Response to immune checkpoint inhibitors in acral melanoma: A nationwide cohort study

Not, Olivier J. van; Meza, Melissa Melanie de; Eertwegh, Alfons J.M. van den; Haanen, John B.A.G.; Blank, Christian U.; Aarts, Maureen J.B.; Berkmortel, Franchette W P J van den; Breeschoten, Jesper van; Groot, Jan-Willem B de; Hospers, Geke A.P.; Ismail, Rawa K; Piersma, Djura; Rijn, R.S. van; Boer, Marion A M Stevense-den; Veldt, Astrid A.M. van der; Vreugdenhil, Gerard; Bonenkamp, Han J.; Boers‐Sonderen, Marye J.; Blokx, Willeke A.M.; Wouters, Michel W.J.M.; Suijkerbuijk, Karijn P M

doi:10.1016/j.ejca.2022.02.026

Cited by 26 publications

(19 citation statements)

References 28 publications

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“…This pipeline was trained to predict outcomes per lesion; these outputs per lesion were then aggregated to a patient level prediction. The clinical model used the same machine learning pipeline, which was fitted on five clinical variables that were consistently shown to be predictive of checkpoint inhibitor treatment outcomes in previous literature [5,14,30,31]. These predictors were (i) ECOG performances status, (ii) LDH level, presence of (iii) brain and (iv) liver metastases, and (v) number of affected organs.…”

Section: Evaluated Modelsmentioning

confidence: 99%

CT radiomics to predict checkpoint inhibitors treatment outcomes in patients with advanced cutaneous melanoma

Maat

Duin

Elias³

et al. 2022

Preprint

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Introduction Predicting checkpoint inhibitors treatment outcomes in melanoma is a relevant task, due to the unpredictable and potentially fatal toxicity and high costs for society. However, accurate biomarkers for treatment outcomes are lacking. Radiomics are a technique to quantitatively capture tumor characteristics on readily available computed tomography (CT) imaging. The purpose of this study was to investigate the added value of radiomics for predicting durable clinical benefit from checkpoint inhibitors in melanoma in a large, multicenter cohort. Methods Patients who received first-line anti-PD1 with or without anti-CTLA4 treatment for advanced cutaneous melanoma were retrospectively identified from nine participating hospitals. For every patient, up to five representative lesions were segmented on baseline CT and radiomics features were extracted. A machine learning pipeline was trained on the radiomics features to predict durable clinical benefit, defined as stable disease for more than six months or response per RECIST 1.1 criteria. This approach was evaluated using a leave-one-center-out cross validation and compared to a model based on previously discovered clinical predictors. Lastly, a combination model was built on the radiomics and clinical model. Results A total of 620 patients were included, of which 59.2% experienced durable clinical benefit. The radiomics model achieved an area under the receiver operator characteristic curve (AUROC) of 0.607 [95%CI 0.562-0.652], lower than that of the clinical model (AUROC=0.646 [95%CI 0.600-0.692]). The combination model yielded no improvement over the clinical model in terms of discrimination (AUROC=0.636 [95%CI 0.592-0.680]) or calibration. The output of the radiomics model was significantly correlated with three out of five input variables of the clinical model (p < 0.001). Discussion The radiomics model achieved a moderate predictive value of durable clinical benefit, which was statistically significant. However, a radiomics approach was unable to add value to a simpler clinical model, most likely due to the overlap in predictive information learned by both models. Future research should focus on the application of deep learning, spectral CT derived radiomics and a multimodal approach for accurately predicting benefit to checkpoint inhibitor treatment in advanced melanoma.

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Section: Evaluated Modelsmentioning

confidence: 99%

CT radiomics to predict checkpoint inhibitors treatment outcomes in patients with advanced cutaneous melanoma

Maat

Duin

Elias³

et al. 2022

Preprint

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“…Previous studies have shown that clinical parameters, such as PD-L1 expression level, tumor histology, and anti-PD-1 monotherapy, are significantly associated with ICI treatment efficacy ( 24 , 25 ). Our findings are consistent with those studies, implying that our findings are reliable.…”

Section: Discussionmentioning

confidence: 99%

Vitamin D metabolism pathway polymorphisms are associated with efficacy and safety in patients under anti-PD-1 inhibitor therapy

Chen

Xiao

et al. 2022

Front. Immunol.

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AimVitamin D (VitD) signaling has been increasingly investigated for its role in stimulating the innate and adaptive immune systems and suppressing inflammatory responses. Therefore, we examined the associations between VitD-related genetic polymorphisms, plasma 25-hydroxyvitamin D (25(OH)D), and the efficacy and safety of immune checkpoint inhibitors (ICIs).Patients and methodsA total of 13 single-nucleotide polymorphisms (SNPs) in VitD metabolic pathway genes were genotyped in 343 cancer patients receiving ICI treatment using the MassARRAY platform. In 65 patients, the associations between plasma 25(OH)D levels and ICI treatment outcomes were investigated further.ResultsWe found that the CYP24A1 rs6068816TT and rs2296241AA genotypes were significantly higher in patients who responded to ICIs. Furthermore, patients with higher plasma 25(OH)D levels had a better treatment response. The distribution of allele and genotype frequencies showed that three SNPs (rs10877012, rs2762934, and rs8018720) differed significantly between patients who had immune-related adverse events (irAEs) and those who did not. There was no statistically significant relationship between plasma 25(OH)D levels and the risk of irAEs.ConclusionIn summary, our findings showed that genetic variations in the VitD metabolism pathway were associated with ICI treatment outcomes, and VitD supplementation may be useful in improving ICI treatment efficacy.

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“…For advanced AM patients who received post-line treatment with ipilimumab, the ORR was 11.4%, the median PFS was 2.5 months, and the median OS was 7.1-16.7 months [20,21]. In contrast, advanced AM patients who received first-line anti-PD-1 monotherapy had an ORR of 34.0-40.0%, median PFS of 3.1-9.2 months, and median OS of 18.6-60.1 months [19,22]. Advanced AM patients who received post-line therapy with anti-PD-1 monotherapy had an ORR of 14.0-32.0%, median PFS of 3.2-4.1 months, and median OS of 16.9-25.8 months [17,[22][23][24][25][26][27].…”

Section: Immunotherapy Immune Checkpoint Inhibitorsmentioning

confidence: 99%

“…In contrast, advanced AM patients who received first-line anti-PD-1 monotherapy had an ORR of 34.0–40.0%, median PFS of 3.1–9.2 months, and median OS of 18.6–60.1 months [ 19 , 22 ]. Advanced AM patients who received post-line therapy with anti-PD-1 monotherapy had an ORR of 14.0–32.0%, median PFS of 3.2–4.1 months, and median OS of 16.9–25.8 months [ 17 , 22 – 27 ].…”

Section: Current Statusmentioning

confidence: 99%

Advanced Acral Melanoma Therapies: Current Status and Future Directions

Zhang

Lan

2022

Curr. Treat. Options in Oncol.

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Opinion statementMelanoma is one of the deadliest malignancies. Its incidence has been significantly increasing in most countries in recent decades. Acral melanoma (AM), a peculiar subgroup of melanoma occurring on the palms, soles, and nails, is the main subtype of melanoma in people of color and is extremely rare in Caucasians. Although great progress has been made in melanoma treatment in recent years, patients with AM have shown limited benefit from current therapies and thus consequently have worse overall survival rates. Achieving durable therapeutic responses in this high-risk melanoma subtype represents one of the greatest challenges in the field. The frequency of BRAF mutations in AM is much lower than that in cutaneous melanoma, which prevents most AM patients from receiving treatment with BRAF inhibitors. However, AM has more frequent mutations such as KIT and CDK4/6, so targeted therapy may still improve the survival of some AM patients in the future. AM may be less susceptible to immune checkpoint inhibitors because of the poor immunogenicity. Therefore, how to enhance the immune response to the tumor cells may be the key to the application of immune checkpoint inhibitors in advanced AM. Anti-angiogenic drugs, albumin paclitaxel, or interferons are thought to enhance the effectiveness of immune checkpoint inhibitors. Combination therapies based on the backbone of PD-1 are more likely to provide greater clinical benefits. Understanding the molecular landscapes and immune microenvironment of AM will help optimize our combinatory strategies.

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Response to immune checkpoint inhibitors in acral melanoma: A nationwide cohort study

Cited by 26 publications

References 28 publications

CT radiomics to predict checkpoint inhibitors treatment outcomes in patients with advanced cutaneous melanoma

CT radiomics to predict checkpoint inhibitors treatment outcomes in patients with advanced cutaneous melanoma

Vitamin D metabolism pathway polymorphisms are associated with efficacy and safety in patients under anti-PD-1 inhibitor therapy

Advanced Acral Melanoma Therapies: Current Status and Future Directions

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