Identification of human leucocyte antigen (HLA)-A*0201-restricted cytotoxic T lymphocyte epitopes derived from HLA-DOβ as a novel target for multiple myeloma

Construction of immune-related gene pairs signature to predict the overall survival of multiple myeloma patients based on whole bone marrow gene expression profiling

Multiple myeloma (MM) is a plasma cell dyscrasia that is characterized by the uncontrolled proliferation of malignant PCs in the bone marrow. Due to immunotherapy, attention has returned to the immune system in MM, and it appears necessary to identify biomarkers in this area. In this study, we created a prognostic model for MM using immune-related gene pairs (IRGPs), with the advantage that it is not affected by technical bias. After retrieving microarray data of MM patients, bioinformatics analyses like COX regression and least absolute shrinkage and selection operator (LASSO) were used to construct the signature. Then its prognostic value is assessed via time-dependent receiver operating characteristic (ROC) and the Kaplan-Meier (KM) analysis. We also used XCELL to examine the status of immune cell infiltration among MM patients. 6-IRGP signatures were developed and proved to predict MM prognosis with a P-value of 0.001 in the KM analysis. Moreover, the risk score was significantly associated with clinicopathological characteristics and was an independent prognostic factor. Of note, the combination of age and β2-microglobulin with risk score could improve the accuracy of determining patients' prognosis with the values of the area under the curve (AUC) of 0.73 in 5 years ROC curves. Our model was also associated with the distribution of immune cells. This novel signature, either alone or in combination with age and β2-microglobulin, showed a good prognostic predictive value and might be used to guide the management of MM patients in clinical practice.

Integration of Transcriptome and Epigenome to Identify and Develop Prognostic Markers for Ovarian Cancer

DNA methylation is a widely researched epigenetic modification. It is associated with the occurrence and development of cancer and has helped evaluate patients' prognoses. However, most existing DNA methylation prognosis models have not simultaneously considered the changes of the downstream transcriptome. Methods. The RNA-Sequencing data and DNA methylation omics data of ovarian cancer patients were downloaded from The Cancer Genome Atlas (TCGA) database. The Consensus Cluster Plus algorithm was used to construct the methylated molecular subtypes of the ovary. Lasso regression was employed to build a multi-gene signature. An independent data set was applied to verify the prognostic value of the signature. The Gene Set Variation Analysis (GSVA) was used to carry out the enrichment analysis of the pathways linked to the gene signature. The IMvigor 210 cohort was used to explore the predictive efficacy of the gene signature for immunotherapy response. Results. We distinguished ovarian cancer samples into two subtypes with different prognosis, based on the omics data of DNA methylation. Differentially expressed genes and enrichment analysis among subtypes indicated that DNA methylation was related to fatty acid metabolism and the extracellular matrix (ECM)-receptor. Furthermore, we constructed an 8-gene signature, which proved to be efficient and stable in predicting prognostics in ovarian cancer patients with different data sets and distinctive pathological characteristics. Finally, the 8-gene signature could predict patients' responses to immunotherapy. The polymerase chain reaction experiment was further used to verify the expression of 8 genes. Conclusion. We analyzed the prognostic value of the related genes of methylation in ovarian cancer. The 8-gene signature predicted the prognosis and immunotherapy response of ovarian cancer patients well and is expected to be valuable in clinical application.

Therapeutic Cancer Vaccines—Antigen Discovery and Adjuvant Delivery Platforms

For decades, vaccines have played a significant role in protecting public and personal health against infectious diseases and proved their great potential in battling cancers as well. This review focused on the current progress of therapeutic subunit vaccines for cancer immunotherapy. Antigens and adjuvants are key components of vaccine formulations. We summarized several classes of tumor antigens and bioinformatic approaches of identification of tumor neoantigens. Pattern recognition receptor (PRR)-targeting adjuvants and their targeted delivery platforms have been extensively discussed. In addition, we emphasized the interplay between multiple adjuvants and their combined delivery for cancer immunotherapy.

Identification and Verification of Necroptosis-Related Gene Signature With Prognosis and Tumor Immune Microenvironment in Ovarian Cancer

Ovarian cancer is the most lethal heterogeneous disease among gynecological tumors with a poor prognosis. Necroptosis, the most studied way of death in recent years, is different from apoptosis and pyroptosis. It is a kind of regulated programmed cell death and has been shown to be closely related to a variety of tumors. However, the expression and prognosis of necroptosis-related genes in ovarian cancer are still unclear. Our study therefore firstly identified the expression profiles of necroptosis-related genes in normal and ovarian cancer tissues. Next, based on differentially expressed necroptosis-related genes, we clustered ovarian cancer patients into two subtypes and performed survival analysis. Subsequently, we constructed a risk model consisting of 5 genes by LASSO regression analysis based on the differentially expressed genes in the two subtypes, and confirmed the strong prognostic ability of the model and its potential as an independent risk factor via survival analysis and independent risk factor analysis. Based on this risk model, patients were divided into high and low risk groups. By exploring differentially expressed genes, enrichment functions and tumor immune microenvironment in patients in high and low risk groups, the results showed that patients in the low risk group were significantly enriched in immune signaling pathways. Besides, immune cells content, immune function activity was significantly better than the high-risk group. Eventually, we also investigated the sensitivity of patients with different risk groups to ICB immunotherapy and chemotherapy drugs. In conclusion, the risk model could effectively predict the survival and prognosis of patients, and explore the tumor microenvironment status of ovarian cancer patients to a certain extent, and provide promising and novel molecular markers for clinical diagnosis, individualized treatment and immunotherapy of patients.

Construction of a Macrophage Infiltration Regulatory Network and Related Prognostic Model of High-Grade Serous Ovarian Cancer

Background

High-grade serous ovarian cancer (HGSOC) carries the highest mortality in the gynecological cancers; however, therapeutic outcomes have not significantly improved in recent decades. Macrophages play an essential role in the occurrence and development of ovarian cancer, so the mechanisms of macrophage infiltration should be elucidated.

Method

We downloaded transcriptome data of ovarian cancers from the Gene Expression Omnibus and The Cancer Genome Atlas. After rigorous screening, 1566 HGSOC were used for data analysis. CIBERSORT was used to estimate the level of macrophage infiltration and WGCNA was used to identify macrophage-related modules. We constructed a macrophage-related prognostic model using machine learning LASSO algorithm and verified it using multiple HGSOC cohorts.

Results

In the GPL570-OV cohort, high infiltration level of M1 macrophages was associated with a good outcome, while high infiltration level of M2 macrophages was associated with poor outcomes. We used WGCNA to select genes correlated with macrophage infiltration. These genes were used to construct protein-protein interaction maps of macrophage infiltration. IFL44L, RSAD2, IFIT3, MX1, IFIH1, IFI44, and ISG15 were the hub genes in the network. We then constructed a macrophage-related prognostic model composed of CD38, ACE2, BATF2, HLA-DOB, and WARS. The model had the ability to predict the overall survival rate of HGSOC patients in GPL570-OV, GPL6480-OV, TCGA-OV, GSE50088, and GSE26712. In exploring the immune microenvironment, we found that CD4 memory T cells and activated mast cells showed that the degree of infiltration was higher in the high-risk group, while M1 macrophages were the opposite, and HLA molecules were overexpressed in the high-risk group.

Conclusion

We constructed a macrophage infiltration-related protein interaction network that provides a basis for studying macrophages in HGSOC. Our macrophage-related prognostic model is robust and widely applicable. It predicts overall survival in HGSOC patients and may improve HGSOC treatment.

High expression of CPNE5 and CPNE9 predicts positive prognosis in multiple myeloma

BACKGROUND

CPNEs are significant biomarkers which can affect the progression and prognosis of various tumor diseases. However, the prognosis role of CPNEs in multiple myeloma (MM) is still unclear.

OBJECTIVES

To investigate the prognosis role of CPNEs in MM.

METHODS

Seven hundred and thirty-five samples from two independent data sets were involved to analyze the clinical and molecular characteristics, and prognosis role of the expression of CPNE1-9 in MM.

RESULTS

MM patients with higher expressions of CPNE5 and CPNE9 had longer event-free survival (EFS) and overall survival (OS) compared with CPNE5low and CPNE9low expression groups (EFS: P= 0.0054, 0.0065; OS: P= 0.015, 0.016, respectively). Multivariate regression analysis showed that CPNE5 was an independent favorable predictor for EFS and OS (EFS: P= 0.005; OS: P= 0.006), and CPNE9 was an independent positive indicator for EFS (P= 0.002). Moreover, the survival probability and the cumulative event of EFS and OS in CPNE5highCPNE9high group were significantly longer than other groups.

CONCLUSIONS

High expressions of CPNE5 and CPNE9 might be used as positive indicators for MM, and their combination was a better predictor for the survival of MM patients.

High expression of chaperonin-containing TCP1 subunit 3 may induce dismal prognosis in multiple myeloma

The prognosis role of CCT3 in MM and the possible pathways it involved were studied in our research. By analyzing ten independent datasets (including 48 healthy donors, 2220 MM, 73 MGUS, and 6 PCL), CCT3 was found to express higher in MM than healthy donors, and the expression level was gradually increased from MGUS, SMM, MM to PCL (all P < 0.01). By analyzing three independent datasets (GSE24080, GSE2658, and GSE4204), we found that CCT3 was a significant indicator of poor prognosis (all P < 0.01). KEGG and GSEA analysis showed that CCT3 expression was associated with JAK-STAT3 pathway, Hippo signaling pathway, and WNT signaling pathway. In addition, different expressed genes analysis revealed MYC, which was one of the downstream genes regulated by JAK-STAT3 pathway, was upregulated in MM. This confirms that JAK-STAT3 signaling pathway may promote the progress of disease which was regulated by CCT3 expression. Our study revealed that CCT3 may play a supporting role at the diagnosis of myeloid, and high expression of CCT3 suggested poor prognosis in MM. CCT3 expression may promote the progression of MM mainly by regulating MYC through JAK-STAT3 signaling pathway.

Whole Blood Targeted Bisulfite Sequencing and Differential Methylation in the C6ORF10 Gene of Patients with Rheumatoid Arthritis

Objective.

Polymorphisms in human major histocompatibility complex (MHC) are the strongest genetic associations with rheumatoid arthritis (RA). Epigenome-wide methylation studies suggest DNA methylation changes within MHC may contribute to disease susceptibility. We profiled MHC-specific methylated CpG (5′–C–phosphate–G–3′) in autoantibody-positive patients with RA and matched unaffected anticitrullinated protein antibodies–negative first-degree relatives (ACPA−/FDR) from an indigenous North American (INA) population that is known to have prevalent RA.

Methods.

DNA was isolated from whole blood and targeted bisulfite sequencing was used to profile methylated CpG in patients with RA and ACPA−/FDR. Differentially methylated CpG loci (DML) were mapped and gene annotated. Ingenuity pathway analysis (IPA) was used for curating biomolecular networks of mapped genes. Transcript abundance was determined by quantitative (q)PCR.

Results.

We identified 74 uniquely methylated CpG sites within the MHC region that were differentially methylated in patients with RA (p < 0.05), compared to ACPA−/FDR. Of these, 32 DML were located on 22 genes. IPA showed these genes are involved in regulating the nuclear factor–κB complex and processes involved in antigen presentation, and immune cell crosstalk in autoimmunity. Pearson correlation analysis demonstrated a negative association between differentially methylated CpG in the C6ORF10 gene and risk factors associated with RA. Analysis by qPCR confirmed differential abundance of C6ORF10, TNXB, and HCG18 mRNA in patients with RA compared to ACPA−/FDR.

Conclusion.

Our results confirm the presence of differential methylation at specific gene loci within the MHC region of INA patients with RA. These epigenetic signatures may precede disease onset, or alternatively, may be a result of developing RA.

Three-way interaction model to trace the mechanisms involved in Alzheimer's disease transgenic mice

Alzheimer's disease (AD) is the most common cause for dementia in human. Currently, more than 46 million people in the world suffer from AD and it is estimated that by 2050 this number increases to more than 131 million. AD is considered as a complex disease. Therefore, understanding the mechanism of AD is a universal challenge. Nowadays, a huge number of disease-related high-throughput “omics” datasets are freely available. Such datasets contain valuable information about disease-related pathways and their corresponding gene interactions. In the present work, a three-way interaction model is used as a novel approach to understand AD-related mechanisms. This model can trace the dynamic nature of co-expression relationship between two genes by introducing their link to a third gene. Apparently, such relationships cannot be traced by the classical two-way interaction model. Liquid association method was applied to capture the statistically significant triplets which are involved in three-way interaction. Subsequently, gene set enrichment analysis (GSEA) and gene regulatory network (GRN) inference were applied to analyze the biological relevance of the statistically significant triplets. The results of this study suggest that the innate immunity processes are important in AD. Specifically, our results suggest that H2-Ob as the switching gene and the gene pair {Csf1r, Milr1} form a statistically significant and biologically relevant triplet, which may play an important role in AD. We propose that the homeostasis-related link between mast cells and microglia is presumably controlled with H2-Ob expression levels as a switching gene.

A novel multi-epitope vaccine from MMSA-1 and DKK1 for multiple myeloma immunotherapy

The identification of novel tumour-associated antigens is urgently needed to improve the efficacy of immunotherapy for multiple myeloma (MM). In this study, we identified a membrane protein MMSA-1 (multiple myeloma special antigen-1) that was specifically expressed in MM and exhibited significantly positive correlation with MM. We then identified HLA-A*0201-restricted MMSA-1 epitopes and tested their cytotoxic T lymphocyte (CTL) response. The MMSA-1 epitope SLSLLTIYV vaccine was shown to induce an obvious CTL response in vitro. To improve the immunotherapy, we constructed a multi-epitope peptide vaccine by combining epitopes derived from MMSA-1 and Dickkopf-1 (DKK1). The effector T cells induced by multi-epitope peptide vaccine-loaded dendritic cells lysed U266 cells more effectively than MMSA-1/DKK1 single-epitope vaccine. In myeloma-bearing severe combined immunodeficient mice, the multi-epitope vaccine improved the survival rate significantly compared with single-epitope vaccine. Consistently, multi-epitope vaccine decreased the tumour volume greatly and alleviated bone destruction. The frequencies of CD4⁺ and CD8⁺ T cells was significantly increased in mouse blood induced by the multi-epitope vaccine, indicating that it inhibits myeloma growth by changing T cell subsets and alleviating immune paralysis. This study identified a novel peptide from MMSA-1 and the multi-epitope vaccine will be used to establish appropriate individualized therapy for MM.

Ribonucleotide Reductase Catalytic Subunit M1 (RRM1) as a Novel Therapeutic Target in Multiple Myeloma

Purpose: To investigate the biological and clinical significance of ribonucleotide reductase (RR) in multiple myeloma.Experimental Design: We assessed the impact of RR expression on patient outcome in multiple myeloma. We then characterized the effect of genetic and pharmacologic inhibition of ribonucleotide reductase catalytic subunit M1 (RRM1) on multiple myeloma growth and survival using siRNA and clofarabine, respectively, in both in vitro and in vivo mouse xenograft models.Results: Newly diagnosed multiple myeloma patients with higher RRM1 expression have shortened survival. Knockdown of RRM1 triggered significant growth inhibition and apoptosis in multiple myeloma cells, even in the context of the bone marrow microenvironment. Gene expression profiling showed upregulation of DNA damage response genes and p53-regulated genes after RRM1 knockdown. Immunoblot and qRT-PCR analysis confirmed that γ-H2A.X, ATM, ATR, Chk1, Chk2, RAD51, 53BP1, BRCA1, and BRCA2 were upregulated/activated. Moreover, immunoblots showed that p53, p21, Noxa, and Puma were activated in p53 wild-type multiple myeloma cells. Clofarabine, a purine nucleoside analogue that inhibits RRM1, induced growth arrest and apoptosis in p53 wild-type cell lines. Although clofarabine did not induce cell death in p53-mutant cells, it did trigger synergistic toxicity in combination with DNA-damaging agent melphalan. Finally, we demonstrated that tumor growth of RRM1-knockdown multiple myeloma cells was significantly reduced in a murine human multiple myeloma cell xenograft model.Conclusions: Our results therefore demonstrate that RRM1 is a novel therapeutic target in multiple myeloma in the preclinical setting and provide the basis for clinical evaluation of RRM1 inhibitor, alone or in combination with DNA-damaging agents, to improve patient outcome in multiple myeloma. Clin Cancer Res; 23(17); 5225-37. ©2017 AACR.

A Comprehensive Gene Expression Meta-analysis Identifies Novel Immune Signatures in Rheumatoid Arthritis Patients

Rheumatoid arthritis (RA), a symmetric polyarticular arthritis, has long been feared as one of the most disabling forms of arthritis. Identification of gene signatures associated with RA onset and progression would lead toward development of novel diagnostics and therapeutic interventions. This study was undertaken to identify unique gene signatures of RA patients through large-scale meta-profiling of a diverse collection of gene expression data sets. We carried out a meta-analysis of 8 publicly available RA patients’ (107 RA patients and 76 healthy controls) gene expression data sets and further validated a few meta-signatures in RA patients through quantitative real-time PCR (RT-qPCR). We identified a robust meta-profile comprising 33 differentially expressed genes, which were consistently and significantly expressed across all the data sets. Our meta-analysis unearthed upregulation of a few novel gene signatures including PLCG2, HLA-DOB, HLA-F, EIF4E2, and CYFIP2, which were validated in peripheral blood mononuclear cell samples of RA patients. Further, functional and pathway enrichment analysis reveals perturbation of several meta-genes involved in signaling pathways pertaining to inflammation, antigen presentation, hypoxia, and apoptosis during RA. Additionally, PLCG2 (phospholipase Cγ2) popped out as a novel meta-gene involved in most of the pathways relevant to RA including inflammasome activation, platelet aggregation, and activation, thereby suggesting PLCG2 as a potential therapeutic target for controlling excessive inflammation during RA. In conclusion, these findings highlight the utility of meta-analysis approach in identifying novel gene signatures that might provide mechanistic insights into disease onset, progression and possibly lead toward the development of better diagnostic and therapeutic interventions against RA.

Identification of human leukemia antigen A*0201-restricted epitopes derived from epidermal growth factor pathway substrate number 8

T-cell-mediated immunotherapy of hematological malignancies requires selection of targeted tumor-associated antigens and T-cell epitopes contained in these tumor proteins. Epidermal growth factor receptor pathway substrate 8 (EPS8), whose function is pivotal for tumor proliferation, progression and metastasis, has been found to be overexpressed in most human tumor types, while its expression in normal tissue is low. The aim of the present study was to identify human leukemia antigen (HLA)-A*0201-restricted epitopes of EPS8 by using a reverse immunology approach. To achieve this, computer algorithms were used to predict HLA-A*0201 molecular binding, proteasome cleavage patterns as well as translocation of transporters associated with antigen processing. Candidate peptides were experimentally validated by T2 binding affinity assay and brefeldin-A decay assay. The functional avidity of peptide-specific cytotoxic T lymphocytes (CTLs) induced from peripheral blood mononuclear cells of healthy volunteers were evaluated by using an enzyme-linked immunosorbent spot assay and a cytotoxicity assay. Four peptides, designated as P455, P92, P276 and P360, had high affinity and stability of binding towards the HLA-A*0201 molecule, and specific CTLs induced by them significantly responded to the corresponding peptides and secreted IFN-γ. At the same time, the CTLs were able to specifically lyse EPS8-expressing cell lines in an HLA-A*0201-restricted manner. The present study demon-strated that P455, P92, P276 and P360 were CTL epitopes of EPS8, and were able to be used for epitope-defined adoptive T-cell transfer and multi-epitope-based vaccine design.

T cell-based targeted immunotherapies for patients with multiple myeloma

Despite high-dose chemotherapy followed by autologs stem-cell transplantation as well as novel therapeutic agents, multiple myeloma (MM) remains incurable. Following the general trend towards personalized therapy, targeted immunotherapy as a new approach in the therapy of MM has emerged. Better progression-free survival and overall survival after tandem autologs/allogeneic stem cell transplantation suggest a graft versus myeloma effect strongly supporting the usefulness of immunological therapies for MM patients. How to induce a powerful antimyeloma effect is the key issue in this field. Pivotal is the definition of appropriate tumor antigen targets and effective methods for expansion of T cells with clinical activity. Besides a comprehensive list of tumor antigens for T cell-based approaches, eight promising antigens, CS1, Dickkopf-1, HM1.24, Human telomerase reverse transcriptase, MAGE-A3, New York Esophageal-1, Receptor of hyaluronic acid mediated motility and Wilms' tumor gene 1, are described in detail to provide a background for potential clinical use. Results from both closed and on-going clinical trials are summarized in this review. On the basis of the preclinical and clinical data, we elaborate on three encouraging therapeutic options, vaccine-enhanced donor lymphocyte infusion, chimeric antigen receptors-transfected T cells as well as vaccines with multiple antigen peptides, to pave the way towards clinically significant immune responses against MM.

Peptide vaccines for hematological malignancies: a missed promise?

Despite the crucial aid that newly developed target therapies are providing to chemotherapy and stem cell transplant, the cure for many hematological malignancies is still an unmet need. Although available therapies are able to induce an effective debulking of the tumor, most of the time, an insidious minimal residual disease survives current treatments and it is responsible for an immediate or delayed relapse. Peptide-derived antitumor vaccines have been developed with the idea that an artificially "educated" immune system may exert an active specific antitumor response able to control and ultimately eradicate underlying post-treatment residual disease. This review will summarize current knowledge of peptide vaccines for hematological malignancies, trying to analyze promises and pitfalls of a safe and intelligent tool that after many years from its first appearance has not yet established its potential role as alternative immune mediated therapeutic approach for hematopoietic tumors.