Comparative evaluation of nuclear and histological grades as prognostic factors for invasive breast cancer

Oshiro, Chiya; Yamasaki, Masaru; Noda, Yuri; Nishimae, Ayaka; Takahashi, Hiroyo; Inaji, Hideo

doi:10.1007/s12282-020-01093-0

Cited by 8 publications

(7 citation statements)

References 25 publications

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“…MCAs may have a long-term risk of local recurrence, and whether they have metastatic potential requires more accumulated cases. Many clinicopathological parameters, including ER, PR, HER2, Ki-67, tumor size, tumor grade, lymph node status, and vascular invasion, have prognostic significance in breast cancer [ 34 ]. For TNBC, the prognostic value of parameters such as tumor grade, tumor size and lymph node status are still questionable; in contrast, high expression of Ki-67 and overexpression of p53 protein may contribute to poor prognosis in such tumors [ 35 , 36 ].…”

Section: Discussionmentioning

confidence: 99%

Mammary mucinous cystadenocarcinoma with long-term follow-up: molecular information and literature review

2023

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Background Mucinous cystadenocarcinoma (MCA) is a very rare form of breast cancer that was first described in 1998. Only 33 cases of primary MCA, including our present case, have been reported thus far. As a consequence, its molecular features, prognosis and treatment regimen are poorly known. Here, we describe a less common presentation of MCA, detail its molecular features, discuss the major differential diagnosis, and provide a brief review of the literature. Case presentation A 59-year-old woman presented with a breast lump in which mammography showed a well-defined nodule. Core needle biopsy (CNB) revealed several lesions lined by tall columnar cells with stratification and abundant mucinous secretion; excision was recommended for final diagnosis. The resected specimens showed cavities of different sizes without surrounding myoepithelial cells. The cavities were rich in mucus, and the nuclei were located at the base of the cells, containing intracellular mucus. Immunohistochemical analysis revealed that it was triple-negative breast cancer (TNBC). Next-generation sequencing (NGS) revealed pathogenic mutations in the PIK3CA, KRAS, MAP2K4, RB1, KDR, PKHD1, TERT, and TP53 genes. A diagnosis of MCA was rendered. The patient has been followed up for 108 months to date and showed no signs of recurrence or metastasis. Conclusion Our study presents the gene profile of an MCA case with no recurrence or metastatic tendency after 108 months of follow-up, and a review of the literature helps us better understand the clinical, pathologic, and molecular features of this tumor.

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Section: Discussionmentioning

confidence: 99%

Mammary mucinous cystadenocarcinoma with long-term follow-up: molecular information and literature review

2023

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“…ER, PR, HER2 and Ki-67) on [18F]FDG uptake can partially be explained by both the interrelations as well as the underlying differences in confounding clinicopathologic factors. Proliferation marker Ki-67, having the single largest effect on [18F]FDG uptake in our meta-analysis, is closely related to histological or nuclear grading and proliferative, poorly differentiated tumours are more common in ER-negative, PR-negative and HER2-positive tumours [ 88 , 89 ]. In addition, tumour size has an independent effect on [18F]FDG uptake and ER-negative, PR-negative, HER2-positive, and Ki-67-positive tumours are associated with larger sizes [ 14 , 88 , 90 ].…”

Section: Discussionmentioning

confidence: 99%

The influence of receptor expression and clinical subtypes on baseline [18F]FDG uptake in breast cancer: systematic review and meta-analysis

et al. 2023

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Background To quantify the relationship between [18F]FDG uptake of the primary tumour measured by PET-imaging with immunohistochemical (IHC) expression of ER, PR, HER2, Ki-67, and clinical subtypes based on these markers in breast cancer patients. Methods PubMed and Embase were searched for studies that compared SUVmax between breast cancer patients negative and positive for IHC expression of ER, PR, HER2, Ki-67, and clinical subtypes based on these markers. Two reviewers independently screened the studies and extracted the data. Standardized mean differences (SMD) and 95% confidence intervals (CIs) were estimated by using DerSimonian-Laird random-effects models. P values less than or equal to 5% indicated statistically significant results. Results Fifty studies were included in the final analysis. SUVmax is significantly higher in ER-negative (31 studies, SMD 0.66, 0.56–0.77, P < 0.0001), PR-negative (30 studies, SMD 0.56; 0.40–0.71, P < 0.0001), HER2-positive (32 studies, SMD − 0.29, − 0.49 to − 0.10, P = 0.0043) or Ki-67-positive (19 studies, SMD − 0.77; − 0.93 to − 0.61, P < 0.0001) primary tumours compared to their counterparts. The majority of clinical subtypes were either luminal A (LA), luminal B (LB), HER2-positive or triple negative breast cancer (TNBC). LA is associated with significantly lower SUVmax compared to LB (11 studies, SMD − 0.49, − 0.68 to − 0.31, P = 0.0001), HER2-positive (15 studies, SMD − 0.91, − 1.21 to − 0.61, P < 0.0001) and TNBC (17 studies, SMD − 1.21, − 1.57 to − 0.85, P < 0.0001); and LB showed significantly lower uptake compared to TNBC (10 studies, SMD − 0.77, − 1.05 to − 0.49, P = 0.0002). Differences in SUVmax between LB and HER2-positive (9 studies, SMD − 0.32, − 0.88 to 0.24, P = 0.2244), and HER2-positive and TNBC (17 studies, SMD − 0.29, − 0.61 to 0.02, P = 0.0667) are not significant. Conclusion Primary tumour SUVmax is significantly higher in ER-negative, PR-negative, HER2-positive and Ki-67-positive breast cancer patients. Luminal tumours have the lowest and TNBC tumours the highest SUVmax. HER2 overexpression has an intermediate effect.

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“…Many previous studies have shown that histological grading is a definite prognostic factor for breast cancer. 2 , 3 It represents a morphological assessment of the biological characteristics of breast cancer and has been shown to provide information related to its clinical behavior. 4 Determining the histological grades can be challenging task, often necessitating preoperative invasive biopsies or the examination of surgically resected tissue samples for pathological microscopic evaluation.…”

Section: Discussionmentioning

confidence: 99%

A Comprehensive Model Based on Dynamic Contrast-Enhanced Magnetic Resonance Imaging Can Better Predict the Preoperative Histological Grade of Breast Cancer Than a Radiomics Model

Wu,

Pan,

Wang

et al. 2023

BCTT

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Background Histological grade is an important prognostic factor for patients with breast cancer and can affect clinical decision-making. From a clinical perspective, developing an efficient and non-invasive method for evaluating histological grading is desirable, facilitating improved clinical decision-making by physicians. This study aimed to develop an integrated model based on radiomics and clinical imaging features for preoperative prediction of histological grade invasive breast cancer. Methods In this retrospective study, we recruited 211 patients with invasive breast cancer and randomly assigned them to either a training group (n=147) or a validation group (n=64) with a 7:3 ratio. Patients were classified as having low-grade tumors, which included grade I and II tumors, or high-grade tumors, which included grade III tumors. Three models were constructed based on basic clinical features, radiomics features, and the sum of the two. To assess diagnostic performance of the radiomics models, we employed measures such as receiver operating characteristic (ROC) curve, decision curve analysis (DCA), accuracy, sensitivity, and specificity, and the predictive performance of the three models was compared using the DeLong test and net reclassification improvement (NRI). Results The area under the curve (AUC) of the clinical model, radiomics model, and comprehensive model was 0.682, 0.833, and 0.882 in the training set and 0.741, 0.751, and 0.836 in the validation set, respectively. NRI analysis confirmed that the combined model was better than the other two models in predicting the histological grade of breast cancer (NRI=21.4% in the testing cohort). Conclusion Compared with the other models, the comprehensive model based on the combination of basic clinical features and radiomics features exhibits more significant potential for predicting histological grade and can better assist clinicians in optimal decision-making.

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Comparative evaluation of nuclear and histological grades as prognostic factors for invasive breast cancer

Cited by 8 publications

References 25 publications

Mammary mucinous cystadenocarcinoma with long-term follow-up: molecular information and literature review

Mammary mucinous cystadenocarcinoma with long-term follow-up: molecular information and literature review

The influence of receptor expression and clinical subtypes on baseline [18F]FDG uptake in breast cancer: systematic review and meta-analysis

A Comprehensive Model Based on Dynamic Contrast-Enhanced Magnetic Resonance Imaging Can Better Predict the Preoperative Histological Grade of Breast Cancer Than a Radiomics Model

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