Clinical relevance of clonal hematopoiesis in persons aged ≥80 years.

Clonal hematopoiesis of indeterminate potential (CHIP) is associated with increased risk of cancers and inflammation-related diseases. This phenomenon becomes common in persons aged ≥80 years, in whom the implications of CHIP are not well defined. We performed a mutational screening in 1794 persons aged ≥80 years and investigated the relationships between CHIP and associated pathologies. Mutations were observed in one-third of persons aged ≥80 years and were associated with reduced survival. Mutations in JAK2 and splicing genes, multiple mutations (DNMT3A, TET2, and ASXL1 with additional genetic lesions), and variant allele frequency ≥0.096 had positive predictive value for myeloid neoplasms. Combining mutation profiles with abnormalities in red blood cell indices improved the ability of myeloid neoplasm prediction. On this basis, we defined a predictive model that identifies 3 risk groups with different probabilities of developing myeloid neoplasms. Mutations in DNMT3A, TET2, ASXL1, or JAK2 were associated with coronary heart disease and rheumatoid arthritis. Cytopenia was common in persons aged ≥80 years, with the underlying cause remaining unexplained in 30% of cases. Among individuals with unexplained cytopenia, the presence of highly specific mutation patterns was associated with myelodysplastic-like phenotype and a probability of survival comparable to that of myeloid neoplasms. Accordingly, 7.5% of subjects aged ≥80 years with cytopenia had presumptive evidence of myeloid neoplasm. In summary, specific mutational patterns define different risk of developing myeloid neoplasms vs inflammatory-associated diseases in persons aged ≥80 years. In individuals with unexplained cytopenia, mutational status may identify those subjects with presumptive evidence of myeloid neoplasms.

The lncRNA CASC15 regulates SOX4 expression in RUNX1-rearranged acute leukemia.

BACKGROUND: Long non-coding RNAs (lncRNAs) play a variety of cellular roles, including regulation of transcription and translation, leading to alterations in gene expression. Some lncRNAs modulate the expression of chromosomally adjacent genes. Here, we assess the roles of the lncRNA CASC15 in regulation of a chromosomally nearby gene, SOX4, and its function in RUNX1/AML translocated leukemia. RESULTS: CASC15 is a conserved lncRNA that was upregulated in pediatric B-acute lymphoblastic leukemia (B-ALL) with t (12; 21) as well as pediatric acute myeloid leukemia (AML) with t (8; 21), both of which are associated with relatively better prognosis. Enforced expression of CASC15 led to a myeloid bias in development, and overall, decreased engraftment and colony formation. At the cellular level, CASC15 regulated cellular survival, proliferation, and the expression of its chromosomally adjacent gene, SOX4. Differentially regulated genes following CASC15 knockdown were enriched for predicted transcriptional targets of the Yin and Yang-1 (YY1) transcription factor. Interestingly, we found that CASC15 enhances YY1-mediated regulation of the SOX4 promoter. CONCLUSIONS: Our findings represent the first characterization of this CASC15 in RUNX1-translocated leukemia, and point towards a mechanistic basis for its action.

miR148b is a major coordinator of breast cancer progression in a relapse-associated microRNA signature by targeting ITGA5, ROCK1, PIK3CA, NRAS, and CSF1.

Breast cancer is often fatal during its metastatic dissemination. To unravel the role of microRNAs (miRs) during malignancy, we analyzed miR expression in 77 primary breast carcinomas and identified 16 relapse-associated miRs that correlate with survival and/or distinguish tumor subtypes in different datasets. Among them, miR-148b, down-regulated in aggressive breast tumors, was found to be a major coordinator of malignancy. In fact, it is able to oppose various steps of tumor progression when overexpressed in cell lines by influencing invasion, survival to anoikis, extravasation, lung metastasis formation, and chemotherapy response. miR-148b controls malignancy by coordinating a novel pathway involving over 130 genes and, in particular, it directly targets players of the integrin signaling, such as ITGA5, ROCK1, PIK3CA/p110α, and NRAS, as well as CSF1, a growth factor for stroma cells. Our findings reveal the importance of the identified 16 miRs for disease outcome predictions and suggest a critical role for miR-148b in the control of breast cancer progression.

Synthetic Data Generation by Artificial Intelligence to Accelerate Research and Precision Medicine in Hematology.

PURPOSE: Synthetic data are artificial data generated without including any real patient information by an algorithm trained to learn the characteristics of a real source data set and became widely used to accelerate research in life sciences. We aimed to (1) apply generative artificial intelligence to build synthetic data in different hematologic neoplasms; (2) develop a synthetic validation framework to assess data fidelity and privacy preservability; and (3) test the capability of synthetic data to accelerate clinical/translational research in hematology. METHODS: A conditional generative adversarial network architecture was implemented to generate synthetic data. Use cases were myelodysplastic syndromes (MDS) and AML: 7,133 patients were included. A fully explainable validation framework was created to assess fidelity and privacy preservability of synthetic data. RESULTS: We generated MDS/AML synthetic cohorts (including information on clinical features, genomics, treatment, and outcomes) with high fidelity and privacy performances. This technology allowed resolution of lack/incomplete information and data augmentation. We then assessed the potential value of synthetic data on accelerating research in hematology. Starting from 944 patients with MDS available since 2014, we generated a 300% augmented synthetic cohort and anticipated the development of molecular classification and molecular scoring system obtained many years later from 2,043 to 2,957 real patients, respectively. Moreover, starting from 187 MDS treated with luspatercept into a clinical trial, we generated a synthetic cohort that recapitulated all the clinical end points of the study. Finally, we developed a website to enable clinicians generating high-quality synthetic data from an existing biobank of real patients. CONCLUSION: Synthetic data mimic real clinical-genomic features and outcomes, and anonymize patient information. The implementation of this technology allows to increase the scientific use and value of real data, thus accelerating precision medicine in hematology and the conduction of clinical trials.

Real-World Validation of Molecular International Prognostic Scoring System for Myelodysplastic Syndromes.

PURPOSE: Myelodysplastic syndromes (MDS) are heterogeneous myeloid neoplasms in which a risk-adapted treatment strategy is needed. Recently, a new clinical-molecular prognostic model, the Molecular International Prognostic Scoring System (IPSS-M) was proposed to improve the prediction of clinical outcome of the currently available tool (Revised International Prognostic Scoring System [IPSS-R]). We aimed to provide an extensive validation of IPSS-M. METHODS: A total of 2,876 patients with primary MDS from the GenoMed4All consortium were retrospectively analyzed. RESULTS: IPSS-M improved prognostic discrimination across all clinical end points with respect to IPSS-R (concordance was 0.81 v 0.74 for overall survival and 0.89 v 0.76 for leukemia-free survival, respectively). This was true even in those patients without detectable gene mutations. Compared with the IPSS-R based stratification, the IPSS-M risk group changed in 46% of patients (23.6% and 22.4% of subjects were upstaged and downstaged, respectively).In patients treated with hematopoietic stem cell transplantation (HSCT), IPSS-M significantly improved the prediction of the risk of disease relapse and the probability of post-transplantation survival versus IPSS-R (concordance was 0.76 v 0.60 for overall survival and 0.89 v 0.70 for probability of relapse, respectively). In high-risk patients treated with hypomethylating agents (HMA), IPSS-M failed to stratify individual probability of response; response duration and probability of survival were inversely related to IPSS-M risk.Finally, we tested the accuracy in predicting IPSS-M when molecular information was missed and we defined a minimum set of 15 relevant genes associated with high performance of the score. CONCLUSION: IPSS-M improves MDS prognostication and might result in a more effective selection of candidates to HSCT. Additional factors other than gene mutations can be involved in determining HMA sensitivity. The definition of a minimum set of relevant genes may facilitate the clinical implementation of the score.

The Genetics of Myelodysplastic Syndromes: Clinical Relevance.

Myelodysplastic syndromes (MDS) are a clonal disease arising from hematopoietic stem cells, that are characterized by ineffective hematopoiesis (leading to peripheral blood cytopenia) and by an increased risk of evolution into acute myeloid leukemia. MDS are driven by a complex combination of genetic mutations that results in heterogeneous clinical phenotype and outcome. Genetic studies have enabled the identification of a set of recurrently mutated genes which are central to the pathogenesis of MDS and can be organized into a limited number of cellular pathways, including RNA splicing (SF3B1, SRSF2, ZRSR2, U2AF1 genes), DNA methylation (TET2, DNMT3A, IDH1/2), transcription regulation (RUNX1), signal transduction (CBL, RAS), DNA repair (TP53), chromatin modification (ASXL1, EZH2), and cohesin complex (STAG2). Few genes are consistently mutated in >10% of patients, whereas a long tail of 40-50 genes are mutated in <5% of cases. At diagnosis, the majority of MDS patients have 2-4 driver mutations and hundreds of background mutations. Reliable genotype/phenotype relationships were described in MDS: SF3B1 mutations are associated with the presence of ring sideroblasts and more recent studies indicate that other splicing mutations (SRSF2, U2AF1) may identify distinct disease categories with specific hematological features. Moreover, gene mutations have been shown to influence the probability of survival and risk of disease progression and mutational status may add significant information to currently available prognostic tools. For instance, SF3B1 mutations are predictors of favourable prognosis, while driver mutations of other genes (such as ASXL1, SRSF2, RUNX1, TP53) are associated with a reduced probability of survival and increased risk of disease progression. In this article, we review the most recent advances in our understanding of the genetic basis of myelodysplastic syndromes and discuss its clinical relevance.

Classification and Personalized Prognostic Assessment on the Basis of Clinical and Genomic Features in Myelodysplastic Syndromes.

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.

Epigenetic heterogeneity affects the risk of relapse in children with t(8;21)RUNX1-RUNX1T1-rearranged AML.

The somatic translocation t(8;21)(q22;q22)/RUNX1-RUNX1T1 is one of the most frequent rearrangements found in children with standard-risk acute myeloid leukemia (AML). Despite the favorable prognostic role of this aberration, we recently observed a higher than expected frequency of relapse. Here, we employed an integrated high-throughput approach aimed at identifying new biological features predicting relapse among 34 t(8;21)-rearranged patients. We found that the DNA methylation status of patients who suffered from relapse was peculiarly different from that of children maintaining complete remission. The epigenetic signature, made up of 337 differentially methylated regions, was then integrated with gene and protein expression profiles, leading to a network, where cell-to-cell adhesion and cell-motility pathways were found to be aberrantly activated in relapsed patients. We identified most of these factors as RUNX1-RUNX1T1 targets, with Ras Homolog Family Member (RHOB) overexpression being the core of this network. We documented how RHOB re-organized the actin cytoskeleton through its downstream ROCK-LIMK-COFILIN axis: this increases blast adhesion by stress fiber formation, and reduces mitochondrial apoptotic cell death after chemotherapy treatment. Altogether, our data show an epigenetic heterogeneity within t(8;21)-rearranged AML patients at diagnosis able to influence the program of the chimeric transcript, promoting blast re-emergence and progression to relapse.

MicroRNA-27a Contributes to Rhabdomyosarcoma Cell Proliferation by Suppressing RARA and RXRA.

BACKGROUND: Rhabdomyosarcomas (RMS) are rare but very aggressive childhood tumors that arise as a consequence of a regulatory disruption in the growth and differentiation pathways of myogenic precursor cells. According to morphological criteria, there are two major RMS subtypes: embryonal RMS (ERMS) and alveolar RMS (ARMS) with the latter showing greater aggressiveness and metastatic potential with respect to the former. Efforts to unravel the complex molecular mechanisms underlying RMS pathogenesis and progression have revealed that microRNAs (miRNAs) play a key role in tumorigenesis. METHODOLOGY/PRINCIPAL FINDINGS: The expression profiles of 8 different RMS cell lines were analyzed to investigate the involvement of miRNAs in RMS. The miRNA population from each cell line was compared to a reference sample consisting of a balanced pool of total RNA extracted from those 8 cell lines. Sixteen miRNAs whose expression discriminates between translocation-positive ARMS and negative RMS were identified. Attention was focused on the role of miR-27a that is up-regulated in the more aggressive RMS cell lines (translocation-positive ARMS) in which it probably acts as an oncogene. MiR-27a overexpressing cells showed a significant increase in their proliferation rate that was paralleled by a decrease in the number of cells in the G1 phase of the cell cycle. It was possible to demonstrate that miR-27a is implicated in cell cycle control by targeting the retinoic acid alpha receptor (RARA) and retinoic X receptor alpha (RXRA). CONCLUSIONS: Study results have demonstrated that miRNA expression signature profiling can be used to classify different RMS subtypes and suggest that miR-27a may have a therapeutic potential in RMS by modulating the expression of retinoic acid receptors.