Distinct p53 phosphorylation patterns in chronic lymphocytic leukemia patients are reflected in the activation of circumjacent pathways upon DNA damage.

TP53 gene abnormalities represent the most important biomarker in chronic lymphocytic leukemia (CLL). Altered protein modifications could also influence p53 function, even in the wild-type protein. We assessed the impact of p53 protein phosphorylations on p53 functions as an alternative inactivation mechanism. We studied p53 phospho-profiles induced by DNA-damaging agents (fludarabine, doxorubicin) in 71 TP53-intact primary CLL samples. Doxorubicin induced two distinct phospho-profiles: profile I (heavily phosphorylated) and profile II (hypophosphorylated). Profile II samples were less capable of activating p53 target genes upon doxorubicin exposure, resembling TP53-mutant samples at the transcriptomic level, whereas standard p53 signaling was triggered in profile I. ATM locus defects were more common in profile II. The samples also differed in the basal activity of the hypoxia pathway: the highest level was detected in TP53-mutant samples, followed by profile II and profile I. Our study suggests that wild-type TP53 CLL cells with less phosphorylated p53 show TP53-mutant-like behavior after DNA damage. p53 hypophosphorylation and the related lower ability to respond to DNA damage are linked to ATM locus defects and the higher basal activity of the hypoxia pathway.

Hierarchical distribution of somatic variants in newly diagnosed chronic myeloid leukaemia at diagnosis and early follow-up.

There is an emerging body of evidence that patients with chronic myeloid leukaemia (CML) may carry not only breakpoint cluster region-Abelson murine leukaemia viral oncogene homologue 1 (BCR-ABL1) kinase domain mutations (BCR-ABL1 KD mutations), but also mutations in other genes. Their occurrence is highest during progression or at failure, but their impact at diagnosis is unclear. In the present study, we prospectively screened for mutations in 18 myeloid neoplasm-associated genes and BCR-ABL1 KD in the following populations: bulk leucocytes, CD34+ CD38+ progenitors and CD34+ CD38- stem cells, at diagnosis and early follow-up. In our cohort of chronic phase CML patients, nine of 49 patients harboured somatic mutations in the following genes: six ASXL1 mutations, one SETBP1, one TP53, one JAK2, but no BCR-ABL1 KD mutations. In seven of the nine patients, mutations were detected in multiple hierarchical populations including bulk leucocytes at diagnosis. The mutation dynamics reflected the BCR-ABL1 transcript decline induced by treatment in eight of the nine cases, suggesting that mutations were acquired in the Philadelphia chromosome (Ph)-positive clone. In one patient, the JAK2 V617F mutation correlated with a concomitant Ph-negative myeloproliferative neoplasm and persisted despite a 5-log reduction of the BCR-ABL1 transcript. Only two of the nine patients with mutations failed first-line therapy. No correlation was found between the mutation status and survival or response outcomes.

LYmphoid NeXt-Generation Sequencing (LYNX) Panel: A Comprehensive Capture-Based Sequencing Tool for the Analysis of Prognostic and Predictive Markers in Lymphoid Malignancies.

B-cell neoplasms represent a clinically heterogeneous group of hematologic malignancies with considerably diverse genomic architecture recently endorsed by next-generation sequencing (NGS) studies. Because multiple genetic defects have a potential or confirmed clinical impact, a tendency toward more comprehensive testing of diagnostic, prognostic, and predictive markers is desired. This study introduces the design, validation, and implementation of an integrative, custom-designed, capture-based NGS panel titled LYmphoid NeXt-generation sequencing (LYNX) for the analysis of standard and novel molecular markers in the most common lymphoid neoplasms (chronic lymphocytic leukemia, acute lymphoblastic leukemia, diffuse large B-cell lymphoma, follicular lymphoma, and mantle cell lymphoma). A single LYNX test provides the following: i) accurate detection of mutations in all coding exons and splice sites of 70 lymphoma-related genes with a sensitivity of 5% variant allele frequency, ii) reliable identification of large genome-wide (≥6 Mb) and recurrent chromosomal aberrations (≥300 kb) in at least 20% of the clonal cell fraction, iii) the assessment of immunoglobulin and T-cell receptor gene rearrangements, and iv) lymphoma-specific translocation detection. Dedicated bioinformatic pipelines were designed to detect all markers mentioned above. The LYNX panel represents a comprehensive, up-to-date tool suitable for routine testing of lymphoid neoplasms with research and clinical applicability. It allows a wide adoption of capture-based targeted NGS in clinical practice and personalized management of patients with lymphoproliferative diseases.

Dynamic miRNA changes during the process of epileptogenesis in an infantile and adult-onset model.

Temporal lobe epilepsy (TLE) is the most common epilepsy type. TLE onset in infancy aggravates features like severity, drug responsiveness, or development of comorbidities. These aggravations may arise from altered micro RNA (miRNA) expression specific to the early onset of the disease. Although the miRNA involvement in TLE is widely studied, the relationship between the onset-age and miRNA expression has not been addressed. Here, we investigated the miRNA profile of infantile and adult-onset TLE in rats combining sequencing and PCR. Since miRNA expression changes with the disease progression, we scrutinized miRNA dynamics across three stages: acute, latent, and chronic. We report that infantile-onset TLE leads to changes in the expression of fewer miRNAs across these stages. Interestingly, the miRNA profile in the acute stage of infantile-onset TLE overlaps in dysregulation of miR-132-5p, -205, and -211-3p with the chronic stage of the disease starting in adulthood. The analysis of putative targets linked the majority of dysregulated miRNAs with pathways involved in epilepsy. Our profiling uncovered miRNA expression characteristic for infantile and adulthood-onset epileptogenesis, suggesting the distinct biology underlying TLE in the onset age-dependent matter. Our results indicate the necessity of addressing the onset age as an important parameter in future epilepsy research.

Low-burden TP53 mutations in CLL: clinical impact and clonal evolution within the context of different treatment options.

Patients with chronic lymphocytic leukemia (CLL) bearing TP53 mutations experience chemorefractory disease and are therefore candidates for targeted therapy. However, the significance of low-burden TP53 mutations with <10% variant allele frequency (VAF) remains a matter for debate. Herein, we describe clonal evolution scenarios of low-burden TP53 mutations, the clinical impact of which we analyzed in a "real-world" CLL cohort. TP53 status was assessed by targeted next-generation sequencing (NGS) in 511 patients entering first-line treatment with chemo- and/or immunotherapy and 159 patients in relapse before treatment with targeted agents. Within the pretherapy cohort, 16% of patients carried low-burden TP53 mutations (0.1% to 10% VAF). Although their presence did not significantly shorten event-free survival after first-line therapy, it affected overall survival (OS). In a subgroup with TP53 mutations of 1% to 10% VAF, the impact on OS was observed only in patients with unmutated IGHV who had not received targeted therapy, as patients benefited from switching to targeted agents, regardless of initial TP53 mutational status. Analysis of the clonal evolution of low-burden TP53 mutations showed that the highest expansion rates were associated with fludarabine, cyclophosphamide, and rituximab regimen in both first- and second-line treatments (median VAF increase, 14.8× and 11.8×, respectively) in contrast to treatment with less intense treatment regimens (1.6×) and no treatment (0.8×). In the relapse cohort, 33% of patients carried low-burden TP53 mutations, which did not expand significantly upon targeted treatment (median VAF change, 1×). Sporadic cases of TP53 mutations' clonal shifts were connected with the development of resistance-associated mutations. Altogether, our data support the incorporation of low-burden TP53 variants in clinical decision making.

Bioinformatic strategies for the analysis of genomic aberrations detected by targeted NGS panels with clinical application.

Molecular profiling of tumor samples has acquired importance in cancer research, but currently also plays an important role in the clinical management of cancer patients. Rapid identification of genomic aberrations improves diagnosis, prognosis and effective therapy selection. This can be attributed mainly to the development of next-generation sequencing (NGS) methods, especially targeted DNA panels. Such panels enable a relatively inexpensive and rapid analysis of various aberrations with clinical impact specific to particular diagnoses. In this review, we discuss the experimental approaches and bioinformatic strategies available for the development of an NGS panel for a reliable analysis of selected biomarkers. Compliance with defined analytical steps is crucial to ensure accurate and reproducible results. In addition, a careful validation procedure has to be performed before the application of NGS targeted assays in routine clinical practice. With more focus on bioinformatics, we emphasize the need for thorough pipeline validation and management in relation to the particular experimental setting as an integral part of the NGS method establishment. A robust and reproducible bioinformatic analysis running on powerful machines is essential for proper detection of genomic variants in clinical settings since distinguishing between experimental noise and real biological variants is fundamental. This review summarizes state-of-the-art bioinformatic solutions for careful detection of the SNV/Indels and CNVs for targeted sequencing resulting in translation of sequencing data into clinically relevant information. Finally, we share our experience with the development of a custom targeted NGS panel for an integrated analysis of biomarkers in lymphoproliferative disorders.

Bioinformatic pipelines for whole transcriptome sequencing data exploitation in leukemia patients with complex structural variants.

BACKGROUND: Extensive genome rearrangements, known as chromothripsis, have been recently identified in several cancer types. Chromothripsis leads to complex structural variants (cSVs) causing aberrant gene expression and the formation of de novo fusion genes, which can trigger cancer development, or worsen its clinical course. The functional impact of cSVs can be studied at the RNA level using whole transcriptome sequencing (total RNA-Seq). It represents a powerful tool for discovering, profiling, and quantifying changes of gene expression in the overall genomic context. However, bioinformatic analysis of transcriptomic data, especially in cases with cSVs, is a complex and challenging task, and the development of proper bioinformatic tools for transcriptome studies is necessary. METHODS: We designed a bioinformatic workflow for the analysis of total RNA-Seq data consisting of two separate parts (pipelines): The first pipeline incorporates a statistical solution for differential gene expression analysis in a biologically heterogeneous sample set. We utilized results from transcriptomic arrays which were carried out in parallel to increase the precision of the analysis. The second pipeline is used for the identification of de novo fusion genes. Special attention was given to the filtering of false positives (FPs), which was achieved through consensus fusion calling with several fusion gene callers. We applied the workflow to the data obtained from ten patients with chronic lymphocytic leukemia (CLL) to describe the consequences of their cSVs in detail. The fusion genes identified by our pipeline were correlated with genomic break-points detected by genomic arrays. RESULTS: We set up a novel solution for differential gene expression analysis of individual samples and de novo fusion gene detection from total RNA-Seq data. The results of the differential gene expression analysis were concordant with results obtained by transcriptomic arrays, which demonstrates the analytical capabilities of our method. We also showed that the consensus fusion gene detection approach was able to identify true positives (TPs) efficiently. Detected coordinates of fusion gene junctions were in concordance with genomic breakpoints assessed using genomic arrays. DISCUSSION: Byapplying our methods to real clinical samples, we proved that our approach for total RNA-Seq data analysis generates results consistent with other genomic analytical techniques. The data obtained by our analyses provided clues for the study of the biological consequences of cSVs with far-reaching implications for clinical outcome and management of cancer patients. The bioinformatic workflow is also widely applicable for addressing other research questions in different contexts, for which transcriptomic data are generated.