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Genetic information has been crucial to understand the pathogenesis of T-cell acute lymphoblastic leukemia (T-ALL) at diagnosis and at relapse, but still nowadays has a limited value in a clinical context. Few genetic markers are associated with the outcome of T-ALL patients, independently of measurable residual disease (MRD) status after therapy. In addition, the prognostic relevance of genetic features may be modulated by the specific treatment used. We analyzed the genetic profile of 145 T-ALL patients by targeted deep sequencing. Genomic information was integrated with the clinicalbiological and survival data of a subset of 116 adult patients enrolled in two consecutive MRD-oriented trials of the Spanish PETHEMA (Programa Español de Tratamientos en Hematología) group. Genetic analysis revealed a mutational profile defined by DNMT3A/ N/KRAS/ MSH2/ U2AF1 gene mutations that identified refractory/resistant patients. Mutations in the DMNT3A gene were also found in the non-leukemic cell fraction of patients with T-ALL, revealing a possible mutational-driven clonal hematopoiesis event to prime T-ALL in elderly. The prognostic impact of this adverse genetic profile was independent of MRD status on day +35 of induction therapy. The combined worse-outcome genetic signature and MRD on day +35 allowed risk stratification of T-ALL into standard or high-risk groups with significantly different 5- year overall survival (OS) of 52% (95% confidence interval: 37-67) and 17% (95% confidence interval: 1-33), respectively. These results confirm the relevance of the tumor genetic profile in predicting patient outcome in adult T-ALL and highlight the need for novel gene-targeted chemotherapeutic schedules to improve the OS of poor-prognosis T-ALL patients.

Genomic analyses have revealed mutational footprints associated with DNA maintenance gone awry, or with mutagen exposures. Because cancer therapeutics often target DNA synthesis or repair, we asked if mutational signatures make useful markers of drug sensitivity. We detect mutational signatures in cancer cell line exomes (where matched healthy tissues are not available) by adjusting for the confounding germline mutation spectra across ancestries. We identify robust associations between various mutational signatures and drug activity across cancer cell lines; these are as numerous as associations with established genetic markers such as driver gene alterations. Signatures of prior exposures to DNA damaging agents - including chemotherapy - tend to associate with drug resistance, while signatures of deficiencies in DNA repair tend to predict sensitivity towards particular therapeutics. Replication analyses across independent drug and CRISPR genetic screening data sets reveal hundreds of robust associations, which are provided as a resource for drug repurposing guided by mutational signature markers., (© 2022. The Author(s).)

The potential prognostic value of conventional karyotyping in adult T-cell acute lymphoblastic leukemia (T-ALL) remains an open question. We hypothesized that a modified cytogenetic classification, based on the number and type of cytogenetic abnormalities, would allow the identification of high-risk adult T-ALL patients. Complex karyotype defined by the presence of ≥3 cytogenetic alterations identified T-ALL patients with poor prognosis in this study. Karyotypes with ≥3 abnormalities accounted for 16 % (22/139) of all evaluable karyotypes, corresponding to the largest poor prognosis cytogenetic subgroup of T-ALL identified so far. Patients carrying karyotypes with ≥3 cytogenetic alterations showed a significantly inferior response to therapy, and a poor outcome in terms of event-free survival (EFS), overall survival (OS) and cumulative incidence of relapse (CIR), independently of other baseline characteristics and the end-induction minimal residual disease (MRD) level. Additional molecular analyses of patients carrying ≥3 cytogenetic alterations showed a unique molecular profile that could contribute to understand the underlying molecular mechanisms of resistance and to evaluate novel targeted therapies (e.g. IL7R directed) with potential impact on outcome of adult T-ALL patients., (Copyright © 2021 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Myelodysplastic syndromes (MDS) are a heterogeneous group of hematological diseases. Among them, the most well characterized subtype is MDS with isolated chromosome 5q deletion (MDS del(5q)), which is the only one defined by a cytogenetic abnormality that makes these patients candidates to be treated with lenalidomide. During the last decade, single cell (SC) analysis has emerged as a powerful tool to decipher clonal architecture and to further understand cancer and other diseases at higher resolution level compared to bulk sequencing techniques. In this study, a SC approach was used to analyze intratumoral heterogeneity in four patients with MDS del(5q). Single CD34+CD117+CD45+CD19- bone marrow hematopoietic stem progenitor cells were isolated using the C1 system (Fluidigm) from diagnosis or before receiving any treatment and from available follow-up samples. Selected somatic alterations were further analyzed in SC by high-throughput qPCR (Biomark HD, Fluidigm) using specific TaqMan assays. A median of 175 cells per sample were analyzed. Inferred clonal architectures were relatively simple and either linear or branching. Similar to previous studies based on bulk sequencing to infer clonal architecture, we were able to observe that an ancestral event in one patient can appear as a secondary hit in another one, thus reflecting the high intratumoral heterogeneity in MDS del(5q) and the importance of patient-specific molecular characterization.

Cell lines are commonly used as cancer models. The tissue of origin provides context for understanding biological mechanisms and predicting therapy response. We therefore systematically examined whether cancer cell lines exhibit features matching the presumed cancer type of origin. Gene expression and DNA methylation classifiers trained on ~9000 tumors identified 35 (of 614 examined) cell lines that better matched a different tissue or cell type than the one originally assigned. Mutational patterns further supported most reassignments. For instance, cell lines identified as originating from the skin often exhibited a UV mutational signature. We cataloged 366 "golden set" cell lines in which transcriptomic and epigenomic profiles strongly resemble the cancer type of origin, further proposing their assignments to subtypes. Accounting for the uncertain tissue of origin in cell line panels can change the interpretation of drug screening and genetic screening data, revealing previously unknown genomic determinants of sensitivity or resistance., (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).)

Chromosomal abnormalities are detected in 20-30% of patients with chronic myelomonocytic leukemia (CMML) and correlate with prognosis. On the mutation level, disruptive alterations are particularly frequent in chromatin regulatory genes. However, little is known about the consequential alterations in the epigenetic marking of the genome. Here, we report the analysis of genomic DNA methylation patterns of 64 CMML patients and 10 healthy controls, using a DNA methylation microarray focused on promoter regions. Differential methylation analysis between patients and controls allowed us to identify abnormalities in DNA methylation, including hypermethylation of specific genes and large genome regions with aberrant DNA methylation. Unsupervised hierarchical cluster analysis identified two main clusters that associated with the clinical, biological, and genetic features of patients. Group 1 was enriched in patients with adverse clinical and biological characteristics and poorer overall and progression-free survival. In addition, significant differences in DNA methylation were observed between patients with low risk and intermediate/high risk karyotypes and between TET2 mutant and wild type patients. Taken together, our results demonstrate that altered DNA methylation patterns reflect the CMML disease state and allow to identify patient groups with distinct clinical features.

Whole genome amplification (WGA) has become an invaluable method for preserving limited samples of precious stock material and has been used during the past years as an alternative tool to increase the amount of DNA before library preparation for next-generation sequencing. Myelodysplastic syndromes (MDS) are a group of clonal hematopoietic stem cell disorders characterized by presenting somatic mutations in several myeloid-related genes. In this work, targeted deep sequencing has been performed on four paired fresh DNA and WGA DNA samples from bone marrow of MDS patients, to assess the feasibility of using WGA DNA for detecting somatic mutations. The results of this study highlighted that, in general, the sequencing and alignment statistics of fresh DNA and WGA DNA samples were similar. However, after variant calling and when considering variants detected at all frequencies, there was a high level of discordance between fresh DNA and WGA DNA (overall, a higher number of variants was detected in WGA DNA). After proper filtering, a total of three somatic mutations were detected in the cohort. All somatic mutations detected in fresh DNA were also identified in WGA DNA and validated by whole exome sequencing.