Aim Integrin alpha 7 (ITGA7) regulates cancer stemness and metastasis in several malignancies, while its role in cervical cancer is obscure. Therefore, the current study aimed to investigate the correlation among ITGA7, cluster of differentiation 133 (CD133), and aldehyde dehydrogenase isoform 1 (ALDH1), as well as their relation to tumor features and survival in cervical cancer patients. Methods A total of 133 surgical cervical cancer patients were enrolled. Tumor ITGA7, CD133, and ALDH1 expressions were determined by immunohistochemistry (IHC). Furthermore, the clinicopathological features, disease‐free survival (DFS), and overall survival (OS) were collected. Results ITGA7 expression positively related to CD133 expression (p = 0.040) and ALDH1 expression (p < 0.001). Besides, ITGA7 (p = 0.001), CD133 (p = 0.016), and ALDH1 (p = 0.009) high expressions linked with poor tumor differentiation; meanwhile, ITGA7 (p = 0.010) and ALDH1 (p = 0.004) high expressions correlated with more prevalence of lymph node metastasis. However, ITGA7, CD133, or ALDH1 expression was not associated with other clinicopathological features. Inspiringly, it was worth noting that ITGA7 (p = 0.009), CD133 (p = 0.041), and ALDH1 (p = 0.035) high expressions predicted unfavorable DFS; meanwhile, both ITGA7 (p = 0.021) and ALDH1 (p = 0.023) high expressions but not CD133 expression (p = 0.169) forecasted exasperated OS. Conclusion ITGA7, CD133, ALDH1 are inter‐correlated, and linked with poor differentiation, lymph node metastasis as well as worse survival in surgical cervical cancer.

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ObjectiveTo investigate risk factors for advanced melanoma over 50 years of age and to develop and validate a new line chart and classification system.MethodsThe SEER database was screened for patients diagnosed with advanced melanoma from 2010 to 2019 and Cox regression analysis was applied to select variables affecting patient prognosis. The area under curve (AUC), relative operating characteristic curve (ROC), Consistency index (C-index), decision curve analysis (DCA), and survival calibration curves were used to verify the accuracy and utility of the model and to compare it with traditional AJCC tumor staging. The Kaplan-Meier curve was applied to compare the risk stratification between the model and traditional AJCC tumor staging.ResultsA total of 5166 patients were included in the study. Surgery, age, gender, tumor thickness, ulceration, the number of primary melanomas, M stage and N stage were the independent prognostic factors of CSS in patients with advanced melanoma (P&lt;0.05). The predictive nomogram model was constructed and validated. The C-index values obtained from the training and validation cohorts were 0.732 (95%CI: 0.717-0.742) and 0.741 (95%CI: 0.732-0.751). Based on the observation and analysis results of the ROC curve, survival calibration curve, NRI, and IDI, the constructed prognosis model can accurately predict the prognosis of advanced melanoma and performs well in internal verification. The DCA curve verifies the practicability of the model. Compared with the traditional AJCC staging, the risk stratification in the model has a better identification ability for patients in different risk groups.ConclusionThe nomogram of advanced melanoma and the new classification system were successfully established and verified, which can provide a practical tool for individualized clinical management of patients.