Moving the needle on immune checkpoint inhibitors with novel targets: are we being TIMid or LAGging behind?
Bibliographic record
Abstract
Immune checkpoint receptors play a crucial role in maintaining self-tolerance and deactivating responses against chronic antigen stimuli by suppressing T-cell activation.1 Cancer cells can evade host immune surveillance by modulating these checkpoint receptors. Targeting this axis can resensitize an inflammatory response against cancer neo-antigens. In 2011, the Food and Drug Administration (FDA) approved ipilimumab, a monoclonal antibody against cytotoxic T lymphocyte antigen 4 (CTLA-4) for metastatic melanoma. This was followed by a surge of approvals for immune checkpoint inhibitors (ICIs) targeting the programmed cell death protein 1 (PD-1) and its ligand (PD-L1), revolutionizing the field of oncology. Treatment with ICIs can lead to deep and durable response in several cancer types.2 Given that multiple checkpoint receptors can be co-expressed, novel ICI targets have been explored to overcome primary or acquired resistance PD-1/PD-L1 ICIs.3 However, compared to the success of anti-CTLA-4 and anti-PD-(L)1 therapies, targeting these alternate immune checkpoints has not yielded the same level of success. In this issue of The Oncologist, Powderly et al. and Gutierrez et al. report the first in human phase 1 trials of novel ICIs targeting lymphocyte activation gene 3 (LAG-3) and T-cell immunoglobulin and mucin domain-containing protein 3 (TIM-3) in patients with refractory immunogenic solid tumors. LAG-3 is an immune checkpoint receptor expressed on memory and regulatory T cells, B cells, natural killer cells, and dendritic cells.4 LAG-3 expression is induced upon chronic activation of T cells and upregulated on exhausted tumor infiltrating lymphocytes and on infiltrating T cells in solid tumors.5,6 Anti-LAG-3 antibodies block its canonical interaction with major histocompatibility complex (MHC) class II molecules expressed on tumor cells.7 This blockade activates antigen-specific T lymphocytes and enhances cytotoxic T-lymphocyte-mediated tumor cell lysis, leading to a reduction in tumor growth, especially in conjunction with another ICI. Several anti-LAG-3 antibodies have already been studied as monotherapy or in combination with anti-PD-1 antibodies, with varying degrees of success.8 Relatlimab received FDA approval for use in advanced melanoma in combination with nivolumab, a PD-1 targeted ICI, based on improvement in progression free survival compared with nivolumab alone, becoming the only approved non-CTLA-4/PD-(L)1 ICI with an indication. However, it was recently announced that phase 3 RELATIVITY-098 trial, evaluating the relatlimab and nivolumab combination as adjuvant treatment for completely resected stage III/IV melanoma, did not meet its primary endpoint of recurrence free survival.9 Furthermore, the clinical development of favezelimab was recently discontinued due to recent clinical trials failing to show improved outcomes in various settings.10 Powderly et al. contribute to this narrative by evaluating the safety, tolerability and efficacy of INCAGN02385, a novel anti- LAG-3 antibody. No dose limiting toxicities (DLTs) were reported and treatment-emergent adverse events (TEAEs) were similar across the five dose levels that were tested (25, 75, 250, 350 and 750 mg intravenously every two weeks). Consistent with other phase 1 trials of other LAG-3 monoclonal antibodies, limited anti-tumor activity observed, with no objective responses by RECIST v1.1 and a disease control rate (DCR) of 27%. Pharmacodynamic studies of LAG-3 receptor occupancy were conducted by incubating patient serum samples from various time points on activated T cells from healthy donors. The authors report that the maximum and trough receptor occupancy using this assay was saturated in patients who received doses ≥ 250mg. As such, the recommend phase 2 dose (RP2D) was determined to be 350mg to account for potential intratumoral differences in receptor occupancy. TIM3 is an inhibitory regulator expressed on various immune cells including regulatory T cells, dendritic cells and natural killer cells. High expression of TIM-3 in cancer cells or tumor infiltrating lymphocytes has been correlated with poor prognosis in various cancers.11 Several anti-TIM-3 antibodies have been developed to block its activation by ligands such as CEACAM1 and Galectin-9; however, their clinical utility is yet to be determined.12 Gutierrez et al. report the safety, tolerability and efficacy of INCAGN02390, a novel anti-TIM-3 antibody. No DLTs were observed across seven dose levels (10, 30, 100, 200, 400, 800, 1600 mg intravenously every two weeks), and the incidence of treatment-emergent adverse events (TEAEs) was similar across all dose levels tested. Consistent with phase I trials of other TIM-3 monoclonal antibodies, limited anti-tumor activity was observed, with only one patient (3%) achieving partial response and a disease control rate (DCR) of 18%. TIM-3 receptor occupancy was measured on peripheral blood monocytes and NK cells by flow cytometry and was determined to be saturated in patients receiving doses ≥ 200mg. The recommend phase 2 dose (RP2D) was established at 400mg for future studies of INCAGN02390. Oncology drug development is increasingly shifting away from the cytotoxic chemotherapy paradigm, which posits that higher dosing leads to greater efficacy for patients. Initiatives such as Project Optimus challenge phase 1 trialists to incorporate early pharmacodynamic, pharmacokinetic, and anti-tumor efficacy readouts to select optimized dosing schedules that balance efficacy and safety.13 Emerging data suggest that lower doses of anti-PD-(L)1 may provide similar efficacy as conventional doses, highlighting the importance of early dose optimization.14,15 This philosophy is reflected by both Powderly et al. and Gutierrez et al., where the RP2Ds for INCAGN02385 and INCAGN02390 are several- fold lower than the maximum administered doses for either agent, as the maximum tolerated dose was not reached in either trial based on the incidence of dose limiting toxicities. Similar to other early phase trials with ICIs, checkpoint receptor occupancy was assessed based on peripheral lymphocyte-based assays as a measure of target engagement across dosing exposures. However, peripheral receptor occupancy may not accurately reflect dynamics within the tumor microenvironment, and thresholds for peripheral receptor occupancy for clinical benefit may differ across different ICIs and tumor types. Early studies of ipilimumab monotherapy identified a dose-dependent effect on both efficacy and toxicity; an objective response rate of 11% was only elicited at doses as high as 10mg/kg in a cohort of heavily pre-treated melanoma patients.16 Furthermore, ipilimumab combined with nivolumab (anti-PD-1) at various dose permutations displayed different rates of toxicity and efficacy.17 Indeed, different dosing combinations and schedules of ipilimumab and nivolumab are currently used not only across various tumor types,18-20 but also for different treatment indications within the same type of cancer.20,21 While we are not proposing dose titration to toxicity as a marker of efficacy,22-24 theoretical questions for reflection remain: Would the RP2Ds have changed if the tumor samples were interrogated to understand the pharmacodynamic effects on the tumor microenvironment across dose levels? Would the fate of novel ICIs be different if we were less timid in pushing the dose levels higher? In addition to LAG-3 and TIM-3, various immune checkpoints have been studied as druggable targets, yielding variable success (Figure 1). Tiragolumab, an anti-TIGIT antibody, recently demonstrated promising early signals for progression-free survival and overall survival for patients with hepatocellular carcinoma when added to the current standard, atezolizumab and bevacizumab.25 Conversely, the combination of tiragolumab and atezolizumab failed to meet the primary endpoint of overall survival compared to atezolizumab monotherapy in PD-L1 positive non-small cell lung cancer. These studies underscore that novel ICIs can hold promise when evaluated in the appropriate combination and context. However, a “brute force” approach to testing various permutations of ICI combinations, tumor types, and disease settings is highly inefficient for both patients and pharmaceutical companies alike. Overview of select immune checkpoint receptors and ligands.. Illustrative overview of the immune checkpoint receptors and ligands that were discussed in this editorial. Stimulatory (green dot) and inhibitory (red dot) interactions are depicted. A non-exhaustive list of ICIs in development are listed, with a focus on drugs in phase 3 clinical trials. Whether immune checkpoint inhibitors (ICIs) exert a class effect and can be used interchangeably remains a subject of ongoing debate.26 Indeed, various anti-PD-(L)1 antibodies have exhibited different outcomes in similarly designed clinical trials.27–30 An immediate challenge is the lack of unified predictive biomarkers for ICIs, which could aid in designing clinical trials with a higher likelihood of success. The identification of predictive biomarkers for PD-(L)1 and CTLA-4 blockade beyond PD-L1 expression and tumor mutation burden, remains an unmet need. This further emphasizes the importance of incorporating serial biopsies into early phase studies to better understand dynamic changes within the tumor microenvironment for novel ICIs. Unlike cytotoxic chemotherapies that act directly on tumor cells, ICIs work indirectly by modulating the patient’s immune system to mount an anti-tumor response. This fundamental difference poses unique challenges in preclinical drug development. Traditional animal models used for chemotherapy are inadequate for immunotherapy, prompting the evolution of new systems that can support both tumor biology and a functional, human-like immune response.31 One such model is the humanized patient-derived xenograft (PDX), where human tumors are implanted into immunodeficient mice engrafted with human hematopoietic stem cells.32,33 While promising, these models have important limitations: they lack mature lymphoid architecture, have short experimental timeframes, and may generate allogeneic immune responses that confound interpretation. To improve the translation of novel ICIs into early-phase trials, ongoing efforts are needed to develop more representative in vivo and ex vivo systems. These should not only simulate the complex interplay between tumor and immune cells, but also capture the immune-related toxicities that are increasingly relevant in clinical settings. Advancing these models will be essential for evaluating immunogenicity, pharmacodynamics, and therapeutic windows of next-generation ICIs. Recent advancements have extended the scope of immunotherapy beyond monoclonal antibodies. Bispecific T-cell engagers (BiTE), like tarlatamab and tebentafusp, have been approved for use in small cell lung cancer and uveal melanoma, respectively.34,35 Afamitresgene autoleucel, a T-cell receptor therapy, was recently approved for patients with synovial sarcoma.36 Novel strategies to utilize immune checkpoints as druggable targets are being explored, including antibody-drug conjugates (ADCs) and bispecific antibodies. As these immune-modulating therapies become more complex and mechanistically diverse, there is an urgent need for preclinical models that can accurately recapitulate both tumor immunobiology and human immune responses. Currently, there are over 100 registered trials with investigational agents targeting the LAG-3 and TIM-3 pathways (www.clinicaltrials.gov). It remains unclear whether we should innovate beyond or emulate the foundational approaches that led to anti-PD(L)-1 and anti-CTLA-4 therapies to drive further advances. Powderly et al. and Gutierrez et al. report well-conducted trials that adhere to the conventional paradigm of early phase drug testing. However, through a recent press release, Incyte has announced that they will not be continuing clinical development of both INCAGN02385 and INCAGN02390, returning the rights to these drugs to Aegenus.37 Given the rapid turnover of investigational immunotherapies in early drug development, it is prudent to reflect on prior successes and failures. Do we need a deeper understanding of the molecular mechanisms of cancer immunotherapy to properly interrogate novel investigational immunotherapy agents? Are pre-clinical models and clinical trial methodologies optimized for immunotherapy development? Innovations in clinical trial designs and comprehensive assessments of pharmacodynamic effects across dose levels through serial biopsies may more accurately inform the next steps in the development of novel checkpoint inhibitors and other immunomodulatory approaches. CLP: Conception/Design; Manuscript writing; Final approval of manuscript PLB: Conception/Design; Manuscript writing; Final approval of manuscript Not applicable PLB: Consultant/Advisory role for: Zymeworks, Lilly, Seattle Genetics, Merck, Amgen, Gilead, Jannsen, Repare, Daiichi Sankyo. Grant/Research support from (Clinical Trials): Amgen, Astra Zeneca, Bayer, Bicara, Boehringer Ingelheim, BristolMyersSquibb, Daiichi Sankyo, Genentech/Roche, Gilead, GlaxoSmithKline, Lilly/Loxo, Medicenna, Merck, Nektar, Novartis, PTC Therapeutics, Sanofi, SeaGen, Servier, SignalChem Life Sciences, Takeda, Zymeworks No new data were generated or analysed in support of this research.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.037 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.014 |
| Scholarly communication | 0.015 | 0.035 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.016 | 0.048 |
| Insufficient payload (model declined to judge) | 0.022 | 0.011 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".