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

Statistical Testing for Protein Equivalence Identifies Core Functional Modules Conserved across 360 Cancer Cell Lines and Presents a General Approach to Investigating Biological Systems

Quantitative proteomics has enhanced our capability to study protein dynamics and their involvement in disease using various techniques, including statistical testing, to discern the significant differences between conditions. While most focus is on what is different between conditions, exploring similarities can provide valuable insights. However, exploring similarities directly from the analyte level, such as proteins, genes, or metabolites, is not a standard practice and is not widely adopted. In this study, we propose a statistical framework called QuEStVar (Quantitative Exploration of Stability and Variability through statistical hypothesis testing), enabling the exploration of quantitative stability and variability of features with a combined statistical framework. QuEStVar utilizes differential and equivalence testing to expand statistical classifications of analytes when comparing conditions. We applied our method to an extensive data set of cancer cell lines and revealed a quantitatively stable core proteome across diverse tissues and cancer subtypes. The functional analysis of this set of proteins highlighted the molecular mechanism of cancer cells to maintain constant conditions of the tumorigenic environment via biological processes, including transcription, translation, and nucleocytoplasmic transport.

A Comparative Study of B Cell Blast Isolation Methods from Bone Marrow Aspirates of Pediatric Leukemia Patients

Density gradient centrifugation is a conventional technique widely utilized to isolate bone marrow mononuclear cells (BM-MNC) from bone marrow (BM) aspirates obtained from pediatric B-cell acute lymphoblastic leukemia (B-ALL) patients. Nevertheless, this technique achieves incomplete recovery of mononuclear cells and is relatively time-consuming and expensive. Given that B-ALL is the most common childhood malignancy, alternative methods for processing B-ALL samples may be more cost-effective. In this pilot study, we use several readouts, including immune phenotype, cell viability, and leukemia-initiating capacity in immune-deficient mice, to directly compare the density gradient centrifugation and buffy coat processing methods. Our findings indicate that buffy coat isolation yields comparable BM-MNC product in terms of both immune and leukemia cell content and could provide a viable, lower cost alternative for biobanks processing pediatric leukemia samples.

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.

Proteomics in Childhood Acute Lymphoblastic Leukemia: Challenges and Opportunities

Acute lymphoblastic leukemia (ALL) is the most common cancer in children and one of the success stories in cancer therapeutics. Risk-directed therapy based on clinical, biologic and genetic features has played a significant role in this accomplishment. Despite the observed improvement in survival rates, leukemia remains one of the leading causes of cancer-related deaths. Implementation of next-generation genomic and transcriptomic sequencing tools has illustrated the genomic landscape of ALL. However, the underlying dynamic changes at protein level still remain a challenge. Proteomics is a cutting-edge technology aimed at deciphering the mechanisms, pathways, and the degree to which the proteome impacts leukemia subtypes. Advances in mass spectrometry enable high-throughput collection of global proteomic profiles, representing an opportunity to unveil new biological markers and druggable targets. The purpose of this narrative review article is to provide a comprehensive overview of studies that have utilized applications of proteomics in an attempt to gain insight into the pathogenesis and identification of biomarkers in childhood ALL.

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.

SQuAPP – Simple Quantitative Analysis of Proteins & PTMs

Summary

The Comprehensive analysis of the proteome and its modulation by post-translational modification 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 post-translational modifications (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 post-translational modification 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

SQuAPP is available at http://squapp.langelab.org/. The source code and local setup instructions can be accessed from https://github.com/LangeLab/SQuAPP.

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.

Integrative multi-omics and drug response profiling of childhood acute lymphoblastic leukemia cell lines

Acute lymphoblastic leukemia (ALL) is the most common childhood cancer. Although standard-of-care chemotherapeutics are sufficient for most ALL cases, there are subsets of patients with poor response who relapse in disease. The biology underlying differences between subtypes and their response to therapy has only partially been explained by genetic and transcriptomic profiling. Here, we perform comprehensive multi-omic analyses of 49 readily available childhood ALL cell lines, using proteomics, transcriptomics, and pharmacoproteomic characterization. We connect the molecular phenotypes with drug responses to 528 oncology drugs, identifying drug correlations as well as lineage-dependent correlations. We also identify the diacylglycerol-analog bryostatin-1 as a therapeutic candidate in the MEF2D-HNRNPUL1 fusion high-risk subtype, for which this drug activates pro-apoptotic ERK signaling associated with molecular mediators of pre-B cell negative selection. Our data is the foundation for the interactive online Functional Omics Resource of ALL (FORALL) with navigable proteomics, transcriptomics, and drug sensitivity profiles at https://proteomics.se/forall.

Childhood acute lymphoblastic leukemia is characterised by a range of genetic aberrations. Here, the authors use multi-omics profiling of ALL cell lines to connect molecular phenotypes and drug responses to provide an interactive resource of drug sensitivity.

The Molecular Subtype of Adult Acute Lymphoblastic Leukemia Samples Determines the Engraftment Site and Proliferation Kinetics in Patient-Derived Xenograft Models

In acute lymphoblastic leukemia (ALL), conventional cell lines do not recapitulate the clonal diversity and microenvironment. Orthotopic patient-derived xenograft models (PDX) overcome these limitations and mimic the clinical situation, but molecular stability and engraftment patterns have not yet been thoroughly assessed. We herein describe and characterize the PDX generation in NSG mice. In vivo tumor cell proliferation, engraftment and location were monitored by flow cytometry and bioluminescence imaging. Leukemic cells were retransplanted for up to four passages, and comparative analyses of engraftment pattern, cellular morphology and genomic hotspot mutations were conducted. Ninety-four percent of all samples were successfully engrafted, and the xenograft velocity was dependent on the molecular subtype, outcome of the patient and transplantation passage. While BCR::ABL1 blasts were located in the spleen, KMT2A-positive cases had higher frequencies in the bone marrow. Molecular changes appeared in most model systems, with low allele frequency variants lost during primary engraftment. After the initial xenografting, however, the PDX models demonstrated high molecular stability. This protocol for reliable ALL engraftment demonstrates variability in the location and molecular signatures during serial transplantation. Thorough characterization of experimentally used PDX systems is indispensable for the correct analysis and valid data interpretation of preclinical PDX studies.

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.

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.

Biochemical Tools for Tracking Proteolysis

All living organisms depend on tightly regulated cellular networks to control biological functions. Proteolysis is an important irreversible post-translational modification that regulates most, if not all, cellular processes. Proteases are a large family of enzymes that perform hydrolysis of protein substrates, leading to protein activation or degradation. The 473 known and 90 putative human proteases are divided into 5 main mechanistic groups: metalloproteases, serine proteases, cysteine proteases, threonine proteases, and aspartic acid proteases. Proteases are fundamental to all biological systems, and when dysregulated they profoundly influence disease progression. Inhibiting proteases has led to effective therapies for viral infections, cardiovascular disorders, and blood coagulation just to name a few. Between 5 and 10% of all pharmaceutical targets are proteases, despite limited knowledge about their biological roles. More than 50% of all human proteases have no known substrates. We present here a comprehensive list of all current known human proteases. We also present current and novel biochemical tools to characterize protease functions in vitro, in vivo, and ex vivo. These tools make it achievable to define both beneficial and detrimental activities of proteases in health and disease.

3D printing technologies for in vitro vaccine testing platforms and vaccine delivery systems against infectious diseases

Recent advances in 3D printing (3DP) and tissue engineering approaches enable the potential application of these technologies to vaccine research. Reconstituting the native tissue or cellular microenvironment will be vital for successful evaluation of pathogenicity of viral infection and screening of potential vaccines. Therefore, establishing a reliable in vitro model to study the vaccine efficiency or delivery of viral disease is important. Here, this review summarizes two major ways that tissue engineering and 3DP strategies could contribute to vaccine research: (1) 3D human tissue models to study the response to virus can be served as a testbed for new potential therapeutics. Using 3D tissue platform attempts to explore alternative options to pre-clinical animal research for evaluating vaccine candidates. (2) 3DP technologies can be applied to improve the vaccination strategies which could replace existing vaccine delivery. Controlled antigen release using carriers that are generated with biodegradable biomaterials can further enhance the efficient development of immunity as well as combination of multiple-dose vaccines into a single injection. This mini review discusses the up-to-date report of current 3D tissue/organ models for potential vaccine potency and known bioengineered vaccine delivery systems.

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.