C-C Motif Chemokine Ligand 5 (CCL5): A Potential Biomarker and Immunotherapy Target for Osteosarcoma

BACKGROUND

Osteosarcoma (OS) is the most common primary malignant tumor of bone tissue, which has an insidious onset and is difficult to detect early, and few early diagnostic markers with high specificity and sensitivity. Therefore, this study aims to identify potential biomarkers that can help diagnose OS in its early stages and improve the prognosis of patients.

METHODS

The data sets of GSE12789, GSE28424, GSE33382 and GSE36001 were combined and normalized to identify Differentially Expressed Genes (DEGs). The data were analyzed by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genome (KEGG) and Disease Ontology (DO). The hub gene was selected based on the common DEG that was obtained by applying two regression methods: the Least Absolute Shrinkage and Selection Operator (LASSO) and Support vVector Machine (SVM). Then the diagnostic value of the hub gene was evaluated in the GSE42572 data set. Finally, the correlation between immunocyte infiltration and key genes was analyzed by CIBERSORT.

RESULTS

The regression analysis results of LASSO and SVM are the following three DEGs: FK501 binding protein 51 (FKBP5), C-C motif chemokine ligand 5 (CCL5), complement component 1 Q subcomponent B chain (C1QB). We evaluated the diagnostic performance of three biomarkers (FKBP5, CCL5 and C1QB) for osteosarcoma using receiver operating characteristic (ROC) analysis. In the training group, the area under the curve (AUC) of FKBP5, CCL5 and C1QB was 0.907, 0.874 and 0.676, respectively. In the validation group, the AUC of FKBP5, CCL5 and C1QB was 0.618, 0.932 and 0.895, respectively. It is noteworthy that these genes were more expressed in tumor tissues than in normal tissues by various immune cell types, such as plasma cells, CD8+ T cells, T regulatory cells (Tregs), activated NK cells, activated dendritic cells and activated mast cells. These immune cell types are also associated with the expression levels of the three diagnostic genes that we identified.

CONCLUSION

We found that CCL5 can be considered an early diagnostic gene of osteosarcoma, and CCL5 interacts with immune cells to influence tumor occurrence and development. These findings have important implications for the early detection of osteosarcoma and the identification of novel therapeutic targets.

Development and Validation of CXCR4 Nomogram-Based Immune Infiltration/Tumor Inflammation in Primary Glioblastoma

Glioblastoma (GBM) is a highly malignant and aggressive tumor with poor prognosis. Therefore, the discovery of new prognostic molecular markers is of great significance for clinical prognosis. The CXC chemokine receptor (CXCR) members play a key regulatory role in many cancers. In this study, we explore the clinical value and application of the CXCR members in primary glioblastoma. Two GBM datasets from The Cancer Genome Atlas (TCGA) and The China Glioma Genome Atlas (CGGA) databases were used to explore the relationship between differential expression of CXCRs and GBM subtypes as well as immune infiltration. C-X-C motif chemokine receptor 4 (CXCR4) was screened as an independent prognostic factor, and a nomogram and risk prediction model were developed and tested in the CGGA database using the TCGA database. Receiver operating curve (ROC) and decision curve analysis (DCA) found good accuracy and net benefit of the models. The correlation of CXCR4 with immune infiltration and tumor was analyzed using CancerSEA and TIMER. In in vitro experiments, we found that CXCR4 was significantly overexpressed in glioblastoma and was closely related to the inflammatory response of U251/U87 cells. CXCR4 is an excellent independent prognostic factor for glioblastoma and positively correlates with tumor inflammation.

Bioinformatics Analysis of Immune Infiltration In Endometrial Carcinoma Tumors and its Relationship With Prognosis

BACKGROUND/AIM

Endometrial carcinoma (EC) is the most common gynecological cancer, but lacks specific targetable markers. In order to explore the immune-related molecules that affect the progression and prognosis of EC, we analyzed the differential expression of genes in different histological grades of the disease.

MATERIALS AND METHODS

EC-related gene-expression data of different histological grades were downloaded from TCGA and GEO databases. The list of immune-related genes was obtained from the ImmPort database. In order to identity differentially-expressed genes (DEGs), differential-expression analysis was performed. The intersection of DEGs and immune-related genes was termed immune-related differentially-expressed genes (IRDEGs). IRDEGs were enriched in cancer-related functional pathways by gene-correlation analysis and GSEA-enrichment analysis. The association of IRDEGs with immune-cell tumor infiltration and gene polymorphisms was analyzed using IRDEG mRNA and protein-expression data in EC from TCGA and THPA databases.

RESULTS

Three IRDEGs, TNFSF15, SEMA3E and TNFSF10, were involved in the analysis of the prognosis of EC patients. IRDEGs were not only related to clinical characteristics but could also affect the prognosis of patients. Gene-correlation and GSEA-enrichment analysis of IRDEGs showed that TNFSF15 and TNFSF10 were co-enriched in the IL2-STAT5 functional pathway. IRDEGs had a significant correlation with a variety of immune-cell types infiltrating EC tumors and were related to EC prognosis. IRDEG mRNA- and protein-expression levels were increased in EC compared to normal tissues.

CONCLUSION

TNFSF15, SEMA3E and TNFSF10 may regulate the progression and prognosis of EC patients by affecting immune-cell infiltration of EC tumors.

LINC00426 is a potential immune phenotype-related biomarker and an overall survival predictor in PAM50 luminal B breast cancer

Background: Breast cancer (BRCA) represents the most frequent diagnosed malignancy in women worldwide. Despite treatment advances, BRCAs eventually develop resistance to targeted therapies, resulting in poor prognosis. The identification of new biomarkers, like immune-related long non-coding RNAs (lncRNAs), could contribute to the clinical management of BRCA patients. In this report, we evaluated the LINC00426 expression in PAM50 BRCA subtypes from two clinical independent cohorts (BRCA-TCGA and GEO-GSE96058 datasets). Methods and results: Using Cox regression models and Kaplan-Meier survival analyses, we identified that LINC00426 expression was a consistent overall survival (OS) predictor in luminal B (LB) BRCA patients. Subsequently, differential gene expression and gene set enrichment analyses identified that LINC00426 expression was associated with different immune-related and cancer-related pathways and processes in LB BRCA. Additionally, the LINC00426 expression was correlated with the infiltration level of diverse immune cell populations, alongside immune checkpoint and cytolytic activity-related gene expression. Conclusion: This evidence suggests that LINC00426 is a potential biomarker of immune phenotype and an OS predictor in PAM50 LB BRCA.

Development and validation of an immune infiltration/tumor proliferation-related Notch3 nomogram for predicting survival in patients with primary glioblastoma

Background: Notch receptors (Notch 1/2/3/4), the critical effectors of the Notch pathway, participate in the tumorigenesis and progression of many malignancies. However, the clinical roles of Notch receptors in primary glioblastoma (GBM) have not been fully elucidated. Methods: The genetic alteration-related prognostic values of Notch receptors were determined in the GBM dataset from The Cancer Genome Atlas (TCGA). Two GBM datasets from TCGA and Chinese Glioma Genome Atlas (CGGA) were used to explore the differential expression between Notch receptors and IDH mutation status, and GBM subtypes. The biological functions of Notch Receptors were explored by Gene Ontology and KEGG analysis. The expression and prognostic significance of Notch receptors were determined in the TCGA and CGGA datasets and further validated in a clinical GBM cohort by immunostaining. A Notch3-based nomogram/predictive risk model was constructed in the TCGA dataset and validated in the CGGA dataset. The model performance was evaluated by receiver operating curves, calibration curves, and decision curve analyses. The Notch3-related phenotypes were analyzed via CancerSEA and TIMER. The proliferative role of Notch3 in GBM was validated in U251/U87 glioma cells by Western blot and immunostaining. Results: Notch receptors with genetic alterations were associated with poor survival of GBM patients. Notch receptors were all upregulated in GBM of TCGA and CGGA databases and closely related to the regulation of transcription, protein-lysine N-methyltransferase activity, lysine N-methyltransferase activity, and focal adhesion. Notch receptors were associated with Classical, Mesenchymal, and Proneural subtypes. Notch1 and Notch3 were closely correlated with IDH mutation status and G-CIMP subtype. Notch receptors displayed the differential expression at the protein level and Notch3 showed a prognostic significance in a clinical GBM cohort. Notch3 presented an independent prognostic role for primary GBM (IDH1 mutant/wildtype). A Notch3-based predictive risk model presented favorable accuracy, reliability, and net benefits for predicting the survival of GBM patients (IDH1 mutant/wildtype and IDH1 wildtype). Notch3 was closely related to immune infiltration (macrophages, CD4⁺ T cells, and dendritic cells) and tumor proliferation. Conclusion: Notch3-based nomogram served as a practical tool for anticipating the survival of GBM patients, which was related to immune-cell infiltration and tumor proliferation.

Multi-Omics Analysis Reveals Intratumor Microbes as Immunomodulators in Colorectal Cancer

Recent studies indicated that intratumor microbes are an essential part of the tumor microenvironment. Here, we performed an integrated analysis of genetic, epigenetic, and intratumor microbial factors to unravel the potential remodeling mechanisms of immune-cell infiltration (ICI) and tumorigenesis of colorectal cancer (CRC). We identified the components and structure of the intratumor microbiome as primary contributors to the difference in survival between ICI subtypes. Multiple tumor-infiltrating immune cells (TIICs) and immune-related genes were associated with intratumor microbial abundance. Additionally, we found that Clostridium was enriched in CRC patients who were nonsensitive to immune checkpoint blockade (ICB) therapy. We further provided clues that the intratumor microbes might influence the response to ICB therapy by mediating TIICs, especially MAIT (mucosa-associated invariant T) cells. Finally, three ICB-related TIICs and 22 of their associated microbes showed the potential to predict the response to ICB therapy (area under the receiver operating characteristic curve [AUC] = 89%). Our findings highlight the crucial role of intratumor microbes in affecting immune-cell infiltration patterns, prognosis, and therapy response of CRC and provide insights for improving current immunotherapeutic treatment strategies and prognosis for CRC patients. IMPORTANCE Using the multi-omics data from The Cancer Genome Atlas (TCGA) colorectal cancer (CRC) cohort, we estimated the tumor microenvironment (TME) infiltration patterns of patients and unraveled the interplay of gene expression, epigenetic modification, and the intratumor microbiome. This study suggests the impact of intratumor microbes on maintaining the tumor immune microenvironment in the pathogenesis of CRC and modulating the response to immune checkpoint blockade (ICB) therapy. We identified a set of combined features, including 3 ICB-related tumor-infiltrating immune cells (TIICs) and 22 of their associated microbes, that are predictive of ICB responses.

Indigo Pulverata Levis (Chung-Dae, Persicaria tinctoria) Alleviates Atopic Dermatitis-like Inflammatory Responses In Vivo and In Vitro

Atopic dermatitis (AD) is a chronic inflammatory skin disease associated with a type 2 T helper cell (Th2) immune response. The IndigoPulverata Levis extract (CHD) is used in traditional Southeast Asian medicine; however, its beneficial effects on AD remain uninvestigated. Therefore, we investigated the therapeutic effects of CHD in 2,4-dinitrochlorobenzene (DNCB)-induced BALB/c mice and tumor necrosis factor (TNF)-α- and interferon gamma (IFN)-γ-stimulated HaCaT cells. We evaluated immune cell infiltration, skin thickness, and the serum IgE and TNF-α levels in DNCB-induced AD mice. Moreover, we measured the expression levels of pro-inflammatory cytokines, mitogen-activated protein kinase (MAPK), and the nuclear factor-kappa B (NF-κB) in the mice dorsal skin. We also studied the effect of CHD on the translocation of NF-κB p65 and inflammatory chemokines in HaCaT cells. Our in vivo results revealed that CHD reduced the dermis and epidermis thicknesses and inhibited immune cell infiltration. Furthermore, it suppressed the proinflammatory cytokine expression and MAPK and NF-κB phosphorylations in the skin tissue and decreased serum IgE and TNF-α levels. In vitro results indicated that CHD downregulated inflammatory chemokines and blocked NF-κB p65 translocation. Thus, we deduced that CHD is a potential drug candidate for AD treatment.

Identification and verification of YBX3 and its regulatory gene HEIH as an oncogenic system: A multidimensional analysis in colon cancer

The novel gene YBX3 is important for regulating translation and RNA catabolism and encodes a protein with a highly conserved cold-shock domain. However, its pathogenic roles across cancers (e.g., colon cancer) and its regulation remain unclear. We identified the pathogenic roles of YBX3 and its regulatory lncRNA HEIH in various cancers and investigated their effects on tumor progression in colon cancer. Methods including RNA pull-down, MS, and TMA of 93 patients, qPCR of 12 patients with diverse clinicopathologic stages, and western blotting were performed. The pancancer analysis showed that YBX3 expression varies significantly among not only cancer types but also molecular and immune subtypes of the same cancer. Furthermore, its expression in colon cancer is clinically significant, and there is an obvious negative regulatory association between HEIH and YBX3. Among various cancers, especially colon cancer, YBX3 is more related than HEIH expression to the clinical features and prognosis of subgroups. The receiver operating characteristic analysis showed that HEIH and YBX3 have similar predictive capacity in various cancers. The analysis of differentially expressed genes in colon cancer revealed that they have similar hub gene networks, indicating an oncogenic system with a strong overlap. The results also suggest that YBX3 is associated with tumor immune evasion via different mechanisms involving T-cell exclusion in different cancer types and by the tumor infiltration of immune cells. Interestingly, scRNA-seq revealed that HEIH inhibits this phenomenon. Our results also suggest that YBX3 expression is associated with immune or chemotherapeutic outcomes in various cancers, and YBX3 exhibited a higher predictive power than two of seven standardized biomarkers for response outcomes and overall survival of immune checkpoint blockade subcohorts. In colon cancer cell lines, lncRNA-HEIH and YBX3 associate. MS confirmed that YBX3 was pulled down with HEIH, and western blot showed that HEIH knockdown disinhibited YBX3. This study strongly suggests that lncRNA-HEIH/YBX3 is a pancancer immune-oncogenic system and could serve as a biomarker for diagnosis and prognosis and as a therapeutic target, especially in colon cancer.

Extracellular Matrix-Related Six-lncRNA Signature as a Novel Prognostic Biomarker for Bladder Cancer

Introduction

Bladder cancer (BC) is the fourth-commones cancer and the sixth-leading cause of cancer-related death among men. However, a lack of reliable biomarkers remains a problem forprognosis and treatment of BC. lncRNAs have been shown to play important roles in various cancers, and have emerged as promising biomarkers for cancer prognosis and treatment.

Methods

In this study, using univariate and multivariate Cox regression analysis, we examined the differential expression profiles of 1,651 lncRNAs in the TCGA BLCA cohort and created a prognostic gene signature composed of six lncRNAs (for SNHG12, MAFG-DT, ASMTL-AS1, LINC02321, LINC01322, and LINC00922), designed the SMALLL signature.

Results

The SMALLL signature displayed significant prognostic power for overall survival for BC patients in multiple cohorts. Gene Ontology analysis showed that genes coexpressed with the SMALLL signature were associated with the extracellular matrix network, and immune cell–infiltration analysis showed that activated naïve B cells, regulatory T cells, M0 macrophages, eosinophils, resting memory CD4 T cells and resting NK cells were significantly different in high- and low-risk groups. We also confirmed differential expression of the lncRNAs of the SMALLL signature in BC tissue and paracancer normal tissue by qRT-PCR analysis. Cell-invasion and -migration experiments showed that MAFG-AS1, ASMTL-AS1, LINC02321, and LINC00922 significantly affected cell invasion and migration.

Conclusion

Our study revealed that the lncRNA signature is an important predictive factor of prognosis and provides a promising biomarker for BC.

Bioinformatics Approaches to Profile the Tumor Microenvironment for Immunotherapeutic Discovery

In the microenvironment of a malignancy, tumor cells do not exist in isolation, but rather in a diverse ecosystem consisting not only of heterogeneous tumor-cell clones, but also normal cell types such as fibroblasts, vasculature, and an extensive pool of immune cells at numerous possible stages of activation and differentiation. This results in a complex interplay of diverse cellular signaling systems, where the immune cell component is now established to influence cancer progression and therapeutic response. It is experimentally difficult and laborious to comprehensively and systematically profile these distinct cell types from heterogeneous tumor samples in order to capitalize on potential therapeutic and biomarker discoveries. One emerging solution to address this challenge is to computationally extract cell-type specific information directly from bulk tumors. Such in silico approaches are advantageous because they can capture both the cell-type specific profiles and the tissue systems level of cell-cell interactions. Accurately and comprehensively predicting these patterns in tumors is an important challenge to overcome, not least given the success of immunotherapeutic drug treatment of several human cancers. This is especially challenging for subsets of closely related immune cell phenotypes with relatively small gene expression differences, which have critical functional distinctions. Here, we outline the existing and emerging novel bioinformatics strategies that can be used to profile the tumor immune landscape.