High GILT Expression and an Active and Intact MHC Class II Antigen Presentation Pathway Are Associated with Improved Survival in Melanoma

Comprehensive analysis of the role of interferon gamma-inducible protein 30 on immune infiltration and prognosis in clear cell renal cell carcinoma

Although the immune factor interferon gamma-inducible protein 30 (IFI30) has been linked to the growth and immune infiltration of various malignancies, its function and mechanism in clear cell renal cell carcinoma (ccRCC) remains unclear. We used several databases to detect and validate IFI30 expression in ccRCC and its connection to immune invasion. We found that IFI30 expression was higher in ccRCC tissues compared to normal tissues, and was strongly associated with tumor grade, T stage, and M stage. Univariate and multivariate analyses showed that ccRCC cases with lower IFI30 expression levels had a higher OS rate than those with high IFI30 expression (P < 0.05). Additionally, we collected a total of 104 cases of ccRCC and adjacent tissues from the First Affiliated Hospital of Jinzhou Medical University between January 2018 and January 2020 for immunohistochemical (IHC) analysis, along with their relevant clinicopathological data. The relationship between IFI30 and expression of CD3E, CD4, CD8A, interleukin 10 (IL-10) and transforming growth factor beta (TGFB2) was examined using the ccRCC data from The Cancer Genome Atlas (TCGA) database, with findings verified by IHC analysis using the collected cases. Statistical analysis performed with SPSS found the positive correlation between the expression of CD3E, CD4, CD8A and IL-10 and the IFI30 expression, and negative correlation of TGFB2 expression with the IFI30 expression in ccRCC. Concurrently, a notable association was observed between high IFI30 expression and immune cell infiltration in ccRCC. High IFI30 expression is connected to the ccRCC's poor prognosis with the infiltration of immune cell. These findings suggest that high IFI30 expression could serve as a marker of poor prognosis and be associated with immune cell infiltration in ccRCC.

Interferon-γ inducible protein 30 promotes the epithelial-mesenchymal transition-like phenotype and chemoresistance by activating EGFR/AKT/GSK3β/β-catenin pathway in glioma

AIMS

Previous studies have indicated that IFI30 plays a protective role in human cancers. However, its potential roles in regulating glioma development are not fully understood.

METHODS

Public datasets, immunohistochemistry, and western blotting (WB) were used to evaluate the expression of IFI30 in glioma. The potential functions and mechanisms of IFI30 were examined by public dataset analysis; quantitative real-time PCR; WB; limiting dilution analysis; xenograft tumor assays; CCK-8, colony formation, wound healing, and transwell assays; and immunofluorescence microscopy and flow cytometry.

RESULTS

IFI30 was significantly upregulated in glioma tissues and cell lines compared with corresponding controls, and the expression level of IFI30 was positively associated with tumor grade. Functionally, both in vivo and in vitro evidence showed that IFI30 regulated the migration and invasion of glioma cells. Mechanistically, we found that IFI30 dramatically promoted the epithelial-mesenchymal transition (EMT)-like process by activating the EGFR/AKT/GSK3β/β-catenin pathway. In addition, IFI30 regulated the chemoresistance of glioma cells to temozolomide directly via the expression of the transcription factor Slug, a key regulator of the EMT-like process.

CONCLUSION

The present study suggests that IFI30 is a regulator of the EMT-like phenotype and acts not only as a prognostic marker but also as a potential therapeutic target for temozolomide-resistant glioma.

Expansion of CD4+ cytotoxic T lymphocytes with specific gene expression patterns may contribute to suppression of tumor immunity in oral squamous cell carcinoma: single-cell analysis and in vitro experiments

Background

Cancer immunotherapy targeting CD8+ T cells has made remarkable progress, even for oral squamous cell carcinoma (OSCC), a heterogeneous epithelial tumor without a substantial increase in the overall survival rate over the past decade. However, the therapeutic effects remain limited due to therapy resistance. Thus, a more comprehensive understanding of the roles of CD4+ T cells and B cells is crucial for more robust development of cancer immunotherapy.

Methods

In this study, we examined immune responses and effector functions of CD4+ T cells, CD8+ T cells and B cells infiltrating in OSCC lesions using single-cell RNA sequencing analysis, T cell receptor (TCR) and B cell receptor (BCR) repertoire sequencing analysis, and multi-color immunofluorescence staining. Finally, two Kaplan-Meier curves and several Cox proportional hazards models were constructed for the survival analysis.

Results

We observed expansion of CD4+ cytotoxic T lymphocytes (CTLs) expressing granzymes, which are reported to induce cell apoptosis, with a unique gene expression patterns. CD4+ CTLs also expressed CXCL13, which is a B cell chemoattractant. Cell-cell communication analysis and multi-color immunofluorescence staining demonstrated potential interactions between CD4+ CTLs and B cells, particularly IgD- CD27- double negative (DN) B cells. Expansion of CD4+ CTLs, DN B cells, and their contacts has been reported in T and B cell-activated diseases, including IgG4-related disease and COVID-19. Notably, we observed upregulation of several inhibitory receptor genes including CTLA-4 in CD4+ CTLs, which possibly dampened T and B cell activity. We next demonstrated comprehensive delineation of the potential for CD8+ T cell differentiation towards dysfunctional states. Furthermore, prognostic analysis revealed unfavorable outcomes of patients with a high proportion of CD4+ CTLs in OSCC lesions.

Conclusion

Our study provides a dynamic landscape of lymphocytes and demonstrates a systemic investigation of CD4+ CTL effects infiltrating into OSCC lesions, which may share some pathogenesis reported in severe T and B cell-activated diseases such as autoimmune and infectious diseases.

EBV-induced T-cell responses in EBV-specific and nonspecific cancers

Epstein-Barr virus (EBV) is a ubiquitous human tumor virus associated with various malignancies, including B-lymphoma, NK and T-lymphoma, and epithelial carcinoma. It infects B lymphocytes and epithelial cells within the oropharynx and establishes persistent infection in memory B cells. With a balanced virus-host interaction, most individuals carry EBV asymptomatically because of the lifelong surveillance by T cell immunity against EBV. A stable anti-EBV T cell repertoire is maintained in memory at high frequency in the blood throughout persistent EBV infection. Patients with impaired T cell immunity are more likely to develop life-threatening lymphoproliferative disorders, highlighting the critical role of T cells in achieving the EBV-host balance. Recent studies reveal that the EBV protein, LMP1, triggers robust T-cell responses against multiple tumor-associated antigens (TAAs) in B cells. Additionally, EBV-specific T cells have been identified in EBV-unrelated cancers, raising questions about their role in antitumor immunity. Herein, we summarize T-cell responses in EBV-related cancers, considering latency patterns, host immune status, and factors like human leukocyte antigen (HLA) susceptibility, which may affect immune outcomes. We discuss EBV-induced TAA-specific T cell responses and explore the potential roles of EBV-specific T cell subsets in tumor microenvironments. We also describe T-cell immunotherapy strategies that harness EBV antigens, ranging from EBV-specific T cells to T cell receptor-engineered T cells. Lastly, we discuss the involvement of γδ T-cells in EBV infection and associated diseases, aiming to elucidate the comprehensive interplay between EBV and T-cell immunity.

Major histocompatibility complex class II in the tumor microenvironment: functions of nonprofessional antigen-presenting cells

Major histocompatibility complex class-II-restricted presentation by nonprofessional antigen-presenting cells in the tumor microenvironment can regulate antitumor T-cell responses. In murine models, tumor cell-specific MHC class II expression decreases in vivo tumor growth, dependent on T cells. Tumor cell-specific MHC class II expression is associated with improved survival and response to immune checkpoint inhibitors in human cancers. Antigen-presenting cancer-associated fibroblasts (apCAF) present MHC class-II-restricted antigens and activate CD4 T cells. The role of MHC class II on apCAFs depends on the cell of origin. MHC class II on tumoral lymphatic endothelial cells leads to expansion of regulatory T cells and increased in vivo tumor growth.

Machine learning-based signature of necrosis-associated lncRNAs for prognostic and immunotherapy response prediction in cutaneous melanoma and tumor immune landscape characterization

Background

Cutaneous melanoma (CM) is one of the malignant tumors with a relative high lethality. Necroptosis is a novel programmed cell death that participates in anti-tumor immunity and tumor prognosis. Necroptosis has been found to play an important role in tumors like CM. However, the necroptosis-associated lncRNAs' potential prognostic value in CM has not been identified.

Methods

The RNA sequencing data collected from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression Project (GTEx) was utilized to identify differentially expressed genes in CM. By using the univariate Cox regression analysis and machine learning LASSO algorithm, a prognostic risk model had been built depending on 5 necroptosis-associated lncRNAs and was verified by internal validation. The performance of this prognostic model was assessed by the receiver operating characteristic curves. A nomogram was constructed and verified by calibration. Furthermore, we also performed sub-group K-M analysis to explore the 5 lncRNAs' expression in different clinical stages. Function enrichment had been analyzed by GSEA and ssGSEA. In addition, qRT-PCR was performed to verify the five lncRNAs' expression level in CM cell line (A2058 and A375) and normal keratinocyte cell line (HaCaT).

Results

We constructed a prognostic model based on five necroptosis-associated lncRNAs (AC245041.1, LINC00665, AC018553.1, LINC01871, and AC107464.3) and divided patients into high-risk group and low-risk group depending on risk scores. A predictive nomogram had been built to be a prognostic indicator to clinical factors. Functional enrichment analysis showed that immune functions had more relationship and immune checkpoints were more activated in low-risk group than that in high-risk group. Thus, the low-risk group would have a more sensitive response to immunotherapy.

Conclusion

This risk score signature could be used to divide CM patients into low- and high-risk groups, and facilitate treatment strategy decision making that immunotherapy is more suitable for those in low-risk group, providing a new sight for CM prognostic evaluation.

Establishment of a novel lysosomal signature for the diagnosis of gastric cancer with in-vitro and in-situ validation

Background

Gastric cancer (GC) represents a malignancy with a multi-factorial combination of genetic, environmental, and microbial factors. Targeting lysosomes presents significant potential in the treatment of numerous diseases, while lysosome-related genetic markers for early GC detection have not yet been established, despite implementing this process by assembling artificial intelligence algorithms would greatly break through its value in translational medicine, particularly for immunotherapy.

Methods

To this end, this study, by utilizing the transcriptomic as well as single cell data and integrating 20 mainstream machine-learning (ML) algorithms. We optimized an AI-based predictor for GC diagnosis. Then, the reliability of the model was initially confirmed by the results of enrichment analyses currently in use. And the immunological implications of the genes comprising the predictor was explored and response of GC patients were evaluated to immunotherapy and chemotherapy. Further, we performed systematic laboratory work to evaluate the build-up of the central genes, both at the expression stage and at the functional aspect, by which we could also demonstrate the reliability of the model to guide cancer immunotherapy.

Results

Eight lysosomal-related genes were selected for predictive model construction based on the inclusion of RMSE as a reference standard and RF algorithm for ranking, namely ADRB2, KCNE2, MYO7A, IFI30, LAMP3, TPP1, HPS4, and NEU4. Taking into account accuracy, precision, recall, and F1 measurements, a preliminary determination of our study was carried out by means of applying the extra tree and random forest algorithms, incorporating the ROC-AUC value as a consideration, the Extra Tree model seems to be the optimal option with the AUC value of 0.92. The superiority of diagnostic signature is also reflected in the analysis of immune features.

Conclusion

In summary, this study is the first to integrate around 20 mainstream ML algorithms to construct an AI-based diagnostic predictor for gastric cancer based on lysosomal-related genes. This model will facilitate the accurate prediction of early gastric cancer incidence and the subsequent risk assessment or precise individualized immunotherapy, thus improving the survival prognosis of GC patients.

Interferons and Resistance Mechanisms in Tumors and Pathogen-Driven Diseases—Focus on the Major Histocompatibility Complex (MHC) Antigen Processing Pathway

Interferons (IFNs), divided into type I, type II, and type III IFNs represent proteins that are secreted from cells in response to various stimuli and provide important information for understanding the evolution, structure, and function of the immune system, as well as the signaling pathways of other cytokines and their receptors. They exert comparable, but also distinct physiologic and pathophysiologic activities accompanied by pleiotropic effects, such as the modulation of host responses against bacterial and viral infections, tumor surveillance, innate and adaptive immune responses. IFNs were the first cytokines used for the treatment of tumor patients including hairy leukemia, renal cell carcinoma, and melanoma. However, tumor cells often develop a transient or permanent resistance to IFNs, which has been linked to the escape of tumor cells and unresponsiveness to immunotherapies. In addition, loss-of-function mutations in IFN signaling components have been associated with susceptibility to infectious diseases, such as COVID-19 and mycobacterial infections. In this review, we summarize general features of the three IFN families and their function, the expression and activity of the different IFN signal transduction pathways, and their role in tumor immune evasion and pathogen clearance, with links to alterations in the major histocompatibility complex (MHC) class I and II antigen processing machinery (APM). In addition, we discuss insights regarding the clinical applications of IFNs alone or in combination with other therapeutic options including immunotherapies as well as strategies reversing the deficient IFN signaling. Therefore, this review provides an overview on the function and clinical relevance of the different IFN family members, with a specific focus on the MHC pathways in cancers and infections and their contribution to immune escape of tumors.

A novel lysosome-related gene signature coupled with gleason score for prognosis prediction in prostate cancer

Background: Prostate cancer (PCa) is highly heterogeneous, which makes it difficult to precisely distinguish the clinical stages and histological grades of tumor lesions, thereby leading to large amounts of under- and over-treatment. Thus, we expect the development of novel prediction approaches for the prevention of inadequate therapies. The emerging evidence demonstrates the pivotal role of lysosome-related mechanisms in the prognosis of PCa. In this study, we aimed to identify a lysosome-related prognostic predictor in PCa for future therapies.

Methods: The PCa samples involved in this study were gathered from The Cancer Genome Atlas database (TCGA) (n = 552) and cBioPortal database (n = 82). During screening, we categorized PCa patients into two immune groups based on median ssGSEA scores. Then, the Gleason score and lysosome-related genes were included and screened out by using a univariate Cox regression analysis and the least absolute shrinkage and selection operation (LASSO) analysis. Following further analysis, the probability of progression free interval (PFI) was modeled by using unadjusted Kaplan–Meier estimation curves and a multivariable Cox regression analysis. A receiver operating characteristic (ROC) curve, nomogram and calibration curve were used to examine the predictive value of this model in discriminating progression events from non-events. The model was trained and repeatedly validated by creating a training set (n = 400), an internal validation set (n = 100) and an external validation (n = 82) from the cohort.

Results: Following grouping by ssGSEA score, the Gleason score and two LRGs—neutrophil cytosolic factor 1 (NCF1) and gamma-interferon-inducible lysosomal thiol reductase (IFI30)—were screened out to differentiate patients with or without progression (1-year AUC = 0.787; 3-year AUC = 0.798; 5-year AUC = 0.772; 10-year AUC = 0.832). Patients with a higher risk showed poorer outcomes (p &lt; 0.0001) and a higher cumulative hazard (p &lt; 0.0001). Besides this, our risk model combined LRGs with the Gleason score and presented a more accurate prediction of PCa prognosis than the Gleason score alone. In three validation sets, our model still achieved high prediction rates.

Conclusion: In conclusion, this novel lysosome-related gene signature, coupled with the Gleason score, works well in PCa for prognosis prediction.

Single-Cell Transcriptomic Analysis of Primary and Metastatic Tumor Ecosystems in Esophageal Squamous Cell Carcinoma

Lymph node metastasis, the leading cause of mortality in esophageal squamous carcinoma (ESCC) with a highly complex tumor microenvironment, remains underexplored. Here, the transcriptomes of 85 263 single cells are analyzed from four ESCC patients with lymph node metastases. Strikingly, it is observed that the metastatic microenvironment undergoes the emergence or expansion of interferon induced IFIT3+ T, B cells, and immunosuppressive cells such as APOC1+ APOE+ macrophages and myofibroblasts with highly expression of immunoglobulin genes (IGKC) and extracellular matrix component and matrix metallopeptidase genes. A poor-prognostic epithelial-immune dual expression program regulating immune effector processes, whose activity is significantly enhanced in metastatic malignant epithelial cells and enriched in CD74+ CXCR4+ and major histocompatibility complex (MHC) class II genes upregulated malignant epithelia cells is discovered. Comparing with primary tumor, differential intercellular communications of metastatic ESCC microenvironment are revealed and furtherly validated via multiplexed immunofluorescence and immunohistochemistry staining, which mainly rely on the crosstalk of APOC1+ APOE+ macrophages with tumor and stromal cell. The data highlight potential molecular mechanisms that shape the lymph-node metastatic microenvironment and may inform drug discovery and the development of new strategies to target these prometastatic nontumor components for inhibiting tumor growth and overcoming metastasis to improve clinical outcomes.

High GILT Expression Is Associated with Improved Survival in Metastatic Melanoma Patients Treated with Immune Checkpoint Inhibition

Simple Summary

Skin cancer is the most common type of cancer, with melanoma being among the deadliest of skin cancers due to its propensity to metastasize. Immune checkpoint inhibitors (ICI) generate anti-tumor immune responses resulting in improved outcomes in patients with metastatic melanoma. However, only a subset of melanoma patients responds to these therapies, which are costly and come with a risk of adverse effects. Therefore, there is a need for biomarkers to predict which patients will respond to ICI. We found that ICI-treated metastatic melanoma patients with high GILT mRNA expression in bulk tumor samples had improved survival. Additionally, high GILT protein expression within metastatic melanoma cells was associated with improved survival in patients treated with ICI. This study suggests that GILT may serve as a biomarker to predict which patients will respond to ICI, which could improve patient care, reduce healthcare costs, and facilitate appropriate selection of therapies for patients with metastatic melanoma.

Abstract

Gamma-interferon-inducible lysosomal thiol reductase (GILT) is critical for MHC class II restricted presentation of multiple melanoma antigens. There is variable GILT protein expression in malignant melanocytes in melanoma specimens. High GILT mRNA expression in melanoma specimens is associated with improved overall survival, before the advent of immune checkpoint inhibitors (ICI). However, the association of GILT in metastatic melanoma with survival in patients treated with ICI and the cell type expressing GILT associated with survival have not been determined. Using RNA sequencing datasets, high GILT mRNA expression in metastatic melanoma specimens was associated with improved progression-free and overall survival in patients treated with ICI. A clinical dataset of metastatic melanoma specimens was generated and annotated with clinical information. Positive GILT immunohistochemical staining in antigen presenting cells and melanoma cells was observed in 100% and 65% of metastatic melanoma specimens, respectively. In the subset of patients treated with ICI in the clinical dataset, high GILT protein expression within melanoma cells was associated with improved overall survival. The association of GILT mRNA and protein expression with survival was independent of cancer stage. These studies support that high GILT mRNA expression in bulk tumor samples and high GILT protein expression in melanoma cells is associated with improved survival in ICI-treated patients. These findings support further investigation of GILT as a biomarker to predict the response to ICI.

GILT Expression in Human Melanoma Cells Enhances Generation of Antigenic Peptides for HLA Class II-Mediated Immune Recognition

Melanoma is an aggressive skin cancer that has become increasingly prevalent in western populations. Current treatments such as surgery, chemotherapy, and high-dose radiation have had limited success, often failing to treat late stage, metastatic melanoma. Alternative strategies such as immunotherapies have been successful in treating a small percentage of patients with metastatic disease, although these treatments to date have not been proven to enhance overall survival. Several melanoma antigens (Ags) proposed as targets for immunotherapeutics include tyrosinase, NY-ESO-1, gp-100, and Mart-1, all of which contain both human leukocyte antigen (HLA) class I and class II-restricted epitopes necessary for immune recognition. We have previously shown that an enzyme, gamma-IFN-inducible lysosomal thiol-reductase (GILT), is abundantly expressed in professional Ag presenting cells (APCs), but absent or expressed at greatly reduced levels in many human melanomas. In the current study, we report that increased GILT expression generates a greater pool of antigenic peptides in melanoma cells for enhanced CD4+ T cell recognition. Our results suggest that the induction of GILT in human melanoma cells could aid in the development of a novel whole-cell vaccine for the enhancement of immune recognition of metastatic melanoma.

IFI30 as a prognostic biomarker and correlation with immune infiltrates in glioma

Background

Increased evidence indicates that the tumour microenvironment (TME) plays an essential role in the development, treatment and prognosis of glioma. High expression of interferon-gamma-inducible protein 30 (IFI30) is associated with the malignant phenotype, but the effect of IFI30 on the tumour immune microenvironment and its potential role in the carcinogenesis of glioma remain unknown.

Methods

The RNA sequencing (RNA-seq) data of 33 types of human cancer were obtained from The Cancer Genome Atlas (TCGA) Genomic Data Commons (GDC). R software was used to perform analyses, such as the expression of IFI30 in pan-cancer, evaluation of IFI30 as a prognostic biomarker in glioma, the relationship between IFI30 expression and clinical characteristics, and immune checkpoint. TIMER was used to analyse the correlation of IFI30 expression level with immune cell infiltration, and also to conduct survival analysis for immune cells and IFI30 in low grade glioma (LGG). DAVID was used for Gene Ontology (GO) functional annotations and Kyoto Encyclopedia of Genes and Genomes (KEGG) for pathway analysis of the genes similar to IFI30 in glioma. The differentially expressed genes (DEGs) between the high- and low-IFI30 expression groups were determined by DESeq2. Gene set enrichment analysis (GSEA) was then conducted to identify IFI30-related functional significance based on the hallmark gene set.

Results

Dysregulated expression of IFI30 was associated with human cancers. High IFI30 expression was associated with poor overall survival (OS), disease-specific survival (DSS) and progression-free interval (PFI). Univariate and multivariate analyses identified IFI30 as an independent predictor for glioma. Meanwhile, IFI30 overexpression significantly correlated with high-grade tumours, poor OS, and immune infiltration. In addition, IFI30-associated genes significantly enriched the hallmark tumour progression-related clusters and cancer pathways.

Conclusions

IFI30 is a prognostic biomarker correlated with immune infiltrates and acts as an oncogene in glioma.

Prognostic value of gamma-interferon-inducible lysosomal thiol reductase expression in female patients diagnosed with breast cancer

Because of the high heterogeneity of breast cancer outcome, identification of novel prognostic biomarkers is critical to improve patient stratification and guide precise treatment. We examined the prognostic value of gamma-interferon-inducible lysosomal thiol reductase (GILT) expression in a training set of 416 breast cancer patients and a validation set of 210 patients, and performed functional studies to investigate the functions and underlying mechanisms of GILT on breast cancer prognosis. Our results indicated that high GILT expression in breast cancer cells was associated with improved disease-free survival (DFS; hazard ratio [HR] = 0.189, 95% confidence interval [CI]: 0.099-0.361) and breast cancer-specific survival (BCSS; HR = 0.187, 95% CI: 0.080-0.437) of breast cancer patients both in the training set and the external validation set (HR = 0.453, 95% CI: 0.235-0.873 for DFS, HR = 0.488, 95% CI: 0.245-0.970 for BCSS). In vitro and in vivo studies showed that GILT overexpression inhibited breast cancer cells proliferation, invasion, migration and tumor formation in nude mice and increased sensitivity of breast cancer cells to standard treatment. Proteomics analysis indicated that GILT inhibited reactive oxygen species (ROS) and autophagy activation in breast cancer cells, and GILT overexpression-mediated tumor growth was further enhanced in the presence of autophagy or ROS inhibitors. Our results demonstrate that GILT expression can be effectively used to predict the prognosis and guide treatment strategies of breast cancer patients.

The Prognostic Model Based on Tumor Cell Evolution Trajectory Reveals a Different Risk Group of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death worldwide, and heterogeneity of HCC is the major barrier in improving patient outcome. To stratify HCC patients with different degrees of malignancy and provide precise treatment strategies, we reconstructed the tumor evolution trajectory with the help of scRNA-seq data and established a 30-gene prognostic model to identify the malignant state in HCC. Patients were divided into high-risk and low-risk groups. C-index and receiver operating characteristic (ROC) curve confirmed the excellent predictive value of this model. Downstream analysis revealed the underlying molecular and functional characteristics of this model, including significantly higher genomic instability and stronger proliferation/progression potential in the high-risk group. In summary, we established a novel prognostic model to overcome the barriers caused by HCC heterogeneity and provide the possibility of better clinical management for HCC patients to improve their survival outcomes.

Expression of gilt acts as a positive regulator of mouse hematopoietic progenitor cells

Gamma interferon inducible lysosomal thiol reductase (GILT), is known to be involved in immunity, but its role in hematopoiesis has not been previously reported. Herein, we demonstrate using gilt knockout (-/-) mice that loss of gilt associates with decreased numbers and cycling status of femoral hematopoietic progenitor cells (CFU-GM, BFU-E, and CFU-GEMM) with more modest effects on splenic progenitor cells. Thus, GILT is associated with positive regulation of hematopoietic progenitor cells in mice, mainly in bone marrow.

IFI30 expression predicts patient prognosis in breast cancer and dictates breast cancer cells proliferation via regulating autophagy

Introduction: Incidence and mortality rates of breast cancer are increasing in women worldwide. Immunotherapy is a relatively popular treatment modality for all malignant tumors including breast cancer in recent years. Interferon γ-inducible protein 30 (IFI30) could catalyze the reduction of disulfide bonds and enhance major histocompatibility complex (MHC) class II-restricted antigen processing. Recent studies showed that IFI30 played an important role in the immune response of malignant tumors. Methods: The Cancer Genome Atlas (TCGA) database and clinical proteomic tumor Analysis consortium (CPTAC) database were applied to predict the role of IFI30 in breast cancer and the relationship between IFI30 and prognosis of breast cancer patients. Then we detected the expression of IFI30 in clinical samples of breast cancer patients, and analyzed the relationship between IFI30 and the prognosis of breast cancer patients. We used lentivirus infection method to construct a stable IFI30 knockdown cell line, and detected the effect of IFI30 in breast cancer cells. Nude mice tumor bearing experiment was performed to investigate the effect of IFI30 on breast cancer cells in vivo. Western blot was used to verify the regulation of autophagy related protein LC3 and p62 by IFI30. Results: We found that IFI30 was highly expressed in breast cancer tissues and was associated with poor outcome of patients. The knockdown of IFI30 could inhibit the proliferation, migration and invasion of breast cancer cells and significantly inhibit tumor growth in vivo. Increased accumulation of LC3-II and p62 suggested impaired autophagy in IFI30 knockdown cells. Discussion: As a result, we suggested that IFI30 might play a key role in the initiation and progression of human breast cancer and might be a new therapeutic target in breast cancer.

Decoding Immune Heterogeneity of Melanoma and identifying immune-prognostic hub genes

Melanoma is an aggressive skin cancer that has gained attention worldwide. Growing evidence has highlighted that the tumor microenvironment (TME) is an important feature of carcinogenesis and contributes to therapeutic efficacy in melanoma. However, additional advances in melanoma immuno-oncology are necessary to achieve a comprehensive knowledge of the immune infiltrate population and to identify accurate and readily measurable biomarkers. In this study, we analyzed gene expression of 468 melanoma cases from the TCGA database, which led to the identification of three melanoma clusters (representedby low, median and high infiltration) that display unique immune features. We found that the microenvironment clusters had substantial prognostic efficacy. The median cluster was characterized by an inability to draw immune cells, highlighting possible immune escape mechanisms, and lower CXCL9 and CXCL10 expression, which was correlated to poor prognosis. Deep molecular characterization of immune cells, cytolytic-activity and tumor-inflammatory status revealed diversity of the local immune infiltration landscape in the melanoma clusters. Differentially expressed genes related to TME were extracted from each infiltration cluster. Functional annotations revealed that these genes were mainly related to immune system activation and the processes of immunoreaction. The top ten hub genes in immune infiltration-related protein-protein interaction (PPI) networks were selected for further prognostic investigation. Further validation showed that five of ten hub genes were good prognostic biomarkers for melanoma in two independent groups from the Gene Expression Omnibus database. In brief, these data highlight that systemic characterization of melanoma could uncover tumor infiltrate characteristics, which can help select the most adequate treatment and identify consistent and important indicators of the local immune tumor microenvironment in melanoma patients.

Single-cell transcriptomic analysis defines the interplay between tumor cells, viral infection, and the microenvironment in nasopharyngeal carcinoma

Nasopharyngeal carcinoma (NPC) is an Epstein-Barr virus (EBV)-associated malignancy with a complex tumor ecosystem. How the interplay between tumor cells, EBV, and the microenvironment contributes to NPC progression and immune evasion remains unclear. Here we performed single-cell RNA sequencing on ~104,000 cells from 19 EBV⁺ NPCs and 7 nonmalignant nasopharyngeal biopsies, simultaneously profiling the transcriptomes of malignant cells, EBV, stromal and immune cells. Overall, we identified global upregulation of interferon responses in the multicellular ecosystem of NPC. Notably, an epithelial-immune dual feature of malignant cells was discovered and associated with poor prognosis. Functional experiments revealed that tumor cells with this dual feature exhibited a higher capacity for tumorigenesis. Further characterization of the cellular components of the tumor microenvironment (TME) and their interactions with tumor cells revealed that the dual feature of tumor cells was positively correlated with the expression of co-inhibitory receptors on CD8⁺ tumor-infiltrating T cells. In addition, tumor cells with the dual feature were found to repress IFN-γ production by T cells, demonstrating their capacity for immune suppression. Our results provide new insights into the multicellular ecosystem of NPC and offer important clinical implications.