Next Article in Journal
Pre- and Post-Zygotic TP53 De Novo Mutations in SHH-Medulloblastoma
Previous Article in Journal
Distinct Clinical Characteristics in Young-Onset Pancreatic Neuroendocrine Tumor
Previous Article in Special Issue
Meta-Analysis Reveals Significant Sex Differences in Chronic Lymphocytic Leukemia Progression in the Eµ-TCL1 Transgenic Mouse Model
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Editorial

Chronic Lymphocytic Leukemia

by
Tiziana Vaisitti
1,*,
Francesca Arruga
1 and
Alessandra Ferrajoli
2
1
Department of Medical Sciences, University of Torino, 10126 Torino, Italy
2
Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
*
Author to whom correspondence should be addressed.
Cancers 2020, 12(9), 2504; https://doi.org/10.3390/cancers12092504
Submission received: 24 August 2020 / Accepted: 26 August 2020 / Published: 3 September 2020
(This article belongs to the Special Issue Chronic Lymphocytic Leukemia)
This Special Issue of Cancers, made up of nine articles (four original papers, four reviews, and a brief report), is dedicated to chronic lymphocytic leukemia (CLL). CLL is a monoclonal disorder characterized by a progressive accumulation of CD19+/CD5+/IgMlow/IgDlow mature B lymphocytes and is the most common form of leukemia found in adults in Western countries [1]. The clinical outcome of CLL is quite heterogeneous, with some patients surviving for many years without any therapy and eventually succumbing to unrelated diseases, whereas others die rapidly, within 2–3 years of diagnosis, because of complications from CLL and despite aggressive therapies [2]. In 10–12% of patients, CLL can evolve to a more aggressive lymphoma, typically diffuse large B cell lymphoma, named Richter’s syndrome, which is still a clinical need due to the lack of efficacy of CLL therapies [3,4].
In the past two decades, significant efforts have been made (i) to define prognostic factors to stratify patients and decide best patient management, (ii) to better understand the biology of the disease, and (iii) to identify potential therapeutic targets and validate novel therapeutic opportunities.
All these efforts have given rise to approximately 12,000 publications exploring the different aspects of the disease. We now have several prognostic factors, in addition to the historical IgVH mutational status [5], that help in stratifying CLL patients and somehow predict disease clinical outcome. These include surface markers (e.g., CD38, CD49d), intracellular kinases (e.g., Zap70), chromosomal aberrations (e.g., del17p, trisomy 12), and genetic variants in critical genes (e.g., TP53, BIRC3, SF3B1, NOTCH1) [6,7,8,9,10,11]. When talking about CLL biology, a huge body of work has been made to define how CLL cells signal and which are the main players involved (e.g., B-cell receptor BCR, among others) [12,13,14]; how they communicate with the microenvironment in a bidirectional crosstalk; how they migrate and recirculate from blood to lymphoid organs, where leukemic cells can find the right cocktails of stimuli that lead to proliferation, survival, and most importantly, to resistance to therapy [15,16]. In this context, significant input has come from the use of ad hoc-generated cellular models as well as in vivo studies, based on the use of the TCL1 mouse model and xenografts [17,18,19,20,21,22]. Finally, regarding therapies, we can now rely on a plethora of compounds and therapeutic options that are able to target CLL cells from different sides. Chemotherapy alone or combined with immunotherapy (e.g., Rituximab) remains a gold standard for most patients and in most countries. However, in recent years, a new wave of drugs has reached the market, mostly designed to selectively target the critical pathways that CLL cells rely on (e.g., Ibrutinib, Venetoclax) [23,24,25].
In this issue, some aspects of these three main features of CLL are both reported and discussed as novel findings and reviewed to make an update of the available data. Porrazzo and colleagues present an original article where they describe the prognostic significance of PET/CT applied to CLL to identify patients characterized by a more pronounced rate of proliferating cells in lymph nodes, an inferior outcome, and at higher risk of developing Richter’s syndrome [26]. In a large, retrospective multicenter study, Autore and colleagues report serum lactate dehydrogenase levels as a statistically significant prognostic marker that can predict progression-free survival, treatment-free survival, and overall survival in CLL patients that harbor trisomy 12 [27]. In contrast, Cohen and co-workers reviewed all the main novel biomarkers and their role as prognosticators of disease progression and overall survival in different subsets of CLL patients treated with different therapeutic approaches, including both chemoimmuno- and targeted therapy [28].
Other papers of this Special Issue are instead focused on some aspects of CLL biology and the possibility to selectively target leukemic cells based on their main biological features or how CLL cells behave following targeted therapy administration. Efremov, Turkalj, and Laurenti point their attention to the B cell receptor (BCR), a driver receptor in CLL as well as in other B cell malignancies. They review the main mechanisms that are responsible for its activation, the consequences of BCR pathway stimulation, and how the various BCR inhibitors impact on clinical aspects in CLL [29]. In line with the need to better understand and characterize the functional impact of the available BCR-targeting agents, Kost and colleagues present an original article where they study the effects of idelalisib, a potent PI3Kδ inhibitor, administered alone or in association with bendamustine. Their data indicate a synergism between these drugs, even in the more aggressive subset of patients or in the presence of a protective microenvironment. Moreover, they report a global RNA synthesis decrease in CLL cells treated with idelalisib, suggesting that this drug may be effective by downmodulating several critical pathways for CLL cell survival [30]. Patrussi, Capitani, and Baldari present an overview of the functions of an adaptor protein, p66Shc, known to have proapoptotic and pro-oxidant roles. They discuss how this protein controls different aspects of B cells biology, including cell trafficking, and the peculiar p66Shc deficiency that characterizes CLL cells and the biological meaning of this loss [31].
Andreani and colleagues present the state-of-the-art on tumor suppressor genes and proteins in CLL, a field still largely unexplored. They describe how tumor suppressors impact on survival and apoptosis of leukemic cells and finally, discuss how these proteins may represent novel opportunities to target these tumor cells [32]. Another field in CLL that is still poorly covered is metabolism of leukemic cells. In the research article presented by Chowdhury et al., they measured the mitochondrial respiration capacity of CLL cells and compared this rate to normal B lymphocytes, finding that tumor cells are characterized by a higher respiration rate and that this feature is correlated to several known negative prognosticators in CLL. More interestingly, they showed the mitochondrial respiration of leukemic cells drop-off in Ibrutinib-treated patients, suggesting that this drug is capable of impacting CLL mitochondrial bioenergetics [33].
Finally, this Special Issue includes a brief report by Koch and colleagues that summarizes the results from a meta-analysis on a large cohort of TCL1 mice, showing that leukemia progression is significantly accelerated in female TCL1 mice compared to males and that additional genetic lesions, besides the TCL1 transgene, further contribute to disease progression [34]. These findings pose several questions on the use of this model, the only one, up to now, available to mimic the human disease apart from xenografts. They also suggest that the experimental design needs to be carefully planned, taking in mind these potential confounding elements.
Overall, this Special Issue of Cancers is a collection of articles discussing different aspects of CLL, some of which are in an advanced stage of knowledge, while others are just at the beginning, opening for novel and interesting points of discussion in the near future. Moreover, this issue underlines our need to understand tumor biology to design novel and more efficacious therapies to eradicate this leukemia.

Funding

This research received no external funding.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Chiorazzi, N.; Rai, K.R.; Ferrarini, M. Chronic lymphocytic leukemia. N. Engl. J. Med. 2005, 352, 804–815. [Google Scholar] [CrossRef] [Green Version]
  2. Hallek, M. Chronic lymphocytic leukemia: 2020 update on diagnosis, risk stratification and treatment. Am. J. Hematol. 2019, 94, 1266–1287. [Google Scholar] [CrossRef] [Green Version]
  3. Rossi, D.; Cerri, M.; Capello, D.; Deambrogi, C.; Rossi, F.M.; Zucchetto, A.; De Paoli, L.; Cresta, S.; Rasi, S.; Spina, V.; et al. Biological and clinical risk factors of chronic lymphocytic leukaemia transformation to Richter syndrome. Br. J. Haematol. 2008, 142, 202–215. [Google Scholar] [CrossRef]
  4. Rossi, D.; Gaidano, G. Richter syndrome: Pathogenesis and management. Semin. Oncol. 2016, 43, 311–319. [Google Scholar] [CrossRef]
  5. Oscier, D.G.; Thompsett, A.; Zhu, D.; Stevenson, F.K. Differential rates of somatic hypermutation in V(H) genes among subsets of chronic lymphocytic leukemia defined by chromosomal abnormalities. Blood 1997, 89, 4153–4160. [Google Scholar] [CrossRef]
  6. Damle, R.N.; Wasil, T.; Fais, F.; Ghiotto, F.; Valetto, A.; Allen, S.L.; Buchbinder, A.; Budman, D.; Dittmar, K.; Kolitz, J.; et al. Ig V gene mutation status and CD38 expression as novel prognostic indicators in chronic lymphocytic leukemia. Blood 1999, 94, 1840–1847. [Google Scholar] [CrossRef] [PubMed]
  7. Rassenti, L.Z.; Huynh, L.; Toy, T.L.; Chen, L.; Keating, M.J.; Gribben, J.G.; Neuberg, D.S.; Flinn, I.W.; Rai, K.R.; Byrd, J.C.; et al. ZAP-70 compared with immunoglobulin heavy-chain gene mutation status as a predictor of disease progression in chronic lymphocytic leukemia. N. Engl. J. Med. 2004, 351, 893–901. [Google Scholar] [CrossRef]
  8. Dohner, H.; Stilgenbauer, S.; Benner, A.; Leupolt, E.; Krober, A.; Bullinger, L.; Dohner, K.; Bentz, M.; Lichter, P. Genomic aberrations and survival in chronic lymphocytic leukemia. N. Engl. J. Med. 2000, 343, 1910–1916. [Google Scholar] [CrossRef] [Green Version]
  9. Messina, M.; Del Giudice, I.; Khiabanian, H.; Rossi, D.; Chiaretti, S.; Rasi, S.; Spina, V.; Holmes, A.B.; Marinelli, M.; Fabbri, G.; et al. Genetic lesions associated with chronic lymphocytic leukemia chemo-refractoriness. Blood 2014, 123, 2378–2388. [Google Scholar] [CrossRef] [PubMed]
  10. Quesada, V.; Conde, L.; Villamor, N.; Ordonez, G.R.; Jares, P.; Bassaganyas, L.; Ramsay, A.J.; Bea, S.; Pinyol, M.; Martinez-Trillos, A.; et al. Exome sequencing identifies recurrent mutations of the splicing factor SF3B1 gene in chronic lymphocytic leukemia. Nat. Genet. 2011, 44, 47–52. [Google Scholar] [CrossRef] [PubMed]
  11. Puente, X.S.; Pinyol, M.; Quesada, V.; Conde, L.; Ordonez, G.R.; Villamor, N.; Escaramis, G.; Jares, P.; Bea, S.; Gonzalez-Diaz, M.; et al. Whole-genome sequencing identifies recurrent mutations in chronic lymphocytic leukaemia. Nature 2011, 475, 101–105. [Google Scholar] [CrossRef] [Green Version]
  12. Stevenson, F.K.; Forconi, F.; Packham, G. The meaning and relevance of B-cell receptor structure and function in chronic lymphocytic leukemia. Semin. Hematol. 2014, 51, 158–167. [Google Scholar] [CrossRef] [PubMed]
  13. Ten Hacken, E.; Gounari, M.; Ghia, P.; Burger, J.A. The importance of B cell receptor isotypes and stereotypes in chronic lymphocytic leukemia. Leukemia 2019, 33, 287–298. [Google Scholar] [CrossRef]
  14. Stamatopoulos, K.; Agathangelidis, A.; Rosenquist, R.; Ghia, P. Antigen receptor stereotypy in chronic lymphocytic leukemia. Leukemia 2017, 31, 282–291. [Google Scholar] [CrossRef] [PubMed]
  15. Burger, J.A.; Gribben, J.G. The microenvironment in chronic lymphocytic leukemia (CLL) and other B cell malignancies: Insight into disease biology and new targeted therapies. Semin. Cancer Biol. 2014, 24, 71–81. [Google Scholar] [CrossRef] [PubMed]
  16. Sutton, L.A.; Rosenquist, R. The complex interplay between cell-intrinsic and cell-extrinsic factors driving the evolution of chronic lymphocytic leukemia. Semin. Cancer Biol. 2015, 34, 22–35. [Google Scholar] [CrossRef] [PubMed]
  17. Bichi, R.; Shinton, S.A.; Martin, E.S.; Koval, A.; Calin, G.A.; Cesari, R.; Russo, G.; Hardy, R.R.; Croce, C.M. Human chronic lymphocytic leukemia modeled in mouse by targeted TCL1 expression. Proc. Natl. Acad. Sci. USA 2002, 99, 6955–6960. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  18. Durig, J.; Ebeling, P.; Grabellus, F.; Sorg, U.R.; Mollmann, M.; Schutt, P.; Gothert, J.; Sellmann, L.; Seeber, S.; Flasshove, M.; et al. A novel nonobese diabetic/severe combined immunodeficient xenograft model for chronic lymphocytic leukemia reflects important clinical characteristics of the disease. Cancer Res. 2007, 67, 8653–8661. [Google Scholar] [CrossRef] [Green Version]
  19. Bagnara, D.; Kaufman, M.S.; Calissano, C.; Marsilio, S.; Patten, P.E.; Simone, R.; Chum, P.; Yan, X.J.; Allen, S.L.; Kolitz, J.E.; et al. A novel adoptive transfer model of chronic lymphocytic leukemia suggests a key role for T lymphocytes in the disease. Blood 2011, 117, 5463–5472. [Google Scholar] [CrossRef]
  20. Bertilaccio, M.T.; Scielzo, C.; Simonetti, G.; Ten Hacken, E.; Apollonio, B.; Ghia, P.; Caligaris-Cappio, F. Xenograft models of chronic lymphocytic leukemia: Problems, pitfalls and future directions. Leukemia 2013, 27, 534–540. [Google Scholar] [CrossRef]
  21. Vaisitti, T.; Audrito, V.; Serra, S.; Buonincontri, R.; Sociali, G.; Mannino, E.; Pagnani, A.; Zucchetto, A.; Tissino, E.; Vitale, C.; et al. The enzymatic activities of CD38 enhance CLL growth and trafficking: Implications for therapeutic targeting. Leukemia 2015, 29, 356–368. [Google Scholar] [CrossRef]
  22. Vaisitti, T.; Braggio, E.; Allan, J.N.; Arruga, F.; Serra, S.; Zamo, A.; Tam, W.; Chadburn, A.; Furman, R.R.; Deaglio, S. Novel Richter Syndrome Xenograft Models to Study Genetic Architecture, Biology, and Therapy Responses. Cancer Res. 2018, 78, 3413–3420. [Google Scholar] [CrossRef] [Green Version]
  23. Rogers, A.; Woyach, J.A. BTK inhibitors and anti-CD20 monoclonal antibodies for treatment-naive elderly patients with CLL. Ther. Adv. Hematol. 2020, 11. [Google Scholar] [CrossRef]
  24. Iovino, L.; Shadman, M. Novel Therapies in Chronic Lymphocytic Leukemia: A Rapidly Changing Landscape. Curr. Treat. Options Oncol. 2020, 21, 24. [Google Scholar] [CrossRef] [PubMed]
  25. Scheffold, A.; Stilgenbauer, S. Revolution of Chronic Lymphocytic Leukemia Therapy: The Chemo-Free Treatment Paradigm. Curr. Oncol. Rep. 2020, 22, 16. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  26. Porrazzo, M.; Nicolai, E.; Riminucci, M.; Vitale, C.; Coscia, M.; De Paoli, L.; Rago, A.; Buscicchio, G.; Maestrini, G.; Ligia, S.; et al. Prognostic Significance of PET/CT in Patients with Chronic Lymphocytic Leukemia (CLL) Treated with Frontline Chemoimmunotherapy. Cancers 2020, 12. [Google Scholar] [CrossRef] [PubMed]
  27. Autore, F.; Strati, P.; Innocenti, I.; Corrente, F.; Trentin, L.; Cortelezzi, A.; Visco, C.; Coscia, M.; Cuneo, A.; Gozzetti, A.; et al. Elevated Lactate Dehydrogenase Has Prognostic Relevance in Treatment-Naive Patients Affected by Chronic Lymphocytic Leukemia with Trisomy 12. Cancers 2019, 11. [Google Scholar] [CrossRef] [Green Version]
  28. Cohen, J.A.; Bomben, R.; Pozzo, F.; Tissino, E.; Harzschel, A.; Hartmann, T.N.; Zucchetto, A.; Gattei, V. An Updated Perspective on Current Prognostic and Predictive Biomarkers in Chronic Lymphocytic Leukemia in the Context of Chemoimmunotherapy and Novel Targeted Therapy. Cancers 2020, 12. [Google Scholar] [CrossRef] [Green Version]
  29. Efremov, D.G.; Turkalj, S.; Laurenti, L. Mechanisms of B Cell Receptor Activation and Responses to B Cell Receptor Inhibitors in B Cell Malignancies. Cancers 2020, 12. [Google Scholar] [CrossRef]
  30. Kost, S.E.F.; Saleh, A.; Mejia, E.M.; Mostafizar, M.; Bouchard, E.D.J.; Banerji, V.; Marshall, A.J.; Gibson, S.B.; Johnston, J.B.; Katyal, S. Transcriptional Modulation by Idelalisib Synergizes with Bendamustine in Chronic Lymphocytic Leukemia. Cancers 2019, 11. [Google Scholar] [CrossRef] [Green Version]
  31. Patrussi, L.; Capitani, N.; Baldari, C.T. P66Shc: A Pleiotropic Regulator of B Cell Trafficking and a Gatekeeper in Chronic Lymphocytic Leukemia. Cancers 2020, 12. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  32. Andreani, G.; Carra, G.; Lingua, M.F.; Maffeo, B.; Brancaccio, M.; Taulli, R.; Morotti, A. Tumor Suppressors in Chronic Lymphocytic Leukemia: From Lost Partners to Active Targets. Cancers 2020, 12. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. Roy Chowdhury, S.; Bouchard, E.D.J.; Saleh, R.; Nugent, Z.; Peltier, C.; Mejia, E.; Hou, S.; McFall, C.; Squires, M.; Hewitt, D.; et al. Mitochondrial Respiration Correlates with Prognostic Markers in Chronic Lymphocytic Leukemia and Is Normalized by Ibrutinib Treatment. Cancers 2020, 12. [Google Scholar] [CrossRef] [Green Version]
  34. Koch, M.; Reinartz, S.; Saggau, J.; Knittel, G.; Rosen, N.; Fedorchenko, O.; Thelen, L.; Barthel, R.; Reinart, N.; Seeger-Nukpezah, T.; et al. Meta-Analysis Reveals Significant Sex Differences in Chronic Lymphocytic Leukemia Progression in the Emicro-TCL1 Transgenic Mouse Model. Cancers 2020, 12. [Google Scholar] [CrossRef] [PubMed]

Share and Cite

MDPI and ACS Style

Vaisitti, T.; Arruga, F.; Ferrajoli, A. Chronic Lymphocytic Leukemia. Cancers 2020, 12, 2504. https://doi.org/10.3390/cancers12092504

AMA Style

Vaisitti T, Arruga F, Ferrajoli A. Chronic Lymphocytic Leukemia. Cancers. 2020; 12(9):2504. https://doi.org/10.3390/cancers12092504

Chicago/Turabian Style

Vaisitti, Tiziana, Francesca Arruga, and Alessandra Ferrajoli. 2020. "Chronic Lymphocytic Leukemia" Cancers 12, no. 9: 2504. https://doi.org/10.3390/cancers12092504

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop