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Review
. 2017 Jun;14(6):335-346.
doi: 10.1038/nrclinonc.2016.205. Epub 2016 Dec 29.

The landscape of new drugs in lymphoma

Affiliations
Review

The landscape of new drugs in lymphoma

Anas Younes et al. Nat Rev Clin Oncol. 2017 Jun.

Abstract

The landscape of drugs for the treatment of lymphoma has become crowded in light of the plethora of new agents, necessitating the efficient prioritization of drugs for expedited development. The number of drugs available, and the fact that many can be given for an extended period of time, has resulted in the emergence of new challenges; these include determining the optimal duration of therapy, and the need to balance costs, benefits, and the risk of late-onset toxicities. Moreover, with the increase in the number of available investigational drugs, the number of possible combinations is becoming overwhelming, which necessitates prioritization plans for the selective development of novel combination regimens. In this Review, we describe the most-promising agents in clinical development for the treatment of lymphoma, and provide expert opinion on new strategies that might enable more streamlined drug development. We also address new approaches for patient selection and for incorporating new end points into clinical trials.

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Conflict of interest statement

Competing interests statement A.Y. receives honouraria and/or consults for Abbvie, Bayer, BMS, Celgene, Gilead, Incyte, Janssen R&D, Sanofi, Seattle Genetics, Merck, and Takeda Millenium, and research support from the John and Barbara Vogelstein Foundation. The other authors declare no competing interests.

Figures

Figure 1
Figure 1. Therapeutic targeting of the B-cell receptor (BCR) signalling pathway in patients with lymphoma
a | BCR signalling pathway. Selective inhibitors for Syk and Btk are either approved by regulatory agencies or are in clinical trials. b | SYK structure. SYK is a non-receptor protein-tyrosine kinase containing tandem SRC homology 2 (SH2) domains. SYK inhibitors are able to competitively bind to the ATP-binding pocket of the kinase domain. Most BTK inhibitors bind covalently to cysteine 481 (C481) residues in the BTK active site, c | BTK structure. BTK is composed of four major domains: an N-terminal pleckstrin homology (PH) domain, a TEC homology (TH) domain, two SRC homology domains (SH3 followed by SH2), and a C-terminal kinase domain. d | A list of kinases that contain a C481 residue in the active kinase site. The IC50 is shown for ibrutinib using a purified kinase assay.
Figure 2
Figure 2. Therapeutic targeting of the PI3K/AKT/mTOR pathway
Several small-molecule inhibitors targeting different nodes in this pathway are under development for the treatment of cancer. Currently, idelalisib, which selectively targets the PI3Kδ isoform, is the only PI3K inhibitor to be approved by regulatory agencies is idelalisib.
Figure 3
Figure 3. Therapeutic induction of cell death through targeting of the mitochondrial apoptosis pathway
Proteins in the BCL-2 family are classified into pro-survival (orange colour) and pro-apoptotic groups. The pro-apoptotic proteins are further sub-divided into BCL-2 homology 3 (BH3)-only proteins (green colour) and effector proteins (blue colour)
Figure 4
Figure 4. Autologous cell activation strategies
a | T cells can be activated by a set of inhibitory antibodies that target cell-surface receptors that inhibit cell function (redr) or by agonistic antibodies that target cell-surface receptors that regulate cell activation (green). b | Autologous T cells can be genetically engineered to express chimeric antigen receptors, which can be selectively activated upon binding with target proteins on cancer cells.
Figure 5
Figure 5. A representative high-throughput screening experiment involving drug combinations with the BET inhibitor JQ1
Each box plot represents data from one combination tested in 12 different lymphoma cell lines using an 8 × 8 viability matrix, with cell viability measured after 72 hours of treatment. The Y axis shows the ratio of expected and observed growth inhibition, on a logarithmic scale. Values above the ‘0’ line indicate additive or synergistic effects. This experiment shows that the BCL2/Bcl-X inhibitor AB737, the checkpoint kinase inhibitor AZD7762, and different PI3K inhibitors (red boxes) have the highest level of synergy when combined with JQ1.

References

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