Biological and clinical significance of dysplastic hematopoiesis in patients with newly diagnosed multiple myeloma.

Risk of developing myelodysplastic syndrome (MDS) is significantly increased in both multiple myeloma (MM) and monoclonal gammopathy of undetermined significance, suggesting that it is therapy independent. However, the incidence and sequelae of dysplastic hematopoiesis at diagnosis are unknown. Here, we used multidimensional flow cytometry (MFC) to prospectively screen for the presence of MDS-associated phenotypic alterations (MDS-PA) in the bone marrow of 285 patients with MM enrolled in the PETHEMA/GEM2012MENOS65 trial (#NCT01916252). We investigated the clinical significance of monocytic MDS-PA in a larger series of 1252 patients enrolled in 4 PETHEMA/GEM protocols. At diagnosis, 33 (11.6%) of 285 cases displayed MDS-PA. Bulk and single-cell-targeted sequencing of MDS recurrently mutated genes in CD34+ progenitors (and dysplastic lineages) from 67 patients revealed clonal hematopoiesis in 13 (50%) of 26 cases with MDS-PA vs 9 (22%) of 41 without MDS-PA; TET2 and NRAS were the most frequently mutated genes. Dynamics of MDS-PA at diagnosis and after autologous transplant were evaluated in 86 of 285 patients and showed that in most cases (69 of 86 [80%]), MDS-PA either persisted or remained absent in patients with or without MDS-PA at diagnosis, respectively. Noteworthy, MDS-associated mutations infrequently emerged after high-dose therapy. Based on MFC profiling, patients with MDS-PA have altered hematopoiesis and T regulatory cell distribution in the tumor microenvironment. Importantly, the presence of monocytic MDS-PA at diagnosis anticipated greater risk of hematologic toxicity and was independently associated with inferior progression-free survival (hazard ratio, 1.5; P = .02) and overall survival (hazard ratio, 1.7; P = .01). This study reveals the biological and clinical significance of dysplastic hematopoiesis in newly diagnosed MM, which can be screened with moderate sensitivity using cost-effective MFC.

Machine Learning-Based Approach Highlights the Use of a Genomic Variant Profile for Precision Medicine in Ovarian Failure.

Ovarian failure (OF) is a common cause of infertility usually diagnosed as idiopathic, with genetic causes accounting for 10-25% of cases. Whole-exome sequencing (WES) may enable identifying contributing genes and variant profiles to stratify the population into subtypes of OF. This study sought to identify a blood-based gene variant profile using accumulation of rare variants to promote precision medicine in fertility preservation programs. A case-control (n = 118, n = 32, respectively) WES study was performed in which only non-synonymous rare variants <5% minor allele frequency (MAF; in the IGSR) and coverage ≥ 100× were considered. A profile of 66 variants of uncertain significance was used for training an unsupervised machine learning model to separate cases from controls (97.2% sensitivity, 99.2% specificity) and stratify the population into two subtypes of OF (A and B) (93.31% sensitivity, 96.67% specificity). Model testing within the IGSR female population predicted 0.5% of women as subtype A and 2.4% as subtype B. This is the first study linking OF to the accumulation of rare variants and generates a new potential taxonomy supporting application of this approach for precision medicine in fertility preservation.

Whole exome sequencing suggests much of non-BRCA1/BRCA2 familial breast cancer is due to moderate and low penetrance susceptibility alleles.

The identification of the two most prevalent susceptibility genes in breast cancer, BRCA1 and BRCA2, was the beginning of a sustained effort to uncover new genes explaining the missing heritability in this disease. Today, additional high, moderate and low penetrance genes have been identified in breast cancer, such as P53, PTEN, STK11, PALB2 or ATM, globally accounting for around 35 percent of the familial cases. In the present study we used massively parallel sequencing to analyze 7 BRCA1/BRCA2 negative families, each having at least 6 affected women with breast cancer (between 6 and 10) diagnosed under the age of 60 across generations. After extensive filtering, Sanger sequencing validation and co-segregation studies, variants were prioritized through either control-population studies, including up to 750 healthy individuals, or case-control assays comprising approximately 5300 samples. As a result, a known moderate susceptibility indel variant (CHEK2 1100delC) and a catalogue of 11 rare variants presenting signs of association with breast cancer were identified. All the affected genes are involved in important cellular mechanisms like DNA repair, cell proliferation and survival or cell cycle regulation. This study highlights the need to investigate the role of rare variants in familial cancer development by means of novel high throughput analysis strategies optimized for genetically heterogeneous scenarios. Even considering the intrinsic limitations of exome resequencing studies, our findings support the hypothesis that the majority of non-BRCA1/BRCA2 breast cancer families might be explained by the action of moderate and/or low penetrance susceptibility alleles.

Deep sequencing of target linkage assay-identified regions in familial breast cancer: methods, analysis pipeline and troubleshooting.

BACKGROUND: The classical candidate-gene approach has failed to identify novel breast cancer susceptibility genes. Nowadays, massive parallel sequencing technology allows the development of studies unaffordable a few years ago. However, analysis protocols are not yet sufficiently developed to extract all information from the huge amount of data obtained. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we performed high throughput sequencing in two regions located on chromosomes 3 and 6, recently identified by linkage studies by our group as candidate regions for harbouring breast cancer susceptibility genes. In order to enrich for the coding regions of all described genes located in both candidate regions, a hybrid-selection method on tiling microarrays was performed. CONCLUSIONS/SIGNIFICANCE: We developed an analysis pipeline based on SOAP aligner to identify candidate variants with a high real positive confirmation rate (0.89), with which we identified eight variants considered candidates for functional studies. The results suggest that the present strategy might be a valid second step for identifying high penetrance genes.