Background Cancer patients are thought to have an increased risk of developing severe Coronavirus Disease 2019 (COVID-19) infection and of dying from the disease. In this work, predictive factors for COVID-19 severity and mortality in cancer patients were investigated. Patients and Methods In this large nationwide retro-prospective cohort study, we collected data on patients with solid tumours and COVID-19 diagnosed between March 1 and June 11, 2020. The primary endpoint was all-cause mortality and COVID-19 severity, defined as admission to an intensive care unit (ICU) and/or mechanical ventilation and/or death, was one of the secondary endpoints. Results From April 4 to June 11, 2020, 1289 patients were analysed. The most frequent cancers were digestive and thoracic. Altogether, 424 (33%) patients had a severe form of COVID-19 and 370 (29%) patients died. In multivariate analysis, independent factors associated with death were male sex (odds ratio 1.73, 95%CI: 1.18-2.52), ECOG PS ≥ 2 (OR 3.23, 95%CI: 2.27-4.61), updated Charlson comorbidity index (OR 1.08, 95%CI: 1.01-1.16) and admission to ICU (OR 3.62, 95%CI 2.14-6.11). The same factors, age along with corticosteroids before COVID-19 diagnosis, and thoracic primary tumour site were independently associated with COVID-19 severity. None of the anticancer treatments administered within the previous 3 months had any effect on mortality or COVID-19 severity, except cytotoxic chemotherapy in the subgroup of patients with detectable SARS-CoV-2 by RT-PCR, which was associated with a slight increase of the risk of death (OR 1.53; 95%CI: 1.00-2.34; p = 0.05). A total of 431 (39%) patients had their systemic anticancer treatment interrupted or stopped following diagnosis of COVID-19. Conclusions Mortality and COVID-19 severity in cancer patients are high and are associated with general characteristics of patients. We found no deleterious effects of recent anticancer treatments, except for cytotoxic chemotherapy in the RT-PCR-confirmed subgroup of patients. In almost 40% of patients, the systemic anticancer therapy was interrupted or stopped after COVID-19 diagnosis.

The Chromosome-Centric Human Proteome Project (C-HPP) aims at cataloguing the proteins as gene products encoded by the human genome in a chromosome-centric manner. The existence of products of about 82% of the genes has been confirmed at the protein level. However, the number of so-called "missing proteins" remains significant. It was recently suggested that the expression of proteins that have been systematically missed might be restricted to particular organs or cell types, for example, the testis. Testicular function, and spermatogenesis in particular, is conditioned by the successive activation or repression of thousands of genes and proteins including numerous germ cell- and testis-specific products. Both the testis and postmeiotic germ cells are thus promising sites at which to search for missing proteins, and ejaculated spermatozoa are a potential source of proteins whose expression is restricted to the germ cell lineage. A trans-chromosome-based data analysis was performed to catalog missing proteins in total protein extracts from isolated human spermatozoa. We have identified and manually validated peptide matches to 89 missing proteins in human spermatozoa. In addition, we carefully validated three proteins that were scored as uncertain in the latest neXtProt release (09.19.2014). A focus was then given to the 12 missing proteins encoded on chromosomes 2 and 14, some of which may putatively play roles in ciliation and flagellum mechanistics. The expression pattern of C2orf57 and TEX37 was confirmed in the adult testis by immunohistochemistry. On the basis of transcript expression during human spermatogenesis, we further consider the potential for discovering additional missing proteins in the testicular postmeiotic germ cell lineage and in ejaculated spermatozoa. This project was conducted as part of the C-HPP initiatives on chromosomes 14 (France) and 2 (Switzerland). The mass spectrometry proteomics data have been deposited with the ProteomeXchange Consortium under the data set identifier PXD002367.

BackgroundIn environmental sequencing studies, fungi can be identified based on nucleic acid sequences, using either highly variable sequences as species barcodes or conserved sequences containing a high-quality phylogenetic signal. For the latter, identification relies on phylogenetic analyses and the adoption of the phylogenetic species concept.Such analysis requires that the reference sequences are well identified and deposited in public-access databases. However, many entries in the public sequence databases are problematic in terms of quality and reliability and these data require screening to ensure correct phylogenetic interpretation.Methods and Principal FindingsTo facilitate phylogenetic inferences and phylogenetic assignment, we introduce a fungal sequence database. The database PHYMYCO-DB comprises fungal sequences from GenBank that have been filtered to satisfy stringent sequence quality criteria. For the first release, two widely used molecular taxonomic markers were chosen: the nuclear SSU rRNA and EF1-α gene sequences. Following the automatic extraction and filtration, a manual curation is performed to remove problematic sequences while preserving relevant sequences useful for phylogenetic studies. As a result of curation, ∼20% of the automatically filtered sequences have been removed from the database. To demonstrate how PHYMYCO-DB can be employed, we test a set of environmental Chytridiomycota sequences obtained from deep sea samples.ConclusionPHYMYCO-DB offers the tools necessary to: (i) extract high quality fungal sequences for each of the 5 fungal phyla, at all taxonomic levels, (ii) extract already performed alignments, to act as ‘reference alignments’, (iii) launch alignments of personal sequences along with stored data. A total of 9120 SSU rRNA and 672 EF1-α high-quality fungal sequences are now available.The PHYMYCO-DB is accessible through the URL http://phymycodb.genouest.org/.