August Selected literature from CNS journals
1 ▏Nature Medicine
The proteogenomic landscape of the human kidney and its implications for cardiovascular-kidney-metabolic health
A plasma proteomics-based candidate biomarker panel predicts amyotrophic lateral sclerosis
High-throughput proteomics-based unbiased panoramic mapping ofnovelCereblon substrates
Super-resolution proximity labeling with isotope-coded probes resolves the spatial proteome of the mitochondrial intracristal space
Mapping early human blood cell differentiation with single-cell proteomics and transcriptomics
Spatial proteomic–transcriptomic analysis reveals the molecular landscape of ovarian borderline tumors and their invasive progression
An AR-to-GR switch differentially regulates TDO2–Kyn–AhR signaling to promote survival and recurrence of therapy-induced dormant prostate cancer cells
The proteogenomic landscape of the human kidney and its implications for cardiovascular-kidney-metabolic health
The proteogenomic landscape of the human kidney and implications for cardio-kidney-metabolic health
Close to one-third of the world's population is affected by cardiovascular-kidney-metabolic (CKM) disease, yet its molecular mechanisms remain poorly understood. A team led by Katalin Susztak at the University of Pennsylvania performed whole-genome sequencing, RNA sequencing and proteomic analysis on 337 human kidney samples, finding that tissue proteomics provides critical information that neither tissue gene expression nor blood proteomics can capture, and establishing a publicly available database. By combining Bayesian colocalization and Mendelian randomization analysis of kidney protein quantitative trait loci with 36 CKM genome-wide association studies, the researchers prioritized 89 proteins associated with CKM traits, revealed the interconnections between different CKM traits, and identified several potential targetable mechanisms. These include the potential role of renal angiopoietin-like protein 3 (ANGPTL3) in blood lipid levels and kidney function, and the role of charged multivesicular body protein 1A in kidney function and hypertension. Notably, the study pinpointed pathways at which evidence from genetic loci, tissue gene expression and protein levels converges. Through large-scale kidney proteomics, it highlights prioritized proteins and targetable mechanisms for CKM disease.▼
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A plasma proteomics-based candidate biomarker panel predicts amyotrophic lateral sclerosis
A plasma proteomics-based candidate biomarker panel predictive of amyotrophic lateral sclerosis
Identifying reliable biomarkers for amyotrophic lateral sclerosis (ALS) is crucial for clinical practice. A team led by Bryan J. Traynor at the US National Institutes of Health used the Olink Explore 3072 platform to explore plasma proteomics as a biomarker tool for this neurodegenerative disease. The study found 33 proteins differentially expressed in the plasma of ALS patients (n=183) compared with controls (n=309). The results were validated in an independent cohort (48 ALS patients and 75 controls), and a machine-learning diagnostic model showed very high accuracy (area under the curve of 98.3%). By analyzing plasma samples collected before ALS symptoms appeared, the team estimated the age of clinical onset and confirmed that disease processes affecting skeletal muscle, nerves and energy metabolism begin years before symptoms emerge. The study suggests that plasma proteins can serve as biomarkers for this fatal disease and provides a molecular interpretation of its prodromal phase.
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High-throughput proteomics-based unbiased panoramic mapping of novel Cereblon substrates
Unbiased mapping of cereblon neosubstrate landscape by high-throughput proteomics
Molecular glue degraders (MGDs) are small molecules that harness the ubiquitin–proteasome system to induce the degradation of target proteins, including traditionally undruggable ones. Their discovery remains challenging, as rational design strategies are lacking and unbiased whole-proteome screening methods offer limited throughput. A multicenter team including the University of Tennessee developed a high-throughput proteomics platform based on label-free data-independent acquisition mass spectrometry (DIA-MS), enabling integrated proteome and ubiquitinome analysis. Using this platform to screen 100 diverse cereblon (CRBN)-targeting ligands, the team identified large numbers of novel degraders and neosubstrates. Global proteomics-guided hit validation and structure–activity relationship analysis revealed highly selective and potent degraders based on phenyl glutarimide that target previously uncharacterized neosubstrates including KDM4B, G3BP2 and VCL — none of which contain the canonical CRBN β-hairpin degron. These findings highlight the power of unbiased high-throughput proteomics in MGD drug discovery and reveal a CRBN neosubstrate repertoire far broader than that defined by classical immunomodulatory imide drugs (IMiDs).▼
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Super-resolution proximity labeling with isotope-coded probes resolves the spatial proteome of the mitochondrial intracristal space
Intracristal space proteome mapping using super-resolution proximity labeling with isotope-coded probes
Proximity labeling with engineered ascorbate peroxidase (APEX) has been widely used to study the proteomes of membrane-enclosed subcellular organelles. Constructing protein distribution maps between two non-partitioned adjacent spaces, however, remains a challenge for existing proximity labeling tools. A team led by Hyun-Woo Rhee at Seoul National University, together with Jung-Min Kee at the Ulsan National Institute of Science and Technology, introduced an APEX labeling method based on isotope-coded phenol probes (ICAX), which enables quantitative analysis, at nanometer resolution, of the spatial proteomes labeled by two APEX enzymes localized to different positions. Using this technique, they resolved the spatial proteome of the mitochondrial intracristal space (ICS) — a region with no physical separation from the mitochondrial periphery. ICAX analysis further revealed unexpectedly dynamic changes in the mitochondrial spatial proteome under MICOS complex inhibition and under mitochondrial uncoupling. Together, these findings underscore the importance of the ICS for mitochondrial quality control under dynamic stress conditions.
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Mapping early human blood cell differentiation with single-cell proteomics and transcriptomics
Mapping early human blood cell differentiation using single-cell proteomics and transcriptomics
Single-cell transcriptomics (scRNA-seq) has greatly advanced the resolution of cell-state heterogeneity and the reconstruction of differentiation trajectories. Relying solely on mRNA measurements, however, may miss important biological information. A team led by Bo T. Porse at the University of Copenhagen used recent advances in single-cell proteomics by mass spectrometry (scp-MS) to build an scp-MS dataset of the in vivo differentiation hierarchy covering more than 2,500 human CD34+ hematopoietic stem and progenitor cells. Integrating this with scRNA-seq data, they identified proteins that are critical for stem cell function but cannot be inferred from mRNA transcripts. In addition, the study showed that modeling translation kinetics can infer cell progression during differentiation and explains mRNA–protein variance better than linear correlation. This work provides a methodological framework for single-cell multi-omics across biological systems.
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Spatial proteomic–transcriptomic analysis reveals the molecular landscape of ovarian borderline tumors and their invasive progression
Spatial proteo-transcriptomic profiling reveals the molecular landscape of borderline ovarian tumors and their invasive progression
Ovarian serous borderline tumors (SBTs) are non-invasive ovarian lesions that may progress into chemotherapy-resistant low-grade serous carcinoma (LGSC). Although genetic alterations suggest the two share an origin, the mechanism by which SBT transforms into LGSC remains unclear. A team led by Professor Ernst Lengyel at the University of Chicago, working with Professor Matthias Mann's team at the Max Planck Institute, integrated cell-type-resolved spatial proteomics and transcriptomics to systematically dissect the evolution of SBT into LGSC and its metastases within the tumor microenvironment, including both stromal and tumor regions. This transition occurs within the epithelial compartment through an intermediate stage with micropapillary features, accompanied by LGSC overexpression of c-Met and multiple brain-specific proteins. Within the tumor microenvironment, interaction networks between cancer cells and stromal cells, together with enzymes that degrade the dense extracellular matrix, point to functional cooperation among multiple cell types. Sixteen drug targets identified through spatial multi-omics were functionally validated; among them, the CDK4/6 inhibitor milciclib combined with the FOLR1-targeting agent mirvetuximab produced marked tumor regression in vivo, offering a potential therapeutic strategy for LGSC.
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An AR-to-GR switch differentially regulates TDO2–Kyn–AhR signaling to promote survival and recurrence of therapy-induced dormant prostate cancer cells
AR to GR switch modulates differential TDO2-Kyn-AhR signalling to promote the survival and recurrence of treatment-induced dormant cells in prostate cancer
Cancer cells can be driven into a dormant state by certain therapies, only to reactivate later as drug-resistant cells and cause relapse. Although the therapy-induced dormancy-to-reactivation switch is a key step in tumor dissemination and recurrence, its underlying molecular mechanisms — particularly the metabolic basis — remain poorly understood. A team led by Yan Chang at Anhui Medical University, together with Hailiang Hu's team at the Southern University of Science and Technology, demonstrated that the tryptophan-catabolizing tryptophan 2,3-dioxygenase (TDO2)–kynurenine (Kyn)–aryl hydrocarbon receptor (AhR) signaling axis both sustains the survival of prostate cancer cells driven into dormancy by androgen deprivation therapy (ADT) and promotes the reactivation and recurrent growth of dormant cells, thereby driving therapeutic resistance by permitting the dormancy-to-reactivation switch. Mechanistically, ADT upregulates TDO2, increases Kyn production and activates AhR, sustaining the survival of dormant cells. At the same time, a transcription factor switch from the androgen receptor (AR) to the glucocorticoid receptor (GR) further drives persistent TDO2 expression and, through the same TDO2–Kyn–AhR axis, promotes the reactivation of dormant cells. Notably, pharmacological inhibition of TDO2 or AhR signaling delayed tumor recurrence after ADT. The study describes a tryptophan-metabolism-mediated signaling circuit that regulates tumor cell dormancy and recurrence, and proposes TDO2 as a new target for combination therapy with ADT in patients with androgen-sensitive prostate cancer.▼
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