Suchergebnisse

Funding Information: The authors thank Dr. Pirkko M Mattila, Dr. Jenni Lahtela and Bhiswa Ghimire for their valuable suggestions on how to improve the web-tool, Olle Hansson for the FIMM cluster server machine to host the web-tool and the database, and all the beta-testers for confirming the smooth operation and reproducibility of the analyses. This work was supported by the Academy of Finland (grants 295504, 310507, 326238, 340141 and 344698 to TA), European Union's Horizon 2020 Research and Innovation Programme (ERA PerMed JAKSTAT-TARGET), the Cancer Society of Finland (TA), the Sigrid Jusélius Foundation (TA), and the Norwegian Cancer Society (grant 216104 to TA). Publisher Copyright: © 2022, The Author(s). ; Identification of cell populations often relies on manual annotation of cell clusters using established marker genes. However, the selection of marker genes is a time-consuming process that may lead to sub-optimal annotations as the markers must be informative of both the individual cell clusters and various cell types present in the sample. Here, we developed a computational platform, ScType, which enables a fully-automated and ultra-fast cell-type identification based solely on a given scRNA-seq data, along with a comprehensive cell marker database as background information. Using six scRNA-seq datasets from various human and mouse tissues, we show how ScType provides unbiased and accurate cell type annotations by guaranteeing the specificity of positive and negative marker genes across cell clusters and cell types. We also demonstrate how ScType distinguishes between healthy and malignant cell populations, based on single-cell calling of single-nucleotide variants, making it a versatile tool for anticancerapplications. The widely applicable method is deployed both as an interactive web-tool (https://sctype.app), and as an open-source R-package. ; Peer reviewed

Funding Information: Academy of Finland [292611, 310507, 313267, 326238 to T.A.]; Cancer Society of Finland [to T.A.]; Sigrid Jus?lius Foundation [to TA]. Funding for open access charge: European Union's Horizon 2020 Research and Innovation Programme [ERA PerMed JAKSTAT-TARGET project]. Funding Information: Academy of Finland [292611, 310507, 313267, 326238 to T.A.]; Cancer Society of Finland [to T.A.]; Sigrid Jusélius Foundation [to TA]. Funding for open access charge: European Union's Horizon 2020 Research and Innovation Programme [ERA PerMed JAKSTAT-TARGET project]. Conflict of interest statement. None declared. Publisher Copyright: © The Author(s) 2020. ; SynergyFinder (https://synergyfinder.fimm.fi) is a stand-alone web-application for interactive analysis and visualization of drug combination screening data. Since its first release in 2017, SynergyFinder has become a widely used web-tool both for the discovery of novel synergistic drug combinations in pre-clinical model systems (e.g. cell lines or primary patient-derived cells), and for better understanding of mechanisms of combination treatment efficacy or resistance. Here, we describe the latest version of SynergyFinder (release 2.0), which has extensively been upgraded through the addition of novel features supporting especially higher-order combination data analytics and exploratory visualization of multi-drug synergy patterns, along with automated outlier detection procedure, extended curve-fitting functionality and statistical analysis of replicate measurements. A number of additional improvements were also implemented based on the user requests, including new visualization and export options, updated user interface, as well as enhanced stability and performance of the web-tool. With these improvements, SynergyFinder 2.0 is expected to greatly extend its potential applications in various areas of multi-drug combinatorial screening and precision medicine. ; Peer reviewed

Funding Information: Conflict of interest SM has received honoraria and research funding from Novartis, Pfizer and Bristol-Myers Squibb (not related to this study). SAA has received research funding from Incyte. SB is a member of Member of the advisory board of Qiagen, Novartis, and Cepheid and has received research funding from Novartis, honoraria from Novartis, Qiagen, Cepheid, and Bristol-Myers Squibb and support from the National Health and Medical Research Council of Australia APP1117718 and APP1104425, the Ray and Shirl Norman Cancer Research Trust, and the Royal Adelaide Hospital Research Foundation. The other authors declare that they have no conflict of interest. Funding Information: Funding This work was supported by Academy of Finland (Grant No. 292605 and 287224), the Finnish Funding Agency for Innovation (Dnro 6113/31/2016), Finnish special governmental subsidy for health sciences, research and training, Signe and Ane Gyllenberg Foundation, Finnish Cultural Foundation, Nordic Cancer Union, Helsinki Institute of Life Science, Cancer Foundation Finland, Relander Foundation, Incyte Nordic Hematology grant, and Finnish Cancer Institute. Publisher Copyright: © 2020, The Author(s). ; Blast-phase chronic myeloid leukemia (BP-CML) is associated with additional chromosomal aberrations, RUNX1 mutations being one of the most common. Tyrosine kinase inhibitor therapy has only limited efficacy in BP-CML, and characterization of more defined molecular subtypes is warranted in order to design better treatment modalities for this poor prognosis patient group. Using whole-exome and RNA sequencing we demonstrate that PHF6 and BCORL1 mutations, IKZF1 deletions, and AID/RAG-mediated rearrangements are enriched in RUNX1mut BP-CML leading to typical mutational signature. On transcriptional level interferon and TNF signaling were deregulated in primary RUNX1mut CML cells and stem cell and B-lymphoid factors upregulated giving a rise to distinct phenotype. This was accompanied with the sensitivity of RUNX1mut blasts to CD19-CAR T cells in ex vivo assays. High-throughput drug sensitivity and resistance testing revealed leukemia cells from RUNX1mut patients to be highly responsive for mTOR-, BCL2-, and VEGFRinhibitors and glucocorticoids. These findings were further investigated and confirmed in CRISPR/Cas9-edited homozygous RUNX1−/− and heterozygous RUNX1−/mut BCR-ABL positive cell lines. Overall, our study provides insights into the pathogenic role of RUNX1 mutations and highlights personalized targeted therapy and CAR T-cell immunotherapy as potentially promising strategies for treating RUNX1mut BP-CML patients. ; Peer reviewed

Abstract
Immunocompromised patients often fail to raise protective vaccine-induced immunity against the global emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants. Although monoclonal antibodies have been authorized for clinical use, most have lost their ability to potently neutralize the evolving Omicron subvariants. Thus, there is an urgent need for treatment strategies that can provide protection against these and emerging SARS-CoV-2 variants to prevent the development of severe coronavirus disease 2019. Here, we report on the design and characterization of a long-acting viral entry-blocking angiotensin-converting enzyme 2 (ACE2) dimeric fusion molecule. Specifically, a soluble truncated human dimeric ACE2 variant, engineered for improved binding to the receptor-binding domain of SARS-CoV-2, was fused with human albumin tailored for favorable engagement of the neonatal fragment crystallizable receptor (FcRn), which resulted in enhanced plasma half-life and allowed for needle-free transmucosal delivery upon nasal administration in human FcRn-expressing transgenic mice. Importantly, the dimeric ACE2-fused albumin demonstrated potent neutralization of SARS-CoV-2 immune escape variants.