, and 1p19q co-deletion status were independent prognostic indicators. Univariate and multivariate regression analyses indicated that RS was an independent prognostic factor for patients with recurrent glioma. Immune analysis revealed low infiltration of resting dendritic cells and high expression of programmed death receptor 1 in the high-risk group.

CONCLUSION

This study comprehensively investigated the correlation between CRGs and recurrent glioma prognosis, offering crucial insights for further research into glioma recurrence mechanisms and treatment strategies.

Profiling and Bioinformatics Analyses of Hypoxia-Induced Differential Expression of Long Non-coding RNA in Glioblastoma Multiforme Cells

Hypoxic microenvironments are intricately linked to malignant characteristics of glioblastoma multiforme (GBM). Long non-coding ribonucleic acids (lncRNAs) have been reported to be involved in the progression of GBM and closely associated with hypoxia. Nevertheless, the differential expression profiles as well as functional roles of lncRNAs in GBM cells under hypoxic conditions remain largely obscure. We explored the expression profiles of lncRNAs in hypoxic U87 cells as well as T98G cells using sequencing analysis. The effect of differentially expressed lncRNAs (DElncRNAs) was assessed through bioinformatic analysis. Furthermore, the expression of lncRNAs significantly dysregulated in both U87 and T98G cells was further validated using quantitative reverse-transcription polymerase chain reaction (qRT-PCR). Relevant cell functional experiments were also conducted. We used predicted RNA-binding proteins (RBPs) to construct an interaction network via the interaction prediction module. U87 and T98G cells showed dysregulation of 1115 and 597 lncRNAs, respectively. Gene Ontology (GO) analysis indicated that altered lncRNA expression was associated with nucleotide-excision repair and cell metabolism in GBM cells. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed the association between dysregulated lncRNAs and the Hippo signaling pathway under hypoxia. The dysregulation of six selected lncRNAs (ENST00000371192, uc003tnq.3, ENST00000262952, ENST00000609350, ENST00000610036, and NR_046262) was validated by qRT-PCR. Investigation of lncRNA-microRNA (miRNA)-mRNA networks centered on HIF-1α demonstrated cross-talk between the six validated lncRNAs and 16 related miRNAs. Functional experiments showed the significant inhibition of GBM cell proliferation, invasion, and migration by the knockdown of uc003tnq.3 in vitro. Additionally, uc003tnq.3 was used to construct a comprehensive RBP-transcription factor (TF)-miRNA interaction network. The expression of LncRNAs was dysregulated in GBM cells under hypoxic conditions. The identified six lncRNAs might exert important effect on the development of GBM under hypoxic microenvironment.

Complement factor I knockdown inhibits colon cancer development by affecting Wnt/β-catenin/c-Myc signaling pathway and glycolysis

BACKGROUND

Colon cancer (CC) occurrence and progression are considerably influenced by the tumor microenvironment. However, the exact underlying regulatory mechanisms remain unclear.

AIM

To investigate immune infiltration-related differentially expressed genes (DEGs) in CC and specifically explored the role and potential molecular mechanisms of complement factor I (CFI).

METHODS

Immune infiltration-associated DEGs were screened for CC using bioinformatics. Quantitative reverse transcription polymerase chain reaction was used to examine hub DEGs expression in the CC cell lines. Stable CFI-knockdown HT29 and HCT116 cell lines were constructed, and the diverse roles of CFI in vitro were assessed using CCK-8, 5-ethynyl-2’-deoxyuridine, wound healing, and transwell assays. Hematoxylin and eosin staining and immunohistochemistry staining were employed to evaluate the influence of CFI on the tumorigenesis of CC xenograft models constructed using BALB/c male nude mice. Key proteins associated with glycolysis and the Wnt pathway were measured using western blotting.

RESULTS

Six key immune infiltration-related DEGs were screened, among which the expression of CFI, complement factor B, lymphoid enhancer binding factor 1, and SRY-related high-mobility-group box 4 was upregulated, whereas that of fatty acid-binding protein 1, and bone morphogenic protein-2 was downregulated. Furthermore, CFI could be used as a diagnostic biomarker for CC. Functionally, CFI silencing inhibited CC cell proliferation, migration, invasion, and tumor growth. Mechanistically, CFI knockdown downregulated the expression of key glycolysis-related proteins (glucose transporter type 1, hexokinase 2, lactate dehydrogenase A, and pyruvate kinase M2) and the Wnt pathway-related proteins (β-catenin and c-Myc). Further investigation indicated that CFI knockdown inhibited glycolysis in CC by blocking the Wnt/β-catenin/c-Myc pathway.

CONCLUSION

The findings of the present study demonstrate that CFI plays a crucial role in CC development by influencing glycolysis and the Wnt/β-catenin/c-Myc pathway, indicating that it could serve as a promising target for therapeutic intervention in CC.

Complement factor I knockdown inhibits colon cancer development by affecting Wnt/β-catenin/c-Myc signaling pathway and glycolysis

BACKGROUND

Colon cancer (CC) occurrence and progression are considerably influenced by the tumor microenvironment. However, the exact underlying regulatory mechanisms remain unclear.

AIM

To investigate immune infiltration-related differentially expressed genes (DEGs) in CC and specifically explored the role and potential molecular mechanisms of complement factor I (CFI).

METHODS

Immune infiltration-associated DEGs were screened for CC using bioinformatics. Quantitative reverse transcription polymerase chain reaction was used to examine hub DEGs expression in the CC cell lines. Stable CFI-knockdown HT29 and HCT116 cell lines were constructed, and the diverse roles of CFI in vitro were assessed using CCK-8, 5-ethynyl-2'-deoxyuridine, wound healing, and transwell assays. Hematoxylin and eosin staining and immunohistochemistry staining were employed to evaluate the influence of CFI on the tumorigenesis of CC xenograft models constructed using BALB/c male nude mice. Key proteins associated with glycolysis and the Wnt pathway were measured using western blotting.

RESULTS

Six key immune infiltration-related DEGs were screened, among which the expression of CFI, complement factor B, lymphoid enhancer binding factor 1, and SRY-related high-mobility-group box 4 was upregulated, whereas that of fatty acid-binding protein 1, and bone morphogenic protein-2 was downregulated. Furthermore, CFI could be used as a diagnostic biomarker for CC. Functionally, CFI silencing inhibited CC cell proliferation, migration, invasion, and tumor growth. Mechanistically, CFI knockdown downregulated the expression of key glycolysis-related proteins (glucose transporter type 1, hexokinase 2, lactate dehydrogenase A, and pyruvate kinase M2) and the Wnt pathway-related proteins (β-catenin and c-Myc). Further investigation indicated that CFI knockdown inhibited glycolysis in CC by blocking the Wnt/β-catenin/c-Myc pathway.

CONCLUSION

The findings of the present study demonstrate that CFI plays a crucial role in CC development by influencing glycolysis and the Wnt/β-catenin/c-Myc pathway, indicating that it could serve as a promising target for therapeutic intervention in CC.

PDE1B, a potential biomarker associated with tumor microenvironment and clinical prognostic significance in osteosarcoma

PDE1B had been found to be involved in various diseases, including tumors and non-tumors. However, little was known about the definite role of PDE1B in osteosarcoma. Therefore, we mined public data on osteosarcoma to reveal the prognostic values and immunological roles of the PDE1B gene. Three osteosarcoma-related datasets from online websites were utilized for further data analysis. R 4.3.2 software was utilized to conduct difference analysis, prognostic analysis, gene set enrichment analysis (GSEA), nomogram construction, and immunological evaluations, respectively. Experimental verification of the PDE1B gene in osteosarcoma was conducted by qRT-PCR and western blot, based on the manufacturer's instructions. The PDE1B gene was discovered to be lowly expressed in osteosarcoma, and its low expression was associated with poor OS (all P < 0.05). Experimental verifications by qRT-PCR and western blot results remained consistent (all P < 0.05). Univariate and multivariate Cox regression analyses indicated that the PDE1B gene had independent abilities in predicting OS in the TARGET osteosarcoma dataset (both P < 0.05). GSEA revealed that PDE1B was markedly linked to the calcium, cell cycle, chemokine, JAK STAT, and VEGF pathways. Moreover, PDE1B was found to be markedly associated with immunity (all P < 0.05), and the TIDE algorithm further shed light on that patients with high-PDE1B expression would have a better immune response to immunotherapies than those with low-PDE1B expression, suggesting that the PDE1B gene could prevent immune escape from osteosarcoma. The PDE1B gene was found to be a tumor suppressor gene in osteosarcoma, and its high expression was related to a better OS prognosis, suppressing immune escape from osteosarcoma.

Thymoquinone affects hypoxia-inducible factor-1α expression in pancreatic cancer cells via HSP90 and PI3K/AKT/mTOR pathways

BACKGROUND

Pancreatic cancer (PC) is associated with some of the worst prognoses of all major cancers. Thymoquinone (TQ) has a long history in traditional medical practice and is known for its anti-cancer, anti-inflammatory, anti-fibrosis and antioxidant pharmacological activities. Recent studies on hypoxia-inducible factor-1α (HIF-1α) and PC have shown that HIF-1α affects the occurrence and development of PC in many aspects. In addition, TQ could inhibit the development of renal cancer by decreasing the expression of HIF-1α. Therefore, we speculate whether TQ affects HIF-1α expression in PC cells and explore the mechanism.

AIM

To elucidate the effect of TQ in PC cells and the regulatory mechanism of HIF-1α expression.

METHODS

Cell counting kit-8 assay, Transwell assay and flow cytometry were performed to detect the effects of TQ on the proliferative activity, migration and invasion ability and apoptosis of PANC-1 cells and normal pancreatic duct epithelial (hTERT-HPNE) cells. Quantitative real-time polymerase chain reaction and western blot assay were performed to detect the expression of HIF-1α mRNA and protein in PC cells. The effects of TQ on the HIF-1α protein initial expression pathway and ubiquitination degradation in PANC-1 cells were examined by western blot assay and co-immunoprecipitation.

RESULTS

TQ significantly inhibited proliferative activity, migration, and invasion ability and promoted apoptosis of PANC-1 cells; however, no significant effects on hTERT-HPNE cells were observed. TQ significantly reduced the mRNA and protein expression levels of HIF-1α in PANC-1, AsPC-1, and BxPC-3 cells. TQ significantly inhibited the expression of the HIF-1α initial expression pathway (PI3K/AKT/mTOR) related proteins, and promoted the ubiquitination degradation of the HIF-1α protein in PANC-1 cells. TQ had no effect on the hydroxylation and von Hippel Lindau protein mediated ubiquitination degradation of the HIF-1α protein but affected the stability of the HIF-1α protein by inhibiting the interaction between HIF-1α and HSP90, thus promoting its ubiquitination degradation.

CONCLUSION

The regulatory mechanism of TQ on HIF-1α protein expression in PC cells was mainly to promote the ubiquitination degradation of the HIF-1α protein by inhibiting the interaction between HIF-1α and HSP90; Secondly, TQ reduced the initial expression of HIF-1α protein by inhibiting the PI3K/AKT/mTOR pathway.

Elevated CDC45 Expression Predicts Poorer Overall Survival Prognoses and Worse Immune Responses for Kidney Renal Clear Cell Carcinoma via Single-Cell and Bulk RNA-Sequencing

The main objective of this paper is to analyze the prognostic and immunological value of CDC45 in kidney renal clear cell carcinoma (KIRC) using single-cell and bulk RNA-sequencing approaches. The expression of CDC45 in KIRC was evaluated by the HPA database, the TCGA-KIRC dataset and verified by PCR analysis and single-cell RNA-sequencing. The ability of CDC45 to independently predict prognosis in KIRC was confirmed by univariate/multivariate regression analysis. Gene set enrichment analysis (GSEA) was employed to explore CDC45-related pathways in KIRC. In addition, Relationships between CDC45 and immunity were also examined. Elevated CDC45 expression in KIRC was demonstrated at mRNA and protein levels. The results of the correlation analysis showed that as CDC45 expression increased, so did the histological grade, clinical stage, and TNM stage of the patients (p < 0.05). Univariate/multivariate regression analysis suggested CDC45 as an independent prognostic factor for KIRC. Seven pathways related to CDC45 were screened through GSEA. Meanwhile, we found that CDC45 was correlated with tumor mutational burden (TMB) and microsatellite instability (MSI) but not tumor neoantigen burden (TNB). Regarding immunity, CDC45 exhibited correlations with the tumor microenvironment, immune cell infiltration, and immune checkpoints. Besides, low CDC45 expression was shown to be associated with a better response to immunotherapy. Single-cell RNA-sequencing revealed that CDC45 was differently expressed in T cells (p < 0.05). CDC45 showed potential as a prognostic biomarker and therapeutic target for KIRC. Meanwhile, the CDC45 low expression group was more sensitive to immunotherapy.

Urinary Proteomics for Discovery of Gastric Cancer Biomarkers to Enable Precision Clinical Oncology

For precision in clinical oncology practice, detection of tumor-derived peptides and proteins in urine offers an attractive and noninvasive alternative for diagnostic or screening purposes. In this study, we report comparative quantitative proteomic profiling of urine samples from patients with gastric cancer and healthy controls using tandem mass tags-based multiplexed mass spectrometry approach. We identified 1504 proteins, of which 246 were differentially expressed in gastric cancer cases. Notably, ephrin A1 (EFNA1), pepsinogen A3 (PGA3), sortilin 1 (SORT1), and vitronectin (VTN) were among the upregulated proteins, which are known to play crucial roles in the progression of gastric cancer. We also found other overexpressed proteins, including shisa family member 5 (SHISA5), mucin like 1 (MUCL1), and leukocyte cell derived chemotaxin 2 (LECT2), which had not previously been linked to gastric cancer. Using a novel approach for targeted proteomics, SureQuant, we validated changes in abundance of a subset of proteins discovered in this study. We confirmed the overexpression of vitronectin and sortilin 1 in an independent set of urine samples. Altogether, this study provides molecular candidates for biomarker development in gastric cancer, and the findings also support the promise of urinary proteomics for noninvasive diagnostics and personalized/precision medicine in the oncology clinic.

USP10 deubiquitinates RUNX1 and promotes proneural-to-mesenchymal transition in glioblastoma

The mesenchymal (MES) subtype of glioblastoma (GBM) is a highly aggressive, malignant and proliferative cancer that is resistant to chemotherapy. Runt-related transcription factor 1 (RUNX1) was shown to support MES GBM, however, its underlying mechanisms are unclear. Here, we identified USP10 as a deubiquitinating enzyme that regulates RUNX1 stabilization and is mainly expressed in MES GBM. Overexpression of USP10 upregulated RUNX1 and induced proneural-to-mesenchymal transition (PMT), thus maintaining MES properties in GBM. Conversely, USP10 knockdown inhibited RUNX1 and resulted in the loss of MES properties. USP10 was shown to interact with RUNX1, with RUNX1 being stabilized upon deubiquitylation. Moreover, we found that USP10 inhibitor Spautin-1 induced RUNX1 degradation and inhibited MES properties in vitro and in vivo. Furthermore, USP10 was strongly correlated with RUNX1 expression in samples of different subtypes of human GBM and had prognostic value for GBM patients. We identified USP10 as a key deubiquitinase for RUNX1 protein stabilization. USP10 maintains MES properties of GBM, and promotes PMT of GBM cells. Our study indicates that the USP10/RUNX1 axis may be a potential target for novel GBM treatments.

A Novel CRISPR/Cas9 Screening Potential Index for Prognostic and Immunological Prediction in Low-Grade Glioma

Glioma is a malignancy with the highest mortality in central nervous system disorders. Here, we implemented the computational tools based on CRISPR/Cas9 to predict the clinical outcomes and biological characteristics of low-grade glioma (LGG). The transcriptional expression profiles and clinical phenotypes of LGG patients were retrieved from The Cancer Genome Atlas and Chinese Glioma Genome Atlas. The CERES algorithm was used to screen for LGG-lethal genes. Cox regression and random survival forest were adopted for survival-related gene selection. Nonnegative matrix factorization distinguished patients into different clusters. Single-sample gene set enrichment analysis was employed to create a novel CRISPR/Cas9 screening potential index (CCSPI), and patients were stratified into low- and high-CCSPI groups. Survival analysis, area under the curve values (AUCs), nomogram, and tumor microenvironment exploration were included for the model validation. A total of 20 essential genes in LGG were used to classify patients into two clusters and construct the CCSPI system. High-CCSPI patients were associated with a worse prognosis of both training and validation set (p < 0.0001) and higher immune fractions than low-CCSPI individuals. The CCSPI system had a promising performance with 1-, 3-, and 5-year AUCs of 0.816, 0.779, 0.724, respectively, and the C-index of the nomogram model reached 0.743 (95% CI = 0.725–0.760). Immune-infiltrating cells and immune checkpoints such as PD-1/PD-L1 and POLD3 were positively associated with CCSPI. In conclusion, the CCSPI had prognostic value in LGG, and the model will deepen our cognition of the interaction between the CNS and immune system in different LGG subtypes.

Prognostic value and immunological role of AXL gene in clear cell renal cell carcinoma associated with identifying LncRNA/RBP/AXL mRNA networks

Backgrounds

This article aimed to explore the prognostic and immunological roles of AXL gene in clear cell renal cell carcinoma (ccRCC) for overall survival (OS) and to identify the LncRNA/RBP/AXL mRNA networks.

Methods

AXL-related gene expression matrix and clinical data were obtained from The Cancer Genome Atlas (TCGA) dataset and AXL-related pathways were identified by gene set enrichment analysis (GSEA). We performed univariate/multivariate Cox regression analysis to evaluate independent prognostic factors and the relationships between AXL and immunity were also investigated.

Results

The outcomes of us indicated that the AXL mRNA expression was up-regulated in ccRCC samples and high expression of AXL was associated with worse OS in TCGA dataset (P < 0.01). Further external verification results from HPA, UALCAN, ICGC dataset, GSE6344, GSE14994, and qRT-PCR remained consistent (all P < 0.05). AXL was also identified as an independent prognostic factor for ccRCC by univariate/multivariate Cox regression analysis (both P < 0.05). A nomogram including AXL expression and clinicopathological factors was established by us and GSEA results found that elevated AXL expression was associated with the JAK-STAT, P53, WNT, VEGF and MAPK signaling pathways. In terms of immunity, AXL was dramatically linked to tumor microenvironment, immune cells, immune infiltration, immune checkpoint molecules and tumor mutational burden (TMB). As for its potential mechanisms, we also identified several LncRNA/RBP/AXL mRNA axes.

Conclusions

AXL was revealed to play prognostic and immunological roles in ccRCC and LncRNA/RBP/AXL mRNA axes were also identified by us for its potential mechanisms.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02322-y.

SMOX expression predicts the prognosis of non-small cell lung cancer

Background

The development of non-small cell lung cancer (NSCLC) is very rapid, and the effect of its treatment is often closely related to the diagnosis time of the disease. Therefore, simple and convenient tumor biomarkers are helpful for the timely diagnosis and prevention of NSCLC.

Methods

Through univariate and multivariate Cox regression analyses, SMOX was determined as an independent prognostic factor of GSE42127, GSE41271, GSE68465, and TCGA datasets. Furthermore, western blot, reverse transcription-polymerase chain reaction (RT-PCR), and immunohistochemical analysis were performed to confirm the predictive efficiency of SMOX expression in NSCLC.

Results

Patients were divided into high and low expression groups according to the median value of SMOX expression, and Kaplan-Meier curves of multiple datasets indicated that patients with low SMOX expression had a better survival rate. According to the analysis of immune infiltration, the immune microenvironment, and immune checkpoints, SMOX expression of the high and low groups showed differences in immunity in NSCLC. By comparing cancer and adjacent tissues using western blot analysis, RT-PCR and immunohistochemical analysis, we found that SMOX was highly expressed in tumor tissues and had low expression in adjacent tissues. Simultaneously, the Kaplan-Meier curve suggested that among the 155 NSCLC patients, those with low SMOX expression had better survival.

Conclusions

SMOX can be used as an effective predictive target for NSCLC.

PRL1 Promotes Glioblastoma Invasion and Tumorigenesis via Activating USP36-Mediated Snail2 Deubiquitination

Regenerating liver phosphatase 1 (PRL1) is an established oncogene in various cancers, although its biological function and the underlying mechanisms in glioblastoma multiforme (GBM) remain unclear. Here, we showed that PRL1 was significantly upregulated in glioma tissues and cell lines, and positively correlated with the tumor grade. Consistently, ectopic expression of PRL1 in glioma cell lines significantly enhanced their tumorigenicity and invasion both in vitro and in vivo by promoting epithelial-mesenchymal transition (EMT). Conversely, knocking down PRL1 blocked EMT in GBM cells, and inhibited their invasion, migration and tumorigenic growth. Additionally, PRL1 also stabilized Snail2 through its deubiquitination by activating USP36, thus revealing Snail2 as a crucial mediator of the oncogenic effects of PRL1 in GBM pathogenesis. Finally, PRL1 protein levels were positively correlated with that of Snail2 and predicted poor outcome of GBMs. Collectively, our data support that PRL1 promotes GBM progression by activating USP36-mediated Snail2 deubiquitination. This novel PRL1/USP36/Snail2 axis may be a promising therapeutic target for glioblastoma.