Upregulation of HOXC9 generates interferon-gamma resistance in gastric cancer by inhibiting the DAPK1/RIG1/STAT1 axis

The HOX Gene Family's Role as Prognostic and Diagnostic Biomarkers in Hematological and Solid Tumors

The HOX gene family encodes for regulatory transcription factors that play a crucial role in embryogenesis and differentiation of adult cells. This highly conserved family of genes consists of thirty-nine genes in humans that are located in four clusters, A-D, on different chromosomes. While early studies on the HOX gene family have been focused on embryonic development and its related disorders, research has shifted to examine aberrant expression of HOX genes and the subsequent implication in cancer prediction and progression. Due to their role of encoding master regulatory transcription factors, the abnormal expression of HOX genes has been shown to affect all stages of tumorigenesis and metastasis. This review highlights the novel role of the HOX family's clinical relevance as both prognostic and diagnostic biomarkers in hematological and solid tumors.

Recent advancements in understanding of biological role of homeobox C9 in human cancers

Homeobox (HOX) C9, a member of the HOX family, is an important transcription factor, and it plays a significant role in various biological processes. This family of genes is highly valued for their essential roles in establishing and maintaining the body axis during embryonic development and adult tissues. Further, HOXC9 plays a central role in neuronal differentiation, angiogenesis, and adipose distribution, which are essential for the development of the nervous system, maturation of tissues and organs, and maintenance of energy balance and metabolic health. Recent research has found that abnormal HOXC9 expression is closely associated with the development and progression of various tumor types. The HOXC9 expression level can be an indicator of tumor prognosis. Therefore, elucidating the association between HOXC9 expression and its regulatory mechanisms and tumorigenesis can provide novel insights on the diagnosis and treatment of patients with cancer.

Identification of a potential bioinformatics-based biomarker in keloids and its correlation with immune infiltration

Keloid formation is a pathological consequence resulting from cutaneous irritation and injury, primarily attributed to excessive collagen matrix deposition and fibrous tissue proliferation. Chronic inflammation, left uncontrolled over an extended period, also stands as a substantial contributing factor. The precise mechanisms underlying keloid formation remain unclear. Therefore, this study aimed to identify key genes for diagnostic purposes. To achieve this, we used two Gene Expression Omnibus (GEO) data sets to identify differentially expressed genes. We identified one particular gene, homeobox C9 (HOXC9), using a thorough strategy involving two algorithms (least absolute shrinkage and selection operator and support vector machine-recursive feature elimination) and weighted gene co-expression network analysis. We then assessed its expression in normal and keloid tissues. In addition, we explored its temporal expression patterns via Mfuzz time clustering analysis. In our comprehensive analysis, we observed that immune infiltration, as well as cell proliferation, are crucial to keloid formation. Thus, we investigated immune cell infiltration in the keloid and normal groups, as well as the correlation between HOXC9 and these immune cells. It was found that HOXC9 was closely associated with the immune microenvironment of keloids. This shows that HOXC9 can serve as a potential biomarker and therapeutic target for keloids.

The role of interferon-gamma and its receptors in gastrointestinal cancers

Gastrointestinal malignancies are the most prevalent type of cancer around the world. Even though numerous studies have evaluated gastrointestinal malignancies, the actual underlying mechanism is still unknown. These tumors have a poor prognosis and are frequently discovered at an advanced stage. Globally, there is an increase in the incidence and mortality of gastrointestinal malignancies, including those of the stomach, esophagus, colon, liver, and pancreas. Growth factors and cytokines are signaling molecules that are part of the tumor microenvironment and play a significant role in the development and spread of malignancies. IFN-γ induce its effects by activation of intracellular molecular networks. The main pathway involved in IFN-γ signaling is the JAK/STAT pathway, which regulates the transcription of hundreds of genes and mediates various biological responses. IFN-γ receptor is composed of two IFN-γR1 chains and two IFN-γR2 chains. Binding to IFN-γ, causes the intracellular domains of IFN-γR2 to oligomerize and transphosphorylate with IFN-γR1 which activates downstream signaling components: JAK1 and JAK2. These activated JAKs phosphorylate the receptor, creating binding sites for STAT1. STAT1 is then phosphorylated by JAK, resulting in the formation of STAT1 homodimers (gamma activated factors or GAFs) that translocate to the nucleus and regulate gene expression. The balance between positive and negative regulation of this pathway is crucial for immune responses and tumorigenesis. In this paper, we evaluate the dynamic roles of IFN- γ and its receptors in gastrointestinal cancers and present evidence that inhibiting IFN- γ signaling may be an effective treatment strategy.

A Novel Molecular Classification Method for Glioblastoma Based on Tumor Cell Differentiation Trajectories

The latest 2021 WHO classification redefines glioblastoma (GBM) as the hierarchical reporting standard by eliminating glioblastoma, IDH-mutant and only retaining the tumor entity of "glioblastoma, IDH-wild type." Knowing that subclassification of tumors based on molecular features is supposed to facilitate the therapeutic choice and increase the response rate in cancer patients, it is necessary to carry out molecular classification of the newly defined GBM. Although differentiation trajectory inference based on single-cell sequencing (scRNA-seq) data holds great promise for identifying cell heterogeneity, it has not been used in the study of GBM molecular classification. Single-cell transcriptome sequencing data from 10 GBM samples were used to identify molecular classification based on differentiation trajectories. The expressions of identified features were validated by public bulk RNA-sequencing data. Clinical feasibility of the classification system was examined in tissue samples by immunohistochemical (IHC) staining and immunofluorescence, and their clinical significance was investigated in public cohorts and clinical samples with complete clinical follow-up information. By analyzing scRNA-seq data of 10 GBM samples, four differentiation trajectories from the glioblastoma stem cell-like (GSCL) cluster were identified, based on which malignant cells were classified into five characteristic subclusters. Each cluster exhibited different potential drug sensitivities, pathways, functions, and transcriptional modules. The classification model was further examined in TCGA and CGGA datasets. According to the different abundance of five characteristic cell clusters, the patients were classified into five groups which we named Ac-G, Class-G, Neo-G, Opc-G, and Undiff-G groups. It was found that the Undiff-G group exhibited the worst overall survival (OS) in both TCGA and CGGA cohorts. In addition, the classification model was verified by IHC staining in 137 GBM samples to further clarify the difference in OS between the five groups. Furthermore, the novel biomarkers of glioblastoma stem cells (GSCs) were also described. In summary, we identified five classifications of GBM and found that they exhibited distinct drug sensitivities and different prognoses, suggesting that the new grouping system may be able to provide important prognostic information and have certain guiding significance for the treatment of GBM, and identified the GSCL cluster in GBM tissues and described its characteristic program, which may help develop new potential therapeutic targets for GSCs in GBM.

Potential mechanisms and prognostic model of eRNAs-regulated genes in stomach adenocarcinoma

Gastric Carcinoma is the fourth leading cause of cancer deaths worldwide, in which stomach adenocarcinoma (STAD) is the most common histological type. A growing amount of evidence has suggested the importance of enhancer RNAs (eRNAs) in the cancer. However, the potential mechanism of eRNAs in STAD remains unclear. The eRNAs-regulated genes (eRRGs) were identified through four different enhancer resources. The differentially expressed eRRGs were obtained by ‘DESeq2’ R package. The prognosis prediction model was constructed by Cox and Lasso regression analysis. The ‘ChAMP’ R package and ‘maftools’ R package were used to investigate the multi-omics characters. In this study, combining the concept of contact domain, a total of 9014 eRRGs including 4926 PCGs and 4088 lncRNAs were identified and these eRRGs showed higher and more stable expression. Besides, the functions of these genes were mainly associated with tumor-related biological processes. Then, a prognostic prediction model was constructed and the AUC values of the 1-, 3- and 5-year survival prediction reached 0.76, 0.84 and 0.84, respectively, indicating that this model has a high accuracy. Finally, the difference between high-risk group and low-risk group were investigated using multi-omics data including gene expression, DNA methylation and somatic mutations. Our study provides significant clues for the elucidation of eRNAs in STAD and may help improve the overall survival for STAD patients.

Mechanism of Herb Pairs Astragalus mongholicus and Curcuma phaeocaulis Valeton in Treating Gastric Carcinoma: A Network Pharmacology Combines with Differential Analysis and Molecular Docking

Background

Gastric carcinoma (GC) is a kind of digestive tract tumor that is highly malignant and has a very poor prognosis. Although both Astragalus mongholicus (AM, huáng qí) and Curcuma phaeocaulis Valeton (CPV, é zhú) can slow the onset and progression of GC, the mechanism by which AM-CPV works in the treatment of GC is uncertain.

Materials and Methods

The traditional Chinese medicine network databases TCMSP, TCMID, and ETCM were used to identify the key functional components and associated targets of AM and CPV. To establish a theoretical foundation, the development of gastric cancer (GC) was predicted utilizing a GEO gene chip and TCGA difference analysis mixed with network pharmacology. A herbal-ingredient-target network and a core target-signal pathway network were created using GO and KEGG enrichment analyses. The molecular docking method was used to evaluate seventeen main targets and their compounds.

Results

Cell activity, reactive oxygen species modification, metabolic regulation, and systemic immune activation may all be involved in the action mechanism of the AM-CPV drug-pair in the treatment of GC. It inhibits the calcium signaling route, the AGE-RAGE signaling system, the cAMP signaling pathway, the PI3K-Akt signaling network, and the MAPK signaling pathway, slowing the progression of GC. The number of inflammatory substances in the tumor microenvironment is reduced, GC cell proliferation is deprived, apoptosis is promoted, and GC progression is retarded through controlling the IL-17 signaling route, TNF signaling pathway, and other inflammation-related pathways.

Conclusions

The AM-CPV pharmaceutical combination regulates GC treatment via a multitarget, component, and signal pathway with a cooperative and bidirectional regulatory mechanism. Its active constituents may treat GC by regulating the expression of STAT1, MMP9, IL6, HSP90AA1, JUN, CCL2, IFNG, CXCL8, and other targets, as well as activating or inhibiting immune-inflammatory and cancer signaling pathways.

Upregulation of HOXC9 generates interferon-gamma resistance in gastric cancer by inhibiting the DAPK1/RIG1/STAT1 axis

Clinical reports indicate that gastric cancer (GC) has a high mortality rate, but its pathological mechanism remains poorly understood. This work integrated bioinformatics analysis with experimental verification to explore novel biomarkers of gastric cancer. First, weighted gene coexpression network analysis was applied to screen significant genes correlated with GC development. Gene set enrichment analysis was also used to unearth the most relevant biological functions of significant genes. As a result, we discovered homeobox C9 (HOXC9) as a novel oncogene in GC, primarily through negatively regulating immune response. High expression of HOXC9 predicted a poor prognosis in GC patients, and knocking down HOXC9 efficiently enhanced the interferon‐gamma (IFNγ)‐dependent apoptosis in two GC cell lines as well as organoids from patients. Furthermore, cleaved caspase‐3/7 and phosphorylated signal transducer and activator of transcription 1 (p‐STAT1) were also significantly enhanced in HOXC9 knockdown cells and organoids treated with IFNγ. Mechanistically, we found that HOXC9 inhibited the death‐associated protein kinase 1 (DAPK1) and its downstream retinoic acid‐inducible gene‐I (RIG1) to generate GC IFNγ resistance. In summary, we identified and confirmed that HOXC9 generates IFNγ resistance in GC by inhibiting the DAPK1/RIG1/p‐STAT1 axis.