Mann Lab

Mann Lab

@mannlab.bsky.social

The Mann Lab is a pioneer in mass spectrometry-based proteomics. Posts represent personal views from lab members and Matthias Mann

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2/3: ~8,000 proteins per tumour. The 4 states cut across histology and stratify survival more sharply, a 5-protein classifier reproduces them, and each state shows distinct candidate vulnerabilities. A foundation for proteome-informed precision therapy.

3/3: Great collaboration across clinic and lab with Rainer Claus & Michaela Kuhlen (Universitätsklinikum Augsburg), Antje Redlich (Universitätsmedizin Magdeburg), the German MET Registry & co-authors in Giessen, Kiel, Bonn & Munich.

SPARCS: Deep Visual Proteomics-style laser microdissection meets genome-wide CRISPR screening. Find genes behind how cells look, isolate them, profile them by mass spec. Now in @cellpress.bsky.social 🎉 Congrats to @sophia-maedler.bsky.social and @nik-as.bsky.social, and all co-authors!!

Gene Center Munich @LMU Munich@genecenter-lmu.bsky.social

📢Amazing publication from the @v-hornung.bsky.social lab, in collaboration with @mannlab.bsky.social and @fabiantheis.bsky.social! They introduce SPARCS, a technology that uses AI to connect genetic perturbations with complex cellular features doi.org/10.1016/j.ce... @nik-as.bsky.social

That's a wrap on #HUPO2026 Singapore! 🎉 Congrats to Katherine Madden (🥇 Poster Competition), Elena Kratz (runner-up) & Kathrin Korff (Thesis Competition runner-up). And to alumni Jesper Olsen, Akhilesh Pandey & Florian Rosenberger, & to Judith Steen, on their HUPO awards! 👏

New preprint: with ADAPT-MS, discovery plasma proteomics becomes a diagnostic tool for ovarian cancer. We separate benign from malignant adnexal masses and generalize to 5 validation cohorts. Collaboration with @lengyel-ovca-lab.bsky.social www.medrxiv.org/content/10.6...

medrxiv.orgDifferentiating benign from malignant adnexal masses by biomarker-agnostic plasma proteomics using adaptive machine learningBackground: Pre-operative triage of adnexal masses with serum CA-125, HE4, and ultrasound (O-RADS) has limited accuracy, contributing to unnecessary surgery. We develop and validate a first of its kind, biomarker panel-free plasma proteomic classifier that distinguishes malignant from benign adnexal masses from a single blood draw, operating directly on discovery-mode mass spectrometry. Methods: In this multicenter prospective observational study, plasma from women with adnexal masses and from healthy controls at a large urban academic center (discovery and four validation cohorts) and an external academic center from another Urban-suburban area (external validation) was analyzed by data-independent-acquisition mass spectrometry (Orbitrap Astral), quantifying >1,000 proteins per sample. Cancerous (malignant, borderline adnexal mass, or metastasis to ovary) versus benign adnexal masses were classified with ADAPT-MS (Adaptive Diagnostic Architecture for Personalized Testing by Mass Spectrometry), which retrains an ElasticNet model for each sample based on the proteins measured. The primary outcome was discrimination (area under the receiver operating characteristic curve [AUC]). Pre-operative O-RADS scores and serum CA-125 were compared and combined with proteomics on matched subsets. Findings: Using a discovery cohort (n=1062), an ADAPT-MS classifier, validated across five independent cohorts (n=623), achieved a summary AUC of 0.835 (cohort range 0.779-0.904). Among patients with pre-operative O-RADS (n=231), proteomics (AUC 0.852) was comparable to O-RADS alone (0.863) and combining them raised discrimination to 0.922. Proteomics outperformed serum CA-125 (0.915 versus 0.777; n=125) and proteome-derived ROMA-like and two-marker surrogates. Biologically, the classification-relevant proteins are enriched for host response proteins rather than tumor cell associated protein changes, comprising ECM remodeling, complement and innate immune response pathways. This explains good detection of tumor with heterogenous pathology and also metastasis to ovary. Interpretation: A single plasma proteomic measurement interpreted using adaptive machine learning discriminates malignant from benign adnexal masses with good internal and external validation, and is complementary to ultrasound, warranting prospective evaluation as a panel-free diagnostic adjunct to imaging. ### Competing Interest Statement MM is an investor in Evosep. All other authors declare no competing interests. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The study was approved by the Institutional Review Board at The University of Chicago and Roswell Park Cancer Institute, and informed written consent was obtained from all women participating in the study. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors. Max Planck Society for the Advancement of Sciences NIH R35 grant Arthur and Nicole Herbst

At #HUPO2026? Come say hi to some of our @mannlab.bsky.social teammates👋 — talks & posters all week on spatial proteomics, plasma biomarkers, a human cell-type proteome atlas, interactomics & AI-driven peptide sequencing. Plenary by Matthias Mann Wed 9:00!

This is so well-deserved. Congratulations!

Our director, F.-Ulrich Hartl, is receiving this year’s “Keio Medical Science Prize”. We extend our warmest congratulations to him and to the other awardee, Seishi Ogawa. ❕Press release: www.biochem.mpg.de/f-ulrich-har...

Proteomics analysis has always lived in its own universe. AlphaPeptTools puts it in #scverse instead, so that proteome, transcriptome and spatial data live in one ecosystem. 11 search engines (DDA+DIA) read in, proteomics-specific statistics, #scverse native. doi.org/10.64898/202...

Same single cell, two modalities—both at depth. We digest protein first, run Smart-seq3xpress + C18 (Evotip) separation: peptides captured, cDNA in flowthrough. In HeLa & stem cells, proteome tracks cell state; RNA variance flags transitioning cells. www.biorxiv.org/content/10.6...

biorxiv.orgIn the same cell, the proteome defines cellular state and the transcriptome marks transitionsBulk transcriptome and proteome correlate only modestly, but this has not been investigated in the same cell or across cell-state changes. Here we introduce a scalable technology that quantifies thous...

Can AI take proteomics to a virtual cell? Our new perspective maps the path — from better peptide/protein ID to spatial & perturbation proteomics to AI Virtual Cells — and calls for an AI-friendly data ecosystem to get there. Together with Tiannan Guo and Zhang labs. www.nature.com/articles/s41...

nature.comAI proteomics: from protein identification to virtual cells - Nature MethodsThis Perspective highlights key research areas within mass spectrometry-based proteomics where AI is poised to drive significant advances.

Congrats to all the well-deserving winners of this year's #JSPAward @mpibiochem.bsky.social and a shout-out to @carolineweiss.bsky.social and Jakob Bader for their outstanding research. www.nature.com/articles/s42... cell.com/cell/fulltex...

cell.comLarge-scale proteomics across neurological disorders uncovers biomarker panel and targets in multiple sclerosisDeep proteome profiling of over 5,000 cerebrospinal fluid samples by mass spectrometry maps protein alterations across major neurological disorders, resolving key sources of variation as well as share...

Last week our very own in house award, the "Junior Scientists Publication Award" (JSPA) was presented. The best publications coming from young researchers were awarded and we congratulate them wholeheartedly - may many awards follow! 🎉

New preprint: Cell-type-resolved spatial proteogenomics, matched genome AND proteome of the same cells. The trick: the flowthrough we normally discard after loading peptides onto an Evotip contains genomic DNA at 85–95% yield. One tip, two molecular layers. www.biorxiv.org/content/10.6...

biorxiv.orgCell-type-resolved spatial proteogenomics from matched genome and proteome of the same cellsThe genome and proteome of the same cells are rarely measured together, which is especially consequential in cancer, where somatic mutations vary across clones and drive disease. We show that a single...
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No new instruments, no splitting scarce sample — just collect what you'd have thrown out. Opens the door to intra-tissue pQTL analyses linking somatic mutations to their protein-level consequences.

New preprint: Cell-type-resolved spatial proteogenomics, matched genome AND proteome of the same cells. The trick: the flowthrough we normally discard after loading peptides onto an Evotip contains genomic DNA at 85–95% yield. One tip, two molecular layers. www.biorxiv.org/content/10.6...

biorxiv.orgCell-type-resolved spatial proteogenomics from matched genome and proteome of the same cellsThe genome and proteome of the same cells are rarely measured together, which is especially consequential in cancer, where somatic mutations vary across clones and drive disease. We show that a single...

Combined with Deep Visual Proteomics, this works on decades-old FFPE tissue. In melanoma we found BRAF V600E shared across cells (early driver) while NRAS Q61K & truncating CDKN2A alteration appeared only in the PRAME+ subpopulation — the known driver hierarchy, resolved in situ.

Sample-prep tips printed with light, not packed by hand: our preprint introduces pSPEC. A robot casts 384 monolith tips at once for fast, reproducible capture-and-digest, feeding standard Evosep LC-MS. ~3,500 protein groups from urine, ~4,800 from saliva in 100 SPD. www.biorxiv.org/content/10.6...

biorxiv.orgIn situ polymerized monolith tips for reproducible, format-flexible proteomic sample preparation applied to biofluidsSample preparation increasingly sets the throughput and reproducibility of mass spectrometry (MS)-based proteomics. StageTips (stop-and-go extraction tips) and variants thereof have long been common i...

That's a wrap for ASMS 2026 for @mannlab.bsky.social team mates. The science on display was genuinely outstanding, and seeing where the field is heading has left us more motivated than ever to keep pushing our own work forward. Until next time! #ASMS2026 #MassSpectrometry #proteomics

At ASMS 2026? Come say hi to the MannLabs team — six talks & posters across the week on single-cell proteomics, interactome profiling, PTM enrichment, deep-learning targeted proteomics, and the latest in mass spec technology. #ASMS2026 #Proteomics #MassSpec #SingleCellProteomics

Our @MichaelJFoxOrg #ASAP grant brings the Mann lab's spatial proteomics — at single-cell-type resolution — to Parkinson's, the world's fastest-growing neurological disease. With Laura Parkkinen (Oxford University), Günter Höglinger & Franziska Hopfner (LMU Klinikum). #Proteomics

@asapresearch.parkinsonsroadmap.org in partnership with The Michael J. Fox Foundation for Parkinson’s Research, has awarded two research grants to Matthias Mann & colleagues to investigate the mechanims underlying Parkinson's disease. ❕More: www.biochem.mpg.de/two-research... @mannlab.bsky.social

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4/5 Cell type resolution exposes biology bulk profiling misses. We find cancer-testis antigens, proteins normally restricted to immune-privileged sites and actively targeted by immunotherapies, in oocytes of the female germline. Worth noting for CTA-directed therapy safety.

2/5 27 cell types × 14 tissues × ~14,000 proteins measured directly in tissue by Deep Visual Proteomics. The human proteome partitions into two regimes: A universal core that sustains cellular life, and tightly restricted programs that define cell type identity. Surprisingly little in between.

3/5 Matched RNA-protein comparison across 27 cell types reveals a clear rule: Concordance is organized by pathway, not by cell type. Metabolic pathways at the protein level and signaling pathways at the transcript level. A practical guide for when RNAseq predicts protein.

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The legendary Tom Cech delivered a masterful distinguished lecture @mpibiochem.bsky.social on how RNA controls DNA. The audience was captivated! Tom's infectious energy, humility and groundbreaking science continue to inspire us all. Thanks so much for your memorable visit!

Characterizing the ZenoTOF 8600 in collaboration @sciex.bsky.social . Scanning DIA on a compact platform — ~10K protein groups in bulk to single-cell proteomics & Parkinson's-relevant phosphosite detection with complementary CID & EAD fragmentation. biorxiv.org/content/10.64898/2026.03.12.711261v1

biorxiv.orgScanning DIA on the ZenoTOF 8600 system enables ultra-sensitive and quantitative proteomics from single cells to post-translational modifications in a compact platformMass spectrometry-based proteomics increasingly demands platforms that combine quantitative rigor with the discovery capabilities of accurate mass systems. Here we present the ZenoTOF 8600 system, a compact mass spectrometry system that integrates enhanced ion capture and transmission optics with an optical detection system, Zeno trap-enhanced MS/MS, electron-activated dissociation, and scanning quadrupole data-independent acquisition (ZT Scan DIA). We show that ZT Scan DIA outperforms conventional variable-window DIA (Zeno SWATH DIA) in both identifications and quantitative reproducibility, and demonstrate the platform's versatility across proteomics applications: thousands of protein groups from bulk samples at up to 500 samples per day, single-cell proteomics yielding up to 4,700 proteins, accurate ratio recovery in mixed-species quantitative benchmarks, low-attomole targeted quantitation, and detection of disease-relevant phosphorylation in a Parkinson's disease cellular model using complementary CID and EAD fragmentation. The instrument's compact footprint makes it attractive for settings where both analytical breadth and operational robustness are required. ### Competing Interest Statement B.L., Y.L.B., N. B., I.B., J.C., A.C., G.I., K.T., T.T., B.S., and J.C.-P. are employees of SCIEX. M.M. is an indirect investor in Evosep Biosystems. The remaining authors declare no competing interests.