NCAPG promotes the oncogenesis and progression of non-small cell lung cancer cells through upregulating LGALS1 expression

PPAR-γ/NF-kB/AQP3 axis in M2 macrophage orchestrates lung adenocarcinoma progression by upregulating IL-6

Aquaporin 3 (AQP3), which is mostly expressed in pulmonary epithelial cells, was linked to lung adenocarcinoma (LUAD). However, the underlying functions and mechanisms of AQP3 in the tumor microenvironment (TME) of LUAD have not been elucidated. Single-cell RNA sequencing (scRNA-seq) was used to study the composition, lineage, and functional states of TME-infiltrating immune cells and discover AQP3-expressing subpopulations in five LUAD patients. Then the identifications of its function on TME were examined in vitro and in vivo. AQP3 was associated with TNM stages and lymph node metastasis of LUAD patients. We classified inter- and intra-tumor diversity of LUAD into twelve subpopulations using scRNA-seq analyses. The analysis showed AQP3 was mainly enriched in subpopulations of M2 macrophages. Importantly, mechanistic investigations indicated that AQP3 promoted M2 macrophage polarization by the PPAR-γ/NF-κB axis, which affected tumor growth and migration via modulating IL-6 production. Mixed subcutaneous transplanted tumor mice and Aqp3 knockout mice models were further utilized, and revealed that AQP3 played a critical role in mediating M2 macrophage polarization, modulating glucose metabolism in tumors, and regulating both upstream and downstream pathways. Overall, our study demonstrated that AQP3 could regulate the proliferation, migration, and glycometabolism of tumor cells by modulating M2 macrophages polarization through the PPAR-γ/NF-κB axis and IL-6/IL-6R signaling pathway, providing new insight into the early detection and potential therapeutic target of LUAD.

Cross-attention enables deep learning on limited omics-imaging-clinical data of 130 lung cancer patients

Deep-learning tools that extract prognostic factors derived from multi-omics data have recently contributed to individualized predictions of survival outcomes. However, the limited size of integrated omics-imaging-clinical datasets poses challenges. Here, we propose two biologically interpretable and robust deep-learning architectures for survival prediction of non-small cell lung cancer (NSCLC) patients, learning simultaneously from computed tomography (CT) scan images, gene expression data, and clinical information. The proposed models integrate patient-specific clinical, transcriptomic, and imaging data and incorporate Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome pathway information, adding biological knowledge within the learning process to extract prognostic gene biomarkers and molecular pathways. While both models accurately stratify patients in high- and low-risk groups when trained on a dataset of only 130 patients, introducing a cross-attention mechanism in a sparse autoencoder significantly improves the performance, highlighting tumor regions and NSCLC-related genes as potential biomarkers and thus offering a significant methodological advancement when learning from small imaging-omics-clinical samples.

A novel LGALS1-depended and immune-associated fatty acid metabolism risk model in acute myeloid leukemia stem cells

Leukemia stem cells (LSCs) are recognized as the root cause of leukemia initiation, relapse, and drug resistance. Lipid species are highly abundant and essential component of human cells, which often changed in tumor microenvironment. LSCs remodel lipid metabolism to sustain the stemness. However, there is no useful lipid related biomarker has been approved for clinical practice in AML prediction and treatment. Here, we constructed and verified fatty acid metabolism-related risk score (LFMRS) model based on TCGA database via a series of bioinformatics analysis, univariate COX regression analysis, and multivariate COX regression analysis, and found that the LFMRS model could be an independent risk factor and predict the survival time of AML patients combined with age. Moreover, we revealed that Galectin-1 (LGALS1, the key gene of LFMRS) was highly expressed in LSCs and associated with poor prognosis of AML patients, and LGALS1 repression inhibited AML cell and LSC proliferation, enhanced cell apoptosis, and decreased lipid accumulation in vitro. LGALS1 repression curbed AML progression, lipid accumulation, and CD8+ T and NK cell counts in vivo. Our study sheds light on the roles of LFMRS (especially LGALS1) model in AML, and provides information that may help clinicians improve patient prognosis and develop personalized treatment regimens for AML.

Novel candidate metastasis-associated genes for synovial sarcoma

Synovial sarcoma (SS) is an aggressive soft tissue sarcoma with poor prognosis due to late recurrence and metastasis. Metastasis is an important prognostic factor of SS. This study aimed to identify the core genes and mechanisms associated with SS metastasis. Microarray data for GSE40021 and GSE40018 were obtained from the Gene Expression Omnibus database. 186 differentially expressed genes (DEGs) were identified. The biological functions and signalling pathways closely associated with SS metastasis included extracellular matrix (ECM) organization and ECM-receptor interaction. Gene set enrichment analysis showed that the terms cell cycle, DNA replication, homologous recombination and mismatch repair were significantly enriched in the metastasis group. Weighted gene co-expression network analysis identified the most relevant module and 133 hub genes, and 31 crossover genes were identified by combining DEGs. Subsequently, four characteristic genes, EXO1, NCAPG, POLQ and UHRF1, were identified as potential biomarkers associated with SS metastasis using the least absolute shrinkage and selection operator algorithm and validation dataset verification analysis. Immunohistochemistry results from our cohort of 49 patients revealed visible differences in the expression of characteristic genes between the non-metastatic and metastatic groups. Survival analysis indicated that high expression of characteristic genes predicted poor prognosis. Our data revealed that primary SS samples from patients who developed metastasis showed activated homologous recombination and mismatch repair compared to samples from patients without metastasis. Furthermore, EXO1, NCAPG, POLQ and UHRF1 were identified as potential candidate metastasis-associated genes. This study provides further research insights and helps explore the mechanisms of SS metastasis.

Up-regulation of NCAPG mediated by E2F1 facilitates the progression of osteosarcoma through the Wnt/β-catenin signaling pathway

Background

In recent years, there are few reports on non-SMC condensin I complex subunit G (NCAPG) in osteosarcoma. Our study aims to explore the biological role of NCAPG in osteosarcoma and its underlying molecular mechanism and to further clarify the reasons for the abnormal expression of NCAPG in osteosarcoma.

Methods

Here, we mined The Cancer Genome Atlas (TCGA) Program public database through bioinformatics methods, analyzed the differential expression of NCAPG in sarcoma tissue and normal tissue, and explored the relationship between NCAPG expression level and sarcoma tissue differentiation, including tumor recurrence, metastasis, and patient survival. Next, the transcription factors responsible for the abnormal expression of NCAPG in osteosarcoma tumors were predicted by multiple online website tools and verified via cellular experiments. Subsequently, loss of function and cell phenotype experiments were performed to confirm the effect of NCAPG on the malignant biological behavior of osteosarcoma cells. Mechanistically, by reviewing the literature, we found that NCAPG can affect the malignant progression of many solid tumors by regulating the Wnt/β-catenin signaling pathway. Therefore, we preliminarily investigated the potential effect of NCAPG on this pathway via western blot experiments in osteosarcoma.

Results

Increased expression of NCAPG was found in sarcoma compared to normal tissues, which was positively correlated with poor differentiation, metastasis, and poor prognosis. Combining the transcription factor prediction results, correlation analysis, and expression level in the TCGA public database with validation outcomes of in vitro cell assays, we found that E2F transcription factor 1 (E2F1) regulated the increased expression of NCAPG in osteosarcoma. The results of cell phenotype experiments showed that silencing NCAPG could inhibit the proliferation, migration, and invasion of osteosarcoma cells. The preliminary mechanistic investigation suggested that NCAPG may affect osteosarcoma progression through the Wnt/β-catenin pathway.

Conclusions

Our data reveal that E2F1 facilitates NCAPG expression in osteosarcoma by regulating the transcription of the NCAPG gene. Up-regulation of NCAPG promotes osteosarcoma progression via the Wnt/β-catenin signaling axis.

Expression of circular RNA has-circ-0009158 and identification of associated miRNA-mRNA network in hepatocellular carcinoma

Primary hepatocellular carcinoma (HCC) affects people all over the world. Circular RNAs are involved in the growth and development of several malignancies and regulate a number of biological processes. However, the roles of has-circ-0009158 in HCC remain unknown. This study explored the expression and associated miRNA-mRNA network of has-circ-0009158 in HCC. Quantitative real-time polymerase chain reaction was used to measure the expression of hsa-circ-0009158 in the HCC tissues of 143 patients and four human HCC cell lines. Then, the potential relationship of hsa-circ-0009158 expression with clinical characteristics and prognosis of patients was analyzed using the GO and KEGG databases. Correlated miRNA-mRNA networks were forecasted using the TCGA database and Cytoscape software. The hsa-circ-0009158 expression was significantly upregulated in HCC tissues and cell lines (P<0.001). The multivariate Cox analysis revealed that HCC patients were associated with high hsa-circ-0009158 expression. The bioinformatics analysis screened 1 miRNA, and 248 mRNAs associated with the circRNA in HCC. A pathway analysis suggested that the differentially expressed genes (DEGs) may be linked to the development and growth of HCC tumors. Ten hub genes (MELK, NCAPG, BUB1B, BIRC5, CDCA8, CENPF, BUB1, CDK1, TTK, TPX2) were identified from the PPI network based on the 248 genes. Additionally, the 10 hub genes that were verified had an association between high expression levels and low overall survival rates. As a result, the high expression of hsa-circ-0009158 was found to be a separate risk factor for recurrence and a poor prognosis in HCC patients.

Sulfotransferase SULT2B1 facilitates colon cancer metastasis by promoting SCD1-mediated lipid metabolism

Metastasis is responsible for at least 90% of colon cancer (CC)-related deaths. Lipid metabolism is a critical factor in cancer metastasis, yet the underlying mechanism requires further investigation. Herein, through the utilisation of single-cell sequencing and proteomics, we identified sulfotransferase SULT2B1 as a novel metastatic tumour marker of CC, which was associated with poor prognosis. CC orthotopic model and in vitro assays showed that SULT2B1 promoted lipid metabolism and metastasis. Moreover, SULT2B1 directly interacted with SCD1 to facilitate lipid metabolism and promoted metastasis of CC cells. And the combined application of SCD1 inhibitor CAY with SULT2B1- konockout (KO) demonstrated a more robust inhibitory effect on lipid metabolism and metastasis of CC cells in comparison to sole application of SULT2B1-KO. Notably, we revealed that lovastatin can block the SULT2B1-induced promotion of lipid metabolism and distant metastasis in vivo. Further evidence showed that SMC1A transcriptionally upregulated the expression of SULT2B1. Our findings unveiled the critical role of SULT2B1 in CC metastasis and provided a new perspective for the treatment of CC patients with distant metastasis.

ZNF643/ZFP69B Exerts Oncogenic Properties and Associates with Cell Adhesion and Immune Processes

The global cancer burden remains high; thus, a better understanding of the molecular mechanisms driving carcinogenesis is needed to improve current prevention and treatment options. We previously detected the ZNF643/ZFP69B gene upregulated in multiple tumors, and we speculated it may play a role in tumor biology. To test this hypothesis, we employed TCGA-centered databases to correlate ZNF643 status with various clinicopathological parameters. We also performed RNA-seq analysis and in vitro studies assessing cancer cell phenotypes, and we searched for ZNF643-bound genomic loci. Our data indicated higher levels of ZNF643 in most analyzed tumors compared to normal samples, possibly due to copy number variations. ZNF643 mRNA correlated with diverse molecular and immune subtypes and clinicopathological features (tumor stage, grade, patient survival). RNA-seq analysis revealed that ZNF643 silencing triggers the deregulation of the genes implicated in various cancer-related processes, such as growth, adhesion, and immune system. Moreover, we observed that ZNF643 positively influences cell cycle, migration, and invasion. Finally, our ChIP-seq analysis indicated that the genes associated with ZNF643 binding are linked to adhesion and immune signaling. In conclusion, our data confirm the oncogenic properties of ZNF643 and pinpoint its impact on cell adhesion and immune processes.

Analysis of two-gene signatures and related drugs in small-cell lung cancer by bioinformatics

Small-cell lung cancer (SCLC) has a poor prognosis and can be diagnosed with systemic metastases. Nevertheless, the molecular mechanisms underlying the development of SCLC are unclear, requiring further investigation. The current research aims to identify relevant biomarkers and available drugs to treat SCLC. The bioinformatics analysis comprised three Gene Expression Omnibus datasets (including GSE2149507, GSE6044, and GSE30219). Using the limma R package, we discovered differentially expressed genes (DEGs) in the current work. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were made by adopting the DAVID website. The DEG protein-protein interaction network was built based on the Search Tool for the Retrieval of Interacting Genes/Proteins website and visualized using the CytoHubba plugin in Cytoscape, aiming to screen the top ten hub genes. Quantitative real-time polymerase chain reaction was adopted for verifying the level of the top ten hub genes. Finally, the potential drugs were screened and identified using the QuartataWeb database. Totally 195 upregulated and 167 downregulated DEGs were determined. The ten hub genes were NCAPG, BUB1B, TOP2A, CCNA2, NUSAP1, UBE2C, AURKB, RRM2, CDK1, and KIF11. Ten FDA-approved drugs were screened. Finally, two genes and related drugs screened could be the prospective drug targets for SCLC treatment.

TRAIP serves as a potential prognostic biomarker and correlates with immune infiltrates in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is one of the major types of lung cancer with high morbidity and mortality. The TRAF-interacting protein (TRAIP) is a ring-type E3 ubiquitin ligase which has been recently identified to play pivotal roles in various cancers. However, the expression and function of TRAIP in LUAD remain elusive.

METHODS

In this study, we used bioinformatic tools as well as molecular experiments to explore the exact role of TRAIP and the underlying mechanism.

RESULTS

Data mining across the UALCAN, GEPIA and GTEx, GEO and HPA databases revealed that TRAIP was significantly overexpressed in LUAD tissues than that in adjacent normal tissues. Kaplan-Meier curve showed that high TRAIP expression was associated with poor overall survival (OS) and relapse-free survival (RFS). Univariate and multivariate cox regression analysis revealed that TRAIP was an independent risk factor in LUAD. And the TRAIP-based nomogram further supported the prognostic role of TRAIP in LUAD. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis demonstrated that TRAIP-associated genes were mainly involved in DNA replication, cell cycle and other processes. The immune infiltration analysis indicated that TRAIP expression was tightly correlated with the infiltration of diverse immune cell types, including B cell, CD8 + T cell, neutrophil and dendritic cell. Moreover, TRAIP expression was observed to be significantly associated with tumor infiltrating lymphocytes (TILs) and immune checkpoint molecules. In vitro experiments further confirmed knockdown of TRAIP inhibited cell migration and invasion, as well as decreasing chemokine production and inhibiting M2-like macrophage recruitment. Lastly, CMap analysis identified 10 small molecule compounds that may target TRAIP, providing potential therapies for LUAD.

CONCLUSIONS

Collectively, our study found that TRAIP is an oncogenic gene in LUAD, which may be a potential prognostic biomarker and promising therapeutic target for LUAD.

Galectin-1-mediated high NCAPG expression correlates with poor prognosis in gastric cancer

Galectin-1 (Gal1) and non-SMC condensin I complex, subunit G (NCAPG) are associated with metastasis in several malignant tumors. However, their precise roles in gastric cancer (GC) remain uncertain. This study explored the clinical significance and relationship of Gal1 and NCAPG in GC. Gal1 and NCAPG expressions were significantly up-regulated in GC compared to adjacent non-cancerous tissues by immunohistochemistry (IHC) and Western blotting. Besides, methods including stable transfection, quantitative real-time reverse transcription PCR, Western blotting, Matrigel invasion and wound-healing assays in vitro, were also conducted. IHC scores for Gal1 and NCAPG had a positive correlation in GC tissues. High Gal1 or NCAPG expression significantly correlated with poor prognosis in GC, and Gal1 combined with NCAPG had a synergetic effect on the prediction of GC prognosis. Gal1 overexpression in vitro enhanced NCAPG expression, cell migration, and invasion in SGC-7901 and HGC-27 cells. Simultaneous Gal1 overexpression and NCAPG knockdown in GC cells partly rescued the migrative and invasive abilities. Thus, Gal1 promoted GC invasion through increased NCAPG expression. The present study demonstrated the prognostic significance of the combination of Gal1 and NCAPG in GC for the first time.

Association of NCAP family genes with prognosis and immune infiltration of human sarcoma

OBJECTIVE

This study was conducted to explore the correlation of NCAP family genes with expression, prognosis, and immune infiltration in human sarcoma.

RESULTS

Compared with normal human tissues, six NCAP family genes were highly expressed in sarcoma tissues, and high expression of the six genes were significantly associated with the poor prognosis of sarcoma patients. The expression of NCAPs in sarcoma was significantly related to the low infiltration level of macrophages and CD4+ T cells. GO and KEGG enrichment analysis showed that NCAPs and their interacting genes were mainly enriched in organelle fission for biological processes (BP), spindle for cellular component (CC), tubulin binding for molecular function (MF), and 'Cell cycle' pathway.

METHODS

We explored the expression of NCAP family members by ONCOMINE, and GEPIA databases. Additionally, the prognostic value of NCAP family genes in sarcoma was detected by Kaplan-Meier Plotter and GEPIA databases. Moreover, we explored the relationship between NCAP family gene expression level and immune infiltration using the TIMER database. Finally, we performed GO and KEGG analysis for NCAPs-related genes by DAVID database.

CONCLUSION

The six members of NCAP gene family can be used as biomarkers to predict the prognosis of sarcoma. They were also correlated with the low immune infiltration in sarcoma.

NCAPG as a novel prognostic biomarker in numerous cancers: a meta-analysis and bioinformatics analysis

BACKGROUND

Identification of effective biomarkers for cancer prognosis is a primary research challenge. Recently, several studies have reported the relationship between NCAPG and the occurrence of various tumors. However, none have combined meta-analytical and bioinformatics approaches to systematically assess the role of NCAPG in cancer.

METHODS

We searched four databases, namely, PubMed, Web of Science, Embase, and the Cochrane Library, for relevant articles published before April 30, 2022. The overall hazard ratio or odds ratio and 95% confidence intervals were calculated to assess the relationship between NCAPG expression and cancer survival prognosis or clinical characteristics. Furthermore, the aforementioned results were validated using the GEPIA2, Kaplan-Meier plotter, and PrognoScan databases.

RESULTS

The meta-analysis included eight studies with 1096 samples. The results showed that upregulation of NCAPG was correlated with poorer overall survival (hazard ratio = 2.90, 95% confidence interval = 2.06-4.10, P < 0.001) in the cancers included in the study. Subgroup analysis showed that in some cancers, upregulation of NCAPG was correlated with age, distant metastasis, lymph node metastasis, TNM stage, relapse, differentiation, clinical stage, and vascular invasion. These results were validated using the GEPIA2, UALCAN, and PrognoScan databases. We also explored the processes of NCAPG methylation and phosphorylation.

CONCLUSION

Dysregulated NCAPG expression is associated with the clinical prognostic and pathological features of various cancers. Therefore, NCAPG can serve as a human cancer therapeutic target and a new potential prognostic biomarker.

LGALS1 was related to the prognosis of clear cell renal cell carcinoma identified by weighted correlation gene network analysis combined with differential gene expression analysis

Understanding the molecular mechanism of clear cell renal cell carcinoma (ccRCC) is essential for predicting the prognosis and developing new targeted therapies. Our study is to identify hub genes related to ccRCC and to further analyze its prognostic significance. The ccRCC gene expression profiles of GSE46699 from the Gene Expression Omnibus (GEO) database and datasets from the Cancer Genome Atlas Database The Cancer Genome Atlas were used for the Weighted Gene Co-expression Network Analysis (WGCNA) and differential gene expression analysis. We screened out 397 overlapping genes from the four sets of results, and then performed Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genome (KEGG) pathways. In addition, the protein-protein interaction (PPI) network of 397 overlapping genes was mapped using the STRING database. We identified ten hub genes (KNG1, TIMP1, ALB, C3, GPC3, VCAN, P4HB, CHGB, LGALS1, EGF) using the CytoHubba plugin of Cytoscape based on the Maximal Clique Centrality (MCC) score. According to Kaplan-Meier survival analysis, higher expression of LGALS1 and TIMP1 was related to poorer overall survival (OS) in patients with ccRCC. Univariate and multivariate Cox proportional hazard analysis showed that the expression of LGALS1 was an independent risk factor for poor prognosis. Moreover, the higher the clinical grade and stage of ccRCC, the higher the expression of LGALS1. LGALS1 may play an important role in developing ccRCC and may be potential a biomarker for prognosis and treatment targets.

MCM4 is a novel prognostic biomarker and promotes cancer cell growth in glioma

BACKGROUND

Gliomas account for 75% of all primary malignant brain tumors in adults and result in high mortality. Accumulated evidence has declared the minichromosome maintenance protein complex (MCM) gene family plays a critical role in modulating the cell cycle and DNA replication stress. However, the biological function and clinic characterization of nine MCM members in low-grade glioma are not yet clarified.

METHODS

In this study, we utilized diverse public databases, including The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), Rembrandt, Human Protein Atlas (HPA), Linkedomics, cbioportal, Tumor and Immune System Interaction Database (TISIDB), single-sample GSEA (ssGSEA), Tumor Immune Estimation Resource (TIMER), Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Therapeutics Response Portal databases to explore the mRNA and protein expression profiles, gene mutation, clinical features, diagnosis, prognosis, signaling pathway, tumor mutational burden (TMB), immune subtype, immune cell infiltration, immune modulator and drug sensitivity of nine MCMs. Afterward, qRT-PCR was utilized to detect the expression of the MCM family in glioblastoma multiforme (GBM) cell lines. The one-, three-, or five-year survival rate was predicted by utilizing a nomogram established by cox proportional hazard regression.

RESULTS

In this study, we found that nine MCMs were consistently up-regulated in glioma tissues and glioma cell lines. Elevated nine MCMs expressions were significantly correlated with a higher tumor stage, isocitrate dehydrogenase (IDH) mutates, 1p/19q codeletion, histological type, and primary therapy outcome. Survival analyses showed that higher expression of MCM2-MCM8 (minichromosome maintenance protein2-8) and MCM10 (minichromosome maintenance protein 10) were linked with poor overall survival (OS) and progression-free survival (PFS) in glioma patients. On the other hand, up-regulated MCM2-MCM8 and MCM10 were significantly associated with shorter disease-specific survival (DSS) in glioma patients. Univariate and multivariate analyses revealed that MCM2 (minichromosome maintenance protein2), MCM4 (minichromosome maintenance protein 4), MCM6 (minichromosome maintenance protein 6), MCM7 (minichromosome maintenance protein 7) expression and tumor grade, 1p/19q codeletion, age, and primary therapy outcome were independent factors correlated with the clinical outcome of glioma patients. More importantly, a prognostic MCMs model constructed using the above five prognostic genes could predict the overall survival of glioma patients with medium-to-high accuracy. Furthermore, functional enrichment analysis indicated that MCMs principal participated in regulating cell cycle and DNA replication. DNA copy number variation (CNV) and DNA methylation significantly affect the expression of MCMs. Finally, we uncover that MCMs expression is highly correlated with immune cell infiltration, immune modulator, TMB, and drug sensitivity.

CONCLUSIONS

In summary, this finding confirmed that MCM4 is a potential target of precision therapy for patients with glioma.

Identification of the hub and prognostic genes in liver hepatocellular carcinoma via bioinformatics analysis

Hepatocellular carcinoma (HCC) is a common malignancy. However, the molecular mechanisms of the progression and prognosis of HCC remain unclear. In the current study, we merged three Gene Expression Omnibus (GEO) datasets and combined them with The Cancer Genome Atlas (TCGA) dataset to screen differentially expressed genes. Furthermore, protein‒protein interaction (PPI) and weighted gene coexpression network analysis (WGCNA) were used to identify key gene modules in the progression of HCC. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses indicated that the terms were associated with the cell cycle and DNA replication. Then, four hub genes were identified (AURKA, CCNB1, DLGAP5, and NCAPG) and validated via the expression of proteins and transcripts using online databases. In addition, we established a prognostic model using univariate Cox proportional hazards regression and least absolute shrinkage and selection operator (LASSO) regression. Eight genes were identified as prognostic genes, and four genes (FLVCR1, HMMR, NEB, and UBE2S) were detrimental gens. The areas under the curves (AUCs) at 1, 3 and 5 years were 0.622, 0.69, and 0.684 in the test dataset, respectively. The effective of prognostic model was also validated using International Cancer Genome Consortium (ICGC) dataset. Moreover, we performed multivariate independent prognostic analysis using multivariate Cox proportional hazards regression. The results showed that the risk score was an independent risk factor. Finally, we found that all prognostic genes had a strong positive correlation with immune infiltration. In conclusion, this study identified the key hub genes in the development and progression of HCC and prognostic genes in the prognosis of HCC, which was significant for the future diagnosis and prognosis of HCC.

The role of NCAPG in various of tumors

Non-SMC Condensin I complex subunit G (NCAPG), a mitosis-associated chromosomal condensation protein, is related to sister chromatid appropriate separation during the condensation and fusion of chromosomes and responsible for the condensation and stabilization of chromosomes during meiosis and mitosis. Studies have shown that NCAPG is highly adjusted in a variety of cancers, and its related molecular mechanism affects tumor cell proliferation, invasion, metastasis, and apoptosis including hepatocellular carcinoma, prostate cancer, breast cancer, gastric cancer, gliomas, lung adenocarcinoma, colorectal cancer, ovarian cancer, and endometrial cancer. Clinically, the expression of NCAPG is strongly correlated with N-classification, M-classification, and clinical stage, and NCAPG is valuable for the prognosis of patients with lung adenocarcinoma. In addition, NCAPG can also reduce the sensitivity of tumor cells such as breast cancer to reduce the reaction of the original chemotherapy, so that tumor cells are drug-resistance. In summary, NCAPG can serve as a new diagnosis and treatment target for a variety of cancers, and is also a very promising prognostic marker. Therefore, this review summarizes the critical role of NCAPG in the diagnosis, treatment, and prognosis for various cancers, and the mechanism by which NCAPG plays its pivotal roles.

AC099850.3/NCAPG Axis Predicts Poor Prognosis and is Associated with Resistance to EGFR Tyrosine-Kinase Inhibitors in Lung Adenocarcinoma

Background

TKI-acquired resistance markedly interferes with treatment of lung cancer patients with EGFR mutant features. Long non-coding RNAs (lncRNAs) modify EGFR-TKI resistance during tumor progression. Non-structural maintenance of chromosomes condensin I complex subunit G (NCAPG) is a mitosis-related protein that is involved in tumorigenesis. We investigated the potential regulatory lncRNAs of NCAPG in lung adenocarcinoma (LUAD) and assessed their roles in EGFR-TKI resistance.

Methods

Data for 1678 lung cancer patients were retrieved from TCGA and GEO databases and used to evaluate NCAPG and lncRNAs expressions, as well as their prognostic significance in LUAD. Protein levels of NCAPG in LUAD were validated by immuno-histochemistry. To assess the relationship between NCAPG levels and EGFR-TKIs sensitivity, a cohort of 57 LUAD patients administered with EGFR-TKIs was used.

Results

Both NCAPG and lncRNA AC099850.3 were over-expressed in LUAD tissues, and correlated with tumor progression and poor prognosis in LUAD. LncRNA AC099850.3 was identified as a potential regulator of NCAPG expressions. The AC099850.3/NCAGP axis was markedly correlated with EGFR mutations and IC₅₀ of EGFR-TKIs. Besides, elevated NCAPG levels were associated with EGFR-TKIs resistance in 57 LUAD patients undergoing TKIs treatment. Gene set enrichment analysis revealed that both AC099850.3 and NCAGP were abundant in the cell cycle and the p53 signaling pathway.

Conclusion

The AC099850.3/NCAPG axis is a potential prognostic predictor and therapeutic biomarker for EGFR-TKIs in LUAD.