Eight lectins were used to study 100 cases of breast carcinoma and 56 cases of non-carcinoma breast tissues by lectin affinity histochemical method. The results showed that Bandeirasa Simplicifolia (BSL) and Peanut ag...Eight lectins were used to study 100 cases of breast carcinoma and 56 cases of non-carcinoma breast tissues by lectin affinity histochemical method. The results showed that Bandeirasa Simplicifolia (BSL) and Peanut agglutinin (PNA) had higher positive rates in breast carcinoma than both normal breast and benign lesions (P<0.005). The positive deposit in malignant lesions was mainly located in cytoplasm, while in non-malignant lesions, it was almost lined along the lumen of glands and small ducts (P<0.005). The authors think that expression of PNA-receptor in the cytoplasm might be associated with the mechanism that the tumor could escape from immune attack. Comparison analysis on the normal breast indicated that PNA affinity histoche-mistry would be useful to the understanding of the metabolism of β-D-galactosyl-N-acetyl-D-galactosa-mine during the development of normal breast and histological origin of breast carcinoma.展开更多
Background:Young breast cancer(YBC)is a subset of breast cancer that is often more aggressive,but less is known about its prognosis.In this study,we aimed to generate nomograms to predict the overall survival(OS)and b...Background:Young breast cancer(YBC)is a subset of breast cancer that is often more aggressive,but less is known about its prognosis.In this study,we aimed to generate nomograms to predict the overall survival(OS)and breast cancer‐specific survival(BCSS)of YBC patients.Methods:Data of women diagnosed with YBC between 2010 and 2020 were obtained from the Surveillance,Epidemiology,and End Results(SEER)database.The patients were randomly allocated into a training cohort(n=15,227)and internal validation cohort(n=6,526)at a 7:3 ratio.With the Cox regression models,significant prognostic factors were identified and used to construct 3‐,5‐,and 10‐year nomograms of OS and BCSS.Data from the Molecular Taxonomy of Breast Cancer International Consortium(METABRIC)database were used as an external validation cohort(n=90).Results:We constructed nomograms incorporating 10 prognostic factors for OS and BCSS.These nomograms demonstrated strong predictive accuracy for OS and BCSS in the training cohort,with C‐indexes of 0.806 and 0.813,respectively.The calibration curves verified that the nomograms have good prediction accuracy.Decision curve analysis demonstrated their practical clinical value for predicting YBC patient survival rates.Additionally,we provided dynamic nomograms to improve the operability of the results.The risk stratification ability assessment also showed that the OS and BCSS rates of the low‐risk group were significantly better than those of the high‐risk group.Conclusions:Here,we generated and validated more comprehensive and accurate OS and BCSS nomograms than models previously developed for YBC.These nomograms can help clinicians evaluate patient prognosis and make clinical decisions.展开更多
文摘Eight lectins were used to study 100 cases of breast carcinoma and 56 cases of non-carcinoma breast tissues by lectin affinity histochemical method. The results showed that Bandeirasa Simplicifolia (BSL) and Peanut agglutinin (PNA) had higher positive rates in breast carcinoma than both normal breast and benign lesions (P<0.005). The positive deposit in malignant lesions was mainly located in cytoplasm, while in non-malignant lesions, it was almost lined along the lumen of glands and small ducts (P<0.005). The authors think that expression of PNA-receptor in the cytoplasm might be associated with the mechanism that the tumor could escape from immune attack. Comparison analysis on the normal breast indicated that PNA affinity histoche-mistry would be useful to the understanding of the metabolism of β-D-galactosyl-N-acetyl-D-galactosa-mine during the development of normal breast and histological origin of breast carcinoma.
基金Provincial‐Level Clinical Key Specialty Construction in Qinghai Province。
文摘Background:Young breast cancer(YBC)is a subset of breast cancer that is often more aggressive,but less is known about its prognosis.In this study,we aimed to generate nomograms to predict the overall survival(OS)and breast cancer‐specific survival(BCSS)of YBC patients.Methods:Data of women diagnosed with YBC between 2010 and 2020 were obtained from the Surveillance,Epidemiology,and End Results(SEER)database.The patients were randomly allocated into a training cohort(n=15,227)and internal validation cohort(n=6,526)at a 7:3 ratio.With the Cox regression models,significant prognostic factors were identified and used to construct 3‐,5‐,and 10‐year nomograms of OS and BCSS.Data from the Molecular Taxonomy of Breast Cancer International Consortium(METABRIC)database were used as an external validation cohort(n=90).Results:We constructed nomograms incorporating 10 prognostic factors for OS and BCSS.These nomograms demonstrated strong predictive accuracy for OS and BCSS in the training cohort,with C‐indexes of 0.806 and 0.813,respectively.The calibration curves verified that the nomograms have good prediction accuracy.Decision curve analysis demonstrated their practical clinical value for predicting YBC patient survival rates.Additionally,we provided dynamic nomograms to improve the operability of the results.The risk stratification ability assessment also showed that the OS and BCSS rates of the low‐risk group were significantly better than those of the high‐risk group.Conclusions:Here,we generated and validated more comprehensive and accurate OS and BCSS nomograms than models previously developed for YBC.These nomograms can help clinicians evaluate patient prognosis and make clinical decisions.
