We report the detailed development of biomarkers to predict the clinical outcome under dengue infection. Transcriptional signatures from purified peripheral blood mononuclear cells were derived from whole-genome gene-expression microarray data, validated by quantitative PCR and tested in independent samples. The study was performed on patients of a well-characterized dengue cohort from Recife, Brazil. The samples analyzed were collected prospectively from acute febrile dengue patients who evolved with different degrees of disease severity: classic dengue fever or dengue hemorrhagic fever (DHF) samples were compared with similar samples from other non-dengue febrile illnesses. The DHF samples were collected 2–3 days before the presentation of the plasma leakage symptoms. Differentially-expressed genes were selected by univariate statistical tests as well as multivariate classification techniques. The results showed that at early stages of dengue infection, the genes involved in effector mechanisms of innate immune response presented a weaker activation on patients who later developed hemorrhagic fever, whereas the genes involved in apoptosis were expressed in higher levels. Some of the gene expression signatures displayed estimated accuracy rates of more than 95%, indicating that expression profiling with these signatures may provide a useful means of DHF prognosis at early stages of infection.

Head and neck squamous cell carcinoma (HNSCC) encompass a group of complex entities of tumours affecting the aerodigestive upper tract. The main risk factors are strongly related to tobacco and alcohol consumption, but also HPV infection is often associated. Surgery, radiotherapy and/or chemotherapy are the standard treatments, though the 5-year overall survival is less than 50%. The advances in genomics, molecular medicine, immunology, and nanotechnology have shed a light on tumour biology which helps clinical researchers to obtain more efficacious and less toxic therapies. Head and neck tumours possess different immune escape mechanisms including diminishing the immune response through modulating immune checkpoints, in addition to the recruitment and differentiation of suppressive immune cells. The insights into the HNSCC biology and its strong interaction with the tumour microenvironment highlights the role of immunomodulating agents. Recently, the knowledge of the immunological features of these tumours has paved the way for the discovery of effective biomarkers that allow a better selection of patients with odds of improving overall survival through immunotherapy. Specially biomarkers regarding immune checkpoint inhibitors antibodies, such as anti-PD-1/PD-L1 and anti-CTLA-4 in combination with standard therapy or as monotherapy. New immunotherapies to treat head and neck cancer carcinomas, such as CAR T cells and nanoparticles have been the center of attention and in this review, we discuss the necessity of finding targets for the T cell in the cancer cells to generate CAR T cells, but also the relevance of evaluating specificity and safety of those therapies.

Symptomatic infection by dengue virus (DENV) can range from dengue fever (DF) to dengue haemorrhagic fever (DHF), however, the determinants of DF or DHF progression are not completely understood. It is hypothesised that host innate immune response factors are involved in modulating the disease outcome and the expression levels of genes involved in this response could be used as early prognostic markers for disease severity. mRNA expression levels of genes involved in DENV innate immune responses were measured using quantitative real time PCR (qPCR). Here, we present a novel application of the support vector machines (SVM) algorithm to analyze the expression pattern of 12 genes in peripheral blood mononuclear cells (PBMCs) of 28 dengue patients (13 DHF and 15 DF) during acute viral infection. The SVM model was trained using gene expression data of these genes and achieved the highest accuracy of ∼85% with leave-one-out cross-validation. Through selective removal of gene expression data from the SVM model, we have identified seven genes (MYD88, TLR7, TLR3, MDA5, IRF3, IFN-α and CLEC5A) that may be central in differentiating DF patients from DHF, with MYD88 and TLR7 observed to be the most important. Though the individual removal of expression data of five other genes had no impact on the overall accuracy, a significant combined role was observed when the SVM model of the two main genes (MYD88 and TLR7) was re-trained to include the five genes, increasing the overall accuracy to ∼96%. Here, we present a novel use of the SVM algorithm to classify DF and DHF patients, as well as to elucidate the significance of the various genes involved. It was observed that seven genes are critical in classifying DF and DHF patients: TLR3, MDA5, IRF3, IFN-α, CLEC5A, and the two most important MYD88 and TLR7. While these preliminary results are promising, further experimental investigation is necessary to validate their specific roles in dengue disease.

Cancer immunotherapy is the most promising trend in oncology, focusing on helping or activating the patient's immune system to identify and fight against cancer. In the last decade, interest in met...

Currently, several assays can confirm acute dengue infection at the point-of-care. However, none of these assays can predict the severity of the disease symptoms. A prognosis test that predicts the likelihood of a dengue patient to develop a severe form of the disease could permit more efficient patient triage and treatment. We hypothesise that mRNA expression of apoptosis and innate immune response-related genes will be differentially regulated during the early stages of dengue and might predict the clinical outcome. Aiming to identify biomarkers for dengue prognosis, we extracted mRNA from the peripheral blood mononuclear cells of mild and severe dengue patients during the febrile stage of the disease to measure the expression levels of selected genes by quantitative polymerase chain reaction. The selected candidate biomarkers were previously identified by our group as differentially expressed in microarray studies. We verified that the mRNA coding for CFD, MAGED1, PSMB9, PRDX4 and FCGR3B were differentially expressed between patients who developed clinical symptoms associated with the mild type of dengue and patients who showed clinical symptoms associated with severe dengue. We suggest that this gene expression panel could putatively serve as biomarkers for the clinical prognosis of dengue haemorrhagic fever.