Comprehensive Characterization of Tumor Purity and Its Clinical Implications in Gastric Cancer - Lou, Shenghan; Zhang, Jian; Yin, Xin; Zhang, Yao; Fang, Tianyi; Wang, Yimin; Xue, Yingwei (Frontiers in Cell and Developmental Biology, 2022)
Solid tumour tissues are composed of tumour and non-tumour cells, such as stromal cells and immune cells. These non-tumour cells constitute an essential part of the tumour microenvironment (TME), which decrease the tumour purity and play an important role in carcinogenesis, malignancy progression, treatment resistance and prognostic assessment. However, the implications of various purity levels in gastric cancer (GC) remain largely unknown. In the present study, we used an in-silico approach to infer the tumour purity of 2,259 GC samples obtained from our hospital and 12 public datasets based on the transcriptomic data. We systematically evaluated the association of tumour purity with clinical outcomes, biological features, TME characteristics and treatment response in GC. We found that tumour purity might be a patient-specific intrinsic characteristic of GC. Low tumour purity was independently correlated with shorter survival time and faster recurrence and significantly associated with mesenchymal, invasive and metastatic phenotypes. Integrating GC purity into a clinical prognostic nomogram significantly improved predictive validity and reliability. In addition, low tumour purity was strongly associated with immune and stromal cell functions. Fibroblasts, endothelial cells and monocytes were markedly enriched in low-purity tumours, serving as robust indicators of a poor prognosis. Moreover, patients with low GC purity may not benefit more from adjuvant chemotherapy. Our findings highlight that tumour purity confers important clinical, biological, microenvironmental and treatment implications for patients with GC. Therefore, a comprehensive evaluation of tumour purity in individual tumours can provide more insights into the molecular mechanisms of GC, facilitate precise classification and clinical prediction and help to develop more effective individualised treatment strategies.