ID

45191

Descripción

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.

Link

dbGaP study = phs000364

Palabras clave

  1. 19/8/22 19/8/22 - Simon Heim
  2. 12/10/22 12/10/22 - Adrian Schulz
Titular de derechos de autor

Riccardo Dalla-Favera, Institute for Cancer Genetics, Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA

Subido en

12 de octubre de 2022

DOI

Para solicitar uno, por favor iniciar sesión.

Licencia

Creative Commons BY 4.0

Comentarios del modelo :

Puede comentar sobre el modelo de datos aquí. A través de las burbujas de diálogo en los grupos de elementos y elementos, puede agregar comentarios específicos.

Comentarios de grupo de elementos para :

Comentarios del elemento para :

Para descargar modelos de datos, debe haber iniciado sesión. Por favor iniciar sesión o Registrate gratis.

dbGaP phs000364 Genome-Wide Analysis of Chronic Lymphocytic Leukemia

This sample attributes table includes variables indicating the tumor/normal status, the body site where the sample was extracted, sample analyte type and histological type.

pht002263
Descripción

pht002263

Sample ID
Descripción

SAMPID

Tipo de datos

string

Alias
UMLS CUI [1,1]
C1299222
Tumor or normal DNA?
Descripción

tumor_normal

Tipo de datos

text

Alias
UMLS CUI [1,1]
C0456204
UMLS CUI [1,2]
C0205307
UMLS CUI [1,3]
C0027651
Material used for analysis (DNA, RNA, etc)
Descripción

Sample analyte type

Tipo de datos

string

Alias
UMLS CUI [1,1]
C0449902
Tumor localization or tissue from which sample was extracted
Descripción

Body site

Tipo de datos

text

Alias
UMLS CUI [1,1]
C0449705
Histological diagnosis
Descripción

Histological type

Tipo de datos

text

Alias
UMLS CUI [1,1]
C0679557

Similar models

This sample attributes table includes variables indicating the tumor/normal status, the body site where the sample was extracted, sample analyte type and histological type.

Name
Tipo
Description | Question | Decode (Coded Value)
Tipo de datos
Alias
Item Group
pht002263
SAMPID
Item
Sample ID
string
C1299222 (UMLS CUI [1,1])
Item
Tumor or normal DNA?
text
C0456204 (UMLS CUI [1,1])
C0205307 (UMLS CUI [1,2])
C0027651 (UMLS CUI [1,3])
Code List
Tumor or normal DNA?
CL Item
Tumor (T)
CL Item
Normal (N)
Sample analyte type
Item
Material used for analysis (DNA, RNA, etc)
string
C0449902 (UMLS CUI [1,1])
Item
Tumor localization or tissue from which sample was extracted
text
C0449705 (UMLS CUI [1,1])
Code List
Tumor localization or tissue from which sample was extracted
CL Item
peripheral blood mononuclear CD5/CD19 positive cells (peripheral blood mononuclear CD5/CD19 positive cells)
CL Item
peripheral blood granulocytes (peripheral blood granulocytes)
CL Item
lymph node (lymph node)
Item
Histological diagnosis
text
C0679557 (UMLS CUI [1,1])
Code List
Histological diagnosis
CL Item
chronic lymphocytic leukemia (CLL)
CL Item
not applicable (if normal DNA) (NA)
CL Item
Richter Syndrome (RS)

Utilice este formulario para comentarios, preguntas y sugerencias.

Los campos marcados con * son obligatorios.

Do you need help on how to use the search function? Please watch the corresponding tutorial video for more details and learn how to use the search function most efficiently.

Watch Tutorial