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Tailored approaches grounded on immunogenetic features for refined prognostication in chronic lymphocytic leukemia

P Baliakas, T Moysiadis, A Hadzidimitriou, A Xochelli, S Jeromin, A Agathangelidis, M Mattsson, LA Sutton, E Minga, L Scarfo, D Rossi, Z Davis, N Villamor, H Parker, J Kotaskova, E Stalika, K Plevova, L Mansouri, D Cortese, A Navarro, J Delgado,...

. 2019 ; 104 (2) : 360-369.

Language English Country Italy

Persistent link   https://www.medvik.cz/link/bmc20017195

Grant support
NV15-30015A MZ0 CEP Register

Chronic lymphocytic leukemia (CLL) patients with differential somatic hypermutation status of the immunoglobulin heavy variable genes, namely mutated or unmutated, display fundamental clinico-biological differences. Considering this, we assessed prognosis separately within mutated (M-CLL) and unmutated (U-CLL) CLL in 3015 patients, hypothesizing that the relative significance of relevant indicators may differ between these two categories. Within Binet A M-CLL patients, besides TP53 abnormalities, trisomy 12 and stereotyped subset #2 membership were equivalently associated with the shortest time-to-first-treatment and a treatment probability at five and ten years after diagnosis of 40% and 55%, respectively; the remaining cases exhibited 5-year and 10-year treatment probability of 12% and 25%, respectively. Within Binet A U-CLL patients, besides TP53 abnormalities, del(11q) and/or SF3B1 mutations were associated with the shortest time-to-first-treatment (5- and 10-year treatment probability: 78% and 98%, respectively); in the remaining cases, males had a significantly worse prognosis than females. In conclusion, the relative weight of indicators that can accurately risk stratify early-stage CLL patients differs depending on the somatic hypermutation status of the immunoglobulin heavy variable genes of each patient. This finding highlights the fact that compartmentalized approaches based on immunogenetic features are necessary to refine and tailor prognostication in CLL. Copyright © 2019 Ferrata Storti Foundation.

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$a Blood. 2016 Jan 21;127(3):303-9, PMID: 26492934 [https://www.ncbi.nlm.nih.gov/pubmed/26492934]
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504    __
$a Blood. 2007 Jun 1;109(11):4679-85, PMID: 17299097 [https://www.ncbi.nlm.nih.gov/pubmed/17299097]
504    __
$a N Engl J Med. 2000 Dec 28;343(26):1910-6, PMID: 11136261 [https://www.ncbi.nlm.nih.gov/pubmed/11136261]
504    __
$a Cancer. 2009 Jan 15;115(2):363-72, PMID: 19090008 [https://www.ncbi.nlm.nih.gov/pubmed/19090008]
504    __
$a Haematologica. 2016 Aug;101(8):959-67, PMID: 27198719 [https://www.ncbi.nlm.nih.gov/pubmed/27198719]
504    __
$a Leukemia. 2014 Jan;28(1):108-17, PMID: 24113472 [https://www.ncbi.nlm.nih.gov/pubmed/24113472]
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$a Semin Cancer Biol. 2015 Oct;34:22-35, PMID: 25963298 [https://www.ncbi.nlm.nih.gov/pubmed/25963298]
504    __
$a J Intern Med. 2016 Apr;279(4):347-57, PMID: 26709197 [https://www.ncbi.nlm.nih.gov/pubmed/26709197]
504    __
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504    __
$a Blood. 2012 May 10;119(19):4467-75, PMID: 22415752 [https://www.ncbi.nlm.nih.gov/pubmed/22415752]
504    __
$a Blood. 2002 Aug 15;100(4):1177-84, PMID: 12149195 [https://www.ncbi.nlm.nih.gov/pubmed/12149195]
504    __
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504    __
$a Blood. 1975 Aug;46(2):219-34, PMID: 1139039 [https://www.ncbi.nlm.nih.gov/pubmed/1139039]
504    __
$a Blood. 2013 Jun 13;121(24):4902-5, PMID: 23637131 [https://www.ncbi.nlm.nih.gov/pubmed/23637131]
504    __
$a Blood. 2008 Jun 15;111(12):5446-56, PMID: 18216293 [https://www.ncbi.nlm.nih.gov/pubmed/18216293]
504    __
$a Leukemia. 2016 Nov;30(11):2251-2253, PMID: 27411488 [https://www.ncbi.nlm.nih.gov/pubmed/27411488]
504    __
$a Leuk Lymphoma. 2014 Oct;55(10):2252-61, PMID: 24397617 [https://www.ncbi.nlm.nih.gov/pubmed/24397617]
504    __
$a Hematology Am Soc Hematol Educ Program. 2016 Dec 2;2016(1):137-145, PMID: 27913472 [https://www.ncbi.nlm.nih.gov/pubmed/27913472]
504    __
$a Br J Haematol. 2009 Jun;146(1):44-53, PMID: 19438486 [https://www.ncbi.nlm.nih.gov/pubmed/19438486]
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$a Blood. 2015 Oct 15;126(16):1921-4, PMID: 26276669 [https://www.ncbi.nlm.nih.gov/pubmed/26276669]
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$a Blood. 2016 May 19;127(20):2375-90, PMID: 26980727 [https://www.ncbi.nlm.nih.gov/pubmed/26980727]
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504    __
$a Blood. 2013 Feb 21;121(8):1403-12, PMID: 23243274 [https://www.ncbi.nlm.nih.gov/pubmed/23243274]
504    __
$a Bioinformatics. 2015 Dec 1;31(23):3844-6, PMID: 26249808 [https://www.ncbi.nlm.nih.gov/pubmed/26249808]
504    __
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$a Blood. 2016 Feb 25;127(8):1007-16, PMID: 26675346 [https://www.ncbi.nlm.nih.gov/pubmed/26675346]
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$a Cell. 2013 Feb 14;152(4):714-26, PMID: 23415222 [https://www.ncbi.nlm.nih.gov/pubmed/23415222]
504    __
$a Lancet Haematol. 2014 Nov;1(2):e74-84, PMID: 27030157 [https://www.ncbi.nlm.nih.gov/pubmed/27030157]
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$a Chronic lymphocytic leukemia (CLL) patients with differential somatic hypermutation status of the immunoglobulin heavy variable genes, namely mutated or unmutated, display fundamental clinico-biological differences. Considering this, we assessed prognosis separately within mutated (M-CLL) and unmutated (U-CLL) CLL in 3015 patients, hypothesizing that the relative significance of relevant indicators may differ between these two categories. Within Binet A M-CLL patients, besides <ovid:i>TP53</ovid:i> abnormalities, trisomy 12 and stereotyped subset #2 membership were equivalently associated with the shortest time-to-first-treatment and a treatment probability at five and ten years after diagnosis of 40% and 55%, respectively; the remaining cases exhibited 5-year and 10-year treatment probability of 12% and 25%, respectively. Within Binet A U-CLL patients, besides <ovid:i>TP53</ovid:i> abnormalities, del(11q) and/or <ovid:i>SF3B1</ovid:i> mutations were associated with the shortest time-to-first-treatment (5- and 10-year treatment probability: 78% and 98%, respectively); in the remaining cases, males had a significantly worse prognosis than females. In conclusion, the relative weight of indicators that can accurately risk stratify early-stage CLL patients differs depending on the somatic hypermutation status of the immunoglobulin heavy variable genes of each patient. This finding highlights the fact that compartmentalized approaches based on immunogenetic features are necessary to refine and tailor prognostication in CLL.<ovid:br/><ovid:br/> Copyright &#xa9; 2019 Ferrata Storti Foundation.
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