Genomics improves risk stratification of adults with T-cell acute lymphoblastic leukemia patients enrolled in measurable residual disease-oriented trials

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 clinical-biological 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 nonleukemic 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 WOG 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) (95% confidence interval [CI]) of 52% (37-67 %) and 17% (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.

Mutational signatures are markers of drug sensitivity of cancer cells

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.

Mutational signatures can reveal the impact of mutagenic processes in cancer, including exposure to therapy. Here, the authors develop an approach that can accurately predict drug responses in cancer using mutational signatures while simultaneously correcting for germline variants with an ancestry matching procedure.

Adverse prognostic impact of complex karyotype (≥3 cytogenetic alterations) in adult T-cell acute lymphoblastic leukemia (T-ALL)

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.

Matching cell lines with cancer type and subtype of origin via mutational, epigenomic, and transcriptomic patterns

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.

Spanish Guidelines for the use of targeted deep sequencing in myelodysplastic syndromes and chronic myelomonocytic leukaemia

The landscape of medical sequencing has rapidly changed with the evolution of next generation sequencing (NGS). These technologies have contributed to the molecular characterization of the myelodysplastic syndromes (MDS) and chronic myelomonocytic leukaemia (CMML), through the identification of recurrent gene mutations, which are present in >80% of patients. These mutations contribute to a better classification and risk stratification of the patients. Currently, clinical laboratories include NGS genomic analyses in their routine clinical practice, in an effort to personalize the diagnosis, prognosis and treatment of MDS and CMML. NGS technologies have reduced the cost of large-scale sequencing, but there are additional challenges involving the clinical validation of these technologies, as continuous advances are constantly being made. In this context, it is of major importance to standardize the generation, analysis, clinical interpretation and reporting of NGS data. To that end, the Spanish MDS Group (GESMD) has expanded the present set of guidelines, aiming to establish common quality standards for the adequate implementation of NGS and clinical interpretation of the results, hoping that this effort will ultimately contribute to the benefit of patients with myeloid malignancies.

DNA methylation profile in chronic myelomonocytic leukemia associates with distinct clinical, biological and genetic features

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.

Inspecting Targeted Deep Sequencing of Whole Genome Amplified DNA Versus Fresh DNA for Somatic Mutation Detection: A Genetic Study in Myelodysplastic Syndrome Patients

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.