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PubMed2024

Deciphering the ghost proteome in ovarian cancer cells by deep proteogenomic characterization.

Proteogenomics is becoming a powerful tool in personalized medicine by linking genomics, transcriptomics and mass spectrometry (MS)-based proteomics. Due to increasing evidence of alternative open reading frame-encoded proteins (AltProts), proteogenomics has a high potential to unravel the characteristics, variants, expression levels of the alternative proteome, in addition to already annotated proteins (RefProts). To obtain a broader view of the proteome of ovarian cancer cells compared to ovarian epithelial cells, cell-specific total RNA-sequencing profiles and customized protein databases were generated. In total, 128 RefProts and 30 AltProts were identified exclusively in SKOV-3 and PEO-4 cells. Among them, an AltProt variant of IP_715944, translated from DHX8, was found mutated (p.Leu44Pro). We show high variation in protein expression levels of RefProts and AltProts in different subcellular compartments. The presence of 117 RefProt and two AltProt variants was described, along with their possible implications in the different physiological/pathological characteristics. To identify the possible involvement of AltProts in cellular processes, cross-linking-MS (XL-MS) was performed in each cell line to identify AltProt-RefProt interactions. This approach revealed an interaction between POLD3 and the AltProt IP_183088, which after molecular docking, was placed between POLD3-POLD2 binding sites, highlighting its possibility of the involvement in DNA replication and repair.

Humans↗

PubMed2026

Proteogenomic features define subtypes of mantle cell lymphoma.

Mantle cell lymphoma (MCL) is a biologically heterogeneous B-cell malignancy. Although genomics and transcriptomics have delineated parts of the MCL disease spectrum, proteomics remains largely unexplored. Here, we conducted a comprehensive proteogenomic analysis integrating genomics, transcriptomics, and proteomics on peripheral blood samples from 27 patients with MCL and 4 healthy donors to investigate the translational and posttranslational dimensions of MCL. Our study identified 1296 downregulated and 468 upregulated proteins in MCL cells. The splicing pathways were significantly upregulated at both the mRNA and protein levels, suggesting a critical role for aberrant RNA splicing in MCL pathogenesis. Integration of proteomic data with genetic aberrations revealed immunoglobulin heavy chain variable mutational status and CCND1 mutation are associated with distinctive transcriptomic and proteomic profiles, which correspond to significant differences in clinical outcomes. A multiomics molecular stratification model incorporating proteomic data showed superior predictive power for patient survival compared with single-omics models (concordance index, 0.83 vs 0.74). This study provides, to our knowledge, the first comprehensive proteogenomic profile of MCL, offering novel insights into its molecular mechanisms and clinical behavior. The identification of molecular subtypes and prognostic protein signatures underscores the potential of proteomics to guide precision medicine strategies for MCL.

Humans↗

PubMed2024

Targeted Dynamic Phospho-Proteogenomic Analysis of Gastric Cancer Cells Suggests Host Immunity Provides Survival Benefit.

Despite of massive emergence of molecular targeting drugs, the mainstay of advanced gastric cancer (GC) therapy is DNA-damaging drugs. Using a reverse-phase protein array-based proteogenomic analysis of a panel of 8 GC cell lines, we identified genetic alterations and signaling pathways, potentially associated with resistance to DNA-damaging drugs, including 5-fluorouracil (5FU), cisplatin, and etoposide. Resistance to cisplatin and etoposide, but not 5FU, was negatively associated with global copy number loss, vimentin expression, and caspase activity, which are considered hallmarks of previously established EMT subtype. The segregation of 19,392 protein expression time courses by sensitive and resistant cell lines for the drugs tested revealed that 5FU-resistant cell lines had lower changes in global protein dynamics, suggesting their robust protein level regulation, than their sensitive counterparts, whereas the cell lines that are resistant to other drugs showed increased protein dynamics in response to each drug. Despite faint global protein dynamics, 5FU-resistant cell lines showed increased signal transducer and activator of transcription 1 phosphorylation and PD-L1 expression in response to 5FU. In publicly available cohort data, expression of signal transducer and activator of transcription 1 and NFκB target genes induced by proinflammatory cytokines was associated with prolonged survival in GC. In our validation cohort, total lymphocyte count, rather than PD-L1 positivity, predicted a better relapse-free survival rate in GC patients with 5FU-based adjuvant chemotherapy than those with surgery alone. Moreover, total lymphocyte count+ patients who had no survival benefit from adjuvant chemotherapy were discriminated by expression of IκBα, a potent negative regulator of NFκB. Collectively, our results suggest that 5FU resistance observed in cell lines may be overcome by host immunity or by combination therapy with immune checkpoint blockade.

Stomach Neoplasms↗

PubMed2026

A Proteogenomic Approach to Discover Novel lncRNA-Derived Microproteins and Their Potential Clinical Utility in Hepatocellular Carcinoma.

Microproteins (i.e., peptides) are increasingly recognized for their functions in versatile biological contexts, but their clinical relevance and utility remain largely unexplored. Proteogenomic approaches can accelerate microprotein discovery in clinical samples by integrating proteomic data with genomics and transcriptomics evidence. However, long noncoding RNA (lncRNA)-derived microproteins (lncPeps) remain largely unidentified, resulting in unmatchable MS/MS spectra. To solve this problem, we have used high-quality Ribo-seq translatomic datasets to generate an extensive database of human liver lncRNA-derived open reading frames (lncORFs), which we subsequently applied to proteomics data of tumor-adjacent normal tissue pairs from hepatocellular carcinoma (HCC) patients. Using the new database, we discovered 104 novel lncPeps, including 46 lncPeps differentially expressed between tumor and nontumor tissues, and 13 lncPeps with significant correlation with prognosis. Remarkably, combining the expression of lncPeps with canonical proteins in a LASSO regression model improved predictive performance for recurrence, increasing the AUC by 0.005 to 0.085 across three recurrence time points. These findings suggest that the discovery of lncPeps contributes to our understanding of the molecular heterogeneity and progression of HCC and broadens the range of potential biomarker candidates and treatment targets for the disease.

Humans↗

PubMed2026

Genomic and proteogenomic insights into Spontaneous Coronary Artery Dissection (SCAD): A systematic review of emerging multi-omic evidence.

BACKGROUND: Spontaneous coronary artery dissection (SCAD) is a major cause of myocardial infarction in young women without traditional cardiovascular risk factors (Hayes et al., 2018; Adlam et al., 2018 [1, 2]). Despite growing awareness, its biological underpinnings remain incompletely understood, and clinical management is largely based on observational evidence rather than mechanistic insight (Saw et al., 2014; Lettieri et al., 2015; Steg et al., 2024 [3-5]). OBJECTIVES: To systematically integrate genomic, epitranscriptomic, proteomic, and metabolomic data in order to characterize the multi-omic architecture of SCAD and identify potential biomarkers and therapeutic targets. METHODS: A systematic review was conducted in accordance with the PRISMA 2020 statement (Arbelo et al., 2023 [6]). PubMed/MEDLINE was searched for original studies investigating genomic and multi-omic features of SCAD. Data were extracted on study design, patient characteristics, identified variants, circulating biomarkers, and implicated biological pathways. Functional enrichment analysis was performed using the DAVID bioinformatics resource (Page et al., 2021 [7]). RESULTS: A total of 16 studies were included. Genome-wide association studies consistently identified susceptibility loci related to arterial structure and extracellular matrix integrity, including ADAMTSL4, PHACTR1/EDN1, LRP1, and FBN1 (Huang et al., 2009; Saw et al., 2020; Turley et al., 2020 [8-10]). Rare variant analyses further supported the role of genes involved in extracellular matrix remodeling and vascular smooth muscle cell function, including COL3A1, COL4A1/2, SMAD3, and TLN1 (Adlam et al., 2023; Turley et al., 2021, 2019; Carss et al., 2020; Zekavat et al., 2022; Wang et al., 2022 [11-16]), while ancestry-specific signals such as TSR1 variants were observed in distinct populations (Turley et al., 2023 [17]). Proteogenomic approaches linked genetic susceptibility loci to circulating proteins involved in matrix remodeling and inflammation, including cathepsin B and ECM1 (Maioli et al., 2010 [18]). Epitranscriptomic analyses identified differential microRNA expression profiles associated with vascular injury and repair pathways (Sun et al., 2019 [19]). CONCLUSIONS: SCAD is characterized by a complex, multi-layered biological architecture involving genetic susceptibility, extracellular matrix dysregulation, and vascular signaling pathways. Integration of multi-omic data provides novel insights into disease mechanisms and highlights potential biomarkers and targets for precision medicine approaches in SCAD.

Animals↗

PubMed2026

Proteogenomic analysis of pediatric and AYA high-grade glioma reveals age-dependent biology, female-male differences, and kinase targets.

High-grade gliomas (HGGs) in children and adolescents and young adults (AYA) exhibit distinct biology across the neurodevelopmental spectrum. To dissect tumor-intrinsic molecular characteristics independent of developmental variation, we perform comprehensive proteogenomic analyses of tumors from 112 HGG patients aged 0-40 years. Our multi-omics analysis identifies two AYA subgroups-adolescents (aged 15-26 years) and young adults (aged 26-40 years)-with distinct molecular profiles and survival outcomes. Tumor-normal comparisons and survival modeling highlight roles of oxidative phosphorylation and neuronal system biology in glioma progression. Causal network analysis and cell line studies provide a rationale for personalized therapies targeting candidate kinases, such as CDK8. Survival modeling, clustering, and immune-landscape analyses identify proteins, post-translational modifications, and immune signatures linked to outcomes and reveal clinically relevant differences between male and female patients.

adolescent and young adult glioma↗

PubMed2026

Long-read proteogenomic atlas of human neuronal differentiation reveals isoform diversity informing neurodevelopmental risk mechanisms.

RNA splicing shapes neuronal identity and disease risk, yet current maps lack the developmental resolution and depth to resolve this complexity. Here, we integrate deep long-read RNA sequencing and proteomics in induced pluripotent stem cell-derived cortical neurons to generate a high-resolution proteogenomic atlas of human neuron development. We identify 182,371 mRNA isoforms (over half previously unknown) and provide direct peptide evidence for the translation of hundreds of novel protein-coding sequences. Population genetics demonstrates that variants affecting novel exons and splice sites are under negative selection, underscoring the potential significance of these isoforms. During neuronal maturation, we observe that autism risk genes undergo dynamic isoform switching, including microexon inclusion and intron retention, that remodel key protein domains and regulatory regions. Furthermore, we uncover widespread, long-range coordination between alternative transcript processing events, including transcription start sites, exon splicing, and polyadenylation. Finally, our atlas enables variant reinterpretation in autism, highlighting the value of an isoform-centric view for interpreting pathogenic variation in neurodevelopment.

Humans↗

PubMed2026

Cross-Ancestry Proteogenomic Analyses Identified New Therapeutic Insights for Ischemic Heart Disease.

BACKGROUND: Most drugs target proteins, and proteome-wide genetic analyses in diverse populations could discover potential novel and repurposed targets for improved prevention and treatment of ischemic heart disease (IHD) beyond statin therapy. OBJECTIVES: The purposes of this study were to use cis-acting single nucleotide polymorphisms (cis-pQTLs) identified for plasma proteins in East Asians and Europeans to discover and validate potential drug targets for IHD. METHODS: We measured plasma levels of 9,520 (Olink/SomaScan: 2,923/7,297) proteins in a case-cohort study of IHD (1,976 incident cases and 2,001 subcohort controls) in statin-free individuals in the prospective China Kadoorie Biobank (CKB). Genome-wide association studies identified 2,895 (Olink/SomaScan: 1,301/1,594) cis-pQTLs for these proteins in CKB. Two-sample Mendelian randomization (MR) and colocalization analyses assessed associations of all available cis-pQTLs for these proteins with IHD in East Asians (n = 29,319 cases), with further replication in Europeans (n = 181,522 cases) and comparison with findings in previous MR studies. RESULTS: In CKB observational analyses, a total of 959 (Olink/SomaScan: 426/533) proteins were associated at false discovery rate-corrected P < 0.05 with IHD after adjusting for major IHD risk factors. Two-sample MR analyses provided genetic support for 54 unique (Olink/SomaScan: 36/28) proteins in IHD etiology. Colocalization analyses confirmed shared gene-protein-IHD associations (posterior probability of hypothesis 4 [PPH4] ≥0.8) for 15 unique (Olink/SomaScan: 10/10) proteins, including 8 lipid-related, 3 inflammation-related, 1 blood pressure-related, and 3 alcohol-related proteins in East Asians. In Europeans, MR analyses of 12 non-alcohol-related proteins showed directionally concordant results for 8 proteins, with 5 having strong colocalization evidence of shared gene-protein-IHD associations (PPH4 ≥0.8), including 4 lipid-related (proprotein convertase subtilisin/kexin type 9, LPA, APOE, cadherin-1) and 1 systolic blood pressure-related (fibroblast growth factor 5) protein. However, 4 proteins showed directionally discordant MR results, including 2 lipid-related (APOA5, SORT1) and 1 inflammation-related (transforming growth factor beta 1) proteins with strong colocalization evidence of shared gene-protein-IHD associations (PPH4 ≥0.8). Comparison with previous MR studies revealed little consistency across studies in the number and identity of target proteins for IHD beyond well-established lipid-related (low-density lipoprotein cholesterol, lipoprotein(a), and triglycerides) or inflammation-related (interleukin-6) protein targets. CONCLUSIONS: The findings support a role for lipid-driven chronic inflammation in IHD etiology, and treatment strategies simultaneously targeting multiple lipid and inflammation pathways should be prioritized for further research to improve drug treatment of IHD beyond statin therapy.

Aged↗

PubMed2024

A Proteogenomic Pipeline for the Analysis of Protein Biosynthesis Errors in the Human Pathogen Candida albicans.

Candida albicans is a diploid pathogen known for its ability to live as a commensal fungus in healthy individuals but causing both superficial infections and disseminated candidiasis in immunocompromised patients where it is associated with high morbidity and mortality. Its success in colonizing the human host is attributed to a wide range of virulence traits that modulate interactions between the host and the pathogen, such as optimal growth rate at 37 °C, the ability to switch between yeast and hyphal forms, and a remarkable genomic and phenotypic plasticity. A fascinating aspect of its biology is a prominent heterogeneous proteome that arises from frequent genomic rearrangements, high allelic variation, and high levels of amino acid misincorporations in proteins. This leads to increased morphological and physiological phenotypic diversity of high adaptive potential, but the scope of such protein mistranslation is poorly understood due to technical difficulties in detecting and quantifying amino acid misincorporation events in complex protein samples. We have developed and optimized mass spectrometry and bioinformatics pipelines capable of identifying rare amino acid misincorporation events at the proteome level. We have also analyzed the proteomic profile of an engineered C. albicans strain that exhibits high level of leucine misincorporation at protein CUG sites and employed an in vivo quantitative gain-of-function fluorescence reporter system to validate our LC-MS/MS data. C. albicans misincorporates amino acids above the background level at protein sites of diverse codons, particularly at CUG, confirming our previous data on the quantification of leucine incorporation at single CUG sites of recombinant reporter proteins, but increasing misincorporation of Leucine at these sites does not alter the translational fidelity of the other codons. These findings indicate that the C. albicans statistical proteome exceeds prior estimates, suggesting that its highly plastic phenome may also be modulated by environmental factors due to translational ambiguity.

Candida albicans↗

PubMed2026

Spatial proteogenomic profiling uncovers sensitization strategies for antibody-drug conjugate in HER2-positive breast cancer.

Antibody-drug conjugates (ADCs) have transformed the treatment of HER2-positive breast cancer, yet resistance remains poorly understood. Using imaging mass cytometry, we profiled 157 regions of interest comprising 912,360 single cells from 47 HER2-positive/hormone receptor-negative breast cancers treated with SHR-A1811 in the FASCINATE-N trial. Spatial proteomic analyses identified two determinants of ADC response: elevated tumor-cell H3K27ac expression was associated with improved ADC efficacy, whereas collagen-positive fibroblasts mediated resistance. Combining ADC with the histone deacetylase inhibitor chidamide or the collagen-modulating agent losartan produced synergistic antitumor effects in preclinical models. These biomarkers and therapeutic vulnerabilities were independently validated in patients with advanced HER2-positive disease receiving trastuzumab deruxtecan. Moreover, based on these spatial features, we developed a clinically applicable ADC barrier prediction model that can be implemented using multiplex immunofluorescence. Taken together, our findings reveal actionable spatial determinants of ADC efficacy and suggest potential combination therapeutic strategies.

Humans↗

PubMed2026

Diet-responsive proteogenomic effects following short-term restriction of animal products in humans.

The effect of diet on genetic regulation in humans remains largely unexplored. Here, we investigate gene-diet interactions in a unique group of healthy individuals (N = 200) who alternate between omnivory and dietary restriction of animal products for religious reasons. Using longitudinal proteomic and genotype data, we identify diet-responsive cis-pQTLs and highlight regulatory effects on LBR and MSRA, proteins involved in cholesterol and methionine metabolism respectively. LBR-associated cis-pQTL rs74148404 colocalizes with obesity exclusively under dietary restriction, suggesting diet-dependent modulation of genetic risk. We also show that a diet-dependent cis-pQTL for metabolic regulator FGF21 colocalizes with eosinophil and platelet traits pointing to diet-sensitive immunometabolic signalling. By parallel profiling of a continuously omnivorous control group (N = 211), we uncover seasonally dynamic genetic regulation for proteins linked to apoptosis in immune system pathways (MAVS, CASP3, PDLIM7, IL12RB1), effects likely masked by animal product restriction. These findings reveal dynamic diet- and season-sensitive regulatory mechanisms with implications for precision nutrition and individualized disease prevention strategies, and underscore the need to integrate environmental context into genetic studies of health and disease.

Humans↗

PubMed2025

The proteogenomic landscape of the human kidney and implications for cardio-kidney-metabolic health.

Nearly one-third of the global population is affected by cardio-kidney-metabolic (CKM) diseases; however, the molecular mechanisms underlying CKM diseases are poorly understood. Here we show that tissue proteomics provide critical insights not captured by tissue gene expression or blood proteomics information by performing whole-genome and RNA sequencing and proteomics analysis of human kidney samples (n = 337), and we generated a publicly available database. Via Bayesian co-localization and Mendelian randomization analyses of kidney protein quantitative trait loci and 36 CKM genome-wide association studies, we prioritized 89 proteins for CKM traits. We prioritized relationships that could underlie the interconnectedness of CKM traits and discovered multiple and targetable mechanisms for CKM diseases, including the potential role of kidney angiopoietin-like protein 3 (ANGPTL3) in serum lipid levels and kidney function as well as the role of charged multivesicular body protein 1A in kidney function and hypertension. Notably, we identify pathways with confluence of evidence from genetic loci, tissue gene expression and protein levels for CKM traits. In summary, our large-scale kidney proteomics study uncovers proteins and targetable mechanisms prioritized for CKM diseases.

Humans↗

PubMed2026

Integrative proteogenomic and observational analysis identifies potential biomarkers for latent autoimmune diabetes in adults.

BACKGROUND: Latent autoimmune diabetes in adults (LADA) shares core genetic and immunological features with type 1 diabetes (T1D) but is frequently misdiagnosed as type 2 diabetes (T2D). With few biomarkers for its timely diagnosis and management, this study integrated proteome-wide Mendelian randomisation (MR) and observational clinical analysis to identify potential LADA biomarkers. METHODS: We performed proteome-wide MR using cis-protein quantitative trait loci (cis-pQTLs) for 1,389 plasma proteins from the deCODE study (n = 35,559) and genome-wide association study (GWAS) data for LADA (2,634 cases and 5,947 controls, European ancestry). Robustness was enhanced via multiple sensitivity analyses. Pathway enrichment analysis, druggability evaluation, phenome-wide MR, and interaction analyses were performed to investigate the clinical relevance and biological context of candidate proteins. Candidate proteins were further evaluated using enzyme-linked immunosorbent assays in a matched Chinese clinical study (n = 241) to assess their discriminative ability for LADA. RESULTS: Proteome-wide MR and colocalisation analyses indicated associations between genetically predicted plasma levels of C-X-C motif chemokine ligand 10 (CXCL10; OR [95% CI] per 1-SD increase in protein levels: 5.49 [1.74,17.32]), serum amyloid A1 (SAA1; 1.28 [1.14,1.45]), and SAA2 (1.22 [1.11,1.34]) with LADA risk. Replication, multi-tissue eQTL, and multivariable MR supported CXCL10's association. Druggability evaluation suggested CXCL10 as a drug target under investigation, and phenome-wide MR of 1,006 diseases and traits indicated no major safety concerns for CXCL10 as a potential biomarker. In the observational clinical study, CXCL10 differentiated LADA from healthy controls (area under the receiver operating characteristic curve [ROC-AUC]: 0.889; precision-recall area under the curve [PR-AUC]: 0.919) and T2D (ROC-AUC: 0.838; PR-AUC: 0.921), with both models showing adequate calibration. CONCLUSIONS: This study suggests that CXCL10 is a putative biomarker associated with LADA, demonstrating discriminative ability to distinguish LADA from T2D in an observational clinical cohort. These findings contribute to understanding the autoimmune molecular aetiology of LADA and support its diagnostic potential in resolving the clinical ambiguity between LADA and T2D.

Humans↗

PubMed2025

UALCAN Mobile, an app for cancer proteogenomic data analysis.

Cancer is a complex disease affecting various organs and is a major cause of death worldwide. During cancer initiation, disease progression, and tumor metastasis, various genomic and proteomic alterations are observed. Recent technological advances have led to the generation of large amounts of molecular data, including genomics and transcriptomics. These large-scale datasets can be utilized to analyze and identify sub-class-specific cancer biomarkers and targets. However, there is a need for the development of user-friendly tools for large-scale data analysis, disseminating the analyzed data in a visualizable format to cancer researchers with no programming skills. We developed UALCAN, a comprehensive platform that allows users to integrate disparate data to better understand the genes, proteins, and pathways perturbed in cancer and make discoveries of potential biomarkers and targets. In the current study, we describe the development of the UALCAN Mobile application (app) that will provide cancer transcriptomic data obtained from The Cancer Genome Atlas (TCGA) project to evaluate protein-coding gene expression based on various stratifications, including stage, grade, race, gender, and molecular-subtypes across over 30 types of cancers. In addition, the UALCAN mobile provides data analysis options for epigenetic changes due to DNA promoter methylation and Clinical Proteomic Tumor Analysis Consortium (CPTAC) cancer proteomic data. The app provides access to large cancer molecular datasets on the go. To find changes in the expression of causative genes and proteins and to identify biomarkers and therapeutic targets, UALCAN mobile app will be extremely valuable. The "UALCAN Mobile" app is free to use and can be downloaded from both the iOS/Apple and the Android Play Store and has been downloaded over 100 times in each of iOS and android app stores.

app↗

PubMed2025

CSF proteogenomics implicates novel proteins and humoral immunity in Alzheimer's disease risk.

We profiled 2,961 cerebrospinal fluid (CSF) proteins in 1,005 participants of the Alzheimer's Disease Neuroimaging Initiative (ADNI), including 1,066 proteins not measured in prior studies, using mass spectrometry (MS). We mapped protein quantitative trait loci (pQTLs) in CSF, compared them with brain and plasma pQTLs, and integrated them with Alzheimer's disease (AD) genome-wide association study (GWAS) data. We identified 1,417 index cis pQTLs for 654 unique genes and 130 index trans pQTLs for 94 unique genes. Cross-tissue and cross-proteomic-platform comparisons show broad consistency between MS-based CSF pQTLs and MS-based brain pQTLs as well as affinity-based CSF and plasma pQTLs. Lastly, through integrating CSF pQTLs with the largest AD GWAS, we identified 24 candidate AD causal proteins in CSF, including 10 novel and 14 previously identified in either brain, CSF, or plasma using similar approaches. These CSF AD candidate causal proteins are involved in immune response - notably humoral immunity (3 of 24) - that expands the role of the immune system in AD beyond innate immunity, as well as lysosomal function and neurovascular growth and remodeling. Together, our findings provide novel insights into AD biology and new targets for biomarker and therapeutic development.

Journal Article↗

PubMed2026

Cross-tissue Mendelian randomization prioritizes RAB27B as a brain-derived candidate protein for postpartum depression.

OBJECTIVE: Postpartum depression (PPD) is one of the most common and debilitating complications of childbirth, yet the candidate proteins linking genetic risk to disease remain poorly defined. Building on recent genome-wide association studies (GWAS), we sought to integrate cross-tissue proteogenomic data to identify candidate proteins for PPD and explore therapeutic opportunities. METHODS: We conducted two-sample Mendelian randomization (MR) using genome-wide significant cis-protein QTLs from brain (n = 608 proteins), cerebrospinal fluid (CSF; n = 214), and plasma (n = 612). PPD summary statistics were obtained from FinnGen R8 (13,657 cases, 236,178 controls) and replicated in an independent GWAS. Phenome-wide association (PheWAS) was used to assess pleiotropy. Potential therapeutic targets were evaluated through DSigDB drug repurposing, molecular docking, and molecular dynamics simulations. RESULTS: Among all proteins tested, RAB27B was the only brain-derived protein surpassing Bonferroni correction (OR = 1.60; 95% CI: 1.30-1.96; P = 6.6 × 10⁻⁶), whereas no significant proteins were identified in CSF or plasma. This association was replicated in an independent GWAS (OR = 1.27; 95% CI: 1.02-1.58; P = 0.037). PheWAS identified no pleiotropic associations at genome-wide significance. In silico drug repurposing identified pregnenolone as a candidate ligand with computationally predicted stable binding to RAB27B, providing a starting point for future experimental validation. CONCLUSION: This study provides the first cross-tissue proteogenomic evidence that RAB27B is a brain-derived, reproducible candidate protein genetically associated with PPD. By extending GWAS signals to functional protein-level mechanisms and therapeutic inference, our findings nominate RAB27B and pregnenolone as promising directions for postpartum psychiatric research.

Humans↗

PubMed2025

Integrating multi-omics approaches in acute myeloid leukemia (AML): Advancements and clinical implications.

Acute myeloid leukemia (AML) is a highly heterogeneous and aggressive hematologic malignancy characterized by clonal proliferation of myeloid precursors. Despite significant advancements in genomic profiling and targeted therapies, patient outcomes remain suboptimal due to disease complexity, resistance mechanisms, and high relapse rates. The integration of multi-omics approaches-spanning genomics, epigenomics, transcriptomics, proteomics, and metabolomics-has revolutionized AML research, offering a comprehensive understanding of leukemogenesis, tumor heterogeneity, and therapeutic vulnerabilities. Recent studies leveraging high-throughput sequencing, mass spectrometry, and advanced computational tools have uncovered novel biomarkers, clonal evolution dynamics, and microenvironmental interactions that drive AML progression and resistance. For instance, single-cell multi-omics has revealed chemotherapy-resistant leukemic stem cell populations, while proteogenomic analyses have identified actionable targets such as MCL1 and metabolic dependencies like OXPHOS. Clinically, integrated omics platforms are refining risk stratification, minimal residual disease (MRD) monitoring, and personalized therapy selection. However, challenges such as data integration complexity, cost barriers, and ethical considerations remain. This review highlights the transformative potential of multi-omics in AML, emphasizing recent advancements in technology, biomarker discovery, and therapeutic innovation. By bridging the gap between molecular insights and clinical practice, multi-omics integration promises to redefine AML management, paving the way for precision oncology and improved patient outcomes.

Humans↗

PubMed2026

The mighty microproteins: from versatile cellular regulators to precision medicine therapeutics.

Microproteins, are tiny proteins encoded by small open reading frame (sORF), translation of these non-canonical open reading frames (ncORFs) has been implicated in diverse biological processes and diseases. This review summarizes recent developments in the discovery, biogenesis, and functional characterization of microproteins, and their involvement in various disease, with special focus on their roles in cancer, cardiovascular, metabolic, neurodegenerative and immune-related disorders. We emphasize the regulation of key cellular pathways by microproteins, including mitochondrial homeostasis, apoptosis, metabolic reprogramming, and immune signaling, all of which affect disease initiation and progression. Emerging evidence also supports their potential as disease biomarkers and therapeutic candidates for precision medicine. Finally, the review critically discusses the current challenges including discrepancies in microprotein annotation, the limitations of ribosome profiling and proteogenomic approaches, the gap between computationally predicted and experimentally validated microproteins, and the need for rigorous orthogonal validation by means of CRISPR-based genome editing, ribosome release assays, mutational analysis, high-resolution mass spectrometry, and functional studies. Finally, we review recent development of AI-assisted ORF prediction, single-cell translatomics, spatial proteomics, and integrated multi-omics as emerging technologies reshaping. Microprotein discovery and functional annotation. Finally, we discuss the translational potential of microproteins and highlight the remaining challenges to clinical application, including peptide stability, pharmacokinetics, tissue-specific delivery, immunogenicity, and the need for rigorous preclinical and clinical validation. Together, this review provides an updated and critical overview of the rapidly evolving microprotein field and highlights future research priorities for translating these molecules into clinically useful biomarkers and precision therapeutics.

Microproteins↗