Prognostic value of different cut-off levels of Ki-67 in breast cancer: a systematic review and meta-analysis of 64,196 patients

Breast Cancer Histopathology in the Age of Molecular Oncology

For more than a century, microscopic histology has been the cornerstone for cancer diagnosis, and breast carcinoma is no exception. In recent years, clinical biomarkers, gene expression profiles, and other molecular tests have shown increasing utility for identifying the key biological features that guide prognosis and treatment of breast cancer. Indeed, the most common histologic pattern-invasive ductal carcinoma of no special type-provides relatively little guidance to management beyond triggering grading, biomarker testing, and clinical staging. However, many less common histologic patterns can be recognized by trained pathologists, which in many cases can be linked to characteristic biomarker and gene expression patterns, underlying mutations, prognosis, and therapy. Herein we describe more than a dozen such histomorphologic subtypes (including lobular, metaplastic, salivary analog, and several good prognosis special types of breast cancer) in the context of their molecular and clinical features.

The Ki67 dilemma: investigating prognostic cut-offs and reproducibility for automated Ki67 scoring in breast cancer

PURPOSE

Quantification of Ki67 in breast cancer is a well-established prognostic and predictive marker, but inter-laboratory variability has hampered its clinical usefulness. This study compares the prognostic value and reproducibility of Ki67 scoring using four automated, digital image analysis (DIA) methods and two manual methods.

METHODS

The study cohort consisted of 367 patients diagnosed between 1990 and 2004, with hormone receptor positive, HER2 negative, lymph node negative breast cancer. Manual scoring of Ki67 was performed using predefined criteria. DIA Ki67 scoring was performed using QuPath and Visiopharm® platforms. Reproducibility was assessed by the intraclass correlation coefficient (ICC). ROC curve survival analysis identified optimal cutoff values in addition to recommendations by the International Ki67 Working Group and Norwegian Guidelines. Kaplan-Meier curves, log-rank test and Cox regression analysis assessed the association between Ki67 scoring and distant metastasis (DM) free survival.

RESULTS

The manual hotspot and global scoring methods showed good agreement when compared to their counterpart DIA methods (ICC > 0.780), and good to excellent agreement between different DIA hotspot scoring platforms (ICC 0.781-0.906). Different Ki67 cutoffs demonstrate significant DM-free survival (p < 0.05). DIA scoring had greater prognostic value for DM-free survival using a 14% cutoff (HR 3.054-4.077) than manual scoring (HR 2.012-2.056). The use of a single cutoff for all scoring methods affected the distribution of prediction outcomes (e.g. false positives and negatives).

CONCLUSION

This study demonstrates that DIA scoring of Ki67 is superior to manual methods, but further study is required to standardize automated, DIA scoring and definition of a clinical cut-off.

The value of the malignant subregion-based texture analysis in predicting the Ki-67 status in breast cancer

Objective

To evaluate the value of the malignant subregion-based texture analysis in predicting Ki-67 status in breast cancer.

Materials and methods

The dynamic contrast-enhanced magnetic resonance imaging data of 119 histopathologically confirmed breast cancer patients (81 patients with high Ki-67 expression status) from January 2018 to February 2023 in our hospital were retrospectively collected. According to the enhancement curve of each voxel within the tumor, three subregions were divided: washout subregion, plateau subregion, and persistent subregion. The washout subregion and the plateau subregion were merged as the malignant subregion. The texture features of the malignant subregion were extracted using Pyradiomics software for texture analysis. The differences in texture features were compared between the low and high Ki-67 expression cohorts and then the receiver operating characteristic (ROC) curve analysis to evaluate the predictive performance of texture features on Ki-67 expression. Finally, a support vector machine (SVM) classifier was constructed based on differential features to predict the expression level of Ki-67, the performance of the classifier was evaluated using ROC analysis and confirmed using 10-fold cross-validation.

Results

Through comparative analysis, 51 features exhibited significant differences between the low and high Ki-67 expression cohorts. Following feature reduction, 5 features were selected to build the SVM classifier, which achieved an area under the ROC curve (AUC) of 0.77 (0.68-0.87) for predicting the Ki-67 expression status. The accuracy, sensitivity, and specificity were 0.76, 0.80, and 0.68, respectively. The average AUC from the 10-fold cross-validation was 0.72 ± 0.14.

Conclusion

The texture features of the malignant subregion in breast cancer were potential biomarkers for predicting Ki-67 expression level in breast cancer, which might be used to precisely diagnose and guide the treatment of breast cancer.

Reliability and Variability of Ki-67 Digital Image Analysis Methods for Clinical Diagnostics in Breast Cancer

Ki-67 is a nuclear protein associated with proliferation, and a strong potential biomarker in breast cancer, but is not routinely measured in current clinical management owing to a lack of standardization. Digital image analysis (DIA) is a promising technology that could allow high-throughput analysis and standardization. There is a dearth of data on the clinical reliability as well as intra- and interalgorithmic variability of different DIA methods. In this study, we scored and compared a set of breast cancer cases in which manually counted Ki-67 has already been demonstrated to have prognostic value (n = 278) to 5 DIA methods, namely Aperio ePathology (Lieca Biosystems), Definiens Tissue Studio (Definiens AG), Qupath, an unsupervised immunohistochemical color histogram algorithm, and a deep-learning pipeline piNET. The piNET system achieved high agreement (interclass correlation coefficient: 0.850) and correlation (R = 0.85) with the reference score. The Qupath algorithm exhibited a high degree of reproducibility among all rater instances (interclass correlation coefficient: 0.889). Although piNET performed well against absolute manual counts, none of the tested DIA methods classified common Ki-67 cutoffs with high agreement or reached the clinically relevant Cohen's κ of at least 0.8. The highest agreement achieved was a Cohen's κ statistic of 0.73 for cutoffs 20% and 25% by the piNET system. The main contributors to interalgorithmic variation and poor cutoff characterization included heterogeneous tumor biology, varying algorithm implementation, and setting assignments. It appears that image segmentation is the primary explanation for semiautomated intra-algorithmic variation, which involves significant manual intervention to correct. Automated pipelines, such as piNET, may be crucial in developing robust and reproducible unbiased DIA approaches to accurately quantify Ki-67 for clinical diagnosis in the future.

Develop and Validate a Nomogram Combining Contrast-Enhanced Spectral Mammography Deep Learning with Clinical-Pathological Features to Predict Neoadjuvant Chemotherapy Response in Patients with ER-Positive/HER2-Negative Breast Cancer

RATIONALE AND OBJECTIVES

To develop and validate a nomogram that combines contrast-enhanced spectral mammography (CESM) deep learning with clinical-pathological features to predict neoadjuvant chemotherapy (NAC) response (either low Miller Payne (MP-L) grades 1-2 or high MP (MP-H) grades 3-5) in patients with ER-positive/HER2-negative breast cancer.

MATERIALS AND METHODS

In this retrospective study, 265 breast cancer patients were randomly allocated into training and test sets (used for models training and testing, respectively) at a 4:1 ratio. Deep learning models, based on the pre-trained ResNet34 model and initially fine-tuned for identifying breast cancer, were trained using low-energy and subtracted CESM images. The predicted results served as deep learning features for the deep learning-based model. Clinical-pathological features, including age, progesterone receptor (PR) status, estrogen receptor (ER) status, Ki67 expression levels, and neutrophil-to-lymphocyte ratio, were used for the clinical model. All these features contributed to the nomogram. Feature selection was performed through univariate analysis. Logistic regression models were developed and chosen using a stepwise selection method. The deep learning-based and clinical models, along with the nomogram, were evaluated using precision-recall curves, receiver operating characteristic (ROC) curves, specificity, recall, accuracy, negative predictive value, positive predictive value (PPV), balanced accuracy, F1-score, and decision curve analysis (DCA).

RESULTS

The nomogram demonstrated considerable predictive ability, with higher area under the ROC curve (0.95, P < 0.05), accuracy (0.94), specificity (0.98), PPV (0.89), and precision (0.89) compared to the deep learning-based and clinical models. In DCA, the nomogram showed substantial clinical value in assisting breast cancer treatment decisions, exhibiting a higher net benefit than the other models.

CONCLUSION

The nomogram, integrating CESM deep learning with clinical-pathological features, proved valuable for predicting NAC response in patients with ER-positive/HER2-negative breast cancer. Nomogram outperformed deep learning-based and clinical models.

Prognostic Molecular Biomarkers in Breast Cancer Lesions with Non-Mass Enhancement on MR

Clustered ring enhancement (CRE) is a new lexicon for non-mass enhancement (NME) of breast MR in the 5th BIRADS, indicating a high suspicion of malignancy. We wonder if the presence of CRE correlates with expression of prognostic molecular biomarkers of breast cancer. A total of 58 breast lesions, which MRI reported with NME, were collected between July 2013 and December 2018. The patterns of enhancement including CRE were reviewed and the pathological results with expression of molecular biomarkers were collected. The association between MRI NME, pathological, and IHC stain findings were investigated under univariate analysis. A total of 58 breast lesions were pathologically proven to have breast cancer, comprising 31 lesions with CRE and 27 lesions without CRE on breast MRI. The expression of the estrogen receptor (ER) (p = 0.017) and the progesterone receptor (PR) (p = 0.017) was significantly lower in lesions with CRE as compared with those without CRE. The expression of Ki-67 (≥25%) was significantly higher in lesions with CRE (p = 0.046). The lesions with CRE had a lower expression ratio of ER (50.71 ± 45.39% vs. 74.26 ± 33.59%, p = 0.028). Our study indicated that lesions with CRE may possess different features from those without CRE in molecular expression, bearing a more aggressive behavior.

The Role of Ki-67 in HR+/HER2- Breast Cancer: A Real-World Study of 956 Patients

Objective

This study determined the cut-off value of Ki-67 expression and discussed the interaction between Ki-67 and histological grade, further explored the prognostic role of Ki-67 in hormone receptor-positive and human epidermal growth factor receptor 2 negative (HR+/HER2-) breast cancer;.

Materials and Methods

We assessed the Ki-67 expression of 956 patients with HR+/HER2 breast cancer diagnosed in the General Hospital of Ningxia Medical University from 2015 to 2019 by immunohistochemistry (IHC), The disease-free survival (DFS) was defined as the time from postoperative to the first local recurrence, distant metastasis or death of the disease. The follow-up by means of inpatient or outpatient medical records and telephone.

Results

22.5% was used as the cut-off for low/high Ki-67 expression in HR+/HER2- breast cancer. Compared with the value of 14%, which is commonly used in clinic at present, the consistency of the two values is moderate (Kappa = 0.484, P<0.001). The expression of Ki-67 was increased with the grade. (Median: G1:10%; G2:20%; G3:40%. Mean: G1:13%; G2:23%; G3:39%, P <0.001). Survival analysis was based on all patients for a median of 51 months (24-89 months), 63 cases had recurrence or metastasis during the follow-up, which 21 cases had low expression of Ki-67 and 42 cases had high expression. The patients with Ki-67 ≥ 22.5% had a 2.969 higher risk of early recurrence and metastasis than the patients with Ki-67 < 22.5%. There were 4 cases of local recurrence, 7 cases of regional lymph node metastasis, and 52 cases of distant metastasis in all patients, the common distant metastases were bone, liver, and lung, and rare metastases were adrenal gland, bone marrow, and pericardium.

Conclusion

In HR+/HER2- breast cancer, patients with Ki-67 > 22.5% have a worse prognosis and are more likely to have early recurrence and metastasis.

A Model Combining Conventional Ultrasound Characteristics, Strain Elastography and Clinicopathological Features to Predict Ki-67 Expression in Small Breast Cancer

To establish a predictive model incorporating conventional ultrasound, strain elastography and clinicopathological features for Ki-67 expression in small breast cancer (SBC) which defined as maximum diameter less than2 cm. In this retrospective study, 165 SBC patients from our hospital were allocated to a high Ki-67 group (n = 104) and a low Ki-67 group (n = 61). Multivariate regression analysis was performed to identify independent indicators for developing predictive models. The area under the receiver operating characteristic (AUC) curve was also determined to establish the diagnostic performance of different predictive models. The corresponding sensitivities and specificities of different models at the cutoff value were compared. Conventional ultrasound parameters (spiculated margin, absence of posterior shadowing and Adler grade 2-3), strain elastic scores and clinicopathological information (HER2 positive) were significantly correlated with high expression of Ki-67 in SBC (all p < .05). Model 2, which incorporated conventional ultrasound features and strain elastic scores, yielded good diagnostic performance (AUC = 0.774) with better sensitivity than model 1, which only incorporated ultrasound characteristics (78.85%vs. 55.77%, p = .000), with specificities of 77.05% and 62.30% (p = .035), respectively. Model 3, which incorporated conventional ultrasound, strain elastography and clinicopathological features, yielded better performance (AUC = 0.853) than model 1 (AUC = 0.694) and model 2 (AUC = 0.774), and the specificity was higher than model 1 (86.89% vs. 77.05%, p = .001). The predictive model combining conventional ultrasound, strain elastic scores and clinicopathological features could improve the predictive performance of Ki-67 expression in SBC.

AI improves accuracy, agreement and efficiency of pathologists for Ki67 assessments in breast cancer

The Ki-67 proliferation index (PI) guides treatment decisions in breast cancer but suffers from poor inter-rater reproducibility. Although AI tools have been designed for Ki-67 assessment, their impact on pathologists' work remains understudied. 90 international pathologists were recruited to assess the Ki-67 PI of ten breast cancer tissue microarrays with and without AI. Accuracy, agreement, and turnaround time with and without AI were compared. Pathologists' perspectives on AI were collected. Using AI led to a significant decrease in PI error (2.1% with AI vs. 5.9% without AI, p < 0.001), better inter-rater agreement (ICC: 0.70 vs. 0.92; Krippendorff's α: 0.63 vs. 0.89; Fleiss' Kappa: 0.40 vs. 0.86), and an 11.9% overall median reduction in turnaround time. Most pathologists (84%) found the AI reliable. For Ki-67 assessments, 76% of respondents believed AI enhances accuracy, 82% said it improves consistency, and 83% trust it will improve efficiency. This study highlights AI's potential to standardize Ki-67 scoring, especially between 5 and 30% PI-a range with low PI agreement. This could pave the way for a universally accepted PI score to guide treatment decisions, emphasizing the promising role of AI integration into pathologist workflows.

An Automated Breast Volume Scanner-Based Intra- and Peritumoral Radiomics Nomogram for the Preoperative Prediction of Expression of Ki-67 in Breast Malignancy

RATIONALE AND OBJECTIVES

This study aimed to create and verify a nomogram for preoperative prediction of Ki-67 expression in breast malignancy to assist in the development of personalized treatment strategies.

MATERIALS AND METHODS

This retrospective study received approval from the institutional review board and included a cohort of 197 patients with breast malignancy who were admitted to our hospital. Ki-67 expression was divided into two groups based on a 14% threshold: low and high. A radiomics signature was built utilizing 1702 radiomics features based on an intra- and peritumoral (10 mm) regions of interest. Using multivariate logistic regression, radiomics signature, and ultrasound (US) characteristics, the nomogram was developed. To evaluate the model's calibration, clinical application, and predictive ability, decision curve analysis (DCA), the calibration curve, and the receiver operating characteristic curve were used, respectively.

RESULTS

The final nomogram included three independent predictors: tumor size (P = .037), radiomics signature (P < .001), and US-reported lymph node status (P = .018). The nomogram exhibited satisfactory performance in the training cohort, demonstrating a specificity of 0.944, a sensitivity of 0.745, and an area under the curve (AUC) of 0.905. The validation cohort recorded a specificity of 0.909, a sensitivity of 0.727, and an AUC of 0.882. The DCA showed the nomogram's clinical utility, and the calibration curve revealed a high consistency among the expected and detected values.

CONCLUSION

The nomogram used in this investigation can accurately predict Ki-67 expression in people with malignant breast tumors, helping to develop personalized treatment approaches.

Relationship of Ki-67 index in biopsies of metastatic breast cancer tissue and circulating tumor cells (CTCs) at the time of biopsy collection

BACKGROUND

The proliferation marker Ki-67 is a major pathological feature for the description of the state of disease in breast cancer. It helps to define the molecular subtype and to stratify between therapy regimens in early breast cancer and helps to assess the therapy response. Circulating tumor cells (CTCs) are a negative prognostic biomarker for progression free (PFS) and overall survival (OS) in patients with metastatic breast cancer. Therefore, the CTC count is often described as surrogate for the tumor burden. Both, decrease of Ki-67 and CTC count are considered as evidence for therapy response. The presented work analyzed the correlation between the Ki-67 indices of metastatic tissue biopsies and CTC counts in biopsy time-adjacent peripheral blood samples.

PATIENTS AND METHODS

Blood samples from 70 metastatic breast cancer patients were obtained before the start of a new line of systemic therapy. CTCs were enumerated using CellSearch® (Menarini Silicon Biosystems, Bologna, Italy) whereas intact CTCs (iCTCs) and non-intact or apoptotic CTCs (aCTCs) were distinguished using morphologic criteria. The proportion of cells expressing Ki-67 was evaluated using immunohistochemistry on biopsies of metastases obtained concurrently with CTC sampling before the start of a new line of systemic therapy.

RESULTS

65.7% of patients had a Ki-67 index of > 25%. 28.6% of patients had ≥ 5, 47.1% ≥ 1 iCTCs. 37.1% had ≥ 5, 51.4% ≥ 1 aCTCs. No correlation was shown between Ki-67 index and iCTC and aCTC count (r = 0.05 resp. r = 0.05, Spearman's correlation index). High CTC-counts did not coincide with high Ki-67 index. High Ki-67, ≥ 5 iCTCs and aCTCs are associated with poor progression free (PFS) and overall survival (OS).

CONCLUSION

CTCs and Ki-67 are independent prognostic markers in metastatic breast cancer. High Ki-67 in metastatic tumor tissue is not correlated to high iCTC or aCTC counts in peripheral blood.

Development of an interpretable machine learning model for Ki-67 prediction in breast cancer using intratumoral and peritumoral ultrasound radiomics features

Background

Traditional immunohistochemistry assessment of Ki-67 in breast cancer (BC) via core needle biopsy is invasive, inaccurate, and nonrepeatable. While machine learning (ML) provides a promising alternative, its effectiveness depends on extensive data. Although the current mainstream MRI-centered radiomics offers sufficient data, its unsuitability for repeated examinations, along with limited accessibility and an intratumoral focus, constrain the application of predictive models in evaluating Ki-67 levels.

Objective

This study aims to explore ultrasound (US) image-based radiomics, incorporating both intra- and peritumoral features, to develop an interpretable ML model for predicting Ki-67 expression in BC patients.

Methods

A retrospective analysis was conducted on 263 BC patients, divided into training and external validation cohorts. From intratumoral and peritumoral regions of interest (ROIs) in US images, 849 distinctive radiomics features per ROI were derived. These features underwent systematic selection to analyze Ki-67 expression relationships. Four ML models-logistic regression, random forests, support vector machine (SVM), and extreme gradient boosting-were formulated and internally validated to identify the optimal predictive model. External validation was executed to ascertain the robustness of the optimal model, followed by employing Shapley Additive Explanations (SHAP) to reveal the significant features of the model.

Results

Among 231 selected BC patients, 67.5% exhibited high Ki-67 expression, with consistency observed across both training and validation cohorts as well as other clinical characteristics. Of the 1698 radiomics features identified, 15 were significantly correlated with Ki-67 expression. The SVM model, utilizing combined ROI, demonstrated the highest accuracy [area under the receiver operating characteristic curve (AUROC): 0.88], making it the most suitable for predicting Ki-67 expression. External validation sustained an AUROC of 0.82, affirming the model's robustness above a 40% threshold. SHAP analysis identified five influential features from intra- and peritumoral ROIs, offering insight into individual prediction.

Conclusion

This study emphasized the potential of SVM model using radiomics features from both intra- and peritumoral US images, for predicting elevated Ki-67 levels in BC patients. The model exhibited strong performance in validations, indicating its promise as a noninvasive tool to enable personalized decision-making in BC care.

A Comprehensive Review of Computer-Aided Models for Breast Cancer Diagnosis Using Histopathology Images

Breast cancer is the second most common cancer in women who are mainly middle-aged and older. The American Cancer Society reported that the average risk of developing breast cancer sometime in their life is about 13%, and this incident rate has increased by 0.5% per year in recent years. A biopsy is done when screening tests and imaging results show suspicious breast changes. Advancements in computer-aided system capabilities and performance have fueled research using histopathology images in cancer diagnosis. Advances in machine learning and deep neural networks have tremendously increased the number of studies developing computerized detection and classification models. The dataset-dependent nature and trial-and-error approach of the deep networks' performance produced varying results in the literature. This work comprehensively reviews the studies published between 2010 and 2022 regarding commonly used public-domain datasets and methodologies used in preprocessing, segmentation, feature engineering, machine-learning approaches, classifiers, and performance metrics.

Exploring the added value of pretherapeutic MR descriptors in predicting breast cancer pathologic complete response to neoadjuvant chemotherapy

OBJECTIVES

To evaluate the association between pretreatment MRI descriptors and breast cancer (BC) pathological complete response (pCR) to neoadjuvant chemotherapy (NAC).

MATERIALS AND METHODS

Patients with BC treated by NAC with a breast MRI between 2016 and 2020 were included in this retrospective observational single-center study. MR studies were described using the standardized BI-RADS and breast edema score on T2-weighted MRI. Univariable and multivariable logistic regression analyses were performed to assess variables association with pCR according to residual cancer burden. Random forest classifiers were trained to predict pCR on a random split including 70% of the database and were validated on the remaining cases.

RESULTS

Among 129 BC, 59 (46%) achieved pCR after NAC (luminal (n = 7/37, 19%), triple negative (n = 30/55, 55%), HER2 + (n = 22/37, 59%)). Clinical and biological items associated with pCR were BC subtype (p < 0.001), T stage 0/I/II (p = 0.008), higher Ki67 (p = 0.005), and higher tumor-infiltrating lymphocytes levels (p = 0.016). Univariate analysis showed that the following MRI features, oval or round shape (p = 0.047), unifocality (p = 0.026), non-spiculated margins (p = 0.018), no associated non-mass enhancement (p = 0.024), and a lower MRI size (p = 0.031), were significantly associated with pCR. Unifocality and non-spiculated margins remained independently associated with pCR at multivariable analysis. Adding significant MRI features to clinicobiological variables in random forest classifiers significantly increased sensitivity (0.67 versus 0.62), specificity (0.69 versus 0.67), and precision (0.71 versus 0.67) for pCR prediction.

CONCLUSION

Non-spiculated margins and unifocality are independently associated with pCR and can increase models performance to predict BC response to NAC.

CLINICAL RELEVANCE STATEMENT

A multimodal approach integrating pretreatment MRI features with clinicobiological predictors, including tumor-infiltrating lymphocytes, could be employed to develop machine learning models for identifying patients at risk of non-response. This may enable consideration of alternative therapeutic strategies to optimize treatment outcomes.

KEY POINTS

• Unifocality and non-spiculated margins are independently associated with pCR at multivariable logistic regression analysis. • Breast edema score is associated with MR tumor size and TIL expression, not only in TN BC as previously reported, but also in luminal BC. • Adding significant MRI features to clinicobiological variables in machine learning classifiers significantly increased sensitivity, specificity, and precision for pCR prediction.

Topoisomerase IIα immunoexpression in feline mammary carcinomas: A correlation with Ki67 immunoexpression and the mitotic count

The aim of the study was to compare the immunohistochemical expression of topoisomerase IIα protein (Topo IIα) with Ki67 expression and mitotic count in feline mammary carcinomas (FMCs). Topo IIα is considered as a proliferation indicator as well as a molecular target of anthracycline chemotherapy. The studied material included 70 FMCs from female cats treated with mastectomy. Primary mouse monoclonal antibodies directed against Topo IIα and Ki67 were used in immunohistochemical reactions. The number of mitotic figures was counted at 400× magnification in a field of 2.37 mm2. Immunohistochemical reaction for Topo IIα occurred in cell nuclei. The Topo IIα index ranged from 6.12% to 54.60% and was positively correlated with the values of the Ki67 index (r = 0.7193) and the mitotic count (r = 0. 2858). This indicates the potential possibility of use of the immunohistochemical expression of Topo IIα to assess the rate of proliferation in FMCs. The wide range of expression of Topo IIα in individual tumorus found in the conducted studies allows us to hypothesize that its assessment could be used as a predictive marker in chemotherapy of FMCs with the use of anthracyclines. However, this requires confirmation in clinical trials.

A nomogram incorporating Ki67 to predict survival of acral melanoma

BACKGROUND

The proliferation marker Ki67 is associated with the progression and prognosis of melanoma. However, its prognostic impact on acral melanoma (AM) remains unclear.

METHODS

A total of 314 AM patients were enrolled from a cohort of 5758 patients with melanoma at Peking University Cancer Hospital between 2006 and 2018. The patients were divided into Ki67 high- and low-expressing groups using a cut-off value of 30%. The associations between Ki67 and clinicopathologic characteristics as well as survival were analyzed. Cox proportional regression analysis was used to establish a nomogram to predict the survival probabilities of AM.

RESULTS

Among 314 patients, the Ki67-high group (Ki67 ≥ 30%) included 49.4% of patients at diagnosis. Patients in the Ki67-high group had lower median melanoma-specific survival (MSS) than those in the Ki67-low group (60.7 months vs. not reached, p < 0.001). In multivariate analyses, Ki67, lymph node metastasis and primary site were independent prognostic factors for MSS. The nomogram showed that Ki67 had the fourth greatest impact on survival, following Breslow thickness, lymph node metastasis and primary site. The C-index of the nomogram was 0.765 and 0.758 in the training and validation cohort, respectively. Area under the curve values were both near 0.8 in the training and validation cohorts. Net reclassification improvement and integrated discrimination improvement demonstrated that the predictive nomogram performed better than the traditional AJCC staging system.

CONCLUSION

Ki67 expression is an independent prognostic factor for MSS in AM. A predictive model incorporating Ki67 and clinical factors was constructed to predict the prognosis of AM.

Quality Assessment of Proteins and RNA Following Storage in Archival Formalin-Fixed Paraffin-Embedded Human Breast Cancer Tissue Microarray Sections

Although the immunogenicity of formalin-fixed paraffin-embedded tissue sections can decrease during storage and transport, the exact mechanism of antigenic loss and how to prevent it are not clear. Herein, we investigated changes in the expression of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER-2), E-cadherin, and Ki-67 in human breast tissue microarray (TMA) tissue sections stored for up to 3 months in dry and wet conditions. The positive rates of ER and PR expression were minimally changed after 3 months of storage, but the Allred scores of ER and PR stored in humid conditions decreased remarkably in comparison to fresh-cut tissue. The HER-2 antigenicity and RNA integrity of breast TMA sections stored in dry conditions diminished gradually with storage time, whereas the immunoreactivity and RNA quality of HER-2 in humid conditions decreased sharply as storage length increased. The area and intensity of E-cadherin staining in tissue sections stored in dry conditions did not change significantly and were minimally changed after 3 months, respectively. In contrast, the area and intensity of E-cadherin staining in tissue sections stored in humid conditions decreased significantly as storage length increased. Finally, the Ki-67 labeling index of tissue sections stored for 3 months in dry (9% decrease) and wet (31.9% decrease) conditions was decreased in comparison to fresh sections. In conclusion, these results indicate that water is a crucial factor for protein and RNA degradation in stored tissue sections, and detailed guidelines are required in the clinic.

Applications of Artificial Intelligence in Breast Pathology

CONTEXT.—

Increasing implementation of whole slide imaging together with digital workflow and advances in computing capacity enable the use of artificial intelligence (AI) in pathology, including breast pathology. Breast pathologists often face a significant workload, with diagnosis complexity, tedious repetitive tasks, and semiquantitative evaluation of biomarkers. Recent advances in developing AI algorithms have provided promising approaches to meet the demand in breast pathology.

OBJECTIVE.—

To provide an updated review of AI in breast pathology. We examined the success and challenges of current and potential AI applications in diagnosing and grading breast carcinomas and other pathologic changes, detecting lymph node metastasis, quantifying breast cancer biomarkers, predicting prognosis and therapy response, and predicting potential molecular changes.

DATA SOURCES.—

We obtained data and information by searching and reviewing literature on AI in breast pathology from PubMed and based our own experience.

CONCLUSIONS.—

With the increasing application in breast pathology, AI not only assists in pathology diagnosis to improve accuracy and reduce pathologists' workload, but also provides new information in predicting prognosis and therapy response.

The Biomarker Ki-67: Promise, Potential, and Problems in Breast Cancer

Ki-67 is a nuclear protein serendipitously discovered by monoclonal antibody selection in the early 1980s. While it has been applied for decades in the context of breast cancer as a putative prognostic and, more recently, predictive, biomarker, even after all this time there is incomplete agreement as to the validity of the immunohistochemical assays employed for Ki-67 assessment, given possible effects of the disparate methodologies employed and possible confounding preanalytical, analytical, and interpretive variables. In this brief review, the history of Ki-67 and the problems, particularly with the analytical and interpretive variables, are highlighted through a selective review of the published literature. The contributions of the International Ki-67 Breast Cancer Working Group are highlighted, and in particular, the recommendations made by this group are reviewed. The potential of Ki-67 as a biomarker for breast cancer has not yet been fully realized, but an understanding of the power as well as the limitations of the methods of Ki-67 assessment are important if this biomarker can realize its potential.

Calcium-Sensing Receptor Expression in Breast Cancer

The calcium-sensing receptor (CaSR) plays a crucial role in maintaining the balance of calcium in the body. Altered signaling through the CaSR has been linked to the development of various tumors, such as colorectal and breast tumors. This retrospective study enrolled 79 patients who underwent surgical removal of invasive breast carcinoma of no special type (NST) to explore the expression of the CaSR in breast cancer. The patients were categorized based on age, tumor size, hormone receptor status, HER2 status, Ki-67 proliferation index, tumor grade, and TNM staging. Immunohistochemistry was conducted on core needle biopsy samples to assess CaSR expression. The results revealed a positive correlation between CaSR expression and tumor size, regardless of the tumor surrogate subtype (p = 0.001). The expression of ER exhibited a negative correlation with CaSR expression (p = 0.033). In contrast, a positive correlation was observed between CaSR expression and the presence of HER2 receptors (p = 0.002). Increased CaSR expression was significantly associated with lymph node involvement and the presence of distant metastasis (p = 0.001 and p = 0.038, respectively). CaSR values were significantly higher in the patients with increased Ki-67 (p = 0.042). Collectively, higher CaSR expression in breast cancer could suggest a poor prognosis and treatment outcome regardless of the breast cancer subtype.

Tumor-infiltrating lymphocytes provides recent survival information for early-stage HER2-low-positive breast cancer: a large cohort retrospective study

Purpose

It has been reported that breast cancer (BC) with low expression of human epidermal growth factor receptor 2 (HER2) might be a distinct subtype of BC. However, the prognostic effect of low HER2 expression on BC patients remains controversial. We aim to conduct this single-institution retrospective analysis to assess HER2-low-positive BC outcomes in Chinese women and the prognostic role of TILs in HER2-low-positive early-stage BC.

Method

We retrospectively enrolled 1,763 BC patients treated in a single institution from 2017 to 2018. TILs are regarded as continuous variables and are divided into low TILs (≤10%) and high TILs (>10%) for statistical analysis. Univariate and multivariable Cox proportional hazards regression models were used to test the associations between TILs and disease-free survival (DFS) with adjustment for clinicopathologic characteristics.

Result

High TIL levels (>10%) were associated with tumor size (>2 cm, p = 0.042), age at diagnosis (p = 0.005), Ki-67 index (>25%; p <0.001), HR (hormone receptor) status (positive, p <0.001), advanced pathological stage (p = 0.043), subtype (p <0.001), and HER2 status (p <0.001). The Kaplan-Meier analysis indicated that no significant difference in DFS (p = 0.83) could be found between HER2-positive, HER2-low-positive, and HER2-0 BC. The DFS of HER2-low-positive BC and HER2-nonamplified BC with high levels of TILs was statistically better than that of patients with low levels of TILs (p = 0.015; p = 0.047). In HER2-low-positive BC patients with high TIL levels (>10%), DFS was significantly improved in both the univariate (HR = 0.44, 95% CI 0.22-0.87, P = 0.018) and multivariate (HR = 0.47, 95% CI 0.23-0.95, P = 0.035) Cox models. For further subgroup analysis, HR (+)/HER2-low-positive BC with high TIL (>10%) levels was associated with improved DFS in both the univariate (HR = 0.41, 95% CI 0.19-0.90, P = 0.025) and multivariate (HR = 0.42, 95% CI 0.19-0.93, P = 0.032) Cox models. The HR (-)/HER2-0 BC with high TIL (>10%) level was not statistically significant in the univariate Cox model, but it was statistically significant in the multivariate (HR = 0.16, 95% CI 0.28-0.96, P = 0.045) Cox model.

Conclusion

Among early-stage BC, no significant survival difference could be found between the HER2-positive, HER2-low-positive, and HER2-0 cohorts. High levels of TILs were significantly associated with improved DFS in HER2-low-positive patients, especially in the HR (+)/HER2-low-positive subtype.

Ki67 in Breast Cancer Assay: An Ad Hoc Testing Recommendation from the Canadian Association of Pathologists Task Force

Ki67, a marker of cellular proliferation, is commonly assessed in surgical pathology laboratories. In breast cancer, Ki67 is an established prognostic factor with higher levels associated with worse long-term survival. However, Ki67 IHC is considered of limited clinical use in breast cancer management largely due to issues related to standardization and reproducibility of scoring across laboratories. Recently, both the American Food and Drug Administration (FDA) and Health Canada have approved the use of abemaciclib (CDK4/6 inhibitor) for patients with HR+/HER2: high-risk early breast cancers in the adjuvant setting. Health Canada and the FDA have included a Ki67 proliferation index of ≥20% in the drug monograph. The approval was based on the results from monarchE, a phase III clinical trial in early-stage chemotherapy-naïve, HR+, HER2 negative patients at high risk of early recurrence. The study has shown significant improvement in invasive disease-free survival (IDFS) with abemaciclib when combined with adjuvant endocrine therapy at two years. Therefore, there is an urgent need by the breast pathology and medical oncology community in Canada to establish national guideline recommendations for Ki67 testing as a predictive marker in the context of abemaciclib therapy consideration. The following recommendations are based on previous IKWG publications, available guidance from the monarchE trial and expert opinions. The current recommendations are by no means final or comprehensive, and their goal is to focus on its role in the selection of patients for abemaciclib therapy. The aim of this document is to guide Canadian pathologists on how to test and report Ki67 in invasive breast cancer. Testing should be performed upon a medical oncologist’s request only. Testing must be performed on treatment-naïve tumor tissue. Testing on the core biopsy is preferred; however, a well-fixed resection specimen is an acceptable alternative. Adhering to ASCO/CAP fixation guidelines for breast biomarkers is advised. Readout training is strongly recommended. Visual counting methods, other than eyeballing, should be used, with global rather than hot spot assessment preferred. Counting 100 cells in at least four areas of the tumor is recommended. The Ki67 scoring app developed to assist pathologists with scoring Ki67 proposed by the IKWG, available for free download, may be used. Automated image analysis is very promising, and laboratories with such technology are encouraged to use it as an adjunct to visual counting. A score of <5 or >30 is more robust. The task force recommends that the results are best expressed as a continuous variable. The appropriate antibody clone and staining protocols to be used may take time to address. For the time being, the task force recommends having tonsils/+pancreas on-slide control and enrollment in at least one national/international EQA program. Analytical validation remains a pending goal. Until the data become available, using local ki67 protocols is acceptable. The task force recommends participation in upcoming calibration and technical validation initiatives.

Immunohistochemical markers of prognosis in adult granulosa cell tumors of the ovary - a review

BACKGROUND

Granulosa cell tumors (GCT) are rare malignant ovarian tumors. The two subtypes, adult and juvenile granulosa cell tumors, differ in clinical and molecular characteristics. GCT are low-malignant tumors and are generally associated with favorable prognosis. However, relapses are common even years and decades after diagnosis. Prognostic and predictive factors are difficult to assess in this rare tumor entity. The purpose of this review is to provide a comprehensive overview of the current state of knowledge on prognostic markers of GCT to identify patients with a high risk of recurrence.

METHODS

Systematic research for adult ovarian granulosa cell tumors and prognosis revealed n = 409 English full text results from 1965 to 2021. Of these articles, n = 35 were considered for this review after title and abstract screening and topic-specific matching. A specific search for pathologic markers with prognostic relevance for GCT identified n = 19 articles that were added to this review.

RESULTS

FOXL2 mutation and FOXL2 mRNA were inverse and immunohistochemical (IHC) expression of CD56, GATA-4 and SMAD3 was associated with reduced prognosis. IHC analysis of estrogen receptor, Anti-Mullerian hormone (AMH) and inhibin was not associated with prognosis for GCT. Analyses of mitotic rate, Ki-67, p53, β-catenin and HER2 revealed inconsistent results.

Risk of Recurrence in Patients with HER2+ Early-Stage Breast Cancer: Literature Analysis of Patient and Disease Characteristics

Human epidermal growth factor receptor 2 (HER2) overexpression occurs in 15% to 20% of patients with early-stage breast cancers (EBCs). Without HER2-targeted therapy, 30% to 50% of patients relapse within 10 years, many developing incurable metastatic disease. This literature review was designed to identify and validate patient- and disease-related factors associated with recurrence in patients with HER2+ EBC. Peer-reviewed primary research articles and congress abstracts were identified by searching MEDLINE. Articles published in English from 2019 to 2022 were included to identify contemporary treatment options. Results were analyzed for the relationship between risk factors and surrogates of HER2+ EBC recurrence to determine how identified risk factors affected HER2+ EBC recurrence. Sixty-one articles and 65 abstracts that assessed age at diagnosis, body mass index (BMI), tumor size at diagnosis, hormone receptor (HR) status, pathologic complete response (pCR) status, and biomarkers were analyzed. We confirmed the results of previously published reviews reporting residual cancer burden >0, non-pCR, and fewer tumor-infiltrating lymphocytes (TILs) as risk factors of recurrence. HR status remained an important risk factor for recurrence, with HER2+/HR+ disease more likely to recur. Two or more positive lymph nodes, higher BMI, larger primary tumor size, and low Ki67 were more commonly associated with HER2+ EBC recurrence. The identification of patient and disease factors frequently associated with HER2+ EBC recurrence in the literature provides insight into potential recurrence risk factors. Further investigation into the risk factors identified in this review could lead to improved treatments for patients at high risk for HER2+ EBC recurrence.

Expression, assessment and significance of Ki67 expression in breast cancer: an update

Ki67 expression is one of the most important and cost-effective surrogate markers to assess for tumour cell proliferation in breast cancer (BC). The Ki67 labelling index has prognostic and predictive value in patients with early-stage BC, particularly in the hormone receptor-positive, HER2 (human epidermal growth factor receptor 2)-negative (luminal) tumours. However, many challenges exist in using Ki67 in routine clinical practice and it is still not universally used in the clinical setting. Addressing these challenges can potentially improve the clinical utility of Ki67 in BC. In this article, we review the function, immunohistochemical (IHC) expression, methods for scoring and interpretation of results as well as address several challenges of Ki67 assessment in BC. The prodigious attention associated with use of Ki67 IHC as a prognostic marker in BC resulted in high expectation and overestimation of its performance. However, the realisation of some pitfalls and disadvantages, which are expected with any similar markers, resulted in an increasing criticism of its clinical use. It is time to consider a pragmatic approach and weigh the benefits against the weaknesses and identify factors to achieve the best clinical utility. Here we highlight the strengths of its performance and provide some insights to overcome the existing challenges.

Prognostic analysis of three forms of Ki-67 in patients with breast cancer with non-pathological complete response before and after neoadjuvant systemic treatment

BACKGROUND

Patients who do not achieve a pathological complete response (pCR) after neoadjuvant systemic treatment (NST) have a significantly worse prognosis. A reliable predictor of prognosis is required to further subdivide non-pCR patients. To date, the prognostic role in terms of disease-free survival (DFS) between the terminal index of Ki-67 after surgery (Ki-67_T ) and the combination of the baseline Ki-67 at biopsy before NST (Ki-67_B ) and the percentage change in Ki-67 before and after NST (Ki-67_C ) has not been compared.

AIM

This study aimed to explore the most useful form or combination of Ki-67 that can provide prognostic information to non-pCR patients.

PATIENTS AND METHODS

We retrospectively reviewed 499 patients who were diagnosed with inoperable breast cancer between August 2013 and December 2020 and received NST with anthracycline plus taxane.

RESULTS

Among all the patients, 335 did not achieve pCR (with a follow-up period of ≥1 year). The median follow-up duration was 36 months. The optimal cutoff value of Ki-67_C to predict a DFS was 30%. A significantly worse DFS was observed in patients with a low Ki-67_C (p < 0.001). In addition, the exploratory subgroup analysis showed relatively good internal consistency. Ki-67_C and Ki-67_T were considered as independent risk factors for DFS (both p < 0.001). The forecasting model combining Ki-67_B and Ki-67_C showed a significantly higher area under the curve at years 3 and 5 than Ki-67_T (p = 0.029 and p = 0.022, respectively).

CONCLUSIONS

Ki-67_C and Ki-67_T were good independent predictors of DFS, whereas Ki-67_B was a slightly inferior predictor. The combination of Ki-67_B and Ki-67_C is superior to Ki-67_T for predicting DFS, especially at longer follow-ups. Regarding clinical application, this combination could be used as a novel indicator for predicting DFS to more clearly identify high-risk patients.

Expression of substance P, neurokinin 1 receptor, Ki-67 and pyruvate kinase M2 in hormone receptor negative breast cancer and evaluation of impact on overall survival

BACKGROUND

Chronic inflammation is a hallmark of cancer, and it can be stimulated by many factors. Substance P (SP), through binding to neurokinin 1 receptor (NK1R), and pyruvate kinase M2 (PKM2) play critical roles in cancer development and progression via modulating the tumor microenvironment. This study aimed to investigate the prognostic significance of SP and PKM2 in combination with NK1R and Ki-67 in hormone receptor negative (HR-ve) breast cancer.

METHODS

Immunohistochemical expression levels of SP, NK1R, PKM2, and Ki-67 were measured in 144 paraffin-embedded breast cancer tissues (77 h -ve and 67 h + ve). SP, NK1R, and PKM2 were scored semiquantitatively, while Ki-67 was obtained by the percentage of total number of tumor cells with nuclear staining. The optimal cutoff value for SP, NK1R, PKM2, and Ki-67 were assessed by Cutoff Finder.

RESULTS

High SP expression in HR -ve breast cancer was associated with TNM stage (p = 0.020), pT stage (p = 0.035), pN stage (p = 0.002), axillary lymph node metastasis (p = 0.003), and NK1R expression level (p = 0.010). In HR + ve breast cancer, SP expression was associated with HER2 status (p = 0.001) and PKM2 expression level (p = 0.012). Regarding PKM2 expression level, it significantly associated with HER2 status (p = 0.001) and history of DCIS (p = 0.046) in HR-ve tumors, and with HER2 status (p < 0.001) and SP expression level (p = 0.012) in HR + ve tumors. Survival analysis revealed that high SP level negatively impacted overall survival in HR-ve tumors that had low NK1R level (p = 0.021). Moreover, high SP negatively impacted overall survival in HR-ve tumors that had low Ki-67 level (p = 0.005). High PKM2 negatively impacted overall survival in HR-ve cases with low SP (p = 0.047).

CONCLUSION

Combined expression levels of SP with NK1R or Ki-67, and PKM2 with SP could be used to predict survival in breast cancer patients with HR-ve tumors. Our findings suggest a role of SP/NK1R pathway and PKM2 in HR-ve breast cancer pathogenesis which should be further investigated to unveil the underlying molecular mechanisms.

Prediction of Ki-67 of Invasive Ductal Breast Cancer Based on Ultrasound Radiomics Nomogram

PURPOSE

The objective of this research was to develop and validate an ultrasound-based radiomics nomogram for the pre-operative assessment of Ki-67 in breast cancer (BC).

MATERIALS AND METHODS

From December 2016 to December 2018, 515 patients with invasive ductal breast cancer who received two-dimensional (2D) ultrasound and Ki-67 examination were studied and analyzed retrospectively. The dataset was distributed at random into a training cohort (n = 360) and a test cohort (n = 155) in the ratio of 7:3. Each tumor region of interest was defined based on 2D ultrasound images and radiomics features were extracted. ANOVA, maximum correlation minimum redundancy (mRMR) algorithm, and minimum absolute shrinkage and selection operator (LASSO) were performed to pick features, and independent clinical predictors were integrated with radscore to construct the nomogram for predicting Ki-67 index by univariate and multivariate logistic regression analysis. The performance and utility of the models were evaluated by plotting receiver operating characteristic (ROC) curves, decision curve analysis (DCA), and calibration curves.

RESULTS

In the testing cohort, the area under the receiver characteristic curve (AUC) of the nomogram was 0.770 (95% confidence interval, 0.690-0.860). In both cohorts, the nomogram outperformed both the clinical model and the radiomics model (P < .05 according to the DeLong test). The analysis of DCA proved that the model has clinical utility.

CONCLUSIONS

The nomogram based on 2D ultrasound images offered an approach for predicting Ki-67 in BC.

A review of prognostic and predictive biomarkers in breast cancer

Breast cancer (BC) is a common cancer all over the world that affects women. BC is one of the leading causes of cancer mortality in women, which today has decreased with the advancement of technology and new diagnostic and therapeutic methods. BCs are histologically divided into in situ and invasive carcinoma, and both of them can be divided into ductal and lobular. The main function after the diagnosis of invasive breast cancer is which patient should use chemotherapy, which patient should receive adjuvant therapy, and which should not. If the decision is for adjuvant therapy, the next challenge is to identify the most appropriate treatment or combination of treatments for a particular patient. Addressing the first challenge can be helped by prognostic biomarkers, while addressing the second challenge can be done by predictive biomarkers. Among the molecular markers related to BC, ER, PR, HER2, and the Mib1/Ki-67 proliferation index are the most significant ones and are tightly confirmed in the standard care of all primary, recurrent, and metastatic BC patients. CEA and CA-15-3 antigens are the most valuable markers of serum tumors in BC patients. Determining the series of these markers helps monitor response to the treatment and early detection of recurrence or metastasis. miRNAs have been demonstrated to be intricate in mammary gland growth, proliferation, and formation of BC known to be incriminated in BC biology. By combining established prognostic factors with valid prognostic/predicted biomarkers, we can start the journey to personalized treatment for every recently diagnosed BC patient.

The Evolution of Ki-67 and Breast Carcinoma: Past Observations, Present Directions, and Future Considerations

The 1983 discovery of a mouse monoclonal antibody-the Ki-67 antibody-that recognized a nuclear antigen present only in proliferating cells represented a seminal discovery for the pathologic assessment of cellular proliferation in breast cancer and other solid tumors. Cellular proliferation is a central determinant of prognosis and response to cytotoxic chemotherapy in patients with breast cancer, and since the discovery of the Ki-67 antibody, Ki-67 has evolved as an important biomarker with both prognostic and predictive potential in breast cancer. Although there is universal recognition among the international guideline recommendations of the value of Ki-67 in breast cancer, recommendations for the actual use of Ki-67 assays in the prognostic and predictive evaluation of breast cancer remain mixed, primarily due to the lack of assay standardization and inconsistent inter-observer and inter-laboratory reproducibility. The treatment of high-risk ER-positive/human epidermal growth factor receptor-2 (HER2) negative breast cancer with the recently FDA-approved drug abemaciclib relies on a quantitative assessment of Ki-67 expression in the treatment decision algorithm. This further reinforces the urgent need for standardization of Ki-67 antibody selection and staining interpretation, which will hopefully lead to multidisciplinary consensus on the use of Ki-67 as a prognostic and predictive marker in breast cancer. The goals of this review are to highlight the historical evolution of Ki-67 in breast cancer, summarize the present literature on Ki-67 in breast cancer, and discuss the evolving literature on the use of Ki-67 as a companion diagnostic biomarker in breast cancer, with consideration for the necessary changes required across pathology practices to help increase the reliability and widespread adoption of Ki-67 as a prognostic and predictive marker for breast cancer in clinical practice.

Clinical significance and prognostic value of receptor conversion after neoadjuvant chemotherapy in breast cancer patients

The hormone receptor (HR) status and human epidermal growth hormone receptor 2 (HER2) status of patients with breast cancer may change following neoadjuvant chemotherapy (NAC). We retrospectively analyzed the clinical data of 294 patients with stage II/III breast cancer to evaluate the clinical significance and prognostic value of receptor transformation after NAC in breast cancer patients. Pathological complete response after NAC was achieved in 10.7% of patients. HR, estrogen receptor (ER), progesterone receptor (PR), HER2, and Ki-67 conversion rates were 9.2%, 6.5%, 13.0%, 4.4%, and 33.7%, respectively. Patients with stable HR (P = 0.01) and HER2 (P = 0.048) expression had more favorable overall survival (OS). Low or reduced Ki-67 expression was associated with better disease-free survival (DFS) (P < 0.001) and OS (P < 0.01). Multivariate analysis showed that the number of lymph nodes after NAC, HR conversion, and radiotherapy were independent prognostic factors for overall survival. HR conversion implied a higher risk of death [hazard ratio, 2.56 (95% confidence interval: 1.19-5.51); P = 0.016]. Patients with HR conversion after NAC who received endocrine therapy had better DFS (P = 0.674) and OS (P = 0.363) than those who did not receive endocrine therapy, even if the HR changed from positive to negative. In conclusion, pathological testing should be performed before and after NAC, and even patients with HR conversion after NAC might benefit from endocrine therapy.

Prognostic impact of 18F-FDG PET/CT in pathologic stage II invasive ductal carcinoma of the breast: re-illuminating the value of PET/CT in intermediate-risk breast cancer

BACKGROUND

The aim of this study is to investigate the impact of ¹⁸F-FDG PET/CT on prognosis of stage II invasive ductal carcinoma (IDC) of the breast primarily treated with surgery.

METHODS

The clinical records of 297 consecutive IDC with preoperative PET/CT and pathologically staged II in surgery from 2013 to 2017 were retrospectively reviewed. The maximum standardized uptake value (SUVmax), peak standardized uptake value (SUVpeak), tumor-to-liver ratio (TLR), and metabolic tumor volume (MTV) were measured. Association of clinicopathologic factors (age, T stage, N stage, AJCC pathologic stage of IIA or IIB, pathologic prognostic stage, grade, hormonal receptor status, HER2 status, Ki-67, and adjuvant therapy) and PET parameters with DFS was assessed using the Cox proportional hazards model.

RESULTS

There were 35 recurrences and 10 deaths at a median follow-up of 49 months (range 0.8 ~ 87.3). All PET parameters were significantly associated with DFS in univariate analysis but in multivariate analysis, SUVpeak was the only factor significantly associated with DFS (hazard ratio 2.58, 95% confidence interval 1.29-5.15, P = 0.007). In cohorts with higher values of SUVpeak or TLR, patients who received adjuvant chemotherapy had significantly superior DFS.

CONCLUSION

Metabolic parameters derived from preoperative PET/CT was significantly associated with recurrence in stage II IDC primarily treated with surgery. PET/CT can be a powerful prognostic tool in conjunction with novel staging systems and current biomarkers for patients undergoing contemporary therapy. Our results urge to reconsider the currently underestimated value of PET/CT confined to diagnostic aspect and to newly recognize its prognostic impact in these intermediate-risk breast cancer.

Correlation between the expression of Ki67 and histopathological grade, tumor size, disease-free survival, and overall survival among breast cancer patients

INTRODUCTION

Identifying Ki67, a monoclonal antibody that recognizes proliferating cells, is important for defining the level of proliferative activity among patients with breast cancer. The purpose of our study was to evaluate the correlation between Ki67's expression and histopathological grade, tumor size, disease-free survival (DFS), and overall survival (OS) among breast cancer patients.

METHODS

Our retrospective cohort study involved examining 114 patients with breast cancer at our institution from January 2018 to December 2019. Participants were retrospectively followed to determine the progression of their disease, and their 2-year progress was examined with survival analysis, especially regarding whether they had postoperative relapse (i.e., DFS) or had died since being diagnosed (i.e., OS). The data were processed with a chi-square test and Kaplan-Meier test, with significance set at p < 0.05.

RESULT

The overexpression of Ki67 correlated significantly with histopathological grade (p = 0.001), tumor size (p = 0.001), DFS (p = 0.001), and OS (p = 0.003).

CONCLUSION

Ki67's overexpression is significantly correlated with the tumor size, DFS, and OS of patients with breast cancer.

Lipidomics-based tissue heterogeneity in specimens of luminal breast cancer revealed by clustering analysis of mass spectrometry imaging: A preliminary study

Cancer tissues reflect a greater number of pathological characteristics of cancer compared to cancer cells, so the evaluation of cancer tissues can be effective in determining cancer treatment strategies. Mass spectrometry imaging (MSI) can evaluate cancer tissues and even identify molecules while preserving spatial information. Cluster analysis of cancer tissues' MSI data is currently used to evaluate the phenotype heterogeneity of the tissues. Interestingly, it has been reported that phenotype heterogeneity does not always coincide with genotype heterogeneity in HER2-positive breast cancer. We thus investigated the phenotype heterogeneity of luminal breast cancer, which is generally known to have few gene mutations. As a result, we identified phenotype heterogeneity based on lipidomics in luminal breast cancer tissues. Clusters were composed of phosphatidylcholine (PC), triglycerides (TG), phosphatidylethanolamine, sphingomyelin, and ceramide. It was found that mainly the proportion of PC and TG correlated with the proportion of cancer and stroma on HE images. Furthermore, the number of carbons in these lipid class varied from cluster to cluster. This was consistent with the fact that enzymes that synthesize long-chain fatty acids are increased through cancer metabolism. It was then thought that clusters containing PCs with high carbon counts might reflect high malignancy. These results indicate that lipidomics-based phenotype heterogeneity could potentially be used to classify cancer for which genetic analysis alone is insufficient for classification.

Is there a potential biomarker in distinguishing invasive breast carcinomas with elevated Ki-67 levels among 2D-SWE, SMI, and 18F-FDG PET-CT/MRI-derived parameters?: A single-center data

PURPOSE

To investigate the strength of quantitative imaging and metabolic parameters in differentiating invasive breast carcinomas with elevated Ki-67 levels.

MATERIALS AND METHODS

A total of 123 patients with 129 breast lesions confirmed as invasive breast carcinoma underwent shear wave elastography (SWE), superb microvascular imaging (SMI) and positron emission tomography (PET)/CT or MRI. Adler's grade (classifying the microvascularity into four types) and Vascular Index (VI) was obtained by SMI as microvascular parameters. In addition, the stiffness value (E_mean ) was evaluated in kilopascal by SWE. The average of consecutive measurements was recorded as mean VI and mean E_mean . PET scan parameters were obtained as SUV_max and SUL_peak . Lesions were divided into two groups according to the Ki-67 expression, low as ≤ 14 and high as >14.

RESULTS

Adler's grading was the most correlated imaging parameter with high Ki-67 expression (p < 0.05), while VI and E_mean had poor correlation (p > 0.05). SUV_max and SUL_peak indicated a significant linear correlation with Ki-67 but a moderate correlation with the high levels of Ki-67 (p < 0,001). The sensitivity of VI, E_mean , SUV_max and SUL_peak was 64.6%, 66.7%, 65.7%, and 66.7% when the cut-off point was set to 5.25, 102.5, 6.59, and 2.63, respectively. SUV_max had the highest AUC value of 0.740, according to the ROC curve analysis.

CONCLUSIONS

Our results suggest that the quantitative parameters obtained by advanced imaging methods may be useful in predicting the high proliferation in invasive breast carcinomas. But none of them is eligible to be used as an independent biomarker in distinguishing aggressive behavior. Nevertheless, as a noninvasive method, visual assessment of microvascular morphology using SMI increases the prognostic efficiency in invasive breast carcinomas.

Correlations between serum lipid and Ki-67 levels in different breast cancer molecular subcategories

Breast cancer has the highest incidence rate among all cancer types worldwide, seriously threatening women's health. The present retrospective study explored differences in serum lipid contents in different breast cancer (BC) subcategories and their correlation with Ki-67 expression levels in patients with invasive BC with the aim of identifying novel diagnostic and prognostic indicators for personalized BC treatment. The study included 170 patients diagnosed with BC who were diagnosed with invasive BC by postoperative pathological examination. Data on patient age, body mass index and menopausal status were collected, in addition to estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2 (HER2) and antigen Ki-67 expression levels and pathological tumor type. Preoperative circulating lipid levels, specifically the levels of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglycerides (TG) and apolipoproteins A1 (ApoA1) and B (ApoB) were also obtained. Molecular subcategories of BC were grouped based on their immunohistochemistry. Differences in serum lipid levels between the groups were assessed, and correlations between serum lipid and Ki-67 expression levels were explored. While TC, LDL-C, HDL-C and ApoA1 levels differed significantly among molecular subcategories. TG and ApoB levels did not. Circulating TC and LDL-C levels were considerably higher in patients with triple-negative BC (TNBC) and HER2-positive [hormone receptor (HR)-negative] BC than in those with luminal A and B (HER2-negative) BC. Serum HDL-C levels were significantly diminished in the TNBC and HER2-positive (HR-negative) groups compared with the luminal A and B (HER2-negative) groups. ApoA1 levels were significantly reduced in cases of TNBC and HER2-positive (HR-negative) BC compared with luminal A and B BC. Ki-67 expression levels were positively correlated with circulating TC and LDL-C levels and inversely correlated with circulating HDL-C and ApoA1 levels but exhibited no correlation with serum ApoB and TG levels. The results indicate that elevated TC and LDL-C levels and diminished HDL-C and ApoA1 levels were high-risk factors in patients with TNBC and HER2-positive (HR-negative) BC, but not patients with luminal subcategories of BC. Abnormal serum lipid levels were correlated with Ki-67 expression levels, with elevated circulating TC and LDL-C levels and reduced circulating HDL-C and ApoA1 levels indicating a poor prognosis in patients with BC.

Integration of ultrasound radiomics features and clinical factors: A nomogram model for identifying the Ki-67 status in patients with breast carcinoma

Objective

The aim of this study was to develop and validate an ultrasound-based radiomics nomogram model by integrating the clinical risk factors and radiomics score (Rad-Score) to predict the Ki-67 status in patients with breast carcinoma.

Methods

Ultrasound images of 284 patients (196 high Ki-67 expression and 88 low Ki-67 expression) were retrospectively analyzed, of which 198 patients belonged to the training set and 86 patients to the test set. The region of interest of tumor was delineated, and the radiomics features were extracted. Radiomics features underwent dimensionality reduction analysis by using the independent sample t test and least absolute shrinkage and selection operator (LASSO) algorithm. The support vector machine (SVM), logistic regression (LR), decision tree (DT), random forest (RF), naive Bayes (NB) and XGBoost (XGB) machine learning classifiers were trained to establish prediction model based on the selected features. The classifier with the highest AUC value was selected to convert the output of the results into the Rad-Score and was regarded as Rad-Score model. In addition, the logistic regression method was used to integrate Rad-Score and clinical risk factors to generate the nomogram model. The leave group out cross-validation (LGOCV) method was performed 200 times to verify the reliability and stability of the nomogram model.

Results

Six classifier models were established based on the 15 non-zero coefficient features. Among them, the LR classifier achieved the best performance in the test set, with the area under the receiver operating characteristic curve (AUC) value of 0.786, and was obtained as the Rad-Score model, while the XGB performed the worst (AUC, 0.615). In multivariate analysis, independent risk factor for high Ki-67 status was age (odds ratio [OR] = 0.97, p = 0.04). The nomogram model based on the age and Rad-Score had a slightly higher AUC than that of Rad-Score model (AUC, 0.808 vs. 0.798) in the test set, but no statistical difference (p = 0.144, DeLong test). The LGOCV yielded a median AUC of 0.793 in the test set.

Conclusions

This study proposed a convenient, clinically useful ultrasound radiomics nomogram model that can be used for the preoperative individualized prediction of the Ki-67 status in patients with BC.

Ki-67 Index Provides Long-Term Survival Information for Early-Stage HER2-Low-Positive Breast Cancer: A Single-Institute Retrospective Analysis

Aim

It has been reported that more than half of breast cancer (BC) could be identified as HER2-low-positive, which might be a distinct subtype. But the results are controversial. We aim to compare the survival outcomes between HER2-low-positive and HER2-0 BC with Asian women based on HR status or Ki-67 index.

Methods

Between January 2009 and December 2017, HER2-nonamplified BC in our single institute was identified. Patients were classified as HER2-low and HER2-0 cohort. Clinical characteristics were compared between these two groups and survival outcomes were calculated by the Kaplan–Meier method. We also performed subgroup analysis according to Ki-67 index and hormone-receptor (HR) status.

Results

Of the 2,230 included patients, 536 presented with HER2-0, and 1,694 with HER2-low positive. After a median follow-up of 85 months (range: 1–152 months), the 8-year OS, BCSS, and RFS of the overall cohort were 91%, 95%, and 89%, respectively. In comparison with the HER2-0 cohort, majority of HER2-low-expression BC concurrently presented with HR positive (82.3% vs. 69%, P < 0.001). There was no significant survival difference between the two groups in terms of OS, BCSS, and RFS (all p > 0.05). We then performed subgroup analysis according to HR status and Ki-67 index (<14% vs. ≥14%). Our results indicated that there was no significant survival difference between HER2-low-positive and HER2-0 tumors regardless of HR status (p > 0.05), while OS (p=0.026) and BCSS (p=0.052) of HER2-0 BC with high Ki-67 index were significantly poorer than that of HER2-low positive with high Ki-67, but not for RFS (p=0.17).

Conclusion

Among early stage HER2-nonamplified BC, no significant survival difference could be found between HER2-low positive and HER2-0 cohort regardless of HR status. Survival outcomes of HER2-low positive with high Ki-67 seem to be poorer than that of HER2-0 tumors with high Ki-67 index.

Analysis of the Influencing Factors of Sentinel Lymph Node Metastasis in Breast Cancer

Objective

To analyze and discuss the influencing factors of sentinel lymph node metastasis in breast cancer.

Methods

A total of 469 breast cancer patients admitted in the Department of Pathology of Guangdong Women and Children Hospital from October 2016 to December 2021 were retrospectively analyzed. The general information, immunohistochemical expression, tumor molecular subtype, tumor size, histological grade, pathological type, and tumor location were collected and the relationship with sentinel lymph node metastasis was analyzed.

Results

For patients with different age, Ki-67 and Human epidermal growth factor receptor-2 (HER-2) immunohistochemical expression level (invasive cancer), molecular subtype (invasive cancer), tumor size, histological grade (invasive cancer) and pathological type. The results of multivariate logistic regression analysis showed that the age was less than or equal to 40 years; the molecular subtype was Luminal B and HER-2 overexpression (invasive cancer); tumor was larger; the histological grade (invasive cancer) was higher; the pathological type was invasive carcinoma, there were independent risk factors for sentinel lymph node metastasis in breast cancer. The sentinel lymph node metastasis rates of invasive lobular carcinoma, invasive micropapillary carcinoma, and metaplastic carcinoma (all met the criteria for squamous cell carcinoma and histological grade III) were higher than 50% in special invasive carcinomas.

Conclusion

Age, expression level of Ki 67 and HER-2, molecular typing, tumor volume and histological grade are all high-risk factors related to sentinel lymph node metastasis of breast cancer. When one or more of the above factors are involved in an examination, pathologists should be more cautious in making a sentinel lymph node frozen diagnosis. By standardizing the sampling and increasing the number of frozen sections (slicing more frozen tissue layers), the section quality can be improved. This may be conducive to reducing the false negative rate and reducing the pain and risk of secondary surgery.

Cancer chemotherapy: insights into cellular and tumor microenvironmental mechanisms of action

Chemotherapy has historically been the mainstay of cancer treatment, but our understanding of what drives a successful therapeutic response remains limited. The diverse response of cancer patients to chemotherapy has been attributed principally to differences in the proliferation rate of the tumor cells, but there is actually very little experimental data supporting this hypothesis. Instead, other mechanisms at the cellular level and the composition of the tumor microenvironment appear to drive chemotherapy sensitivity. In particular, the immune system is a critical determinant of chemotherapy response with the depletion or knock-out of key immune cell populations or immunological mediators completely abrogating the benefits of chemotherapy in pre-clinical models. In this perspective, we review the literature regarding the known mechanisms of action of cytotoxic chemotherapy agents and the determinants of response to chemotherapy from the level of individual cells to the composition of the tumor microenvironment. We then summarize current work toward the development of dynamic biomarkers for response and propose a model for a chemotherapy sensitive tumor microenvironment.

Novel Signatures Based on the Lymphocyte-to-C-Reactive Protein Ratio Predict the Prognosis of Patients with Early Breast Cancer: A Retrospective Study

Background

The value of the lymphocyte-to-C-reactive protein (CRP) ratio (LCR) in early breast cancer (BC) is unclear. We explored the correlation between the LCR and survival of patients with early BC and established effective LCR-based prognostic signatures for predicting prognosis.

Methods

In this retrospective study, we randomized 623 patients with early-stage BC diagnosed in December 2010 to October 2012 at the Sun Yat-sen University Cancer Center to training and verification datasets. The median follow-up of all patients was 109 months. The survival differences were calculated by Kaplan–Meier method using the Log rank test. For overall survival (OS) and disease-free survival (DFS), the independent factors in the training dataset were identified using univariate and multivariate Cox analyses, in which two-tailed P-values < 0.05 were considered statistically significant. Based on this, we respectively constructed novel signatures for survival prediction and validated the efficiency of signatures through the concordance index (C-index), calibration and receiver operating characteristic (ROC) curves in both datasets.

Results

The LCR, lymphatic vessel invasion (LVI), progesterone receptor (PR) status, and Ki67 index were independent prognostic factors of OS. And the LCR and LVI are associated to DFS too. High LCR was associated with better OS and DFS. We constructed the prediction signatures based on those independent prognostic factors and calculated the risk scores. Patients in the training dataset with higher risk scores had significantly worse prognosis (P < 0.001). The signature had excellent discrimination capacity, with an OS C-index of 0.785 [95% confidence interval (CI): 0.713–0.857] and 0.750 (95% CI: 0.669–0.832) in the training and verification datasets, respectively. The time–ROC curves also suggest accurate prediction by the signature.

Conclusion

The LCR was a significant prognostic predictor of OS and DFS in early BC. The LCR-based prognostic signatures could be a useful tool for individualized therapeutic guidance.

Update on prognostic and predictive biomarkers of breast cancer

Breast cancer represents a heterogeneous group of human cancer at both histological and molecular levels. Estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2) are the most commonly used biomarkers in clinical practice for making treatment plans for breast cancer patients by oncologists. Recently, PD-L1 testing plays an important role for immunotherapy for triple-negative breast cancer. With the increased understanding of the molecular characterization of breast cancer and the emergence of novel targeted therapies, more potential biomarkers are needed for the development of more personalized treatments. In this review, we summarized several main prognostic and predictive biomarkers in breast cancer at genomic, transcriptomic and proteomic levels, including hormone receptors, HER2, Ki67, multiple gene expression assays, PD-L1 testing, mismatch repair deficiency/microsatellite instability, tumor mutational burden, PIK3CA, ESR1 andNTRK and briefly introduced the roles of digital imaging analysis in breast biomarker evaluation.

Conventional and digital Ki67 evaluation and their correlation with molecular prognosis and morphological parameters in luminal breast cancer

Digital counting methods were developed to decrease the high intra- and inter-observer variability of immunohistochemical markers such as Ki67, with most presenting a good correlation coefficient (CC). Since Ki67 is one of the major contributors to Oncotype DX, it is conceivable that Ki67 expression and the recurrence score (RS) obtained by the multigene panel are positively correlated. We decided first to test to what extent conventional and digital Ki67 quantification methods correlate in daily practice and, second, to determine which of these methods correlates better with the prognostic capacity of the Oncotype DX test. Both Ki67 evaluations were performed in 89 core biopsies with a diagnosis of estrogen receptor (ER) positive HER2-negative breast cancer (BC). Cases were, thus, classified twice for surrogate subtype: first by conventional analysis and then by digital evaluation. The Oncotype RS was obtained in 55 cases that were subsequently correlated to Ki67 evaluation by both methods. Conventional and digital Ki67 evaluation showed good concordance and correlation (CC = 0.81 (95% CI 0.73–0.89)). The correlation of Oncotype DX risk groups and surrogate derived subtypes was slightly higher for the digital technique (r_s = 0.46, p < 0.01) compared to the conventional method (r_s = 0.39, p < 0.01), even though both were statistically significant. In conclusion, we show that digital evaluation could be an alternative to conventional counting, and also has advantages for predicting the risk established by the Oncotype DX test in ER-positive BC. This study also supports the importance of an accurate Ki67 analysis which can influence the decision to submit ER-positive HER2-negative BC to prognostic molecular platforms.

Association between tumor 18F-fluorodeoxyglucose metabolism and survival in women with estrogen receptor-positive, HER2-negative breast cancer

We examined whether ¹⁸F-fluorodeoxyglucose metabolism is associated with distant relapse-free survival (DRFS) and overall survival (OS) in women with estrogen receptor (ER)-positive, HER2-negative breast cancer. This was a cohort study examining the risk factors for survival that had occurred at the start of the study. A cohort from Asan Medical Center, Korea, recruited between November 2007 and December 2014, was included. Patients received anthracycline-based neoadjuvant chemotherapy. The maximum standardized uptake value (SUV) of ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) was measured. The analysis included 466 women. The median (interquartile range) follow-up period without distant metastasis or death was 6.2 (5.3-7.6) years. Multivariable analysis of hazard ratio (95% confidence interval [CI]) showed that the middle and high tertiles of SUV were prognostic for DRFS (2.93, 95% CI 1.62-5.30; P < 0.001) and OS (4.87, 95% CI 1.94-12.26; P < 0.001). The 8-year DRFS rates were 90.7% (95% CI 85.5-96.1%) for those in the low tertile of maximum SUV vs. 73.7% (95% CI 68.0-79.8%) for those in the middle and high tertiles of maximum SUV. ¹⁸F-fluorodeoxyglucose PET/CT may assess the risk of distant metastasis and death in ER-positive, HER2-negative patients.

Whole breast radiotherapy in cN0 early breast cancer patients with pathological sentinel lymph nodes (pN1mic, pN1a) without axillary dissection: preliminary results of the observational LISEN trial

Purpose

Axillary management remains unclear when sentinel lymph node (SLN) results are positive in cN0 patients with breast cancer (BC). The trial ACOSOG Z0011 represented a revolution with axillary lymph node dissection (ALND) omission in SLN+ patients, despite critiques regarding non-uniformity of radiation fields. We conducted an observational study (LISEN) where whole breast radiotherapy (WBRT) was planned with tangential fields without nodal irradiation in patients eligible for the Z0011 trial.

Methods

Inclusion criteria were female patients with histologically proven BC, cT1-2cN0, planned conservative surgery, no neoadjuvant therapy. Patients were stratified into two groups: micrometastatic (pN1mic, group 1) and macrometastatic (pN1a, group 2) lymph nodes. Tangential field WBRT was mandatory. Clinical outcomes were analysed, measured from surgery until the first event.

Results

In all, 199 patients underwent conservative surgery and SLN biopsy; 133 patients meeting criteria were analysed: 41 patients (30.8%) pN1mic and 92 (69.2%) pN1a. The 5‑year disease-free survival (DFS) was 95.0% (85.9–100%) in group 1 and 93.0% (86.3–100.0%) in group 2 (p = 0.78). Overall survival (OS) was 100% (100–100%) in group 1 and 97.4% (92.4–100%) in group 2 (p = 0.74). For the whole cohort DFS and OS were 93.6% (88.2–99.4%) and 96.9% (91.5–100.0%), respectively. For groups 1 and 2, the 5‑year outcomes were 5.0% (0.0–14.4%) and 2.3% (0.0–6.1%) for local recurrence (p = 0.51), and 6.2% (0.0–17.4%) and 7.0% (0.0–13.7%) for distant metastasis (p = 0.61), respectively. In group 1, regional recurrence (RR) and local regional recurrence (LRR) were 5.0% (0.0–14.1%; p = 0.13). In group 2, RR and LRR were 0.0% (0.0–0.0%).

Conclusion

Our results showed good regional control in patients who met the Z0011 trial criteria. WBRT, without nodal surgery or RT, avoiding axillary morbidity, seems to be a good choice.

Correlation of prognostic factors of carcinoma breast with Ki 67 proliferation assay

Prognostic factors are important for the diagnosis of breast cancer as it helps in identification of high risk patients.  The objective of the study is to assess the proliferation index, Ki-67 and correlate it with other markers. The present study was a cohort study conducted in the Department of General Surgery at Tertiary Care Teaching Hospital over a period of 1 year with a sample size of 98. All the patients meeting the inclusion and exclusion criteria are recruited sequentially by convenient sampling until the sample size is attained, with the agreement of the institutional ethics committee. A total of 98 patients with a mean age of 53.61 ± 12.48 years were studied in the final analysis. The mean duration of lump was 4.62 ± 2.18 months and only 6.12% had the complaint of pain.  Majority of them had stage IIIB carcinoma at 43.88%, followed by stage IIA at 27.55%, 15.31% stage IIB, 13.27% stage IIIA.  At cut off 20, 69(70.40%) had ki67 proliferation index ≥20 and 29(29.59%) had<20. Correlation of Ki-67 Index with expression of estrogen receptor status had a p value of 0.019 and with progesterone receptor status, p 0.003 which was significant. 

Definition of High-Risk Early Hormone-Positive HER2−Negative Breast Cancer: A Consensus Review

Breast cancer is one of the major causes of cancer-related morbidity and mortality in women worldwide. During the past three decades, several improvements in the adjuvant treatment of hormone receptor-positive/HER2−negative breast cancer have been achieved with the introduction of optimized adjuvant chemotherapy and endocrine treatment. However, estimating the risk of relapse of breast cancer on an individual basis is still challenging. The IRIDE (hIGh Risk DEfinition in breast cancer) working group was established with the aim of reviewing evidence from the literature to synthesize the current relevant features that predict hormone-positive/HER2−negative early breast cancer relapse. A panel of experts in breast cancer was involved in identifying clinical, pathological, morphological, and genetic factors. A RAND consensus method was used to define the relevance of each risk factor. Among the 21 features included, 12 were considered relevant risk factors for relapse. For each of these, we provided a consensus statement and relevant comments on the supporting scientific evidence. This work may guide clinicians in the practical management of hormone-positive/HER2−negative early breast cancers.

Mutational Analysis of BRCA1 and BRCA2 Genes in Breast Cancer Patients from Eastern Sicily

Purpose

Germline mutations of BRCA1 and BRCA2 are associated with a defined lifetime risk of breast (BC), ovarian (OC) and other cancers. Testing BRCA genes is pivotal to assess individual risk, but also to pursue preventive approaches in healthy carriers and tailored treatments in tumor patients. The prevalence of BRCA1 and BRCA2 alterations varies broadly across different geographic regions and, despite data about BRCA pathogenic variants among Sicilian families exist, studies specifically addressing eastern Sicily population are lacking. The aim of our study was to investigate the incidence and distribution of BRCA pathogenic germline alterations in a cohort of BC patients from eastern Sicily and to evaluate their associations with specific BC features.

Patients and Methods

Mutational status was assessed in a cohort of 389 BC patients, using next generation sequencing. The presence of alterations was correlated with tumor grading and proliferation index.

Results

Overall, 35 patients (9%) harbored a BRCA pathogenic variant, 17 (49%) in BRCA1 and 18 (51%) in BRCA2. BRCA1 alterations were prevalent among triple negative BC patients, whereas BRCA2 mutations were more common in subjects with luminal B BC. Tumor grading and proliferation index were both significantly higher among subjects with BRCA1 variants compared to non-carriers.

Conclusion

Our findings provide an overview about BRCA mutational status among BC patients from eastern Sicily and confirm the role of NGS analysis to identify hereditary BC patients. Overall, these data are consistent with previous evidences supporting BRCA screening to properly prevent and treat cancer among mutation carriers.