Assessment of Ki67 in Breast Cancer: Updated Recommendations From the International Ki67 in Breast Cancer Working Group

Molecular characterisation of the residual disease after neoadjuvant endocrine therapy in ER+/HER2- breast cancer uncovers biomarkers of tumour response

BACKGROUND

Neoadjuvant endocrine therapy (NET) in oestrogen receptor-positive /HER2-negative breast cancer (ER+/HER2- BC) allows real-time evaluation of treatment sensitivity by monitoring tumour response and offers the opportunity of personalised therapy. However, the lack of reproducible biomarkers to assess response and long-term prognosis after NET is a significant barrier to increase its indications.

METHODS

In this study we searched for clinically relevant molecular reporters of response to NET in a multicentre population of ER+/HER2- BC patients (n = 87) by using: PAM50 gene expression panel and immunohistochemical evaluation of key proteins involved in tumorigenesis.

RESULTS

Our PAM50 analyses show that tumours changing from luminal A to normal-like subtype after NET presented better radiological and pathological tumour responses, a significant larger decrease in Ki67 at surgery, lower preoperative endocrine prognostic index score (PEPI) and lower tumour cellularity size (TCS) than those with persistent luminal A status. Patients with the highest response to NET showed the largest decrease in PAM50-derived risk of recurrence (ROR) following NET. In addition, the percentage of p53 positive cells was associated with decreased response to NET.

CONCLUSIONS

Our findings highlight the change of intrinsic subtype from luminal A to normal-like after NET as a putative biomarker characterising the patient population that obtains the highest benefit from NET. Our study also suggests that changes in PAM50-derived ROR score and p53 evaluation could also help to identify those patients. Thus, this study uncovers potential biomarkers of response to NET and prognosis, which should be validated in independent cohorts, helping to the implementation of NET in the clinical practice.

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.

Analysis of Tumor Proliferation Markers in Early-Stage Luminal Breast Cancer: A Comprehensive Study Using Mitotic Activity Index, Ki-67, and Phosphohistone H3 Expression

Introduction and Aim: Routinely used proliferation markers such as mitotic activity index (MAI) and Ki-67 index show limited reproducibility due to high interobserver variability in breast cancer assessment. Phosphohistone H3 (PhH3), a novel proliferation marker, is gaining attention in breast cancer research. This study aimed to evaluate the inter-rater agreement among MAI, Ki-67, and PhH3 expressions in early-stage luminal breast cancer and assess the impact of replacing MAI with PhH3 index on tumor histological grading. Materials and Methods: Three pathologists assessed MAI, Ki-67, and PhH3 expressions in 66 early-stage luminal breast cancer specimens. Mitotic Activity Index was scored based on mitotic figures in an area of 2 mm2 while Ki-67 index utilized a 14% threshold for positively stained nuclei. Phosphohistone H3 expression cutoff was set at 13 positive cells per 2 mm2. The inter-rater agreement for the 3 variables was analyzed using Cohen kappa statistics. Results: Among the 3 parameters, the kappa score of the PhH3 expression reflected very strong agreement between the 3 observers (κ = 0.991, 0.907, and 0.916). Only moderate agreement was noted for MAI (κ = 0.898, 0.562, and 0.592) and substantial agreement for Ki-67 index (κ = 0.869, 0.673, and 0.678). Moreover, replacing MAI with PhH3 index led to upgrade of histological grade in 15% to 16% of patients. Conclusion: Our study demonstrated that PhH3 is a more reproducible proliferation marker than MAI and Ki-67. Incorporation of PhH3-based mitotic index in breast cancer grading might reduce the variation in the assessment of histological grade.

Ki-67 and 21-gene recurrence score assay in decision making for adjuvant chemotherapy in breast cancer patients

Although significant advances have been made in the molecular subtyping of breast cancers, identification of patients who do not benefit from the chemotherapy is a major challenge. Pioneer studies have examined the predictive value of the clinicopathological factors, such as tumor size, disease stage, the expression levels of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER2) molecules and more importantly tumor cells proliferation index (Ki-67) to help guide patients' treatment and predict their outcome in the adjuvant chemotherapy setting. However, despite their clinical importance, no consensus is reached on their validity for chemotherapy decision. These challenges have ignited researchers to evaluate genomic signatures, which has led to the introduction of several genomic tests that can now help oncologists to include/exclude chemotherapy from the treatment regimen with more confidence. The present review aims to look back over the literature on the clinical significance of Ki-67 as well as the 21-gene recurrence score assay in identification of breast cancer patients who may benefit from the adjuvant chemotherapy.

Ki-67-Playing a key role in breast cancer but difficult to apply precisely in the real world

The Ki-67 index, which is a proliferative index, has become more important in making treatment decisions for patients with breast cancer (BC) and plays both a predictive role and a prognostic role. However, a few factors limit its use in clinical practice, particularly the assessment of the percentage of Ki-67-positive cells and the cutoff value of Ki-67. In this study, we examined the expression of Ki-67 via immunohistochemistry and systematically evaluated the value of the Ki-67 index in patients with BC. This was a retrospective study including 280 patients diagnosed with BC. There were marked differences in overall survival (OS) between patients with BC when the Ki-67 index ranged from 46 to 68% (χ2 = 5.87, P = 0.0154; χ2 = 7.64, P = 0.0057, respectively), and the same results were also found when the staining density was added to the Ki-67 index; however, the staining density alone has limited value in assessing the value of Ki-67. There were marked differences in disease-free survival (DFS) among BC patients when the Ki-67 index ranged from 50 to 58% (χ2 = 7.31, P = 0.0069; χ2 = 7.88, P = 0.005). When 14% was used as a cutoff point to classify the molecular type of BC, the luminal A-type patients were significantly different from patients with HER2-overexpressing subtype BC in terms of OS (χ2 = 5.33, P = 0.021). There was a significant difference in the OS of patients with human epidermal growth factor receptor 2 (HER-2)-overexpressing subtype BC when the Ki-67 index fell within the range of 49-60% (χ2 = 4.86, P = 0.0275; χ2 = 5.50, P = 0.019, respectively). There were significant differences between luminal A-type BC and HER2-overexpressing subtype BC in terms of OS (χ2 = 5.53, P = 0.019), according to suggestions of the 2019 CSCO consensus. There were significant differences between the two groups of luminal B HER-2(-) BC when the Ki-67 index was 52% (χ2 = 6.61, P = 0.0101). The differentiated Ki-67 index can be used to assess the OS and DFS of patients with BC, and the staining density of Ki-67 has little value in assessing prognosis in these patients. Different molecular classification methods may influence the assessment of prognosis and the results of molecular subtype in patients with BC. To predict the prognosis of BC patients, it is more scientifically feasible to use the interval values of Ki-67 than a specific value.

MRI-based habitat analysis for Intratumoral heterogeneity quantification combined with deep learning for HER2 status prediction in breast cancer

BACKGROUND

Human epidermal growth factor receptor 2 (HER2) is a crucial determinant of breast cancer prognosis and treatment options. The study aimed to establish an MRI-based habitat model to quantify intratumoral heterogeneity (ITH) and evaluate its potential in predicting HER2 expression status.

METHODS

Data from 340 patients with pathologically confirmed invasive breast cancer were retrospectively analyzed. Two tasks were designed for this study: Task 1 distinguished between HER2-positive and HER2-negative breast cancer. Task 2 distinguished between HER2-low and HER2-zero breast cancer. We developed the ITH, deep learning (DL), and radiomics signatures based on the features extracted from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Clinical independent predictors were determined by multivariable logistic regression. Finally, a combined model was constructed by integrating the clinical independent predictors, ITH signature, and DL signature. The area under the receiver operating characteristic curve (AUC) served as the standard for assessing the performance of models.

RESULTS

In task 1, the ITH signature performed well in the training set (AUC = 0.855) and the validation set (AUC = 0.842). In task 2, the AUCs of the ITH signature were 0.844 and 0.840, respectively, which still showed good prediction performance. In the validation sets of both tasks, the combined model exhibited the best prediction performance, with AUCs of 0.912 and 0.917 respectively, making it the optimal model.

CONCLUSION

A combined model integrating clinical independent predictors, ITH signature, and DL signature can predict HER2 expression status preoperatively and noninvasively.

Pathological complete response and prognostic predictive factors of neoadjuvant chemoimmunotherapy in early stage triple-negative breast cancer

Background

Neoadjuvant chemoimmunotherapy (nCIT) has shown promise in treating early-stage triple-negative breast cancer (eTNBC), but predictive biomarkers for pathological response and prognosis remain poorly defined.

Objective

This study aimed to explore pathological complete response and prognostic predictive factors in eTNBC patients treated with nCIT.

Materials and methods

We retrospectively analyzed 112 eTNBC patients who underwent surgery after nCIT at Sun Yat-sen University Cancer Center between June 2019 and June 2023. Pathological response was assessed using Miller-Payne grade. Clinicopathological features and hematologic markers were analyzed with univariate and multivariate logistic regression or Cox regression, as well as Kaplan-Meier survival curves. Objective response rate (ORR), pathological complete response (pCR), and disease-free survival (DFS) were evaluated. Nomograms predicting pCR and DFS were constructed based on significant risk factors and the systemic inflammatory response index (SIRI).

Results

Higher baseline lymphocyte counts (P=0.004) were independently associated with a higher pCR rate, while elevated monocyte counts (P=0.006), neutrophil-to-lymphocyte ratio (P=0.005), platelet-to-lymphocyte ratio (p = 0.005), SIRI (P=0.037), systemic immune-inflammation index (P=0.029), and preoperative SIRI (P=0.010) were associated with a lower pCR rate. Higher baseline SIRI (P= 0.009) was correlated with shorter DFS, while higher preoperative lymphocyte counts (P=0.019) predicted longer DFS. Nomograms incorporating SIRI showed high accuracy in predicting pCR and DFS.

Conclusion

Hematologic inflammatory markers, particularly SIRI, are cost-effective and reliable predictors of prognosis and treatment efficacy in eTNBC patients undergoing nCIT, helping clinicians develop personalized treatment strategies.

Clinical trial registration

https://www.medicalresearch.org.cn/, identifier MR-44-24-046099.

Denosumab as an immune modulator in HER2-negative early breast cancer: results of the window-of-opportunity D-BIOMARK clinical trial

BACKGROUND

The RANK pathway has been extensively investigated for its role in bone resorption; however, its significance extends beyond bone metabolism. Preclinical models suggest that inhibition of RANK signaling can prevent mammary tumor development by reducing proliferation and tumor cell survival. Additionally, both preclinical and clinical data support the ability of RANK pathway inhibitors to enhance the anti-tumor immune response.

METHODS

D-BIOMARK is a prospective, randomized window-of-opportunity clinical trial assessing the biological effects of denosumab, a monoclonal antibody against RANKL, in patients with HER2-negative early breast cancer. The study aims to assess denosumab's impact on breast tumor cell proliferation, apoptosis, and its potential to influence the tumor immune microenvironment. A total of 60 patients were enrolled and randomized 2:1 to receive two doses of single agent denosumab (120 mg one week apart) before surgery or to the control arm (no treatment). Fifty-eight patients were evaluated, 27 pre-menopausal and 31 post-menopausal women, 48 with luminal tumors and 10 with triple negative breast cancer. Paired tumor samples were collected to compare baseline (core biopsy) and surgical (surgical specimen) time points, as well as serum samples at both time points.

RESULTS

Denosumab demonstrated its ability to reduce serum free RANKL levels (experimental p < 0.001, control p = 0.270). However, a reduction in tumor cell proliferation or cell survival was not observed. A denosumab-driven increase in tumor infiltrating lymphocytes (TILs) was observed (experimental p = 0.001, control p = 0.060), particularly in the luminal B-like population (experimental p = 0.012, control p = 0.070) and a similar trend in the TNBC group (experimental p = 0.079, control p = 0.237). Denosumab led to increased TILs in both pre-menopausal (experimental p = 0.048, control p = 0.639) and post-menopausal (experimental p = 0.041, control p = 0.062) women with luminal tumors. RANK protein expression in tumor and stroma was associated with markers of tumor aggressiveness but an increase in TILs was observed in the experimental arm, irrespectively of RANK and RANKL expression in tumor or stromal cells.

CONCLUSIONS

The D-BIOMARK trial suggests a potential role for denosumab as an immune-enhancing agent in early HER2-negative breast cancer. Although preoperative denosumab did not reduce tumor proliferation or increased apoptosis, it led to an increase in TILs, particularly in luminal B-like tumors. These findings underscore the importance of further investigation into the multifaceted aspects of the RANK pathway. Trial registration EudraCT number: 2016-002678-11 registered on June 15, 2018.

CLINICALTRIALS

gov identifier: NCT03691311, retrospectively registered on September 04, 2018.

Study on predicting breast cancer Ki-67 expression using a combination of radiomics and deep learning based on multiparametric MRI

PURPOSE

To develop a multiparametric breast MRI radiomics and deep learning-based multimodal model for predicting preoperative Ki-67 expression status in breast cancer, with the potential to advance individualized treatment and precision medicine for breast cancer patients.

METHODS

We included 176 invasive breast cancer patients who underwent breast MRI and had Ki-67 results. The dataset was randomly split into training (70 %) and test (30 %) sets. Features from T1-weighted imaging (T1WI), diffusion-weighted imaging (DWI), T2-weighted imaging (T2WI), and dynamic contrast-enhanced MRI (DCE-MRI) were fused. Separate models were created for each sequence: T1, DWI, T2, and DCE. A multiparametric MRI (mp-MRI) model was then developed by combining features from all sequences. Models were trained using five-fold cross-validation and evaluated on the test set with receiver operating characteristic (ROC) curve area under the curve (AUC), accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and F1 score. Delong's test compared the mp-MRI model with the other models, with P < 0.05 indicating statistical significance.

RESULTS

All five models demonstrated good performance, with AUCs of 0.83 for the T1 model, 0.85 for the DWI model, 0.90 for the T2 model, 0.92 for the DCE model, and 0.96 for the mp-MRI model. Delong's test indicated statistically significant differences between the mp-MRI model and the other four models, with P values < 0.05.

CONCLUSIONS

The multiparametric breast MRI radiomics and deep learning-based multimodal model performs well in predicting preoperative Ki-67 expression status in breast cancer.

Optimization of guidelines for Risk Of Recurrence/Prosigna testing using a machine learning model: a Swedish multicenter study

PURPOSE

Gene expression profiles are used for decision making in the adjuvant setting in hormone receptor-positive, HER2-negative (HR+/HER2-) breast cancer. While algorithms to optimize testing exist for RS/Oncotype Dx, no such efforts have focused on ROR/Prosigna. This study aims to enhance pre-selection of patients for testing using machine learning.

METHODS

We included 348 postmenopausal women with resected HR+/HER2-node-negative breast cancer tested with ROR/Prosigna across four Swedish regions. We developed a machine learning model using simple prognostic factors (size, progesterone receptor expression, grade, and Ki67) to predict ROR/Prosigna output and compared the performance regarding over- and undertreatment with commonly employed risk stratification schemes.

RESULTS

Previous classifications resulted in significant undertreatment or large intermediate groups needing gene expression profiling. The machine learning model achieved AUC under ROC of 0.77 in training and 0.83 in validation cohorts for prediction of indication for adjuvant chemotherapy according to ROR/Prosigna. By setting and validating upper and lower cut-offs corresponding to low, intermediate and high-risk disease, we improved risk stratification accuracy and reduced the proportion of patients needing ROR/Prosigna testing compared to current risk stratification.

CONCLUSION

Machine learning algorithms can enhance patient selection for gene expression profiling, though further external validation is needed.

Oxoisoaporphine Alkaloid Iridium(III) Derivative: An Immunogenic Cell Death Inducer That Engages the Autophagy-Dependent Regulator Cathepsin D

Autophagy has been recognized as one of the pathways for eliciting immunogenic cell death (ICD). However, the specific molecular target responsible for autophagy-mediated ICD has not yet been elucidated. Here, we report that an oxoisoaporphine alkaloid-modified iridium(III) complex (2a) displays autophagy-inducing ICD activity. Through unbiased thermal proteome profiling (TPP), this new complex was found to interact with the lysosomal protease cathepsin D (Cat D). Subsequent cellular and biochemical assays─including the cellular thermal shift assay, isothermal dose-response assay, enzymatic assays, and molecular docking─confirmed that 2a binds to and inhibits Cat D. Further pathway analysis demonstrated that 2a triggers autophagy-dependent ICD via the LKB1-AMPK-ULK1 signaling pathway by inhibiting Cat D. Several other autophagy-dependent ICD inducers were tested and likewise found to inhibit Cat D. In contrast, an earlier reported analogue of 2a, complex 1a, was found to bind and destabilize binding immunoglobulin protein (BiP) and promote its ICD activity through an endoplasmic reticulum stress response. We believe that the findings reported here will enhance the understanding of the novel mechanisms of ICD agents and pave the way for the design of new ICD inducers with high specificity and efficacy.

Molecular Landscape, Genomic Shift, and Prediction in the Neoadjuvant Setting of Human Epidermal Growth Factor Receptor 2-Positive Breast Cancer

The amplification or overexpression of human epidermal growth factor receptor 2 (HER2) defines a breast cancer subtype, which benefits from neoadjuvant HER2-targeted therapy. However, at least 40% of patients respond poorly or do not respond to treatment. We analyzed the main genomic alterations of 64 HER2+ patients by next-generation sequencing to identify new predictors of response and correlate them with clinicopathological parameters. We also compared the genomic alterations between primary and residual tumors after neoadjuvant treatment. The TP53 gene was the most frequently mutated gene, and in combination with ERBB2 overexpression, the 2 were predictive of residual cancer burden (P = .001). Furthermore, the combination of their immunohistochemical counterpart (p53 mutant and score 3+ for HER2) can predict complete pathological response and the grade of response (P = .038 and P = .031, respectively). Therefore, p53 could be included in the initial panel of breast cancer biomarkers to help therapeutic decision-making in HER2+ cases.

Creation and Characterization of a Breast Cancer Tissue Microarray Including Black and White Patients from Florida and Hispanic Patients from Puerto Rico and Florida

Breast cancer is a leading cause of cancer-related mortality among women worldwide and is known to have higher mortality among women with African ancestry. Herein, we describe the creation and characterization of a multiethnic breast cancer tissue microarray (ME-BrTMA) representing tumors from non-Hispanic White (n = 41), non-Hispanic Black (NHB; n = 45), and Hispanic patients from Puerto Rico (n = 36) and Florida (n = 52). This ME-BrTMA comprises five blocks with a total of 610 cores: 371 breast cancer tumor cores, 93 breast stromal cores, 96 normal breast tissue cores, 30 non-breast cancer tumor cores, and 20 cores representing normal tissues. Initial characterization of the ME-BrTMA includes standard IHC staining of well-characterized clinical biomarkers, including the estrogen hormone receptors and progesterone hormone receptors, HER2, and Ki-67, interpreted by the coauthoring pathologist (Marilin Rosa). The IHC results indicated good but imperfect alignment with clinical diagnoses. Cores from breast cancer tumors from the NHB cohort most frequently scored negative for estrogen receptor (63%, P < 0.005) and progesterone receptor (80%, P < 0.005) and most frequently have high expression of the Ki-67 proliferation marker (38%, P < 0.05). Prediction Analysis of Microarray 50 (PAM50) analysis using RNA from secondary patient blocks showed that the NHB group also most frequently scored in the basal-like category (61%, P < 0.05). Taken together, the initial characterization of the ME-BrTMA suggests that it may serve as a representative resource to understand the underlying biology of breast cancer and its relationship to patient outcomes.

SIGNIFICANCE

The ME-BrTMA described herein provides a resource that may serve as a tool to understand the underlying biology of breast cancer.

Reliability of Ki67-Labeling Index in Core Needle Biopsy Specimens of ER+/HER2- Breast Cancers

The reliability of Ki67-labeling index (LI) in core needle biopsy (CNB) of ER+/HER2- invasive breast carcinoma (IBC) and factors affecting the discordance of Ki67-LI between CNB and surgical resection (SR) remain unsolved. We aimed to elucidate factors influencing the discordance of Ki67-LI between CNB and SR to classify ER+/HER2- IBC into luminal A-like (LumA) and luminal B-like (LumB). The cohort included 326 ER+/HER2- IBCs available with Ki67-LI data at both CNB and SR specimens. Survival analysis was performed on 122 patients. Spearman's rank correlation coefficient of Ki67-LI between them was 0.683. The log-rank test showed that patients with ER+/HER2- IBC with ≥ 20% Ki67-LI at CNB (p < 0.001) and SR specimens (p < 0.001) had significantly shorter disease-free survival. In multivariate analysis, a negative PgR (p = 0.002) and > 2 cm pathological tumor size (p < 0.001) had the most significant effect on the discordance of Ki67-LI between CNB and SR at 20% and 30% cutoffs, respectively. Histological grade III had a significant effect on the concordance between them (p = 0.01) at 20% cutoff. Ki67-LI assessment in CNB may be useful for classifying ER+/HER2- IBC into LumA and LumB with caution of some prognostic factors and cutoffs.

Toward Accurate Deep Learning-Based Prediction of Ki67, ER, PR, and HER2 Status From H&E-Stained Breast Cancer Images

Despite improvements in machine learning algorithms applied to digital pathology, only moderate accuracy, to predict molecular information from histology alone, has been achieved so far. One of the obstacles is the lack of large data sets to properly train machine learning models. We therefore built a data set of 185,538 breast cancer (BC) including hematoxylin and eosin (H&E) and associated immunohistochemistry (IHC) images of the proliferative marker Ki67, estrogen receptor (ER), progesterone receptor (PR), and the human epidermal growth factor receptor 2 (HER2). Optimal registration of H&E and IHC pairs was achieved. Ki67, ER, and PR IHC labels, to be predicted, were extracted from IHC assays using image analysis. These labels were ordinaly classified with incremental thresholds (cumulative logit models with balanced and partial proportional odds). HER2 label was determined as follows: positive if tumor IHC 3+ pattern is identified and otherwise negative. Cases with IHC equivocal score (2+) were excluded. A vision transformer (ViT)-based pipeline, trained with this data set, achieved prediction performance of 90% in terms of area under the curve (AUC) of the receiver operating characteristic (ROC) curves. ViT outperformed the weakly supervised clustering-constrained attention multiple instance learning (CLAM) which was developed to automatically identify subregions of high diagnostic value in whole slide. As a first step to "explain" artificial intelligence (AI), we evaluated the ability of both classifiers to localize these high diagnostic value subregions by inspecting their respective "attention" heat-maps. Despite high ViT AUC-ROC results, heat-maps do not obviously match areas of high diagnostic value subregions; it might however provide direction for future work to improve AI attention within whole slide images. Our proposed data set is publicly available.

Navigating Endocrine Sensitivity Assessment in Nonmetastatic Breast Cancer Through Early On-Treatment Ki67 Understanding

In the landscape of breast cancer management, precise assessment of endocrine sensitivity significantly influences therapeutic strategies. The utilization of Ki67, an immunohistochemical marker of tumor proliferation, in tumor rebiopsy holds paramount importance in unraveling breast cancer's response to endocrine therapy. This narrative review aims to elucidate the pivotal role of Ki67 in endocrine sensitivity assessment. We explore the nuanced process of Ki67 evaluation, its timing, and its implications for clinical outcomes in breast cancer patients. From a clinical perspective to pathological response and risk of recurrence, we navigate the spectrum of Ki67's impact. By delving into these facets, we underscore Ki67's potential to guide personalized treatment strategies, shedding light on the intricate interplay between endocrine therapy and clinical outcomes in breast cancer patients.

Discovery of a Novel Selective PAK1/HDAC6/HDAC10 Inhibitor ZMF-25 that Induces Mitochondrial Metabolic Breakdown and Autophagy-Related Cell Death in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype, and addressing its intrinsic heterogeneity has emerged as a valuable avenue for novel clinical treatment strategy. Here, we put forward an innovative strategy for TNBC treatment by simultaneously suppressing both p21-activated kinase 1 (PAK1) and histone deacetylase (HDAC) class IIb (HDAC6/10). A series of pyrido [2,3-d]pyrimidin-7(8H)-one moiety derivatives was successfully designed and synthesized to target PAK1/HDAC6/HDAC10 by utilizing structure-based screening and pharmacophore integration. ZMF-25 demonstrates marked inhibitory activity against PAK1, HDAC6, and HDAC10 with respective IC50 values of 33, 64, and 41 nM, remarkable selectivity over HDACs and PAKs, as well as prominent antiproliferative efficiency in MDA-MB-231 cells. Additionally, ZMF-25 effectively suppresses TNBC proliferation and migration by inhibiting PAK1/HDAC6/HDAC10. Moreover, it was found to impair glycolysis and trigger reactive oxygen species generation, resulting in autophagy-related cell death by inhibiting the AKT/mTOR/ULK1 signaling. Furthermore, ZMF-25 exhibits remarkable therapeutic potential with no obvious toxicity in vivo and good pharmacokinetics. In summary, these observations indicate that ZMF-25 is a novel and potent triple-targeting PAK1/HDAC6/HDAC10 inhibitor, which is expected to provide a novel and effective strategy for TNBC treatment.

Intratumoral and peritumoral radiomics signature based on DCE-MRI can distinguish between luminal and non-luminal breast cancer molecular subtypes

Distinguishing the luminal subtypes of breast cancer (BC) remaining challenging. Thus, the aim of this study was to investigate the feasibility of radiomic signature using intratumoral and peritumoral features obtained from dynamic contrast-enhanced MRI (DCE-MRI) in preoperatively discriminating the luminal from non-luminal type in patients with BC. A total of 305 patients with pathologically confirmed BC from three hospitals were retrospectively enrolled. The LASSO method was then used for selecting features, and the radiomic score (radscore) for each patient was calculated. Based on the radscore, Radiomic signature of intratumoral, peritumoral, and combined intratumoral and peritumoral were established, respectively. The performances of the radiomic signatures were validated with receiver operator characteristic (ROC) curve and decision curve analysis. For predicting molecular subtypes, the AUC for intratumoral radiomic signature was 0.817, 0.838, and 0.883 in the training set, internal validation set, and external validation set, respectively. AUC for the peritumoral radiomic signature was 0.863, 0.895, and 0.889 in the training set, internal validation set, and external validation set, respectively. The AUC for combined intratumoral and peritumoral radiomic signature was 0.956, 0.945, and 0.896 in the training set, internal validation set, and external validation set, respectively. Additional contributing value of combined intratumoral and peritumoral radiomic signature to the intratumoral radiomic signature was statistically significant [NRI, 0.300 (95% CI: 0.117-0.482), P = 0.001 in internal validation set; NRI, 0.224 (95% CI: 0.038-0.410), P = 0.018 in external validation set]. These results indicated that the radiomic signature combining intratumoral and peritumoral features showed good performance in predicting the luminal type of breast cancer.

Oncotype DX Recurrence Score and Germline BRCA Variants in Patients with HR-Positive/HER2-Negative Early Breast Cancer: A Retrospective Observational Study

INTRODUCTION

The Oncotype DX (ODX) recurrence score (RS) is prognostic and predictive of chemotherapy benefit in patients with hormone receptor (HR)-positive/human epidermal growth factor receptor 2 (HER2)-negative early breast cancer. Data on the distribution of germline BRCA1 and/or BRCA2 pathogenic variants (gBRCA PV) by RS are limited. This retrospective, real-world study explored demographics, clinical characteristics, gBRCA testing rates, and gBRCA PV prevalence in HR-positive/HER2-negative stage I-III breast cancer, stratified by RS.

METHODS

Deidentified patient data (from 1 January 2011 to 30 September 2022) from US electronic health records in a nationwide database were used. Patients aged ≥ 18 years with HR-positive/HER2-negative breast cancer and a known ODX RS were included. Demographics, clinical characteristics, and genetic testing rates were compared in patients with low, intermediate, and high tumor RS. gBRCA PV prevalence was compared across categories in patients who underwent genetic testing.

RESULTS

Of 3637 patients (median age: 62 years), 950 (26.1%) had low, 2155 (59.3%) had intermediate, and 532 (14.6%) had high tumor RS. Despite increases in genetic testing over time, gBRCA status was determined in only 31.5% (n = 1147/3637) of patients. Among tested patients, 37/1147 (3.2%) had gBRCA PV; median age was lower in gBRCA PV carriers than in noncarriers (52 versus 56 years; p = 0.034); tumors from gBRCA PV carriers had significantly higher grade (p = 0.002) and median RS (p = 0.001) than tumors from noncarriers; prevalence of gBRCA PV was highest among tested patients with high tumor RS (n = 14/185; 7.6%), but gBRCA PVs were identified among patients with intermediate (n = 19/674; 2.8%) and low (n = 4/288; 1.4%) tumor RS.

CONCLUSIONS

Prevalence of gBRCA PV was highest among patients with high tumor RS, but not negligible in patients with intermediate and low tumor RS. Wider implementation of genetic testing, irrespective of ODX RS, could help optimize the management of patients with HR-positive/HER2-negative early breast cancer.

Cost-effectiveness of Prosigna for Adjuvant Treatment Decisions in Early Breast Cancer: Healthcare Sector and Societal Perspectives

BACKGROUND

Gene expression profiling tests such as the Prosigna-assay are used to aid adjuvant treatment decisions in hormone receptor positive (HR+) HER2 negative (HER2-) early breast cancer (EBC). In this evaluation, the cost-effectiveness of Prosigna against immunohistochemical (IHC) markers including Ki-67, was evaluated from the Norwegian healthcare- and societal perspective.

MATERIALS AND METHODS

The treatment decision impact of Prosigna was tested in the prospective, observational EMIT-1 trial. Using individual data collected the first 12 months post-surgery, a decision model was built to project the economic consequences of using the Prosigna compared to IHC-markers for the adjuvant treatment decisions. Health benefits were measured by cost per quality-adjusted life-years (QALYs) and data on income and welfare benefit was obtained from Statistics Norway.

RESULTS

Of 2,178 HR+/HER2- pN0 EBC patients in the EMIT-1 trial, 1,985 had available health economic data and 1,850 had complete income and welfare benefit records. Including all pN0 patients in the Prosigna-test strategy, the test was above the cost-effective threshold (€26,000; incremental cost-per QALY gained (ICER) €255,622) in a healthcare sector perspective. Incorporating also productivity costs, Prosigna was cost-saving (ICER €-435,677). Restricting Prosigna-testing to patients assessed as clear/uncertain chemotherapy candidates, the strategy was cost-effective in both the healthcare and societal perspective (ICER €8884 and €-620170, respectively).

CONCLUSIONS

Using the Prosigna-assay for all HR+/HER2- pN0 EBC patients was not cost-effective from a healthcare perspective, but from the societal perspective it was cost-saving. Selecting patients who are clear/uncertain candidates for chemotherapy based on IHC-classification, Prosigna is cost-effective from both perspectives.

High Ki-67 expression is associated with increased risk of distant recurrence in Oncotype Dx low risk breast cancer

PURPOSE

To assess whether high Ki-67 protein expression level could independently predict the distant recurrence in early-stage breast cancer with low Oncotype Dx scores (≤ 25).

METHODS

This single-center retrospective cohort study included 278 patients with hormone receptor positive (HR+) human epidermal growth factor receptor 2 negative (HER2-), T1-2N0M0, low Oncotype Dx recurrence score (RS) (≤ 25) breast cancer. We identified 2 groups: "high Ki-67″ ≥ 15% (n = 130, 47%) and "low Ki-67″ < 15% (n = 148, 53%). Clinical characteristics, treatment and survival were abstracted from chart review. Fisher's exact test was used to assess differences between Ki-67 groups. Cox-regression models were used to assess differences in survival.

RESULTS

After a median follow up of 7 years, 13 (4.7%) patients experienced distant metastasis. Recurrence rate was significantly higher in the "high Ki-67″ group 9.2% (12/130) versus the "low Ki-67″ group 0.7% (1/148) (P = .001). Distant metastasis-free survival (dMFS) was significantly shorter in the "high Ki-67″ group (HR 12.90, 95% CI, 12.53-13.27, P = .008). Tumor size ≥ 2 cm was associated with shorter dMFS (HR, 12.90; 95% CI, 12.53-13.27; P < .001). In a multivariable analysis, tumor size ≥ 2 cm and "High Ki-67″ were independent prognosis factors for dMFS.

CONCLUSION

Ki-67 expression level may help to identify a subset of low risk Oncotype Dx patients who could benefit from adjuvant chemotherapy.

FDG-PET/CT and Multimodal Machine Learning Model Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer

Purpose: Triple-negative breast cancer (TNBC) is a biologically and clinically heterogeneous disease, associated with poorer outcomes when compared with other subtypes of breast cancer. Neoadjuvant chemotherapy (NAC) is often given before surgery, and achieving a pathological complete response (pCR) has been associated with patient outcomes. There is thus strong clinical interest in the ability to accurately predict pCR status using baseline data. Materials and Methods: A cohort of 57 TNBC patients who underwent FDG-PET/CT before NAC was analyzed to develop a machine learning (ML) algorithm predictive of pCR. A total of 241 predictors were collected for each patient: 11 clinical features, 11 histopathological features, 13 genomic features, and 206 PET features, including 195 radiomic features. The optimization criterion was the area under the ROC curve (AUC). Event-free survival (EFS) was estimated using the Kaplan-Meier method. Results: The best ML algorithm reached an AUC of 0.82. The features with the highest weight in the algorithm were a mix of PET (including radiomics), histopathological, genomic, and clinical features, highlighting the importance of truly multimodal analysis. Patients with predicted pCR tended to have a longer EFS than patients with predicted non-pCR, even though this difference was not significant, probably due to the small sample size and few events observed (p = 0.09). Conclusions: This study suggests that ML applied to baseline multimodal data can help predict pCR status after NAC for TNBC patients and may identify correlations with long-term outcomes. Patients predicted as non-pCR may benefit from concomitant treatment with immunotherapy or dose intensification.

Evaluating the Impact of a Ki-67 Decision Support Algorithm on Pathology Residents' Scoring Accuracy

Ki-67 scoring is of essential importance in the evaluation of breast cancer. We evaluated a Ki-67 algorithm as a decision support tool to improve accuracy for pathology residents. We retrospectively evaluated Ki-67 scores on whole slide images (WSI) obtained from 156 consecutive breast cancer patients. Two senior pathologists determined the 2.1 mm2 hotspot to be evaluated. Ki-67 scores from senior pathologists were compared with results generated by the algorithm, results from 10 pathology residents, and results from pathology residents with the assistance of the algorithm. In addition to numerical results from the algorithm, residents were also presented with a visual representation of nuclei that were counted and excluded. Statistical analysis was performed using Wilcoxon and intra-class correlation (ICC) tests. The mean Ki-67 scores from senior pathologists and the algorithm were 23 ± 18 and 24 ± 18, respectively (ICC, 0.98). Ki-67 scores from the residents were 19 ± 16 and 22 ± 16, without and with input from the algorithm, respectively. With input from the algorithm, residents' scores were significantly closer to those obtained by senior pathologists (p = 0.008). Residents modified their scores in 53.8% of the cases where 74% of the better scores were characterized by an increase in the original scores. The results obtained by the Ki-67 algorithm were highly correlated with those assessed by senior pathologists. We demonstrated that the algorithm may serve as a decision support tool for residents to align their results with those of senior pathologists.

Proliferative Markers in Breast Cancer and Chemotherapy Implications: A Comprehensive Review

Background and Aims

Breast cancer is the most common cancer and a leading cause of cancer-related death among women globally. Determining which patients will benefit from chemotherapy remains challenging. Proliferative markers such as Ki-67, mini chromosome maintenance (MCM) proteins, and proliferating cell nuclear antigen (PCNA) offer valuable insights into tumor growth and treatment response. This review evaluates their clinical roles, with a focus on chemotherapy implications and emerging digital pathology techniques for marker quantification.

Methods

A narrative review was conducted by searching PubMed, Scopus, and Google Scholar for studies related to Ki-67, MCM, PCNA, breast cancer, and chemotherapy. Studies were thematically categorized into five areas. A bibliometric analysis of publications from 2000 to April 2023 was performed using the Bibliometrix R package and VOSviewer to assess research trends and thematic evolution.

Results

Eighty studies were included in the narrative synthesis. Ki-67 is the most commonly used marker, particularly useful in predicting response to neoadjuvant chemotherapy (NAC). MCM proteins show promise for identifying proliferative potential across tumor grades, while PCNA is associated with aggressive tumor features and poor prognosis. Post-chemotherapy changes in Ki-67 levels are linked to survival outcomes. Bibliometric analysis revealed a shift in research focus from basic mechanisms to clinical applications and digital quantification.

Conclusion

Proliferative markers play an essential role in breast cancer management. Ki-67 remains a key predictor of chemotherapy response, while MCM and PCNA offer complementary prognostic insights. Integration of these markers with digital pathology and AI-driven tools may enhance diagnostic accuracy and personalized treatment strategies. Standardization of assessment methods is crucial for broader clinical application.

Mucin 4 expression is associated with metastasis in triple-negative breast cancer and can be tackled by soluble TNF blockade, improving immunotherapy outcome

PURPOSE

Triple-negative breast cancer (TNBC) has the worst prognosis among breast cancers. Immunotherapy is a therapeutic option, but there is no biomarker to guide promising combination treatments. Mucin 4 (MUC4) favors metastasis in preclinical cancer models. This study evaluates the efficacy of soluble TNF (sTNF) neutralization to tackle MUC4 expression preventing metastasis in combination with immunotherapy, and the potential use of MUC4 as a prognostic and predictive biomarker in TNBC patients.

EXPERIMENTAL DESIGN

To explore TNF modulation of MUC4 expression, a panel of TNBC cell lines was used. To assess the effect of sTNF blockade with a dominant negative molecule in combination with anti-PD-1 antibody on lung metastasis and overall survival (OS), 4T1 and LMM3 tumors were used. MUC4, PD-L1 and Ki-67 expression was evaluated by immunohistochemistry, and tumor infiltrating lymphocytes (TILs) were assessed by H&E staining, in a cohort of 49 early TNBC patients treated with chemotherapy.

RESULTS

TNF neutralization reduces MUC4 expression in TNBC cell lines. Only the combination of sTNF blockade with anti-PD-1 antibody prevents metastasis and increases mice survival. In early TNBC patients MUC4 expression is inversely associated with TILs presence and PD-L1 and Ki-67 expression. Finally, MUC4 is associated with metastasis and is an independent biomarker of poor OS.

CONCLUSIONS

We proved the existence of a sTNF/MUC4 axis in TNBC that can be actionable by sTNF neutralization, preventing metastasis. We suggest that MUC4 is a suitable biomarker to guide immunotherapy in TNBC, together with the administration of sTNF blocking drugs to improve outcome.

The prognostic value of changes in Ki67 following neoadjuvant chemotherapy in residual triple-negative breast cancer: a Swedish nationwide registry-based study

PURPOSE

To evaluate the prognostic significance of changes in pre- and post-neoadjuvant chemotherapy (NACT) Ki67 in patients with primary invasive triple-negative breast cancer (TNBC).

METHODS

Population-based registry data were retrieved for patients diagnosed with TNBC between 2007 and 2021 (n = 9262). Multivariable Cox regression analysis was performed for disease-specific survival (DSS) and overall survival (OS) adjusted for age and residual disease in the breast and nodes (RDBN).

RESULTS

Of the 1777 TNBC patients receiving NACT, 54 achieved pathologic complete response (pCR) and 755 had residual disease. Most patients were overweight with stage II disease (78%), grade 3 tumors (53%), and RDBN score 3 (42%). Compared to baseline, tumor size (30 vs. 15 mm; P < 0.0001) and Ki67 levels (63% vs. 48%; P < 2.2e - 16) generally decreased after NACT. Although only 5% of samples increased in size, Ki67 levels often remained unchanged (75%) or increased (0.9%) after treatment, respectively. However, 34% of patients discontinued treatment. Patients showing no changes in Ki67% had more unfavorable OS (P < 0.0001) and DSS (P = 0.00032), with significantly lower 5-year survival probabilities (OS: 66%; DSS: 78%) than those with decreased Ki67% (OS: 87%; DSS: 89%). All patients reaching pCR were alive 5 years after diagnosis. However, only the RDBN score was an independent predictor of survival in the multivariable analyses.

CONCLUSION

Ki67 often remained unchanged in TNBC patients treated with neoadjuvant chemotherapy, resulting in adverse clinical outcomes. These findings highlight the need for individualized treatment regimens and dynamic monitoring of TNBC patients with high Ki67 post-NACT.

DNA methylation profiles for breast cancer subtype classifications: A translational study from microarray to methylation-specific PCR (MSP)

Breast cancer subtypes can be categorized based on their gene expression profiles using immunohistochemistry into Luminal A, Luminal B, human epidermal growth factor receptor 2-positive (HER2+), and triple-negative breast cancer (TNBC) subtypes. However, immunohistochemistry has certain limitations that can lead to misclassification. DNA methylation is an epigenetic modification, and changes in the promoter region can alter gene expression and the quantity of functional protein synthesized, disrupting gene function. The aim of this study was to identify DNA methylation biomarkers for subtype classification in breast cancer using microarray and methylation-specific polymerase chain reaction (MSP) methods. DNA samples were extracted, subjected to bisulfite conversion and then used for both the microarray and MSP methods. This study successfully identified differentially methylated CpGs (DMCs) as biomarker for each subtype classification of breast cancer: Luminal A (hypermethylation of ADAMTSL2 gene; cg14397888), Luminal B (hypomethylation of ADAMTSL2 gene; cg14397888), HER2+ (hypermethylation of PTPRN2 gene; cg25910261), and TNBC (hypomethylation of LCLATl gene; cg15652532). The DMC biomarker found for the HER2+ subtype, hypermethylation in the PTPRN2 gene (cg25910261), has the potential to be used by healthcare providers to identify HER2+ patients and provide the HER2-targeted therapy to improve the patient's survival. In addition, our developed MSP method could produce an effective diagnostic tool for classifying the Luminal A and Luminal B subtypes, with accuracies of 75% and 76%, respectively.

Radiomics-clinical nomogram for preoperative tumor-node-metastasis staging prediction in breast cancer patients using dynamic enhanced magnetic resonance imaging

Background

Breast cancer is one of the most commonly diagnosed malignancies in women worldwide, and the disease burden continues to aggravate. The tumor-node-metastasis (TNM) staging information is crucial for oncology physicians to develop appropriate clinical strategies. This study aimed to investigate the value of a radiomics-clinical model for predicting TNM stage in breast cancer patients using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).

Methods

DCE-MRI images from 166 patients with pathologically confirmed breast cancer were retrospectively collected, including early stage (TNM0-TNM2) and locally advanced or advanced stage (TNM3-TNM4). Included patients were divided into a training cohort (n=116) and a test cohort (n=50). The radiomics, clinical and integrated models were constructed and a nomogram was established to distinguish the TNM0-TNM2 stage from the TNM3-TNM4 stage. Receiver operating characteristic (ROC) curves, calibration curves and decision curve analysis (DCA) were employed to assess the predictability of the models.

Results

Eighty-five patients were at the early stages, while 81 patients were at the other stages. In the training and test cohorts, the area under the curve (AUC) values for distinguishing early and advanced breast cancer were 0.870 and 0.818 for the nomogram, respectively. The nomogram calibration curves showed good agreement between the predicted and observed TNM stages in the training and test cohorts. The Hosmer-Lemeshow test showed that the nomogram fit perfectly in the two cohorts. DCA indicated that the nomogram displayed clear superiority in forecasting TNM staging over clinical and radiomic signatures.

Conclusions

Compared to traditional imaging methods, the clinical-radiomics nomogram acquired by DCE-MRI could potentially be utilized to preoperatively evaluate the TNM stage of breast cancer with relatively high accuracy. It can be an effective method to guide clinical decisions.

Differences in Clinical, Epidemiological, and Pathological Features of Breast Cancer in the Saudi Population: An Analytical Cross-Sectional Single Institution Study

Background: In Saudi Arabia, breast cancer is the most common malignancy among women, significantly impacting cancer-related morbidity and mortality. The country's unique demographics and rapid socioeconomic development contribute to distinct breast cancer patterns. Objective: To analyze demographic and pathological characteristics of breast cancer with an emphasis on associations between the Ki67 proliferation index, tumor stages, and molecular subtypes. Materials and Methods: An analytical cross-sectional study was conducted on 294 breast cancer patients from 2013 to 2019, recruited from the Comprehensive Cancer Center at King Fahad Medical City, Riyadh, Saudi Arabia. A one-way ANOVA and logistic regression were used to identify risk factors associated with elevated Ki67 levels. Significance was set at a 95% confidence level. Results: The mean age of patients was 51.58. Among them, 67% were overweight/obese, 21.1% were diabetic, and 17% were hypertensive. Approximately 28.9% of all tumors were classified as T3, 46.9% as Grade III, and 40% as Stage IV. Invasive ductal carcinomas (83.9%) were the most common. ER, PR, and HER2 expression were positive in 63.4%, 54.3%, and 34.9% of patients, respectively, with a high Ki67 index in 50.7%. As compared to Grade I cancer, grade II cancer increased the likelihood of elevated Ki67 by 41 times (p = 0.001), Grade III cancer by 7.43 times (p = 0.001), and Stage IV cancer by 2.26 times (p = 0.03). Conversely, invasive lobular carcinomas and other cancer types were significantly less likely to have high Ki67 levels (p < 0.05). Conclusions: Elevated Ki67 appeared to predict higher tumor grades and certain molecular subtypes cancer.

Ki-67 as a Prognostic Marker in Squamous Cell Carcinomas of the Vulva: A Systematic Review

Background/Objectives: To evaluate the prognostic impact of immunohistochemical ki-67 staining analysis regarding lymph node involvement and survival data (overall/progression-free survival) in squamous cell carcinoma of the vulva. Methods: A systematic literature search of English and German articles was conducted (PubMed, Embase, Scopus, Web of Science) from 1980 to December 2023, including the search terms "vulvar Neoplasms", "vulvar cancer", "vulvar carcinoma", "vulvar tumor", "vulvar tumour", "vulvar malignancy", "vulvar malignant", "ki-67", "MIB-1", "MIB1", "proliferative index", "proliferative activity", "mitotic index", and "mitotic count". Study quality was assessed using a two-step "mixed-criteria" approach; to synthesize study results, a narrative summary is provided. Results: In total, 13 studies were included in this systematic literature review. In general, two distinct methods of staining interpretation could be retrieved: A "pattern-based" method, as well as a cell count-based method. Ten of the included studies examined the relationship between ki-67 and lymph node involvement, nine studies included survival data as a parameter of interest; and only five studies defined both groin lymph node metastasis and survival data as outcome variables. While nine out of ten studies found no statistically significant association between ki-67 staining and lymph node metastasis, five out of nine studies determined an association between ki-67 status and overall survival, especially when employing a "pattern-based" method of staining interpretation. Conclusions: The prognostic value of ki-67 staining in terms of survival data has been reported ambivalently and should be subject to future studies. Furthermore, we did not find convincing evidence of an association between ki-67 and lymph node involvement.

Oxidative Phosphorylation Is a Metabolic Vulnerability of Endocrine Therapy-Tolerant Persister Cells in ER+ Breast Cancer

Despite adjuvant treatment with endocrine therapies, estrogen receptor-positive (ER+) breast cancers recur in a significant proportion of patients. Recurrences are attributable to clinically undetectable endocrine-tolerant persister cancer cells that retain tumor-forming potential. Therefore, strategies targeting such persister cells may prevent recurrent disease. Using CRISPR-Cas9 genome-wide knockout screening in ER+ breast cancer cells, we identified a survival mechanism involving metabolic reprogramming with reliance upon mitochondrial respiration in endocrine-tolerant persister cells. Quantitative proteomic profiling showed reduced levels of glycolytic proteins in persisters. Metabolic tracing of glucose revealed an energy-depleted state in persisters, in which oxidative phosphorylation was required to generate ATP. A phase II clinical trial was conducted to evaluate changes in mitochondrial markers in primary ER+/HER2- breast tumors induced by neoadjuvant endocrine therapy (NCT04568616). In an analysis of tumor specimens from 32 patients, tumors exhibiting residual cell proliferation after aromatase inhibitor-induced estrogen deprivation with letrozole showed increased mitochondrial content. Genetic profiling and barcode lineage tracing showed that endocrine-tolerant persistence occurred stochastically without genetic predisposition. Pharmacologic inhibition of mitochondrial complex I suppressed the tumor-forming potential of persisters in mice and synergized with the antiestrogen drug fulvestrant to induce regression of patient-derived xenografts. These findings indicate that mitochondrial metabolism is essential in endocrine-tolerant persister ER+ breast cancer cells and warrant the development of treatment strategies to leverage this vulnerability for treating breast cancer. Significance: Persister cancer cells that survive endocrine therapy exhibit increased energetic dependence upon mitochondria for survival and tumor regrowth potential, indicating that therapies targeting this metabolic dependency could help prevent disease recurrence.

The prognostic value of the tumor-stroma ratio compared to tumor-infiltrating lymphocytes in triple-negative breast cancer: a review

Previous literature extensively explored biomarkers to personalize treatment for breast cancer patients. The clinical need is especially high in patients with triple-negative breast cancer (TNBC) due to its aggressive nature and limited treatment modalities. This review aims to evaluate the value of tumor-infiltrating lymphocytes (TILs) and tumor-stroma ratio (TSR) as prognostic biomarkers in TNBC patients and assess their clinical potential. A literature search was conducted in PubMed, Embase, Emcare, Web of Science, and Cochrane Library. Papers comparing survival outcomes of TNBC patients with low/high or negative/positive TSR and immune cells were included. The most frequently mentioned subgroups of TILs were selected and reported in this review. Data from 43 articles on TILs and eight articles on TSR were included. Among TNBC patients, high CD8 expression was generally associated with better survival. Notable, the poor survival outcomes were related to high intra-tumoral PD-L1 expression, whereas high stromal PD-L1 expression more often was correlated with favorable outcomes. For the TSR, a high amount of stroma in the primary tumor of TNBC patients was consistently associated with worse survival. This review highlights that a high number of CD8-positive T-cells is a promising prognostic factor for TNBC patients. PD-L1 expression analyzed for intra-tumoral and stromal expression separately reports strong but contrasting information. Finally, the TSR shows potential to be an important prognostic marker, especially for TNBC patients. Utilizing both biomarkers, either on itself or combined, could enhance clinical decision-making and personalization of treatment.

Biomarker-Directed Radiotherapy in Breast Cancer: A Narrative Review

Importance

Integration of molecular biomarker information into systemic therapy has become standard practice in breast cancer care. However, its implementation in guiding radiotherapy (RT) is slower. Although postoperative RT is recommended for most patients after breast-conserving surgery and, depending on risk factors, following mastectomy, emerging evidence has indicated that patients with low scores on gene expression signatures or selected clinical-pathological features may have very low local recurrence rates. This narrative review explored the potential of biomarker-directed personalized RT approaches, which may optimize treatment strategies and be associated with improved patient outcomes and experiences.

Observations

Distinctions between prognostic and predictive biomarkers were highlighted, emphasizing the importance of analytical and clinical validity in biomarker-based studies. Findings from studies investigating the prognostic and predictive value of various genomic signatures and immunohistochemical markers for guiding breast RT were presented. These included the Adjuvant Radiotherapy Intensification Classifier and the Profile for the Omission of Local Adjuvant Radiation, which have shown potential in predicting RT benefits. The genomic-adjusted radiation dose and role of tumor-infiltrating lymphocytes were also discussed. Ongoing clinical trials exploring the use of biomarkers in ductal carcinoma in situ and invasive breast cancer to refine RT decision-making were illustrated.

Conclusions and Relevance

The results of this narrative review suggest that evidence-based shared decision-making is crucial to optimize treatment according to the individual's predicted benefits and risks along with their personal preferences. Incorporation of biomarker-directed approaches in RT for breast cancer may hold promise for personalized treatment, potentially facilitating omission of RT for patients at low risk of recurrence, while identifying those who may benefit from intensified therapy. This personalized RT approach may be associated with improved clinical outcomes and quality of life and facilitate decision-making for people with breast cancer. However, there remains a need for robust clinical and analytical validation of biomarkers to ensure reliability and clinical utility for RT optimization.

Omitting Radiotherapy after Breast-Conserving Surgery in Luminal A Breast Cancer: The LUMINA Study

The modern generation of trials evaluating the role of adjuvant radiation have turned to genomic profiling as a further risk stratification tool. The LUMINA trial by Whelan and colleagues, published in the New England Journal of Medicine , applied Ki67 testing to identify those with luminal A disease and evaluated locoregional outcomes with breast-conserving surgery and endocrine therapy alone. This article was reviewed at the Canadian Association of General Surgeons' "Evidence-Based Reviews in Surgery" webinar series. Here, we present the Evidence-Based Reviews in Surgery panel's methodologic review and clinical commentary. The LUMINA study demonstrated very low rates of local recurrence in low-risk patients with luminal A biologic subtype treated with breast-conserving surgery and endocrine therapy alone without radiation. Although the LUMINA study was rigorously designed and executed, there are significant pragmatic limitations to the implementation of the proposed approach using their protocol. We advocate that there is no "one-size-fits-all" approach to early estrogen receptor + breast cancer. The choice of treatment strategy should strongly consider patient goals and preferences, with the need for incorporation of quality of life and patient-reported endpoints into future studies evaluating this population to help guide these nuanced decisions.

Low-Invasive Biomarkers of Canine Mammary Tumours

Canine mammary tumours (CMTs) are the most common type of tumours in older bitches. An early, precise and low-invasive diagnosis is essential, due to some CMTs being malignant and having a poor prognosis. Fine needle aspiration cytology (FNAC) and blood tests are both low-invasive diagnostic methods that have been used in veterinary medicine. However, the perfect biomarkers should be identified to diagnose and evaluate the prognosis of CMTs. This review focuses on biomarkers that can be tested by FNA or blood samples based on current literature. Until now, the most studied biomarkers of FNAC, such as Ki-67, human epidermal growth factor receptor 2 (HER-2), oestrogen receptor (ER), progesterone receptor (PR), P53, E-cadherin and cyclooxygenase-2 (COX-2). Some common blood biomarkers that have been widely studied include lactate dehydrogenase (LDH), C-reactive protein (CRP), carbohydrate antigen 15-3 (CA15-3) and carcinoembryonic antigen (CEA). The novel biomarkers will also be mentioned: cancer stem cells (CSCs), circulating tumour cells (CTCs), miRNAs and circulating cell-free DNA (cfDNA); they are all useful markers. Copper ion and serum ferritin (SF) are good markers of human breast cancer; they may be candidates of CMTs biomarkers, too. In conclusion, many biomarkers are suitable for diagnosing and/or prognosing CMTs; combining a couple of them can increase the specificity; more detailed research should be done.

Assessing neoadjuvant treatment response through serum human epidermal growth factor receptor 2 (HER2) dynamics

Background

Human epidermal growth factor receptor 2 (HER2)-positive invasive breast cancer (BC) accounts for 15-20% of all cases, requiring HER2-targeted neoadjuvant therapy (NAT). Despite the success of trastuzumab and other HER2-targeted treatments, many patients still experience inadequate responses, highlighting the need for more accurate and accessible biomarkers to predict treatment outcomes. Serum HER2 (sHER2) levels, as a non-invasive biomarker, have shown promise in monitoring treatment response; however, the role of sHER2 dynamics during treatment remains underexplored. The aim of this study was to investigate the potential of sHER2 dynamics as a predictor of pathological complete response (pCR) in HER2-positive BC patients undergoing NAT.

Methods

This retrospective study analyzed 120 HER2-positive BC patients who underwent standard NAT followed by surgery at Fudan University Shanghai Cancer Center (FUSCC). sHER2 levels were measured at three time points: baseline, after the second cycle of therapy (C2), and at surgery. Logistic regression analysis was used to assess the association between changes in sHER2 levels and the achievement of pCR. The study also examined the influence of other clinicopathological factors such as estrogen receptor (ER) status, Ki67, and tissue HER2 (tHER2) levels on pCR.

Results

During NAT, sHER2 levels showed a significant decline, with a more pronounced reduction observed in patients achieving pCR. The greatest reduction in sHER2 levels after C2 was strongly associated with pCR. Both univariate and multivariate analyses identified significant reductions in sHER2 levels after C2 and ER-negative status as independent predictors of pCR. Notably, sHER2 changes from baseline to C2 demonstrated a stronger predictive value for pCR compared to changes observed later in treatment.

Conclusions

Our study confirms that reductions in sHER2 levels after C2 are a strong indicator of favorable treatment response in HER2-positive BC patients undergoing NAT. Monitoring sHER2 dynamics early in treatment can serve as a useful, non-invasive biomarker to predict pCR and may guide therapeutic decisions in clinical practice.

A bottom-up initiated digital external quality assessment scheme for the state-of-the-art pathology in Sweden: reduced variability between pathology departments

External quality assessment (EQA) schemes for pathology are essential, yet large/international programmes do not assess morphology-based biomarkers or address local/regional needs. This study outlines bottom-up initiated, flexible Swedish Digital Pathology EQA rounds for breast pathology, and presents results from the 2021 and 2023 rounds. Six breast carcinoma cases were selected for each EQA round by the Swedish Breast Pathology Expert Group (KVAST Breast). Whole tissue slides stained with HE, IHC, and ISH were anonymized, digitized, and uploaded to the digital EQA platform. Biomarkers were selected based on national registry data analysis and pathologist and clinician feedback. The 2021 round assessed Nottingham grade (NHG), oestrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2), while the 2023 round focused on NHG, HER2-low, and global Ki67. Twenty-seven pathology departments participated. From 2021 to 2023, the variability of NHG assessment on digital slides improved from moderate to substantial (kappa 0.50; 95% CI 0.45-0.55 to 0.64; 95% CI 0.60-0.68), with better agreement for NHG3 than NHG1. Participants showed substantial and excellent agreement in ER (kappa 1) and PR (0.75 (95% CI 0.69-0.82). We found similar agreement in distinguishing HER2 IHC 0 (0.78; 95% CI 0.72-0.82) and HER2 IHC 3 + (0.94; 95% CI 0.88-1.00) from other HER2 IHC scores. Participants showed substantial agreement in detecting Ki67 high and Ki67 low cases (kappa 0.65; 95% CI 0.60-0.71 and 0.69; 95% CI 0.64-0.74, respectively). This digital EQA identifies local issues and complements large international EQAs to address challenges in the rapidly changing biomarkers of cancer therapy.

The association between Ki-67 expression and survival in breast cancer subtypes: a cross-sectional study of Ki-67 cut-point in northern Thailand

BACKGROUND

Breast cancer is a major health concern worldwide, and Ki-67 level index is a prognostic factor that indicates tumor proliferation and predicts survival outcomes. However, the standard Ki 67 cut-off level varies between local laboratories, and in Thailand, there is no established optimal cut-off level.

OBJECTIVE

This study aimed to determine the optimal cut-off point for Ki-67 expression and investigate the association between Ki-67 levels and other prognostic factors with 8-year overall survival.

METHOD

A retrospective review of Ki-67 levels was conducted in non-metastatic breast cancer patients treated at Maharaj Nakorn Chiangmai hospital from January 2013-December 2015, including 507 breast cancer patients.

RESULTS

The ROC curve analysis identified the optimal Ki-67 cut-point as ≥ 30%, with 75% sensitivity and 48.85% specificity. Age over 60 was associated with higher mortality regardless of cancer stage. Locally advanced staging, nodal involvement, Ki-67 ≥ 30%, and triple-negative subtype correlated with poorer survival. Even after adjustments, these factors remained significant in prognostic evaluation. Chemotherapy notably improved survival, especially in high Ki-67 (≥ 30) patients. However, this effect was not seen in low Ki-67 patients. High Ki-67 patients receiving chemotherapy showed improved survival in early-stage, node-negative cases compared to those who did not receive chemotherapy. HER2-positive patients with high Ki-67 benefited from chemotherapy, but statistical significance was not reached in hormone-positive patients.

CONCLUSION

This study identified the optimal cut point for Ki-67 in Northern Thailand as 30%. Patients with KI-67 above 30% show significantly lower 8-year survival rates. This is especially relevant for low-risk patients, like those with hormonal subtypes or early-stage nodal negativity. In these cases, KI-67 becomes crucial for treatment decisions. Our study not only aids Northern Thailand's understanding but also aligns with broader research, emphasizing KI-67's vital role in planning treatment for low-risk breast cancer patients.

Clinico-pathological factors predicting pathological response in early triple-negative breast cancer

Pathological complete response (pCR) after neoadjuvant chemoimmunotherapy (NACi) is associated with improved patient outcomes in early triple-negative breast cancer (TNBC). This study aimed to identify factors associated with pCR after NACi. This cohort included all patients with stage II-III TNBC treated with NACi who underwent surgery at Institut Curie hospitals between 08/2021-06/2023. Among 208 patients, the overall pCR rate was 70% and was similar in ER < 1% (69%) and ER-low TNBC (73%, p = 0.6). In a multivariate model, Ki-67 ≥ 30% (OR 5.19 [1.73-17.3]), centralized TILs ≥ 30% (OR = 3.08 [1.42-7.04]), absence of DCIS at initial biopsy (OR = 2.56 [1.08-6.25]) and germline mutations in homologous recombination genes (OR = 9.50 [2.37-67.7]) remained strong independent predictors of pCR. These findings may guide treatment decisions in patients with TNBC undergoing NACi. Almost all patients with germline mutations in HR genes achieved pCR, supporting de-escalation trials. We suggest that ER-low tumors should be managed as TNBC tumors.

Dynamics of molecular heterogeneity in high-risk luminal breast cancer-From intrinsic to adaptive subtyping

We evaluate therapy-induced molecular heterogeneity in longitudinal samples from high-risk, hormone-receptor positive/HER2-negative breast cancer patients with residual tumor after neoadjuvant chemotherapy from the Penelope-B trial (NCT01864746; EudraCT 2013-001040-62). Intrinsic subtypes are prognostic in pre-therapeutic (Tx) samples (n = 629, p < 0.0001) and post-Tx residual tumors (n = 782, p < 0.0001). After neoadjuvant chemotherapy, a shift of intrinsic subtypes is observed from pre-Tx luminal (Lum) B to post-Tx LumA, with reverse transition back to LumB in metastases. In a combined analysis of 540 paired pre-Tx and post-Tx samples, we identify five adaptive clusters (AC-1-5) based on transcriptomic changes before and after neoadjuvant chemotherapy. These AC-subtypes are prognostic beyond classical intrinsic subtyping, categorizing patients into groups with excellent prognosis (AC-1 and AC-2), poor prognosis (AC-3 and AC-4), and very poor prognosis (AC-5, enriched for basal-like subtype). Our analysis provides a basis for an extended molecular classification of breast cancer patients and improved identification of high-risk patient populations.

Exploring the Potential of Adjuvant CDK4/6 Inhibitors in Hormone Receptor-Positive Early Breast Cancer: A Consistent Approach for All

BACKGROUND/OBJECTIVES

Hormone receptor-positive, HER2-negative breast cancer is the most common subtype, with endocrine therapy as the standard treatment. Despite the advancements in adjuvant endocrine therapy, recurrence remains a challenge, particularly in high-risk patients. Recent trials on cyclin D kinase 4/6 (CDK4/6) inhibitors in adjuvant therapy have shown promise in reducing early recurrence and improving survival.

METHODS

This review analyzes the clinical evidence supporting the use of CDK4/6 inhibitors, focusing on the NATALEE and monarchE trials, which demonstrate comparable efficacy and manageable safety profiles for ribociclib and abemaciclib.

RESULTS AND CONCLUSIONS

Ribociclib, with its broader applicability and impact on the decision making for axillary lymph node surgery, may be the preferred option in high-risk populations. The review also addresses unanswered clinical questions and highlights the need for ongoing research to optimize the adjuvant therapy strategies.

Intratumoral heterogeneity of Ki67 proliferation index outperforms conventional immunohistochemistry prognostic factors in estrogen receptor-positive HER2-negative breast cancer

In breast cancer (BC), pathologists visually score ER, PR, HER2, and Ki67 biomarkers to assess tumor properties and predict patient outcomes. This does not systematically account for intratumoral heterogeneity (ITH) which has been reported to provide prognostic value. This study utilized digital image analysis (DIA) and computational pathology methods to investigate the prognostic value of ITH indicators in ER-positive (ER+) HER2-negative (HER2-) BC patients. Whole slide images (WSIs) of surgically excised specimens stained for ER, PR, Ki67, and HER2 from 254 patients were used. DIA with tumor tissue segmentation and detection of biomarker-positive cells was performed. The DIA-generated data were subsampled by a hexagonal grid to compute Haralick's texture indicators for ER, PR, and Ki67. Cox regression analyses were performed to assess the prognostic significance of the immunohistochemistry (IHC) and ITH indicators in the context of clinicopathologic variables. In multivariable analysis, the ITH of Ki67-positive cells, measured by Haralick's texture entropy, emerged as an independent predictor of worse BC-specific survival (BCSS) (hazard ratio (HR) = 2.64, p-value = 0.0049), along with lymph node involvement (HR = 2.26, p-value = 0.0195). Remarkably, the entropy representing the spatial disarrangement of tumor proliferation outperformed the proliferation rate per se established either by pathology reports or DIA. We conclude that the Ki67 entropy indicator enables a more comprehensive risk assessment with regard to BCSS, especially in cases with borderline Ki67 proliferation rates. The study further demonstrates the benefits of high-capacity DIA-generated data for quantifying the essentially subvisual ITH properties.

High comorbidity and tumor proliferation predict survival of localized breast cancer patients after curative surgery: A retrospective analysis of real-world data in Finland

BACKGROUND

The aim of this study was to analyze the characteristics of breast cancer patients and their impact on real-world treatment and survival outcomes.

PATIENTS AND METHODS

We conducted a retrospective study including all patients newly diagnosed with breast cancer during 2019 in the Southwest Finland. We identified 458 patients diagnosed with either localized (n = 435, 95 %) or metastatic (n = 23, 5 %) breast cancer.

RESULTS

In localized breast cancer, the five-year overall survival (OS) was 90.9 %, while the five-year disease-free survival (DFS) was 93.5 %. In metastatic breast cancer, the five-year progression-free survival (PFS) was 13.0 % and five-year OS 34.2 %. The median PFS was 10.9 months (95 % CI 2.5-19.4 months) and median OS was 30.6 months (lower 95 % CI 6.9 months - not reached). In the univariate analyses, the most important tumor-specific parameters predicting decreased DFS were tumor proliferation index >20 %, low estrogen receptor expression status and tumor size >2 cm. Univariate predictors for decreased OS included Eastern Cooperative Oncology Group (ECOG) performance status ≥2 and Charlson Comorbidity Index (CCI) score ≥3. In the multivariable analyses, CCI score ≥3 and high proliferation index (21-100 % vs. 0-20 %) predicted poorer DFS, while CCI score ≥3 and increased stage (stage 2 vs. 1) predicted poorer OS. The administration of post-operative radiotherapy was significant in the multivariable analyses of both DFS (HR 4.23, 95 % CI 1.85-9.67, p = 0.0006) and OS (HR 6.84, 95 % CI 3.33-14.02, p < 0.0001).

CONCLUSION

Our results demonstrate that careful clinical evaluation of ECOG and comorbidities, alongside well-established tumor characteristics predict patient survival in a population where overall five-year survival in breast cancer is over 90 %.

Can Ki-67 serve as a suitable marker to indicate the necessity of staging diagnostics in cases of low-risk breast cancer?

BACKGROUND

For many years, staging tests have not been routinely employed for low-risk early breast cancer (EBC). However, the role of Ki-67 in determining the need for staging tests in low-risk EBC remains unclear. Our study aimed to assess the number and types of staging diagnostics, additional imaging, false-positive results, and rate of distant metastases in low-risk EBC with low and high Ki-67 (< / ≥ 25%).

METHODS

This is a retrospective, single institution cohort study. All patients with newly diagnosed low-risk breast cancer at the University Medical Center in Freiburg in 2017 and 2021 were included. Low-risk was defined as clinical tumor stage T1/2, node negative (N0), hormone receptor positive, HER2 negative, asymptomatic EBC. Information on demographics, clinical and pathological characteristics, as well as number and type of performed staging diagnostics was obtained. Rate and type of additional imaging or follow-up diagnostics due to suspicious findings was analyzed. The patients were divided into two groups (Ki-67 < and ≥ 25%) and rates of distant metastases, performed staging diagnostics and false positive rates were compared.

RESULTS

A total of 189 patients with low-risk EBC were identified, with 54% (n = 102) having Ki-67 < 25% and 46% (n = 87) having Ki-67 ≥ 25%. Risk for distant metastases was 0% in Ki-67 < 25% and 1.1% in patients with Ki-67 ≥ 25% (p = 0.46). Due to suspicious findings in the initial staging diagnostic, additional imaging was required for 11.8% (n = 12) of patients with Ki-67 < 25% compared to 19.5% (n = 17) of patients with Ki-67 ≥ 25% (p = 0.16). False positive rates did not differ significantly between the two groups (7.6% in Ki-67 < 25% vs. 9.8% in Ki-67 ≥ 25%; p = 0.55).

CONCLUSION

Distant metastases are rare in low-risk EBC. All in all, staging diagnostics should not be routinely employed in this patient population. Only patients with high Ki-67 developed distant metastases. In these cases, staging diagnostics may be discussed with the patient.

Retained Rim Enhancement in Mucinous Breast Cancer Suggests Aggressive Biology: A Case Report

A 44-year-old premenopausal woman was referred to our hospital for a detailed examination of her left rapidly growing breast mass. Mammography only showed focal asymmetric density. Ultrasound showed a 14 mm oval mass with distinct borders, a high depth/width rate of 0.79, numerous punctate echogenic foci against background low echoes, and slightly enhanced posterior echoes. Magnetic resonance imaging (MRI) of the mass showed low signal intensity on T1-weighted images and high signal intensity with a slightly low signal intensity area in the mass center on fat-suppressed T2-weighted images. Subtraction MRI depicted early and retained rim enhancement patterns. The patient underwent a core needle biopsy of the breast mass. Pathological study showed that the tumor had atypical cells growing in a papillary fashion with abundant mucus, leading to the diagnosis of mucinous breast cancer. The patient, therefore, underwent breast-conserving surgery and sentinel node biopsy. A post-operative pathological study showed that the tumor had cancer cells mainly distributed in a ring fashion and extremely sparse cancer cells with thick fibrous septa in the mass center. Immunostaining showed that the mucinous breast cancer had estrogen and progesterone receptor positivities, human epidermal growth factor receptor type 2 equivocation, and a high Ki-labelling index of 50%. Diagnostic physicians should note that retained rim enhancement may predict the biological aggressiveness of mucinous breast cancers.

Prognostic Impact of Stimulator of Interferon Genes Expression in Triple Negative Breast Cancer

BACKGROUND

Patients with triple negative breast cancer (TNBC) who have a poor response to neoadjuvant chemotherapy (NAC) have worse survival and new treatment strategies need to be developed. TNBC is considered a subtype in which the cyclic GMP-AMP synthase (cGAS) is linked to the stimulator of interferon genes (STING) pathway, an innate immune response that recognizes cytosolic nucleic acid components, is activated when DNA damage occurs, and is attracting attention as a new therapeutic target.

METHODS

Patients with TNBC who underwent surgery following NAC and for whom pre- and post-treatment tissue specimens were available were enrolled in this study. To examine the association of STING expression with immune profiles and prognosis, STING, cGAS, CD8, and programmed cell death ligand 1 (PD-L1) expressions in tumor cells (TCs) and immune cells (ICs), and tumor infiltrating lymphocytes (TILs) were assessed using immunohistochemistry of specimens obtained at pre-treatment and at surgery.

RESULTS

Ninety-one cases were eligible, of which 68 cases were evaluable and included in the analysis. The high STING expression at baseline was marginally correlated with TILs, but not with CD8+ cells or PD-L1 expression. Patients with sustained high expression of STING before and after NAC had a significantly poorer prognosis than that of others for distant recurrence-free survival and breast cancer-specific survival independent of nodal status, lymphatic invasion and therapeutic effects (p = 0.024 and 0.014, respectively).

CONCLUSION

TNBCs with sustained high STING expression following NAC demonstrated a poor prognosis and will be a target for new treatment strategies.

An overview about biomarkers in breast cancer: Insights into the diagnostic and prognostic significance

Breast cancer (BC) is one of the most significant neoplasms globally due to its high incidence and mortality, particularly among females. As a highly heterogeneous pathology, biomarkers are essential for characterizing specific tumors. Currently, several biological processes are well-described in the context of this neoplasm, such as alterations in BRCA1/2, HER, and pathways involving estrogen and progesterone hormone receptors. These studies have enabled the use of these findings as more precise methods for diagnosis, prognosis, and treatment. However, beyond patients who do not exhibit these classic markers, some individuals within the same risk group respond differently to treatment. Therefore, the search for biological markers that can improve diagnosis, aid in stratification, or serve as therapeutic targets is continuous and urgent. Genetic signatures have led to molecular tests currently used in clinical practice, though certain limitations persist. Understanding genetic and epigenetic mechanisms facilitates the identification of potential biomarkers. Biomarker targets must undergo experimental and clinical trials on samples of significant size before reaching clinical utility. In this review, we compile the classical markers and describe the potential use of other markers associated with the biological processes of this neoplasm.

Advances in research on malignant tumors and targeted agents for TOP2A (Review)

The DNA topoisomerase isoform topoisomerase IIα (TOP2A) is essential for the condensation and segregation of cellular mitotic chromosomes and the structural maintenance. It has been demonstrated that TOP2A is highly expressed in various malignancies, including lung adenocarcinoma (LUAD), hepatocellular carcinoma (HCC) and breast cancer (BC), associating with poor prognosis and aggressive tumor behavior. Additionally, TOP2A has emerged as a promising target for cancer therapy, with widespread clinical application of associated chemotherapeutic agents. The present study explored the impact of TOP2A on malignant tumor growth and the advancements in research on its targeted drugs. The fundamental mechanisms of TOP2A have been detailed, its specific roles in tumor cells are analyzed, and its potential as a biomarker for tumor prognosis and therapeutic targeting is highlighted. Additionally, the present review compiles findings from the latest clinical trials of relevant targeted agents, information on newly developed inhibitors, and discusses future research directions and clinical application strategies in cancer therapy, aiming to propose novel ideas and methods.

Detection of breast cancer lesions using APT weighted MRI: a systematic review

Amide proton transfer (APT) is a novel magnetic resonance imaging (MRI) technique that has shown promising ability to study cancers. This paper systematically reviewed the literature on the use of APT MRI in the prognosis of breast cancer. A literature search was conducted on Pubmed and Embase and a total of 14 articles comprising 775 patients were included in the review. APT MRI had the ability to distinguish between benign and malignant lesions with an AUC as high as 0.959. There is a positive correlation between APT signal intensity and tumor grade/stage as well as Ki-67, whereas no correlation was found with ER/PR/Her-2 receptor status. There was a greater decrease in APT signal intensity after neoadjuvant chemotherapy (NAC) in responders compared to non-responders, suggesting that APT MRI may serve as a valuable supplemental tool in the early identification of chemotherapy response. APT has the potential to complement with other imaging methods in the diagnosis, prognosis, treatment monitoring, and management of breast cancer. Additional studies and standardization of APT acquisition methods are needed.

High Ki67 expression, HER2 overexpression, and low progesterone receptor levels in high-grade DCIS: significant associations with clinical practice implications

Simple summary

We investigated the role of Ki67, a ubiquitous marker in cancer, within the context of ductal carcinoma in situ (DCIS), a precursor of invasive breast cancer. Through rigorous analysis of histopathological and immunopathological samples from a substantial cohort, this study revealed robust correlations between heightened Ki67 expression, diminished progesterone (PR) levels, and HER2 overexpression, indicative of aggressive DCIS phenotypes. These findings offer novel insights into the surrogate immunomolecular subtyping landscape of DCIS, potentially refining risk stratification and therapeutic approaches. This elucidation underscores the translational significance of Ki67 as a prognostic and predictive biomarker in DCIS, with implications for personalized treatment paradigms and patient outcomes.

Background

The Ki67 proliferation index is widely used in various tumors, including invasive breast carcinoma (IBC). However, its prognostic utility is often constrained by technical complexity. Its diagnostic and clinical significance in ductal carcinoma in situ (DCIS) remains uncertain. We studied Ki67 immunohistochemistry interobserver diagnostic agreement at different cutoff values in high-grade DCIS. Additionally, we investigated the associations between Ki67 expression, PR levels, and human epidermal growth factor receptor 2 (HER2) in high-grade DCIS among various subtypes (Luminal (Lum) A, LumB HER2-, LumB HER2+, HER2-enriched, and triple-negative)).

Methods

Using histopathological specimens from 484 patients diagnosed with DCIS between 1996 and 2018, we implemented the 2013 St. Gallen recommendations for surrogate immunomolecular subtyping of IBC. Subtypes were classified, and the Ki67 interobserver diagnostic agreement between Counting Pathologist 1 (CP1) and CP2 was calculated using Cohen's kappa coefficient at various cutoff values.

Results

The Cohen's kappa coefficient for interobserver agreement between CP1 and CP2 was κ = 0.586, indicating moderate agreement. Ki67 levels varied significantly among subtypes (p < 0.0001), with a median Ki67% being higher in cases with invasive components (p = 0.0351). Low PR combined with high Ki67% was significantly associated with HER2 overexpression (p = 0.0107).

Conclusions

Interobserver agreement for the Ki67 count was moderate. Ki67 expression showed considerable variability in high-grade DCIS. Low PR levels combined with high Ki67 expression were linked to HER2 overexpression, showing possible clinical implications for identifying high-risk DCIS.