Metastatic melanoma: can FDG-PET predict success of anti-PD-1 therapy and help determine when it can be discontinued?

Hindié, Elif

doi:10.1007/s00259-020-04826-7

Cited by 8 publications

(5 citation statements)

References 44 publications

(85 reference statements)

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“…This index has shown to estimate the risk of disease progression and predict survival 8 weeks following ICI treatment initiation ( 86 ). Finally, another potential use of 18 F-FDG-PET/CT in the follow-up of patients treated with ICI is to guide clinicians in the decision of eventual therapy discontinuation for safety reasons ( 87 ).…”

Section: Response Assessmentmentioning

confidence: 99%

Tumor response assessment on imaging following immunotherapy

et al. 2022

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In recent years, various systemic immunotherapies have been developed for cancer treatment, such as monoclonal antibodies (mABs) directed against immune checkpoints (immune checkpoint inhibitors, ICIs), oncolytic viruses, cytokines, cancer vaccines, and adoptive cell transfer. While being estimated to be eligible in 38.5% of patients with metastatic solid or hematological tumors, ICIs, in particular, demonstrate durable disease control across many oncologic diseases (e.g., in melanoma, lung, bladder, renal, head, and neck cancers) and overall survival benefits. Due to their unique mechanisms of action based on T-cell activation, response to immunotherapies is characterized by different patterns, such as progression prior to treatment response (pseudoprogression), hyperprogression, and dissociated responses following treatment. Because these features are not encountered in the Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST 1.1), which is the standard for response assessment in oncology, new criteria were defined for immunotherapies. The most important changes in these new morphologic criteria are, firstly, the requirement for confirmatory imaging examinations in case of progression, and secondly, the appearance of new lesions is not necessarily considered a progressive disease. Until today, five morphologic (immune-related response criteria (irRC), immune-related RECIST (irRECIST), immune RECIST (iRECIST), immune-modified RECIST (imRECIST), and intra-tumoral RECIST (itRECIST)) criteria have been developed to accurately assess changes in target lesion sizes, taking into account the specific response patterns after immunotherapy. In addition to morphologic response criteria, 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography/computed tomography (18F-FDG-PET/CT) is a promising option for metabolic response assessment and four metabolic criteria are used (PET/CT Criteria for Early Prediction of Response to Immune Checkpoint Inhibitor Therapy (PECRIT), PET Response Evaluation Criteria for Immunotherapy (PERCIMT), immunotherapy-modified PET Response Criteria in Solid Tumors (imPERCIST5), and immune PERCIST (iPERCIST)). Besides, there is evidence that parameters on 18F-FDG-PET/CT, such as the standardized uptake value (SUV)max and several radiotracers, e.g., directed against PD-L1, may be potential imaging biomarkers of response. Moreover, the emerge of human intratumoral immunotherapy (HIT-IT), characterized by the direct injection of immunostimulatory agents into a tumor lesion, has given new importance to imaging assessment. This article reviews the specific imaging patterns of tumor response and progression and available imaging response criteria following immunotherapy.

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Section: Response Assessmentmentioning

confidence: 99%

Tumor response assessment on imaging following immunotherapy

et al. 2022

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“…The FDG glucose-based tracer non-invasively measures glycolytic metabolism that presents a “metabolic signature” reflecting a tumor's overall energy consumption, in a conceptually similar manner to TumorIO . Recent F-FDG PET/CT studies suggest a negative correlation between baseline metabolic activity and ICI monotherapy response (Hindié, 2020 ; Lang et al, 2020 ), although the underlying etiology for this finding has been elusive in the radiology literature. Importantly, these data closely parallel our finding of low nutrient availability in tumors with strong ICI response.…”

Section: Discussionmentioning

confidence: 99%

Next generation immuno-oncology tumor profiling using a rapid, non-invasive, computational biophysics biomarker in early-stage breast cancer

Cook

Biancalana

Liadis

et al. 2023

Front. Artif. Intell.

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BackgroundImmuno-oncology (IO) therapies targeting the PD-1/PD-L1 axis, such as immune checkpoint inhibitor (ICI) antibodies, have emerged as promising treatments for early-stage breast cancer (ESBC). Despite immunotherapy's clinical significance, the number of benefiting patients remains small, and the therapy can prompt severe immune-related events. Current pathologic and transcriptomic predictions of IO response are limited in terms of accuracy and rely on single-site biopsies, which cannot fully account for tumor heterogeneity. In addition, transcriptomic analyses are costly and time-consuming. We therefore constructed a computational biomarker coupling biophysical simulations and artificial intelligence-based tissue segmentation of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRIs), enabling IO response prediction across the entire tumor.MethodsBy analyzing both single-cell and whole-tissue RNA-seq data from non-IO-treated ESBC patients, we associated gene expression levels of the PD-1/PD-L1 axis with local tumor biology. PD-L1 expression was then linked to biophysical features derived from DCE-MRIs to generate spatially- and temporally-resolved atlases (virtual tumors) of tumor biology, as well as the TumorIO biomarker of IO response. We quantified TumorIO within patient virtual tumors (n = 63) using integrative modeling to train and develop a corresponding TumorIO Score.ResultsWe validated the TumorIO biomarker and TumorIO Score in a small, independent cohort of IO-treated patients (n = 17) and correctly predicted pathologic complete response (pCR) in 15/17 individuals (88.2% accuracy), comprising 10/12 in triple negative breast cancer (TNBC) and 5/5 in HR+/HER2- tumors. We applied the TumorIO Score in a virtual clinical trial (n = 292) simulating ICI administration in an IO-naïve cohort that underwent standard chemotherapy. Using this approach, we predicted pCR rates of 67.1% for TNBC and 17.9% for HR+/HER2- tumors with addition of IO therapy; comparing favorably to empiric pCR rates derived from published trials utilizing ICI in both cancer subtypes.ConclusionThe TumorIO biomarker and TumorIO Score represent a next generation approach using integrative biophysical analysis to assess cancer responsiveness to immunotherapy. This computational biomarker performs as well as PD-L1 transcript levels in identifying a patient's likelihood of pCR following anti-PD-1 IO therapy. The TumorIO biomarker allows for rapid IO profiling of tumors and may confer high clinical decision impact to further enable personalized oncologic care.

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“… 12 , 39 This trial led to the FDA approval of the combination therapy of ipilimumab and nivolumab, which became the standard of care for metastatic melanoma in the first-line setting. 12 , 39 – 42 RELATIVITY-047 trial compared dual checkpoint inhibition with relatlimab and nivolumab to nivolumab alone, similar to the comparison made in the CheckMate-067 trial between the two arms. This allowed for direct comparison of dual checkpoint inhibition to single-agent immunotherapy in metastatic melanoma in both trials.…”

Section: The Emerging Role and Clinical Outcomes Of Lag-3 Inhibitionmentioning

confidence: 99%

The introduction of LAG-3 checkpoint blockade in melanoma: immunotherapy landscape beyond PD-1 and CTLA-4 inhibition

Kreidieh

Tawbi

2023

Ther Adv Med Oncol

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Despite major advances with immunotherapy and targeted therapy in the past decade, metastatic melanoma continues to be a deadly disease for close to half of all patients. Over the past decade, advancement in immune profiling and a deeper understanding of the immune tumor microenvironment (TME) have enabled the development of novel approaches targeting and a multitude of targets being investigated for the immunotherapy of melanoma. However, to date, immune checkpoint blockade has remained the most successful with programmed cell death-1 (PD-1)/programmed cell death ligand-1 (PD-L1) and cytotoxic T-lymphocyte antigen-4 (CTLA-4) inhibitors, alone or in combination, yielding the most robust and durable clinical outcome in patients with metastatic melanoma. The highest rate of durable responses is achieved with the combination with PD-1 and CTLA-4 inhibition, and is effective in a variety of settings including brain metastases; however, it comes at the expense of a multitude of life-threatening toxicities occurring in up to 60% of patients. This has also established melanoma as the forefront of immuno-oncology (IO) drug development, and the search for novel checkpoints has been ongoing with multiple relevant targets including T-cell immunoglobulin and mucinodomain containing-3 (TIM-3), LAG-3, V-domain immunoglobulin suppressor T-cell activation (VISTA), T-cell immunoglobulin and immunoreceptor tyrosine-based inhibitory motif (ITIM) domain (TIGIT), among others. Lymphocyte activation gene-3 (LAG-3), which is a co-inhibitory receptor on T cells that suppress their activation, has revolutionized immunomodulation in melanoma. The ‘game changing’ results from the RELATIVITY-047 trial validated LAG-3 blockade as a relevant biological target and established it as the third clinically relevant immune checkpoint. Importantly, LAG-3 inhibition in combination with PD-1 inhibition offered impressive efficacy with modest increases in toxicity over single agent PD-1 inhibitor and has been U.S. Food and Drug Administration approved for the first-line therapy of patients with metastatic melanoma. The efficacy of this combination in patients with untreated brain or leptomeningeal metastases or with rare melanoma types, such as uveal melanoma, remains to be established. The challenge remains to elucidate specific mechanisms of response and resistance to LAG-3 blockade and to extend its benefits to other malignancies. Ongoing trials are studying the combination of LAG-3 antibodies with PD-1 inhibitors in multiple cancers and settings. The low toxicity of the combination may also allow for further layering of additional therapeutic approaches such as chemotherapy, oncolytic viruses, cellular therapies, and possibly novel cytokines, among others.

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Metastatic melanoma: can FDG-PET predict success of anti-PD-1 therapy and help determine when it can be discontinued?

Cited by 8 publications

References 44 publications

Tumor response assessment on imaging following immunotherapy

Tumor response assessment on imaging following immunotherapy

Next generation immuno-oncology tumor profiling using a rapid, non-invasive, computational biophysics biomarker in early-stage breast cancer

The introduction of LAG-3 checkpoint blockade in melanoma: immunotherapy landscape beyond PD-1 and CTLA-4 inhibition

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