| Literature DB >> 36230498 |
Nicola Hermann1,2, Lara Valeska Maul3, Milad Ameri1,2,4, Stephan Traidl1,4,5, Reihane Ziadlou1,2,4, Karolina Papageorgiou1, Isabel Kolm1,2, Mitchell Levesque1,2, Julia-Tatjana Maul1,2, Marie-Charlotte Brüggen1,2,4.
Abstract
Vitiligo-like depigmentation (VLD) is an immune-related adverse event (irAE) of checkpoint-inhibitor (CPI) treatment, which has previously been associated with a favourable outcome. The aim of this study was to explore clinical, biological and prognostic features of melanoma patients with VLD under CPI-treatment and to explore whether they exhibit a characteristic immune response profile in peripheral blood. Melanoma patients developing VLD under CPI were included in a prospective observational single-center cohort study. We collected and analysed clinical parameters, photographs and serum from 28 VLD patients. They received pembrolizumab (36%), nivolumab (11%), ipilimumab/nivolumab (32%) or clinical trial medications (21%). We performed a high-throughput proteomics assay (Olink), in which we identified a distinct proteomic signature in VLD patients in comparison to non-VLD CPI patients. Our clinical assessments revealed that VLD lesions had a predominantly symmetrical distribution pattern, with mostly smaller "freckle-like" macules and a preferential distribution in UV-exposed areas. Patients with previous targeted therapy showed a significantly longer time lapse between CPI initiation and VLD onset compared to non-pre-treated patients (12.5 vs. 6.25 months). Therapy responders exhibited a distinct proteomic profile when compared with non-responders in VLD such as upregulation of EDAR and downregulation of LAG3. ITGA11 was elevated in the VLD-group when compared to non-VLD-CPI-treated melanoma patients. Our findings demonstrate that on a proteomic level, VLD is characterized by a distinct immune signature when compared to CPI-treated patients without VLD and that therapy responsiveness is reflected by a characteristic immune profile. The pathomechanisms underlying these findings and how they could relate to the antitumoral response in melanoma remain to be elucidated.Entities:
Keywords: BRAF; LDH; checkpoint inhibitors; immune-related toxicity; melanoma; survival; vitiligo; vitiligo-like depigmentation
Year: 2022 PMID: 36230498 PMCID: PMC9558529 DOI: 10.3390/cancers14194576
Source DB: PubMed Journal: Cancers (Basel) ISSN: 2072-6694 Impact factor: 6.575
Baseline characteristics.
| Clinical and Disease Features of Patients with VLD | |
|---|---|
| Characteristics (n = 28 patients) | |
| Sex, n (%) | |
| Female | 9 (32) |
| Male | 19 (68) |
| Checkpoint inhibitor, n (%) | |
| Nivolumab | 3 (11) |
| Pembrolizumab | 10 (36) |
| Ipilimumab/Nivolumab | 9 (32) |
| Clinical Studies * | 6 (21) |
| Type of melanoma, n (%) | |
| ALM | 1 (4) |
| Nodular | 7 (25) |
| Not clear | 4 (14) |
| Sinunasal | 3 (11) |
| SSM | 4 (14) |
| Unknown primary | 5 (18) |
| Uveal | 3 (11) |
| NA | 1 (4) |
| Previous targeted therapy | |
| Yes | 5 (18) |
| No | 22 (79) |
| NA | 1 (4) |
| BRAF mutated | |
| Yes | 9 (32) |
| No | 18 (64) |
| NA | 1 (4) |
| LDH elevated | |
| Yes | 15(54) |
| No | 13 (46) |
| Tumor stage at melanoma diagnosis, n (%) | |
| I | 1 (4) |
| I-II (uveal) | 3 (11) |
| IIB | 2 (7) |
| IIC | 1 (4) |
| IIIB | 8 (29) |
| IIIC | 6 (21) |
| IV | 6 (21) |
| NA | 1 (4) |
| Tumor stage at VLD diagnosis, n (%) | |
| IIIB | 1 (4) |
| IIIC | 3 (11) |
| IV | 24 (86) |
| Line of immunotherapy before VLD onset, n (%) | |
| Adjuvant | 2 (7) |
| 1st line | 20 (71) |
| 2nd line | 5 (18) |
| 3rd line | 1 (4) |
| Line of systemic therapy in general before VLD onset, n (%) | |
| 1st line | 20 (71) |
| 2nd line | 5 (18) |
| 3rd line | 2 (7) |
| 4th line | 1 (4) |
ALM, acrolentiginous melanoma; SSM, superficial spreading melanoma; NA, not available. * Other medication given in the clinical trials were ribociclib (CDK4-6 inhibitor), lenvatinib (multi-kinase-inhibitor), MCS 110 (humanized macrophage colony stimulating factor), epacadostat (inhibitor of indoleamine 2,3-dioxygenase-1 (IDO1)) and tebentafusp (T-cell redirecting agent), the latter having been recently approved for monotherapy in metastatic uveal melanoma.
Figure 1Serum protein analysis investigating differences between VLD and non-VLD (nVLD) patients. (A) Principal component analysis comparing VLD with nVLD patients (with nVLD irAE and without irAE). (B) Heatmap depicting VLD and nVLD patients. (C) Volcano plot showing several decreased proteins in VLD patients compared to nVLD individuals. (D) Boxplot showing the normalized protein expression (NPX) of ITGA11 as the most upregulated protein in VLD patients (***, p < 0.001). (E) Heatmap showing the significant different proteins (ANOVA) comparing all three groups (**, p < 0.01; *, p < 0.05). TGF-α showed the highest value in nVLD without irAE and the lowest in VLD patients. ITGA11: Integrin alpha-11, TGF-α: Transforming Growth Factor alpha.
Figure 2Different VLD patterns. (A) Small macule pattern, symmetrical distribution, partly confluent on the arms, representing the most prevalent pattern. (B) Large patch pattern, symmetrical distribution, confluent on the back, arms and legs. (C) Asymmetrical distribution on the neck and on the groin area. (D) Areas with Koebner’s phenomenon. (E) Sun-exposed areas without Koebner’s phenomenon. (F) Halo phenomenon around cutaneous metastases, asymmetrical pattern.
Figure 3Different patterns in absolute frequencies with examples. (A) Confluent big patches. (B) Large patch-pattern non-confluent. (C) Patches and macules, confluent pattern. (D) Small macules, non-confluent. (E) Confluent macules (most frequent pattern).
Distribution of VLD skin lesions and clinical features: Analysis of the distribution and appearance of the depigmented lesions.
| Clinical and Disease Features of Patients with VLD | |
|---|---|
| Characteristics (n = 28 patients) | |
| Distribution pattern, n (%) | |
| Symmetric | 20 (71) |
| Asymmetric | 5 (18) |
| NA | 3 (11) |
| Face, n (%) | |
| Yes | 15 (54) |
| No | 5 (18) |
| NA | 8 (29) |
| Scalp, n (%) | |
| Yes | 8 (29) |
| No | 7 (25) |
| NA | 13 (46) |
| Hair, n (%) | |
| Yes | 8 (29) |
| No | 8 (29) |
| NA | 12 (43) |
| Acral, n (%) | |
| Yes | 20 (71) |
| No | 3 (11) |
| NA | 5 (18) |
| Upper extremities, n (%) | |
| Yes | 23 (82) |
| No | 2 (7) |
| NA | 3 (11) |
| Lower extremities, n (%) | |
| Yes | 11 (39) |
| No | 6 (21) |
| NA | 11 (39) |
| Genital area, n (%) | |
| Yes | 3 (11) |
| No | 4 (14) |
| NA | 21 (75) |
| Oral mucosa, n (%) | |
| Yes | 3 (11) |
| No | 7 (25) |
| NA | 18 (64) |
| Neck trunk sun-exposed, n (%) | |
| Yes | 21 (75) |
| No | 3 (11) |
| NA | 4 (14) |
| Lower trunk, n (%) | |
| Yes | 13 (46) |
| No | 7 (25) |
| NA | 8 (29) |
| Trunk general, n (%) | |
| Yes | 20 (71) |
| No | 4 (14) |
| NA | 4 (14) |
| Koebner areas, n (%) | |
| Yes | 16 (57) |
| No | 11 (39) |
| NA | 1 (4) |
VLD: vitiligo-like depigmentation. NA: not available.
Figure 4Kaplan–Meier survival analysis and prediction in 26 patients developing VLD after receiving immunotherapy for metastatic melanoma. (A) Progression-free survival of all VLD patients with a 3-year PFS of 60.4% (95% confidence interval 43–84%). (B) OS of all VLD patients with a 3-year OS of 73.7% (95% confidence interval 57.5–94.6%).
Figure 5Time lapse between start of CPI and VLD onset. (A) Box plot showing a significant difference in the time lapse of VLD onset between patients with previous targeted therapy vs. no previous targeted therapy (** p < 0.001). (B) Box plot showing no significant time lapse of VLD onset of therapy responders vs. non-responders.
Univariable and multivariable Cox regression analyses of the progression-free survival.
| Univariable and Multivariable Cox Regression Analyses of PFS (n = 26) | |||||
|---|---|---|---|---|---|
| Variable | Hazard Ratio (95% CI) | Variable | Hazard Ratio (95% CI) | ||
| PFS univariate analysis | PFS multivariate analysis | ||||
| LDH elevated |
| LDH elevated |
| ||
| Yes | 1 | Yes | 1 | ||
| No | 0.18 (0.04–0.83) | No | 0.12 (0.021–0.73) | ||
| Dist symmetric | 0.94 | Dist symmetric | 0.80 | ||
| Yes | 1 | Yes | 1 | ||
| No | 0.95 (0.24–3.81) | No | 0.79 (0.15–4.32) | ||
| BRAF mutated | 0.46 | BRAF mutated | 0.49 | ||
| Yes | 1 | Yes | 1 | ||
| No | 1.65 (0.44–6.16) | No | 1.84 (0.32–10.49) | ||
| Koebner | 0.85 | Koebner | 0.61 | ||
| Yes | Yes | ||||
| No | 1.12 (0.35–3.58) | No | 0.62 (0.097–3.94) | ||
| Patches | 0.56 | Patches | 0.81 | ||
| Yes | 1 | Yes | 1 | ||
| No | 0.71 (0.22–2.25) | No | 0.77 (0.09–6.47) | ||
| Macules | 0.49 | Macules | 0.27 | ||
| Yes | 1 | Yes | 1 | ||
| No | 1.52 (0.45–5.17) | No | 0.27 (0.025–2.80) | ||
| Confluent | 0.52 | ||||
| Yes | 1 | ||||
| No | 1.48 (0.45–4.78) | ||||
Bold entries are statistically significant values. PFS, progression free-survival; CI, confidence interval; Dist, distribution; LDH, lactate dehydrogenase; OS, overall survival; VLD, vitiligo-like depigmentation.
Univariable and multivariable Cox regression analyses of the overall survival.
| Univariable and Multivariable Cox Regression Analyses of OS (n = 26) | |||||
|---|---|---|---|---|---|
| Variable | Hazard Ratio (95% CI) | Variable | Hazard Ratio (95% CI) | ||
| OS univariate analysis | OS multivariate analysis | ||||
| LDH elevated | 0.06 | LDH elevated | 0.05 | ||
| Yes | 1 | Yes | 1 | ||
| No | 0.13 (0.016–1.06) | No | 0.10 (0.01–1.04) | ||
| Distribution symmetric | 0.41 | Distribution symmetric | 0.44 | ||
| Yes | 1 | Yes | 1 | ||
| No | 1.96 (0.40–9.53) | No | 2.33 (0.27–19.8) | ||
| BRAF mutated | 0.55 | BRAF mutated | 0.32 | ||
| Yes | 1 | Yes | 1 | ||
| No | 1.63 (0.32–8.20) | No | 4.02 (0.27–60.4) | ||
| Koebner | 0.9 | Koebner | 0.26 | ||
| Yes | Yes | ||||
| No | 0.9 (0.21–3.8) | No | 0.32 (0.04–2.33) | ||
| Patches | 0.26 | Macules | 0.17 | ||
| Yes | 1 | Yes | 1 | ||
| No | 0.43 (0.10–1.85) | No | 0.14 (0.001–2.39) | ||
| Macules | 0.37 | ||||
| Yes | 1 | ||||
| No | 1.93 (0.45–8.19) | ||||
| Confluent | 0.34 | ||||
| Yes | 1 | ||||
| No | 1.99 (0.48–8.30) | ||||
PFS, progression free-survival; CI, confidence interval; Dist, distribution; LDH, lactate dehydrogenase; OS, overall survival; VLD, vitiligo-like depigmentation.
Figure 6Olink protein analyses comparing responder and non-responder VLD patients. (A) Principal component analysis showing an overlap of responder (green) and non-responder (red). (B) Heatmap of the significant different proteins compared by applying t-test. Z-score scaling across the rows are depicted. (C) Heatmap showing the log2 fold changes and p-values comparing responders and non-responders. (D) Boxplot showing the normalized protein expression of EDAR as one of the upregulated proteins in responders with the highest p-value (***, p < 0.001). (E) LAG3, IL-18R1, ARNT, IFN-γ showed significant increase in the non-responder group applying t-test (**, p < 0.01; *, p < 0.05). ARNT: Aryl Hydrocarbon Receptor Nuclear Translocator, EDAR: Ectodysplasin A Receptor, IFN-γ: Interferon gamma.