Tumor protein p53 (TP53) is the most frequently mutated gene in cancer 1,2. In patients with myelodysplastic syndromes (MDS), TP53 mutations are associated with high-risk disease 3,4 , rapid transformation to acute myeloid leukemia (AML) 5 , resistance to conventional therapies 6-8 and dismal outcomes 9. Consistent with the tumor-suppressive role of TP53, patients harbor both mono-and biallelic mutations 10. However, the biological and clinical implications of TP53 allelic state have not been fully investigated in MDS or any other cancer type. We analyzed 3,324 patients with MDS for TP53 mutations and allelic imbalances and delineated two subsets of patients with distinct phenotypes and outcomes. One-third of TP53-mutated patients had monoallelic mutations whereas two-thirds had multiple hits (multi-hit) consistent with biallelic targeting. Established associations with complex karyotype, few co-occurring mutations, high-risk presentation and poor outcomes were specific to multi-hit patients only. TP53 multi-hit state predicted risk of death and leukemic transformation independently of the Revised International Prognostic Scoring System (IPSS-R) 11. Surprisingly, monoallelic patients did not differ from TP53 wild-type patients in outcomes and response to therapy. This study shows that consideration of TP53 allelic state is critical for diagnostic and prognostic precision in MDS as well as in future correlative studies of treatment response. In collaboration with the International Working Group for Prognosis in MDS (Supplementary Table 1), we assembled a cohort of 3,324 peridiagnostic and treatment-naive patients with MDS or closely related myeloid neoplasms (Extended Data Fig. 1 and Supplementary Fig. 1). Genetic profiling included conventional G-banding analyses (CBA) and tumor-only, capture-based, next-generation sequencing (NGS) of a panel of genes recurrently mutated in MDS, as well as genome-wide copy number probes. Allele-specific copy number profiles were generated from NGS data using the CNACS algorithm 7 (see Methods and Code availability). An additional 1,120 samples derived from the Japanese MDS consortium (Extended Data Fig. 2) were used as a validation cohort. To study the effect of TP53 allelic state on genome stability, clinical presentation, outcome and response to therapy, we performed a detailed characterization of alterations at the TP53 locus. First, we assessed genome-wide allelic imbalances in the cohort of 3,324 patients, to include arm-level or focal (~3 Mb) ploidy alterations and regions of copy-neutral loss of heterozygosity (cnLOH) (Extended Data Fig. 3, Supplementary Figs. 2-4 and Methods).

No abstract

Over 90% of myelodysplastic/myeloproliferative neoplasms (MDS/MPN) harbor somatic mutations in myeloid-related genes, but still, current diagnostic criteria do not include molecular data. We performed genome-wide sequencing techniques to characterize the mutational landscape of a large and clinically well-characterized cohort including 367 adult MDS/MPN: chronic myelomonocytic leukemia (CMML, n=119), atypical chronic myeloid leukemia (aCML, n=71), MDS/MPN with ring sideroblasts and thrombocytosis (MDS/MPN-RS-T, n=71) and MDS/MPN unclassifiable (MDS/MPN-U, n=106). A total of 30 genes were recurrently mutated in ≥3% of the cohort. Distribution of recurrently mutated genes and clonal architecture differed among MDS/MPN subtypes. Statistical analysis revealed significant correlations between recurrently mutated genes, as well as genotype-phenotype associations. We identified specific gene combinations that associated with distinct MDS/MPN subtypes and that were mutually exclusive with most of the other MDS/MPN (e.g. TET2-SRSF2 in CMML, ASXL1-SETBP1 in aCML or SF3B1-JAK2 in MDS/MPN-RS-T). Patients with MDS/MPN-U were the most heterogeneous and displayed different molecular profiles that mimicked the ones observed in other MDS/MPN subtypes and that had an impact on the outcome of the patients. Specific gene mutations also had an impact on the outcome of the different MDS/MPN, which may be relevant for clinical decision-making. Overall, the results of this study help to elucidate the heterogeneity found in these neoplasms, which can be of use in the clinical setting of MDS/MPN.

PURPOSE Recurrently mutated genes and chromosomal abnormalities have been identified in myelodysplastic syndromes (MDS). We aim to integrate these genomic features into disease classification and prognostication. METHODS We retrospectively enrolled 2,043 patients. Using Bayesian networks and Dirichlet processes, we combined mutations in 47 genes with cytogenetic abnormalities to identify genetic associations and subgroups. Random-effects Cox proportional hazards multistate modeling was used for developing prognostic models. An independent validation on 318 cases was performed. RESULTS We identify eight MDS groups (clusters) according to specific genomic features. In five groups, dominant genomic features include splicing gene mutations ( SF3B1, SRSF2, and U2AF1) that occur early in disease history, determine specific phenotypes, and drive disease evolution. These groups display different prognosis (groups with SF3B1 mutations being associated with better survival). Specific co-mutation patterns account for clinical heterogeneity within SF3B1- and SRSF2-related MDS. MDS with complex karyotype and/or TP53 gene abnormalities and MDS with acute leukemia–like mutations show poorest prognosis. MDS with 5q deletion are clustered into two distinct groups according to the number of mutated genes and/or presence of TP53 mutations. By integrating 63 clinical and genomic variables, we define a novel prognostic model that generates personally tailored predictions of survival. The predicted and observed outcomes correlate well in internal cross-validation and in an independent external cohort. This model substantially improves predictive accuracy of currently available prognostic tools. We have created a Web portal that allows outcome predictions to be generated for user-defined constellations of genomic and clinical features. CONCLUSION Genomic landscape in MDS reveals distinct subgroups associated with specific clinical features and discrete patterns of evolution, providing a proof of concept for next-generation disease classification and prognosis.

SummaryBone marrow mesenchymal stem/stromal cells (BM-MSCs) are key components of the hematopoietic niche thought to have a direct role in leukemia pathogenesis. BM-MSCs from patients with acute myeloid leukemia (AML) have been poorly characterized due to disease heterogeneity. We report a functional, genetic, and immunological characterization of BM-MSC cultures from 46 AML patients, stratified by molecular/cytogenetics into low-risk (LR), intermediate-risk (IR), and high-risk (HR) subgroups. Stable MSC cultures were successfully established and characterized from 40 of 46 AML patients irrespective of the risk subgroup. AML-derived BM-MSCs never harbored tumor-specific cytogenetic/molecular alterations present in blasts, but displayed higher clonogenic potential than healthy donor (HD)-derived BM-MSCs. Although HD- and AML-derived BM-MSCs equally provided chemoprotection to AML cells in vitro, AML-derived BM-MSCs were more immunosuppressive/anti-inflammatory, enhanced suppression of lymphocyte proliferation, and diminished secretion of pro-inflammatory cytokines. Multivariate analysis revealed that the level of interleukin-10 produced by AML-derived BM-MSCs as an independent prognostic factor negatively affected overall survival. Collectively our data show that AML-derived BM-MSCs are not tumor related, but display functional differences contributing to therapy resistance and disease evolution.

Extracellular vesicles have created great interest as possible source of biomarkers for different biological processes and diseases. Although the biological function of these vesicles is not fully understood, it is clear that they participate in the removal of unnecessary cellular material and act as carriers of various macromolecules and signals between the cells. In this report, we analyzed the proteome of extracellular vesicles secreted by primary hepatocytes. We used one- and two-dimensional liquid chromatography combined with data-independent mass spectrometry. Employing label-free quantitative proteomics, we detected significant changes in vesicle protein expression levels in this in vitro model after exposure to well-known liver toxins (galactosamine and Escherichia coli-derived lipopolysaccharide). The results allowed us to identify candidate markers for liver injury. We validated a number of these markers in vivo, providing the basis for the development of novel methods to evaluate drug toxicity. This report strongly supports the application of proteomics in the study of extracellular vesicles released by well-controlled in vitro cellular systems. Analysis of such systems should help to identify specific markers for various biological processes and pathological conditions.

Characterization of nanoscale extracellular vesicles by Raman tweezers microspectroscopy is described in detail. Intra-sample biomolecular heterogeneity is revealed for individual exosomes from human urine and rat hepatocytes.

The discovery that the cells communicate through emission of vesicles has opened new opportunities for better understanding of physiological and pathological mechanisms. This discovery also provides a novel source for non-invasive disease biomarker research. Our group has previously reported that hepatocytes release extracellular vesicles with protein content reflecting the cell-type of origin. Here, we show that the extracellular vesicles released by hepatocytes also carry RNA. We report the messenger RNA composition of extracellular vesicles released in two non-tumoral hepatic models: primary culture of rat hepatocytes and a progenitor cell line obtained from a mouse foetal liver. We describe different subpopulations of extracellular vesicles with different densities and protein and RNA content. We also show that the RNA cargo of extracellular vesicles released by primary hepatocytes can be transferred to rat liver stellate-like cells and promote their activation. Finally, we provide in vitro and in vivo evidence that liver-damaging drugs galactosamine, acetaminophen, and diclofenac modify the RNA content of these vesicles. To summarize, we show that the extracellular vesicles secreted by hepatocytes contain various RNAs. These vesicles, likely to be involved in the activation of stellate cells, might become a new source for non-invasive identification of the liver toxicity markers.