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Biology subjects

Kalxdorf, M.

Publications and source records attributed to Kalxdorf, M..

5 recordsLinked to original sources

CRISPR screens establish regulatory maps of immunosuppressive surface molecules in cancer

Cancer cells can evade immune surveillance by triggering inhibitory checkpoint responses in tumor-associated T cells through the expression of immunosuppressive surface molecules. While therapeutic blockade of such receptors has emerged as a pillar of cancer therapy, tumor cell-intrinsic mechanisms controlling their expression remain incompletely understood. Fluorescence-activated cell sorting (FACS)-based genetic screens can be used to decipher regulatory pathways, but conventional screening approaches are biased towards regulators that are dispensable for cancer cell proliferation and survival. Here, we used a tetracycline-inducible Cas9 system enabling fully time-controllable CRISPR-based mutagenesis to gain a more comprehensive and comparative survey of regulators controlling the expression of four major immunosuppressive surface molecules, PD-L1 (CD274), CD47, CD276 and HLA-E, as well as CD151, a candidate surface target associated with tumor growth and invasion. As a prominent hit, our screens identify the membrane-trafficking factor DNAJC13 as a regulator of PD-L1 and CD276. Among DNAJC13-controlled surface proteins, we identify other known and proposed immune-checkpoint molecules. Based on this function, suppression of DNAJC13 strongly increases the sensitivity of human cancer cells to T-cell attack in vitro and prolongs survival of mice bearing pancreatic tumors. Together, our study establishes regulatory maps of major immune-modulatory surface molecules and identifies DNAJC13 as a potential target for the coordinated inhibition of multiple immunosuppressive signals.

molecular biology↗

Pharmacoproteomic profiling identifies secreted markers for aberrant drug action

Adverse drug reactions (ADRs) contribute significantly to late-stage attrition in drug discovery due to their unpredictability and enigmatic underlying mechanisms. Here we applied mass spectrometry-based proteomics to assess the effects of 46 approved or retracted drugs with various levels of concerns for drug-induced liver injury and annotated for mitochondrial mechanisms, along with 8 tool compounds, on the secretome of a hepatocyte liver model. We observed distinct clusters of non-canonical secretion, and intracellular thermal proteome profiling linked dysregulated mechanisms to extracellular markers. Functional follow-up confirmed lysosomal alterations by cationic-amphiphilic drugs, connected damage of the respiratory chain to Rab7-dependent secretion of mitochondrial proteins, and linked drug-induced endoplasmic reticulum stress to reduced basal secretion. Perturbation of sphingolipid biosynthesis pathways specifically induced secretion of the cargo sorting protein SDF4 whilst suppressing secretion of its cargo proteins. Thermal stability changes of clusters of membrane proteins in distinct subcellular compartments suggest local accumulation as important driver for unexpected drug effects through direct and indirect interactions.

pharmacology and toxicology↗

IceR improves proteome coverage and data completeness in global and single-cell proteomics

Label-free proteomics by data-dependent acquisition (DDA) enables the unbiased quantification of thousands of proteins, however it notoriously suffers from high rates of missing values, thus prohibiting consistent protein quantification across large sample cohorts. To solve this, we here present IceR, an efficient and user-friendly quantification workflow that combines high identification rates of DDA with low missing value rates similar to DIA. Specifically, IceR uses ion current information in DDA data for a hybrid peptide identification propagation (PIP) approach with superior quantification precision, accuracy, reliability and data completeness compared to other quantitative workflows. We demonstrate greatly improved quantification sensitivity on published plasma and single-cell proteomics data, enhancing the number of reliably quantified proteins, improving discriminability between single-cell populations, and allowing reconstruction of a developmental trajectory. IceR will be useful to improve performance of large scale global as well as low-input proteomics applications, facilitated by its availability as an easy-to-use R-package.

bioinformatics↗

Automated sample preparation with SP3 for low-input clinical proteomics

High-throughput and streamlined workflows are essential in clinical proteomics for standardized processing of samples originating from a variety of sources, including fresh frozen tissue, FFPE tissue, or blood. To reach this goal, we have implemented single-pot solid-phase-enhanced sample preparation (SP3) on a liquid handling robot for automated processing (autoSP3) of tissue lysates in a 96-well format, performing unbiased protein purification and digestion, and delivering peptides that can be directly analyzed by LCMS. AutoSP3 eliminates hands-on time and minimizes the risk of error, reduces variability in protein quantification and improves longitudinal performance and reproducibility. We demonstrate the distinguishing ability of autoSP3 to process low-input samples, reproducibly quantifying 500-1000 proteins from 100-1000 cells (<100 ng protein). Furthermore, we applied this approach to a cohort of clinical FFPE pulmonary adenocarcinoma (ADC) samples, and recapitulate their separation into known histological growth patterns based on proteome profiles. Collectively, autoSP3 provides a generic, scalable, and cost-effective pipeline for routine and standardized proteomic sample processing that should enable reproducible proteomics in a broad range of clinical and non-clinical applications.

molecular biology↗

Proteome thermal stability reflects organ physiology and identifies drug-target engagement in vivo

Studying biological processes at a molecular level and monitoring drug-target interactions is established for simple cell systems but challenging in vivo. We introduce and apply a methodology for proteome-wide thermal stability measurements to characterize organ physiology and activity of many fundamental biological processes across tissues, such as energy metabolism and protein homeostasis. This method, termed tissue thermal proteome profiling (tissue-TPP), also enabled target and off-target identification and occupancy measurements in tissues derived from animals dosed with the non-covalent histone deacetylase inhibitor, panobinostat. Finally, we devised blood-CETSA, a thermal stability-based method to monitor target engagement in whole blood. Our study generates the first proteome-wide map of protein thermal stability in tissue and provides tools that will be of great impact for translational research.

cell biology↗