The somatic hypermutation (SHM) status of the clonotypic immunoglobulin heavy variable (IGHV) gene is a critical biomarker for assessing the prognosis of patients with chronic lymphocytic leukemia (CLL). Importantly, independent studies have documented that IGHV SHM status is also a predictor of responses to therapy, including both chemoimmunotherapy (CIT) and novel, targeted agents. Moreover, immunogenetic analysis in CLL has revealed that different patients may express (quasi)identical, stereotyped B cell receptor immunoglobulin (BcR IG) and are classified into subsets based on this common feature. Patients in certain stereotyped subsets display consistent biology, clinical presentation, and outcome that are distinct from other patients, even with concordant IGHV gene SHM status. All of the above highlights the relevance of immunogenetic analysis in CLL, which is considered a cornerstone for accurate risk stratification and clinical decision making. Recommendations for robust immunogenetic analysis exist thanks to dedicated efforts by ERIC, the European Research Initiative on CLL, covering all test phases, from the pre-analytical and analytical to the post-analytical, pertaining to the analysis, interpretation, and reporting of the findings. That said, these recommendations apply to Sanger sequencing, which is increasingly being superseded by next generation sequencing (NGS), further underscoring the need for an update. Here, we present an overview of the clinical utility of immunogenetics in CLL and update our analytical recommendations with the aim to assist in the refined management of patients with CLL.
Immunogenetic analysis in CLL: key to understanding and treating CLL
Immunogenetic studies have offered strong evidence for the central role of the B cell receptor immunoglobulin (BcR IG) in the natural history of chronic lymphocytic leukemia (CLL). Restrictions in the BcR IG gene repertoire, culminating in the existence of subsets with stereotyped BcR IG, strongly implicate antigen selection in CLL pathogenesis . Of clinical relevance, the somatic hypermutation (SHM) status of the rearranged immunoglobulin heavy variable (IGHV) gene has emerged as key to accurate risk stratification in CLL . Moreover, this biomarker remains stable over time, thus contrasting other, “cell-intrinsic” biomarkers, such as genomic aberrations, that are enriched in patients with advanced and/or relapsed/refractory disease .
On these grounds, it becomes apparent that robust immunogenetic characterization has an important role in the proper management of patients with CLL. This is reflected in the guidelines of the International Workshop on CLL (iwCLL) indicating that this biomarker should be assessed prior to treatment in all patients with CLL, i.e., in both general practice and clinical trials;  and, it has now been translated into clinical recommendations by many professional scientific societies worldwide, such as the National Comprehensive Cancer Network (NCCN) and the European Society for Medical Oncology (ESMO).
IGHV gene somatic hypermutation status as a prognosticator in CLL
The prognostic value of SHM within the clonotypic rearranged IGHV genes was first recognized in 1999 [5, 6], when it was shown that patients with no or limited SHM (‘unmutated’ CLL, U-CLL) usually experience an aggressive form of CLL, while those with a significant SHM load (‘mutated’ CLL, M-CLL) follow more indolent disease courses . Since then, many studies have confirmed these findings, rendering the analysis of IGHV gene SHM status an invaluable and non-dispensable tool for prognostication in CLL, regarding any relevant outcome measure.
Indeed, this biomarker may assist in predicting how soon patients will require treatment after the initial diagnosis, in other words, it can discriminate patients with shorter versus longer time-to-first-treatment (TTFT). Unsurprisingly, therefore, IGHV gene SHM status has been included in various prognostic tools/models/scores for TTFT, e.g., the CLL international prognostic index (CLL-IPI) , the CLL1 prognostic model , the International Prognostic Score for Early-stage CLL(IPS-E)  and the CLL WithOut Need of Treatment (CLL-WONT) risk score . In both the CLL-IPI and the CLL1 model, unmutated IGHV gene status was given the highest score after del(17p), while in the IPS-E and CLL-WONT the presence of unmutated IGHV genes was independently associated with shorter TTFT [7, 10, 11]. Interestingly, the CLL-IPI and CLL-WONT were combined to identify patients with a very low risk of 5-year TTFT that can be initially managed by primary healthcare providers .
That notwithstanding, despite the strong prognostic value of IGHV gene SHM status at the cohort level, this test may not always be accurate at the individual case level. On the one hand, not all U-CLL patients will require treatment, while, on the other hand, some M-CLL cases will experience disease progression and need therapy. This finding raises doubts concerning the clinical utility of this information at the individual patient level at the time of diagnosis, before the development of any evidence of active disease.
Independent studies from the chemoimmunotherapy era have shown that U-CLL patients have a worse overall survival (OS) than M-CLL patients [12,13,14,15,16], with a meta-analysis of 13 studies published in 2016 reporting an OS hazard ratio of 1.6 to 6.9 for U-CLL patients . M-CLL patients have been consistently found to fare better, except for two studies: more specifically, Shanafelt et al. showed that amongst M-CLL patients only those <75 years experienced an OS benefit , while in a small cohort by Ouillette et al. IGHV gene SHM status did not impact on OS .
IGHV gene somatic hypermutation status as a predictor of responses to treatment in CLL
Results from prospective clinical trials have disclosed the predictive value of IGHV gene SHM status in patients with CLL who required treatment. Starting with chemoimmunotherapy, unmutated IGHV genes predicted for a worse progression-free survival (PFS). Specifically, in the CLL8 trial , which compared fludarabine, cyclophosphamide, and rituximab (FCR) versus fludarabine and cyclophosphamide (FC), where the presence of unmutated IGHV genes was predictive of worse PFS irrespective of the regimen used. In a longer follow-up of this study, M-CLL patients experienced better PFS and OS when treated with FCR compared with FC . Similar results were reported by Thompson et al. ., who found a high rate of prolonged PFS in M-CLL patients treated with FCR; and, by Rossi et al. who documented a particularly good response to FCR in M-CLL patients lacking del(17p) or del(11q) .
The importance of IGHV gene SHM status was also highlighted in clinical trials of novel agents, such as BTK inhibitors (BTKis). In the RESONATE and RESONATE-2 trials, patients treated with ibrutinib, either in the front-line setting or for relapsed/refractory disease, experienced a better PFS and OS than patients treated with ofatumumab or chlorambucil, respectively [24, 25]. The superiority of BTKis over CIT was also documented in elderly patients and in the relapsed/refractory setting, more particularly the ALLIANCE (ibrutinib ± rituximab versus bendamustine + rituximab) , ASCEND (acalabrutinib versus idelalisib + rituximab or bendamustine + rituximab)  and ILLUMINATE (ibrutinib + obinutuzumab versus chlorambucil + obinutuziumab) trials . In those studies, the PFS benefit of BTKis was apparent, yet irrespective of the IGHV gene SHM status. However, in the ECOG 1912 (ibrutinib + rituximab (IR) versus FCR)  and ELEVATE-TN (acalabrutinib ± obinutuzumab versus chlorambucil + obinutuzumab) trials, the impact of U-CLL became apparent: in particular, U-CLL patients had a statistically superior PFS when treated with a BTKi based regimen compared with CIT, while the PFS difference for M-CLL patients was not significanty different . Of note, longer follow-ups of RESONATE, RESONATE-2 and ELEVATE-TN trials showed no PFS difference between patients with M-CLL and U-CLL when treated with BTKis, highlighting the potential of this drug class to abrogate the prognostic impact of IGHV gene SHM status [27, 28, 30].
The relevance of IGHV gene SHM status has also been underscored by trials comparing the BCL2 inhibitor venetoclax plus anti-CD20 antibodies against CIT [31, 32]. Particularly for frontline treatment, in the CLL14 trial, U-CLL and M-CLL patients treated with venetoclax + obinutuzumab for 12 months had a superior PFS compared to those treated with chlorambucil + obinutuzumab . Interestingly, the PFS benefit for venetoclax + obinutuzumab appeared to be inferior for U-CLL versus M-CLL [34,35,36], raising the question as to whether fixed-duration treatment represents the optimal choice for U-CLL patients.
Altogether, immunogenetic analysis offers critical information that impacts the choice of treatment in CLL. A consensus exists that U-CLL patients have inferior outcomes when treated with CIT, therefore, these patients should preferentially be treated with novel agents .
BcR IG stereotypy is clinically relevant: what is the evidence?
BcR IG stereotypy defines subsets of patients with consistent disease biology [38,39,40,41,42,43,44], clinical presentation, course, and outcome [1, 45, 46], including the response to therapy , at least for major subsets that have been the focus of most research. From a clinical perspective, the most notable examples are stereotyped subsets #2 and #8, both associated with aggressive disease [11, 45, 46]. Subset #2 includes patients with CLL expressing BcR IG encoded by the IGHV3-21/IGLV3-21 genes with distinctive, restricted VH and VL CDR3 sequences [1, 47,48,49,50], of whom the majority (~60–65%) carry somatically hypermutated IGHV genes. Subset #2 displays a remarkable enrichment for mutations of the SF3B1 gene [38, 51, 52] and aberrations of the ATM gene, including both deletions and mutations . Retrospective analyses of different cohorts of increasing size revealed that subset #2 patients experience a particularly aggressive disease course, irrespective of their IGHV gene SHM status [46,47,48, 54,55,56,57]. Notably, similar results were obtained in a meta-analysis of 3 prospective clinical trials conducted by the German CLL Study Group (CLL8: fludarabine-cyclophosphamide-rituximab versus fludarabine-cyclophosphamide; CLL10: fludarabine-cyclophosphamide-rituximab versus bendamustine-rituximab; CLL11: chlorambucil versus chlorambucil-rituximab versus chlorambucil-obinutuzumab). Membership of subset #2 was found to be an independent prognostic marker for shorter TTFT, time-to-next-treatment (TTNT), and PFS, irrespective of the SHM status . These findings corroborate previous findings from the retrospective analysis of a large multi-institutional cohort of cases treated outside clinical trials where no improvement in OS was observed for subset #2 patients treated with CIT . This evidence suggests that CIT may be less optimal for subset #2 patients, while also highlighting the usefulness of this information for risk stratification of patients, a practice already followed by different study groups worldwide. In that regard, it is relevant to mention the results of the NCRI FLAIR trial, where a hazard ratio for disease progression and death of 0.32 was reported for subset #2 patients treated with FCR versus IR, though not reaching statistical significance (p = 0.191), likely due to low numbers (FCR, n = 20; IR, n = 26) .
Subset #8 includes patients with CLL expressing BcR IG encoded by the IGHV4-39/IGKV1(D)-39 genes with distinctive, restricted VH and VK CDR3 sequences [54, 59]. The clonotypic IGHV genes are unmutated [54, 59], whereas, interestingly, all patients carry IgG-switched BcR , which is remarkable given their overalllow incidence in CLL (~8% of all cases). Subset #8 displays a significant enrichment for trisomy 12  and NOTCH1 mutations [38, 51, 52], offering yet another example of subset-biased profiles of genomic aberrations.
In the original report by Ghiotto et al. , it was noted that 2 of 5 patients belonging to subset #8 experienced Richter’s transformation. This initial observation was subsequently corroborated by a collaborative study from Italy, where it was reported that patients belonging to subset #8 had a 10-fold higher risk for this development compared to all other patients with CLL . Subsequently, the meta-analysis of 3 prospective clinical trials conducted by the German CLL Study Group showed that patients belonging to subset #8 experienced the highest risk of Richter’s transformation, albeit the incidence was lower . On these grounds, a closer follow-up and a lower threshold for a fluorodeoxyglucose positron emission tomography (PET)/CT guided biopsy is warranted for subset #8 patients experiencing evidence of disease progression (also under therapy) in order to exclude the possibility of Richter’s transformation.
Assignment to subset #8 is also relevant from an immunogenetic standpoint, given the fact that the immunogenetic relation between the CLL and aggressive lymphoma clones represents the most important prognostic marker for cases with Richter syndrome (RS). More specifically, in the chemoimmunotherapy era, cases with immunogenetically unrelated RS clones exhibit a better prognosis (median survival of ∼5 years) compared to those with immunogenetically related RS clones (median survival of 8–16 months) [61, 62].
Next-generation immunogenetic analysis in CLL: new possibilities, new challenges
Until a few years ago, Sanger sequencing was the only available methodology for immunogenetic studies in CLL, offering reliable information provided that rigorous standards recommended by ERIC, the European Research Initiative on CLL, were met . The introduction of next-generation sequencing (NGS) allowed a far more detailed view of the BcR IG repertoires . On the plus side, this added to our understanding of CLL [65,66,67,68,69]. On the minus side, several aspects of NGS in immunogenetics are not yet settled, especially in a diagnostic context. Indicatively, one could mention amplification biases and quantification issues as well as the paucity of multicenter-validated protocols. Another important consideration concerns the 98% germline identity cut-off, applied for discriminating cases into U-CLL and M-CLL categories . This cut-off was decided through the study of Sanger-derived sequence data (i.e., low complexity) and its value has not been evaluated to the same degree in the NGS context (i.e., high complexity). Having said that, NGS immunogenetic analysis has not yet led to concrete evidence that would imply the need for reappraisal of the established 98% cut-off. Besides, employing NGS may cause issues of interpretation; indeed, NGS-based analysis can reveal the existence in the same patient of minor related clonotypes (corresponding to subclones arising due to intraclonal diversification) or unrelated clonotypes (corresponding to distinct clones) .
Update of the ERIC recommendations for immunogenetic analysis in CLL
ERIC has issued recommendations on how to perform immunogenetic analysis in CLL that have been widely used by the CLL community [63, 70, 71]. Our accumulated knowledge and experience along with recent developments in the field prompted us to update these recommendations; the full list of our updated recommendations appears in Table 1. Selected topics are elaborated in more detail in the following paragraphs.
Standard cases characterized by the presence of a single productive IGHV-IGHD-IGHJ gene rearrangement should be analyzed according to the ERIC guidelines. Within this category, two major challenges are posed.
The first challenge concerns cases with borderline-mutated status i.e., those with a germline identity of 97–97.99%, for which we have already raised caution regarding the prognostic implications despite their formal assignment to the M-CLL category . Recent studies showed that borderline-mutated cases either display a TTFT similar to that of M-CLL, excepting those belonging to subset #2 , or that the use of germline identy % as a continuous variable is associated with PFS and OS . Against that however, accumulating evidence from the study of the borderline-mutated SHM subgroup revealed an enrichment of cases assigned to not only subset #2 but also its immunogenetic satellite, subset #169 , as well as other IGLV3-21 expressing cases, all harboring the R110 mutation [74,75,76]. This feature has emerged as adverse-prognostic irrespective of the BcR IGH rearrangement, underscoring the need to closely follow-up patients with borderline SHM status.
The second challenge concerns BcR IG rearrangements belonging to the clinically aggressive stereotyped subsets #2 and #8 . As already mentioned, subset #2 membership has emerged as an independent prognostic factor for inferior response to CIT and shorter TTNT, whereas membership in subset #8 has been associated with the highest risk for Richter’s transformation among all CLL. This information must be conveyed clearly to the physicians and included in the lab report . Membership of either of these subsets can be investigated using either ARResT/AssignSubsets (http://bat.infspire.org/arrest/assignsubsets/) or IMGT/V-QUEST (http://www.imgt.org/IMGT_vquest/input), simply by selecting a new advanced functionality (Fig. 1).
Single unproductive rearrangements
IGHV-IGHD-IGHJ gene rearrangements can be rendered unproductive if they carry pseudogenes; out-of-frame VDJ junctions; stop codons; and/or indels leading to frameshifts within the coding part of the sequence. CLL cells are mature B cells that should express functional IG molecules on their surface. Hence, the identification of a single unproductive IGH rearrangement is exceedingly rare (<0.1% of all CLL)  and should always prompt further investigation in order to detect the productive IGHV-IGHD-IGHJ gene rearrangement on the other allele of the IGH locus. The possible mitigation steps when applying Sanger-based methodologies mainly concern the primers (utilize an alternative set), the starting material (try both gDNA and cDNA) and, occasionally, the sample (ask for a new sample). However, if all these approaches fail, NGS would be a reasonable alternative.
A similar issue may also arise with NGS in cases where the dominant clonotype is unproductive and coexists with one or more minor productive clonotypes. The most likely reasons for this finding are sequencing errors and/or amplification biases. In such cases, the analysis should be repeated; if the same result is obtained, one could attempt to PCR-amplify the unproductive as well as the most frequent productive rearrangements using IGHV- and IGHJ-gene specific primers and then apply bidirectional Sanger sequencing. If all the above strategies fail, single-cell analysis would be the only remaining approach. Admittedly, this is beyond the scope of a diagnostic lab and represents a research issue.
Double rearrangements: one productive and one unproductive
CLL cases with double rearrangements collectively account for 10.5% of all CLL ; within this category, the vast majority (~90% or 8.4% of all CLL) concern those cases with a productive and an unproductive rearrangement . To date, there is no evidence supporting any kind of biological and/or clinical relevance for unproductive BcRIG gene rearrangements in CLL. Thus, the SHM status of such cases should be defined based solely on the productive IG rearrangement, irrespective of the SHM status of the unproductive rearrangement.
Double productive rearrangements with discordant mutational status
The identification of two, unrelated productive IGH rearrangements in cases with CLL could be due to the co-existence of two independent B cell clones: either a CLL clone and a separate, non-CLL B cell clone (i.e., a different malignancy) or two distinct CLL cell clones. Systematic immunophenotypic, molecular and morphological cell analysis may be required in order to make this distinction. In terms of prognosis, CLL cases with two B cell clones (a CLL and a non-CLL) have been reported to display earlier need for treatment against cases with monoclonal CLL; this may reflect a stronger clinical relevance of the other B cell malignancy compared to CLL . In regard to cases with two unrelated CLL clones, if these clones present with concordant IGHV gene SHM status, they should be considered as either U-CLL or M-CLL, depending on the case.
A challenging scenario concerns cases carrying double productive rearrangements with discordant IGHV gene SHM status (<0.1% of all CLL) . Evidence from low-throughput analysis  supports the notion that, in most cases, multiple productive IGH rearrangements in CLL derive from independent clones and display clonal drift, given the change in their relative frequencies observed over time. From a clinical perspective, these cases were found to exhibit adverse prognostic markers and aggressive disease, presenting with early need for treatment, similar to patients with U-CLL . Evidence from NGS studies [68, 69] further supported the existence of biclonal cases in CLL. Interestingly, single-cell analysis showed that minor IG rearrangements can persist over time and may account for a sizeable fraction of the total repertoire (frequency range: 0.2–3%), indicating their biological and, perhaps, clinical relevance .
In this context, immunophenotypic analysis should be performed in order to verify the presence of the two B cell clonal populations. If their presence is verified, we recommend that both IGH gene rearrangements are reported to the physician. Regarding the clinical implications, the difficulty in providing a definitive assignment into one SHM category should be acknowledged. That said, erring on the side of benefit for the patient, we would propose/favor to manage these patients as U-CLL.
Multiple (3 or more) productive rearrangements
Patients carrying multiple (3 or more) IGH gene rearrangements were particularly scarce with Sanger analysis. Using NGS, multiple clonotypes can be detected in a varying fraction of cases: in most of these, multiple secondary clonotypes persisted over a significant period of time without major changes against the primary CLL clonotype [68, 69]. Having said that, a proper cut-off value for discriminating between secondary leukemic expansions, immune reactive cell clones and the normal “background” has not been established. Careful examination of the immunophenotypic results is strongly warranted in order to verify the presence of actual leukemic or reactive cell clones. To date, the evidence regarding the true meaning of multiple co-existing, immunogenetically unrelated, clonotypes remains inconclusive.
As above, we suggest that all verified IGH gene rearrangements are reported to the physician, including their relative frequencies. The difficulty in categorizing such cases when their SHM statusis discordant should be acknowledged. However, we would suggest to manage such cases as U-CLL, particularly if the dominant clonotype belongs to this category.
Immunogenetic analysis is key to understanding and managing CLL. Relevant procedures are standardized end-to-end, allowing to offer robust and accurate information in both general practice and clinical trials. As for any other laboratory test, challenging cases will always exist, albeit very infrequently: in such cases, careful assessment of all pertinent information is warranted before reaching conclusions. Any scientist and/or physician who would like to request assistance should also be aware of the dedicated online troubleshooting service by ERIC (https://barcelo.eventsair.com/submission-of-ighv-sequences/ighv-sequences/Site/Register) who can offer expert guidance and suggestions for overcoming the challenge.
ERIC will continue its efforts to facilitate the standardization of immunogenetic analysis in CLL, through accumulating knowledge from scientific discoveries as well as experience from the application of novel NGS methodologies.
Agathangelidis A, Chatzidimitriou A, Gemenetzi K, Giudicelli V, Karypidou M, Plevova K, et al. Higher-order connections between stereotyped subsets: implications for improved patient classification in CLL. Blood 2021;137. https://doi.org/10.1182/blood.2020007039.
Sutton L-A, Hadzidimitriou A, Baliakas P, Agathangelidis A, Langerak AW, Stilgenbauer S, et al. Immunoglobulin genes in chronic lymphocytic leukemia: key to understanding the disease and improving risk stratification. Haematologica 2017;102. https://doi.org/10.3324/haematol.2017.165605.
Baliakas P, Hadzidimitriou A, Sutton L-A, Rossi D, Minga E, Villamor N, et al. Recurrent mutations refine prognosis in chronic lymphocytic leukemia. Leukemia 2015;29. https://doi.org/10.1038/leu.2014.196.
Hallek M, Cheson BD, Catovsky D, Caligaris-Cappio F, Dighiero G, Döhner H, et al. iwCLL guidelines for diagnosis, indications for treatment, response assessment, and supportive management of CLL. Blood 2018;131. https://doi.org/10.1182/blood-2017-09-806398.
Damle RN, Wasil T, Fais F, Ghiotto F, Valetto A, Allen SL, et al. Ig V Gene mutation status and CD38 expression as novel prognostic indicators in chronic lymphocytic leukemia. Blood 1999;94. https://doi.org/10.1182/blood.V94.6.1840.
Hamblin TJ, Davis Z, Gardiner A, Oscier DG, Stevenson FK, Unmutated Ig VH genes are associated with a more aggressive form of chronic lymphocytic leukemia. Blood 1999;94. https://doi.org/10.1182/blood.V94.6.1848.
International CLL-IPI working group. An international prognostic index for patients with chronic lymphocytic leukaemia (CLL-IPI): a meta-analysis of individual patient data. The Lancet Oncol. 2016;17. https://doi.org/10.1016/S1470-2045(16)30029-8.
Hoechstetter MA, Busch R, Eichhorst B, Bühler A, Winkler D, Bahlo J, et al. Prognostic model for newly diagnosed CLL patients in Binet stage A: results of the multicenter, prospective CLL1 trial of the German CLL study group. Leukemia 2020;34. https://doi.org/10.1038/s41375-020-0727-y.
Condoluci A, Terzi di Bergamo L, Langerbeins P, Hoechstetter MA, Herling CD, de Paoli L, et al. International prognostic score for asymptomatic early-stage chronic lymphocytic leukemia. Blood. 2020;135:1859–69.
Brieghel C, Galle V, Agius R, da Cunha‐Bang C, Andersen MA, Vlummens P, et al. Identifying patients with chronic lymphocytic leukemia without need of treatment: End of endless watch and wait? Eur. J. Haematol. 2022. https://doi.org/10.1111/ejh.13743.
Jaramillo S, Agathangelidis A, Schneider C, Bahlo J, Robrecht S, Tausch E, et al. Prognostic impact of prevalent chronic lymphocytic leukemia stereotyped subsets: analysis within prospective clinical trials of the German CLL Study Group (GCLLSG). Haematologica 2019;105. https://doi.org/10.3324/haematol.2019.231027.
Kröber A, Seiler T, Benner A, Bullinger L, Brückle E, Lichter P, et al. V H mutation status, CD38 expression level, genomic aberrations, and survival in chronic lymphocytic leukemia. Blood 2002;100. https://doi.org/10.1182/blood.V100.4.1410.h81602001410_1410_1416.
Oscier DG, Gardiner AC, Mould SJ, Glide S, Davis ZA, Ibbotson RE, et al. Multivariate analysis of prognostic factors in CLL: clinical stage, IGVH gene mutational status, and loss or mutation of the p53 gene are independent prognostic factors. Blood 2002;100. https://doi.org/10.1182/blood.V100.4.1177.h81602001177_1177_1184.
Delgado J, Pratt G, Phillips N, Briones J, Fegan C, Nomdedeu J, et al. Beta2-microglobulin is a better predictor of treatment-free survival in patients with chronic lymphocytic leukaemia if adjusted according to glomerular filtration rate. Br. J. Haematol. 2009;145. https://doi.org/10.1111/j.1365-2141.2009.07699.x.
Kaderi MA, Kanduri M, Buhl AM, Sevov M, Cahill N, Gunnarsson R, et al. LPL is the strongest prognostic factor in a comparative analysis of RNA-based markers in early chronic lymphocytic leukemia. Haematologica 2011;96. https://doi.org/10.3324/haematol.2010.039396.
Pflug N, Bahlo J, Shanafelt TD, Eichhorst BF, Bergmann MA, Elter T, et al. Development of a comprehensive prognostic index for patients with chronic lymphocytic leukemia. Blood 2014;124. https://doi.org/10.1182/blood-2014-02-556399.
Parikh SA, Strati P, Tsang M, West CP, Shanafelt TD Should IGHV status and FISH testing be performed in all CLL patients at diagnosis? A systematic review and meta-analysis. Blood 2016;127. https://doi.org/10.1182/blood-2015-10-620864.
Shanafelt TD, Rabe KG, Kay NE, Zent CS, Jelinek DF, Reinalda MS, et al. Age at diagnosis and the utility of prognostic testing in patients with chronic lymphocytic leukemia. Cancer 2010;116. https://doi.org/10.1002/cncr.25292.
Ouillette P, Collins R, Shakhan S, Li J, Peres E, Kujawski L, et al. Acquired genomic copy number aberrations and survival in chronic lymphocytic leukemia. Blood. 2011;118:3051–61.
Stilgenbauer S, Schnaiter A, Paschka P, Zenz T, Rossi M, Döhner K, et al. Gene mutations and treatment outcome in chronic lymphocytic leukemia: results from the CLL8 trial. Blood. 2014;123:3247–54.
Fischer K, Bahlo J, Fink AM, Goede V, Herling CD, Cramer P, et al. Long-term remissions after FCR chemoimmunotherapy in previously untreated patients with CLL: updated results of the CLL8 trial. Blood 2016;127. https://doi.org/10.1182/blood-2015-06-651125.
Thompson PA, Tam CS, O’Brien SM, Wierda WG, Stingo F, Plunkett W, et al. Fludarabine, cyclophosphamide, and rituximab treatment achieves long-term disease-free survival in IGHV-mutated chronic lymphocytic leukemia. Blood 2016;127. https://doi.org/10.1182/blood-2015-09-667675.
Rossi D, Terzi-di-Bergamo L, de Paoli L, Cerri M, Ghilardi G, Chiarenza A, et al. Molecular prediction of durable remission after first-line fludarabine-cyclophosphamide-rituximab in chronic lymphocytic leukemia. Blood 2015;126. https://doi.org/10.1182/blood-2015-05-647925.
Munir T, Brown JR, O’Brien S, Barrientos JC, Barr PM, Reddy NM, et al. Final analysis from RESONATE: Up to six years of follow‐up on ibrutinib in patients with previously treated chronic lymphocytic leukemia or small lymphocytic lymphoma. Am. J. Hematol. 2019;94. https://doi.org/10.1002/ajh.25638.
Burger JA, Barr PM, Robak T, Owen C, Ghia P, Tedeschi A, et al. Long-term efficacy and safety of first-line ibrutinib treatment for patients with CLL/SLL: 5 years of follow-up from the phase 3 RESONATE-2 study. Leukemia 2020;34. https://doi.org/10.1038/s41375-019-0602-x.
Woyach JA, Ruppert AS, Heerema NA, Zhao W, Booth AM, Ding W, et al. Ibrutinib regimens versus chemoimmunotherapy in older patients with untreated CLL. N. Engl J Med. 2018;379:2517–28.
Ghia P, Pluta A, Wach M, Lysak D, Kozak T, Simkovic M, et al. ASCEND: Phase III, randomized trial of acalabrutinib versus idelalisib plus rituximab or bendamustine plus rituximab in relapsed or refractory chronic lymphocytic leukemia. J. Clin. Oncol. 2020;38. https://doi.org/10.1200/JCO.19.03355.
Moreno C, Greil R, Demirkan F, Tedeschi A, Anz B, Larratt L, et al. Ibrutinib plus obinutuzumab versus chlorambucil plus obinutuzumab in first-line treatment of chronic lymphocytic leukaemia (iLLUMINATE): a multicentre, randomised, open-label, phase 3 trial. The Lancet Oncol. 2019;20. https://doi.org/10.1016/S1470-2045(18)30788-5.
Shanafelt TD, Wang X v., Kay NE, Hanson CA, O’Brien S, Barrientos J, et al. Ibrutinib–Rituximab or chemoimmunotherapy for chronic lymphocytic leukemia. New Engl. J. Med. 2019;381. https://doi.org/10.1056/NEJMoa1817073.
Sharman JP, Egyed M, Jurczak W, Skarbnik A, Pagel JM, Flinn IW, et al. Acalabrutinib with or without obinutuzumab versus chlorambucil and obinutuzumab for treatment-naive chronic lymphocytic leukaemia (ELEVATE-TN): a randomised, controlled, phase 3 trial. The Lancet 2020;395. https://doi.org/10.1016/S0140-6736(20)30262-2.
Seymour JF, Kipps TJ, Eichhorst B, Hillmen P, D’Rozario J, Assouline S, et al. Venetoclax–Rituximab in relapsed or refractory chronic lymphocytic leukemia. New Engl. J. Med. 2018;378. https://doi.org/10.1056/NEJMoa1713976.
Fischer K, Al-Sawaf O, Bahlo J, Fink A-M, Tandon M, Dixon M, et al. Venetoclax and Obinutuzumab in patients with CLL and coexisting conditions. New Engl. J. Med. 2019;380. https://doi.org/10.1056/NEJMoa1815281.
Al-Sawaf O, Zhang C, Lu T, Liao MZ, Panchal A, Robrecht S, et al. Minimal residual disease dynamics after venetoclax-obinutuzumab treatment: extended off-treatment follow-up from the randomized CLL14 study. J Clin Oncol. 2021;39:4049–60.
Tausch E, Schneider C, Robrecht S, Zhang C, Dolnik A, Bloehdorn J, et al. Prognostic and predictive impact of genetic markers in patients with CLL treated with obinutuzumab and venetoclax. Blood 2020;135. https://doi.org/10.1182/blood.2019004492.
Tausch E, Schneider C, Yosifov D, Robrecht S, Zhang C, Al‐Sawaf O, et al. Genetic markers and outcome with front line obinutuzumab plus either chlorambucil or venetoclax ‐ updated analysis of the CLL14 trial. Hematol. Oncol. 2021;39:hon.30_2879.
Al-Sawaf O, Zhang C, Tandon M, Sinha A, Fink A-M, Robrecht S, et al. Venetoclax plus obinutuzumab versus chlorambucil plus obinutuzumab for previously untreated chronic lymphocytic leukaemia (CLL14): follow-up results from a multicentre, open-label, randomised, phase 3 trial. Lancet Oncol. 2020;21:1188–1200.
Eichhorst B, Robak T, Montserrat E, Ghia P, Niemann CU, Kater AP, et al. Chronic lymphocytic leukaemia: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann. Oncol. 2021;32. https://doi.org/10.1016/j.annonc.2020.09.019.
Sutton L-A, Young E, Baliakas P, Hadzidimitriou A, Moysiadis T, Plevova K, et al. Different spectra of recurrent gene mutations in subsets of chronic lymphocytic leukemia harboring stereotyped B-cell receptors. Haematologica. 2016;101:959–67.
Marincevic M, Cahill N, Gunnarsson R, Isaksson A, Mansouri M, Goransson H, et al. High-density screening reveals a different spectrum of genomic aberrations in chronic lymphocytic leukemia patients with “stereotyped” IGHV3-21 and IGHV4-34 B-cell receptors. Haematologica. 2010;95:1519–25.
Kanduri M, Cahill N, Göransson H, Enström C, Ryan F, Isaksson A, et al. Differential genome-wide array-based methylation profiles in prognostic subsets of chronic lymphocytic leukemia. Blood. 2010;115:296–305.
Marincevic M, Mansouri M, Kanduri M, Isaksson A, Goransson H, Smedby KE, et al. Distinct gene expression profiles in subsets of chronic lymphocytic leukemia expressing stereotyped IGHV4-34 B-cell receptors. Haematologica. 2010;95:2072–9.
Arvaniti E, Ntoufa S, Papakonstantinou N, Touloumenidou T, Laoutaris N, Anagnostopoulos A, et al. Toll-like receptor signaling pathway in chronic lymphocytic leukemia: distinct gene expression profiles of potential pathogenic significance in specific subsets of patients. Haematologica. 2011;96:1644–52.
Ntoufa S, Vardi A, Papakonstantinou N, Anagnostopoulos A, Aleporou-Marinou V, Belessi C, et al. Distinct innate immunity pathways to activation and tolerance in subgroups of chronic lymphocytic leukemia with distinct immunoglobulin receptors. Mol Med. 2012;18:1281–91.
Papakonstantinou N, Ntoufa S, Chartomatsidou E, Papadopoulos G, Hatzigeorgiou A, Anagnostopoulos A, et al. Differential microRNA profiles and their functional implications in different immunogenetic subsets of chronic lymphocytic leukemia. Mol Med. 2013;19:115–23.
Rossi D, Spina V, Cerri M, Rasi S, Deambrogi C, de Paoli L, et al. Stereotyped B-cell receptor is an independent risk factor of chronic lymphocytic leukemia transformation to richter syndrome. Clin Cancer Res. 2009;15:4415–22.
Baliakas P, Hadzidimitriou A, Sutton L-A, Minga E, Agathangelidis A, Nichelatti M, et al. Clinical effect of stereotyped B-cell receptor immunoglobulins in chronic lymphocytic leukaemia: a retrospective multicentre study. Lancet Haematol. 2014;1:e74–e84.
Tobin G, Thunberg U, Johnson A, Thörn I, Söderberg O, Hultdin M, et al. Somatically mutated Ig VH3-21 genes characterize a new subset of chronic lymphocytic leukemia. Blood. 2002;99:2262–4.
Tobin G, Thunberg U, Johnson A, Eriksson I, Söderberg O, Karlsson K, et al. Chronic lymphocytic leukemias utilizing the VH3-21 gene display highly restricted Vλ2-14 gene use and homologous CDR3s: implicating recognition of a common antigen epitope. Blood. 2003;101:4952–7.
Minici C, Gounari M, Übelhart R, Scarfò L, Dühren-von Minden M, Schneider D, et al. Distinct homotypic B-cell receptor interactions shape the outcome of chronic lymphocytic leukaemia. Nat Commun. 2017;8:15746.
Gemenetzi K, Psomopoulos F, Carriles AA, Gounari M, Minici C, Plevova K, et al. Higher-order immunoglobulin repertoire restrictions in CLL: the illustrative case of stereotyped subsets 2 and 169. Blood. 2021;137:1895–904.
Strefford JC, Sutton L-A, Baliakas P, Agathangelidis A, Malčíková J, Plevova K, et al. Distinct patterns of novel gene mutations in poor-prognostic stereotyped subsets of chronic lymphocytic leukemia: the case of SF3B1 and subset #2. Leukemia. 2013;27:2196–9.
Rossi D, Spina V, Bomben R, Rasi S, Dal-Bo M, Bruscaggin A, et al. Association between molecular lesions and specific B-cell receptor subsets in chronic lymphocytic leukemia. Blood. 2013;121:4902–5.
Navrkalova V, Young E, Baliakas P, Radova L, Sutton L-A, Plevova K, et al. ATM mutations in major stereotyped subsets of chronic lymphocytic leukemia: enrichment in subset #2 is associated with markedly short telomeres. Haematologica. 2016;101:e369–e373.
Stamatopoulos K, Belessi C, Moreno C, Boudjograh M, Guida G, Smilevska T, et al. Over 20% of patients with chronic lymphocytic leukemia carry stereotyped receptors: pathogenetic implications and clinical correlations. Blood. 2007;109:259–70.
Bomben R, Dal Bo M, Capello D, Forconi F, Maffei R, Laurenti L, et al. Molecular and clinical features of chronic lymphocytic leukaemia with stereotyped B cell receptors: results from an Italian multicentre study. Br J Haematol. 2009;144:492–506.
Baliakas P, Agathangelidis A, Hadzidimitriou A, Sutton L-A, Minga E, Tsanousa A, et al. Not all IGHV3-21 chronic lymphocytic leukemias are equal: prognostic considerations. Blood 2015;125. https://doi.org/10.1182/blood-2014-09-600874.
Baliakas P, Mattsson M, Hadzidimitriou A, Minga E, Agathangelidis A, Sutton L-A, et al. No improvement in long-term survival over time for chronic lymphocytic leukemia patients in stereotyped subsets #1 and #2 treated with chemo(immuno)therapy. Haematologica. 2018;103:e158–e161.
Hillmen P, Pitchford A, Bloor A, Broom A, Young M, Kennedy B, et al. Ibrutinib Plus Rituximab is superior to FCR in previously untreated CLL: Results of the Phase III NCRI FLAIR trial. Blood. 2021;138:642–642.
Ghiotto F, Fais F, Valetto A, Albesiano E, Hashimoto S, Dono M, et al. Remarkably similar antigen receptors among a subset of patients with chronic lymphocytic leukemia. J Clin Investig. 2004;113:1008–16.
Vardi A, Agathangelidis A, Sutton L-A, Chatzouli M, Scarfò L, Mansouri L, et al. IgG-Switched CLL has a distinct immunogenetic signature from the common MD variant: ontogenetic implications. Clin Cancer Res. 2014;20:323–30.
Abrisqueta P, Delgado J, Alcoceba M, González M, Oliveira AC, Loscertales J, et al. Clinical outcome and prognostic factors of patients with richter’s syndrome: retrospective multicenter Study of the Spanish Chronic Lymphocytic Leukemia (CLL) Study Group (GELLC). In: Blood. American Society of Hematology, 2017, pp 2995–2995.
Rossi D, Spina V, Deambrogi C, Rasi S, Laurenti L, Stamatopoulos K, et al. The genetics of Richter syndrome reveals disease heterogeneity and predicts survival after transformation. Blood. 2011;117:3391–401.
Rosenquist R, Ghia P, Hadzidimitriou A, Sutton L-A, Agathangelidis A, Baliakas P, et al. Immunoglobulin gene sequence analysis in chronic lymphocytic leukemia: updated ERIC recommendations. Leukemia 2017;31. https://doi.org/10.1038/leu.2017.125.
Davi F, Langerak AW, de Septenville AL, Kolijn PM, Hengeveld PJ, Chatzidimitriou A, et al. Immunoglobulin gene analysis in chronic lymphocytic leukemia in the era of next generation sequencing. Leukemia 2020;34. https://doi.org/10.1038/s41375-020-0923-9.
Gemenetzi K, Agathangelidis A, Sutton L-A, Vlachonikola E, Galigalidou C, Psomopoulos F, et al. Remarkable functional constraints on the antigen receptors of CLL Stereotyped Subset #2: high-throughput immunogenetic evidence. Blood 2018;132. https://doi.org/10.1182/blood-2018-99-119125.
Gemenetzi K, Agathangelidis A, Psomopoulos F, Pasentsis K, Koravou E, Iskas M, et al. VH CDR3-focused somatic hypermutation in CLL IGHV-IGHD-IGHJ gene rearrangements with 100% IGHV germline identity. Blood 2019;134. https://doi.org/10.1182/blood-2019-127979.
Sutton LA, Gemenetzi K, Stalika E, Vardi A, Psomopoulos F, Anagnostopoulos A, et al. High throughput immunoprofiling of chronic lymphocytic leukemia patients assigned to stereotyped subset #4: novel insights into the depth, diversity and temporal dynamics of clonal evolution. XVII International Workshop on Chronic Lymphocytic Leukemia May 12-15, New York 2017;58. https://doi.org/10.1080/10428194.2017.1377942.
Kriangkum J, Motz SN, Mack T, Beiggi S, Baigorri E, Kuppusamy H, et al. Single-cell analysis and next-generation immuno-sequencing show that multiple clones persist in patients with chronic lymphocytic leukemia. PLOS ONE 2015;10. https://doi.org/10.1371/journal.pone.0137232.
Stamatopoulos B, Timbs A, Bruce D, Smith T, Clifford R, Robbe P, et al. Targeted deep sequencing reveals clinically relevant subclonal IgHV rearrangements in chronic lymphocytic leukemia. Leukemia 2017;31. https://doi.org/10.1038/leu.2016.307.
Ghia P, Stamatopoulos K, Belessi C, Moreno C, Stilgenbauer S, Stevenson F, et al. ERIC recommendations on IGHV gene mutational status analysis in chronic lymphocytic leukemia. Leukemia 2007;21. https://doi.org/10.1038/sj.leu.2404457.
Langerak AW, Davi F, Ghia P, Hadzidimitriou A, Murray F, Potter KN, et al. Immunoglobulin sequence analysis and prognostication in CLL: guidelines from the ERIC review board for reliable interpretation of problematic cases. Leukemia 2011;25. https://doi.org/10.1038/leu.2011.49.
Raponi S, Ilari C, della Starza I, Cappelli LV, Cafforio L, Piciocchi A, et al. Redefining the prognostic likelihood of chronic lymphocytic leukaemia patients with borderline percentage of immunoglobulin variable heavy chain region mutations. Br J Haematol. 2020;189:853–9.
Jain P, Nogueras González GM, Kanagal-Shamanna R, Rozovski U, Sarwari N, Tam C, et al. The absolute percent deviation of IGHV mutation rather than a 98% cut-off predicts survival of chronic lymphocytic leukaemia patients treated with fludarabine, cyclophosphamide and rituximab. Br J Haematol. 2018;180:33–40.
Nadeu F, Royo R, Clot G, Duran-Ferrer M, Navarro A, Martín S, et al. IGLV3-21R110 identifies an aggressive biological subtype of chronic lymphocytic leukemia with intermediate epigenetics. Blood. 2021;137:2935–46.
Maity PC, Bilal M, Koning MT, Young M, van Bergen CAM, Renna V, et al. IGLV3-21 * 01 is an inherited risk factor for CLL through the acquisition of a single-point mutation enabling autonomous BCR signaling. Proc Natl Acad Sci. 2020;117:4320–7.
Stamatopoulos B, Smith T, Crompot E, Pieters K, Clifford R, Mraz M, et al. The light chain IgLV3-21 defines a new poor prognostic subgroup in chronic lymphocytic leukemia: results of a multicenter study. Clin Cancer Res. 2018;24:5048–57.
Sanchez M-L, Almeida M-L, Gonzalez D, Gonzalez M, Garcia-Marcos M-A, Balanzategui A, et al. Incidence and clinicobiologic characteristics of leukemic B-cell chronic lymphoproliferative disorders with more than one B-cell clone. Blood. 2003;102:2994–3002.
Plevova K, Francova HS, Burckova K, Brychtova Y, Doubek M, Pavlova S, et al. Multiple productive immunoglobulin heavy chain gene rearrangements in chronic lymphocytic leukemia are mostly derived from independent clones. Haematologica 2014;99. https://doi.org/10.3324/haematol.2013.087593.
ERIC is the WP7 on CLL of the European Leukemia Net (ELN) and the SWG on CLL of the European Hematology Association (EHA). This work has been supported in part by: the Hellenic Precision Medicine Network in Oncology, a flagship initiative of the General Secretariat of Research and Innovation of Greece; the Hellenic Foundation for Research and Innovation (HFRI) and the General Secretariat for Research and Innovation of Greece, under grant agreement No 336 (Project CLLon); the project ODYSSEAS (Intelligent and Automated Systems for enabling the Design, Simulation and Development of Integrated Processes and Products) implemented under the “Action for the Strategic Development on the Research and Technological Sector”, funded by the Operational Programme “Competitiveness, Entrepreneurship and Innovation” (NSRF 2014–2020) and co-financed by Greece and the European Union, with grant agreement no: MIS 5002462; the Swedish Cancer Society, the Swedish Research Council, the Knut and Alice Wallenberg Foundation, Karolinska Institutet, Karolinska University Hospital, and Radiumhemmets Forskningsfonder, Stockholm; Associazione Italiana per la Ricerca sul Cancro—AIRC, Milano, Italy (Special Program on Metastatic Disease—5 per mille #21198); TRANSCAN 2/NOVEL funded under JTC 2016 from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 643638.
KS has received research support from Janssen, Abbvie, and AstraZeneca. AWL has received research support from Janssen, Gilead and Roche. RR has received honoraria from Abbvie, AstraZeneca, Janssen, Illumina, and Roche. PG has received honoraria rom AbbVie, ArQule/MSD, AstraZeneca, BeiGene, Celgene/Juno/BMS, Janssen, Lilly/Loxo, MEI, Roche, Sanofi, and research support from AbbVie, AstraZeneca, Janssen, Sunesis. FD has received honoraria from Janssen and Gilead.
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Agathangelidis, A., Chatzidimitriou, A., Chatzikonstantinou, T. et al. Immunoglobulin gene sequence analysis in chronic lymphocytic leukemia: the 2022 update of the recommendations by ERIC, the European Research Initiative on CLL. Leukemia 36, 1961–1968 (2022). https://doi.org/10.1038/s41375-022-01604-2