Prosigna® breast cancer assay: histopathologic correlation, development, and assessment of size, nodal status, Ki-67 (SiNK™) index for breast cancer prognosis

Evaluation and Comparison of Prognostic Multigene Tests in Early-Stage Breast Cancer: Which Is the Most Effective? A Literature Review Exploring Clinical Utility to Enhance Therapeutic Management in Luminal Patients

Breast cancer is the most common malignancy affecting women, marked by significant complexity and heterogeneity. This disease includes multiple subtypes, each with unique biological features and treatment responses. Despite significant advancements in detection and therapy, challenges remain, particularly in managing aggressive forms like triple-negative breast cancer and overcoming drug resistance. Breast cancer classification and subtype determination are typically performed by immunohistochemistry (IHC) method, which assesses four key markers (ER, PR, HER2, KI67); however, due to the recognized issues with this approach-especially regarding the evaluation of Ki67-there is a risk of misclassification. Patients who may be suitable for chemotherapy could miss possible advantages and only experience needless toxicity as a result of improper treatment decisions. Molecular profiling has improved breast cancer management, enabling the creation of multigene prognostic tests (MPTs) like Oncotype Dx, MammaPrint, Prosigna, Endopredict, and Breast Cancer Index which assess gene expression profiles to more accurately predict recurrence risks. These tools help personalize treatment, identifying patients who can avoid chemotherapy and/or extended endocrine therapy. While many MPTs are available, only Oncotype Dx and MammaPrint have prospective validation, with Prosigna providing additional prognostic insights by incorporating clinical variables. Molecular tests are especially usefull in the "gray zone," which includes tumors measuring between 1 and 3 cm with 0-3 positive lymph nodes and an intermediate proliferation index. However, their clinical utility has not been definitively established, and significant differences exist between them. This article provides an in-depth analysis of established genomic assays, including testing procedures, clinical validity, utility, diagnostic frameworks, and methodologies. Our comparison aims to improve early breast cancer management by guiding pathologists and oncologists in optimizing the use of genomic assays in clinical practice. By presenting this information, we aim to enhance understanding of the clinical utility and effectiveness of these assays, supporting the development of personalized treatment strategies for early breast cancer patients. Genomic assays offer important insights that can support treatment decisions in early-stage breast cancer, especially when used alongside other clinical evaluations, predictive tools, and management guidelines. While multiple gene expression profiling tests are available, they classify patients differently and are not interchangeable; therefore, their application should be at the clinician's discretion during the decision-making process. It is essential that these tests are not the sole factor in determining the best treatment plan: other clinical considerations and patient preferences should also play a significant role in guiding treatment decisions.

Development and verification of a radiomics model to forecast Ki67 index and prognosis in advanced gastric tubular adenocarcinoma

BACKGROUND

The purpose of this research is to evaluate the predictive capabilities of a radiomics model for the Ki67 index and its correlation with prognosis in advanced gastric tubular adenocarcinoma patients.

METHODS

Clinical data from 213 patients were analyzed, categorizing patients into high and low Ki67 index groups. The radiomic features of 192 patients were selected by lasso method and the model was constructed, which was validated using the TCIA dataset. Univariate and multivariate Cox regression analyses were used to further analyze clinical features associated with the prognosis of gastric cancer, radiomic models are also used to assess patient outcomes.

RESULTS

The radiomics model demonstrated moderate accuracy, with AUC values of 0.634, 0.666, and 0.602 for the training, validation 1, and validation 2 sets, respectively. Additionally, a significant correlation was found between the Ki67 index and radiomics scores, a higher Ki67 index was associated with improved outcomes. Kaplan-Meier analysis showed distinct survival differences between patients with high and low radiomics scores, indicating that higher scores predict better prognosis.

CONCLUSIONS

The radiomics model accurately predicts the Ki67 index and correlates with prognosis in advanced gastric tubular adenocarcinoma, offering valuable insights for clinical decision-making and personalized treatment strategies.

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.

A comprehensive analysis of the prognostic value, expression characteristics and immune correlation of MKI67 in cancers

Background

nuclear-associated antigen Ki67 (Ki67) emerges as a clinically practical biomarker for proliferation assessment among many cancer types. However, the definite prognostic value of Ki67 against a specific cancer type has remained vague. This study aims to perform a comprehensive pan-cancer analysis of the prognosis value of Ki67 across various cancer types.

Methods

This study explored the expression, prognostic value, and tumor-infiltrating immune of MKI67 in the TCGA database by pan-cancer, and then performed immunohistochemical, correlation analysis and prognostic analysis using 10028 patients of the top 10 cancer patients in China we collected. The correlation between MKI67 expression and survival outcome, clinical features, MSI, TMB, and tumor-infiltrating immune cells by TCGA database, xCell, and TIMER algorithms.

Results

MKI67 expression was significantly upregulated across varied cancer types verified by datasets. We found MKI67 expression was significantly associated with poor prognosis in LUADLUSC, LIHC, and BRCA patients, but good prognosis in COADREAD and READ patients via Kaplan-Meier survival analysis using 10028 patients collected. These results of our validation were generally consistent with TCGA database except BRCA, COADREAD and READ. Meanwhile, upregulation of MKI67 elevates the degree of immune infiltration of several immune cell subtypes, such as functional T cells, CD4+ T cells, and CD8+ T cells, as well as, MKI67 was related to Cell cycle, Oocyte meiosis, p53 and other pathways.

Conclusion

Our comprehensive analysis may supply useful guidance on MKI67 applicability across various cancer types. These observed results contribute to the promise of MKI67 in a realistic clinical setting and improve the outcomes of cancer patients.

The Evolving Role of Genomic Testing in Early Breast Cancer: Implications for Diagnosis, Prognosis, and Therapy

Multigene prognostic genomic assays have become indispensable in managing early breast cancer (EBC), offering crucial information for risk stratification and guiding adjuvant treatment strategies in conjunction with traditional clinicopathological parameters. The American Society of Clinical Oncology (ASCO) guidelines endorse these assays, though some clinical contexts still lack definitive recommendations. The dynamic landscape of EBC management demands further refinement and optimization of genomic assays to streamline their incorporation into clinical practice. The breast cancer community is poised at the brink of transformative advances in enhancing the clinical utility of genomic assays, aiming to significantly improve the precision and effectiveness of both diagnosis and treatment for women with EBC. This article methodically examines the testing methodologies, clinical validity and utility, costs, diagnostic frameworks, and methodologies of the established genomic tests, including the Oncotype Dx Breast Recurrence Score®, MammaPrint, Prosigna®, EndoPredict®, and Breast Cancer Index (BCI). Among these tests, Prosigna and EndoPredict® have at present been validated only on a prognostic level, while Oncotype Dx, MammaPrint, and BCI hold both a prognostic and predictive role. Oncologists and pathologists engaged in the management of EBC will find in this review a thorough comparison of available genomic assays, as well as strategies to optimize the utilization of the information derived from them.

Update on the Use of Molecular Subtyping in Breast Cancer

The standard of care for invasive cancers of the breast has been and continues to be to evaluate them for breast prognostic markers: estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 by immunohistochemistry. Over 2 decades ago, a study was the first to report on the molecular subtypes of breast cancer. Four main subtypes were reported. Since then there have been some changes in the molecular subtype classification, but overall many studies have shown that this subtyping has clinical prognostic and predictive value. More recently, molecular assays have been developed and studies have shown similar clinical prognostic and predictive value. We reviewed the literature for studies evaluating the clinical significance of all 3 of these methods of evaluation and the follow-up findings of that review are presented below.

Collagen content and C-X-C motif chemokine ligand 12 expression in neoplastic breast stroma

OBJECTIVE

This study aimed to evaluate the expression of C-X-C motif chemokine ligand 12 and its C-X-C chemokine receptor type 4, and the tumor-stroma ratio using collagen stromal content of breast cancer samples, correlating it with clinicopathological data.

METHODS

Through a retrospective cohort study, samples were obtained from female patients, over 18 years of age, with the disease in stages 1-4, who underwent mastectomy or lumpectomy. The biopsies were provided by the Oncology sector of the Hospital das Clínicas of Universidade Federal de Pernambuco, Recife city, in 2011-2014, including samples of invasive ductal carcinoma, ductal carcinoma in situ, or benign changes (fibroadenoma and hypertrophy), which were analyzed between 2020 and 2022 by immunohistochemistry for the expression of stromal cell characteristics. Collagen content was tested by Gomori staining and digital analysis of images.

RESULTS

Absence of stromal expression of C-X-C motif chemokine ligand 12 was associated with longer disease-free survival (disease-free survival=0.481), and expression of C-X-C chemokine receptor type 4 was associated with lower disease-free survival. An association was observed between clinicopathological variables and stromal expression of chemokines, that is, an association of stromal C-X-C motif chemokine ligand 12 with histological grade, angiolymphatic invasion, and an association between C-X-C chemokine receptor type 4 expression and histological grade. Analyses of digital pixels images of collagen and tumor cells showed a lower percentage of collagen in the invasive ductal carcinoma samples (39%), unlike samples without neoplasms (78%).

CONCLUSION

Low expression of C-X-C motif chemokine ligand 12 may be associated with a worse prognosis for breast cancer. Collagen staining analyzed using digital images represents an opportunity for clinical application and is indicative of the prognosis of the tumor microenvironment in breast carcinoma.

Ki67 and breast cancer mortality in women with invasive breast cancer

BACKGROUND

The percentage of cells staining positive for Ki67 is sometimes used for decision-making in patients with early invasive breast cancer (IBC). However, there is uncertainty regarding the most appropriate Ki67 cut points and the influence of interlaboratory measurement variability. We examined the relationship between breast cancer mortality and Ki67 both before and after accounting for interlaboratory variability and 8 patient and tumor characteristics.

METHODS

A multicenter cohort study of women with early IBC diagnosed during 2009-2016 in more than 20 NHS hospitals in England and followed until December 31, 2020.

RESULTS

Ki67 was strongly prognostic of breast cancer mortality in 8212 women with estrogen receptor (ER)-positive, human epidermal growth factor receptor 2 (HER2)-negative early IBC (Ptrend < .001). This relationship remained strong after adjustment for patient and tumor characteristics (Ptrend < .001). Standardization for interlaboratory variability did little to alter these results. For women with Ki67 scores of 0%-5%, 6%-10%, 11%-19%, and 20%-29% the corresponding 8-year adjusted cumulative breast cancer mortality risks were 3.3% (95% confidence interval [CI] = 2.8% to 4.0%), 3.7% (95% CI = 3.0% to 4.4%), 3.4% (95% CI = 2.8% to 4.1%), and 3.4% (95% CI = 2.8% to 4.1%), whereas for women with Ki67 scores of 30%-39% and 40%-100%, these risks were higher, at 5.1% (95% CI = 4.3% to 6.2%) and 7.7% (95% CI = 6.6% to 9.1) (Ptrend < .001). Similar results were obtained when the adjusted analysis was repeated with omission of pathological information about tumor size and nodal involvement, which would not be available preoperatively for patients being considered for neoadjuvant therapy.

CONCLUSION

Our findings confirm the prognostic value of Ki67 scores of 30% or more in women with ER-positive, HER2-negative early IBC, irrespective of interlaboratory variability. These results also suggest that Ki67 may be useful to aid decision-making in the neoadjuvant setting.

The Prediction Analysis of Microarray 50 (PAM50) Gene Expression Classifier Utilized in Indeterminate-Risk Breast Cancer Patients in Hungary: A Consecutive 5-Year Experience

BACKGROUND

Breast cancer has been categorized into molecular subtypes using immunohistochemical staining (IHC) and fluorescence in situ hybridization (FISH) since the early 2000s. However, recent research suggests that gene expression testing, specifically Prosigna® Prediction Analysis of Microarray 50 (PAM50), provides more accurate classification methods. In this retrospective study, we compared the results of IHC/FISH and PAM50 testing. We also examined the impact of various PAM50 parameters on overall survival (OS) and progression-free survival (PFS).

RESULTS

We analyzed 42 unilateral breast cancer samples, with 18 classified as luminal A, 10 as luminal B, 8 as Human epidermal growth factor receptor 2 (HER2)-positive, and 6 as basal-like using PAM50. Interestingly, 17 out of the 42 samples (40.47%) showed discordant results between histopathological assessment and the PAM50 classifier. While routine IHC/FISH resulted in classification differences for a quarter to a third of samples within each subtype, all basal-like tumors were misclassified. Hormone receptor-positive tumors (hazard rate: 8.7803; p = 0.0085) and patients who had higher 10-year recurrence risk scores (hazard rate: 1.0539; p = 0.0201) had shorter OS and PFS.

CONCLUSIONS

Our study supports the existing understanding of molecular subtypes in breast cancer and emphasizes the overlap between clinical characteristics and molecular subtyping. These findings underscore the value of gene expression profiling, such as PAM50, in improving treatment decisions for breast cancer patients.

Extensive review on breast cancer its etiology, progression, prognostic markers, and treatment

As the most frequent and vulnerable malignancy among women, breast cancer universally manifests a formidable healthcare challenge. From a biological and molecular perspective, it is a heterogenous disease and is stratified based on the etiological factors driving breast carcinogenesis. Notably, genetic predispositions and epigenetic impacts often constitute the heterogeneity of this disease. Typically, breast cancer is classified intrinsically into histological subtypes in clinical landscapes. These stratifications empower physicians to tailor precise treatments among the spectrum of breast cancer therapeutics. In this pursuit, numerous prognostic algorithms are extensively characterized, drastically changing how breast cancer is portrayed. Therefore, it is a basic requisite to comprehend the multidisciplinary rationales of breast cancer to assist the evolution of novel therapeutic strategies. This review aims at highlighting the molecular and genetic grounds of cancer additionally with therapeutic and phytotherapeutic context. Substantially, it also renders researchers with an insight into the breast cancer cell lines as a model paradigm for breast cancer research interventions.

Concordance between results of inexpensive statistical models and multigene signatures in patients with ER+/HER2- early breast cancer

Multigene signatures (MGS) are used to guide adjuvant chemotherapy (aCT) decisions in patients diagnosed with estrogen receptor (ER)-positive HER2-negative early breast cancer. We used results from three MGS (Oncotype DX® (ODX), MammaPrint® (MP) or Prosigna®) and assessed the concordance between high or low risk of recurrence and the predicted risk of recurrence based on statistical models. In addition, we looked at the impact of MGS results on final aCT administration during the multidisciplinary meeting (MDM). We retrospectively included 129 patients with ER-positive HER2-negative early breast cancer for which MGS testing was performed after MDM at University Hospitals Leuven between May 2013 and April 2019 in case there was doubt about aCT recommendation. Tumor tissue was analyzed either by ODX (N = 44), MP (N = 28), or Prosigna® (N = 57). Eight statistical models were computed: Magee equations (ME), Memorial Sloan Kettering simplified risk score (MSK-SRS), Breast Cancer Recurrence Score Estimator (BCRSE), OncotypeDXCalculator (ODXC), new Adjuvant! Online (nAOL), Mymammaprint.com (MyMP), PREDICT, and SiNK. Concordance, negative percent agreement, and positive percent agreement were calculated. Of 129 cases, 53% were MGS low and 47% MGS high risk. Concordances of 100.0% were observed between risk results obtained by ODX and ME. For MP, BCRSE demonstrated the best concordance, and for Prosigna® the average of ME. Concordances of <50.0% were observed between risk results obtained by ODX and nAOL, ODX and MyMP, ODX and SiNK, MP and MSK-SRS, MP and nAOL, MP and MyMP, MP and SiNK, and Prosigna® and ODXC. Integration of MGS results during MDM resulted in change of aCT recommendation in 47% of patients and a 15% relative and 9% absolute reduction. In conclusion, statistical models, especially ME and BCRSE, can be useful in selecting ER-positive HER2-negative early breast cancer patients who may need MGS testing resulting in enhanced cost-effectiveness and reduced delay in therapeutic decision-making.