To address the increasing need for detecting and validating protein biomarkers in clinical specimens, mass spectrometry (MS)-based targeted proteomic techniques, including the selected reaction monitoring (SRM), parallel reaction monitoring (PRM), and massively parallel data-independent acquisition (DIA), have been developed. For optimal performance, they require the fragment ion spectra of targeted peptides as prior knowledge. In this report, we describe a MS pipeline and spectral resource to support targeted proteomics studies for human tissue samples. To build the spectral resource, we integrated common open-source MS computational tools to assemble a freely accessible computational workflow based on Docker. We then applied the workflow to generate DPHL, a comprehensive DIA pan-human library, from 1096 data-dependent acquisition (DDA) MS raw files for 16 types of cancer samples. This extensive spectral resource was then applied to a proteomic study of 17 prostate cancer (PCa) patients. Thereafter, PRM validation was applied to a larger study of 57 PCa patients and the differential expression of three proteins in prostate tumor was validated. As a second application, the DPHL spectral resource was applied to a study consisting of plasma samples from 19 diffuse large B cell lymphoma (DLBCL) patients and 18 healthy control subjects. Differentially expressed proteins between DLBCL patients and healthy control subjects were detected by DIA-MS and confirmed by PRM. These data demonstrate that the DPHL supports DIA and PRM MS pipelines for robust protein biomarker discovery. DPHL is freely accessible at https://www.iprox.org/page/project.html?id=IPX0001400000.

Splicing factor (SF) mutations are important contributors to the pathogenesis of hematological malignancies; however, their relevance in risk classification of acute myeloid leukemia (AML) warrants further investigation. To gain more insight into the characteristics of patients with AML carrying SF mutations, we studied their association with clinical features, cytogenetic and molecular abnormalities, and clinical outcome in a large cohort of 1447 patients with AML and high-risk myelodysplastic syndrome. SF mutations were identified in 22% of patients and were associated with multiple unfavorable clinical features, such as older age, antecedent myeloid disorders, and adverse risk factors (mutations in RUNX1 and ASXL1). Furthermore, they had significantly shorter event-free and overall survival. Notably, in European LeukemiaNet (ELN) 2017 favorable- and intermediate-risk groups, SF3B1 mutations were indicative of relatively poor prognosis. In addition, patients carrying concomitant SF mutations and RUNX1 mutations had a particularly adverse prognosis. In patients without any of the 4 most common SF mutations, RUNX1 mutations were associated with relatively good outcome, which was comparable to that of intermediate-risk patients. In this study, we propose that SF mutations be considered for incorporation into prognostic classification systems. First, SF3B1 mutations could be considered an intermediate prognostic factor when co-occurring with favorable risk features and as an adverse prognostic factor for patients currently categorized as having intermediate risk, according to the ELN 2017 classification. Second, the prognostic value of the current adverse factor RUNX1 mutations seems to be limited to its co-occurrence with SF mutations.

Glucocorticoid (GC) resistance is a crucial determinant of inferior response to chemotherapy in pediatric acute lymphoblastic leukemia (ALL); however, molecular mechanisms underlying this phenomenon are poorly understood. Deregulated splicing is a common feature of many cancers, which impacts drug response and constitutes an attractive therapeutic target. Therefore, the aim of the current study was to characterize global splicing profiles associated with GC resistance and determine whether splicing modulation could serve as a novel therapeutic option for GC-resistant patients. To this end, 38 primary ALL samples were profiled using RNA-seq-based differential splicing analysis. The impact of splicing modulators was investigated in GC-resistant leukemia cell lines and primary leukemic specimens. Our findings revealed, for the first time, markedly distinct splicing landscapes in ALL samples of B-cell precursor (BCP)-ALL and T-ALL lineages. Differential splicing events associated with GC resistance were involved in RNA processing, a direct response to GCs, survival signaling, apoptosis, cell cycle regulation and energy metabolism. Furthermore, our analyses showed that GC-resistant ALL cell lines and primary samples are sensitive to splicing modulation, alone and in combination with GC. Together, these findings suggest that aberrant splicing is associated with GC resistance and splicing modulators deserve further interest as a novel treatment option for GC-resistant patients.

Non-human primates (NHPs), particularly Macaca fascicularis (cynomolgus macaque), represent an essential model for preclinical assessment of biologics due to their high genetic and physiological similarity to humans. However, mounting regulatory pressure to reduce NHP use and the lack of a unified, well-annotated single-cell atlas currently limits both target qualification and mechanistic interpretation of toxicity in this species. To address this gap, we assembled and harmonized the largest single-cell transcriptomic atlas of M. fascicularis to date, integrating 30 publicly available studies spanning 57 anatomical regions, 43 organs and 14 physiological systems. We implemented a scalable framework for cross-species cell type annotation by embedding both cynomolgus monkeys and human (Tabula Sapiens V2) datasets into a shared reference space using Universal Cell Embeddings (UCE), enabling consistent harmonization of cell identities. In total, 27 organs were annotated using human reference labels, while the remaining sets retained author-provided annotations or labels transferred from other cynomolgus studies with available annotations. The resulting atlas comprises over 2.5 million cells and demonstrates concordance in cell-type-specific expression patterns between cynomolgus and humans, including tissue-specific markers and targets relevant for biologics development. Through translational use cases, we illustrate how this resource can be applied to assess target expression in tissues affected by concordant human-NHP toxicities, investigate ocular adverse events associated with antibody-drug conjugates (ADCs), and identify species-specific features of immune cell subtypes with known safety implications. By enabling scalable, high-resolution, cross-species comparisons of gene expression across organs, tissues, and cell states, this atlas supports improved target qualification, more mechanistic interpretation of toxicities, and evidence-based decisions on the relevance and design of NHP studies. Collectively, this work provides a unified cross-species single-cell resource for cynomolgus monkey and a modular computational framework that advances new approach methodologies and contributes to the refinement and reduction of NHP use in preclinical research.