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影响美国印第安人（AI）社区的癌症发病率和相关死亡率明显高于美国其他种族。更具体地说，肾细胞癌（RCC）是AI人群中最常见的癌症形式，与其他种族相比，诊断发生在更年轻的年龄。目前用于改善个性化医疗的测序数据集缺乏来自AI癌症样本的信息，这是由于AI缺乏参与基因组和遗传研究。我们这个项目的最终目标是将我们的发现转化为改善所有人群的精准医疗，了解AI癌症患者的独特原因和驱动突变是必要的。我们假设AI癌症样本中存在功能相关和独特的突变特征和分子途径破坏，它们的鉴定将为癌症发病机制，进展提供重要见解，并有助于改善诊断和治疗。

Cancer incidence and associated death rates affecting American Indian (AI) communities are significantly higher than other races in the United States. More specifically, renal cell carcinoma (RCC) is the most common form of cancer in AI populations with diagnoses occurring at a younger age when compared to other races. Current sequencing datasets that are used for improving personalized medicine lacks information from AI cancer samples due to the lack of AI involvement in genomic and genetic research. Our ultimate goal for this project is to translate our findings to improve precision medicine for all populations, understanding the unique causes and driver mutations in AI cancer patients is a necessity. We hypothesize that functionally relevant and unique mutational signatures and molecular pathway disruption exist in the AI cancer samples and their identification will provide significant insights into cancer pathogenesis, progression, and will also help to improve diagnoses and treatment.