BACKGROUND AND PURPOSE The Rasch-Built Pompe-Specific Activity (R-PAct) scale is a patient-reported outcome measure specifically designed to quantify the effects of Pompe disease on daily life activities, developed for use in Dutch- and English-speaking countries. This study aimed to validate the R-PAct for use in other countries. METHODS Four other language versions (German, French, Italian, and Spanish) of the R-PAct were created and distributed among Pompe patients (≥16 years old) in Germany, France, Spain, Italy, and Switzerland and pooled with data of newly diagnosed patients from Australia, Belgium, Canada, the Netherlands, New Zealand, the USA, and the UK and the original validation cohort (n = 186). The psychometric properties of the scale were assessed by exploratory factor analysis and Rasch analysis. RESULTS Data for 520 patients were eligible for analysis. Exploratory factor analysis suggested that the items separated into two domains: Activities of Daily Living and Mobility. Both domains independently displayed adequate Rasch model measurement properties, following the removal of one item ("Are you able to practice a sport?") from the Mobility domain, and can be added together to form a "higher order" factor as well. Differential item functioning (DIF)-by-language assessment indicated DIF for several items; however, the impact of accounting for DIF was negligible. We recalibrated the nomogram (raw score interval-level transformation) for the updated 17-item R-PAct scale. The minimal detectable change value was 13.85 for the overall R-PAct. CONCLUSIONS After removing one item, the modified-R-PAct scale is a valid disease-specific patient-reported outcome measure for patients with Pompe disease across multiple countries.

Glioblastoma’s (GBM) origin, recurrence and resistance to treatment are driven by GBM cancer stem cells (GSCs). Existing transcriptomic characterisations of GBM classify the tumours to three subtypes: classical, proneural, and mesenchymal. The comprehension of how expression patterns of the GBM subtypes are reflected at global proteome level in GSCs is limited. To characterise protein expression in GSCs, we performed in-depth proteogenomic analysis of patient-derived GSCs by RNA-sequencing and mass-spectrometry proteomics. We identified and quantified over 10,000 proteins in two independent GSCs panels, and propose a GSC-associated proteomic signature (GSAPS) that defines two distinct morphological conditions; one defined by a set of proteins expressed in non-mesenchymal - proneural and classical - GSCs (GPC-like), and another expressed in mesenchymal GSCs (GM-like). The expression of GM-like protein set in GBM tissue was associated with hypoxia, necrosis, recurrence, and worse overall survival in GBM patients. In a proof-of-concept proteogenomic approach, we discovered 252 non-canonical peptides expressed in GSCs, i.e., protein sequences that are variant or derive from genome regions previously considered protein-non-coding. We report new variants of the heterogeneous ribonucleoproteins (HNRNPs), which are implicated in mRNA splicing. Furthermore, we show that per-gene mRNA-protein correlations in GSCs are moderate and vary compared to GBM tissue.

To the Editor, The high demand for COVID19 vaccines, combined with a significant lack of supply, leaves smaller and developing countries behind in mass immunization. This prompts the question whether administering a single vaccine dose in SARSCoV2 seropositive individuals could be a method for rationing available vaccine doses. We report results from a prospective study on Macedonian healthcare workers who received two doses of the Pfizer/BioNTech BNT162b2 mRNA vaccine, comparing antibody titres and frequency of side effects after vaccine administration between individuals who were SARSCoV2 seropositive (SeroPOS group) and seronegative (SeroNEG group) prior to immunization. The study included 226 participants recruited through convenience sampling, of whom 41 were SeroPOS (73.17% female; mean age 43 years, SD: 10.571), and 185 were SeroNEG (68.11% female, mean age 46 years, SD: 10.523). Baseline patients’ characteristics are provided in the Supplementary Appendix (Table S1). Blood samples were collected 18– 21 days after the first vaccine dose and 25– 28 days after the second dose. Baseline antibody levels were obtained from patient records. All participants gave blood samples after the first dose and filed a questionnaire for side effects, and 189 participants (83.63%) returned for assessment four weeks after the second dose. Serological testing was performed using the commercially available quantitative CLIA antiSARSCoV2 RBD kit (Snibe, Shenzhen, China),1 which targets the S1 subunit of the viral spike protein. More details on methods are available in the Supplementary Appendix. AntiSARSCoV2 RBD IgG antibody levels after the first dose of BNT162b2 were on average 11.7times higher in SeroPOS individuals (mean: 923.40 AU/ml, SD: 948.119, range 15.04– 5034.70) compared to SeroNEG individuals (mean: 79.06 AU/ml, SD: 253.243, range 0.912– 1867.30; Wilcoxon ranksum test, p < 2e16, Figure 1A). After the second dose, antiSARSCoV2 RBD IgG antibody levels were still higher in SeroPOS individuals (mean: 602.59 AU/ml, SD: 511.545, range 25.41– 1986.00) compared to SeroNEG individuals (mean: 375.567 AU/ml, SD: 437.088, range 9.617– 3704.40; Wilcoxon ranksum test, p = 0.006, Figure 1B). SeroNEG individuals had on average a 5.35fold increase in antiSARSCoV2 RBD IgG antibody levels after the second dose (Wilcoxon signedrank test, p < 2e16, Figure 1B), whereas SeroPOS individuals had no benefit of increased antibody levels after the second dose (Wilcoxon signedrank test, p = 0.529, Figure 1B). SeroPOS individuals had higher antibody levels after the first dose than SeroNEG individuals after the second dose (Wilcoxon ranksum test, p = 0.0039, Figure 1B). Exploratory analysis of the influence of sex and age on antibody response showed that older age had a reducing effect on antibody levels after the first and second vaccine dose (Supplementary Appendix, Table S2). The vast majority of the study participants reported at least one side effect after the first dose (91.15%, Figure 1C), mostly minor local pain (69.47%). A higher proportion of study participants reported at least one side effect after the second dose (97.35%, Figure 1D), again mostly minor local pain (53.97%). Our findings are in line with previous reports of higher antibody levels in SeroPOS individuals after a single dose of BNT162b2 compared to SeroNEG individuals25 and support the hypothesis that a single dose of BNT162b2 in SARSCoV2 seropositive individuals might provide sufficient humoral immunity towards SARSCoV2. These findings should be validated in a clinical trial setting as soon as possible, due to direct implications for public health policy in developing countries with limited access to vaccines. Future investigations should incorporate analyses of the cellular immunity and take into consideration the duration of the immune response, which have not been evaluated in this study. The more rational use of vaccines could accelerate the attainment of collective immunity at reduced costs.

Objective: To explain the global between-countries variance in number of deaths per million citizens (nDpm) and case fatality rate (CFR) due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Design: Systematic analysis. Data sources: Worldometer, European Centre for Disease Prevention and Control, United Nations Main outcome measures: The explanators of nDpm and CFR were mathematically hypothesised and tested on publicly-available data from 88 countries with linear regression models on May 1st 2020. The derived explanators - age-adjusted infection fatality rate (IFRadj) and case detection rate (CDR) - were estimated for each country based on a SARS-CoV-2 model of China. The accuracy and agreement of the models with observed data was assessed with R2 and Bland-Altman plots, respectively. Sensitivity analyses involved removal of outliers and testing the models at five retrospective and two prospective time points. Results: Globally, IFRadj estimates varied between countries, ranging from below 0.2% in the youngest nations, to above 1.3% in Portugal, Greece, Italy, and Japan. The median estimated global CDR of SARS-CoV-2 infections on April 16th 2020 was 12.9%, suggesting that most of the countries have a much higher number of cases than reported. At least 93% and up to 99% of the variance in nDpm was explained by reported prevalence expressed as cases per million citizens (nCpm), IFRadj, and CDR. IFRadj and CDR accounted for up to 97% of the variance in CFR, but this model was less reliable than the nDpm model, being sensitive to outliers (R2 as low as 67.5%). Conclusions: The current differences in SARS-CoV-2 mortality between countries are driven mainly by reported prevalence of infections, age distribution, and CDR. The nDpm might be a more stable estimate than CFR in comparing mortality burden between countries.

Background Immune checkpoint inhibitors (ICIs) have significantly improved the outcome in metastatic cutaneous melanoma (CM). However, therapy response is limited to subgroups of patients and clinically useful predictive biomarkers are lacking. Methods To discover treatment-related systemic changes in plasma and potential biomarkers associated with treatment outcome, we analyzed serial plasma samples from 24 patients with metastatic CM, collected before and during ICI treatment, with mass-spectrometry-based global proteomics (high-resolution isoelectric focusing liquid chromatography–mass spectrometry (HiRIEF LC-MS/MS)) and targeted proteomics with proximity extension assays (PEAs). In addition, we analyzed plasma proteomes of 24 patients with metastatic CM treated with mitogen-activated protein kinase inhibitors (MAPKis), to pinpoint changes in protein plasma levels specific to the ICI treatment. To detect plasma proteins associated with treatment response, we performed stratified analyses in anti-programmed cell death protein 1 (anti-PD-1) responders and non-responders. In addition, we analyzed the association between protein plasma levels and progression-free survival (PFS) by Cox proportional hazards models. Results Unbiased HiRIEF LC-MS/MS-based proteomics showed plasma levels’ alterations related to anti-PD-1 treatment in 80 out of 1160 quantified proteins. Circulating PD-1 had the highest increase during anti-PD-1 treatment (log2-FC=2.03, p=0.0008) and in anti-PD-1 responders (log2-FC=2.09, p=0.005), but did not change in the MAPKis cohort. Targeted, antibody-based proteomics by PEA confirmed this observation. Anti-PD-1 responders had an increase in plasma proteins involved in T-cell response, neutrophil degranulation, inflammation, cell adhesion, and immune suppression. Furthermore, we discovered new associations between plasma proteins (eg, interleukin 6, interleukin 10, proline-rich acidic protein 1, desmocollin 3, C-C motif chemokine ligands 2, 3 and 4, vascular endothelial growth factor A) and PFS, which may serve as predictive biomarkers. Conclusions We detected an increase in circulating PD-1 during anti-PD-1 treatment, as well as diverse immune plasma proteomic signatures in anti-PD-1 responders. This study demonstrates the potential of plasma proteomics as a liquid biopsy method and in discovery of putative predictive biomarkers for anti-PD-1 treatment in metastatic CM.

9574 Background: The introduction of immune checkpoint inhibitors (ICIs) or therapies targeting the MAPK-pathway (MAPKis) has significantly improved clinical outcomes in metastatic melanoma patients. Still, a large proportion of the patients become resistant to therapy and there is a need for treatment predictive biomarkers. The aim of this study was to analyze the treatment predictive biomarkers based on the plasma proteome of patients with metastatic melanoma treated with ICIs or MAPKis. Methods: We analyzed serial plasma samples from 48 patients with metastatic melanoma collected; 24 patients were treated with ICIs and with MAPKis, respcetively. A non-biased, high-resolution isoelectric focusing of peptides-liquid chromatography-mass spectrometry (HiRIEFLC-MS/MS)-based method, and with proximity ligation assays (PEA) targeting 92 immuno-oncology-related proteins were used.We analyzed the change in protein levels during treatment with a paired t-test, and their association with progression free survival (PFS) with Cox proportional hazards models. Results: HiRIEFLC-MS/MS detected 1,835 proteins.We detected statistically-significant log2-fold-changes in 109 protein levels out of 1,160 proteins tested (not corrected for multiple testing). PDCD-1 had the highest log2-fold change (FC = 1.27) after treatment (p = 0.02). After stratifying for treatment type, PDCD-1 levels increased in patients treated with ICIs (FC = 2.13, p= 0.0008), but not in MAPKis-treated patients. PEA analyses confirmed this observation. The PEA panel showed association between 44 proteins and shorter PFS (pcoefficient <0.05, pLRT<0.05, qLRT<0.05), among them: LGALS1, CSF1, VEGFA, CASP8, CCL2, TNFSF14, ANGPT2, IL10, IL6, and ADGRG1. Of these, increase in plasma levels during treatment of LGALS1, CCL2 and ADGRG1 were associated with longer PFS. HiRIEF LC-MS/MS detected 69 proteins associated with PFS (pcoefficient< 0.05, pLRT< 0.05, qLRT < 0.05). Conclusions: By using HiRIEFLC-MS/MS, we could detect putative treatment predictive proteins in plasma from patients with metastatic melanoma treated with ICIs or MAPKis. Our findings require further validation.