Cutaneous neoplasias in epidermolysis bullosa: molecular characterization and application of augmented intelligence

大疱性表皮松解症中的皮肤肿瘤：分子特征和增强智能的应用

• 批准号: 459731775
• 负责人: Dr. Antonia Reimer-Taschenbrecker
• 金额: --
• 依托单位: Feinberg School of Medicine
• 依托单位国家: 德国
• 项目类别: WBP Fellowship
• 财政年份: 2021
• 资助国家: 德国
• 起止时间: 2020-12-31 至 2022-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/459731775?language=en
• 关键词: Cutaneous; neoplasias; epidermolysis; bullosa; molecular

Epidermolysis bullosa (EB) is a rare and serious skin condition. The skin is fragile, minor injuries lead to blisters and wounds, and patients suffer from frequent pain and infections. As a severe complication, patients with EB develop skin cancer, particularly squamous cell carcinoma (SCC). SCCs in EB occur at a young age and are aggressive, so early discovery is key. However, recognizing this cancer is difficult. In this project, we will train a computer using artificial intelligence (AI) to recognize SCC on EB skin. This method has recently proven successful in dermatology, and AI was equal to dermatologists in recognizing certain skin cancers on “normal” skin after being trained on thousands of photographs. However, EB patient cohorts and thus image collections in national centers are small. To solve this, this project joins several international reference centers to amass a large number of photographs of EB SCCs and EB skin for computer training. The goal is to create a smartphone application for both physicians and patients. Applying AI in rare skin disease is a new and important step to improve diagnostics, therapy, and patients’ quality of life.Another characteristic, but poorly understood skin finding in EB, is the EB nevus. These large pigmented spots occur in up to 14% of EB patients, grow rapidly, and show certain characteristics of melanoma, the most severe skin cancer in humans. Although EB nevi are common, they are worrisome to patients and physicians. Knowledge about EB nevi is sparse and results solely from small case studies. Why and how some patients develop EB nevi is unclear. To date, no EB nevus has transformed to melanoma, which may simply reflect the reduced lifespan of patients. It is also unknown whether EB nevi are in fact true nevi, which carry certain genetic changes in BRAF or NRAS genes; we think they are, which means they could turn into cancer.In this project, we will deepen our understanding of the clinical appearance, behavior (i.e., size, location, progression), and cause of EB nevi. For this, we will join patient cohorts of several international reference centers and collect photographs, clinical data, and tissue samples of EB nevi. From sections of tissue samples, specific markers of the pigmentary cells (melanocytes) and of the structures holding skin together that malfunction in EB will be stained and assessed. DNA will be isolated and genetic examination regarding BRAF and NRAS genes will be performed. We will then model the EB nevus in the laboratory by cultivating melanocytes and EB keratinocytes together and assessing their behavior and interaction. From this, we will better understand how EB nevi develop and what course they take.Together, both project parts will fill gaps in EB knowledge and can serve as examples for the large field of rare diseases. Most importantly, the new findings will directly benefit patients with EB.

大疱性表皮病（EB）是一种罕见而严重的皮肤病。皮肤很脆弱，轻微的伤害会导致水泡和伤口，患者经常遭受疼痛和感染。作为一种严重的并发症，EB患者会发展为皮肤癌，特别是鳞状细胞癌（SCC）。EB中的SCC发生在年轻时，并且具有侵略性，因此早期发现是关键。然而，识别这种癌症是困难的。在这个项目中，我们将使用人工智能（AI）训练计算机识别EB皮肤上的SCC。这种方法最近在皮肤病学中被证明是成功的，人工智能在经过数千张照片的训练后，在识别“正常”皮肤上的某些皮肤癌方面与皮肤科医生相当。然而，EB患者队列和国家中心的图像收集量很小。为了解决这个问题，本项目联合几个国际参考中心，收集了大量的EB SCC和EB皮肤的照片，用于计算机培训。我们的目标是为医生和患者创建一个智能手机应用程序。将AI应用于罕见皮肤病是改善诊断、治疗和患者生活质量的一个新的重要步骤。EB的另一个特征是EB痣，但人们对EB的皮肤发现知之甚少。这些大的色素斑发生在高达14%的EB患者中，生长迅速，并显示出黑色素瘤的某些特征，黑色素瘤是人类最严重的皮肤癌。虽然EB痣是常见的，他们是令人担忧的病人和医生。关于EB痣的知识是稀疏的，结果仅仅从小的案例研究。一些患者为什么以及如何发展EB痣尚不清楚。迄今为止，没有EB痣转化为黑色素瘤，这可能只是反映了患者寿命的缩短。目前还不清楚EB痣是否真的是痣，它携带BRAF或NRAS基因的某些遗传变化;我们认为它们是，这意味着它们可能变成癌症。在这个项目中，我们将加深我们对临床表现，行为（即，大小，位置，进展）和EB痣的原因。为此，我们将加入几个国际参考中心的患者队列，并收集EB痣的照片，临床数据和组织样本。从组织样本的切片中，将染色并评估色素细胞（黑素细胞）和将皮肤保持在一起的结构的特异性标志物，该结构在EB中发生故障。将分离DNA，并进行BRAF和NRAS基因的遗传学检查。然后，我们将在实验室中通过一起培养黑素细胞和EB角质形成细胞并评估它们的行为和相互作用来模拟EB痣。由此，我们将更好地了解EB痣是如何发展的，以及它们的发展历程。这两个项目部分将共同填补EB知识的空白，并可作为罕见病这一大领域的范例。最重要的是，新发现将直接使EB患者受益。