Biology subjects

Burger, R.

Publications and source records attributed to Burger, R..

3 recordsLinked to original sources

bioRxiv2025

Retargeted adenoviruses for local IgA and CD47 blocker production as a novel cancer therapy

Despite advances in IgG-based cancer immunotherapy, challenges remain in effectively engaging innate immune responses against solid tumors. Here, IgA antibodies hold promise due to their ability to activate neutrophils and macrophages. We present a novel retargeted adenovirus-mediated approach that transforms cancer cells into "biofactories" for localized production of monomeric or dimeric IgA antibodies and a CD47 blocker to potentiate the effect of IgA antibodies. With our approach tumor cells effectively produced IgA antibodies against tumor antigens such as EGFR or EpCAM and a soluble SIRP-Fc fusion protein, which blocks the CD47-SIRP axis. In a perfused tumor-on-a-chip model, locally produced IgA triggered neutrophil- and macrophage-mediated tumor cell killing, further potentiated by SIRP-Fc co-production. In FcRI-transgenic, tumor-bearing mice, intratumoral adenoviral injection induced strong local IgA and SIRP-Fc expression, immune cell infiltration, and more than 50% tumor volume reduction after a single treatment. We found that dimeric IgA exerts stronger effects than monomeric IgA, which is of particular interest since dimeric IgA necessitates a local production approach. Together, these results demonstrate that adenovirus-mediated, tumor-restricted delivery of IgA antibodies and CD47 blockade effectively engages innate immune mechanisms, providing a promising new avenue to enhance cancer immunotherapy. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=93 SRC="FIGDIR/small/686998v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@183dd88org.highwire.dtl.DTLVardef@452624org.highwire.dtl.DTLVardef@1cb10e8org.highwire.dtl.DTLVardef@c2fa85_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2025

Myeloid cell-mediated killing of B-ALL by CD38 and CD20IgA antibody variants is enhanced by CD47/SIRPα interference

Enhancing myeloid effector cell recruitment may improve immunotherapy by monoclonal antibodies - including that against acute lymphoblastic leukemia (ALL). To assess expression of target antigens in B-ALL, we compared mRNA profiling of 559 patient leukemia samples across 18 molecular subtypes with that of representative cell lines. The latter served as target cells to compare human IgG1 or IgA2 variants against CD19, CD20 or CD38 in antibody-dependent cellular phagocytosis (ADCP) by macrophages and antibody-dependent cell-mediated cytotoxicity (ADCC) by polymorphonuclear leukocytes (PMN). Interestingly, antibodies against broadly expressed CD19 were negligibly effective in mediating ADCP or ADCC. Antibodies against CD20 or CD38, the former variably expressed across subtypes, triggered ADCP by macrophages both as IgG1 and IgA2. However, PMN mediated ADCC against CD20 or CD38 was only observed with IgA2 variants, but not with respective IgG1 antibodies. Blocking the myeloid checkpoint molecule CD47 with a CD47 antibody or a soluble SIRP-Fc fusion protein enhanced ADCP and ADCC by IgA2 antibodies. The binding site for SIRP on CD47 contains an N-terminal pyroglutamate (pGlu), whose formation is catalyzed by glutaminyl-peptide cyclotransferase like (QPCTL). The direct involvement of pGlu in CD47/SIRP interactions was shown by using engineered CD47 variants. Both CD47 and QPCTL were broadly expressed across BCP-ALL subtypes, indicating QPCTL inhibitors as additional therapeutic option. Importantly, the combination of anti-CD38 IgA2 and CD47 blockade was effective against xenografted B-ALL cells in human FcRI (CD89) transgenic (tg) NXG mice. Together, these studies support the combination of anti-CD38 IgA2 with CD47 interference to improve myeloid effector cell recruitment for immunotherapy of B-ALL. Data sharing statementRNA-Seq data from BCP-ALL patients and B cells from healthy donors are available in the European Genome-Phenome Archive (EGA) accession numbers EGAS00001006107 and EGAS00001007305, respectively. Mass spectrometry data of analyzed proteins will be made available after manuscript acceptance on PRIDE - PRoteomics IDEntifications Database. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=174 HEIGHT=200 SRC="FIGDIR/small/669665v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@15220daorg.highwire.dtl.DTLVardef@eace04org.highwire.dtl.DTLVardef@17b87daorg.highwire.dtl.DTLVardef@1142822_HPS_FORMAT_FIGEXP M_FIG C_FIG Key pointsO_LIIgG1 and IgA2 antibodies against CD38 or CD20 were effective in recruiting macrophages for ADCP, but only IgA2 triggered ADCC by PMN C_LIO_LIMyeloid effector cell activation was enhanced by interfering with the CD47/SIRP axis, especially when IgA2 antibodies were applied C_LI

cancer biology↗

bioRxiv2025

EssentCell: Discovering Essential Evolutionary Relations in Noisy Single-Cell Data

Single-cell sequencing (SCS) enables investigating tumor evolution at a single cell resolution. A common type of analysis to investigate evolutionary structure from an SCS experiment is to determine a phylogenetic tree structure from the data. This problem has been well-studied under the assumption that mutations only accumulate in the evolution of cancer and there is a simple characterization of when the data is compatible with a perfect phylogeny based on the absence of a special "conflict" submatrix. SCS data can be represented as a binary matrix, where the ij-th entry indicates whether cell i has mutation j. In practice, SCS data is noisy, so a natural question is what is the minimum number of entries to flip in the data matrix, in order that the matrix becomes "conflict-free" and thus compatible with a perfect phylogeny. Furthermore, the false positive rate is orders of magnitude smaller than the false negative rate, so that at most a few false positives occur with high probability. We consider a variation of the minimum-flip problem in which the number of false positives in the solution is a parameter. Often, there can be multiple optimal solutions, so a natural question is what relations are true among all optimal solutions for a small range of possible false positives values; we call such relations essential. In this work, we propose an efficient algorithm based on integer linear programming to determine all essential relations in the data. We test our software tool, EssentCell, on several data sets and discuss the results found.

cancer biology↗