Biology subjects

Astaburuaga-Garcia, R.

Publications and source records attributed to Astaburuaga-Garcia, R..

3 recordsLinked to original sources

bioRxiv2024

Rewired type I IFN signaling is linked to age-dependent differences in COVID-19

Advanced age is the most important risk factor for severe disease or death from COVID-19, but a thorough mechanistic understanding of the molecular and cellular underpinnings is lacking. Multi-omics analysis of samples from SARS-CoV-2 infected persons aged 1 to 84 years, revealed a rewiring of type I interferon (IFN) signaling with a gradual shift from signal transducer and activator of transcription 1 (STAT1) to STAT3 activation in monocytes, CD4+ T cells and B cells with increasing age. Diversion of interferon IFN signaling was associated with increased expression of inflammatory markers, enhanced release of inflammatory cytokines, and delayed contraction of infection-induced CD4+ T cells. A shift from IFN-responsive germinal center B (GCB) cells towards CD69high GCB and atypical B cells corresponded to the formation of IgA in children while complement fixing IgG was dominant in adults. Our data provide a mechanistic basis for inflammation-prone responses to infections and associated pathology during aging. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=144 SRC="FIGDIR/small/619479v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@723896org.highwire.dtl.DTLVardef@e12b2aorg.highwire.dtl.DTLVardef@d8de22org.highwire.dtl.DTLVardef@1df96ec_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2024

Reporter-based screening identifies RAS-RAF stabilizing mutations as drivers of resistance to broad-spectrum RAS inhibition in colorectal cancer

Therapy-induced acquired resistance limits the clinical effectiveness of mutation-specific RAS inhibitors in colorectal cancer. It is unknown whether broad-spectrum active-state RAS inhibitors meet similar limitations. Here, we identify and categorize mechanisms of resistance to the broad-spectrum active-state RAS inhibitor RMC-7977 in colorectal cancer cell lines. We found that KRAS-mutant colorectal cancer cell lines are universally sensitive to RMC-7977, inhibiting the RAS-RAF-MEK-ERK axis, halting proliferation and in some cases inducing apoptosis. To monitor KRAS downstream effector pathway activity, we developed a compartment-specific dual-color ERK activity reporter. RMC-7977 treatment reduced reporter activity. However, long-term dose escalation with RMC-7977 revealed multiple patterns of reporter reactivation in emerging resistant cell populations that correlated with phosphorylation states of compartment-specific ERK targets. Cells sorted for high, low, or cytoplasmic reporter activity exhibited distinct patterns of genomic mutations, phospho-protein, and transcriptional activities. Notably, all resistant subpopulations showed dynamic ERK regulation in the presence of the RAS inhibitor, unlike the parental sensitive cell lines. High levels of RAS downstream activities were observed in cells characterized by a KRAS Y71H resistance mutation. In contrast, RAS inhibitor-resistant populations with low, or cytoplasmic ERK reporter reactivation displayed different genetic alterations, among them RAF1 S257L and S259P mutations. Colorectal cancer cells resistant to RMC-7977 and harboring the RAF1 mutation specifically exhibited synergistic sensitivity to concurrent RAS and RAF inhibition. Our findings endorse reporter-assisted screening together with single-cell analyses as a powerful approach for dissecting the complex landscape of therapy resistance. The strategy offers opportunities to develop clinically relevant combinatorial treatments to counteract emergence of resistant cancer cells.

cancer biology↗

bioRxiv2024

RUCova: Removal of Unwanted Covariance in mass cytometry data

High dimensional mass cytometry is confounded by unwanted covariance due to variations in cell size and staining efficiency, making analysis and interpretation challenging. We present RUCova, a novel method designed to address confounding factors in mass cytometry data. RUCova removes unwanted covariance using multivariate linear regression on Surrogates of Unwanted Covariance (SUCs), and Principal Component Analysis (PCA). We exemplify the use of RUCova and show that it effectively removes unwanted covariance while preserving genuine biological signals. Our results demonstrate the efficacy of RUCova in elucidating complex data patterns, facilitating the identification of activated signalling pathways, and improving the classification of important cell populations. By providing a robust framework for data normalization and interpretation, RUCova enhances the accuracy and reliability of mass cytometry analyses, contributing to advancements in our understanding of cellular biology and disease mechanisms. The R package is available on https://github.com/molsysbio/RUCova. Detailed documentation, data, and the code required to reproduce the results are available on https://doi.org/10.5281/zenodo.10913464. Supplementary material: Available at bioRxiv.

bioinformatics↗