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. 2023 Dec 12;7(23):7384-7391.
doi: 10.1182/bloodadvances.2023010132.

IGLV3-21R110 mutation has prognostic value in patients with treatment-naive chronic lymphocytic leukemia

Charlotte Syrykh  1   2 , Berta Pons-Brun  1 , Núria Russiñol  1 , Heribert Playa-Albinyana  1   3 , Tycho Baumann  4 , Martí Duran-Ferrer  1   3 , Marta Kulis  1 , Anna Carbó-Meix  1 , Pablo Mozas  1   4 , Miguel Alcoceba  3   5 , Marcos González  3   5 , Almudena Navarro-Bailón  3   5 , Enrique Colado  6 , Ángel R Payer  6 , Marta Aymerich  1   3   4 , María J Terol  7 , Junyan Lu  8 , Binyamin A Knisbacher  9   10 , Cynthia K Hahn  9   11 , Sílvia Ruiz-Gaspà  1 , Anna Enjuanes  1 , Catherine J Wu  9   11   12   13 , Gad Getz  9   12   14   15 , Thorsten Zenz  16 , Armando López-Guillermo  1   3   4   17 , José I Martín-Subero  1   3   17   18 , Dolors Colomer  1   3   4   17 , Julio Delgado  1   3   4   17 , Elías Campo  1   3   4   17 , Ferran Nadeu  1   3
Affiliations

IGLV3-21R110 mutation has prognostic value in patients with treatment-naive chronic lymphocytic leukemia

Charlotte Syrykh et al. Blood Adv. .
No abstract available

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Conflict of interest statement

Conflict-of-interest disclosure: C.J.W., G.G., B.A.K., and C.K.H. are inventors on a patent “Compositions, panels, and methods for characterizing chronic lymphocytic leukemia” (PCT/US21/45144). E. Campo has been a consultant for Takeda, NanoString, AbbVie, and Illumina; has received honoraria from Janssen, EUSA Pharma, and Roche for speaking at educational activities; has received research funding from AstraZeneca; and is an inventor of 2 patents filed by the National Institutes of Health, National Cancer Institute: “Methods for selecting and treating lymphoma types,” licensed to NanoString Technologies, and “Evaluation of mantle cell lymphoma and methods related thereof,” not related to this project. F.N. received honoraria from Janssen, AbbVie, and SOPHiA GENETICS for speaking during educational activities. E. Campo and F.N. licensed the use of protected IgCaller algorithm for Diagnóstica Longwood. The remaining authors declare no competing financial interests.

The current affiliation for T.B. is Hospital Universitario 12 de Octubre, Madrid, Spain.

Figures

Figure 1.
Figure 1.
IGLV3-21R110 detection through a mutation-specific polymerase chain reaction assay and its clinical value in 2 independent CLL cohorts. (A) Primer design combining 2 forward primers aligning to distinct regions of the IGLV3-21 gene (green arrows) and 2 R110-specific reverse primers matching the IGLJ1, and IGLJ2/3 genes, respectively (red and orange arrows). A third pair of primers targeting exon 9 of FBXW7 (black arrows) was used as the internal control (top). QIAxcel Advanced System (QIAGEN) capillary electrophoresis image of msPCR analysis. The black arrow indicates the amplification of the internal control (FBXW7 exon 9). The middle and bottom arrows (in green) indicate the 2 bands amplifying in IGLV3-21R110 mutated tumors. (B) Schema of the cohorts studied. (C) Frequency of IGLV3-21R110 mutations in CLL subtypes in cohort 1 (top) and cohort 2 (bottom). (D) Distribution of the IGHV mutational load (% IGHV identity) and epigenetic subtypes within M-CLL, IGLV3-21R110 CLL, and U-CLL. (E) Comparison of TTFT among patients with CLL stratified according to epigenetic subtypes and IGLV3-21R110 in cohort 1 (left) and cohort 2 (right). C+, positive control; C–, negative control; DFCI, Dana-Farber Cancer Institute (∗120 CLL from DFCI has been previously published in reference; Nadeu et al6); n-CLL, naïve-like CLL; R110, sample positive for IGLV3-21R110; UHH, University Hospital Heidelberg (cohort described in reference; no IGLV3-21R110 analysis performed in this previous publication); WT, wild type (ie, sample negative for IGLV3-21R110).
Figure 1.
Figure 1.
IGLV3-21R110 detection through a mutation-specific polymerase chain reaction assay and its clinical value in 2 independent CLL cohorts. (A) Primer design combining 2 forward primers aligning to distinct regions of the IGLV3-21 gene (green arrows) and 2 R110-specific reverse primers matching the IGLJ1, and IGLJ2/3 genes, respectively (red and orange arrows). A third pair of primers targeting exon 9 of FBXW7 (black arrows) was used as the internal control (top). QIAxcel Advanced System (QIAGEN) capillary electrophoresis image of msPCR analysis. The black arrow indicates the amplification of the internal control (FBXW7 exon 9). The middle and bottom arrows (in green) indicate the 2 bands amplifying in IGLV3-21R110 mutated tumors. (B) Schema of the cohorts studied. (C) Frequency of IGLV3-21R110 mutations in CLL subtypes in cohort 1 (top) and cohort 2 (bottom). (D) Distribution of the IGHV mutational load (% IGHV identity) and epigenetic subtypes within M-CLL, IGLV3-21R110 CLL, and U-CLL. (E) Comparison of TTFT among patients with CLL stratified according to epigenetic subtypes and IGLV3-21R110 in cohort 1 (left) and cohort 2 (right). C+, positive control; C–, negative control; DFCI, Dana-Farber Cancer Institute (∗120 CLL from DFCI has been previously published in reference; Nadeu et al6); n-CLL, naïve-like CLL; R110, sample positive for IGLV3-21R110; UHH, University Hospital Heidelberg (cohort described in reference; no IGLV3-21R110 analysis performed in this previous publication); WT, wild type (ie, sample negative for IGLV3-21R110).
Figure 2.
Figure 2.
IGLV3-21R110 status and prognostic value in an integrative cohort of 1487 patients with CLL (n = 1323) or MBL (n = 164). (A) Oncoprint representation showing the disease stage, IGHV gene SHM status, epigenetic subtypes, and stereotyped subset of IGLV3-21R110 positive and negative CLL (left) and MBL (right). Bar plots on the right show the frequency of each variable in IGLV3-21R110 positive and negative CLL/MBL. (B) TTFT curves of patients with CLL stratified based on epigenetic subtype. Patients classified as having i-CLL were divided based on the presence or absence of IGLV3-21R110. i-CLL without IGLV3-21R110 was further stratified based on their IGHV gene SHM status as M-CLL or U-CLL. (C) Multivariate analysis of TTFT integrating disease stage (Binet stage), epigenetic subtypes, and IGLV3-21R110 in patients with CLL. (D) TTFT curves of patients with CLL stratified by IGHV gene SHM status and presence/absence of IGLV3-21R110. (E) TTFT curves of patients with CLL stratified by IGHV gene SHM status, presence/absence of IGLV3-21R110, and stereotyped subset. Patients were first stratified based on IGLV3-21R110. CLL without IGLV3-21R110 was divided based on their IGHV gene SHM status. CLL carrying IGLV3-21R110 were stratified based on their stereotyped subset as stereotyped subset #2 (#2), no stereotyped subset #2 (no #2), or unknown subset (unknown). (F) Multivariate analysis of TTFT integrating disease stage (Binet stage), IGHV gene SHM status, stereotyped subset #2, and IGLV3-21R110 in patients with CLL. (G) Multivariate analysis of TTFT integrating Binet stage, IGHV gene SHM status, stereotyped subset #2, IGLV3-21R110, TP53 mutation/deletion, trisomy 12, and deletions of 11q and 13q in patients with CLL.
Figure 2.
Figure 2.
IGLV3-21R110 status and prognostic value in an integrative cohort of 1487 patients with CLL (n = 1323) or MBL (n = 164). (A) Oncoprint representation showing the disease stage, IGHV gene SHM status, epigenetic subtypes, and stereotyped subset of IGLV3-21R110 positive and negative CLL (left) and MBL (right). Bar plots on the right show the frequency of each variable in IGLV3-21R110 positive and negative CLL/MBL. (B) TTFT curves of patients with CLL stratified based on epigenetic subtype. Patients classified as having i-CLL were divided based on the presence or absence of IGLV3-21R110. i-CLL without IGLV3-21R110 was further stratified based on their IGHV gene SHM status as M-CLL or U-CLL. (C) Multivariate analysis of TTFT integrating disease stage (Binet stage), epigenetic subtypes, and IGLV3-21R110 in patients with CLL. (D) TTFT curves of patients with CLL stratified by IGHV gene SHM status and presence/absence of IGLV3-21R110. (E) TTFT curves of patients with CLL stratified by IGHV gene SHM status, presence/absence of IGLV3-21R110, and stereotyped subset. Patients were first stratified based on IGLV3-21R110. CLL without IGLV3-21R110 was divided based on their IGHV gene SHM status. CLL carrying IGLV3-21R110 were stratified based on their stereotyped subset as stereotyped subset #2 (#2), no stereotyped subset #2 (no #2), or unknown subset (unknown). (F) Multivariate analysis of TTFT integrating disease stage (Binet stage), IGHV gene SHM status, stereotyped subset #2, and IGLV3-21R110 in patients with CLL. (G) Multivariate analysis of TTFT integrating Binet stage, IGHV gene SHM status, stereotyped subset #2, IGLV3-21R110, TP53 mutation/deletion, trisomy 12, and deletions of 11q and 13q in patients with CLL.
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References

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