CLEC10A is a prognostic biomarker and correlated with clinical pathologic features and immune infiltrates in lung adenocarcinoma

From mitochondria to tumor suppression: ACAT1's crucial role in gastric cancer

Acetyl CoA acetyltransferase 1 (ACAT1), a mitochondrial enzyme, is mainly involved in the formation and decomposition of ketones, isoleucine, and fatty acids. Previous clinical studies showed that mutations in the ACAT1 gene lead to ketoacidosis, Notably the role of ACAT1 in human cancer' pathogenesis varies depending on cancer type, and its specific role in gastric cancer remains largely unknown. In the current study, we found that the expression of ACAT1 in primary late-stage gastric cancer tumor tissues was significantly lower than in early-stage tumors. This observation was further confirmed in high-grade gastric cancer cell line MKN45. The expression of CD44 and OCT4 was decreased, while CD24 expression was increased by overexpressing ACAT1 in MKN45 gastric cancer cells. Moreover, the ability of gastric cancer cells to form colonies on soft agar was also reduced by ACAT1 overexpression. Likewise, overexpression of ACAT1 inhibited epithelial mesenchymal transition (EMT) in gastric cancer cells evidenced by increased expression of the epithelial marker E-Cadherin, decreased expression of mesenchymal marker vimentin, and decreased expression levels of SNAI 1/3. In addition, ACAT1 overexpression inhibited cell migration and invasion, improved the response to 5-Fluorouracil (5-FU) and etoposide. In contrast, inhibition of ACAT1 activity promoted the proliferation of gastric cancer cells. The xenotransplantation results in nude mice showed that overexpression of ACAT1 in gastric cancer cells inhibited tumor growth in vivo. In addition, the low expression of ACAT1 in gastric cancer was further validated by searching public databases and conducting bioinformatic analyses. Mechanistically, bioinformatic analysis found that the inhibitory effect of ACAT1 in gastric cancer may be related to the Adipocytokine Signaling Pathway, Ppar Signaling Pathway, Propanoate Metabolism and P53 Signaling Pathway. Correlation analysis indicated ACAT1 mRNA expression was correlated with immune infiltrates. Collectively, our data show that ACAT1 induces pronounced inhibitory effects on gastric cancer initiation and development, which may impact future strategies to treat this aggressive cancer.

Exploring the astonishing beneficial effects of round gourd (Praecitrullus fistulosus) and plant lectins towards cancer: A comprehensive review

Praecitrullus fistulosus, commonly known as round gourd or tinda, is a remarkable source of bioactive substances like polyphenols, antioxidants, carotene, magnesium, and vitamin C. It is considered one of the Cucurbitaceae family due to its medicinal features. Plant lectins are carbohydrate-binding proteins that can bind and identify the carbohydrate moieties upon cancerous cells demonstrated some anticancer potentials. Several plant lectins are helpful as cancer biomarkers because they can find cancer cells and contribute to cell death initiation via apoptosis and autophagy, suggesting the possible role of cancer-inhibiting pathways. Therefore, round gourd and lectins might be useful in the controlling of cancer. This study compiled the most recent scientific literature regarding the round gourd and numerous plant lectins, and the clinical trials of lectins exploring their effects on cancer were examined. Research according to the literature, round gourd, and lectins demonstrated pharmacological alterations not only in cancer but in many other disorders as well. Thus, clinical investigations proved the beneficial impacts of round gourd and lectins on cancer due to their antioxidants, anti-inflammatory, and anticarcinogenic properties. Further studies are required to fully comprehend the potential applications of these plant-derived compounds against cancer, as well as to identify the round gourd components and clarify their mode of action.

Significance of NKX2-1 as a biomarker for clinical prognosis, immune infiltration, and drug therapy in lung squamous cell carcinoma

Background

This study was performed to determine the biological processes in which NKX2-1 is involved and thus its role in the development of lung squamous cell carcinoma (LUSC) toward improving the prognosis and treatment of LUSC.

Methods

Raw RNA sequencing (RNA-seq) data of LUSC from The Cancer Genome Atlas (TCGA) were used in bioinformatics analysis to characterize NKX2-1 expression levels in tumor and normal tissues. Survival analysis of Kaplan-Meier curve, the time-dependent receiver operating characteristic (ROC) curve, and a nomogram were used to analyze the prognosis value of NKX2-1 for LUSC in terms of overall survival (OS) and progression-free survival (PFS). Then, differentially expressed genes (DEGs) were identified, and Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and Gene Set Enrichment Analysis (GSEA) were used to clarify the biological mechanisms potentially involved in the development of LUSC. Moreover, the correlation between the NKX2-1 expression level and tumor mutation burden (TMB), tumor microenvironment (TME), and immune cell infiltration revealed that NKX2-1 participates in the development of LUSC. Finally, we studied the effects of NKX2-1 on drug therapy. To validate the protein and gene expression levels of NKX2-1 in LUSC, we employed immunohistochemistry(IHC) datasets, The Gene Expression Omnibus (GEO) database, and qRT-PCR analysis.

Results

NKX2-1 expression levels were significantly lower in LUSC than in normal lung tissue. It significantly differed in gender, stage and N classification. The survival analysis revealed that high expression of NKX2-1 had shorter OS and PFS in LUSC. The multivariate Cox regression hazard model showed the NKX2-1 expression as an independent prognostic factor. Then, the nomogram predicted LUSC prognosis. There are 51 upregulated DEGs and 49 downregulated DEGs in the NKX2-1 high-level groups. GO, KEGG and GSEA analysis revealed that DEGs were enriched in cell cycle and DNA replication.The TME results show that NKX2-1 expression was positively associated with mast cells resting, neutrophils, monocytes, T cells CD4 memory resting, and M2 macrophages but negatively associated with M1 macrophages. The TMB correlated negatively with NKX2-1 expression. The pharmacotherapy had great sensitivity in the NKX2-1 low-level group, the immunotherapy is no significant difference in the NKX2-1 low-level and high-level groups. The analysis of GEO data demonstrated concurrence with TCGA results. IHC revealed NKX2-1 protein expression in tumor tissues of both LUAD and LUSC. Meanwhile qRT-PCR analysis indicated a significantly lower NKX2-1 expression level in LUSC compared to LUAD. These qRT-PCR findings were consistent with co-expression analysis of NKX2-1.

Conclusion

We conclude that NKX2-1 is a potential biomarker for prognosis and treatment LUSC. A new insights of NKX2-1 in LUSC is still needed further research.

Ligand Recognition by the Macrophage Galactose-Type C-Type Lectin: Self or Non-Self?-A Way to Trick the Host's Immune System

The cells and numerous macromolecules of living organisms carry an array of simple and complex carbohydrates on their surface, which may be recognized by many types of proteins, including lectins. Human macrophage galactose-type lectin (MGL, also known as hMGL/CLEC10A/CD301) is a C-type lectin receptor expressed on professional antigen-presenting cells (APCs) specific to glycans containing terminal GalNAc residue, such as Tn antigen or LacdiNAc but also sialylated Tn antigens. Macrophage galactose-type lectin (MGL) exhibits immunosuppressive properties, thus facilitating the maintenance of immune homeostasis. Hence, MGL is exploited by tumors and some pathogens to trick the host immune system and induce an immunosuppressive environment to escape immune control. The aims of this article are to discuss the immunological outcomes of human MGL ligand recognition, provide insights into the molecular aspects of these interactions, and review the MGL ligands discovered so far. Lastly, based on the human fetoembryonic defense system (Hu-FEDS) hypothesis, this paper raises the question as to whether MGL-mediated interactions may be relevant in the development of maternal tolerance toward male gametes and the fetus.

Machine-learning and combined analysis of single-cell and bulk-RNA sequencing identified a DC gene signature to predict prognosis and immunotherapy response for patients with lung adenocarcinoma

BACKGROUND

Innate immune effectors, dendritic cells (DCs), influence cancer prognosis and immunotherapy significantly. As such, dendritic cells are important in killing tumors and influencing tumor microenvironment, whereas their roles in lung adenocarcinoma (LUAD) are largely unknown.

METHODS

In this study, 1658 LUAD patients from different cohorts were included. In addition, 724 cancer patients who received immunotherapy were also included. To identify DC marker genes in LUAD, we used single-cell RNAsequencing data for analysis and determined 83 genes as DC marker genes. Following that, integrative machine learning procedure was developed to construct a signature for DC marker genes.

RESULTS

Using TCGA bulk-RNA sequencing data as the training set, we developed a signature consisting of seven genes and classified patients by their risk status. Another six independent cohorts demonstrated the signature' s prognostic power, and multivariate analysis demonstrated it was an independent prognostic factor. LUAD patients in the high-risk group displayed more advanced features, discriminatory immune-cell infiltrations and immunosuppressive states. Cell-cell communication analysis indicates that tumor cells with lower risk scores communicate more actively with the tumor microenvironment. Eight independent immunotherapy cohorts revealed that patients with low-risk had better immunotherapy responses. Drug sensitivity analysis indicated that targeted therapy agents exhibited greater sensitivity to low-risk patients, while chemotherapy agents displayed greater sensitivity to high-risk patients. In vitro experiments confirmed that CTSH is a novel protective factor for LUAD.

CONCLUSIONS

An unique signature based on DC marker genes that is highly predictive of LUAD patients' prognosis and response to immunotherapy. CTSH is a new biomarker for LUAD.

Silencing of CD147 inhibits cell proliferation, migration, invasion, lipid metabolism dysregulation and promotes apoptosis in lung adenocarcinoma via blocking the Rap1 signaling pathway

OBJECTIVE

CD147 is an important glycoprotein that participates in the progression of diverse cancers. This study aims to explore the specific function of CD147 in lung adenocarcinoma (LUAD) and to reveal related downstream molecular mechanisms.

METHODS

Followed by silencing of CD147, the viability, migration, invasion, and apoptosis of LUAD cells were measured by CCK8, wound healing, transwell assay, and flow cytometer, respectively. The expression of CD147 and two markers of lipid metabolism (FASN and ACOX1) were detected by qRT-PCR. A xenograft tumor model was constructed to investigate the function of CD147 in vivo. Then transcriptome sequencing was performed to explore the potential mechanisms. After measuring the expression of Rap1 and p-p38 MAPK/p38 MAPK by western blot, the changes of CD147 and lipid metabolism markers (FASN, ACOX1) was detected by Immunohistochemistry. Moreover, a Rap1 activator and a Rap1 inhibitor were applied for feedback functional experiments.

RESULTS

CD147 was up-regulated in LUAD cells, and its silencing inhibited cell proliferation, migration, invasion, lipid metabolism dysregulation and promoted apoptosis, while overexpression of CD147 showed the opposite results. Silencing of CD147 also inhibited the growth of tumor xenografts in mice. Transcriptome sequencing revealed 834 up-regulated differentially expressed genes (DEGs) and 602 down-regulated DEGs. After functional enrichment, the Rap1 signaling pathway was selected as a potential target, which was then verified to be blocked by CD147 silencing. In addition, the treatment of Rap1 activator weakened the inhibiting effects of si-CD147 on the proliferation, migration, invasion, and lipid metabolism in LUAD cells, while the intervention of RAP1 inhibitor showed the opposite results.

CONCLUSIONS

Silencing of CD147 inhibited the proliferation, migration, invasion, lipid metabolism dysregulation and promoted apoptosis of LUAD cells through blocking the Rap1 signaling pathway.

Bioinformatics Analysis Reveals Novel Differentially Expressed Genes Between Ectopic and Eutopic Endometrium in Women with Endometriosis

Background

Endometriosis is one of the chronic and prevalent diseases among women. There is limited knowledge about its pathophysiology at the cellular and molecular levels, causing a lack of a definite cure for this disease. In this study, differentially expressed genes (DEGs) between ectopic and paired eutopic endometrium in women with endometriosis were analyzed through bioinformatics analysis for better understanding of the molecular pathogenesis of endometriosis.

Methods

Gene expression data of ectopic and paired eutopic endometrium were taken from the Gene Expression Omnibus database. DEGs were screened by the Limma package in R with considering specific criteria. Then, the protein-protein interaction network was reconstructed between DEGs. The fast unfolding clustering algorithm was used to find sub-networks (modules). Finally, the three most relevant modules were selected and the functional and pathway enrichment analyses were performed for the selected modules.

Results

A total of 380 DEGs (245 up-regulated and 135 down-regulated) were identified in the ectopic endometrium and compared with paired eutopic endometrium. The DEGs were predominantly enriched in an ensemble of genes encoding the extracellular matrix and associated proteins, metabolic pathways, cell adhesions and the innate immune system. Importantly, DPT, ASPN, CHRDL1, CSTA, HGD, MPZ, PED1A, and CLEC10A were identified as novel DEGs between the human ectopic tissue of endometrium and its paired eutopic endometrium.

Conclusion

The results of this study can open up a new window to better understanding of the molecular pathogenesis of endometriosis and can be considered for designing new treatment modalities.

Identification of PIMREG as a novel prognostic signature in breast cancer via integrated bioinformatics analysis and experimental validation

Background

Phosphatidylinositol binding clathrin assembly protein interacting mitotic regulator (PIMREG) expression is upregulated in a variety of cancers. However, its potential role in breast cancer (BC) remains uncertain.

Methods

The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were used to gather relevant information. The expression of PIMREG and its clinical implication in BC were assessed by using Wilcoxon rank-sum test. The prognostic value of PIMREG in BC was evaluated through the Cox regression model and nomogram, and visualized by Kaplan-Meier survival curves. Genes/proteins that interact with PIMREG in BC were also identified through GeneMANIA and MaxLink. Gene set enrichment analysis (GSEA) was then performed. The correlations of the immune cell infiltration and immune checkpoints with the expression of PIMREG in BC were explored via TIMER, TISIDB, and GEPIA. Potential drugs that interact with PIMREG in BC were explored via Q-omic. The siRNA transfection, CCK-8, and transwell migration assay were conducted to explore the function of PIMREG in cell proliferation and migration.

Results

PIMREG expression was significantly higher in infiltrating ductal carcinoma, estrogen receptor negative BC, and progestin receptor negative BC. High expression of PIMREG was associated with poor overall survival, disease-specific survival, and progression-free interval. A nomogram based on PIMREG was developed with a satisfactory prognostic value. PIMREG also had a high diagnostic ability, with an area under the curve of 0.940. Its correlations with several immunomodulators were also observed. Immune checkpoint CTLA-4 was significantly positively associated with PIMREG. HDAC2 was found as a potentially critical link between PIMREG and BRCA1/2. In addition, PIMREG knockdown could inhibit cell proliferation and migration in BC.

Conclusions

The high expression of PIMREG is associated with poor prognosis and immune checkpoints in BC. HDAC2 may be a critical link between PIMREG and BRCA1/2, potentially a therapeutic target.

Molecular fingerprints of nuclear genome and mitochondrial genome for early diagnosis of lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is the most prevalent subtype of lung cancer with high morbidity and mortality rates. Due to the heterogeneity of LUAD, its characteristics remain poorly understood. Exploring the clinical and molecular characteristics of LUAD is challenging but vital for early diagnosis.

METHODS

This observational and validation study enrolled 80 patients and 13 healthy controls. Nuclear and mtDNA-captured sequencings were performed.

RESULTS

This study identified a spectrum of nuclear and mitochondrial genome mutations in early-stage lung adenocarcinoma and explored their association with diagnosis. The correlation coefficient for somatic mutations in cfDNA and patient-matched tumor tissues was high in nuclear and mitochondrial genomes. The mutation number of highly mutated genes was evaluated, and the Least Absolute Shrinkage and Selection Operator (LASSO) established a diagnostic model. Receiver operating characteristic (ROC) curve analysis explored the diagnostic ability of the two panels. All models were verified in the testing cohort, and the mtDNA panel demonstrated excellent performance. This study identified somatic mutations in the nuclear and mitochondrial genomes, and detecting mutations in cfDNA displayed good diagnostic performance for early-stage LUAD. Moreover, detecting somatic mutations in the mitochondria may be a better tool for diagnosing early-stage LUAD.

CONCLUSIONS

This study identified specific and sensitive diagnostic biomarkers for early-stage LUAD by focusing on nuclear and mitochondrial genome mutations. This also further developed an early-stage LUAD-specific mutation gene panel for clinical utility. This study established a foundation for further investigation of LUAD molecular pathogenesis.

Discovery of drug targets and therapeutic agents based on drug repositioning to treat lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is the one of the most common subtypes in lung cancer. Although various targeted therapies have been used in the clinical practice, the 5-year overall survival rate of patients is still low. Thus, it is urgent to identify new therapeutic targets and develop new drugs for the treatment of the LUAD patients.

METHODS

Survival analysis was used to identify the prognostic genes. Gene co-expression network analysis was used to identify the hub genes driving the tumor development. A profile-based drug repositioning approach was used to repurpose the potentially useful drugs for targeting the hub genes. MTT and LDH assay were used to measure the cell viability and drug cytotoxicity, respectively. Western blot was used to detect the expression of the proteins.

FINDINGS

We identified 341 consistent prognostic genes from two independent LUAD cohorts, whose high expression was associated with poor survival outcomes of patients. Among them, eight genes were identified as hub genes due to their high centrality in the key functional modules in the gene-co-expression network analysis and these genes were associated with the various hallmarks of cancer (e.g., DNA replication and cell cycle). We performed drug repositioning analysis for three of the eight genes (CDCA8, MCM6, and TTK) based on our drug repositioning approach. Finally, we repurposed five drugs for inhibiting the protein expression level of each target gene and validated the drug efficacy by performing in vitro experiments.

INTERPRETATION

We found the consensus targetable genes for the treatment of LUAD patients with different races and geographic characteristics. We also proved the feasibility of our drug repositioning approach for the development of new drugs for disease treatment.

An integrative pan-cancer analysis reveals the carcinogenic effects of NCAPH in human cancer

BACKGROUND

Non-chromosomal structure maintenance protein condensin complex I subunit H (NCAPH) has been reported to play a regulatory role in a variety of cancers and is associated with tumor poor prognosis. This study aims to explore the potential role of NCAPH with a view to providing insights on pathologic mechanisms.

METHODS

The expression of NCAPH in different tumors was explored by The Cancer Genome Atlas (TCGA) and Genotype Tissue Expression (GTEx). The prognostic value of NCAPH was retrieved through GEPIA and Kaplan-Meier Plotter databases. Tumor Immunity Estimation Resource (TIMER) and Single-Sample Gene Set Enrichment Analysis (GSEA) to search for the association of NCAPH with tumor immune infiltration. The cBioPortal and PhosphoSite Plus databases showed NCAPH phosphorylation status in tumors. Gene set enrichment analysis (GSEA) was performed using bioinformatics.

RESULTS

Our findings revealed that NCAPH showed high expression levels in a wide range of tumor types, and was strongly correlated with the prognosis of patients. Moreover, a higher phosphorylation level at S59, S67, S76, S190, S222 and T38 site was discovered in head and neck squamous cell carcinoma (HNSC). NCAPH overexpression was positively correlated with the infiltration level of CD8+T cells and myeloid dendritic infiltration in breast cancer and thymoma.

CONCLUSIONS

The up-regulation of NCAPH was significantly correlated with the poor prognosis and immune infiltration in pan-cancer, and NCAPH could be served as a potential immunotherapeutic target for cancers.

The Prognostic Significance of FKBP1A and Its Related Immune Infiltration in Liver Hepatocellular Carcinoma

Liver hepatocellular carcinoma (LIHC) remains a global health challenge with poor prognosis and high mortality. FKBP1A was first discovered as a receptor for the immunosuppressant drug FK506 in immune cells and is critical for various tumors and cancers. However, the relationships between FKBP1A expression, cellular distribution, tumor immunity, and prognosis in LIHC remain unclear. Here, we investigated the expression level of FKBP1A and its prognostic value in LIHC via multiple datasets including ONCOMINE, TIMER, GEPIA, UALCAN, HCCDB, Kaplan–Meier plotter, LinkedOmics, and STRING. Human liver tissue microarray was employed to analyze the characteristics of FKBP1A protein including the expression level and pathological alteration in cellular distribution. FKBP1A expression was significantly higher in LIHC and correlated with tumor stage, grade and metastasis. The expression level of the FKBP1A protein was also increased in LIHC patients along with its accumulation in endoplasmic reticulum (ER). High FKBP1A expression was correlated with a poor survival rate in LIHC patients. The analysis of gene co-expression and the regulatory pathway network suggested that FKBP1A is mainly involved in protein synthesis, metabolism and the immune-related pathway. FKBP1A expression had a significantly positive association with the infiltration of hematopoietic immune cells including B cells, CD8⁺ T cells, CD4⁺ T cells, macrophages, neutrophils, and dendritic cells. Moreover, M2 macrophage infiltration was especially associated with a poor survival prognosis in LIHC. Furthermore, FKBP1A expression was significantly positively correlated with the expression of markers of M2 macrophages and immune checkpoint proteins such as PD-L1, CTLA-4, LAG3 and HAVCR2. Our study demonstrated that FKBP1A could be a potential prognostic target involved in tumor immune cell infiltration in LIHC.

Comprehensive analysis of clinical prognosis and CLIC1 immune invasion in lung adenocarcinoma

BACKGROUND

Chloride intracellular channel 1 (CLIC1) plays an important role in the process of cell epithelial transport, and is also involved in tumor invasion and metastasis. Due to its aberrant expression in cancer, the mechanism of action of CLIC1 in cancer has been carefully studied. In this study, we tried to investigate the relationship between CLIC1 and lung adenocarcinoma (LUAD).

METHODS

The RNA-sequencing data and clinical information of CLIC1 in lung adenocarcinoma were collected from the the cancer genome altas (TCGA) database and analyzed with R software. Paired t test and Mann-Whitney U test were used to detect differences between LUAD tissue and adjacent normal tissue, and the pROC software package performed reactive oxygen species (ROC) curves to detect cutoff values for CLIC1. The expression of CLIC1 in normal human tissues was extracted from the human protein altas (HPA) database, and analyzed clinical proteomic tumor analysis consortium by using UALCAN programme. The relationship between CLIC1 and LUAD was explored by enrichment analysis using gene oncology and Kyoto encyclopedia of genes and genomes. The tumor immunity estimation resource (TIMER) and integrated repository portal for tumor-immune system interactions (TISIDB) databases were used to analyze the correlation between CLIC1 and LUAD immune cell infiltration. Survival analysis of CLIC1 in LUAD was assessed by the PrognoScan database.

RESULTS

Compared with normal tissues, both mRNA (messenger Ribose Nucleic Acid) and protein of CLIC1 were overexpressed in LUAD, which was associated with shorter overall survial (OS). In addition, CLIC1 expression was in connection with some clinical-pathological characteristics like tumor node metatasis stages and lymph node metastases. What's more, CLIC1 may play a role in the immune infiltration of LUAD.

CONCLUSION

In summary, CLIC1 is up-regulated in LUAD and is associated with tumor metastasis, tumor staging, and OS. It may be regarded as a novel marker for prognostic judgement in LUAD.

GRAP2 is a prognostic biomarker and correlated with immune infiltration in lung adenocarcinoma

BACKGROUND

GRAP2 is an adaptor protein involved in leukocyte signal activation; however, the prognostic value of GRAP2 and its correlation with immune infiltration in lung adenocarcinoma (LUAD) are unclear.

METHODS

Original data were downloaded from the TCGA database and Gene Expression Omnibus (GEO) database. GRAP2 expression was analyzed with the TCGA and TIMER databases. We evaluated the influence of GRAP2 on clinical prognosis using the Kaplan-Meier plotter, GEO, and GEPIA database. The TIMER and TISIDB databases were used to investigate correlations between GRAP2 expression and cancer immune characteristics. Finally, we confirmed the expression of GRAP2 in LUAD by immunohistochemistry staining.

RESULTS

The transcription levels of GRAP2 were significantly lower in several human cancer types, including LUAD, than in adjacent normal tissues. Immunohistochemistry staining confirmed that LUAD tumor tissues had lower GRAP2 protein expression levels than adjacent normal tissues. GRAP2 downregulation was associated with poorer overall survival, pathologic stage, T stage, N stage, and primary therapy outcome in LUAD. Mechanistically, we found a hub gene set that included a total of 91 genes coexpressed with GRAP2, which were closely related to the immune response in LUAD. The expression levels of GRAP2 were positively correlated with the infiltration levels of multiple immune cells and the cumulative survival time of a few immune cells. GRAP2 expression was found to be positively correlated with that of multiple immune markers, chemokines, chemokine receptors, and MHC molecules in LUAD.

CONCLUSIONS

GRAP2 can be used as a biomarker for assessing prognosis and immune infiltration levels in LUAD.

Investigation of Biomarkers Associated with Low Platelet Counts in Normal Karyotype Acute Myeloid Leukemia

Acute myeloid leukemia (AML) patients are at risk of bleeding due to disease-related lack of platelets and systemic coagulopathy. Platelets play a role in hemostasis. Leukemic blasts have been shown to alter platelet activation in vitro. Here we investigated biomarkers associated with thrombocytopenia in normal karyotype AML (NK-AML). From The Cancer Genome Atlas database, case-control study was performed between normal karyotype (NK) platelet-decreased AML (PD-AML, platelet count < 100 × 109/L, n = 24) and NK platelet-not-decreased AML (PND-AML, with platelet count ≥ 100 × 109/L, n = 13). Differentially expressed gene analysis, pathway analysis and modelling for predicting platelet decrease in AML were performed. DEG analysis and pathway analysis revealed 157 genes and eight pathways specific for PD-AML, respectively. Most of the eight pathways were significantly involved in G-protein-coupled receptor-related pathway, cytokine-related pathway, and bone remodeling pathway. Among the key genes involved in at least one pathway, three genes including CSF1R, TNFSF15 and CLEC10A were selected as promising biomarkers for predicting PD-AML (0.847 of AUC in support vector machine model). This is the first study that identified biomarkers using RNA expression data analysis and could help understand the pathophysiology in AML with low platelet count.

Immunological role and prognostic potential of CLEC10A in pan-cancer

OBJECTIVES

CLEC10A is expressed in a variety of cells, involved in a variety of biological pathways including immune response, and is closely related to the development of tumor immune response. However, the role of CLEC10A from a pan-cancer perspective has not yet been analyzed, and its role in human cancer prognosis and immunology remains largely unclear.

METHODS

We studied the expression levels of CLEC10A and investigated its prognostic value in various cancers across distinct datasets including Oncomine, cBioPortal, and TCGA, and conducted immunohistochemical experiments using fresh bladder cancer and breast cancer samples to verify the results. In addition, we also performed GSEA of CLEC10A and explored the relationship between CLEC10A expression and immune infiltration, immune checkpoints, immune activation genes, immunosuppressive genes, chemokines and chemokine receptors.

RESULTS

The results showed that the expression level of CLEC10A in most tumors was significantly lower compared with non-cancerous tissue, and the decreased expression was related to poor prognosis and more advanced cancer stages. We also found that the expression of CLEC10A was significantly related to the immunomodulatory interaction between lymph and non-lymphocytes. Furthermore, the expression of CLEC10A was not only significantly correlated with the level of infiltration of CD4+T cells and CD8+T cells, but also closely related to immune checkpoints, immune activation genes, immunosuppressive genes, chemokines, and chemokine receptors. Importantly, our analysis of the relationship between CLEC10A and TMB and MSI also confirmed the speculation that CLEC10A may influence antitumor immunity by regulating the composition and immune mechanisms of the tumor microenvironment.

CONCLUSIONS

In conclusion, CLEC10A may serve as a new target for tumor immunotherapy and has great potential as a molecular biomarker for predicting pan-cancer prognosis and immune infiltration.

Diagnostic Value, Prognostic Value, and Immune Infiltration of LOX Family Members in Liver Cancer: Bioinformatic Analysis

Background

Liver cancer (LC) is well known for its prevalence as well as its poor prognosis. The aberrant expression of lysyl oxidase (LOX) family is associated with liver cancer, but their function and prognostic value in LC remain largely unclear. This study aimed to explore the function and prognostic value of LOX family in LC through bioinformatics analysis and meta-analysis.

Results

The expression levels of all LOX family members were significantly increased in LC. Area under the receiver operating characteristic curve (AUC) of LOXL2 was 0.946 with positive predictive value (PPV) of 0.994. LOX and LOXL3 were correlated with worse prognosis. Meta-analysis also validated effect of LOX on prognosis. Nomogram of these two genes and other predictors was also plotted. There was insufficient data from original studies to conduct meta-analysis on LOXL3. The functions of LOX family members in LC were mostly involved in extracellular and functions and structures. The expressions of LOX family members strongly correlated with various immune infiltrating cells and immunomodulators in LC.

Conclusions

For LC patients, LOXL2 may be a potential diagnostic biomarker, while LOX and LOXL3 have potential prognostic and therapeutic values. Positive correlation between LOX family and infiltration of various immune cells and immunomodulators suggests the need for exploration of their roles in the tumor microenvironment and for potential immunotherapeutic to target LOX family proteins.

Eukaryotic translation initiation factor 3 subunit B could serve as a potential prognostic predictor for breast cancer

The EIF3 gene family is essential in controlling translation initiation during the cell cycle. The significance of the EIF3 subunits as prognostic markers and therapeutic targets in breast cancer is not yet clear. We analyzed the expression of EIF3 subunits in breast cancer on the GEPIA and Oncomine databases and compared their expression in breast cancer and normal tissues using BRCA data downloaded from TCGA. Then we performed clinical survival analysis on the Kaplan–Meier Plotter database and clinicopathologic analysis on the bc-genexMiner v4.1 database. And EIF3B was chosen for mutation analysis via the Cancer SEA online tool. Meanwhile, we performed the immunohistochemical assay, real-time RT-PCR, and Western blotting to analyze EIF3B expression levels in breast cancer. An EIF3B knockdown and a negative control cell line were conducted for MTT assay and cell cycle analysis to assess cell growth. Specifically, the results of TCGA and online databases demonstrated that upregulated EIF3B was associated with poorer overall and advanced tumor progression. We also confirmed that EIF3B was more highly expressed in breast cancer cells and tissues than normal and correlated with a worse outcome. And knockdown of EIF3B expression inhibited the cell cycle and proliferation. Furthermore, EIF3B was highly mutated in breast cancer. Collectively, our results suggested EIF3B as a potential prognostic marker and therapeutic target for breast cancer.

ECE2 is a prognostic biomarker associated with m6A modification and involved in immune infiltration of lung adenocarcinoma

BACKGROUND

The targeted therapy for lung cancer relies on prognostic genes and requires further research. No research has been conducted to determine the effect of endothelin-converting enzyme 2 (ECE2) in lung cancer.

METHODS

We analyzed the expression of ECE2 in lung adenocarcinoma (LUAD) and normal adjacent tissues and its relationship with clinicopathological characteristics from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus database (GEO). Immunohistochemical staining was used to further validate the findings. GO/KEGG enrichment analysis and gene set enrichment analysis (GSEA) of ECE2 co-expression were performed using R software. Data from TIMER, the GEPIA database, and TCGA were analyzed to determine the relationship between ECE2 expression and LUAD immune infiltration. To investigate the relationship between ECE2 expression levels and LUAD m6A modification, TCGA data and GEO data were analyzed.

RESULTS

ECE2 is highly expressed in various cancers including LUAD. ECE2 showed high accuracy in distinguishing tumor and normal sample results. The expression level of ECE2 in LUAD was significantly correlated with tumor stage and prognosis. GO/KEGG enrichment analysis showed that ECE2 was closely related to mitochondrial gene expression, ATPase activity and cell cycle. GSEA analysis showed that ECE2-related differential gene enrichment pathways were related to mitotic cell cycle, MYC pathway, PLK1 pathway, DNA methylation pathway, HIF1A pathway and Oxidative stress-induced cellular senescence. Analysis of the TIMER, GEPIA database, and TCGA datasets showed that ECE2 expression levels were significantly negatively correlated with B cells, CD4+ cells, M2 macrophages, neutrophils, and dendritic cells. TCGA and GEO datasets showed that ECE2 was significantly associated with m6A modification-related genes HNRNPC, IGF2BP1, IGF2BP3 and RBM1.

CONCLUSION

ECE2 is associated with m6A modification and immune infiltration and is a prognostic biomarker in LUAD.

Identification of CDK2-Related Immune Forecast Model and ceRNA in Lung Adenocarcinoma, a Pan-Cancer Analysis

Background

Tumor microenvironment (TME) plays important roles in different cancers. Our study aimed to identify molecules with significant prognostic values and construct a relevant Nomogram, immune model, competing endogenous RNA (ceRNA) in lung adenocarcinoma (LUAD).

Methods

“GEO2R,” “limma” R packages were used to identify all differentially expressed mRNAs from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Genes with P-value <0.01, LogFC>2 or <-2 were included for further analyses. The function analysis of 250 overlapping mRNAs was shown by DAVID and Metascape software. By UALCAN, Oncomine and R packages, we explored the expression levels, survival analyses of CDK2 in 33 cancers. “Survival,” “survminer,” “rms” R packages were used to construct a Nomogram model of age, gender, stage, T, M, N. Univariate and multivariate Cox regression were used to establish prognosis-related immune forecast model in LUAD. CeRNA network was constructed by various online databases. The Genomics of Drug Sensitivity in Cancer (GDSC) database was used to explore correlations between CDK2 expression and IC50 of anti-tumor drugs.

Results

A total of 250 differentially expressed genes (DEGs) were identified to participate in many cancer-related pathways, such as activation of immune response, cell adhesion, migration, P13K-AKT signaling pathway. The target molecule CDK2 had prognostic value for the survival of patients in LUAD (P = 5.8e-15). Through Oncomine, TIMER, UALCAN, PrognoScan databases, the expression level of CDK2 in LUAD was higher than normal tissues. Pan-cancer analysis revealed that the expression, stage and survival of CDK2 in 33 cancers, which were statistically significant. Through TISIDB database, we selected 13 immunodepressants, 21 immunostimulants associated with CDK2 and explored 48 genes related to these 34 immunomodulators in cBioProtal database (P < 0.05). Gene Set Enrichment Analysis (GSEA) and Metascape indicated that 49 mRNAs were involved in PUJANA ATM PCC NETWORK (ES = 0.557, P = 0, FDR = 0), SIGNAL TRANSDUCTION (ES = –0.459, P = 0, FDR = 0), immune system process, cell proliferation. Forest map and Nomogram model showed the prognosis of patients with LUAD (Log-Rank = 1.399e-08, Concordance Index = 0.7). Cox regression showed that four mRNAs (SIT1, SNAI3, ASB2, and CDK2) were used to construct the forecast model to predict the prognosis of patients (P < 0.05). LUAD patients were divided into two different risk groups (low and high) had a statistical significance (P = 6.223e-04). By “survival ROC” R package, the total risk score of this prognostic model was AUC = 0.729 (SIT1 = 0.484, SNAI3 = 0.485, ASB2 = 0.267, CDK2 = 0.579). CytoHubba selected ceRNA mechanism medicated by potential biomarkers, 6 lncRNAs-7miRNAs-CDK2. The expression of CDK2 was associated with IC50 of 89 antitumor drugs, and we showed the top 20 drugs with P < 0.05.

Conclusion

In conclusion, our study identified CDK2 related immune forecast model, Nomogram model, forest map, ceRNA network, IC50 of anti-tumor drugs, to predict the prognosis and guide targeted therapy for LUAD patients.

CLEC10A is a prognostic biomarker and correlated with clinical pathologic features and immune infiltrates in lung adenocarcinoma

CLEC10A, (C-type lectin domain family 10, member A), as the member of C-type lectin receptors (CLRs), plays a vital role in modulating innate immunity and adaptive immunity and has shown great potential as an immunotherapy target for cancers. However, there is no functional research of CLEC10A in prognostic risk, immunotherapy or any other treatment of lung adenocarcinoma (LUAD). We performed bioinformatics analysis on LUAD data downloaded from TCGA (The Cancer Genome Atlas) and GEO (Gene Expression Omnibus), and jointly analysed with online databases such as HPA, LinkedOmics, TIMER, ESTIMATE and TISIDB. We found that lower expression of CLEC10A was accompanied with worse outcomes of LUAD patients. Moreover, CLEC10A expression was significantly correlated with a variety of the tumour-infiltrating immune cells (TIICs). As a promising prognosis predictor and potential immunotherapy target, the potential influence and mechanisms of CLEC10A in LUAD deserve further exploring.