Correlation of tumor PD-L1 expression in different tissue types and outcome of PD-1-based immunotherapy in metastatic melanoma – analysis of the DeCOG prospective multicenter cohort study ADOREG/TRIM

Background PD-1-based immune checkpoint inhibition (ICI) is the major backbone of current melanoma therapy. Tumor PD-L1 expression represents one of few biomarkers predicting ICI therapy outcome. The objective of the present study was to systematically investigate whether the type of tumor tissue examined for PD-L1 expression has an impact on the correlation with ICI therapy outcome. Methods Pre-treatment tumor tissue was collected within the prospective DeCOG cohort study ADOREG/TRIM (CA209-578; NCT05750511) between February 2014 and May 2020 from 448 consecutive patients who received PD-1-based ICI for non-resectable metastatic melanoma. The primary study endpoint was best overall response (BOR), secondary endpoints were progression-free (PFS) and overall survival (OS). All endpoints were correlated with tumor PD-L1 expression (quantified with clone 28–8; cutoff ≥5%) and stratified by tissue type. Findings Tumor PD-L1 was determined in 95 primary tumors (PT; 36.8% positivity), 153 skin/subcutaneous (34.0% positivity), 115 lymph node (LN; 50.4% positivity), and 85 organ (40.8% positivity) metastases. Tumor PD-L1 correlated with BOR if determined in LN (OR = 0.319; 95% CI = 0.138–0.762; P = 0.010), but not in skin/subcutaneous metastases (OR = 0.656; 95% CI = 0.311–1.341; P = 0.26). PD-L1 positivity determined on LN metastases was associated with favorable survival (PFS, HR = 0.490; 95% CI = 0.310–0.775; P = 0.002; OS, HR = 0.519; 95% CI = 0.307–0.880; P = 0.014). PD-L1 positivity determined in PT (PFS, HR = 0.757; 95% CI = 0.467–1.226; P = 0.27; OS; HR = 0.528; 95% CI = 0.305–0.913; P = 0.032) was correlated with survival to a lesser extent. No relevant survival differences were detected by PD-L1 determined in skin/subcutaneous metastases (PFS, HR = 0.825; 95% CI = 0.555–1.226; P = 0.35; OS, HR = 1.083; 95% CI = 0.698–1.681; P = 0.72). Interpretation For PD-1-based immunotherapy in melanoma, tumor PD-L1 determined in LN metastases was stronger correlated with therapy outcome than that assessed in PT or organ metastases. PD-L1 determined in skin/subcutaneous metastases showed no outcome correlation and therefore should be used with caution for clinical decision making. Funding Bristol-Myers Squibb (ADOREG/TRIM, NCT05750511); German Research Foundation (DFG; Clinician Scientist Program UMEA); Else Kröner-Fresenius-Stiftung (EKFS; Medical Scientist Academy UMESciA)

Brain metastasis and survival outcomes after first-line therapy in metastatic melanoma: a multicenter DeCOG study on 1704 patients from the prospective skin cancer registry ADOREG

Background Despite the availability of effective systemic therapies, a significant number of advanced melanoma patients develops brain metastases. This study investigated differences in incidence and time to diagnosis of brain metastasis and survival outcomes dependent on the type of first-line therapy.Methods Patients with metastatic, non-resectable melanoma (AJCCv8 stage IIIC–V) without brain metastasis at start of first-line therapy (1L-therapy) were identified from the prospective multicenter real-world skin cancer registry ADOREG. Study endpoints were incidence of brain metastasis, brain metastasis-free survival (BMFS), progression-free survival (PFS), and overall survival (OS).Results Of 1704 patients, 916 were BRAF wild-type (BRAFwt) and 788 were BRAF V600 mutant (BRAFmut). Median follow-up time after start of 1L-therapy was 40.4 months. BRAFwt patients received 1L-therapy with immune checkpoint inhibitors (ICI) against CTLA-4+PD-1 (n=281) or PD-1 (n=544). In BRAFmut patients, 1L-therapy was ICI in 415 patients (CTLA-4+PD-1, n=108; PD-1, n=264), and BRAF+MEK targeted therapy (TT) in 373 patients. After 24 months, 1L-therapy with BRAF+MEK resulted in a higher incidence of brain metastasis compared with PD-1±CTLA-4 (BRAF+MEK, 30.3%; CTLA-4+PD-1, 22.2%; PD-1, 14.0%). In multivariate analysis, BRAFmut patients developed brain metastases earlier on 1L-therapy with BRAF+MEK than with PD-1±CTLA-4 (CTLA-4+PD-1: HR 0.560, 95% CI 0.332 to 0.945, p=0.030; PD-1: HR 0.575, 95% CI 0.372 to 0.888, p=0.013). Type of 1L-therapy, tumor stage, and age were independent prognostic factors for BMFS in BRAFmut patients. In BRAFwt patients, tumor stage was independently associated with longer BMFS; ECOG Performance status (ECOG-PS), lactate dehydrogenase (LDH), and tumor stage with OS. CTLA-4+PD-1 did not result in better BMFS, PFS, or OS than PD-1 in BRAFwt patients. For BRAFmut patients, multivariate Cox regression revealed ECOG-PS, type of 1L-therapy, tumor stage, and LDH as independent prognostic factors for PFS and OS. 1L-therapy with CTLA-4+PD-1 led to longer OS than PD-1 (HR 1.97, 95% CI 1.122 to 3.455, p=0.018) or BRAF+MEK (HR 2.41, 95% CI 1.432 to 4.054, p=0.001), without PD-1 being superior to BRAF+MEK.Conclusions In BRAFmut patients 1L-therapy with PD-1±CTLA-4 ICI resulted in a delayed and less frequent development of brain metastasis compared with BRAF+MEK TT. 1L-therapy with CTLA-4+PD-1 showed superior OS compared with PD-1 and BRAF+MEK. In BRAFwt patients, no differences in brain metastasis and survival outcomes were detected for CTLA-4+PD-1 compared with PD-1

Validating Automatic Concept-Based Explanations for AI-Based Digital Histopathology

Digital histopathology poses several challenges such as label noise, class imbalance, limited availability of labelled data, and several latent biases to deep learning, negatively influencing transparency, reproducibility, and classification performance. In particular, biases are well known to cause poor generalization. Proposed tools from explainable artificial intelligence (XAI), bias detection, and bias discovery suffer from technical challenges, complexity, unintuitive usage, inherent biases, or a semantic gap. A promising XAI method, not studied in the context of digital histopathology is automated concept-based explanation (ACE). It automatically extracts visual concepts from image data. Our objective is to evaluate ACE’s technical validity following design science principals and to compare it to Guided Gradient-weighted Class Activation Mapping (Grad-CAM), a conventional pixel-wise explanation method. To that extent, we created and studied five convolutional neural networks (CNNs) in four different skin cancer settings. Our results demonstrate that ACE is a valid tool for gaining insights into the decision process of histopathological CNNs that can go beyond explanations from the control method. ACE validly visualized a class sampling ratio bias, measurement bias, sampling bias, and class-correlated bias. Furthermore, the complementary use with Guided Grad-CAM offers several benefits. Finally, we propose practical solutions for several technical challenges. In contradiction to results from the literature, we noticed lower intuitiveness in some dermatopathology scenarios as compared to concept-based explanations on real-world images

Rare TERT Promoter Mutations Present in Benign and Malignant Cutaneous Vascular Tumors

Mutations in the promoter of the telomerase reverse transcriptase (TERT) gene have been described as the most common hot-spot mutations in different solid tumors. High frequencies of TERT promoter mutations have been reported to occur in tumors arising in tissues with low rates of self-renewal. For cutaneous vascular tumors, the prevalence of TERT promoter mutations has not yet been investigated in larger mixed cohorts. With targeted next-generation sequencing (NGS), we screened for different known recurrent TERT promoter mutations in various cutaneous vascular proliferations. In our cohort of 104 representative cutaneous vascular proliferations, we identified 7 TERT promoter mutations. We could show that 4 of 64 (6.3%) hemangiomas and vascular malformations harbored TERT promoter mutations (1 Chr.5:1295228 C > T mutations, 1 Chr.5:1295228_9 CC > TT mutation, and 2 Chr.5:1295250 C > T mutations), 1 of 19 (5.3%) angiosarcomas harbored a Chr.5:1295250 C > T TERT promoter mutation, and 2 of 21 (9.5%) Kaposi’s sarcomas harbored TERT promoter mutations (2 Chr.5:1295250 C > T mutations). To our knowledge, this is the first general description of the distribution of TERT promoter mutations in a mixed cohort of cutaneous vascular tumors, revealing that TERT promoter mutations seem to occur with low prevalence in both benign and malignant cutaneous vascular proliferations

Computed tomography-guided biopsy of radiologically unclear lesions in advanced skin cancer: A retrospective analysis of 47 cases

Background: Radiological imaging such as computed tomography (CT) is used frequently for disease staging and therapy monitoring in advanced skin cancer patients. Detected lesions of unclear dignity are a common challenge for treating physicians. The aim of this study was to assess the frequency and outcome of CT-guided biopsy (CTGB) of radiologically unclear, suspicious lesions and to depict its usefulness in different clinical settings. Methods: This retrospective monocentric study included advanced skin cancer patients (melanoma, Merkel cell carcinoma, squamous cell carcinoma, angiosarcoma, cutaneous lymphoma) with radiologically unclear lesions who underwent CTGB between 2010 and 2018. Results: Of 59 skin cancer patients who received CTGB, 47 received CTGB to clarify radio logically suspicious lesions of unclear dignity. 32 patients had no systemic therapy (cohort A), while 15 patients received systemic treatment at CTGB (cohort B). In both cohorts, CTGB revealed skin cancer metastasis in a large proportion of patients (37.5%, 40.0%, respectively), but benign tissue showing inflammation, fibrosis or infection in an equally large percentage (37.5%, 46.7%, respectively). Additionally, a significant number of other cancer entities was found (25.0%, 13.3%, respectively). In patients receiving BRAF/MEK inhibitors, CTGB confirmed suspicious lesions as skin cancer metastasis in 83.3%, leading to treatment change. In immune checkpoint inhibitor-treated patients, skin cancer metastasis was confirmed in 11.1% of patients only, whereas benign tissue changes (inflammation/fibrosis) were found in 77.8%. Conclusions: Our results highlight the relevance of clarifying radiologically unclear lesions by CTGB before start or change of an anti-tumour therapy to exclude benign alterations and secondary malignancies. (c)& nbsp;2021 Elsevier Ltd. All rights reserved

Genetic and Clinical Characteristics of ARID1A Mutated Melanoma Reveal High Tumor Mutational Load without Implications on Patient Survival

(1) Background: Melanoma has the highest mortality of all cutaneous tumors, despite recent treatment advances. Many relevant genetic events have been identified in the last decade, including recurrent ARID1A mutations, which in various tumors have been associated with improved outcomes to immunotherapy. (2) Methods: Retrospective analysis of 116 melanoma samples harboring ARID1A mutations. Assessment of clinical and genetic characteristics was performed as well as correlations with treatment outcome applying Kaplan–Meier (log-rank test), Fisher’s exact and Chi-squared tests. (3) Results: The majority of ARID1A mutations were in cutaneous and occult melanoma. ARID1A mutated samples had a higher number of mutations than ARID1A wild-type samples and harbored UV-mutations. A male predominance was observed. Many samples also harbored NF1 mutations. No apparent differences were noted between samples harboring genetically inactivating (frame-shift or nonsense) mutations and samples with other mutations. No differences in survival or response to immunotherapy of patients with ARID1A mutant melanoma were observed. (4) Conclusions: ARID1A mutations primarily occur in cutaneous melanomas with a higher mutation burden. In contrast to findings in other tumors, our data does not support ARID1A mutations being a biomarker of favorable response to immunotherapies in melanoma. Larger prospective studies would still be warranted

Factors influencing the adjuvant therapy decision: results of a real-world multicenter data analysis of 904 melanoma patients

Adjuvant treatment of melanoma patients with immune-checkpoint inhibition (ICI) and targeted therapy (TT) significantly improved recurrence-free survival. This study investigates the real-world situation of 904 patients from 13 German skin cancer centers with an indication for adjuvant treatment since the approval of adjuvant ICI and TT. From adjusted log-binomial regression models, we estimated relative risks for associations between various influence factors and treatment decisions (adjuvant therapy yes/no, TT vs. ICI in BRAF mutant patients). Of these patients, 76.9% (95% CI 74–80) opted for a systemic adjuvant treatment. The probability of starting an adjuvant treatment was 26% lower in patients >65 years (RR 0.74, 95% CI 68–80). The most common reasons against adjuvant treatment given by patients were age (29.4%, 95% CI 24–38), and fear of adverse events (21.1%, 95% CI 16–28) and impaired quality of life (11.9%, 95% CI 7–16). Of all BRAF-mutated patients who opted for adjuvant treatment, 52.9% (95% CI 47–59) decided for ICI. Treatment decision for TT or ICI was barely associated with age, gender and tumor stage, but with comorbidities and affiliated center. Shortly after their approval, adjuvant treatments have been well accepted by physicians and patients. Age plays a decisive role in the decision for adjuvant treatment, while pre-existing autoimmune disease and regional differences influence the choice between TT or ICI

Baroreflexaktivierungstherapie bei therapieresistenter Hypertonie : Empfehlungen der BAT-Konsensusgruppe zu Implantation und Nachsorge

Die Wirksamkeit interventioneller Verfahren in der Behandlung der therapierefraktären arteriellen Hypertonie scheint wesentlich von Patientenselektion und Erfahrung der Anwender abhängig zu sein. So zeigte eine aktuelle europäische Kohortenstudie, dass bei 731 vermeintlich therapierefraktären Hypertonikern, die einer interventionellen Hochdrucktherapie zugewiesen wurden (davon 75,6% durch Spezialisten), diese nur in etwa 40% der Fälle indiziert war. Häufigste Gründe für die unzureichende Blutdruck(BD)-Einstellung waren in dieser Untersuchung eine inadäquate medikamentöse Therapie, unentdeckte Formen einer sekundären Hypertonie und eine mangelnde Therapieadhärenz. Insbesondere bei Patienten mit vermeintlich therapierefraktärer Hypertonie ist die Nonadhärenz ein häufiges Problem, das in nichtselektionierten Kollektiven in bis zu 50% der Fälle beschrieben wird und sogar bei Patienten, die zur renalen Sympathikusdenervation überwiesen werden, mit einer Prävalenz von 23% noch auffallend häufig ist. Entsprechend haben in der Pathway-2-Studie die 10 größ- ten Hypertoniezentren Großbritanniens unter Anwendung vielfältiger Untersuchungsmethoden zum Ausschluss von Nonadhärenz und Weißkittelhypertonie annährend 5 Jahre gebraucht, um 346 Patienten mit systolischen BD-Werten von mehr als 140mmHg unter einer antihypertensiven Dreifachkombination zu finden. Die Prävalenz der therapierefraktären Hypertonie wird oftmals mit etwa 10% angegeben. Schätzungen zufolge liegt unter Berücksichtigung der Therapieadhärenz und des medikamentösen Optimierungspotenzials eine reale therapierefraktäre Hypertonie lediglich bei etwa 4–5% der Patienten mit Bluthochdruck vor. Bei einem Teil dieser Patienten scheint ein Ungleichgewicht des vegetativen Nervensystems mit Überaktivität des Sympathikus und vermindertem Parasympathikotonus für die Entwicklung des Bluthochdrucks von zentraler Bedeutung zu sein. Der physiologische Regelkreis der Barorezeptoren hingegen ist bei chronisch erhöhtem BD oft desensibilisiert. Die Baroreflexaktivierungstherapie (BAT) soll über eine direkte elektrische Stimulation der Barorezeptoren am Glomus caroticum zu einer Reaktivierung dieses Reflexbogens mit Hemmung des Sympathikus und Aktivierung des Parasympathikus führen. Dabei könnte bereits die exakte Platzierung der einseitigen Knopfelektrode einen wesentlichen Einfluss auf die Effektivität der Therapie haben. Das Konsensuspapier fasst die aktuelle Evidenz zur Wirksamkeit und Sicherheit der BAT zusammen. Zudem werden, basierend auf den Erfahrungen von Experten auf dem Gebiet der therapierefraktären Hypertonie, erstmalig Anforderungen an die Implantationstechnik zusammengefasst, die die Voraussetzung für eine effiziente Anwendung der BAT darstellen. Die Empfehlungen basieren auf der Interpretation von Studien und den Erfahrungen der Konsensusgruppe. Die genannten Qualitätsmerkmale sollen helfen, durch optimale Implantationstechnik und Nachsorge einen effizienten Einsatz der Ressourcen und die größte Wirksamkeit der BAT bei Patienten mit therapierefraktärer Hypertonie zu erzielen

Treatment management for BRAF-mutant melanoma patients with tumor recurrence on adjuvant therapy: a multicenter study from the prospective skin cancer registry ADOREG

Background Adjuvant therapy with immune-checkpoint inhibitors (CPI) or BRAF/MEK-directed targeted therapy (TT) improves recurrence-free survival (RFS) for patients with advanced, BRAFV600-mutant (BRAFmut) resected melanoma. However, 40% of these patients will develop distant metastases (DM) within 5 years, which require systemic therapy. Little data exist to guide the choice of upfront adjuvant therapy or treatment management upon DM. This study evaluated the efficacy of subsequent treatments following tumor recurrence upon upfront adjuvant therapy.Methods For this multicenter cohort study, we identified 515 BRAFmut patients with resected stage III melanoma who were treated with PD-1 inhibitors (anti-PD1) or TT in the adjuvant setting. Disease characteristics, treatment regimens, details on tumor recurrence, subsequent treatment management, and survival outcomes were collected within the prospective, real-world skin cancer registry ADOReg. Primary endpoints included progression-free survival (PFS) following DM and best tumor response to first-line (1L) treatments.Results Among 515 eligible patients, 273 patients received adjuvant anti-PD1 and 242 adjuvant TT. At a median follow-up of 21 months, 54.6% of anti-PD1 patients and 36.4% of TT patients recurred, while 39.6% (anti-PD1) and 29.3% (TT) developed DM. Risk of recurrence was significantly reduced in patients treated with TT compared with anti-PD1 (adjusted HR 0.52; 95% CI 0.40 to 0.68, p<0.001). Likewise, median RFS was significantly longer in TT-treated patients (31 vs 17 months, p<0.001). Patients who received TT as second adjuvant treatment upon locoregional recurrence had a longer RFS2 as compared with adjuvant CPI (41 vs 6 months, p=0.009). Patients who recurred at distant sites following adjuvant TT showed favorable response rates (42.9%) after switching to 1L ipilimumab+nivolumab (ipi+nivo). Patients with DM during adjuvant anti-PD1 achieved response rates of 58.7% after switching to 1L TT and 35.3% for 1L ipi+nivo. Overall, median PFS was significantly longer in patients who switched treatments for stage IV disease (median PFS 9 vs 5 months, p=0.004).Conclusions BRAFmut melanoma patients who developed DM upon upfront adjuvant therapy achieve favorable tumor control and prolonged PFS after switching treatment modalities in the first-line setting of stage IV disease. Patients with locoregional recurrence benefit from complete resection of recurrence followed by a second adjuvant treatment with TT

Superior skin cancer classification by the combination of human and artificial intelligence

Background: In recent studies, convolutional neural networks (CNNs) outperformed dermatologists in distinguishing dermoscopic images of melanoma and nevi. In these studies, dermatologists and artificial intelligence were considered as opponents. However, the combination of classifiers frequently yields superior results, both in machine learning and among humans. In this study, we investigated the potential benefit of combining human and artificial intelligence for skin cancer classification. Methods: Using 11,444 dermoscopic images, which were divided into five diagnostic categories, novel deep learning techniques were used to train a single CNN. Then, both 112 dermatologists of 13 German university hospitals and the trained CNN independently classified a set of 300 biopsy-verified skin lesions into those five classes. Taking into account the certainty of the decisions, the two independently determined diagnoses were combined to a new classifier with the help of a gradient boosting method. The primary end-point of the study was the correct classification of the images into five designated categories, whereas the secondary end-point was the correct classification of lesions as either benign or malignant (binary classification). Findings: Regarding the multiclass task, the combination of man and machine achieved an accuracy of 82.95%. This was 1.36% higher than the best of the two individual classifiers (81.59% achieved by the CNN). Owing to the class imbalance in the binary problem, sensitivity, but not accuracy, was examined and demonstrated to be superior (89%) to the best individual classifier (CNN with 86.1%). The specificity in the combined classifier decreased from 89.2% to 84%. However, at an equal sensitivity of 89%, the CNN achieved a specificity of only 81.5% Interpretation: Our findings indicate that the combination of human and artificial intelligence achieves superior results over the independent results of both of these systems. (C) 2019 The Author(s). Published by Elsevier Ltd