| Literature DB >> 32787882 |
Basit Salik1, Mark J Smyth1, Kyohei Nakamura2.
Abstract
Immune checkpoint blockade (ICB) therapies such as anti-programmed death 1 (PD-1) and anti-CTLA-4 (cytotoxic T lymphocyte-associated protein 4) have dramatically transformed treatment in solid tumor oncology. While immunotherapeutic approaches such as stem cell transplantation and anti-cancer monoclonal antibodies have made critical contributions to improve outcomes in hematological malignancies, clinical benefits of ICB are observed in only limited tumor types that are particularly characterized by a high infiltration of immune cells. Importantly, even patients that initially respond to ICB are unable to achieve long-term disease control using these therapies. Indeed, primary and acquired resistance mechanisms are differentially orchestrated in hematological malignancies depending on tumor types and/or genotypes, and thus, an in-depth understanding of the disease-specific immune microenvironments will be essential in improving efficacy. In addition to PD-1 and CTLA-4, various T cell immune checkpoint molecules have been characterized that regulate T cell responses in a non-redundant manner. Several lines of evidence suggest that these T cell checkpoint molecules might play unique roles in hematological malignancies, highlighting their potential as therapeutic targets. Targeting innate checkpoint molecules on natural killer cells and/or macrophages has also emerged as a rational approach against tumors that are resistant to T cell-mediated immunity. Given that various monoclonal antibodies against tumor surface proteins have been clinically approved in hematological malignancies, innate checkpoint blockade might play a key role to augment antibody-mediated cellular cytotoxicity and phagocytosis. In this review, we discuss recent advances and emerging roles of immune checkpoint blockade in hematological malignancies.Entities:
Keywords: Hematological malignancy; Immune checkpoint molecule; Immunotherapy; Tumor microenvironment
Mesh:
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Year: 2020 PMID: 32787882 PMCID: PMC7425174 DOI: 10.1186/s13045-020-00947-6
Source DB: PubMed Journal: J Hematol Oncol ISSN: 1756-8722 Impact factor: 17.388
Fig. 1CTLA-4-mediated immune regulation. Schematic illustrating T cell-intrinsic (left) and extrinsic regulation by CTLA-4 (right). Left: CTLA-4 is upregulated on activated T cells and competes with the CD28 co-stimulatory receptor due to its higher affinity for CD80/CD86. Right: CTLA-4 plays a critical role in Treg-mediated immune regulation. The CTLA-4/CD80 interaction between Treg/APCs induces indoleamine 2,3-dioxygenase (IDO), a key enzyme that suppresses T cells by tryptophan deprivation. Additionally, Tregs down-modulate CD80/86 expression on APCs by transendocytosis
Fig. 2PD-1-mediated immune regulation. Under low expression levels of PD-L1, CD80 restricts PD-L1 function by forming the PD-L1/CD80 cis-heterodimer. The PD-L1/CD80 cis-heterodimer prevents the PD-1/PD-L1 trans-interaction, whereas the ability to bind to the CD28 co-stimulatory receptor is retained (left). Upregulation of PD-L1 on APCs allows the PDL-1/PD-1 trans-interaction, leading to SHP2-dependent negative regulation of the CD28 signaling pathway as well as transcriptional repression of TCR-induced effector genes (right)
Notable clinical trials targeting immune checkpoints in hematological malignancies
| Clinical trial | Phase | Patient characteristics | Intervention | Response | Reference |
|---|---|---|---|---|---|
| NCT01592370 | I | Relapsed or refractory HL | Nivolumab | ORR 87% | [ |
| CheckMate 205 (NCT02181738) | II | cHLCohort A: brentuximab vedotin naïve Cohort B: brentuximab vedotin after auto-HCT Cohort C: brentuximab vedotin before and/or after auto-HCT Cohort D: nivolumab monotherapy followed by nivolumab plus doxorubicin, vinblastine, and dacarbazine for newly diagnosed HL | Nivolumab | ORR: Cohort A 65% Cohort B 68% Cohort C 73% Cohort D 84% | [ |
| KEYNOTE-013 (NCT01953692) | I | cHL after brentuximab vedotin failure | Pembrolizumab | ORR 65% | [ |
| KEYNOTE-087 (NCT02453594) | II | Relapsed or refractory cHL, Cohort 1: after ASCT/brentuximab vedotin Cohort 2: ineligible for ASCT and experienced treatment failure with brentuximab vedotin Cohort 3: No brentuximab vedotin after ASCT | Pembrolizumab | ORR: Cohort 1 73.9% Cohort 2 64.2% Cohort 3 70% | [ |
| NCT02038933 | II | Relapsed or refractory DLBCL Cohort 1: auto-HCT-failed Cohort 2: auto-HCT-ineligible | Nivolumab | ORR: Cohort 1 10% Cohort 2 3% | [ |
| NCT02446457 | II | Relapsed FL | Pembrolizumab Rituximab | Pre-planned interim analysis: ORR 80% | [ |
| NCT03245021 | II | Previously untreated FL | Single-agent nivolumab followed by combined nivolumab and rituximab | Pre-planned interim analysis: ORR 84% | [ |
| NCT03278782 | I/II | Relapsed or refractory peripheral T cell lymphoma (PTCL) | Pembrolizumab Romidepsin | ORR 44% | [ |
| NCT02243579 | II | Recurrent mycosis fungoides and Sezary syndrome | Pembrolizumab | ORR 38% | [ |
| KEYNOTE-023 (NCT02036502) | I | Relapsed or refractory MM | Pembrolizumab combined with lenalidomide and low-dose dexamethasone | ORR 44% | [ |
| KEYNOTE-183 (NCT02576977) | III | Relapsed or refractory MM | Pembrolizumab plus pomalidomide and dexamethasone | Pembrolizumab plus pomalidomide and dexamethasone group: Median PFS: 5.6 months (95% CI 3.7–7.5); Pomalidomide and dexamethasone group: 8.4 months (5.9–not reached) | [ |
| KEYNOTE-185 (NCT02579863) | III | Treatment-naive MM | Pembrolizumab plus lenalidomide and dexamethasone | Progression-free survival estimates at 6-months were 82.0% (95% CI 73.2–88.1) versus 85.0% (76.8–90.5; hazard ratio [HR] 1.22; 95% CI 0.67–2.22; | [ |
| NCT01822509 | I | Patients with relapse after allogeneic transplantation: AML (in 12 patients, including 3 with leukemia cutis and 1 with a myeloid sarcoma), HL (in 7), NHL (in 4), and myelodysplastic syndrome (in 2). One patient each had MM, myeloproliferative neoplasm, and acute lymphoblastic leukemia | Ipilimumab | Patients that received a dose of 10 mg/kg: CR (23%) | [ |
| NCT02397720 | II | Relapsed or refractory AML | Azacitidine and nivolumab | ORR 33% | [ |
cHL classic Hodgkin lymphoma, NHL non-Hodgkin’s lymphoma, PTCL peripheral T cell lymphoma, MM multiple myeloma, AML acute myeloid leukemia, ASCT allogeneic stem cell transplantation, HCT hematopoietic cell transplantation, ORR objective response rate, CR complete response, HR hazard ratio, PFS progression-free survival, FL follicular lymphoma, DLBCL diffuse large B cell lymphoma
Fig. 3Negative regulators of T cell immunity other than PD-1 and CTLA-4. Schematic illustrating receptors and their ligands regulating T cell immunity. Multiple immune checkpoint molecules are differentially implicated in the regulation of activated T cells including LAG-3, TIM-3, and TIGIT. Plus and minus signs denote stimulatory and inhibitory signaling respectively. Single-headed and double-headed arrows denote uni-directional and bi-directional signaling respectively. APC, antigen-presenting cell; TCR, T cell receptor; LAG-3, lymphocyte-activation gene 3; CD112R, CD112 receptor; MHC, major histocompatibility complex; FGL1, fibrinogen-like protein 1; DNAM-1, DNAX accessory molecule 1; TIGIT, T cell immunoreceptor with Ig and ITIM domains; TIM-3, T cell immunoglobulin mucin-3
Fig. 4Negative regulators of innate anti-tumor immunity. Schematic illustrating receptors and their ligands regulating anti-tumor immunity by NK cells (top) and macrophages (bottom). In NK cells, inhibitory receptors that recognize MHC class 1 molecules are recognized as a potential target to enhance NK cell-mediated cytotoxicity against tumors. Targeting macrophage phagocytosis checkpoints has also emerged as a potential approach in combination with various cancer mAb therapies due to its potential in enhancing the elimination of antibody-coated tumor cells. An immunosuppressive metabolite, adenosine, also potently inhibits innate and adaptive anti-tumor immunity. ADCP, antibody-dependent cellular phagocytosis; ADCC, antibody-dependent cellular cytotoxicity; DNAM-1, DNAX accessory molecule 1; TIGIT, T cell immunoreceptor with Ig and ITIM domains; NKG2A, NK group 2 member A; KIRs, killer-cell immunoglobulin-like receptors; HLA, human leukocyte antigen; MHC, major histocompatibility complex; LILRB1, leukocyte immunoglobulin-like receptor B1; SIRPα, signal regulatory protein α, Siglec-10, Sialic acid-binding Ig-like lectin 10