Affolter Annette, Lammert Anne, Kern Johann, Scherl Claudia, Rotter Nicole
Department of Otorhinolaryngology, Head and Neck Surgery, University Hospital Mannheim, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
Front Cell Dev Biol. 2021 Jul 8;9:666515. doi: 10.3389/fcell.2021.666515. eCollection 2021.
Despite the current progress in the development of new concepts of precision medicine for head and neck squamous cell carcinoma (HNSCC), in particular targeted therapies and immune checkpoint inhibition (CPI), overall survival rates have not improved during the last decades. This is, on the one hand, caused by the fact that a significant number of patients presents with late stage disease at the time of diagnosis, on the other hand HNSCC frequently develop therapeutic resistance. Distinct intratumoral and intertumoral heterogeneity is one of the strongest features in HNSCC and has hindered both the identification of specific biomarkers and the establishment of targeted therapies for this disease so far. To date, there is a paucity of reliable preclinical models, particularly those that can predict responses to immune CPI, as these models require an intact tumor microenvironment (TME). The "ideal" preclinical cancer model is supposed to take both the TME as well as tumor heterogeneity into account. Although HNSCC patients are frequently studied in clinical trials, there is a lack of reliable prognostic biomarkers allowing a better stratification of individuals who might benefit from new concepts of targeted or immunotherapeutic strategies. Emerging evidence indicates that cancer stem cells (CSCs) are highly tumorigenic. Through the process of stemness, epithelial cells acquire an invasive phenotype contributing to metastasis and recurrence. Specific markers for CSC such as CD133 and CD44 expression and ALDH activity help to identify CSC in HNSCC. For the majority of patients, allocation of treatment regimens is simply based on histological diagnosis and on tumor location and disease staging (clinical risk assessments) rather than on specific or individual tumor biology. Hence there is an urgent need for tools to stratify HNSCC patients and pave the way for personalized therapeutic options. This work reviews the current literature on novel approaches in implementing three-dimensional (3D) HNSCC and tumor models in the clinical daily routine. Stem-cell based assays will be particularly discussed. Those models are highly anticipated to serve as a preclinical prediction platform for the evaluation of stable biomarkers and for therapeutic efficacy testing.
尽管目前在头颈部鳞状细胞癌(HNSCC)精准医学新概念的开发方面取得了进展,特别是靶向治疗和免疫检查点抑制(CPI),但在过去几十年中总体生存率并未提高。一方面,这是由于大量患者在诊断时已处于疾病晚期,另一方面,HNSCC经常产生治疗耐药性。明显的肿瘤内和肿瘤间异质性是HNSCC最显著的特征之一,迄今为止,这既阻碍了特异性生物标志物的识别,也阻碍了针对该疾病的靶向治疗的建立。迄今为止,缺乏可靠的临床前模型,尤其是那些能够预测对免疫CPI反应的模型,因为这些模型需要完整的肿瘤微环境(TME)。“理想”的临床前癌症模型应该同时考虑TME和肿瘤异质性。尽管HNSCC患者经常在临床试验中接受研究,但缺乏可靠的预后生物标志物,无法更好地对可能从靶向或免疫治疗策略新概念中获益的个体进行分层。新出现的证据表明,癌症干细胞(CSC)具有高度致瘤性。通过干性过程,上皮细胞获得侵袭性表型,促进转移和复发。CSC的特异性标志物,如CD133和CD44表达以及ALDH活性,有助于在HNSCC中识别CSC。对于大多数患者,治疗方案的分配仅仅基于组织学诊断、肿瘤位置和疾病分期(临床风险评估),而不是基于特定的或个体的肿瘤生物学。因此,迫切需要工具来对HNSCC患者进行分层,并为个性化治疗选择铺平道路。这项工作回顾了当前关于在临床日常工作中实施三维(3D)HNSCC和肿瘤模型的新方法的文献。将特别讨论基于干细胞的检测方法。这些模型被高度期待作为一个临床前预测平台,用于评估稳定的生物标志物和治疗效果测试。