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

Evaluating the impact of histological vs. nuclear grading on CPS + EG Score for HR + /HER2-early breast cancer

PURPOSE

The CPS + EG score, widely used for risk assessment in high-risk HR + /HER2-early breast cancer following neoadjuvant chemotherapy (NAC), integrates clinical and pathological staging, estrogen receptor status, and nuclear grading (nG). However, histological grading (hG) is often used in clinical practice due to better availability. This study aims to assess the concordance between nG and hG and examine their impact on CPS + EG scores.

METHODS

A retrospective analysis was conducted at the Red Cross Hospital Munich with two cohorts. Cohort 1 included 610 consecutively treated patients in 2022 to evaluate the concordance of nG and hG scores. Cohort 2 involved 106 high-risk patients treated between 2019 and 2022, comparing CPS + EG scores calculated using nG versus hG values.

RESULTS

In Cohort 1, nG and hG were discordant in 31.2% of cases, with nG3 classifications outnumbering hG3. Cohort 2 showed a similar discordance rate of 33.0%, with more tumors classified as nG3 (52.8%) than hG3 (36.8%). Among non-pCR patients, a CPS + EG score of ≥ 3 was found in 29.7% of cases with nG, versus 19.0% with hG, indicating hG may underestimate risk.

CONCLUSION

Using hG instead of nG for CPS + EG calculations may underestimate risks related to distant metastasis-free and disease-specific survival, suggesting a potential need for nG prioritization in clinical risk assessments.

Development of an Ultrasound-based Nomogram for Predicting Pathologic Complete Response and Axillary Response in Node-Positive Patients with Triple- Negative Breast Cancer

BACKGROUND

The accurate prediction of pathological complete response (pCR) in the breast and axillary lymph nodes (ALN) before neoadjuvant chemotherapy (NAC) is of utmost importance for the development of treatment strategies. We aim to construct a nomogram on ultrasound (US) and clinical-pathologic factors to predict breast and ALN pCR in node-positive triple-negative breast cancers (TNBCs).

METHODS

Patients identified with TNBCs from institution 1 (n = 328) were used for training cohort and those from institution 2 (n = 192) were for validation cohort. US was conducted before and after NAC, and characteristics were obtained from medical records. Univariate and multivariate regression analysis were performed to identify US and clinical-pathologic factors associated with breast and ALN pCR in the training cohort. The assessment of predictive performance was conducted using the receiving operating characteristic curve (ROC), discrimination, and calibration.

RESULTS

Overall, 34.6% of patients achieved breast pCR and 48.1% of patients achieved ALN pCR. The nomogram 1 used for predicting pCR in the breast (AUC, 0.84; 95% CI: 0.79, 0.88) outperformed the clinical (AUC, 0.73; 95% CI: 0.68, 0.78) and US models (AUC, 0.79; 95% CI: 0.74, 0.83). The nomogram 2 used for predicting pCR in the axllia (AUC, 0.83; 95% CI: 0.78, 0.87) also outperformed the clinical (AUC, 0.64; 95% CI: 0.58, 0.69) and US models (AUC, 0.80; 95% CI: 0.75, 0.84). The calibration curve and discrimination curve indicate that the nomogram has good calibration performance and clinical applicability.

CONCLUSION

The nomogram showed promising predictive performance for predicting breast and ALN pCR in patients with TNBCs.

Breast Cancer Stem Cells and Tumor Heterogeneity: Characteristics and Therapeutic Strategies

Breast cancer is one of the most frequently detected malignancies worldwide. It is responsible for more than 15% of all death cases caused by cancer in women. Breast cancer is a heterogeneous disease representing various histological types, molecular characteristics, and clinical profiles. However, all breast cancers are organized in a hierarchy of heterogeneous cell populations, with a small proportion of cancer stem cells (breast cancer stem cells (BCSCs)) playing a putative role in cancer progression, and they are responsible for therapeutic failure. In different molecular subtypes of breast cancer, they present different characteristics, with specific marker profiles, prognoses, and treatments. Recent efforts have focused on tackling the Wnt, Notch, Hedgehog, PI3K/Akt/mTOR, and HER2 signaling pathways. Developing diagnostics and therapeutic strategies enables more efficient elimination of the tumor mass together with the stem cell population. Thus, the knowledge about appropriate therapeutic methods targeting both "normal" breast cancer cells and breast cancer stem cell subpopulations is crucial for success in cancer elimination.

Preoperative Dynamic Contrast-Enhanced and Diffusion-Weighted Breast Magnetic Resonance Imaging Findings for Prediction of Lymphovascular Invasion of the Lesions in Node-Negative Invasive Breast Cancer

Purpose: Our single-center retrospective study aimed to investigate the relationship between preoperative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) findings and apparent diffusion coefficient (ADC) values and lymphovascular invasion (LVI) status of the lesions in patients with clinically-radiologically lymph node-negative invasive breast cancer. Methods: A total of 250 breast lesions diagnosed in preoperative magnetic resonance imaging were identified. All patients were divided into 2 subgroups: LVI-negative and LVI-positive according to the pathological findings of surgical specimens. The 2 groups' DCE-MRI findings, ADC values, and histopathological results of lesions were compared. Results: LVI was detected in 100 of 250 lesions. Younger age than 45 years and larger lesion size than 20 mm were found to be associated with the presence of LVI (P < .001). High histological and nuclear grade (P = .001), HER2-enriched molecular subtype (P = .001), and Ki-67 positivity (P = .016) were significantly associated with LVI. The LVI positivity rate was significantly higher in the lesions with medium-rapid initial phase kinetic curve and washout delayed phase kinetic curve (P = .001). The presence of LVI was significantly associated with the presence of peritumoral edema, sentinel lymph node metastasis, adjacent vessel sign, and increased whole breast vascularity (P < .001). When diffusion-weighted imaging findings were evaluated, it was determined that tumoral ADC values lower than 1068 × 10-6 mm2/second (P = .002) and peritumoral-tumoral ADC ratios higher than 1.5 (P = .001) statistically increased the probability of LVI. Conclusion: The patient's age, various histopathological and DCE-MRI findings, tumoral ADC value, and peritumoral-tumoral ADC ratio may be useful in the preoperative prediction of LVI status in breast cancer lesions.

Assessment of nuclear grade-based recurrence risk classification in patients with hormone receptor-positive, human epidermal growth factor receptor 2-negative, node-positive high-risk early breast cancer

BACKGROUND

Histological grade (HG) has been used in the MonrachE trial to select patients with hormone receptor (HR)-positive, human epidermal growth factor receptor 2 (HER2)-negative, node-positive high-risk early breast cancer (EBC). Although nuclear grade (NG) is widely used in Japan, it is still unclear whether replacing HG with NG can appropriately select high-risk patients.

METHODS

We retrospectively reviewed 647 patients with HR-positive, HER2-negative, node-positive EBC and classified them into the following four groups: group 1: ≥ 4 positive axillary lymph nodes (pALNs) or 1-3 pALNs and either grade 3 of both grading systems or tumors ≥ 5 cm; group 2: 1-3 pALNs, grade < 3, tumor < 5 cm, and Ki-67 ≥ 20%; group 3: 1-3 pALNs, grade < 3, tumor < 5 cm, and Ki-67 < 20%; and group 4: group 2 or 3 by HG classification but group 1 by NG classification. We compared invasive disease-free survival (IDFS) and distant relapse-free survival (DRFS) among the four groups using the Kaplan-Meier method with the log-rank test.

RESULTS

Group 1 had a significantly worse 5-year IDFS and DRFS than groups 2 and 3 (IDFS 80.8% vs. 89.5%, P = 0.0319, 80.8% vs. 95.5%, P = 0.002; DRFS 85.2% vs. 95.3%, P = 0.0025, 85.2% vs. 98.4%, P < 0.001, respectively). Group 4 also had a significantly worse 5-year IDFS (78.0%) and DRFS (83.6%) than groups 2 and 3.

CONCLUSIONS

NG was useful for stratifying the risk of recurrence in patients with HR-positive, HER2-negative, node-positive EBC and was the appropriate risk assessment for patient groups not considered high-risk by HG classification.

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

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.

A multi-dimensional nomogram to predict non-sentinel lymph node metastases in T1-2HR+ breast cancer

Background

Axillary lymph node dissection (ALND) could be omitted for T1-2 breast cancer patients with 1-2 positive sentinel lymph node (SLN) after breast-conserving surgery when radiation is planned. However, whether ALND could be replaced by radiation in patients with 1-3 positive SLNs when no more non-SLN metastasis were observed after mastectomy are still controversial. The aim of our study was to develop and validate a nomogram for predicting the possibility of non-SLN metastasis in T1-2 and hormone receptor (HR) positive breast cancer patients with 1-3 positive SLNs after mastectomy.

Methods

We retrospectively reviewed and analyzed the data including the basic information, preoperative sonographic characteristics, and pathological features in breast cancer patients with 1-3 positive SLNs in our medical center between Jan 2016 and Dec 2021. The Chi-square, Fisher's exact test, and t test were used for comparison of categorical and qualitative variables among patients with or without non-SLN metastasis. Univariate and multivariate logistic regression were used to determine the risk factors for non-SLN metastasis. These predictors were used to build the nomogram. The C-index and area under the receiver operating characteristic curve (AUC) was calculated to assess the accuracy of the model.

Results

A total of 49 in 107 (45.8%) patients were identified with non-SLN metastasis. In multivariate analysis, four variables including younger age, lower estrogen receptor (ER) expression, higher histological score, and cortex thickening of the lymph nodes were determined to be significantly associated with non-SLN metastasis. An individualized nomogram was consequently established with a favorable C-index of 0.822 and verified via two internal validation cohorts.

Conclusions

The current study developed a nomogram predicting non-SLN metastasis for T1-2 and HR+ breast cancer with 1-3 positive SLNs after mastectomy and found that patients in the high-risk group exhibited worse relapse-free survival. The novel nomogram may further help surgeons to determine whether ALND could be omitted when 1-3 positive SLNs were observed in T1-2 and HR+ breast cancer patients.

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

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.

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

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.