While myelodysplastic syndromes with del(5q) (del(5q) MDS) comprises a well-defined hematological subgroup, the molecular basis underlying its origin remains unknown. Using single cell RNA-seq (scRNA-seq) on CD34⁺ progenitors from del(5q) MDS patients, we have identified cells harboring the deletion, characterizing the transcriptional impact of this genetic insult on disease pathogenesis and treatment response. Interestingly, both del(5q) and non-del(5q) cells present similar transcriptional lesions, indicating that all cells, and not only those harboring the deletion, may contribute to aberrant hematopoietic differentiation. However, gene regulatory network (GRN) analyses reveal a group of regulons showing aberrant activity that could trigger altered hematopoiesis exclusively in del(5q) cells, pointing to a more prominent role of these cells in disease phenotype. In del(5q) MDS patients achieving hematological response upon lenalidomide treatment, the drug reverts several transcriptional alterations in both del(5q) and non-del(5q) cells, but other lesions remain, which may be responsible for potential future relapses. Moreover, lack of hematological response is associated with the inability of lenalidomide to reverse transcriptional alterations. Collectively, this study reveals transcriptional alterations that could contribute to the pathogenesis and treatment response of del(5q) MDS.

Patients with myeloid neoplasms who relapsed after allogenic hematopoietic stem cell transplant (HSCT) have poor prognosis. Monitoring of chimerism and specific molecular markers as a surrogate measure of relapse is not always helpful; therefore, improved systems to detect early relapse are needed. We hypothesized that the use of next generation sequencing (NGS) could be a suitable approach for personalized follow-up post-HSCT. To validate our hypothesis, we analyzed by NGS, a retrospective set of peripheral blood (PB) DNA samples previously evaluated by high-sensitive quantitative PCR analysis using insertion/deletion polymorphisms (indel-qPCR) chimerism engraftment. Post-HCST allelic burdens assessed by NGS and chimerism status showed a similar time-course pattern. At time of clinical relapse in 8/12 patients, we detected positive NGS-based minimal residual disease (NGS-MRD). Importantly, in 6/8 patients, we were able to detect NGS-MRD at time points collected prior to clinical relapse. We also confirmed the disappearance of post-HCST allelic burden in non-relapsed patients, indicating true clinical specificity. This study highlights the clinical utility of NGS-based post-HCST monitoring in myeloid neoplasia as a complementary specific analysis to high-sensitive engraftment testing. Overall, NGS-MRD testing in PB is widely applicable for the evaluation of patients following HSCT and highly valuable to personalized early treatment intervention when mixed chimerism is detected.

Precision medicine can significantly improve outcomes for patients with cancer, but implementation requires comprehensive characterization of tumor cells to identify therapeutically exploitable vulnerabilities. Here, we describe somatic biallelic TET2 mutations in an elderly patient with acute myeloid leukemia (AML) that was chemoresistant to anthracycline and cytarabine but acutely sensitive to 5 ′ -azacitidine (5 ′ -Aza) hypomethylating monotherapy, resulting in long-term morphological remission. Given the role of TET2 as a regulator of genomic methylation, we hypothesized that mutant TET2 allele dosage affects response to 5 ′ -Aza. Using an isogenic cell model system and an orthotopic mouse xenograft, we demonstrate that biallelic TET2 mutations confer sensitivity to 5 ′ -Aza compared with cells with monoallelic mutations. Our data argue in favor of using hypomethylating agents for chemoresistant disease or as first-line therapy in patients with biallelic TET2 -mutated AML and demonstrate the importance of considering mutant allele dosage in the implementation of precision medicine for patients with cancer.

Smoldering multiple myeloma (SMM) precedes multiple myeloma (MM). The risk of progression of SMM patients is not uniform, thus different progression-risk models have been developed, although they are mainly based on clinical parameters. Recently, genomic predictors of progression have been defined for untreated SMM. However, the usefulness of such markers in the context of clinical trials evaluating upfront treatment in high-risk SMM (HR SMM) has not been explored yet, precluding the identification of baseline genomic alterations leading to drug resistance. For this reason, we carried out next-generation sequencing and fluorescent in-situ hybridization studies on 57 HR and ultra-high risk (UHR) SMM patients treated in the phase II GEM-CESAR clinical trial (NCT02415413). DIS3, FAM46C, and FGFR3 mutations, as well as t(4;14) and 1q alterations, were enriched in HR SMM. TRAF3 mutations were specifically associated with UHR SMM but identified cases with improved outcomes. Importantly, novel potential predictors of treatment resistance were identified: NRAS mutations and the co-occurrence of t(4;14) plus FGFR3 mutations were associated with an increased risk of biological progression. In conclusion, we have carried out for the first time a molecular characterization of HR SMM patients treated with an intensive regimen, identifying genomic predictors of poor outcomes in this setting.

Acute myeloid leukemia (AML) in the elderly remains a clinical challenge, with a five-year overall survival rate below 10%. The current ELN 2017 genetic risk classification considers cytogenetic and mutational characteristics to stratify fit AML patients into different prognostic groups. However, this classification is not validated for elderly patients treated with a non-intensive approach, and its performance may be suboptimal in this context. Indeed, the transcriptomic landscape of AML in the elderly has been less explored and it might help stratify this group of patients. In the current study, we analyzed the transcriptome of 224 AML patients > 65 years-old at diagnosis treated in the Spanish PETHEMA-FLUGAZA clinical trial in order to identify new prognostic biomarkers in this population. We identified a specific transcriptomic signature for high-risk patients with mutated TP53 or complex karyotype, revealing that low expression of B7H3 gene with high expression of BANP gene identifies a subset of high-risk AML patients surviving more than 12 months. This result was further validated in the BEAT AML cohort. This unique signature highlights the potential of transcriptomics to identify prognostic biomarkers in in elderly AML.

Clonal evolution in acute myeloid leukemia (AML) originates long before diagnosis and is a dynamic process that may affect survival. However, it remains uninvestigated during routine diagnostic workups. We hypothesized that the mutational status of bone marrow dysplastic cells and leukemic blasts, analyzed at the onset of AML using integrated multidimensional flow cytometry (MFC) immunophenotyping and fluorescence-activated cell sorting (FACS) with next-generation sequencing (NGS), could reconstruct leukemogenesis. Dysplastic cells were detected by MFC in 285 of 348 (82%) newly diagnosed patients with AML. Presence of dysplasia according to MFC and World Health Organization criteria had no prognostic value in older adults. NGS of dysplastic cells and blasts isolated at diagnosis identified 3 evolutionary patterns: stable (n = 12 of 21), branching (n = 4 of 21), and clonal evolution (n = 5 of 21). In patients achieving complete response (CR), integrated MFC and FACS with NGS showed persistent measurable residual disease (MRD) in phenotypically normal cell types, as well as the acquisition of genetic traits associated with treatment resistance. Furthermore, whole-exome sequencing of dysplastic and leukemic cells at diagnosis and of MRD uncovered different clonal involvement in dysplastic myelo-erythropoiesis, leukemic transformation, and chemoresistance. Altogether, we showed that it is possible to reconstruct leukemogenesis in ∼80% of patients with newly diagnosed AML, using techniques other than single-cell multiomics.