Underexpression of Specific Interferon Genes Is Associated with Poor Prognosis of Melanoma

Unveiling the therapeutic prospects of IFNW1 and IFNA21: insights into glioma pathogenesis and clinical significance

Glioma, a type of brain tumor, poses significant challenges due to its heterogeneous nature and limited treatment options. Interferon-related genes (IRGs) have emerged as potential players in glioma pathogenesis, yet their expression patterns and clinical implications remain to be fully elucidated. We conducted a comprehensive analysis to investigate the expression patterns and functional enrichment of IRGs in glioma. This involved constructing protein-protein interaction networks, heatmap analysis, survival curve plotting, diagnostic and prognostic assessments, differential expression analysis across glioma subgroups, GSVA, immune infiltration analysis, and drug sensitivity analysis. Our analysis revealed distinct expression patterns and functional enrichment of IRGs in glioma. Notably, IFNW1 and IFNA21 were markedly downregulated in glioma tissues compared to normal tissues, and higher expression levels were associated with improved overall survival and disease-specific survival. Furthermore, these genes showed diagnostic capabilities in distinguishing glioma tissues from normal tissues and were significantly downregulated in higher-grade and more aggressive gliomas. Differential expression analysis across glioma subgroups highlighted the association of IFNW1 and IFNA21 expression with key pathways and biological processes, including metabolic reprogramming and immune regulation. Immune infiltration analysis revealed their influence on immune cell composition in the tumor microenvironment. Additionally, elevated expression levels were associated with increased resistance to chemotherapeutic agents. Our findings underscore the potential of IFNW1 and IFNA21 as diagnostic biomarkers and prognostic indicators in glioma. Their roles in modulating glioma progression, immune response, and drug sensitivity highlight their significance as potential therapeutic targets. These results contribute to a deeper understanding of glioma biology and may inform the development of personalized treatment strategies for glioma patients.

Serine-arginine splicing factor 2 promotes oesophageal cancer progression by regulating alternative splicing of interferon regulatory factor 3

OBJECTIVE

Often, alternative splicing is used by cancer cells to produce or increase proteins that promote growth and survival through alternative splicing. Although RNA-binding proteins are known to regulate alternative splicing events associated with tumorigenesis, their role in oesophageal cancer (EC) has rarely been explored.

METHODS

We analysed the expression pattern of several relatively well characterized splicing regulators on 183 samples from TCGA cohort of oesophageal cancer; the effectiveness of the knockdown of SRSF2 was subsequently verified by immunoblotting; we measured the ability of cells treated with lenti-sh-SRSF2/lenti-sh2-SRSF2 to invade through an extracellular matrix coating by transwell invasion assay; using RNA-seq data to identify its potential target genes; we performed qRT-PCR to detect the changes of exon 2 usage in lenti-sh-SRSF2 transduced KYSE30 cells to determine the possible effect of SRSF2 on splicing regulation of IRF3; RNA Electrophoretic mobility shift assay (RNA-EMSA) was performed by the incubation of purified SRSF2 protein and biotinylated RNA probes; we performed luciferase assay to confirm the effect of SRSF2 on IFN1 promoter activity.

RESULTS

We found upregulation of SRSF2 is correlated with the development of EC; Knock-down of SRSF2 inhibits EC cell proliferation, migration, and invasion; SRSF2 regulates the splicing pattern of IRF3 in EC cells; SRSF2 interacts with exon 2 of IRF3 to regulate its exclusion; SRSF2 inhibits the transcription of IFN1 in EC cells.

CONCLUSION

This study identified a novel regulatory axis involved in EC from the various aspects of splicing regulation.

Integrin alpha 6 is upregulated and drives hepatocellular carcinoma progression through integrin α6β4 complex

Integrin α6 (ITGA6) forms integrin receptors with either integrin β1 (ITGB1) or integrin β4 (ITGB4). How it functions to regulate hepatocellular carcinoma (HCC) progression is not well-elucidated. We found that ITGA6 RNA and protein expression levels are significantly elevated in human HCC tissues in comparison with paired adjacent nontumor tissues by RNA sequencing, RT-qPCR, Western blotting and immunofluorescence staining. Stable knockdown of ITGA6 with different ITGA6 shRNA expression lentivectors significantly inhibited proliferation, migration and anchorage-independent growth of HCC cell lines in vitro, and xenograft tumor growth in vivo. The inhibition of anchorage-dependent and -independent growth of HCC cell lines was also confirmed with anti-ITGA6 antibody. ITGA6 knockdown was shown to induce cell-cycle arrest at G0/G1 phase. Immunoprecipitation assay revealed apparent interaction of ITGA6 with ITGB4, but not ITGB1. Expression studies showed that ITGA6 positively regulates the expression of ITGB4 with no or negative regulation of ITGB1 expression. Finally, while high levels of ITGA6 and ITGB4 together were associated with significantly worse survival of HCC patients in TCGA data set, the association was not significant for high levels of ITGA6 and ITGB1. In conclusion, ITGA6 is upregulated in HCC tumors and has a malignant promoting role in HCC cells through integrin α6β4 complex. Thus, integrin α6β4 may be a therapeutic target for treating patients with HCC.

Association of tumors having Epstein-Barr virus in surrounding lymphocytes with poor prognosis

Infection with certain viruses is an important cause of cancer. The Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium recently analyzed the whole-genome sequencing (WGS) data from 2656 cases across 21 cancer types, and indicated that Epstein-Barr virus (EBV) is detected in many different cancer cases at a higher frequency than previously reported. However, whether EBV-positive cancer cases detected by WGS-based screening correspond to those detected by conventional histopathological techniques is still unclear. In this study, to elucidate the involvement of EBV in various cancers, we reanalyzed the WGS data of the PCAWG cohort combined with the analysis of clinical samples of gastric and pancreatic cancer in our cohort. Based on EBV copy number in each case, we classified tumors into three subgroups: EBV-High, EBV-Low, and EBV-Negative. The EBV-High subgroup was found to be EBV-positive in the cancer cells themselves, whereas the EBV-Low subgroup was EBV-positive in the surrounding lymphocytes. Further, the EBV-Low subgroup showed a significantly worse prognosis for both gastric cancer and across cancer types. In summary, we classified tumors based on EBV copy number and found a unique cancer subgroup, EBV-positive in the surrounding lymphocytes, which was associated with a poor prognosis.

Profiling senescent cells in human brains reveals neurons with CDKN2D/p19 and tau neuropathology

Senescent cells contribute to pathology and dysfunction in animal models1. Their sparse distribution and heterogenous phenotype have presented challenges for detecting them in human tissues. We developed a senescence eigengene approach to identify these rare cells within large, diverse populations of postmortem human brain cells. Eigengenes are useful when no single gene reliably captures a phenotype, like senescence; they also help to reduce noise, which is important in large transcriptomic datasets where subtle signals from low-expressing genes can be lost. Each of our eigengenes detected ~2% senescent cells from a population of ~140,000 single nuclei derived from 76 postmortem human brains with various levels of Alzheimer's disease (AD) pathology. More than 97% of the senescent cells were excitatory neurons and overlapped with tau-containing neurofibrillary tangles (NFTs). Cyclin dependent kinase inhibitor 2D (CDKN2D/p19) was predicted as the most significant contributor to the primary senescence eigengene. RNAscope and immunofluorescence confirmed its elevated expression in AD brain tissue whereby p19-expressing neurons had 1.8-fold larger nuclei and significantly more cells with lipofuscin than p19-negative neurons. These hallmark senescence phenotypes were further elevated in the presence of NFTs. Collectively, CDKN2D/p19-expressing neurons with NFTs represent a unique cellular population in human AD with a senescence phenotype. The eigengenes developed may be useful in future senescence profiling studies as they accurately identified senescent cells in snRNASeq datasets and predicted biomarkers for histological investigation.

DNA methylation analysis improves the prognostication of acute myeloid leukemia

Integration of orthogonal data could provide new opportunities to pinpoint the underlying molecular mechanisms of hematologic disorders. Using a novel gene network approach, we integrated DNA methylation data from The Cancer Genome Atlas (n = 194 cases) with the corresponding gene expression profile. Our integrated gene network analysis classified AML patients into low-, intermediate-, and high-risk groups. The identified high-risk group had significantly shorter overall survival compared to the low-risk group (p-value ≤10-11). Specifically, our approach identified a particular subgroup of nine high-risk AML cases that died within 2 years after diagnosis. These high-risk cases otherwise would be incorrectly classified as intermediate-risk solely based on cytogenetics, mutation profiles, and common molecular characteristics of AML. We confirmed the prognostic value of our integrative gene network approach using two independent datasets, as well as through comparison with European LeukemiaNet and LSC17 criteria. Our approach could be useful in the prognostication of a subset of borderline AML cases. These cases would not be classified into appropriate risk groups by other approaches that use gene expression, but not DNA methylation data. Our findings highlight the significance of epigenomic data, and they indicate integrating DNA methylation data with gene coexpression networks can have a synergistic effect.

Development of an IFNγ response-related signature for predicting the survival of cutaneous melanoma

Background

The tumor microenvironment (TME) plays a critical role in tumorigenesis, development, and therapeutic efficacy. Major advances have been achieved in the treatment of various cancers through immunotherapy. Nevertheless, only a minority of patients have positive responses to immunotherapy, which is partly due to conditions of the immunosuppressive microenvironment. Therefore, it is essential to identify prognostic biomarkers that reflect heterogeneous landscapes of the TME.

Methods and materials

Based upon the ESTIMATE algorithm, we evaluated the infiltrating levels of immune and stromal components derived from patients afflicted by various types of cancer from The Cancer Genome Atlas database (TCGA). According to respective patient immune and stromal scores, we categorized cases into high‐ and low‐scoring subgroups for each cancer type to explore associations between TME and patient prognosis. Gene Set Enrichment Analyses (GSEA) were conducted and genes enriched in IFNγ response signaling pathway were selected to facilitate establishment of a risk model for predicting overall survival (OS). Furthermore, we investigated the associations between the prognostic signature and tumor immune infiltration landscape by using CIBERSORT algorithm and TIMER database.

Results

Among the cancers assessed, the immune scores for skin cutaneous melanoma (SKCM) were the most significantly correlated with patients' survival time (P < .0001). We identified and validated a five‐IFNγ response‐related gene signature (UBE2L6, PARP14, IFIH1, IRF2, and GBP4), which was closely correlated with the prognosis for SKCM afflicted patients. Multivariate Cox regression analysis indicated that this risk model was an independent prognostic factor for SKCM. Tumor‐infiltrating lymphocytes and specific immune checkpoint molecules had notably differential levels of expression in high‐ compared to low‐risk samples.

Conclusion

In this study, we established a novel five‐IFNγ response‐related gene signature that provided a better and increasingly comprehensive understanding of tumor immune landscape, and which demonstrated good performance in predicting outcomes for patients afflicted by SKCM.

Immune expression signatures as candidate prognostic biomarkers of age and gender survival differences in cutaneous melanoma

This study aims to investigate the difference of gene expression and its prognostic significance in younger women with melanoma. Significantly upregulated genes in tumors compared to normal skin tissues were extracted. Among these genes, genes that significantly affected survival according to expression level were selected, and pathway annotation was performed. The patient proportion with high/low expression of the most significant pathways was analyzed in each age (< 50, 50-59, ≥ 60) and gender group. Survival was analyzed according to age, gender, and pathways. The most significant pathways that were upregulated in tumor tissues and also had impacts on survival were programmed cell death protein [PD]-1, interferon-γ, and interferon-α/β pathways. In women, the immune signaling rate in patients was higher than men and decreased with age (63.5%, 53.8%, and 47.6%). In men, the decreasing tendency was minimal (47.6%, 50.0%, and 41.6%). In patients aged < 60 years, women had a favorable survival rate than men (p = 0.055). Except for patients with high immune signaling, no survival difference was observed between genders (p = 0.6). In conclusion, younger female melanoma patients had high immune signaling than older women and men. This immune signaling improved survival of the younger female patients.

Interferons α and β in cancer: therapeutic opportunities from new insights

Over the past decade, preclinical and clinical research have confirmed the essential role of interferons for effective host immunological responses to malignant cells. Type I interferons (IFNα and IFNβ) directly regulate transcription of >100 downstream genes, which results in a myriad of direct (on cancer cells) and indirect (through immune effector cells and vasculature) effects on the tumour. New insights into endogenous and exogenous activation of type I interferons in the tumour and its microenvironment have given impetus to drug discovery and patient evaluation of interferon-directed strategies. When combined with prior observations or with other effective modalities for cancer treatment, modulation of the interferon system could contribute to further reductions in cancer morbidity and mortality. This Review discusses new interferon-directed therapeutic opportunities, ranging from cyclic dinucleotides to genome methylation inhibitors, angiogenesis inhibitors, chemoradiation, complexes with neoantigen-targeted monoclonal antibodies, combinations with other emerging therapeutic interventions and associations of interferon-stimulated gene expression with patient prognosis - all of which are strategies that have or will soon enter translational clinical evaluation.

Applications of Bayesian network models in predicting types of hematological malignancies

Network analysis is the preferred approach for the detection of subtle but coordinated changes in expression of an interacting and related set of genes. We introduce a novel method based on the analyses of coexpression networks and Bayesian networks, and we use this new method to classify two types of hematological malignancies; namely, acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS). Our classifier has an accuracy of 93%, a precision of 98%, and a recall of 90% on the training dataset (n = 366); which outperforms the results reported by other scholars on the same dataset. Although our training dataset consists of microarray data, our model has a remarkable performance on the RNA-Seq test dataset (n = 74, accuracy = 89%, precision = 88%, recall = 98%), which confirms that eigengenes are robust with respect to expression profiling technology. These signatures are useful in classification and correctly predicting the diagnosis. They might also provide valuable information about the underlying biology of diseases. Our network analysis approach is generalizable and can be useful for classifying other diseases based on gene expression profiles. Our previously published Pigengene package is publicly available through Bioconductor, which can be used to conveniently fit a Bayesian network to gene expression data.

Distinct prognostic value of mRNA expression of guanylate-binding protein genes in skin cutaneous melanoma

The purpose of the present study was to assess if guanylate-binding protein (GBP) mRNAs could be prognostic biomarkers for patients with skin cutaneous melanoma (SKCM). The prognostic value of GBP mRNA expression in patients with SKCM was investigated by analyzing gene expression data in 459 SKCM patients. The data were extracted from the OncoLnc database of The Cancer Genome Atlas. A high expression of GBP1, GBP2, GBP3, GBP4 and GBP5 were correlated with favorable overall survival (OS) in the SKCM patients followed for over 30 years. In addition, a high expression of GBP6 mRNA was not correlated with OS in the SKCM patients. A joint effects analysis showed that the co-incidence of the high expression of GBP1-5 was correlated with favorable overall survival in SKCM patients. Our findings suggest that GBP1-5 mRNAs in SKCM are associated with favorable prognosis and may be potential prognostic biomarkers. The combination of GBP1-5 could improve the sensitivity for predicting OS in SKCM patients.

Silencing of interferon regulatory factor gene 6 in melanoma

BACKGROUND

Methylation of a CpG island (CGI; a dense cluster of CpGs) located in the 5' region of a gene suppresses transcription of that gene. Interferon regulatory factor 6 (IRF6) is associated with the expression of interferon, which is used as an effective adjuvant therapy for melanoma, and is regarded as a tumor suppressor. However, little is known about the methylation status of the IRF6 gene in melanoma.

OBJECTIVE

The purpose was to determine the methylation status of the CGI located in the 5' region of IRF6 (5' IRF6 CGI) in melanoma.

METHODS

Quantitative real-time methylation-specific PCR (RT-MSP) and bisulfite sequencing were performed to examine IRF6 gene methylation status. Quantitative real-time reverse transcription-PCR (RT-PCR) was performed to examine IRF6 expression.

RESULTS

The methylation level of the 5' IRF6 CGI was completely inversely correlated with cell sensitivity to interferon-β in eight examined melanoma cell lines. These methylation levels were high in the melanoma cell lines with suppression of IRF6 expression and were low in the cell lines with IRF6 expression. The methylation levels of the 5' IRF6 CGI ranged widely from 0.0% to 65.4% in 21 clinical melanoma samples but showed a narrow range of low levels between 0.0% to 7.2% in 24 clinical melanocytic nevus samples. These methylation levels were not associated with clinical parameters except for melanoma subtypes.

CONCLUSION

IRF6 is aberrantly silenced by DNA methylation of the 5' IRF6 CGI in melanoma. The methylation status of IRF6 is potentially associated with the sensitivity of melanoma to interferon.