- 2024-04-18 - 4 Formulär, 1 Item-grupp, 3 Dataelement, 1 Språk
Item-grupp: pht004924
Principal Investigator: Catherine Wu, MD, Dana-Farber Cancer Institute, Boston, MA, USA MeSH: Leukemia, Lymphocytic, Chronic, B-Cell https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000922 Large-scale whole-exome sequencing (WES) of primary tumor samples enables the unbiased discovery of recurrent putative driver events and patterns of clonal evolution. We report the identification of 44 recurrently mutated genes and 11 recurrent CNVs through the WES of 538 chronic lymphocytic leukemia (CLL) and matched germline DNAs. These include previously unrecognized cancer drivers (e.g., RPS15, IKZF3), and collectively identify nuclear export, MYC activity and MAPK signaling as central pathways affected by somatic mutation in CLL. A clonality analysis of this large dataset further enabled the reconstruction of temporal relationships between these driver events. Several drivers were associated with shorter progression-free survival (PFS) in 280 samples that were collected prior to uniform treatment with front line chemo-immunotherapy, with mature follow up of greater than 10 years. Direct comparison between matched pretreatment and relapse CLL from 59 samples demonstrated marked clonal evolution occurring in more than 95% of these patients. Distinct patterns of clonal evolution in relationship to specific gene alteration were observed, suggesting a hierarchy of fitness amongst mutations. Thus, large WES datasets of clinically informative samples enable the discovery of novel driver genes as well as the network of relationships between the drivers and their impact on disease relapse and clinical outcome. Additionally, we performed RNA-seq for 268 CLL samples (including 26 follow-up samples) and used them to identify expression subtypes of CLL. RRBS for 30 of these samples was also generated. In an integrative analysis of genetic, transcriptomic, and epigenetic data, incorporating known and newly identified subtypes of CLL, we built new models to improve patient prognostication.

pht004925.v2.p1

1 Item-grupp 2 Dataelement

pht004926.v2.p1

1 Item-grupp 2 Dataelement

pht004927.v2.p1

1 Item-grupp 7 Dataelement
- 2023-06-21 - 4 Formulär, 1 Item-grupp, 2 Dataelement, 1 Språk
Item-grupp: pht006063

pht006064.v1.p1

1 Item-grupp 3 Dataelement

pht006065.v1.p1

1 Item-grupp 6 Dataelement

pht006066.v1.p1

1 Item-grupp 4 Dataelement
- 2023-06-02 - 4 Formulär, 1 Item-grupp, 3 Dataelement, 1 Språk
Item-grupp: pht005769

pht005770.v1.p1

1 Item-grupp 3 Dataelement

pht005771.v1.p1

1 Item-grupp 3 Dataelement

pht005772.v1.p1

1 Item-grupp 6 Dataelement
- 2023-04-26 - 6 Formulär, 1 Item-grupp, 2 Dataelement, 1 Språk
Item-grupp: pht007857
Principal Investigator: Neil E. Caporaso, MD, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA MeSH: Leukemia, Lymphocytic, Chronic, B-Cell,Hodgkin Disease,Lymphoma, Non-Hodgkin,Waldenstrom Macroglobulinemia,Leukemia, Hairy Cell,Leukemia, Myeloid, Acute,Leukemia, Myelomonocytic, Juvenile https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001219 We have been conducting genetic studies on families at high risk of different hematologic malignancies, in order to define the related tumors in the families, define precursor and other related conditions, and map and identify susceptibility genes. We have focused mainly on four types of lymphoid malignancies: chronic lymphocytic leukemia (CLL), Hodgkin lymphoma (HL), non-Hodgkin lymphoma (NHL), and Waldenström macroglobulinemia (WM). A few families with a rare lymphoma subtype, hairy cell leukemia (HCL) are included. In addition, single large pedigrees with acute myeloid leukemia (AML), and juvenile myelomocytic leukemia (JMML) are included. Families are ascertained for having at least two patients with the same hematologic malignancy and are classified by the type of malignancy that predominates in the family. Multiple types of lymphoid malignancies are often found in the same family. Other data has shown that these conditions aggregate together in families. Verification of cancer diagnoses is obtained through medical records, pathology reports, and flow cytometry. Family members with precursor traits are also included, monoclonal B-cell lymphocytosis (MBL) in CLL families and IgM monoclonal gammopathy of undetermined significance (MGUS) in WM families.

pht007858.v1.p1

1 Item-grupp 6 Dataelement

Eligibility

1 Item-grupp 1 Dataelement

pht007859.v1.p1

1 Item-grupp 3 Dataelement

pht007860.v1.p1

1 Item-grupp 10 Dataelement

pht007861.v1.p1

1 Item-grupp 5 Dataelement
- 2022-10-12 - 4 Formulär, 1 Item-grupp, 4 Dataelement, 1 Språk
Item-grupp: pht002524
Principal Investigator: Catherine Wu, Broad Institute, Cambridge, MA, Dana Farber Cancer Institute, Boston MA, USA MeSH: Chronic Lymphocytic Leukemia,Leukemia, Lymphocytic, Chronic, B-Cell https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000435 The somatic genetic basis of chronic lymphocytic leukemia (CLL), a common and clinically heterogenous adult leukemia, remains poorly understood. Massively parallel sequencing technology now provides a method for systematic discovery of genetic alterations that underlie disease, and for uncovering new therapeutic targets and biomarkers. In study version 2 we presented a dataset consisting of DNA sequencing from 169 CLL samples (with matched germline controls). Samples were collected from patients displaying a wide range of characteristics representing the broad clinical spectrum of CLL. Understanding the mutational landscape of CLL provides a starting point for systematic analyses to address fundamental questions in CLL, including how mutated genes alter cellular networks and phenotypes, and thereby contribute to disease heterogeneity. Intratumoral heterogeneity plays a critical role in tumor evolution. To define the contribution of DNA methylation to heterogeneity within tumors, we performed genome-scale bisulfite sequencing of 100 primary chronic lymphocytic leukemias (CLLs; data presented in study version 3). Compared with 26 normal B cell samples, CLLs consistently displayed higher intrasample variability of DNA methylation patterns across the genome, which appears to arise from stochastically disordered methylation in malignant cells. Transcriptome analysis of bulk and single CLL cells revealed that methylationdisorder was linked to low-level expression. Disordered methylation was further associated with adverse clinical outcome. We therefore propose that disordered methylation plays a similar role to that of genetic instability, enhancing the ability of cancer cells to search for superior evolutionary trajectories.

pht002521.v3.p1

1 Item-grupp 6 Dataelement

pht002522.v3.p1

1 Item-grupp 3 Dataelement

pht002523.v3.p1

1 Item-grupp 11 Dataelement
- 2022-10-12 - 5 Formulär, 1 Item-grupp, 1 Dataelement, 1 Språk
Item-grupp: IG.elig
Principal Investigator: Riccardo Dalla-Favera, Institute for Cancer Genetics, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA MeSH: Chronic Lymphocytic Leukemia,Richter Syndrome https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000364 *Analysis of the chronic lymphocytic leukemia coding genome: role of NOTCH1 mutational activation* The pathogenesis of chronic lymphocytic leukemia (CLL), the most common leukemia in adults, is still largely unknown since the full spectrum of genetic lesions that are present in the CLL genome, and therefore the number and identity of dysregulated cellular pathways, have not been identified. By combining next-generation sequencing and copy number analysis, we show here that the typical CLL coding genome contains less than 20 clonally represented gene alterations/case, including predominantly non-silent mutations and fewer copy number aberrations. These analyses led to the discovery of several genes not previously known to be altered in CLL. While most of these genes were affected at low frequency in an expanded CLL screening cohort, mutational activation of NOTCH1, observed in 8.3% of CLL at diagnosis, was detected at significantly higher frequency during disease progression toward Richter transformation (31.0%) as well as in chemorefractory CLL (20.8%). Consistent with the association of NOTCH1 mutations with clinically aggressive forms of the disease, NOTCH1 activation at CLL diagnosis emerged as an independent predictor of poor survival. These results provide initial data on the complexity of the CLL coding genome and identify a dysregulated pathway of diagnostic and therapeutic relevance. *Genetic Lesions associated with Chronic Lymphocytic Leukemia transformation to Richter Syndrome* Richter syndrome (RS) derives from the rare transformation of chronic lymphocytic leukemia (CLL) into an aggressive lymphoma, most commonly of the diffuse large B cell type (DLBCL). The molecular pathogenesis of RS is only partially understood. By combining whole-exome sequencing and copy-number analysis of 9 CLL-RS pairs and of an extended panel of 43 RS cases, we show that this aggressive disease typically arises from the predominant CLL clone by acquiring an average of ~20 genetic lesions/case. RS lesions are heterogeneous in terms of load and spectrum among patients, and include those involved in CLL progression and chemorefractoriness (TP53 disruption and NOTCH1 activation) as well as some not previously implicated in CLL or RS pathogenesis. In particular, disruption of the CDKN2A/B cell cycle regulator locus is associated with ~30% of RS cases. Finally, we report that the genomic landscape of RS is significantly different from that of de novo DLBCL, suggesting that they represent distinct disease entities. These results provide insights into RS pathogenesis, and identify dysregulated pathways of potential diagnostic and therapeutic relevance.

pht002260.v2.p1

1 Item-grupp 2 Dataelement

pht002261.v2.p1

1 Item-grupp 3 Dataelement

pht002262.v2.p1

1 Item-grupp 3 Dataelement

pht002263.v2.p1

1 Item-grupp 5 Dataelement
- 2021-09-27 - 1 Formulär, 16 Item-grupper, 80 Dataelement, 1 Språk
Item-grupper: Randomization, Pharmacokinetic assessments, Vital signs and physical measurements, Sitting measurements after al least 5 minutes rest, "B" symptoms, General physical examination, ECG, Laboratory analysis, Hematology, Blood chemistry, Electrocytes, Administration of Rituximab, Administration of Fludarabine, Fludarabine Medication, Administration of Cyclophosphamide, Cyclophosphamide Medication

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