Simonaggio Audrey, Epaillard Nicolas, Pobel Cédric, Moreira Marco, Oudard Stéphane, Vano Yann-Alexandre
Medical Oncology, Hôpital Européen Georges Pompidou, APHP Centre-Université de Paris, 75015 Paris, France.
INSERM, UMR_S 1138, Centre de Recherche des Cordeliers, Team "Cancer, Immune Control and Escape", University Paris Descartes Paris 5, Sorbonne Paris Cite, F-75006 Paris, France.
Cancers (Basel). 2021 Jan 10;13(2):231. doi: 10.3390/cancers13020231.
Renal cell carcinoma (RCC) is the seventh most frequently diagnosed malignancy with an increasing incidence in developed countries. Despite a greater understanding of the cancer biology, which has led to an increase of therapeutic options, metastatic clear cell renal cell carcinoma (mccRCC) still have a poor prognosis with a median five-years survival rate lower than 10%. The standard of care for mccRCC has changed dramatically over the past decades with the emergence of new treatments: anti-VEGFR tyrosine kinase inhibitors, mTOR Inhibitors and immune checkpoint inhibitors (ICI) such as anti-Programmed cell-Death 1 (PD-1) and anti-anti-Programmed Death Ligand-1 (PD-L1) used as monotherapy or as a combination with anti CTLA-4 or anti angiogenic therapies. In the face of these rising therapeutic options, the question of the therapeutic sequences is crucial. Predictive biomarkers are urgently required to provide a personalized treatment for each patient. Disappointingly, the usual ICI biomarkers, PD-L1 expression and Tumor Mutational Burden, approved in melanoma or non-small cell lung cancer (NSCLC) have failed to distinguish good and poor mccRCC responders to ICI. The tumor microenvironment is known to be involved in ICI response. Innovative technologies can be used to explore the immune contexture of tumors and to find predictive and prognostic biomarkers. Recent comprehensive molecular characterization of RCC has led to the development of robust genomic signatures, which could be used as predictive biomarkers. This review will provide an overview of the components of the RCC tumor microenvironment and discuss their role in disease progression and resistance to ICI. We will then highlight the current and future ICI predictive biomarkers assessed in mccRCC with a major focus on immunohistochemistry markers and genomic signatures.
肾细胞癌(RCC)是第七大最常被诊断出的恶性肿瘤,在发达国家其发病率呈上升趋势。尽管对癌症生物学有了更深入的了解,这使得治疗选择有所增加,但转移性透明细胞肾细胞癌(mccRCC)的预后仍然很差,中位五年生存率低于10%。在过去几十年中,随着新治疗方法的出现,mccRCC的治疗标准发生了巨大变化:抗血管内皮生长因子受体(VEGFR)酪氨酸激酶抑制剂、雷帕霉素靶蛋白(mTOR)抑制剂以及免疫检查点抑制剂(ICI),如抗程序性细胞死亡蛋白1(PD-1)和抗程序性死亡配体1(PD-L1),可作为单一疗法或与抗细胞毒性T淋巴细胞相关抗原4(CTLA-4)或抗血管生成疗法联合使用。面对这些不断增加的治疗选择,治疗顺序的问题至关重要。迫切需要预测性生物标志物为每位患者提供个性化治疗。令人失望的是,在黑色素瘤或非小细胞肺癌(NSCLC)中获批的常用ICI生物标志物,即PD-L1表达和肿瘤突变负荷,未能区分mccRCC对ICI反应良好和反应不佳的患者。已知肿瘤微环境与ICI反应有关。创新技术可用于探索肿瘤的免疫特征并寻找预测性和预后性生物标志物。最近对RCC的全面分子特征分析导致了强大的基因组特征的发展,这些特征可作为预测性生物标志物。本综述将概述RCC肿瘤微环境的组成部分,并讨论它们在疾病进展和对ICI耐药中的作用。然后,我们将重点介绍目前和未来在mccRCC中评估的ICI预测性生物标志物,主要关注免疫组织化学标志物和基因组特征。