invasive breast cancer
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The Breast ◽  
2022 ◽  
Vol 61 ◽  
pp. 11-21
Author(s):  
Huan Wang ◽  
Peter Donnan ◽  
E. Jane Macaskill ◽  
Lee Jordan ◽  
Alastair Thompson ◽  
...  

2022 ◽  
Vol 8 (1) ◽  
Author(s):  
Ko Woon Park ◽  
Seon Woo Kim ◽  
Heewon Han ◽  
Minsu Park ◽  
Boo-Kyung Han ◽  
...  

AbstractPatients with a biopsy diagnosis of ductal carcinoma in situ (DCIS) may be diagnosed with invasive breast cancer after excision. We evaluated the preoperative clinical and imaging predictors of DCIS that were associated with an upgrade to invasive carcinoma on final pathology and also compared the diagnostic performance of various statistical models. We reviewed the medical records; including mammography, ultrasound (US), and magnetic resonance imaging (MRI) findings; of 644 patients who were preoperatively diagnosed with DCIS and who underwent surgery between January 2012 and September 2018. Logistic regression and three machine learning methods were applied to predict DCIS underestimation. Among 644 DCIS biopsies, 161 (25%) underestimated invasive breast cancers. In multivariable analysis, suspicious axillary lymph nodes (LNs) on US (odds ratio [OR], 12.16; 95% confidence interval [CI], 4.94–29.95; P < 0.001) and high nuclear grade (OR, 1.90; 95% CI, 1.24–2.91; P = 0.003) were associated with underestimation. Cases with biopsy performed using vacuum-assisted biopsy (VAB) (OR, 0.42; 95% CI, 0.27–0.65; P < 0.001) and lesion size <2 cm on mammography (OR, 0.45; 95% CI, 0.22–0.90; P = 0.021) and MRI (OR, 0.29; 95% CI, 0.09–0.94; P = 0.037) were less likely to be upgraded. No significant differences in performance were observed between logistic regression and machine learning models. Our results suggest that biopsy device, high nuclear grade, presence of suspicious axillary LN on US, and lesion size on mammography or MRI were independent predictors of DCIS underestimation.


2022 ◽  
Author(s):  
Yunhao Gan ◽  
Fuxin Zhong ◽  
Lingyu Li ◽  
Hao Wang

Abstract Background: Invasive breast carcinoma (BRCA) is a common type of breast cancer with high incidence in clinics, so it is significant to find an effective biomarker for BRCA diagnosis and treatment. Although some Armadillo (Arm)-repeat proteins families are confirmed to be biomarkers in cancers, the role of Armadillo repeat-containing 1 (ARMC1) in BRCA remains unknown.Methods: We analyzed the ARMC1 expression in normal breast tissues and BRCA samples, and its association with overall survival by the public database. χ² test evaluated the risks associated with ARMC1 expression in TCGA-BRCA patient samples. The ARMC1 mutations in BRCA were explored in the cBioportal database. Besides, the GO and KEGG analysis was used to explore the potential signaling pathways of ARMC1 in BRCA. Lastly, Immunohistochemistry and immunohistochemistry were performed to validate the ARMC1 expression in BRCA.Results: ARMC1 level in tumor sample was significantly higher than that in normal tissue, and it was also related to lower survival. The factors in clinical patients such as tumor stage and grade and histology were associated with ARMC1 expression. There were 32% of ARMC1 genetic mutations in BRCA, and the amplification and high expression made up the majority of them. Also, ARMC1 might regulate BRCA by involving in the cell cycle. Increased ARMC1 expression was found in clinical breast carcinoma tissues by our confirmatory experiments.Conclusions: All the results revealed that ARMC1 may play a significant role in BRCA as a biomarker, it provides valuable clues for the treatment and diagnosis of invasive breast cancer.


2022 ◽  
pp. 000313482110697
Author(s):  
Ileana Horattas ◽  
Andrew Fenton ◽  
Joseph Gabra ◽  
Amanda Mendiola ◽  
Fanyong Li ◽  
...  

Background Molecular subtype in invasive breast cancer guides systemic therapy. It is unknown whether molecular subtype should also be considered to tailor surgical therapy. The present investigation was designed to evaluate whether breast cancer subtype impacted surgical margins in patients with invasive breast cancer stage I through III undergoing breast-conserving therapy. Methods Data from 2 randomized trials evaluating cavity shave margins (CSM) on margin status in patients undergoing partial mastectomy (PM) were used for this analysis. Patients were included if invasive carcinoma was present in the PM specimen and data for all 3 receptors (ER, PR, and HER2) were known. Patients were classified as luminal if they were ER and/or PR positive; HER2 enriched if they were ER and PR negative but HER2 positive; and TN if they were negative for all 3 receptors. The impact of subtype on the margin status was evaluated at completion of standard PM, prior to randomization to CSM versus no CSM. Non-parametric statistical analyses were performed using SPSS Version 26. Results Molecular subtype was significantly correlated with race ( P = .011), palpability ( P = .007), and grade ( P < .001). Subtype did not correlate with Hispanic ethnicity ( P = .760) or lymphovascular invasion ( P = .756). In this cohort, the overall positive margin rate was 33.7%. This did not vary based on molecular subtype (positive margin rate 33.7% for patients with luminal tumors vs 36.4% for those with TN tumors, P = .425). Discussion Molecular subtype does not predict margin status. Therefore, molecular subtype should not, independent of other factors, influence surgical decision-making.


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