The Eµ-Ret mouse is a novel model of hyperdiploid B-cell acute lymphoblastic leukemia.

The presence of supernumerary chromosomes is the only abnormality shared by all patients diagnosed with high-hyperdiploid B cell acute lymphoblastic leukemia (HD-ALL). Despite being the most frequently diagnosed pediatric leukemia, the lack of clonal molecular lesions and complete absence of appropriate experimental models have impeded the elucidation of HD-ALL leukemogenesis. Here, we report that for 23 leukemia samples isolated from moribund Eµ-Ret mice, all were characterized by non-random chromosomal gains, involving combinations of trisomy 9, 12, 14, 15, and 17. With a median gain of three chromosomes, leukemia emerged after a prolonged latency from a preleukemic B cell precursor cell population displaying more diverse aneuploidy. Transition from preleukemia to overt disease in Eµ-Ret mice is associated with acquisition of heterogeneous genomic abnormalities affecting the expression of genes implicated in pediatric B-ALL. The development of abnormal centrosomes in parallel with aneuploidy renders both preleukemic and leukemic cells sensitive to inhibitors of centrosome clustering, enabling targeted in vivo depletion of leukemia-propagating cells. This study reveals the Eµ-Ret mouse to be a novel tool for investigating HD-ALL leukemogenesis, including supervision and selection of preleukemic aneuploid clones by the immune system and identification of vulnerabilities that could be targeted to prevent relapse.

Targetable lesions and proteomes predict therapy sensitivity through disease evolution in pediatric acute lymphoblastic leukemia.

Childhood acute lymphoblastic leukemia (ALL) genomes show that relapses often arise from subclonal outgrowths. However, the impact of clonal evolution on the actionable proteome and response to targeted therapy is not known. Here, we present a comprehensive retrospective analysis of paired ALL diagnosis and relapsed specimen. Targeted next generation sequencing and proteome analysis indicate persistence of actionable genome variants and stable proteomes through disease progression. Paired viably-frozen biopsies show high correlation of drug response to variant-targeted therapies but in vitro selectivity is low. Proteome analysis prioritizes PARP1 as a pan-ALL target candidate needed for survival following cellular stress; diagnostic and relapsed ALL samples demonstrate robust sensitivity to treatment with two PARP1/2 inhibitors. Together, these findings support initiating prospective precision oncology approaches at ALL diagnosis and emphasize the need to incorporate proteome analysis to prospectively determine tumor sensitivities, which are likely to be retained at disease relapse.

Positional proteomics: is the technology ready to study clinical cohorts?

INTRODUCTION: Positional proteomics provides proteome-wide information on protein termini and their modifications, uniquely enabling unambiguous identification of site-specific, limited proteolysis. Such proteolytic cleavage irreversibly modifies protein sequences resulting in new proteoforms with distinct protease-generated neo-N and C-termini and altered localization and activity. Misregulated proteolysis is implicated in a wide variety of human diseases. Protein termini, therefore, constitute a huge, largely unexplored source of specific analytes that provides a deep view into the functional proteome and a treasure trove for biomarkers. AREAS COVERED: We briefly review principal approaches to define protein termini and discuss recent advances in method development. We further highlight the potential of positional proteomics to identify and trace specific proteoforms, with a focus on proteolytic processes altered in disease. Lastly, we discuss current challenges and potential for applying positional proteomics in biomarker and pre-clinical research. EXPERT OPINION: Recent developments in positional proteomics have provided significant advances in sensitivity and throughput. In-depth analysis of proteolytic processes in clinical cohorts thus appears feasible in the near future. We argue that this will provide insights into the functional state of the proteome and offer new opportunities to utilize proteolytic processes altered or targeted in disease as specific diagnostic, prognostic and companion biomarkers.

Shift of the insoluble content of the proteome in the aging mouse brain.

During aging, the cellular response to unfolded proteins is believed to decline, resulting in diminished proteostasis. In model organisms, such as Caenorhabditis elegans, proteostatic decline with age has been linked to proteome solubility shifts and the onset of protein aggregation. However, this correlation has not been extensively characterized in aging mammals. To uncover age-dependent changes in the insoluble portion of a mammalian proteome, we analyzed the detergent-insoluble fraction of mouse brain tissue by mass spectrometry. We identified a group of 171 proteins, including the small heat shock protein α-crystallin, that become enriched in the detergent-insoluble fraction obtained from old mice. To enhance our ability to detect features associated with proteins in that fraction, we complemented our data with a meta-analysis of studies reporting the detergent-insoluble proteins in various mouse models of aging and neurodegeneration. Strikingly, insoluble proteins from young and old mice are distinct in several features in our study and across the collected literature data. In younger mice, proteins are more likely to be disordered, part of membraneless organelles, and involved in RNA binding. These traits become less prominent with age, as an increased number of structured proteins enter the pellet fraction. This analysis suggests that age-related changes to proteome organization lead a group of proteins with specific features to become detergent-insoluble. Importantly, these features are not consistent with those associated with proteins driving membraneless organelle formation. We see no evidence in our system of a general increase of condensate proteins in the detergent-insoluble fraction with age.

Adaptation of the Th-MYCN Mouse Model of Neuroblastoma for Evaluation of Disseminated Disease.

High-risk neuroblastoma remains a profound clinical challenge that requires eradication of neuroblastoma cells from a variety of organ sites, including bone marrow, liver, and CNS, to achieve a cure. While preclinical modeling is a powerful tool for the development of novel cancer therapies, the lack of widely available models of metastatic neuroblastoma represents a significant barrier to the development of effective treatment strategies. To address this need, we report a novel luciferase-expressing derivative of the widely used Th-MYCN mouse. While our model recapitulates the non-metastatic neuroblastoma development seen in the parental transgenic strain, transplantation of primary tumor cells from disease-bearing mice enables longitudinal monitoring of neuroblastoma growth at distinct sites in immune-deficient or immune-competent recipients. The transplanted tumors retain GD2 expression through many rounds of serial transplantation and are sensitive to GD2-targeted immune therapy. With more diverse tissue localization than is seen with human cell line-derived xenografts, this novel model for high-risk neuroblastoma could contribute to the optimization of immune-based treatments for this deadly disease.

RNA Polymerase II transcription independent of TBP in murine embryonic stem cells.

Transcription by RNA Polymerase II (Pol II) is initiated by the hierarchical assembly of the pre-initiation complex onto promoter DNA. Decades of research have shown that the TATA-box binding protein (TBP) is essential for Pol II loading and initiation. Here, we report instead that acute depletion of TBP in mouse embryonic stem cells has no global effect on ongoing Pol II transcription. In contrast, acute TBP depletion severely impairs RNA Polymerase III initiation. Furthermore, Pol II transcriptional induction occurs normally upon TBP depletion. This TBP-independent transcription mechanism is not due to a functional redundancy with the TBP paralog TRF2, though TRF2 also binds to promoters of transcribed genes. Rather, we show that the TFIID complex can form and, despite having reduced TAF4 and TFIIA binding when TBP is depleted, the Pol II machinery is sufficiently robust in sustaining TBP-independent transcription.

ASAP─Automated Sonication-Free Acid-Assisted Proteomes─from Cells and FFPE Tissues.

Formalin-fixed, paraffin-embedded (FFPE) tissues are an invaluable resource for retrospective studies, but protein extraction and subsequent sample processing steps have been shown to be challenging for mass spectrometry (MS) analysis. Streamlined high-throughput sample preparation workflows are essential for efficient peptide extraction from complex clinical specimens such as fresh frozen tissues or FFPE. Overall, proteome analysis has gained significant improvements in the instrumentation, acquisition methods, sample preparation workflows, and analysis pipelines, yet even the most recent FFPE workflows remain complex and are not readily scalable. Here, we present an optimized workflow for automated sonication-free acid-assisted proteome (ASAP) extraction from FFPE sections. ASAP enables efficient protein extraction from FFPE specimens, achieving similar proteome coverage as established methods using expensive sonicators, resulting in reduced sample processing time. The broad applicability of ASAP on archived pediatric tumor FFPE specimens resulted in high-quality data with increased proteome coverage and quantitative reproducibility. Our study demonstrates the practicality and superiority of the ASAP workflow as a streamlined, time- and cost-effective pipeline for high-throughput FFPE proteomics of clinical specimens.

SQuAPP-simple quantitative analysis of proteins and PTMs.

SUMMARY: The comprehensive analysis of the proteome and its modulation by post-translational modification (PTM) is increasingly used in biological and biomedical studies. As a result, proteomics data analysis is ever more carried out by scientists with limited expertise in this type of data. While excellent software solutions for comprehensive and rigorous analysis of quantitative proteomic data exist, most are complex and not well suited for non-proteomics scientists. Integrative analysis of multi-level proteomics data on protein and diverse PTMs, like phosphorylation or proteolytic processing, remains particularly challenging and inaccessible to most biologists. To fill this void, we developed SQuAPP, an R-Shiny web-based analysis pipeline for the quantitative analysis of proteomic data. SQuAPP uses a streamlined workflow model to guide expert and novice users through quality control, data pre-processing, statistical analysis and visualization steps. Processing the protein, peptide and PTM datasets in parallel and their quantitative integration enable rapid identification of protein-level-independent modulation of protein modifications and intuitive interpretation of dynamic dependencies between different protein modifications. AVAILABILITY AND IMPLEMENTATION: SQuAPP is available at http://squapp.langelab.org/. The source code and local setup instructions can be accessed from https://github.com/LangeLab/SQuAPP.

Multi-omic profiling of the leukemic microenvironment shows bone marrow interstitial fluid is distinct from peripheral blood plasma.

BACKGROUND: The bone marrow is the place of hematopoiesis with a microenvironment that supports lifelong maintenance of stem cells and high proliferation. It is not surprising that this environment is also favourable for malignant cells emerging in the bone marrow or metastasizing to it. While the cellular composition of the bone marrow microenvironment has been extensively studied, the extracellular matrix and interstitial fluid components have received little attention. Since the sinusoids connect the bone marrow interstitial fluid to the circulation, it is often considered to have the same composition as peripheral blood plasma. Stark differences in the cellular composition of the bone marrow and peripheral blood with different secretory capacities would however suggest profound differences. METHODS: In this study we set out to better define if and how the bone marrow interstitial fluid (BMIF) compares to the peripheral blood plasma (PBP) and how both are remodeled during chemotherapy. We applied a multi-omic strategy to quantify the metabolite, lipid and protein components as well as the proteolytic modification of proteins to gain a comprehensive understanding of the two compartments. RESULTS: We found that the bone marrow interstitial fluid is clearly distinct from peripheral blood plasma, both during active pediatric acute lymphoblastic leukemia and following induction chemotherapy. Either compartment was shaped differently by active leukemia, with the bone marrow interstitial fluid being rich in extracellular vesicle components and showing protease dysregulation while the peripheral blood plasma showed elevation of immune regulatory proteins. Following chemotherapy, the BMIF showed signs of cellular remodeling and impaired innate immune activation while the peripheral blood plasma was characterized by restored lipid homeostasis. CONCLUSION: This study provides a comprehensive examination of the fluid portion of the acute lymphoblastic leukemia microenvironment and finds the contribution of either microenvironment to tumourigenesis.

Isolation of Detergent Insoluble Proteins from Mouse Brain Tissue for Quantitative Analysis Using Data Independent Acquisition (DIA).

Enrichment of detergent insoluble proteins is a commonly used technique for analyzing proteins that may be aggregating in disease or with age. However, various methods for enriching for these proteins are used. Here we present a method using a mild detergent (Triton X-100) and high centrifugation speed (20,000 × g) allowing for sufficient protein extraction and enrichment for large protein assemblies. Digestion is performed on columns allowing for a methanol chloroform wash to remove the highly prevalent lipids in brain tissue. This is followed by analysis by data independent acquisition mass spectrometry, which we have found to be highly reproducible. Our method is intended to enrich for amorphous aggregates, which may accumulate upon the collapse of protein homeostasis.

HUNTER: Sensitive Automated Characterization of Proteolytic Systems by N Termini Enrichment from Microscale Specimen.

Proteolysis occurs at low frequency in the cellular environment. Protein N termini reveal essential mechanisms associated with cellular functions, and are useful indicators to track dysfunctional regulation of proteins and pathways in diseases. N terminomics has so far relied on labor-intensive methods, which require relatively large starting sample amounts rendering it ill-suited for high-throughput systems biology studies. Here, we describe protocols for the first scalable and automatable method for sensitive enrichment and identification of N termini from minute samples.

Pathogenic BRCA1 variants disrupt PLK1-regulation of mitotic spindle orientation.

Preneoplastic mammary tissues from human female BRCA1 mutation carriers, or Brca1-mutant mice, display unexplained abnormalities in luminal differentiation. We now study the division characteristics of human mammary cells purified from female BRCA1 mutation carriers or non-carrier donors. We show primary BRCA1 mutant/+ cells exhibit defective BRCA1 localization, high radiosensitivity and an accelerated entry into cell division, but fail to orient their cell division axis. We also analyse 15 genetically-edited BRCA1 mutant/+ human mammary cell-lines and find that cells carrying pathogenic BRCA1 mutations acquire an analogous defect in their division axis accompanied by deficient expression of features of mature luminal cells. Importantly, these alterations are independent of accumulated DNA damage, and specifically dependent on elevated PLK1 activity induced by reduced BRCA1 function. This essential PLK1-mediated role of BRCA1 in controlling the cell division axis provides insight into the phenotypes expressed during BRCA1 tumorigenesis.

Modification of BRCA1-associated breast cancer risk by HMMR overexpression.

Breast cancer risk for carriers of BRCA1 pathological variants is modified by genetic factors. Genetic variation in HMMR may contribute to this effect. However, the impact of risk modifiers on cancer biology remains undetermined and the biological basis of increased risk is poorly understood. Here, we depict an interplay of molecular, cellular, and tissue microenvironment alterations that increase BRCA1-associated breast cancer risk. Analysis of genome-wide association results suggests that diverse biological processes, including links to BRCA1-HMMR profiles, influence risk. HMMR overexpression in mouse mammary epithelium increases Brca1-mutant tumorigenesis by modulating the cancer cell phenotype and tumor microenvironment. Elevated HMMR activates AURKA and reduces ARPC2 localization in the mitotic cell cortex, which is correlated with micronucleation and activation of cGAS-STING and non-canonical NF-κB signaling. The initial tumorigenic events are genomic instability, epithelial-to-mesenchymal transition, and tissue infiltration of tumor-associated macrophages. The findings reveal a biological foundation for increased risk of BRCA1-associated breast cancer.

Sensitive Identification of Known and Unknown Protease Activities by Unsupervised Linear Motif Deconvolution.

The cleavage-site specificities for many proteases are not well understood, restricting the utility of supervised classification methods. We present an algorithm and web interface to overcome this limitation through the unsupervised detection of overrepresented patterns in protein sequence data, providing insight into the mixture of protease activities contributing to a complex system. Here, we apply the RObust LInear Motif Deconvolution (RoLiM) algorithm to confidently detect substrate cleavage patterns for SARS-CoV-2 MPro protease in the N-terminome data of an infected human cell line. Using mass spectrometry-based peptide data from a case-control comparison of 341 primary urothelial bladder cancer cases and 110 controls, we identified distinct sequence motifs indicative of increased matrix metallopeptidase activity in urine from cancer patients. The evaluation of N-terminal peptides from patient plasma post-chemotherapy detected novel granzyme B/corin activity. RoLiM will enhance the unbiased investigation of peptide sequences to establish the composition of known and uncharacterized protease activities in biological systems. RoLiM is available at http://langelab.org/rolim/.

A cross-standardized flow cytometry platform to assess phenotypic stability in precursor B-cell acute lymphoblastic leukemia (B-ALL) xenografts.

With the continued poor outcome of relapsed acute lymphoblastic leukemia (ALL), new patient-specific approaches for disease progression monitoring and therapeutic intervention are urgently needed. Patient-derived xenografts (PDX) of primary ALL in immune-deficient mice have become a powerful tool for studying leukemia biology and therapy response. In PDX mice, the immunophenotype of the patient's leukemia is commonly believed to be stably propagated. In patients, however, the surface marker expression profile of the leukemic population often displays poorly understood immunophenotypic shifts during chemotherapy and ALL progression. We therefore developed a translational flow cytometry platform to study whether the patient-specific immunophenotype is faithfully recapitulated in PDX mice. To enable valid assessment of immunophenotypic stability and subpopulation complexity of the patient's leukemia after xenotransplantation, we comprehensively immunophenotyped diagnostic B-ALL from children and their matched PDX using identical, clinically standardized flow protocols and instrument settings. This cross-standardized approach ensured longitudinal stability and cross-platform comparability of marker expression intensity at high phenotyping depth. This analysis revealed readily detectable changes to the patient leukemia-associated immunophenotype (LAIP) after xenotransplantation. To further investigate the mechanism underlying these complex immunophenotypic shifts, we applied an integrated analytical approach that combined clinical phenotyping depth and high analytical sensitivity with unbiased high-dimensional algorithm-based analysis. This high-resolution analysis revealed that xenotransplantation achieves patient-specific propagation of phenotypically stable B-ALL subpopulations and that the immunophenotypic shifts observed at the level of bulk leukemia were consistent with changes in underlying subpopulation abundance. By incorporating the immunophenotypic complexity of leukemic populations, this novel cross-standardized analytical platform could greatly expand the utility of PDX for investigating ALL progression biology and assessing therapies directed at eliminating relapse-driving leukemic subpopulations.

Robust unsupervised deconvolution of linear motifs characterizes 68 protein modifications at proteome scale.

The local sequence context is the most fundamental feature determining the post-translational modification (PTM) of proteins. Recent technological improvements allow for the detection of new and less prevalent modifications. We found that established state-of-the-art algorithms for the detection of PTM motifs in complex datasets failed to keep up with this technological development and are no longer robust. To overcome this limitation, we developed RoLiM, a new linear motif deconvolution algorithm and webserver, that enables robust and unbiased identification of local amino acid sequence determinants in complex biological systems demonstrated here by the analysis of 68 modifications found across 30 tissues in the human draft proteome map. Furthermore, RoLiM analysis of a large-scale phosphorylation dataset comprising 30 kinase inhibitors of 10 protein kinases in the EGF signalling pathway identified prospective substrate motifs for PI3K and EGFR.

PDX models reflect the proteome landscape of pediatric acute lymphoblastic leukemia but divert in select pathways.

BACKGROUND: Murine xenografts of pediatric leukemia accurately recapitulate genomic aberrations. How this translates to the functional capacity of cells remains unclear. Here, we studied global protein abundance, phosphorylation, and protein maturation by proteolytic processing in 11 pediatric B- and T- cell ALL patients and 19 corresponding xenografts. METHODS: Xenograft models were generated for each pediatric patient leukemia. Mass spectrometry-based methods were used to investigate global protein abundance, protein phosphorylation, and limited proteolysis in paired patient and xenografted pediatric acute B- and T- cell lymphocytic leukemia, as well as in pediatric leukemia cell lines. Targeted next-generation sequencing was utilized to examine genetic abnormalities in patients and in corresponding xenografts. Bioinformatic and statistical analysis were performed to identify functional mechanisms associated with proteins and protein post-translational modifications. RESULTS: Overall, we found xenograft proteomes to be most equivalent with their patient of origin. Protein level differences that stratified disease subtypes at diagnostic and relapse stages were largely recapitulated in xenografts. As expected, PDXs lacked multiple human leukocyte antigens and complement proteins. We found increased expression of cell cycle proteins indicating a high proliferative capacity of xenografted cells. Structural genomic changes and mutations were reflected at the protein level in patients. In contrast, the post-translational modification landscape was shaped by leukemia type and host and only to a limited degree by the patient of origin. Of 201 known pediatric oncogenic drivers and drug-targetable proteins, the KMT2 protein family showed consistently high variability between patient and corresponding xenografts. Comprehensive N terminomics revealed deregulated proteolytic processing in leukemic cells, in particular from caspase-driven cleavages found in patient cells. CONCLUSION: Genomic and host factors shape protein and post-translational modification landscapes differently. This study highlights select areas of diverging biology while confirming murine patient-derived xenografts as a generally accurate model system.

Detectability of Biotin Tags by LC-MS/MS.

The high affinity of biotin to streptavidin has made it one of the most widely used affinity tags in proteomics. Early methods used biotin for enrichment alone and mostly ignored the biotin-labeled peptide. Recent advances in labeling have led to an increase in biotinylation efficiency and shifted the interest to the detection of the site of biotinylation. This has increased the confidence in identification and provided additional structural information, yet it requires the efficient release of the biotinylated protein/peptide and the sensitive separation and detection of biotinylated peptides by LC-MS/MS. Despite its long use in affinity proteomics, the effect of biotinylation on the chromatographic, ionization, and fragmentation behavior and the ultimate detection of peptides is not well understood. To address this, we compare two commercially available biotin labels, EZ-Link Sulfo-NHS-Biotin and Sulfo-NHS-SS-Biotin, the latter containing a labile linker to efficiently release biotin to determine the effects of peptide modification on peptide detection. We describe an increase in the hydrophobicity and charge reduction with an increasing number of biotin labels attached. On the basis of our data, we recommend gradient optimization to account for more hydrophobic biotinylated peptides and include singly charged precursors to account for charge reduction by biotin.

Multi-Omic Approach to Identify Phenotypic Modifiers Underlying Cerebral Demyelination in X-Linked Adrenoleukodystrophy.

X-linked adrenoleukodystrophy (ALD) is a peroxisomal metabolic disorder with a highly complex clinical presentation. ALD is caused by mutations in the ABCD1 gene, and is characterized by the accumulation of very long-chain fatty acids in plasma and tissues. Disease-causing mutations are 'loss of function' mutations, with no prognostic value with respect to the clinical outcome of an individual. All male patients with ALD develop spinal cord disease and a peripheral neuropathy in adulthood, although age of onset is highly variable. However, the lifetime prevalence to develop progressive white matter lesions, termed cerebral ALD (CALD), is only about 60%. Early identification of transition to CALD is critical since it can be halted by allogeneic hematopoietic stem cell therapy only in an early stage. The primary goal of this study is to identify molecular markers which may be prognostic of cerebral demyelination from a simple blood sample, with the hope that blood-based assays can replace the current protocols for diagnosis. We collected six well-characterized brother pairs affected by ALD and discordant for the presence of CALD and performed multi-omic profiling of blood samples including genome, epigenome, transcriptome, metabolome/lipidome, and proteome profiling. In our analysis we identify discordant genomic alleles present across all families as well as differentially abundant molecular features across the omics technologies. The analysis was focused on univariate modeling to discriminate the two phenotypic groups, but was unable to identify statistically significant candidate molecular markers. Our study highlights the issues caused by a large amount of inter-individual variation, and supports the emerging hypothesis that cerebral demyelination is a complex mix of environmental factors and/or heterogeneous genomic alleles. We confirm previous observations about the role of immune response, specifically auto-immunity and the potential role of PFN1 protein overabundance in CALD in a subset of the families. We envision our methodology as well as dataset has utility to the field for reproducing previous or enabling future modifier investigations.

Fold-Change Compression: An Unexplored But Correctable Quantitative Bias Caused by Nonlinear Electrospray Ionization Responses in Untargeted Metabolomics.

The nonlinear signal response of electrospray ionization (ESI) presents a critical limitation for mass spectrometry (MS)-based quantitative analysis. In the field of metabolomics research, this issue has largely remained unaddressed; MS signal intensities are usually directly used to calculate fold changes for quantitative comparison. In this work, we demonstrate that, due to the nonlinear ESI response, signal intensity ratios of a metabolic feature calculated between two samples may not reflect their real metabolic concentration ratios (i.e., fold-change compression), implying that conventional fold-change calculations directly using MS signal intensities can be misleading. In this regard, we developed a quality control (QC) sample-based signal calibration workflow to overcome the quantitative bias caused by the nonlinear ESI response. In this workflow, calibration curves for every metabolic feature are first established using a QC sample injected in serial injection volumes. The MS signals of each metabolic feature are then calibrated to their equivalent QC injection volumes for comparative analysis. We demonstrated this novel workflow in a targeted metabolite analysis, showing that the accuracy of fold-change calculations can be significantly improved. Furthermore, in a metabolomic comparison of the bone marrow interstitial fluid samples from leukemia patients before and after chemotherapy, an additional 59 significant metabolic features were found with fold changes larger than 1.5, and an additional 97 significant metabolic features had fold changes corrected by more than 0.1. This work enables high-quality quantitative analysis in untargeted metabolomics, thus providing more confident biological hypotheses generation.