Altered tumor microenvironment heterogeneity of penile cancer during progression from non-lymphatic to lymphatic metastasis.

BACKGROUND: Lymphatic metastasis is the major challenge in the treatment of penile cancer. The prognosis of individuals with lymphatic metastasis is extremely poor. Therefore, early identification of disease progression and lymphatic metastasis is an urgent task for researchers in penile cancer worldwide. METHODS: In this study, using single-cell RNA sequencing, an immune landscape was established for the cancer ecosystem based on 46,861 cells from six patients with penile cancer (four with lymphatic metastasis [stage IV] and two without lymphatic metastasis [stage I]). Using bulk RNA sequencing, the discrepancy between the cancers and their respective metastatic lymph nodes was depicted based on seven patients with penile cancer. RESULTS: The interaction between epithelial cells, fibroblasts, and endothelial cells, and the functional cooperation among invasion, epithelial-mesenchymal transition, and angiogenesis were found to be important landscapes in the penile cancer ecosystem, playing important roles in progression of cancer and lymph node metastasis. CONCLUSIONS: This study is the first to investigate the altered tumor microenvironment heterogeneity of penile cancer as it evolves from non-lymphatic to lymphatic metastasis and provides insights into the mechanisms underlying malignant progression, the premetastatic niche, and lymphatic metastasis in penile cancer.

Predicting distant metastasis in nasopharyngeal carcinoma using gradient boosting tree model based on detailed magnetic resonance imaging reports.

BACKGROUND: Development of distant metastasis (DM) is a major concern during treatment of nasopharyngeal carcinoma (NPC). However, studies have demonstrated improved distant control and survival in patients with advanced NPC with the addition of chemotherapy to concomitant chemoradiotherapy. Therefore, precise prediction of metastasis in patients with NPC is crucial. AIM: To develop a predictive model for metastasis in NPC using detailed magnetic resonance imaging (MRI) reports. METHODS: This retrospective study included 792 patients with non-distant metastatic NPC. A total of 469 imaging variables were obtained from detailed MRI reports. Data were stratified and randomly split into training (50%) and testing sets. Gradient boosting tree (GBT) models were built and used to select variables for predicting DM. A full model comprising all variables and a reduced model with the top-five variables were built. Model performance was assessed by area under the curve (AUC). RESULTS: Among the 792 patients, 94 developed DM during follow-up. The number of metastatic cervical nodes (30.9%), tumor invasion in the posterior half of the nasal cavity (9.7%), two sides of the pharyngeal recess (6.2%), tubal torus (3.3%), and single side of the parapharyngeal space (2.7%) were the top-five contributors for predicting DM, based on their relative importance in GBT models. The testing AUC of the full model was 0.75 (95% confidence interval [CI]: 0.69-0.82). The testing AUC of the reduced model was 0.75 (95%CI: 0.68-0.82). For the whole dataset, the full (AUC = 0.76, 95%CI: 0.72-0.82) and reduced models (AUC = 0.76, 95%CI: 0.71-0.81) outperformed the tumor node-staging system (AUC = 0.67, 95%CI: 0.61-0.73). CONCLUSION: The GBT model outperformed the tumor node-staging system in predicting metastasis in NPC. The number of metastatic cervical nodes was identified as the principal contributing variable.