RESUMEN
The SARS-CoV-2 pandemic has elicited a unique international mobilization of the scientific community to better understand this coronavirus and its associated disease and to develop efficient tools to combat infection. Similar to other coronavirae, SARS-CoV-2 hijacks the host cell complex secretory machinery to produce properly folded viral proteins that will compose the nascent virions; including Spike, Envelope and Membrane proteins, the most exposed membrane viral proteins to the host immune system. Antibody response is part of the anti-viral immune arsenal that infected patients develop to fight viral particles in the body. Herein, we investigate the immunogenic potential of Spike (S), Envelope (E) and Membrane (M) proteins using a human cell-based system to mimic membrane insertion and N-glycosylation. We show that both S and M proteins elicit the production of specific IgG, IgM and IgA in SARS-CoV-2 infected patients. Elevated Ig responses were observed in COVID+ patients with moderate and severe forms of the disease. Finally, when SARS-CoV-2 Spike D614 and G614 variants were compared, reduced Ig binding was observed with the Spike G614 variant. Altogether, this study underlines the needs for including topological features in envelop proteins to better characterize the serological status of COVID+ patients, points towards an unexpected immune response against the M protein and shows that our assay could represent a powerful tool to test humoral responses against actively evolving SARS-CoV-2 variants and vaccine effectiveness.
RESUMEN
BACKGROUND: Glioblastoma (GBM) is the most common and lethal primary brain tumor in adults. Several recent transcriptomic studies in GBM have identified different signatures involving immune genes associated with GBM pathology, overall survival (OS) or response to treatment. METHODS: In order to clarify the immune signatures found in GBM, we performed a co-expression network analysis that grouped 791 immune-associated genes (IA genes) in large clusters using a combined dataset of 161 GBM specimens from published databases. We next studied IA genes associated with patient survival using 3 different statistical methods. We then developed a 6-IA gene risk predictor which stratified patients into two groups with statistically significantly different survivals. We validated this risk predictor on two other Affymetrix data series, on a local Agilent data series, and using RT-Q-PCR on a local series of GBM patients treated by standard chemo-radiation therapy. RESULTS: The co-expression network analysis of the immune genes disclosed 6 powerful modules identifying innate immune system and natural killer cells, myeloid cells and cytokine signatures. Two of these modules were significantly enriched in genes associated with OS. We also found 108 IA genes linked to the immune system significantly associated with OS in GBM patients. The 6-IA gene risk predictor successfully distinguished two groups of GBM patients with significantly different survival (OS low risk: 22.3 months versus high risk: 7.3 months; p < 0.001). Patients with significantly different OS could even be identified among those with known good prognosis (methylated MGMT promoter-bearing tumor) using Agilent (OS 25 versus 8.1 months; p < 0.01) and RT-PCR (OS 21.8 versus 13.9 months; p < 0.05) technologies. Interestingly, the 6-IA gene risk could also distinguish proneural GBM subtypes. CONCLUSIONS: This study demonstrates the immune signatures found in previous GBM genomic analyses and suggests the involvement of immune cells in GBM biology. The robust 6-IA gene risk predictor should be helpful in establishing prognosis in GBM patients, in particular in those with a proneural GBM subtype, and even in the well-known good prognosis group of patients with methylated MGMT promoter-bearing tumors.