FCGR1A Serves as a Novel Biomarker and Correlates With Immune Infiltration in Four Cancer Types

Fc gamma receptors: Their evolution, genomic architecture, genetic variation, and impact on human disease

Fc gamma receptors (FcγRs) are a family of receptors that bind IgG antibodies and interface at the junction of humoral and innate immunity. Precise regulation of receptor expression provides the necessary balance to achieve healthy immune homeostasis by establishing an appropriate immune threshold to limit autoimmunity but respond effectively to infection. The underlying genetics of the FCGR gene family are central to achieving this immune threshold by regulating affinity for IgG, signaling efficacy, and receptor expression. The FCGR gene locus was duplicated during evolution, retaining very high homology and resulting in a genomic region that is technically difficult to study. Here, we review the recent evolution of the gene family in mammals, its complexity and variation through copy number variation and single-nucleotide polymorphism, and impact of these on disease incidence, resolution, and therapeutic antibody efficacy. We also discuss the progress and limitations of current approaches to study the region and emphasize how new genomics technologies will likely resolve much of the current confusion in the field. This will lead to definitive conclusions on the impact of genetic variation within the FCGR gene locus on immune function and disease.

Comparative transcriptomes reveal different tolerance mechanisms to Streptococcus agalactiae in hybrid tilapia, nile tilapia, and blue tilapia

Tilapia is one of the most economically important freshwater fish farmed in China. Streptococcosis outbreaks have been extensively documented in farmed tilapia species. Hybrid tilapia (Oreochromis niloticus ♀ × O. aureus ♂) exhibit greater disease resistance than Nile tilapia (O. niloticus) and blue tilapia (O. aureus). However, the molecular mechanism underlying the enhanced tolerance of hybrid tilapia is still poorly understood. In this study, comparative transcriptome analysis was performed to reveal the different tolerance mechanisms to Streptococcus agalactiae in the three tilapia lines. In total, 1982, 2355, and 2076 differentially expressed genes were identified at 48 h post-infection in hybrid tilapia, Nile tilapia, and blue tilapia, respectively. Functional enrichment analysis indicated that numerous metabolic and immune-related pathways were activated in all three tilapia lines. The differential expression of specific genes associated with phagosome, focal adhesion, cytokine-cytokine receptor interaction, and toll-like receptor signaling pathways contributed to the resistance of hybrid tilapia. Notably, immune response genes in hybrid tilapia, such as P38, TLR5, CXCR3, CXCL12, PSTPIP1, and TFR, were generally suppressed under normal conditions but selectively induced following pathogen challenge. These results expand our knowledge of the molecular mechanisms underlying S. agalactiae tolerance in hybrid tilapia and provide valuable insights for tilapia breeding programs.

Identification of Cell Type-Specific Effects of DNMT3A Mutations on Relapse in Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is a heterogeneous disease caused by distinctive mutations in individual patients; therefore, each patient may display different cell-type compositions. Although most patients with AML achieve complete remission (CR) through intensive chemotherapy, the likelihood of relapse remains high. Several studies have attempted to characterize the genetic and cellular heterogeneity of AML; however, our understanding of the cellular heterogeneity of AML remains limited. In this study, we performed single-cell RNA sequencing (scRNAseq) of bone marrow-derived mononuclear cells obtained from same patients at different AML stages (diagnosis, CR, and relapse). We found that hematopoietic stem cells (HSCs) at diagnosis were abnormal compared to normal HSCs. By improving the detection of the DNMT3A R882 mutation with targeted scRNAseq, we identified that DNMT3A-mutant cells that mainly remained were granulocyte-monocyte progenitors (GMPs) or lymphoid-primed multipotential progenitors (LMPPs) from CR to relapse and that DNMT3A-mutant cells have gene signatures related to AML and leukemic cells. Copy number variation analysis at the single-cell level indicated that the cell type that possesses DNMT3A mutations is an important factor in AML relapse and that GMP and LMPP cells can affect relapse in patients with AML. This study advances our understanding of the role of DNMT3A in AML relapse and our approach can be applied to predict treatment outcomes.

A functional gene module identification algorithm in gene expression data based on genetic algorithm and gene ontology

Since genes do not function individually, the gene module is considered an important tool for interpreting gene expression profiles. In order to consider both functional similarity and expression similarity in module identification, GMIGAGO, a functional Gene Module Identification algorithm based on Genetic Algorithm and Gene Ontology, was proposed in this work. GMIGAGO is an overlapping gene module identification algorithm, which mainly includes two stages: In the first stage (initial identification of gene modules), Improved Partitioning Around Medoids Based on Genetic Algorithm (PAM-GA) is used for the initial clustering on gene expression profiling, and traditional gene co-expression modules can be obtained. Only similarity of expression levels is considered at this stage. In the second stage (optimization of functional similarity within gene modules), Genetic Algorithm for Functional Similarity Optimization (FSO-GA) is used to optimize gene modules based on gene ontology, and functional similarity within gene modules can be improved. Without loss of generality, we compared GMIGAGO with state-of-the-art gene module identification methods on six gene expression datasets, and GMIGAGO identified the gene modules with the highest functional similarity (much higher than state-of-the-art algorithms). GMIGAGO was applied in BRCA, THCA, HNSC, COVID-19, Stem, and Radiation datasets, and it identified some interesting modules which performed important biological functions. The hub genes in these modules could be used as potential targets for diseases or radiation protection. In summary, GMIGAGO has excellent performance in mining molecular mechanisms, and it can also identify potential biomarkers for individual precision therapy.

The Carotenoid Diatoxanthin Modulates Inflammatory and Angiogenesis Pathways In Vitro in Prostate Cancer Cells

Xanthophylls, a group of carotenoids, have attracted attention as human health benefit compounds thanks to their functionality and bioavailability. The great antioxidant and anti-inflammatory abilities of diatoxanthin (Dt), a photoprotective xanthophyll synthetized by diatoms, were recently documented. This study investigates the capacity of Dt to intercept prostate cancer progression in vitro on different human cell lines, exploring its role against cancer proliferation and angiogenesis. Our results highlighted the chemopreventive role of Dt already at low concentration (44.1 pM) and suggest that the Dt-induced cancer cell death occurred through oxidative stress mechanisms. This hypothesis was supported by variations on the expression of key genes and proteins. Oxidative stress cell deaths (e.g., ferroptosis) are recently described types of cell death that are closely related to the pathophysiological processes of many diseases, such as tumors. Nonetheless, the interest of Dt was further strengthened by its ability to inhibit angiogenesis. The results are discussed considering the actual progress and requirements in cancer therapy, notably for prostate cancer.

Differences in Prostate Cancer Transcriptomes by Age at Diagnosis: Are Primary Tumors from Older Men Inherently Different?

Older age at diagnosis is consistently associated with worse clinical outcomes in prostate cancer. We sought to characterize gene expression profiles of prostate tumor tissue by age at diagnosis. We conducted a discovery analysis in The Cancer Genome Atlas prostate cancer dataset (n = 320; 29% of men >65 years at diagnosis), using linear regressions of age at diagnosis and mRNA expression and adjusting for TMPRSS2:ERG fusion status and race. This analysis identified 13 age-related candidate genes at FDR < 0.1, six of which were also found in an analysis additionally adjusted for Gleason score. We then validated the 13 age-related genes in a transcriptome study nested in the Health Professionals Follow-up Study and Physicians' Health Study (n = 374; 53% of men >65 years). Gene expression differences by age in the 13 candidate genes were directionally consistent, and age at diagnosis was weakly associated with the 13-gene score. However, the age-related genes were not consistently associated with risk of metastases and prostate cancer-specific death. Collectively, these findings argue against tumor genomic differences as a main explanation for age-related differences in prostate cancer prognosis.

PREVENTION RELEVANCE

Older age at diagnosis is consistently associated with worse clinical outcomes in prostate cancer. This study with independent discovery and validation sets and long-term follow-up suggests that prevention of lethal prostate cancer should focus on implementing appropriate screening, staging, and treatment among older men without expecting fundamentally different tumor biology.

Altered transcription factor targeting is associated with differential peripheral blood mononuclear cell proportions in sarcoidosis

Introduction

In sarcoidosis, peripheral lymphopenia and anergy have been associated with increased inflammation and maladaptive immune activity, likely promoting development of chronic and progressive disease. However, the molecular mechanisms that lead to reduced lymphocyte proportions, particularly CD4+ T-cells, have not been fully elucidated. We posit that paradoxical peripheral lymphopenia is characterized by a dysregulated transcriptomic network associated with cell function and fate that results from altered transcription factor targeting activity.

Methods

Messenger RNA-sequencing (mRNA-seq) was performed on peripheral blood mononuclear cells (PBMCs) from ACCESS study subjects with sarcoidosis and matched controls and findings validated on a sarcoidosis case-control cohort and a sarcoidosis case series. Preserved PBMC transcriptomic networks between case-control cohorts were assessed to establish cellular associations with gene modules and define regulatory targeting involved in sarcoidosis immune dysregulation utilizing weighted gene co-expression network analysis and differential transcription factor involvement analysis. Network centrality measures identified master transcriptional regulators of subnetworks related to cell proliferation and death. Predictive models of differential PBMC proportions constructed from ACCESS target gene expression corroborated the relationship between aberrant transcription factor regulatory activity and imputed and clinical PBMC populations in the validation cohorts.

Results

We identified two unique and preserved gene modules significantly associated with sarcoidosis immune dysregulation. Strikingly, increased expression of a monocyte-driven, and not a lymphocyte-driven, gene module related to innate immunity and cell death was the best predictor of peripheral CD4+ T-cell proportions. Within the gene network of this monocyte-driven module, TLE3 and CBX8 were determined to be master regulators of the cell death subnetwork. A core gene signature of differentially over-expressed target genes of TLE3 and CBX8 involved in cellular communication and immune response regulation accurately predicted imputed and clinical monocyte expansion and CD4+ T-cell depletion.

Conclusions

Altered transcriptional regulation associated with aberrant gene expression of a monocyte-driven transcriptional network likely influences lymphocyte function and survival. Although further investigation is warranted, this indicates that crosstalk between hyperactive monocytes and lymphocytes may instigate peripheral lymphopenia and underlie sarcoidosis immune dysregulation and pathogenesis. Future therapies selectively targeting master regulators, or their targets, may mitigate dysregulated immune processes in sarcoidosis and disease progression.

Construction of immunotherapy-related prognostic gene signature and small molecule drug prediction for cutaneous melanoma

Background

Cutaneous melanoma (CM), a kind of skin cancer with a high rate of advanced mortality, exhibits a wide variety of driver and transmitter gene alterations in the immunological tumor microenvironment (TME) associated with tumor cell survival and proliferation.

Methods

We analyzed the immunological infiltration of TME cells in normal and malignant tissues using 469 CM and 556 normal skin samples. We used a single sample gene set enrichment assay (ssGSEA) to quantify the relative abundance of 28 cells, then used the LASSO COX regression model to develop a riskScore prognostic model, followed by a small molecule drug screening and molecular docking validation, which was then validated using qRT-PCR and IHC.

Results

We developed a prognosis model around seven essential protective genes for the first time, dramatically elevated in tumor tissues, as did immune cell infiltration. Multivariate Cox regression results indicated that riskScore is an independent and robust prognostic indicator, and its predictive value in immunotherapy was verified. Additionally, we identified Gabapentin as a possible small molecule therapeutic for CM.

Conclusions

A riskScore model was developed in this work to analyze patient prognosis, TME cell infiltration features, and treatment responsiveness. The development of this model not only aids in predicting patient response to immunotherapy but also has significant implications for the development of novel immunotherapeutic agents and the promotion of tailored treatment regimens.

FCGR3A Is a Prognostic Biomarker and Correlated with Immune Infiltrates in Lower-Grade Glioma

Low-grade gliomas (LGGs) are primary invasive brain tumors that grow slowly but are incurable and eventually develop into high malignant glioma. Fc fragment of IgG receptor IIIa (FCGR3A) gene polymorphism may correlate with some cancers' treatment responses. However, the expression and prognosis value of FCGR3A and correlation with tumor-immune infiltrate in LGG remain unclear. FCGR3A mRNA expression in gastric cancer (GC) was examined using TIMER and GEPIA databases. Correlations between FCGR3A expression and clinicopathological parameters were analyzed using ULACAN and CGGA databases. GEPIA, OncoLnc, and ULACAN databases were used to examine the clinical prognostic significance of FCGR3A in LGG. TIMER was used to analyze the correlations among FCGR3A and tumor-infiltrating immune cells. Signaling pathways related to FCGR3A expression were identified by LinkedOmics. We found that FCGR3A expression was higher in LGG than in normal tissue and was correlated with various clinical parameters. In addition, high FCGR3A expression predicted poor overall survival in LGG. More importantly, FCGR3A expression positively correlated with immune checkpoint molecules, including PD1, PD-L1, PD-L2, CTLA4, LAG-3 and TIM-3, and tumor-associated macrophage (TAM) gene markers in LGG. GO and KEGG pathway analyses indicated that TUBA1C may potentially regulate the pathogenesis of LGG through immune-related pathways. These findings indicated that FCGR3A plays a vital role in the infiltration of immune cells and could constitute a promising prognostic biomarker in LGG patients.

The Interferon Gamma-Related Long Noncoding RNA Signature Predicts Prognosis and Indicates Immune Microenvironment Infiltration in Colon Adenocarcinoma

Colon adenocarcinoma (COAD) is one of the most common clinically malignant tumours of the digestive system, with high incidence and mortality and poor prognosis. Interferon-gamma (IFN-γ) and long noncoding RNAs (lncRNAs) have prognostic values and were closely associated with immune microenvironment in COAD. Thus, identifying IFN-γ-related lncRNAs may be valuable in predicting the survival of patients with COAD. In this study, we identified IFN-γ-related lncRNAs and divided COAD patients from the Cancer Genome Atlas (TCGA) database into training and validation sets. Pearson’s correlation analysis and least absolute shrinkage and selection operator (LASSO) Cox regression were performed to select IFN-γ-related lncRNA-associated prognoses. Thirteen lncRNAs (AC025165.8, AC091633.3, FENDRR, LINC00882, LINC01828, LINC01829, MYOSLID, RP11-154H23.4, RP11-20J15.3, RP11-324L17.1, RP11-342A23.2, RP11-805I24.3, SERTAD4-AS1) were identified to construct an IFN-γ-related lncRNA prognostic signature in TCGA training (n =213) and validation (n =213) cohorts. COAD patient risk scores were calculated and classified into high- and low-risk groups based on the median value of the risk scores in each dataset. We compared the overall survival (OS) of patients stratified by age, gender, and stage. The OS in the high-risk group was significantly shorter than that in the low-risk group. In addition, the clinical nomogram incorporating the prognostic signature and clinical features showed a high concordance index of 0.78 and accurately predicted 1-, 3-, and 5-year survival times among COAD patients in the high- and low-risk groups. Based on the risk model, the high- and low-risk groups exhibited distinct differences in the immune system by gene set enrichment analysis (GSEA) functional annotation, and differentially expressed genes (DEGs) between the high- and low-risk groups were subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. We investigated the expression of multiple immune checkpoint genes in the high- and low-risk groups and plotted Kaplan-Meier survival curves, indicating that immune checkpoint genes, such as LAG3 and PD. L1, STING and TIM 3, were also expressed differently between the two risk groups. Subsequently, there were dramatic differences in mutated genes, SNV (single nucleotide variants) classes, variant types and variant allele frequencies between low- and high-risk patients with COAD. Patients stratified by risk scores had different sensitivities to common chemotherapeutic agents. Finally, we used quantitative real-time polymerase chain reaction (qRT-PCR) assays to demonstrate that three lncRNAs were significantly differentially expressed in COAD tissues and adjacent normal tissues. Considered together, a thirteen-lncRNA prognostic signature has great potential to be a prognostic biomarker and could play an essential role in the immune microenvironment of COAD.

Concomitant High Apoptosis Inhibitor of Macrophage (AIM) and Low Prostate-Specific Antigen (PSA) Indicates Activated T Cell-Mediated Anticancer Immunity, Enhance Sensitivity to Pembrolizumab, and Elicit Good Prognosis in Prostate Cancer

BACKGROUND

Despite its widespread use, the use of prostate-specific antigen (PSA) alone as a screening biomarker for prostate cancer (PCa) leads often to unwarranted prostate biopsy, over-diagnosis, and consequently, over-treatment, because of its limited specificity. There are reports that the apoptosis inhibitor of macrophage (AIM), secreted mainly by macrophages and epithelial cells, is upregulated during inflammation and facilitates immune recognition of cancerous cells by blocking human regulator of complement activation.

OBJECTIVE

These controversies around the PSA utility necessitate a reexamination of its use as a screening tool. More so, despite the suggested implication of AIM in anticancer immunosurveillance, there is a dearth of information on its role in therapy response, disease progression, and clinical outcomes of patients with PCa. These inform the present study to probe the nature and role of AIM/PSA signaling in anticancer immunity and prognosis in PCa.

METHODS

A combination of bioinformatics-aided statistical analyses, gene function annotation, and immune infiltrate analyses, coupled with tissue staining, and function assays, namely migration, invasion, and clonogenicity assays, we employed.

RESULTS

We demonstrated that AIM and PSA expression levels are inversely correlated in PCa clinical samples and cell lines, with AIM^lowPSA^high defining PCa, compared to AIM^highPSA^low in normal samples. Concomitant aberrant PSA and significantly suppressed AIM expression levels positively correlated with high-grade disease and characterized by advanced stage prostate cancer, regardless of mutation status. We found that a high PSA/AIM ratio is associated with disease recurrence in patients with prostate cancer but is equivocal for overall survival. In addition, PSA-associated AIM suppression is implicated in the enhanced 'metastability' of PCa and a high AIM/PSA ratio is associated with strong castration-induced regression. CRISPR-mediated AIM knockout was associated with higher PSA expression while ectopic expression of AIM significantly attenuated the migration and invasive capability of PC3 and DU145 cells. Interestingly, compared to normal samples, we observed that AIM, biomarkers of T-cell activation and M1 phenotype markers are co-suppressed in PCa samples.

CONCLUSION

Herein, we demonstrate that AIM/CD5L binds to PSA and that a high PSA/AIM ratio defines advanced stage PCa (regardless of mutation status), is implicated in enhanced metastability, and associated with disease recurrence, while a high AIM/PSA ratio is associated with strong castration-induced regression. More so, the ectopic expression of AIM significantly enhances the anticancer effect of Pembrolizumab and elicits an increased CD8+ T-cell count in AIM^hiPSA^loPDL1+ PCa cases that are respondent to Pembrolizumab treatment.

Integrated Bioinformatics Analysis of DNA Methylation Biomarkers in Thyroid Cancer Based on TCGA Database

Previous studies have reported a cluster of aberrant promoter methylation changes associated with silencing of tumor suppressor genes in thyroid cancer (TC), but these results of individual genes are far from enough. In this work, we aimed to investigate the onset and pattern of methylation changes during the progression of TC by informatics analysis. We downloaded the DNA methylation and RNA sequencing datasets from The Cancer Genome Atlas focusing on TC. Abnormally methylated differentially expressed genes (DEGs) were sorted and pathways were analyzed. The KEGG and GO were then used to perform enrichment and functional analysis of identified pathways and genes. Gene-drug interaction network and human protein atlas were applied to obtain feature DNA methylation biomarkers. In total, we identified 2170 methylation-driven DEGs, including 1054 hypermethylatedlow-expression DEGs and 1116 hypomethylated-high-expression DEGs at the screening step. Further analysis screened total of eight feature DNA methylation biomarkers (RXRG, MET, PDGFRA, FCGR3A, VEGFA, CSF1R, FCGR1A and C1QA). Pathway analysis showed that aberrantly methylated DEGs mainly associated with transcriptional misregulation in cancer, MAPK signaling, and intrinsic apoptotic signaling in TC. Taken together, we have identified novel aberrantly methylated genes and pathways linked to TC, which might serve as novel biomarkers for precision diagnosis and disease treatment.

Identification of tumor antigens and immune subtypes of cholangiocarcinoma for mRNA vaccine development

BACKGROUND

The mRNA-based cancer vaccine has been considered a promising strategy and the next hotspot in cancer immunotherapy. However, its application on cholangiocarcinoma remains largely uncharacterized. This study aimed to identify potential antigens of cholangiocarcinoma for development of anti-cholangiocarcinoma mRNA vaccine, and determine immune subtypes of cholangiocarcinoma for selection of suitable patients from an extremely heterogeneous population.

METHODS

Gene expression profiles and corresponding clinical information were collected from GEO and TCGA, respectively. cBioPortal was used to visualize and compare genetic alterations. GEPIA2 was used to calculate the prognostic index of the selected antigens. TIMER was used to visualize the correlation between the infiltration of antigen-presenting cells and the expression of the identified antigens. Consensus clustering analysis was performed to identify the immune subtypes. Graph learning-based dimensionality reduction analysis was conducted to visualize the immune landscape of cholangiocarcinoma.

RESULTS

Three tumor antigens, such as CD247, FCGR1A, and TRRAP, correlated with superior prognoses and infiltration of antigen-presenting cells were identified in cholangiocarcinoma. Cholangiocarcinoma patients were stratified into two immune subtypes characterized by differential molecular, cellular and clinical features. Patients with the IS1 tumor had immune "hot" and immunosuppressive phenotype, whereas those with the IS2 tumor had immune "cold" phenotype. Interestingly, patients with the IS2 tumor had a superior survival than those with the IS1 tumor. Furthermore, distinct expression of immune checkpoints and immunogenic cell death modulators was observed between different immune subtype tumors. Finally, the immune landscape of cholangiocarcinoma revealed immune cell components in individual patient.

CONCLUSIONS

CD247, FCGR1A, and TRRAP are potential antigens for mRNA vaccine development against cholangiocarcinoma, specifically for patients with IS2 tumors. Therefore, this study provides a theoretical basis for the anti-cholangiocarcinoma mRNA vaccine and defines suitable patients for vaccination.