Cullin-RING finger ligases (CRLs) represent the largest family of ubiquitin ligases. They are responsible for the ubiquitination of ∼20% of cellular proteins degraded through the proteasome, by catalyzing the transfer of E2-loaded ubiquitin to a substrate. Seven Cullins are described in vertebrates. Among them, CUL4 associates with DDB1 to form the CUL4-DDB1 ubiquitin ligase complex, which is involved in protein ubiquitination and in the regulation of many cellular processes. Substrate recognition adaptors named DDB1/CUL4 associated factors (DCAF) mediate the specificity of CUL4-DDB1 and have a short structural motif of approximately forty amino acids terminating in tryptophan (W)-aspartic acid (D) dipeptide, called the WD40 domain. Using different approaches (bioinformatics/structural analyses), independent studies suggested that at least sixty WD40-containing proteins could act as adaptors for the DDB1/CUL4 complex. To better define this association and classification, the interaction of each DCAFs with DDB1 was determined, and new partners and potential substrates were identified. Using BioID and AP-MS approaches, we demonstrated that seven WD40 proteins can be considered DCAFs with a high confidence level. Identifying protein interactions does not always lead to identifying protein substrates for E3-ubiquitin ligases, so we measured changes in protein stability or degradation by pulse-SILAC to identify changes in protein degradation following the expression of each DCAF. In conclusion, these results provide new insights into the roles of DCAFs in regulating the activity of the DDB1-CUL4 complex, in protein targeting, and characterized the cellular processes involved.

Defining the molecular phenotype of single cells in-situ is key for understanding tissue architecture in health and disease. Advanced imaging platforms have recently been joined by spatial omics technologies, promising unparalleled insights into the molecular landscape of biological samples. Furthermore, high-precision laser microdissection of tissue on membrane glass slides is a powerful method for spatial omics technologies and single-cell type spatial proteomics in particular. However, current histology protocols have not been compatible with glass membrane slides and laser microdissection for automated staining platforms and routine histology procedures. This has prevented the combination of advanced staining procedures with laser microdissection. In this study we describe a novel method for handling glass membrane slides that enables automated, eight-color multiplexed immunofluorescence staining and high-quality imaging followed by precise laser-guided extraction of single cells. The key advance is the glycerol-based modification of heat-induced epitope retrieval protocols, termed 'G-HIER'. We find that this altered antigen-retrieval solution prevents membrane distortion. Importantly, G-HIER is fully compatible with current antigen retrieval workflows and mass spectrometry-based proteomics and does not affect proteome depth or quality. To demonstrate the versatility of G-HIER for spatial proteomics, we apply the recently introduced Deep Visual Proteomics technology to perform single-cell type analysis of adjacent suprabasal and basal keratinocytes of human skin. G-HIER overcomes previous incompatibility of standard and advanced staining protocols with membrane glass slides and enables robust integration with routine histology procedures, high-throughput multiplexed imaging and sophisticated downstream spatial omics technologies.

Uterine environment is tightly and finely regulated via various signalling pathways mediated through endocrine, exocrine, autocrine, juxtracrine and paracrine mechanisms. In utero signalling processes are paramount for normal and abnormal physiology which involves cell to cell, cells to gametes, cells to embryo and even inter-kingdom communications due to presence of uterine microbiota. Extracellular vesicles (EVs) in the uterine fluid (UF) and their cargo components are known to be mediators of in utero signalling and communications. Interestingly, the changes in UF-EV proteome during the bovine oestrous cycle and the effects of these differentially enriched proteins on embryo development are yet to be fully discovered. In this study, shotgun quantitative proteomics-based mass-spectrometry was employed to compare UF-EV proteomes at day 0, 7 and 16 of the oestrous cycle to understand the oestrous cycle dependant dynamics. Furthermore, different phase UF-EVs were supplemented in embryo cultures to evaluate their impact on embryo development. 159 UF-EV proteins were differentially enriched at different time points indicating the UF-EV proteome is cycle dependent. Overall, many identified pathways are important for normal uterine functions, early embryo development and its nutritional needs, such as antioxidant activity, cell morphology and cycle, cellular homeostasis, cell adhesion and carbohydrate metabolic process. Furthermore, the luteal phase UF-EVs supplementation increased in vitro blastocyst rates from 25.0 ± 5.9% to 41.0 ± 4.0% (P ≤ 0.05). Our findings highlight the importance of bovine UF-EV in uterine communications throughout the oestrous cycle. Interestingly, comparison of hormone synchronized EV-proteomes to natural cycle UF-EVs indicated shift of signalling. Finally, UF-EVs can be used to improve embryo production in vitro.

Cell metabolism generates numerous intermediate metabolites that could serve as feedback and feed-forward regulation substances for post-translational modification. Lactate, a metabolic product of glycolysis, has recently been conceptualized to play a pleiotropic role in shaping cell identities through metabolic rewiring and epigenetic modifications. Lactate-derived carbons, sourced from glucose, mediate the crosstalk among glycolysis, lactate and lactylation. Furthermore, the multiple metabolic fates of lactate make it an ideal substrate for metabolic imaging in clinical application. Several studies have identified the crucial role of protein lactylation in human diseases associated with cell fate determination, embryonic development, inflammation, neoplasm and neuropsychiatric disorders. Herein, this review will focus on the metabolic fate of lactate-derived carbon to provide useful information for further research and therapeutic approaches in human diseases. We comprehensively discuss its role in reprogramming and modification during the regulation of glycolysis, the clinical translation prospects of the hyperpolarized lactate signal, lactyl modification in human diseases, and its application with other techniques and omics.

We present an integrated immunopeptidomics and proteomics study of SARS-CoV-2 infection to comprehensively decipher the changes in host cells in response to viral infection. Immunopeptidomics analysis identified viral antigens presented by host cells through both Class I and Class II MHC system for recognition by the adaptive immune system. The host proteome changes were characterized by quantitative proteomics and glycoproteomics and from these data, the activation of TLR3-interferon pathway was identified. Glycosylation analysis of HLA proteins from the elution and flow-through of immunoprecipitation revealed that SARS-CoV-2 infection changed the glycosylation pattern of certain HLA alleles with different HLA alleles showing distinct dynamic changes in relative abundance. The difference in the glycosylation and abundance of HLA alleles changed the number of strong binding antigens each allele presented, suggesting the impact of SARS-CoV-2 infection on antigen presentation is allele specific. These results could be further exploited to explain the imbalanced response from innate and adaptive immune system in severe COVID-19 cases, which would be helpful for the development of therapeutics and vaccine for COVID-19 and preparation for future pandemic.

Imaging mass spectrometry (IMS) is a molecular technology utilized for spatially driven research, providing molecular maps from tissue sections. This article reviews matrix-assisted laser desorption ionization (MALDI) IMS and its progress as a primary tool in the clinical laboratory. MALDI mass spectrometry has been used to classify bacteria and perform other bulk analyses for plate-based assays for many years. However, the clinical application of spatial data within a tissue biopsy for diagnoses and prognoses is still an emerging opportunity in molecular diagnostics. This work considers spatially driven mass spectrometry approaches for clinical diagnostics and addresses aspects of new imaging-based assays that include analyte selection, quality control/assurance metrics, data reproducibility, data classification, and data scoring. It is necessary to implement these tasks for the rigorous translation of IMS to the clinical laboratory; however, this requires detailed standardized protocols for introducing IMS into the clinical laboratory to deliver reliable and reproducible results that inform and guide patient care.

Prostate cancer (PCa) is the second most prevalent malignancy and the fifth cause of cancer-related deaths in men. A crucial challenge is identifying the population at risk of rapid progression from hormone-sensitive prostate cancer (HSPC) to lethal castration-resistant prostate cancer (CRPC). We collected 78 HSPC biopsies and measured their proteomes using pressure cycling technology and a pulsed data-independent acquisition pipeline. We quantified 7355 proteins using these HSPC biopsies. A total of 251 proteins showed differential expression between patients with a long- or short-term progression to CRPC. Using a random forest model, we identified seven proteins that significantly discriminated long- from short-term progression patients, which were used to classify PCa patients with an area under the curve of 0.873. Next, one clinical feature (Gleason sum) and two proteins (BGN and MAPK11) were found to be significantly associated with rapid disease progression. A nomogram model using these three features was generated for stratifying patients into groups with significant progression differences (p-value = 1.3×10-4). To conclude, we identified proteins associated with a fast progression to CRPC and an unfavorable prognosis. Based on these proteins, our machine learning and nomogram models stratified HSPC into high- and low-risk groups and predicted their prognoses. These models may aid clinicians in predicting the progression of patients, guiding individualized clinical management and decisions.

The asialoglycoprotein receptor (ASGPR) and the mannose receptor C-type 1 (MRC1) are well known for their selective recognition and clearance of circulating glycoproteins. Terminal galactose and N-Acetylgalactosamine are recognized by ASGPR, while terminal mannose, fucose, and N-Acetylglucosamine are recognized by MRC1. The effects of ASGPR and MRC1 deficiency on the N-glycosylation of individual circulating proteins have been studied. However, the impact on the homeostasis of the major plasma glycoproteins is debated and their glycosylation has not been mapped with high molecular resolution in this context. Therefore, we evaluated the total plasma N-glycome and plasma proteome of ASGR1 and MRC1 deficient mice. ASGPR deficiency resulted in an increase in O-acetylation of sialic acids accompanied by higher levels of apolipoprotein D, haptoglobin, and vitronectin. MRC1 deficiency decreased fucosylation without affecting the abundance of the major circulating glycoproteins. Our findings confirm that concentrations and N-glycosylation of the major plasma proteins are tightly controlled and further suggest that glycan-binding receptors have redundancy, allowing compensation for the loss of one major clearance receptor.

The National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) provides unique opportunities for cancer target discovery using protein expression. Proteomics data from CPTAC tumor types have been primarily generated using a multiplex tandem mass tag (TMT) approach, which is designed to provide protein quantification relative to reference samples. However, relative protein expression data are suboptimal for prioritization of targets within a tissue type, which requires additional reprocessing of the original proteomics data to derive absolute quantitation estimation. We evaluated the feasibility of using differential protein analysis coupled with intensity-based absolute quantification (iBAQ) to identify tumor-enriched and highly expressed cell surface antigens, employing tandem mass tag (TMT) proteomics data from CPTAC. Absolute quantification derived from TMT proteomics data was highly correlated with that of label-free proteomics data from the CPTAC colon adenocarcinoma cohort, which contains proteomics data measured by both approaches. We validated the TMT-iBAQ approach by comparing the iBAQ value to the receptor density value of HER2 and TROP2 measured by flow cytometry in about 30 selected breast and lung cancer cell lines from the Cancer Cell Line Encyclopedia. Collections of these tumor-enriched and highly expressed cell surface antigens could serve as a valuable resource for the development of cancer therapeutics, including antibody-drug conjugates and immunotherapeutic agents.

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease, although disease stratification using in-depth plasma proteomics has not been performed to date. By measuring more than 1000 proteins in the plasma of 147 DLBCL patients using data-independent acquisition mass spectrometry and antibody array, DLBCL patients were classified into four proteomic subtypes (PS-I-IV). Patients with the PS-IV subtype and worst prognosis had increased levels of proteins involved in inflammation, including a high expression of metalloproteinase inhibitor-1 (TIMP-1) that was associated with poor survival across two validation cohorts (n = 180). Notably, the combination of TIMP-1 with the international prognostic index (IPI) identified 64.00% to 88.24% of relapsed and 65.00% to 80.49% of deceased patients in the discovery and two validation cohorts, which represents a 24.00% to 41.67% and 20.00% to 31.70% improvement compared to the IPI score alone, respectively. Taken together, we demonstrate that DLBCL heterogeneity is reflected in the plasma proteome and that TIMP-1, together with the IPI, could improve the prognostic stratification of patients.

Secondary mutation, T790M, conferring tyrosine kinase inhibitors (TKIs) resistance beyond oncogenic epidermal growth factor receptor (EGFR) mutations presents a challenging unmet need. Although TKI-resistant mechanisms are intensively investigated, the underlying responses of cancer cells adapting drug perturbation are largely unknown. To illuminate the molecular basis linking acquired mutation to TKI resistance, affinity purification coupled mass spectrometry was adopted to dissect EGFR interactome in TKI-sensitive and TKI-resistant non-small cell lung cancer cells. The analysis revealed TKI-resistant EGFR-mutant interactome allocated in diverse subcellular distribution and enriched in endocytic trafficking, in which gefitinib intervention activated autophagy-mediated EGFR degradation and thus autophagy inhibition elevated gefitinib susceptibility. Alternatively, gefitinib prompted TKI-sensitive EGFR translocating toward cell periphery through Rab7 ubiquitination which may favor efficacy to TKIs suppression. This study revealed that T790M mutation rewired EGFR interactome that guided EGFR to autophagy-mediated degradation to escape treatment, suggesting that combination therapy with TKI and autophagy inhibitor may overcome acquired resistance in non-small cell lung cancer.

Data-independent acquisition (DIA) mass spectrometry-based proteomics generates reproducible proteome data. The complex processing of the DIA data has led to the development of multiple data analysis tools. In this study, we assessed the performance of five tools (OpenSWATH, EncyclopeDIA, Skyline, DIA-NN, and Spectronaut) using six DIA datasets obtained from TripleTOF, Orbitrap, and TimsTOF Pro instruments. By comparing identification and quantification metrics and examining shared and unique cross-tool identifications, we evaluated both library-based and library-free approaches. Our findings indicate that library-free approaches outperformed library-based methods when the spectral library had limited comprehensiveness. However, our results also suggest that constructing a comprehensive library still offers benefits for most DIA analyses. This study provides comprehensive guidance for DIA data analysis tools, benefiting both experienced and novice users of DIA-mass spectrometry technology.

Characterization of highly glycosylated biopharma-ceuticals by mass spectrometry is challenging because of the huge chemical space of coexistent glycoforms present. Here, we report the use of an array of HPLC-mass spectrometry-based approaches at different structural levels of released glycan, glycopeptide, and hitherto unexplored intact glycoforms to scrutinize the biopharmaceutical Myozyme, containing the highly complex lysosomal enzyme recombinant acid α-glucosidase. The intrinsic heterogeneity of recombinant acid α-glucosidase glycoforms was unraveled using a novel strong anion exchange HPLC-mass spectrometry approach involving a pH-gradient of volatile buffers to facilitate chromatographic separation of glycoforms based on their degree of sialylation, followed by the acquisition of native mass spectra in an Orbitrap mass spectrometer. Upon considering the structures of 60 different glycans attached to seven glycosylation sites in the intact protein, the large set of interdependent data acquired at different structural levels was integrated using a set of bioinformatic tools and allowed the annotation of intact glycoforms unraveling more than 1,000,000 putative intact glycoforms. Detectable isoforms also included several mannose-6-phosphate variants, which are essential for directing the drug toward its target, the lysosomes. Finally, for the first time, we sought to validate the intact glycoform annotations by integrating experimental data on the enzymatically dissected proteoforms, which reduced the number of glycoforms supported by experimental evidence to 42,104. The latter verification clearly revealed the strengths but also intrinsic limitations of this approach for fully characterizing such highly complex glycoproteins by mass spectrometry.

Targeted mass spectrometry (MS)-based proteomic assays, such as multiplexed multiple reaction monitoring (MRM)-MS assays, enable sensitive and specific quantification of proteotypic peptides as stoichiometric surrogates for proteins. Efforts are underway to expand the use of MRM-MS assays in clinical environments, which requires a reliable strategy to monitor proteolytic digestion efficiency within individual samples. Towards this goal, extended stable isotope-labeled standard (SIS) peptides (hE), which incorporate native proteolytic cleavage sites, can be spiked into protein lysates prior to proteolytic (trypsin) digestion, and release of the tryptic SIS peptide (hT) can be monitored. However, hT measurements alone cannot monitor the extent of digestion and may be confounded by matrix effects specific to individual patient samples; therefore, they are not sufficient to monitor sample-to-sample digestion variability. We hypothesized that measuring undigested hE, along with its paired hT, would improve detection of digestion issues compared to only measuring hT. We tested the ratio of the SIS pair measurements, or hE/hT, as a quality control (QC) metric of trypsin digestion for two MRM assays: a direct-MRM (398 targets) and an immuno-MRM (126 targets requiring immunoaffinity peptide enrichment) assay, with extended SIS peptides observable for 54% (216) and 62% (78) of the targets, respectively. We evaluated the quantitative bias for each target in a series of experiments that adversely affected proteolytic digestion (e.g., variable digestion times, pH, and temperature). We identified a subset of SIS pairs (36 for the direct-MRM, 7 for the immuno-MRM assay) for which the hE/hT ratio reliably detected inefficient digestion that resulted in decreased assay sensitivity and unreliable endogenous quantification. The hE/hT ratio was more responsive to a decrease in digestion efficiency than a metric based on hT measurements alone. For clinical-grade MRM-MS assays, this study describes a ready-to-use QC panel and also provides a road map for designing custom QC panels.

Single-cell technologies are currently widely applied to obtain a deeper understanding of the phenotype of single-cells in heterogenous mixtures. However, integrated multilayer approaches including simultaneous detection of mRNA, protein expression, and intracellular phospho-proteins are still challenging. Here, we combined an adapted method to in vitro-differentiate peripheral B-cells into antibody-secreting cells (ASCs) (i.e., plasmablasts and plasma cells) with integrated multi-omic single-cell sequencing technologies to detect and quantify immunoglobulin subclass-specific surface markers, transcriptional profiles, and signaling transduction pathway components. Using a common set of surface proteins, we integrated two multimodal datasets to combine mRNA, protein expression, and phospho-protein detection in one integrated dataset. Next, we tested whether ASCs that only seem to differ in its ability to secrete different IgM, IgA, or IgG antibodies exhibit other differences that characterize these different ASCs. Our approach detected differential expression of plasmablast and plasma cell markers, homing receptors, and TNF receptors. In addition, differential sensitivity was observed for the different cytokine stimulations that were applied during in vitro differentiation. For example, IgM ASCs were more sensitive to IL-15, while IgG ASC responded more to IL-6 and IFN addition. Furthermore, tonic BCR activity was detected in IgA and IgM ASCs, while IgG ASC exhibited active BCR-independent SYK activity and NF-κB and mTOR signaling. We confirmed these findings using flow cytometry and small molecules inhibitors, demonstrating the importance of SYK, NF-κB, and mTOR activity for plasmablast/plasma cell differentiation/survival and/or IgG secretion. Taken together, our integrated multi-omics approach allowed high-resolution phenotypic characterization of single cells in a heterogenous sample of in vitro-differentiated human ASCs. Our strategy is expected to further our understanding of human ASCs in healthy and diseased samples and provide a valuable tool to identify novel biomarkers and potential drug targets.

Serum antibodies IgM and IgG are elevated during Coronavirus Disease 2019 (COVID-19) to defend against viral attacks. Atypical results such as negative and abnormally high antibody expression were frequently observed whereas the underlying molecular mechanisms are elusive. In our cohort of 144 COVID-19 patients, 3.5% were both IgM and IgG negative, whereas 29.2% remained only IgM negative. The remaining patients exhibited positive IgM and IgG expression, with 9.3% of them exhibiting over 20-fold higher titers of IgM than the others at their plateau. IgG titers in all of them were significantly boosted after vaccination in the second year. To investigate the underlying molecular mechanisms, we classed the patients into four groups with diverse serological patterns and analyzed their 2-year clinical indicators. Additionally, we collected 111 serum samples for TMTpro-based longitudinal proteomic profiling and characterized 1494 proteins in total. We found that the continuously negative IgM and IgG expression during COVID-19 were associated with mild inflammatory reactions and high T cell responses. Low levels of serum IgD, inferior complement 1 activation of complement cascades, and insufficient cellular immune responses might collectively lead to compensatory serological responses, causing overexpression of IgM. Serum CD163 was positively correlated with antibody titers during seroconversion. This study suggests that patients with negative serology still developed cellular immunity for viral defense and that high titers of IgM might not be favorable to COVID-19 recovery.

AMP-activated protein kinase alpha 2 (AMPKα2) regulates energy metabolism, protein synthesis, and glucolipid metabolism myocardial cells. Ketone bodies produced by fatty acid β-oxidation, especially β-hydroxybutyrate, are fatty energy-supplying substances for the heart, brain, and other organs during fasting and long-term exercise. They also regulate metabolic signaling for multiple cellular functions. Lysine β-hydroxybutyrylation (Kbhb) is a β-hydroxybutyrate-mediated protein posttranslational modification. Histone Kbhb has been identified in yeast, mouse, and human cells. However, whether AMPK regulates protein Kbhb is yet unclear. Hence, the present study explored the changes in proteomics and Kbhb modification omics in the hearts of AMPKα2 knockout mice using a comprehensive quantitative proteomic analysis. Based on mass spectrometry (LC-MS/MS) analysis, the number of 1181 Kbhb modified sites in 455 proteins were quantified between AMPKα2 knockout mice and wildtype mice; 244 Kbhb sites in 142 proteins decreased or increased after AMPKα2 knockout (fold change >1.5 or <1/1.5, p < 0.05). The regulation of Kbhb sites in 26 key enzymes of fatty acid degradation and tricarboxylic acid cycle was noted in AMPKα2 knockout mouse cardiomyocytes. These findings, for the first time, identified proteomic features and Kbhb modification of cardiomyocytes after AMPKα2 knockout, suggesting that AMPKα2 regulates energy metabolism by modifying protein Kbhb.

Caenorhabditis elegans is a frequently-employed genetic model organism and has been the object of a wide range of developmental, genetic, proteomic and glycomic studies. Here, using an off-line MALDI-TOF-MS approach, we have analysed the N-glycans of mixed embryos and liquid- or plate-grown L4 larvae. Of the over 200 different annotatable N-glycan structures, variations between the stages as well as the mode of cultivation were observed. While the embryonal N-glycome appears less complicated overall, the liquid- and plate-grown larvae differ especially in terms of methylation of bisecting fucose, α-galactosylation of mannose and di-β-galactosylation of core α1,6-fucose. Furthermore, we analysed the O-glycans by LC-ESI-MS following β-elimination; especially the embryonal O-glycomes included a set of phosphorylcholine-modified structures, previously not shown to exist in nematodes. However, the set of glycan structures cannot be clearly correlated with levels of glycosyltransferase transcripts in developmental RNA-seq datasets, but there is an indication for co-ordinated expression of clusters of potential glycosylation-relevant genes. Thus, there are still questions to be answered in terms of how and why a simple nematode synthesizes such a diverse glycome.

MYCN amplification is an independent risk factor for poor prognosis in neuroblastoma (NB), but its protein product cannot be directly targeted due to protein structure. Thus, this study aimed to explore novel ways to indirectly target N-Myc by regulating its posttranslational modifications (PTMs) and therefore protein stability. N-Myc co-immunoprecipitation combined with HPLC-MS/MS identified 16 PTM residues and 114 potential N-Myc interacting proteins. Notably, both acetylation and ubiquitination were identified on lysine 199 of N-Myc. We then discovered that p300, which can interact with N-Myc, modulated the protein stability of N-Myc in MYCN-amplified NB cell lines, and simultaneously regulated the acetylation level on lysine-199 and ubiquitination level of N-Myc protein in vitro. Furthermore, p300 correlated with poor prognosis in public NB datasets. Taken together, p300 can be considered as a potential therapeutic target to treat MYCN-amplified NB patients, and other identified PTMs and interacting proteins also provide potential targets for further study.

Conventional proteomic approaches measure the averaged signal from mixed cell populations or bulk tissues, leading to the dilution of signals arising from subpopulations of cells that might serve as important biomarkers. Recent developments in bottom-up proteomics have enabled spatial mapping of cellular heterogeneity in tissue microenvironments. However, bottom-up proteomics cannot unambiguously define and quantify proteoforms, which are intact (i.e., functional) forms of proteins capturing genetic variations, alternatively spliced transcripts and posttranslational modifications. Herein, we described a spatially resolved top-down proteomics (TDP) platform for proteoform identification and quantitation directly from tissue sections. The spatial TDP platform consisted of a nanodroplet processing in one pot for trace samples-based sample preparation system and an laser capture microdissection-based cell isolation system. We improved the nanodroplet processing in one pot for trace samples sample preparation by adding benzonase in the extraction buffer to enhance the coverage of nucleus proteins. Using ∼200 cultured cells as test samples, this approach increased total proteoform identifications from 493 to 700; with newly identified proteoforms primarily corresponding to nuclear proteins. To demonstrate the spatial TDP platform in tissue samples, we analyzed laser capture microdissection-isolated tissue voxels from rat brain cortex and hypothalamus regions. We quantified 509 proteoforms within the union of top-down mass spectrometry-based proteoform identification and characterization and TDPortal identifications to match with features from protein mass extractor. Several proteoforms corresponding to the same gene exhibited mixed abundance profiles between two tissue regions, suggesting potential posttranslational modification-specific spatial distributions. The spatial TDP workflow has prospects for biomarker discovery at proteoform level from small tissue sections.