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Teodosio, C.

Publications and source records attributed to Teodosio, C..

3 recordsLinked to original sources

Targeted KRAS(G12V) degradation elicits efficient and durable lung adenocarcinoma regression in vivo

Recent drug discovery breakthroughs led to the approval of KRASG12C inhibitors in lung adenocarcinoma (LUAD). Unfortunately, clinical responses remain limited due to rapid resistance onset. Proteolysis-targeting chimeras (PROTACs) have emerged as promising alternatives to traditional inhibition. However, there is limited mechanistic understanding of KRAS degradation in vivo. Here, we developed a preclinical LUAD mouse model and demonstrated that targeted oncogenic KRAS degradation induces rapid tumor regression. Transcriptional, histological, and immunophenotypic analyses revealed a substantial remodeling of the tumor microenvironment. Notably, disease relapse observed during long-term degrader treatment stems from proteolysis machinery dysregulation, indicating resistance mechanisms distinct from those reported upon KRAS inhibition. Our findings highlight the therapeutic potential of KRAS degradation in LUAD, offering insights into cell-intrinsic and extrinsic mechanisms driving durable antitumor responses and supporting further clinical exploration. SIGNIFICANCEGiven the short duration of the clinical responses to KRAS inhibitors, complementary therapies are a dire medical need. Our preclinical findings endorse KRAS degradation as a therapeutic alternative in LUAD, where cell-intrinsic and extrinsic mechanisms drive tumor regression and durable therapeutic responses.

cancer biology↗

Single-cell immune profiling reveals novel thymus-seeding populations, T cell commitment, and multi-lineage development in the human thymus

T cell development in the mouse thymus has been studied rather extensively; in contrast, strikingly little is known regarding T cell development in the human thymus. To close this knowledge gap, we used a combination of single-cell techniques and functional assays to perform deep immune profiling of human T cell development, focusing on the initial stages of pre-lineage commitment. We identified three thymus-seeding progenitor populations that also have counterparts in the bone marrow. In addition, we found that the human thymus physiologically supports the development of monocytes, dendritic cells, and NK cells, as well as limited development of B cells. These results are an important step towards monitoring and guiding regenerative therapies in patients following hematopoietic stem cell transplantation.

immunology↗

Population matched (PM) germline allelic variants of immunoglobulin (IG) loci: New pmIG database to better understand IG repertoire and selection processes in disease and vaccination

At the population level, immunoglobulin (IG) loci harbor inter-individual allelic variants in the many different germline IG variable (V), Diversity (D) and Joining (J) genes of the IG heavy (IGH), IG kappa (IGK) and IG lambda (IGL) loci, which together form the genetic basis of the highly diverse antigen-specific B-cell receptors. These inter-individual allelic variants can be shared between or be specific to human populations. The current IG databases IMGT, VBASE2 and IgPdb hold information about germline alleles, most of which are partial sequences, obtained from a mixture of human (B-cell) samples, many with sequence errors and/or acquired (non-germline) IG variations, induced by somatic hypermutation (SHM) during antigen-specific B-cell responses. We systematically identified true germline alleles (without SHM) from 26 different human populations around the world, profiled by the "1000 Genomes data". Our resource is uniquely enriched with complete IG allele sequences and their frequencies across human populations. We identified 409 IGHV, 179 IGKV, and 199 IGLV germline alleles supported by at least seven haplotypes (= minimum of four individuals), after removal of potential false-positives, based on using other genomic databases, i.e. ENSEMBL, TopMed, ExAC, ProjectMine. Remarkably, the positions of the identified variant nucleotides of the different alleles are not at random (as observed in case of SHM), but show striking patterns, restricted to limited nucleotide positions, the same as found in other IG data bases, suggesting over-time evolutionary selection processes. The identification of these specific patterns provides extra evidence that the identified variant nucleotides are not sequencing errors, but genuine allelic variants. The diversity of germline allelic variants in IGH and IGL loci is the highest in Africans, while the IGK locus is most diverse in Europeans. We also report on the presence of recombination signal sequences (RSS) in V pseudogenes, explaining their usage in V(D)J rearrangements. We propose that this new set of genuine germline IG sequences can serve as a new population-matched IG (pmIG) database for better understanding B-cell repertoire and B-cell receptor selection processes in disease and vaccination within and between different human populations. The database in format of fasta is available via GitHub (https://github.com/InduKhatri/pmIG). Contribution to the Field StatementWe present a catalogue of immunoglobulin (IG) germline-alleles of unprecedented completeness and accuracy from 26 different human populations belonging to five different large ethnicities (Source: 1000 Genomes). We identified the population distribution of several known germline alleles and identified multiple new alleles, especially in African populations, indicative of high allelic diversity of IG genes in Africa. Strikingly, the identified variant nucleotides of the different alleles are not at random, but show striking patterns, restricted to limited nucleotide positions, the same as found in other IG databases, suggesting over-time evolutionary selection processes. Furthermore, we identified recombination signal sequences in pseudogenes (previously not known). We provide an overview of IG germline alleles shared with and between known databases and also point to potential sources of non-germline variation and incompleteness of the existing IG databases. More importantly, we believe that this information can serve as a novel population-matched IG (pmIG) database, highly valuable for the research community in supporting the dissection and understanding of differences in effectiveness of antibody-based immune responses in infectious diseases, other (immune) diseases and vaccination within and between human populations. Such knowledge might be used in developing population-specific vaccination strategies e.g. for currently ongoing SARS-CoV2 pandemic.

immunology↗