SnapShot: Chronic Lymphocytic Leukemia Maria Ciccone,1 Alessandra Ferrajoli,1 Michael J. Keating,1 and George A. Calin1,2 Department of Leukemia, 2Department of Experimental Therapeutics The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA

1

Primary genetic event

Cell of Origin

Evolutionary biology

B cell receptor stimulation, secondary genetic events

MBL: Monoclonal B cell lymphocytosis

(Early mutations and/or non-coding RNA abnormalities)

IGHV unmutated MBL

T cell independent zone

Follicular mantle

CLL: Chronic lymphocytic leukemia

Progressed CLL

Memory CD27+ B cell

T cell

Secondary genetic events: del(13q), del(11q) (ATM, miR-34b/c), trisomy 12, del(17p), TP53 and NOTCH1 mutations

Mutations in NOTCH signaling, mRNA splicing/processing/transport, DNA damage response pathways

Marginal Zone

T cell dependent zone

B cell

Clonal expansion, antigen stimulation, early genetic events: del(13q), high miR-155

Marginal Zone B cell

CD34+ cell SF3B1, NOTCH1, NFKBIE, XPO1

IGHV unmutated CLL

Expansion of resistant clones and additional genetic abnormalities: del(17p)/TP53 mutations, NOTCH1, SF3B1, BIRC3, ATM mutations, abnormal MYC levels, high miR-155 and miR-181 family

IGHV Mutated CLL

IGHV Mutated MBL

Naïve B cell Proliferation center

Refractory CLL or Richter transformation

Mutations in innate inflammatory pathways

Therapy from the bench to the bedside

ComplementMAC mediated cytotoxicity

BAD

Lyn

BCL-2 BCL-xL MCL-1

NOXA Direct death

P

B cell receptor targeting agents:

Syk

AKT

B cell antigen

CELL DEATH

P

Cyclophosphamide Chlorambucil Bendamustine Fludarabine Pentostatin

CD38

HSP90 Pl3K

P

miR-15a miR-16-1

p53

C3

B CELL

CD79A

B cell antigen

CD79B

C1

Therapeutic agents in RED

B-cell receptor

Chemotherapy

Antibody-dependent cell-mediated cytoxicity

CD19

Anti-CD20 Anti-CD19 Anti-CD23 Anti-CD38

Anti heat shock protein

FcR

ZAP70

EFFECTOR CELL

Monoclonal antibodies

miR-34

BAX

BTK

BCL-2 inhibitors

PLCγ P

mTOR

IP3

DAG

BTK inhibitors PI3K inhibitors Tyrosine kinase inhibitors PP2A phosphatase activating drugs (PADs) *

* Not in clinical phase

Ca++

Immunomodulatory agents T CELL

NF-κB

Fas

B7-1 MHC-I

FasL CD28 TCR CD40L

Cyclin B/ CDK1

CD40 Cyclin A/ CDK2

PROLIFERATION SURVIVAL

G1

Cytokine release

Prognostic factors

Low

Patient-related markers

19

CD

Anti CD19 Costimulatory Molecule 2

Costimulatory Molecule 1

19

Cyclin-dependent kinase (CDK) inhibitors

Cyclin E/CDK2

Risk category

CD

Cyclin D/CDK4,6

G2 M S

NF-κB

CD3ζ

CAR T-cell First and second generation

cLL mouse models Models

Disease-related markers

Mutant gene/driver

B cell phenotype

CLL subtype

Eµ-TCL1 transgenic

T cell leukemia/lymphoma protein 1A (TCL1)

CD5+IgM+B220+ Unmutated stereotypic CDR3

Aggressive

Age ≤ 60 years

β2 microglobulin < 3.5 mg/L

Normal FISH or deletion 13q-

CD38 ≤ 30%

ECOG PS 0

Rai stage 0-1

Mutated IGVH

ZAP70 ≤ 20%

Serum Thymidine Kinase < 10.0 U/L

MYD88

TNF receptor associated factor 2 (TRAF2) and BCL-2

CD5+IgMhighIgDlow/B220moderateCD21low/CD23-CD11blow

N/A

Female

TRAF2DN/BCL-2 transgenic

Age > 60 years

β2 microglobulin > 3.5 mg/L

Unmutated IGVH and IGHV4-39

CD38 > 30%

Irf4-/-Vh11

Interferon regulatory factor 4 (IRF4) deficiency

CD5+IgM+CD19+ B220low/-CD23-CD21IgDlowCD1dint

MBL, indolent and aggressive

ECOG PS > 0

Rai stage 2-4

Deletion 11qand deletion 17p

ZAP70 > 20%

TNFSF13/APRIL transgenic

A proliferation-inducing ligand APRIL

IgM+CD5+B220+

Indolent

Male

Serum Thymidine Kinase > 10.0 U/L

Short telomere

Stereotyped CDR3

Altered microRNA

Deletion of DLEU2/miR-15a/16-1 cluster or transgenic miR-29a

IgM+CD5+B220+

Indolent

New Zealand Black

Age-associated

IgM+B220dimCD5dim

Indolent, familial

High

ATM, TP53, NOTCH1, and/or BIRC abnormalities

770 Cancer Cell 26, November 10, 2014 ©2014 Elsevier Inc.

DOI http://dx.doi.org/10.1016/j.ccell.2014.10.020

See online version for legend and references.

SnapShot: Chronic Lymphocytic Leukemia Maria Ciccone,1 Alessandra Ferrajoli,1 Michael J. Keating,1 and George A. Calin1,2 Department of Leukemia, 2Department of Experimental Therapeutics The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA

1

Cell of Origin Chronic lymphocytic leukemia (CLL) is the most common leukemia among adults in western countries. Although several hypotheses have been proposed, the precise cell of origin of CLL is still debated. CLL tumor cells typically express CD19, CD5, CD23, and the low-intensity surface immunoglobulins IgM and IgD. The identification of two subsets of CLL, mutated (mCLL) and unmutated (uCLL), according to immunoglobulin heavy (IGH) chain variable gene segment (IGHV) mutational status, led to the hypothesis that mCLL might derive from a cell that has experienced the germinal center, where the somatic hypermutation occurs. On the other hand, a naive B cell could represent the normal counterpart of uCLL. However, gene expression profiling studies have shown that mCLL and uCLL are transcriptionally overlapping and clearly distinct from normal CD5+ cells. This observation suggests that both subsets, not only mCLL, might originate from antigen-experienced cells. Accordingly, it has been postulated that mCLL derives from a CD5+CD27+ memory B cell, whereas uCLL tends to be more similar to CD5+CD27− cells that can be activated by antigenic stimuli in a T cell-independent fashion under some circumstances. Interestingly, recent findings have substantially revolutionized the concept that CLL is a disease arising from a mature B cell, indicating the involvement of a hematopoietic stem cell in the transformation process. Through the use of deep sequencing of flow-sorted cells from mCLL and uCLL patients, acquired mutations affecting known lymphoid oncogenes (including SF3B1 and NOTCH1) were observed in both myeloid progenitors (CD34+) and CLL tumor cells, suggesting that driver mutations probably occur early in the evolutionary biography of CLL. According to the hypothesis that the cell of origin is a common hematopoietic precursor, the naive B cell, harboring clonal passenger mutations, would enter the lymph node, where secondary genetic events triggered by B cell receptor (BCR) activation may favor definitive clonal transformation and expansion of a CD5+ B cell. However, mutated genes in CLL B cells cluster in a few pathways (i.e., NOTCH1 signaling, mRNA splicing processing and transport, DNA damage response, and innate inflammatory response) that are differently represented in mCLL and uCLL. Evolution, Progression, and Transformation The progression of CLL disease matches the paradigm of clonal evolution elapsing from the initiating event(s), following malignant transformation of a CD5+ B cell through to Richter’s transformation. Monoclonal B cell lymphocytosis (MBL), an indolent condition, is believed to precede overt CLL. The next step to the CLL stage is driven by stimulation of the B cell receptor by microenvironmental antigens. Subsequently, the occurrence of secondary genomic abnormalities yielding clonal heterogeneity within tumors leads to progressed CLL. Finally, the selection and expansion of highly fit subclones, those bearing driver mutations, in response to intrinsic (genetic instability) or extrinsic (chemotherapy) pressures is responsible of disease progression, Richter’s transformation, and chemorefractoriness. Prognostic Factors Over the last two decades, several studies have shown a relationship between the clinical heterogeneity of CLL and the presence of specific patient- or disease-associated features. Several cytogenetic abnormalities and IGHV mutational status have been validated as predictors of clinical evolution and chemoresistance. Most recently, specific IGHV gene usage and stereotyped CDR3, ZAP70, and CD38 expression levels have been associated with a higher susceptibility of BCR to be stimulated by antigen and thus with an increased predisposition to cell proliferation and clonal expansion. MicroRNAs (miRNAs), small regulatory noncoding RNAs, are causally involved in CLL initiation (cluster of miR-15a and miR-16-1), progression (miR-21, miR-29 family, or miR34 family), and resistance to therapy (miR-155 and miR-181 family). The availability of next-generation sequencing data has provided us with new insights into the understanding of CLL biology and clinical heterogeneity. NOTCH1, BIRC3, MYC, SF3B1, and MYD88 abnormalities have emerged as key drivers in CLL progression and, therefore, as powerful tools to define prognosis and targets for therapy in the near future. Therapy: From Bench to Bedside Although chemoimmunotherapy is still recommended for the treatment of certain CLL patients, new compounds that specifically target cellular pathways that are abnormally regulated in CLL tumor cells have been approved for the treatment of patients with CLL. Many more new molecules with a variety of targeted mechanisms of action are in various stages of preclinical and clinical development. Immunomodulatory agents and chimeric-antigen receptor (CAR) T cells have also shown marked antileukemic activity in patients with CLL, which underscores the importance of the immune system and the microenvironment in disease control. Additionally, antisense and anti-miRNA molecules are opening new avenues for the treatment of CLL. Mouse Models Several mouse models reproducing different subtypes of CLL have been developed. Transgenic mice overexpressing TCL1 in B cells (Eµ-TCL1 mice) recapitulate aggressive disease, whereas mir-15a/16-1-deleted mice and the New Zealand Black strain mimic indolent CLL. Mouse models represent an important tool to help decipher the role of gene mutations in CLL and allow preclinical testing of new compounds. References Calin, G.A., and Croce, C.M. (2009). Blood 114, 4761–4770. Chiorazzi, N., and Ferrarini, M. (2011). Blood 117, 1781–1791. Damm, F., Mylonas, E., Cosson, A., Yoshida, K., Della Valle, V., Mouly, E., Diop, M., Scourzic, L., Shiraishi, Y., Chiba, K., et al. (2014). Cancer Discov. 4, 1088–1101. Gaidano, G., Foà, R., and Dalla-Favera, R. (2012). J. Clin. Invest. 122, 3432–3438. Landau, D.A., Carter, S.L., Stojanov, P., McKenna, A., Stevenson, K., Lawrence, M.S., Sougnez, C., Stewart, C., Sivachenko, A., Wang, L., et al. (2013). Cell 152, 714–726. Puente, X.S., and López-Otín, C. (2013). Nat. Genet. 45, 229–231. Rossi, D., Rasi, S., Spina, V., Bruscaggin, A., Monti, S., Ciardullo, C., Deambrogi, C., Khiabanian, H., Serra, R., Bertoni, F., et al. (2013). Blood 121, 1403–1412. Seifert, M., Sellmann, L., Bloehdorn, J., Wein, F., Stilgenbauer, S., Dürig, J., and Küppers, R. (2012). J. Exp. Med. 209, 2183–2198. Tam, C.S., and Keating, M.J. (2010). Nat. Rev. Clin. Oncol. 7, 521–532. Wang, L., Lawrence, M.S., Wan, Y., Stojanov, P., Sougnez, C., Stevenson, K., Werner, L., Sivachenko, A., DeLuca, D.S., Zhang, L., et al. (2011). N. Engl. J. Med. 365, 2497–2506.

770.e1  Cancer Cell 26, November 10, 2014 ©2014 Elsevier Inc.  DOI http://dx.doi.org/10.1016/j.ccell.2014.10.020