scholarly journals Ultrasound-Based Radiomics Analysis for Predicting Disease-Free Survival of Invasive Breast Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Lang Xiong ◽  
Haolin Chen ◽  
Xiaofeng Tang ◽  
Biyun Chen ◽  
Xinhua Jiang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Invasive Breast Cancer ◽  
Cox Regression ◽  
Validation Cohort ◽  
Disease Free Survival ◽  
Free Survival ◽  
Net Reclassification Improvement ◽  
Additional Value ◽  
Disease Free ◽  
Radiomics Signature

BackgroundAccurate prediction of recurrence is crucial for personalized treatment in breast cancer, and whether the radiomics features of ultrasound (US) could be used to predict recurrence of breast cancer is still uncertain. Here, we developed a radiomics signature based on preoperative US to predict disease-free survival (DFS) in patients with invasive breast cancer and assess its additional value to the clinicopathological predictors for individualized DFS prediction.MethodsWe identified 620 patients with invasive breast cancer and randomly divided them into the training (n = 372) and validation (n = 248) cohorts. A radiomics signature was constructed using least absolute shrinkage and selection operator (LASSO) Cox regression in the training cohort and validated in the validation cohort. Univariate and multivariate Cox proportional hazards model and Kaplan–Meier survival analysis were used to determine the association of the radiomics signature and clinicopathological variables with DFS. To evaluate the additional value of the radiomics signature for DFS prediction, a radiomics nomogram combining the radiomics signature and clinicopathological predictors was constructed and assessed in terms of discrimination, calibration, reclassification, and clinical usefulness.ResultsThe radiomics signature was significantly associated with DFS, independent of the clinicopathological predictors. The radiomics nomogram performed better than the clinicopathological nomogram (C-index, 0.796 vs. 0.761) and provided better calibration and positive net reclassification improvement (0.147, P = 0.035) in the validation cohort. Decision curve analysis also demonstrated that the radiomics nomogram was clinically useful.ConclusionUS radiomics signature is a potential imaging biomarker for risk stratification of DFS in invasive breast cancer, and US-based radiomics nomogram improved accuracy of DFS prediction.

Radiomics features on ultrasound imaging for the prediction of disease-free survival in triple negative breast cancer: a multi-institutional study

2021 ◽  
pp. 20210188
Author(s):  
Feihong Yu ◽  
Jing Hang ◽  
Jing Deng ◽  
Bin Yang ◽  
Jianxiang Wang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Triple Negative ◽  
Validation Cohort ◽  
External Validation ◽  
Disease Free Survival ◽  
Internal Validation ◽  
Free Survival ◽  
Clinicopathological Variables ◽  
Disease Free ◽  
Radiomics Signature

Objectives: To explore the predictive value of radiomics nomogram using pretreatment ultrasound for disease-free survival (DFS) after resection of triple negative breast cancer (TNBC). Methods and materials: A total of 486 TNBC patients from 3 different institutions were consecutively recruited for this study. They were categorized into the primary cohort (n = 216), as well as the internal validation cohort (n = 108) and external validation cohort (n = 162). In primary cohort, least absolute shrinkage and selection operator logistic regression algorithm was used to select recurrence-related radiomics features extracted from the breast tumor and peritumor regions, and a radiomics signature was constructed derived from the grayscale ultrasound images. A radiomic nomogram integrating independent clinicopathological variables and radiomic signature was established with uni- and multivariate cox regressions. The predictive nomogram was validated using an internal cohort and an independent external cohort regarding abilities of discrimination, calibration and clinical usefulness. Results: The patients with higher Rad-score had a worse prognostic outcome than those with lower Rad-score in primary cohort and two validation cohorts (All p < 0.05).The radiomics nomogram indicated more effective prognostic performance compared with the clinicopathological model and tumor node metastasis staging system (p < 0.01), with a training C-index of 0.75 (95% confidence interval (CI), 0.71–0.80), an internal validation C-index of 0.73 (95% CI, 0.69–0.78) and an external validation 0.71 (95% CI,0.66–0.76). Moreover, the calibration curves revealed a good consistency for survival prediction of the radiomics model. Conclusions: The ultrasound-based radiomics signature was a promising biomarker for risk stratification for TNBC patients. Furthermore, the proposed radiomics modal integrating the optimal radiomics features and clinical data provided individual relapse risk accurately. Advances in knowledge: The radiomics model integrating radiomic signature and independent clinicopathological variables could improve individual prognostic evaluation and facilitate therapeutic decision-making, which demonstrated the incremental value of the radiomics signature for prognostic prediction in TNBC.

scholarly journals Relationship between Ribosomal Protein S6-pS240 Expression and other Prognostic Factors in Non-Special Type Invasive Breast Cancer

Breast Care ◽  
2018 ◽  
Vol 14 (3) ◽  
pp. 171-175
Author(s):  
Frederik Cuperjani ◽  
Lumturije Gashi ◽  
Fisnik Kurshumliu ◽  
Shemsedin Dreshaj ◽  
Fitim Selimi
Keyword(s):  
Breast Cancer ◽  
Ribosomal Protein ◽  
Invasive Breast Cancer ◽  
Menopausal Status ◽  
Treatment Protocol ◽  
Prognostic Index ◽  
Disease Free Survival ◽  
Ki 67 ◽  
Free Survival ◽  
Disease Free

Background: The aim of this study was to investigate the immunohistochemical expression of ribosomal protein (RP) S6-pS240 in non-special type invasive breast cancer in relation to other prognostic markers and gain new insights to facilitate more individualized treatment. Methods: The following clinical and histopathological parameters of 120 patients were determined: S6-pS240 expression, age, menopausal status, tumor size and grade, TNM stage, Nottingham Prognostic Index (NPI), lymph node stage, estrogen and progesterone receptor (ER/PR) expression, HER2/neu amplification, lymphovascular invasion, and proliferative index as measured by Ki-67. Treatment protocol and disease-free survival were evaluated accordingly. Results: Significant positive correlations were seen between S6-pS240 expression and Ki-67 values (rho = 0.530, p < 0.001), and NPI (rho = 0.370, p < 0.001) and HER2/neu amplification (rho = 0.368, p < 0.001). A negative correlation was found between S6-pS240 and ER/PR expression (rho = 0.362, p < 0.001). Patients with negative RP S6-pS240 expression had significantly longer disease-free survival (log-rank test, p = 0.005). Conclusion: Immunohistochemical analysis of RP S6-pS240 is a valuable additional prognostic marker in patients with invasive breast cancer. Routine use of S6-pS240 immunohistochemistry is recommended.

High Expression of Obesity-Linked Phosphatase SHIP2 in Invasive Breast Cancer Correlates with Reduced Disease-Free Survival

Tumor Biology ◽  
2008 ◽  
Vol 29 (5) ◽  
pp. 330-341 ◽  
Author(s):  
Nagendra K. Prasad ◽  
Manish Tandon ◽  
Anant Handa ◽  
George E. Moore ◽  
Charles F. Babbs ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Invasive Breast Cancer ◽  
Disease Free Survival ◽  
High Expression ◽  
Free Survival ◽  
Disease Free

Machine learning radiomics signature on magnetic resonance imaging associated with phenotypes and disease-free survival in patients with breast cancer (RBC-01): A registry-based, multicenter cohort study.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 3563-3563
Author(s):  
Herui Yao ◽  
Yunfang Yu ◽  
Yujie Tan ◽  
Qiugen Hu ◽  
Jie Ouyang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cohort Study ◽  
Disease Free Survival ◽  
Risk Scores ◽  
Breast Cancer Patients ◽  
Free Survival ◽  
Training Cohort ◽  
Clinicopathological Findings ◽  
Disease Free ◽  
Radiomics Signature

3563 Background: The early stage breast cancer patients can vary in disease-free survival (DFS), innovative predictors evaluate the prognostic capacity are urgently needed. We aimed to develop and independently validate a radiomics signature based on MRI associated with phenotypes and DFS in patients with breast cancer and to establish a radiomics nomogram that incorporates the radiomics signature and clinicopathological findings using computational algorithms. Methods: In this multicenter, retrospective, cohort study, we analyzed preoperative contrast–enhanced MRI data from the prospective cohort study (n = 123) of patients who had been treated with neoadjuvant chemotherapy in phase 3 trials and independent cohort (n = 438) at the Sun Yat-sen Memorial Hospital as training cohort to develop the radiomic signature, and validated it in validation cohort (Foshan cohort, n = 121; Dongguan cohort, n = 89) between November 17, 2011, and September 21, 2019, and validated in TGCA cohort (n = 84). Machine-learning algorithm to identify robust imaging subtypes and evaluated their clinical and biologic relevance. A nomogram combining the radiomic signature and clinicopathological findings to predict individual survival based on Cox regression model. The primary endpoint was disease-free survival (DFS). This study is registered with ClinicalTrials.gov, number NCT04003558, and Chinese Clinical Trail Registry, number ChiCTR1900024020. Results: A total of 855 breast cancer patients were included. Radiomics signature was generated to classify patients into high-risk and low-risk groups in the Guangzhou training cohort. Patients with low-risk scores in the training cohort had higher DFS (hazard ratio [HR] 0.55, 95% CI 0.31 to 0.99; P= 0.045) than patients with high-risk scores, and validated in in validation cohort (HR 0.14, 95% CI 0.03 to 0.62; P= 0.003). The nomogram combined radiomics score with clinicopathological factors could accurately predict DFS benefits in training cohort (C-index = 0.83; AUC, 1, 2, 3-year were 0.80, 0.85, 0.82, respectively) and validated in validation cohorts. Conclusions: The radiomics signature are significantly associated with the DFS in patients with breast cancer. Combining the radiomics nomogram improved individualized DFS pretiction. Clinical trial information: NCT04003558 .

Clinicopathological significance of Sox10 expression in triple-negative breast carcinoma

2020 ◽  
Author(s):  
Linfang Jin ◽  
Chenglin Qin ◽  
Xiaowei Qi ◽  
Tingting Hong ◽  
Xiaodong Yang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Metastatic Breast Cancer ◽  
Invasive Breast Cancer ◽  
Triple Negative ◽  
Disease Free Survival ◽  
Metastatic Breast ◽  
Free Survival ◽  
Primary Invasive Breast Cancer ◽  
Sox10 Expression ◽  
Disease Free

Abstract Purpose The present study aimed to investigate the Sox10 expression in the pathological diagnosis of triple-negative breast cancer (TNBC). Furthermore, its correlation with the clinicopathological characteristics and disease-free survival rate in patients with TNBC was also evaluated to identify the diagnostic utility of Sox10 as a reliable biomarker for diagnosis and prognosis of TNBC. Methods Using immunohistochemistry, we identified the expression of Sox10, GATA-3, FOXA1, GCDFP15 and MGB in 376 cases of primary invasive breast cancer, and 77 cases of metastatic breast cancer. The expression of Sox10 in different molecular subtypes of primary invasive breast cancer and metastatic breast cancer were also compared. Furthermore, the correlation between Sox10 expression and clinicopathological parameters and disease-free survival (DFS) of patients with primary TNBC were also analyzed. Results Expression of Sox10 was only detected in the myoepithelial cells of normal breast, but not in any other types of cells, including luminal cell and fibroblasts. The positive rate of Sox10 in primary and metastatic TNBC was significantly higher than that in the other two types (P < 0.001, P < 0.001, respectively). The sensitivity and specificity of Sox10 expression in primary TNBC and metastatic TNBC were significantly lower than GATA-3, significantly higher than FOXA1, GCDFP15, and MGB (P < 0.001, P = 0.0004, P = 0.0064, P = 0.0229, respectively). In 71 cases of primary TNBC, a higher expression rate of Sox10 was significantly associated with high-grade tumors, late-stage tumors, and tumors with involvement of four or more lymph node metastases (P = 0.0145, P = 0.0105, P = 0.0249, respectively). Conclusion Sox10 may be used as a novel reliable putative marker for the diagnosis of TNBC. Notably, Sox10 combined with GATA-3 expression may serve as a supplementary differential diagnostic biomarker for primary and metastatic TNBC. Besides, Sox10 may be a good predictor of the prognosis of primary and metastatic TNBC. This study also highlights the significance of targeting Sox10 as a promising potential therapeutic target gene for TNBC therapy.

Topoisomerase IIα expression correlates with diminished disease-free survival in invasive breast cancer

2006 ◽  
Vol 65 (5) ◽  
pp. 1411-1415 ◽  
Author(s):  
John K. O’Connor ◽  
Lisa J. Hazard ◽  
James M. Avent ◽  
R. Jeffrey Lee ◽  
Jennifer Fischbach ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Invasive Breast Cancer ◽  
Disease Free Survival ◽  
Topoisomerase Iiα ◽  
Free Survival ◽  
Disease Free

scholarly journals Interleukin-13 receptor alpha 2 expression in tumor cells is associated with reduced disease-free survival in patients with luminal subtype invasive breast cancer

Tumor Biology ◽  
2018 ◽  
Vol 40 (6) ◽  
pp. 101042831878365 ◽  
Author(s):  
Hee Jung Kwon ◽  
Jung Eun Choi ◽  
Young Kyung Bae
Keyword(s):  
Breast Cancer ◽  
Invasive Breast Cancer ◽  
Disease Free Survival ◽  
Luminal Breast Cancer ◽  
Breast Cancer Patients ◽  
Free Survival ◽  
Receptor Alpha ◽  
Interleukin 13 ◽  
Clinicopathological Variables ◽  
Disease Free

Interleukin-13 receptor alpha 2 is one of the subunits of transmembrane receptor for interleukin-13. The aim of this study was to investigate the prognostic value of interleukin-13 receptor alpha 2 expression in invasive breast cancer. Interleukin-13 receptor alpha 2 expressions were assessed by immunohistochemistry in tissue microarrays of 1283 invasive breast cancer samples, and associations between these expressions and clinicopathological variables and clinical outcomes were investigated. Interleukin-13 receptor alpha 2 expression was observed in 138 (10.8%) samples, and found to be associated with positive estrogen receptor (p < 0.001) and progesterone receptor (p < 0.001) and with the luminal subtype (p < 0.001). No significant association was found between interleukin-13 receptor alpha 2 expression and other clinicopathological variables including age, tumor size, lymph node metastasis, histologic types, histologic grade, HER2 status, Ki-67 labeling index, or tumor-infiltrating lymphocytes levels. Patients with interleukin-13 receptor alpha 2 expression tended to have poorer disease-free survival, but the difference was not statistically significant (p = 0.069). Subgroup analysis showed luminal breast cancer patients positive for interleukin-13 receptor alpha 2 expression had significantly poorer disease-free survival (p = 0.018) than luminal breast cancer patients negative for interleukin-13 receptor alpha 2 expression. However, no association between interleukin-13 receptor alpha 2 expression and clinical outcome was observed in HER2-positive and triple-negative subgroups (p = 0.574 and p = 0.936, respectively). Multivariate analysis showed interleukin-13 receptor alpha 2 expression was an independent poor prognostic factor for luminal breast cancer (p = 0.03). This study shows interleukin-13 receptor alpha 2 expression could be a useful prognostic marker for selecting patients with luminal breast cancer likely to follow a clinically aggressive course despite receiving systemic therapy.

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