HCK is a Potential Prognostic Biomarker that Correlates with Immune Cell Infiltration in Acute Myeloid Leukemia

Comprehensive analysis of the HCK gene in myeloid neoplasms: Insights into biological functions, prognosis, and response to antineoplastic agents

Myeloid neoplasms result from molecular alterations in hematopoietic stem cells, with acute myeloid leukemia (AML) being one of the most aggressive and with a poor prognosis. Hematopoietic cell kinase (HCK) is a proto-oncogene that encodes a protein-tyrosine kinase of the Scr family, and it is highly expressed in AML. The present study investigated HCK expression in normal hematopoietic cells across myeloid differentiation stages and myeloid neoplasm patients. Within the AML cohort, we explored the impact of HCK expression on clinical outcomes and its correlation with clinical, genetic, and laboratory characteristics. Furthermore, we evaluated the association between HCK expression and the response to antineoplastic agents using ex vivo assay data from AML patients. HCK expression is higher in differentiated subpopulations of myeloid cells. High HCK expression was observed in patients with chronic myelomonocytic leukemia, chronic myeloid leukemia, and AML. In patients with AML, high levels of HCK negatively impacted overall and disease-free survival. High HCK expression was also associated with worse molecular risk groups and white blood cell count; however, it was not an independent prognostic factor. In functional genomic analyses, high HCK expression was associated with several biological and molecular processes relevant to leukemogenesis. HCK expression was also associated with sensitivity and resistance to several drugs currently used in the clinic. In conclusion, our analysis confirmed the differential expression of HCK in myeloid neoplasms and its potential association with unfavorable molecular risks in AML. We also provide new insights into HCK biological functions, prognosis, and response to antineoplastic agents.

Identification of key signaling pathways and hub genes related to immune infiltration in Kawasaki disease with resistance to intravenous immunoglobulin based on weighted gene co-expression network analysis

Background: Kawasaki disease (KD) is an acute vasculitis, that is, the leading cause of acquired heart disease in children, with approximately 10%-20% of patients with KD suffering intravenous immunoglobulin (IVIG) resistance. Although the underlying mechanism of this phenomenon remains unclear, recent studies have revealed that immune cell infiltration may associate with its occurrence. Methods: In this study, we downloaded the expression profiles from the GSE48498 and GSE16797 datasets in the Gene Expression Omnibus database, analyzed differentially expressed genes (DEGs), and intersected the DEGs with the immune-related genes downloaded from the ImmPort database to obtain differentially expressed immune-related genes (DEIGs). Then CIBERSORT algorithm was used to calculate the immune cell compositions, followed by the WGCNA analysis to identify the module genes associated with immune cell infiltration. Next, we took the intersection of the selected module genes and DEIGs, then performed GO and KEGG enrichment analysis. Moreover, ROC curve validation, Spearman analysis with immune cells, TF, and miRNA regulation network, and potential drug prediction were implemented for the finally obtained hub genes. Results: The CIBERSORT algorithm showed that neutrophil expression was significantly higher in IVIG-resistant patients compared to IVIG-responsive patients. Next, we got differentially expressed neutrophil-related genes by intersecting DEIGs with neutrophil-related module genes obtained by WGCNA, for further analysis. Enrichment analysis revealed that these genes were associated with immune pathways, such as cytokine-cytokine receptor interaction and neutrophil extracellular trap formation. Then we combined the PPI network in the STRING database with the MCODE plugin in Cytoscape and identified 6 hub genes (TLR8, AQP9, CXCR1, FPR2, HCK, and IL1R2), which had good diagnostic performance in IVIG resistance according to ROC analysis. Furthermore, Spearman's correlation analysis confirmed that these genes were closely related to neutrophils. Finally, TFs, miRNAs, and potential drugs targeting the hub genes were predicted, and TF-, miRNA-, and drug-gene networks were constructed. Conclusion: This study found that the 6 hub genes (TLR8, AQP9, CXCR1, FPR2, HCK, and IL1R2) were significantly associated with neutrophil cell infiltration, which played an important role in IVIG resistance. In a word, this work rendered potential diagnostic biomarkers and prospective therapeutic targets for IVIG-resistant patients.

Clinicopathological value of hematopoietic cell kinase overexpression in laryngeal squamous cell carcinoma tissues

Laryngeal squamous cell carcinoma (LSCC) is the most lethal cancer in head and neck tumors. Although hematopoietic cell kinase (HCK) has been proven to be an oncogene in several solid tumors, its roles in LSCC remain obscure. This is the first study to evaluate the clinical value of HCK in LSCC, with the aim of exploring its expression status and potential molecular mechanisms underlying LSCC. LSCC tissue-derived gene chips and RNA-seq data were collected for a quantitive integration of HCK mRNA expression level. To confirm the protein expression level of HCK, a total of 82 LSCC tissue specimens and 56 non-tumor laryngeal epithelial controls were collected for in-house tissue microarrays and immunohistochemical staining. Kaplan-Meier curves were generated to determine the ability of HCK in predicting overall survival, progress-free survival, and disease-free survival of LSCC patients. LSCC overexpressed genes and HCK co-expressed genes were intersected to preliminarily explore the enriched signaling pathways of HCK. It was noticed that HCK mRNA was markedly overexpressed in 323 LSCC tissues compared with 196 non-LSCC controls (standardized mean difference = 0.81, p < 0.0001). Upregulated HCK mRNA displayed a moderate discriminatory ability between LSCC tissues and non-tumor laryngeal epithelial controls (area under the curve = 0.78, sensitivity = 0.76, specificity = 0.68). The higher expression level of HCK mRNA could predict worse overall survival and disease-free survival for LSCC patients (p = 0.041 and p = 0.013). Lastly, upregulated co-expression genes of HCK were significantly enriched in leukocyte cell-cell adhesion, secretory granule membrane, and extracellular matrix structural constituent. Immune-related pathways were the predominantly activated signals, such as cytokine-cytokine receptor interaction, Th17 cell differentiation, and Toll-like receptor signaling pathway. In conclusion, HCK was upregulated in LSCC tissues and could be utilized as a risk predictor. HCK may promote the development of LSCC by disturbing immune signaling pathways.

CD86 Is Associated with Immune Infiltration and Immunotherapy Signatures in AML and Promotes Its Progression

Background

Cluster of differentiation 86 (CD86), also known as B7-2, is a molecule expressed on antigen-presenting cells that provides the costimulatory signals required for T cell activation and survival. CD86 binds to two ligands on the surface of T cells: the antigen CD28 and cytotoxic T lymphocyte-associated protein 4 (CTLA-4). By binding to CD28, CD86-together with CD80-promotes the participation of T cells in the antigen presentation process. However, the interrelationships among CD86, immunotherapy, and immune infiltration in acute myeloid leukemia (AML) are unclear.

Methods

The immunological effects of CD86 in various cancers (including on chemokines, immunostimulators, MHC, and receptors) were evaluated through a pan-cancer analysis using TCGA and GEO databases. The relationship between CD86 expression and mononucleotide variation, gene copy number variation, methylation, immune checkpoint blockers (ICBs), and T-cell inflammation score in AML was subsequently examined. ESTIMATE and limma packages were used to identify genes at the intersection of CD86 with StromalScore and ImmuneScore. Subsequently, GO/KEGG and PPI network analyses were performed. The immune risk score (IRS) model was constructed, and the validation set was used for verification. The predictive value was compared with the TIDE score.

Results

CD86 was overexpressed in many cancers, and its overexpression was associated with a poor prognosis. CD86 expression was positively correlated with the expression of CTLA4, PDCD1LG2, IDO1, HAVCR2, and other genes and negatively correlated with CD86 methylation. The expression of CD86 in AML cell lines was detected by QRT-PCR and Western blot, and the results showed that CD86 was overexpressed in AML cell lines. Immune infiltration assays showed that CD86 expression was positively correlated with CD8 T cell, Dendritic cell, macrophage, NK cell, and Th1_cell and also with immune examination site, immune regulation, immunotherapy response, and TIICs. ssGSEA showed that CD86 was enriched in immune-related pathways, and CD86 expression was correlated with mutations in the genes RB1, ERBB2, and FANCC, which are associated with responses to radiotherapy and chemotherapy. The IRS score performed better than the TIDE website score.

Conclusion

CD86 appears to participate in immune invasion in AML and is an important player in the tumor microenvironment in this malignancy. At the same time, the IRS score developed by us has a good effect and may provide some support for the diagnosis of AML. Thus, CD86 may serve as a potential target for AML immunotherapy.

A novel natural killer cell-related signatures to predict prognosis and chemotherapy response of pancreatic cancer patients

Background: Natural killer (NK) cells are involved in monitoring and eliminating cancers. The purpose of this study was to develop a NK cell-related genes (NKGs) in pancreatic cancer (PC) and establish a novel prognostic signature for PC patients. Methods: Omic data were downloaded from The Cancer Genome Atlas Program (TCGA), Gene Expression Omnibus (GEO), International Cancer Genome Consortium (ICGC), and used to generate NKG-based molecular subtypes and construct a prognostic signature of PC. NKGs were downloaded from the ImmPort database. The differences in prognosis, immunotherapy response, and drug sensitivity among subtypes were compared. 12 programmed cell death (PCD) patterns were acquired from previous study. A decision tree and nomogram model were constructed for the prognostic prediction of PC. Results: Thirty-two prognostic NKGs were identified in PC patients, and were used to generate three clusters with distinct characteristics. PCD patterns were more likely to occur at C1 or C3. Four prognostic DEGs, including MET, EMP1, MYEOV, and NGFR, were found among the clusters and applied to construct a risk signature in TCGA dataset, which was successfully validated in PACA-CA and GSE57495 cohorts. The four gene expressions were negatively correlated with methylation level. PC patients were divided into high and low risk groups, which exerts significantly different prognosis, clinicopathological features, immune infiltration, immunotherapy response and drug sensitivity. Age, N stage, and the risk signature were identified as independent factors of PC prognosis. Low group was more easily to happened on PCD. A decision tree and nomogram model were successfully built for the prognosis prediction of PC patients. ROC curves and DCA curves demonstrated the favorable and robust predictive capability of the nomogram model. Conclusion: We characterized NKGs-derived molecular subtypes of PC patients, and established favorable prognostic models for the prediction of PC prognosis, which may serve as a potential tool for prognosis prediction and making personalized treatment in PC.

A panel of seven immune-related genes can serve as a good predictive biomarker for cervical squamous cell carcinoma

Objective: Cervical cancer is one of the most common gynecological malignancies. The interaction between tumor microenvironment and immune infiltration is closely related to the progression of cervical squamous cell carcinoma (CSCC) and patients' prognosis. Herein, a panel of immune-related genes was established for more accurate prognostic prediction. Methods: The transcriptome information of tumor and normal samples were obtained from TCGA-CSCC and GTEx. Differentially expressed genes (DEGs) were defined from it. Immune-related genes (IRGs) were retrieved from the ImmPort database. After removing the transcriptome data which not mentioned in GSE44001, IR-DEGs were preliminarily identified. Then, TCGA-CSCC samples were divided into training and testing set (3:1) randomly. Univariate Cox analysis, LASSO regression analysis and multivariate Cox analysis were used in turn to construct the signature to predict the overall survival (OS) and disease-free survival (DFS). External validation was performed in GSE44001, and initial clinical validation was performed by qRT-PCR. Function enrichment analysis, immune infiltration analysis and establishment of nomogram were conducted as well. Results: A prognostic prediction signature consisting of seven IR-DEGs was established. High expression of NRP1, IGF2R, SERPINA3, TNF and low expression of ICOS, DES, HCK suggested that CSCC patients had shorter OS (POS<0.001) and DFS (PDFS<0.001). AUC values of 1-, 3-, five- year OS were 0.800, 0.831 and 0.809. Analyses in other validation sets showed good consistency with the results in training set. The signature can serve as an independent prognostic factor for OS (HR = 1.166, p < 0.001). AUC values of 1-, 3-, five- year OS based on the nomogram were 0.769, 0.820 and 0.807. Functional enrichment analysis suggested that these IR-DEGs were associated with receptor interaction and immune cell activity. Immune infiltration analysis indicated that patients in high-risk group had lower immune infiltration, weaker immune function, and were more likely to benefit from immune checkpoint inhibitor therapy. Through qRT-PCR on clinical samples, expression of NRP1, IGF2R, SERPINA3 and TNF were significantly upregulated in tumor tissue, while ICOS and DES were significantly downregulated. Conclusion: To conclude, the immune-related signature can provide strong support for exploration of immune infiltration, prediction of prognosis and response to immunotherapy through stratify CSCC patients into subgroups.