DKK1 as a novel target for myeloma immunotherapy

Mitochondrial-related genes markers that predict survival in patients with head and neck squamous cell carcinoma affect immunomodulation through hypoxia, glycolysis, and angiogenesis pathways

Mitochondria play a crucial role in the occurrence and development of tumors. We used mitochondria-related genes for consistent clustering to identify three stable molecular subtypes of head and neck squamous cell carcinoma (HNSCC) with different prognoses, mutations, and immune characteristics. Significant differences were observed in clinical characteristics, immune microenvironment, immune cell infiltration, and immune cell scores. TP53 was the most significantly mutated; cell cycle-related pathways and tumorigenesis-related pathways were activated in different subtypes. Risk modeling was conducted using a multifactor stepwise regression method, and nine genes were identified as mitochondria-related genes affecting prognosis (DKK1, EFNB2, ITGA5, AREG, EPHX3, CHGB, P4HA1, CCND1, and JCHAIN). Risk score calculations revealed significant differences in prognosis, immune cell scores, immune cell infiltration, and responses to conventional chemotherapy drugs. Glycolysis, angiogenesis, hypoxia, and tumor-related pathways were positively correlated with the RiskScore. Clinical samples were subjected to qPCR to validate the results. In this work, we constructed a prognostic model based on the mitochondrial correlation score, which well reflects the risk and positive factors for the prognosis of patients with HNSCC. This model can be used to guide individualized adjuvant and immunotherapy in patients with HNSCC.

Plasmid DNA for Therapeutic Applications in Cancer

Recently, the interest in using nucleic acids for therapeutic applications has been increasing. DNA molecules can be manipulated to express a gene of interest for gene therapy applications or vaccine development. Plasmid DNA can be developed to treat different diseases, such as infections and cancer. In most cancers, the immune system is limited or suppressed, allowing cancer cells to grow. DNA vaccination has demonstrated its capacity to stimulate the immune system to fight against cancer cells. Furthermore, plasmids for cancer gene therapy can direct the expression of proteins with different functions, such as enzymes, toxins, and cytotoxic or proapoptotic proteins, to directly kill cancer cells. The progress and promising results reported in animal models in recent years have led to interesting clinical results. These DNA strategies are expected to be approved for cancer treatment in the near future. This review discusses the main strategies, challenges, and future perspectives of using plasmid DNA for cancer treatment.

Drug Discovery of DKK1 Inhibitors

Dickkopf-1 (DKK1) is a well-characterized Wnt inhibitor and component of the Wnt/β-catenin signaling pathway, whose dysregulation is associated with multiple abnormal pathologies including osteoporosis, Alzheimer's disease, diabetes, and various cancers. The Wnt signaling pathway has fundamental roles in cell fate determination, cell proliferation, and survival; thus, its mis-regulation can lead to disease. Although DKK1 is involved in other signaling pathways, including the β-catenin-independent Wnt pathway and the DKK1/CKAP4 pathway, the inhibition of DKK1 to propagate Wnt/β-catenin signals has been validated as an effective way to treat related diseases. In fact, strategies for developing DKK1 inhibitors have produced encouraging clinical results in different pathological models, and many publications provide detailed information about these inhibitors, which include small molecules, antibodies, and nucleic acids, and may function at the protein or mRNA level. However, no systematic review has yet provided an overview of the various aspects of their development and prospects. Therefore, we review the DKK1 inhibitors currently available or under study and provide an outlook on future studies involving DKK1 and drug discovery.

Construction of a five-gene prognostic model based on immune-related genes for the prediction of survival in pancreatic cancer

Purpose: To identify differentially expressed immune-related genes (DEIRGs) and construct a model with survival-related DEIRGs for evaluating the prognosis of patients with pancreatic cancer (PC).

Methods: Six microarray gene expression datasets of PC from the Gene Expression Omnibus (GEO) and Immunology Database and Analysis Portal (ImmPort) were used to identify DEIRGs. RNA sequencing and clinical data from The Cancer Genome Atlas Program-Pancreatic Adenocarcinoma (TCGA-PAAD) database were used to establish the prognostic model. Univariate, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analyses were applied to determine the final variables of the prognostic model. The median risk score was used as the cut-off value to classify samples into low- and high-risk groups. The prognostic model was further validated using an internal validation set of TCGA and an external validation set of GSE62452.

Results: In total, 142 DEIRGs were identified from six GEO datasets, 47 were survival-related DEIRGs. A prognostic model comprising five genes (i.e., ERAP2, CXCL9, AREG, DKK1, and IL20RB) was established. High-risk patients had poor survival compared with low-risk patients. The 1-, 2-, 3-year area under the receiver operating characteristic (ROC) curve of the model reached 0.85, 0.87, and 0.93, respectively. Additionally, the prognostic model reflected the infiltration of neutrophils and dendritic cells. The expression of most characteristic immune checkpoints was significantly higher in the high-risk group versus the low-risk group.

Conclusions: The five-gene prognostic model showed reliably predictive accuracy. This model may provide useful information for immunotherapy and facilitate personalized monitoring for patients with PC.

Monoclonal Antibodies for the Treatment of Multiple Myeloma: An Update

The past two decades have seen a revolution in multiple myeloma (MM) therapy with the introduction of several small molecules, mostly orally effective, whose mechanisms are based on proteasome inhibition, histone deacetylase (HDAC) blockade, and immunomodulation. Immunotherapeutic approaches to MM treatment using monoclonal antibodies (mAbs), while long in development, began to reap success with the identification of CD38 and SLAMF7 as suitable targets for development, culminating in the 2015 Food and Drug Administration (FDA) approval of daratumumab and elotuzumab, respectively. This review highlights additional mAbs now in the developmental pipeline. Isatuximab, another anti-CD38 mAb, currently is under study in four phase III trials and may offer certain advantages over daratumumab. Several antibody-drug conjugates (ADCs) in the early stages of development are described, including JNJ-63723283, which has attained FDA breakthrough status for MM. Other mAbs described in this review include denosumab, recently approved for myeloma-associated bone loss, and checkpoint inhibitors, although the future status of the latter combined with immunomodulators has been clouded by unacceptably high death rates that caused the FDA to issue clinical holds on several of these trials. Also highlighted are the therapies based on the B Cell Maturation Antigen (BCMA), another very promising target for anti-myeloma development.

The role of Dickkopf-1 as a potential prognostic marker in pancreatic ductal adenocarcinoma

Dickkopf-1(DKK-1), the downstream target of β-catenin/T-cell factor, participates in a negative feedback loop in the Wnt signaling and reported as an important biomarker in many tumors. In this study, we analyzed the expression of DKK-1 in pancreatic ductal adenocarcinoma (PDAC) patients at both mRNA and protein levels. We used real-time PCR to detect the expression of DKK-1 in 32 PDAC and paired adjacent non-tumor tissues, results suggested that the expression of DKK-1 was increased in PDAC tissues. We found the similar results in the analysis of 3 independent microarray data sets. Immunohistochemical staining of 311 pairs of PDAC tissues suggested that DKK-1 expression was significantly associated with T classification (P = 0.039) and lymph node metastasis (P = 0.035). Furthermore, Kaplan-Meier analysis for DKK-1 expression demonstrated that patients with higher DKK-1 level had shorter overall survival (OS) and relapse-free survival (RFS) time in Ren Ji cohort and online PDAC database at both mRNA and protein levels. Univariable and multivariable Cox regression analysis confirmed that DKK-1 as well as lymph node metastasis and histology were independent predictors of OS in patients with PDAC. This study demonstrated that DKK-1 may be a predictor for prognosis in PDAC patients.

MMSA-1 expression pattern in multiple myeloma and its clinical significance

Multiple myeloma-associated antigen-1 (MMSA-1) is a novel multiple myeloma (MM)-associated antigen which has been recently identified. Herein, we have tried to examine its clinical significance by studying the relationship between its expression and selected clinicopathological features. We extracted mononuclear cells from the bone marrow of MM patients and healthy donors and compared the MMSA-1 expression by RT-PCR and Western blot analysis. In addition, we also analyzed MMSA-1 expression in patients that were grouped based on selected clinical parameters. Moreover, the impact of MMSA-1 on patients' survival was also explored. MMSA-1 mRNA and protein were significantly upregulated in MM patients in comparison with healthy donors. Moreover, among the newly diagnosed and relapsed/refractory patients, the MMSA-1 expression was higher in relapsed/refractory patients. In addition, MMSA-1 mRNA expression not only showed significantly higher correlation with clinical parameters such as age, Durie and Salmon stage, bone lesion condition, albumin, creatinine and lactate dehydrogenase but also has a close relationship with myeloma bone disease-related cytokines, genetic abnormalities and treatment response. Multivariate COX analysis predicted MMSA-1 and LDH levels to be independently associated with a poor progression-free survival and overall survival in myeloma patients. Our findings provide initial proof of concept that MMSA-1 is a potent gene that is specifically expressed in MM patients and could be a feasible biomarker and independent prognostic factor.

Evaluating gene expression profiling by quantitative polymerase chain reaction to develop a clinically feasible test for outcome prediction in multiple myeloma

The gene expression profiles (GEPs) of 96 selected genes were analysed by real-time quantitative polymerase chain reaction (qPCR) with a TaqMan low-density array card in isolated tumour plasma cells (PCs) from 157 newly diagnosed multiple myeloma (MM) patients. This qPCR-based GEP correctly classified cases following the Translocation-cyclin D classification. Classic prognostic parameters and qPCR-based GEP predicted MM patient outcome and, although multivariate analyses revealed that cytogenetic risk (standard vs. high risk) was the variable that most strongly predicted prognosis, GEP added significant information for risk stratification. Considering only the standard risk cytogenetic patients, multivariate analyses revealed that high β2-microglobulin, low CDKN1A and high SLC19A1 gene expression levels independently predicted a short time-to-progression (TTP), while high International Staging System stage, low CDKN2B and high TBRG4 gene expression predicted poor overall survival (OS). A gene expression risk score enabled the division of standard risk patients into two groups with different TTPs (83% vs. 38% at 3 years, P < 0·0001) and OS rates (88% vs. 61% at 5 years; P = 0·003). This study demonstrates that quantitative PCR is a robust, accurate and feasible technique for implementing in the daily routine as a surrogate for GEP-arrays.