Analytical validation of a standardised scoring protocol for Ki67 immunohistochemistry on breast cancer excision whole sections: an international multicentre collaboration

Impact of Prosigna test on adjuvant treatment decision in lymph node-negative early breast cancer-a prospective national multicentre study (EMIT-1)

BACKGROUND

EMIT-1 is a national, observational, single-arm trial designed to assess the value of the Prosigna, Prediction Analysis of Microarray using the 50 gene classifier (PAM50)/Risk of Recurrence (ROR), test as a routine diagnostic tool, examining its impact on adjuvant treatment decisions, clinical outcomes, side-effects and cost-effectiveness. Here we present the impact on treatment decisions.

PATIENTS AND METHODS

Patients with hormone receptor-positive, human epidermal growth factor receptor 2-negative pT1-pT2 lymph node-negative early breast cancer (EBC) were included. The Prosigna test and standard histopathology assessments were carried out. Clinicians' treatment decisions were recorded before (pre-Prosigna) and after (post-Prosigna) the Prosigna test results were disclosed.

RESULTS

Of 2217 patients included, 2178 had conclusive Prosigna results. The pre-Prosigna treatment decisions were: no systemic treatment (NT) in 27% of patients, endocrine treatment alone (ET) in 38% and chemotherapy (CT) followed by ET (CT + ET) in 35%. Post-Prosigna treatment decisions were 25% NT, 51% ET and 24% CT + ET, respectively. Adjuvant treatment changed in 28% of patients, including 21% change in CT use. Among patients assigned to CT + ET pre-Prosigna, 45% were de-escalated to ET post-Prosigna. Of patients assigned to ET, 12% were escalated to CT + ET and 8% were de-escalated to NT; of those assigned to NT, 18% were escalated to ET/CT + ET. CT was more frequently recommended for patients aged ≤50 years. In the subgroup with pT1c-pT2 G2 and intermediate Ki67 (0.5-1.5× local laboratory median Ki67 score), the pre-Prosigna CT treatment decision varied widely across hospitals (3%-51%). Post-Prosigna, the variability of CT use was markedly reduced (8%-24%). The correlation between Ki67 and ROR score within this subgroup was poor (r = 0.25-0.39). The median ROR score increased by increasing histological grade, but the ROR score ranges were wide (for G1 0-79, G2 0-90, G3 16-94).

CONCLUSION

The Prosigna test result changed adjuvant treatment decisions in all EBC clinical risk groups, markedly decreased the CT use for patients categorized as higher clinical risk pre-Prosigna and reduced treatment decision discrepancies between hospitals.

Automated AI-based grading of neuroendocrine tumors using Ki-67 proliferation index: comparative evaluation and performance analysis

Early detection is critical for successfully diagnosing cancer, and timely analysis of diagnostic tests is increasingly important. In the context of neuroendocrine tumors, the Ki-67 proliferation index serves as a fundamental biomarker, aiding pathologists in grading and diagnosing these tumors based on histopathological images. The appropriate treatment plan for the patient is determined based on the tumor grade. An artificial intelligence-based method is proposed to aid pathologists in the automated calculation and grading of the Ki-67 proliferation index. The proposed system first performs preprocessing to enhance image quality. Then, segmentation process is performed using the U-Net architecture, which is a deep learning algorithm, to separate the nuclei from the background. The identified nuclei are then evaluated as Ki-67 positive or negative based on basic color space information and other features. The Ki-67 proliferation index is then calculated, and the neuroendocrine tumor is graded accordingly. The proposed system's performance was evaluated on a dataset obtained from the Department of Pathology at Meram Faculty of Medicine Hospital, Necmettin Erbakan University. The results of the pathologist and the proposed system were compared, and the proposed system was found to have an accuracy of 95% in tumor grading when compared to the pathologist's report.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Fit-for-Purpose Ki-67 Immunohistochemistry Assays for Breast Cancer

New therapies are being developed for breast cancer, and in this process, some "old" biomarkers are reutilized and given a new purpose. It is not always recognized that by changing a biomarker's intended use, a new biomarker assay is created. The Ki-67 biomarker is typically assessed by immunohistochemistry (IHC) to provide a proliferative index in breast cancer. Canadian laboratories assessed the analytical performance and diagnostic accuracy of their Ki-67 IHC laboratory-developed tests (LDTs) of relevance for the LDTs' clinical utility. Canadian clinical IHC laboratories enrolled in the Canadian Biomarker Quality Assurance Pilot Run for Ki-67 in breast cancer by invitation. The Dako Ki-67 IHC pharmDx assay was employed as a study reference assay. The Dako central laboratory was the reference laboratory. Participants received unstained slides of breast cancer tissue microarrays with 32 cases and performed their in-house Ki-67 assays. The results were assessed using QuPath, an open-source software application for bioimage analysis. Positive percent agreement (PPA, sensitivity) and negative percent agreement (NPA, specificity) were calculated against the Dako Ki-67 IHC pharmDx assay for 5%, 10%, 20%, and 30% cutoffs. Overall, PPA and NPA varied depending on the selected cutoff; participants were more successful with 5% and 10%, than with 20% and 30% cutoffs. Only 4 of 16 laboratories had robust IHC protocols with acceptable PPA for all cutoffs. The lowest PPA for the 5% cutoff was 85%, for 10% was 63%, for 20% was 14%, and for 30% was 13%. The lowest NPA for the 5% cutoff was 50%, for 10% was 33%, for 20% was 50%, and for 30% was 57%. Despite many years of international efforts to standardize IHC testing for Ki-67 in breast cancer, our results indicate that Canadian clinical LDTs have a wide analytical sensitivity range and poor agreement for 20% and 30% cutoffs. The poor agreement was not due to the readout but rather due to IHC protocol conditions. International Ki-67 in Breast Cancer Working Group (IKWG) recommendations related to Ki-67 IHC standardization cannot take full effect without reliable fit-for-purpose reference materials that are required for the initial assay calibration, assay performance monitoring, and proficiency testing.

Clinical and Analytical Validation of Two Methods for Ki-67 Scoring in Formalin Fixed and Paraffin Embedded Tissue Sections of Early Breast Cancer

Proliferation determined by Ki-67 immunohistochemistry has been proposed as a useful prognostic and predictive marker in breast cancer. However, the clinical validity of Ki-67 is questionable. In this study, Ki-67 was retrospectively evaluated by three pathologists using two methods: a visual assessment of the entire slide and a quantitative assessment of the tumour margin in 411 early-stage breast cancer patients with a median follow-up of 26.8 years. We found excellent agreement between the three pathologists for both methods. The risk of recurrence for Ki-67 was time-dependent, as the high proliferation group (Ki-67 ≥ 30%) had a higher risk of recurrence initially, but after 4.5 years the risk was higher in the low proliferation group. In estrogen receptor (ER)-positive patients, the intermediate Ki-67 group initially followed the high Ki-67 group, but eventually followed the low Ki-67 group. ER-positive pN0-1 patients with intermediate Ki-67 treated with endocrine therapy alone had a similar outcome to patients treated with chemotherapy. A cut-off value of 20% appeared to be most appropriate for distinguishing between the high and low Ki-67 groups. To summarize, a simple visual whole slide Ki-67 assessment turned out to be a reliable method for clinical decision-making in early breast cancer patients. We confirmed Ki-67 as an important prognostic and predictive biomarker.

Subspecialized breast pathologists have suboptimal interobserver agreement in Ki-67 evaluation using 20% as the cutoff

PURPOSE

Ki-67 expression levels in breast cancer have prognostic and predictive significance. Therefore, accurate Ki-67 evaluation is important for optimal patient care. Although an algorithm developed by the International Ki-67 in Breast Cancer Working Group (IKWG) improves interobserver variability, it is tedious and time-consuming. In this study, we simplify IKWG algorithm and evaluate its interobserver agreement among breast pathologists in Ki-67 evaluation.

METHODS

Six subspecialized breast pathologists (4 juniors, 2 seniors) assessed the percentage of positive cells in 5% increments in 57 immunostained Ki-67 slides. The time spent on each slide was recorded. Two rounds of ring study (R1, R2) were performed before and after training with the modified IKWG algorithm (eyeballing method at 400× instead of counting 100 tumor nuclei per area). Concordance was assessed using Kendall's and Kappa coefficients.

RESULTS

Analysis of ordinal scale ratings for all categories with 5% increments showed almost perfect agreement in R1 (0.821) and substantial in R2 (0.793); Seniors and juniors had substantial agreement in R1 (0.718 vs. 0.649) and R2 (0.756 vs. 0.658). In dichotomous scale analysis using 20% as the cutoff, the overall agreement was moderate in R1 (0.437) and R2 (0.479), among seniors (R1: 0.436; R2: 0.437) and juniors (R1: 0.445; R2: 0.505). Average scoring time per case was higher in R2 (71 vs. 37 s).

CONCLUSION

The modified IKWG algorithm does not significantly improve interobserver agreement. A better algorithm or assistance from digital image analysis is needed to improve interobserver variability in Ki-67 evaluation.

Ki-67 Testing in Breast Cancer: Assessing Variability With Scoring Methods and Specimen Types and the Potential Subsequent Impact on Therapy Eligibility

Abemaciclib was originally FDA approved for patients with ER-positive/HER2-negative breast cancer with Ki-67 expression ≥20%. However, there were no guidelines provided on which specimen to test or which scoring method to use. We performed a comprehensive study evaluating the variation in Ki-67 expression in breast specimens from 50 consecutive patients who could have been eligible for abemaciclib therapy. Three pathologists with breast expertise each performed a blinded review with 3 different manual scoring methods [estimated (EST), unweighted (UNW), and weighted (WT) (WT recommended by the International Ki-67 in Breast Cancer Working Group)]. Quantitative image analysis (QIA) using the HALO platform was also performed. Three different specimen types [core needle biopsy (CNB) (n=63), resection (RES) (n=52), and axillary lymph node metastasis (ALN) (n=50)] were evaluated for each patient. The average Ki-67 for all specimens was 14.68% for EST, 14.46% for UNW, 14.15% for WT, and 11.15% for QIA. For the manual methods, the range between the lowest and highest Ki-67 for each specimen between the 3 pathologists was 8.44 for EST, 5.94 for WT, and 5.93 for UNW. The WT method limited interobserver variability with ICC1=0.959 (EST ICC1=0.922 and UNW=0.949). Using the aforementioned cutoff of Ki-67 ≥20% versus <20% to determine treatment eligibility, the averaged EST method yields 20 of 50 patients (40%) who would have been treatment-eligible, versus 15 (30%) for the UNW, 17 (34%) for the WT, and 12 (24%) for the QIA. There was no statistically significant difference in Ki-67 among the 3 specimen types. The average Ki-67 difference was 4.36 for CNB vs RES, 6.95 for CNB versus ALN, and RES versus ALN (P=0.93, 0.99, and 0.94, respectively). Our study concludes that further refinement in Ki-67 scoring is advisable to reduce clinically significant variation.

Analysis of Diffusion-Weighted and T2-Weighted Imaging in the Prediction of Distinct Granulation Patterns of Somatotroph Adenomas

OBJECTIVE

The heterogeneity of the somatotroph adenomas, especially for sparsely granulated (SG) and densely granulated (DG) subtypes, has attracted great attention in identifying their imaging biomarker. The purpose of the current study was to compare the diagnostic performance of diffusion-weighted and T2-weighted magnetic resonance imaging (MRI) sequences for preoperatively distinguishing the granulation patterns of somatotroph adenomas.

METHODS

Thirty-two patients with a clinical diagnosis of somatotroph adenomas from October 2018 to March 2023 were included in this study. Coronal diffusion-weighted imaging (DWI) and T2-weighted MRI sequence data were collected from 3.0T MRI and compared between SG and DG groups. The immunohistochemistry was used to confirm the electron microscopy pathologic subtypes and Ki67 expression levels of somatotroph adenomas postoperatively.

RESULTS

Patients in the SG group had significantly higher signal intensity (SI) ratio of DWI (rDWI) (P < 0.001), lower SI ratio of apparent diffusion coefficient (rADC) (P < 0.001), and higher SI ratio of T2-weighted imaging (P = 0.011). The combined diagnosis index of rDWI and rADC had the highest diagnostic efficiency in predicting SG adenomas (sensitivity, 93.3%; specificity, 88.2%; P < 0.001). The rDWI and rADC values had positive and negative correlations with the Ki67 index and tumor maximum diameter, respectively. Lower rADC×103 was an independent predictor for SG adenomas.

CONCLUSIONS

Our results indicated that compared with previously used T2-weighted imaging, the DWI sequence, especially the combined diagnosis index of rDWI and rADC, could more efficiently distinguish the granulation patterns of somatotroph adenomas preoperatively.

Clinicopathologic and genetic analysis of invasive breast carcinomas in women with germline CHEK2 variants

PURPOSE

Germline pathogenic variants in checkpoint kinase 2 (CHEK2) are associated with a moderately increased risk of breast cancer (BC). The spectrum of clinicopathologic features and genetics of these tumors has not been fully established.

METHODS

We characterized the histopathologic and clinicopathologic features of 44 CHEK2-associated BCs from 35 women, and assessed responses to neoadjuvant chemotherapy. A subset of cases (n = 23) was additionally analyzed using targeted next-generation DNA sequencing (NGS).

RESULTS

Most (94%, 33/35) patients were heterozygous carriers for germline CHEK2 variants, and 40% had the c.1100delC allele. Two patients were homozygous, and five had additional germline pathogenic variants in ATM (2), PALB2 (1), RAD50 (1), or MUTYH (1). CHEK2-associated BCs occurred in younger women (median age 45 years, range 25-75) and were often multifocal (20%) or bilateral (11%). Most (86%, 38/44) were invasive ductal carcinomas of no special type (IDC-NST). Almost all (95%, 41/43) BCs were ER + (79% ER + HER2-, 16% ER + HER2 + , 5% ER-HER2 +), and most (69%) were luminal B. Nottingham grade, proliferation index, and results of multiparametric molecular testing were heterogeneous. Biallelic CHEK2 alteration with loss of heterozygosity was identified in most BCs (57%, 13/23) by NGS. Additional recurrent alterations included GATA3 (26%), PIK3CA (226%), CCND1 (22%), FGFR1 (22%), ERBB2 (17%), ZNF703 (17%), TP53 (9%), and PPM1D (9%), among others. Responses to neoadjuvant chemotherapy were variable, but few patients (21%, 3/14) achieved pathologic complete response. Most patients (85%) were without evidence of disease at time of study (n = 34). Five patients (15%) developed distant metastasis, and one (3%) died (mean follow-up 50 months).

CONCLUSION

Almost all CHEK2-associated BCs were ER + IDC-NST, with most classified as luminal B with or without HER2 overexpression. NGS supported the luminal-like phenotype and confirmed CHEK2 as an oncogenic driver in the majority of cases. Responses to neoadjuvant chemotherapy were variable but mostly incomplete.

International Society of Urological Pathology Consensus Conference on Current Issues in Bladder Cancer. Working Group 4: Molecular Subtypes of Bladder Cancer-Principles of Classification and Emerging Clinical Utility

Molecular subtyping has been a major focus of bladder cancer research over the past decade. Despite many promising associations with clinical outcomes and treatment response, its clinical impact has yet to be defined. As part of the 2022 International Society of Urological Pathology Conference on Bladder Cancer, we reviewed the current state of the science for bladder cancer molecular subtyping. Our review included several different subtyping systems. We derived the following 7 principles, which summarize progress and challenges of molecular subtyping: (1) bladder cancer has 3 major molecular subtypes: luminal, basal-squamous, and neuroendocrine; (2) signatures of the tumor microenvironment differ greatly among bladder cancers, particularly among luminal tumors; (3) luminal bladder cancers are biologically diverse, and much of this diversity results from differences in features unrelated to the tumor microenvironment, such as FGFR3 signaling and RB1 inactivation; (4) molecular subtype of bladder cancer associates with tumor stage and histomorphology; (5) many subtyping systems include idiosyncrasies, such as subtypes recognized by no other system; (6) there are broad fuzzy borders between molecular subtypes, and cases that fall on these fuzzy borders are often classified differently by different subtyping systems; and (7) when there are histomorphologically distinct regions within a single tumor, the molecular subtypes of these regions are often discordant. We reviewed several use cases for molecular subtyping, highlighting their promise as clinical biomarkers. Finally, we conclude that data are currently insufficient to support the routine use of molecular subtyping to guide bladder cancer management, an opinion shared with the majority of conference attendees. We also conclude that molecular subtype should not be considered an "intrinsic" property of a tumor but should instead be considered the result of a specific laboratory test, performed using a specific testing platform and classification algorithm, validated for a specific clinical application.

AI-Powered Segmentation of Invasive Carcinoma Regions in Breast Cancer Immunohistochemical Whole-Slide Images

AIMS

The automation of quantitative evaluation for breast immunohistochemistry (IHC) plays a crucial role in reducing the workload of pathologists and enhancing the objectivity of diagnoses. However, current methods face challenges in achieving fully automated immunohistochemistry quantification due to the complexity of segmenting the tumor area into distinct ductal carcinoma in situ (DCIS) and invasive carcinoma (IC) regions. Moreover, the quantitative analysis of immunohistochemistry requires a specific focus on invasive carcinoma regions.

METHODS AND RESULTS

In this study, we propose an innovative approach to automatically identify invasive carcinoma regions in breast cancer immunohistochemistry whole-slide images (WSIs). Our method leverages a neural network that combines multi-scale morphological features with boundary features, enabling precise segmentation of invasive carcinoma regions without the need for additional H&E and P63 staining slides. In addition, we introduced an advanced semi-supervised learning algorithm, allowing efficient training of the model using unlabeled data. To evaluate the effectiveness of our approach, we constructed a dataset consisting of 618 IHC-stained WSIs from 170 cases, including four types of staining (ER, PR, HER2, and Ki-67). Notably, the model demonstrated an impressive intersection over union (IoU) score exceeding 80% on the test set. Furthermore, to ascertain the practical utility of our model in IHC quantitative evaluation, we constructed a fully automated Ki-67 scoring system based on the model's predictions. Comparative experiments convincingly demonstrated that our system exhibited high consistency with the scores given by experienced pathologists.

CONCLUSIONS

Our developed model excels in accurately distinguishing between DCIS and invasive carcinoma regions in breast cancer immunohistochemistry WSIs. This method paves the way for a clinically available, fully automated immunohistochemistry quantitative scoring system.

Effect of storage time of paraffin sections on the expression of PD-L1 (SP142) in invasive breast cancer

BACKGROUND

PD-L1 staining using long-stored paraffin sections may not be consistent with the true PD-L1 expression of patients. Therefore, it is necessary to explore the expression of PD-L1(SP142) in paraffin sections of invasive breast cancer with different storage times and the optimal storage temperature for unstained paraffin sections.

METHODS

The study included 71 cases of PD-L1(SP142) positive breast cancer. The unstained paraffin sections were stored at room temperature conditions (20-25 °C), 4 °C, -20 °C and - 80 °C, respectively. PD-L1 staining was performed at 1, 2, 3, 4, 8, 12 and 24 weeks of storage. PD-L1 expression was assessed with a continuity score.

RESULTS

The PD-L1 antigen was gradually lost as the storage time of paraffin sections increased. The PD-L1 positivity rate was 97.18% at 1 week for the sections stored at room temperature, and decreased from 83.10 to 71.83% for the sections stored for 2 weeks to 4 weeks, and 61.97%, 54.93%, and 32.93% for 8, 12, and 24 weeks, respectively. When stored at low temperatures of 4 °C, -20 °C and - 80 °C, the positivity rate decreases with the same trend but more slowly compared to room temperature. The mean IC score of PD-L1 also showed a gradual decrease in all cases. In the consistency analysis, PD-L1 expression in slices stored at room temperature for 2 weeks was consistent with PD-L1 expression in fresh slices (ICC ≥ 0.9 for all slices), and PD-L1 expression in slices stored at 4 °C or -20 °C for 4 weeks was consistent with PD-L1 expression in fresh slices (ICC ≥ 0.9 for all slices). When stored under refrigeration at -80 °C, PD-L1 expression in slices stored for 3 weeks was consistent with that in fresh slices (ICC ≥ 0.9).

CONCLUSIONS

To our knowledge, this is the first article on the effect of preservation time and preservation temperature of paraffin sections on PD-L1 expression in breast cancer. Long-term storage of paraffin sections of unstained invasive breast cancer can lead to antigen loss of PD-L1 (SP142). Refrigerated storage of paraffin sections can delay antigen loss, with best results at 4 °C or -20 °C, and a storage time of no more than 4 weeks is recommended.

Ki67 assessment protocol as an integral biomarker for avoiding radiotherapy in the LUMINA breast cancer trial

AIMS

The LUMINA trial demonstrated a very low local recurrence rate in women ≥55 years with low-risk luminal A breast cancer (defined as grade I-II, T1N0, hormone receptor positive, HER2 negative and Ki67 index ≤13.25%) treated with breast-conserving surgery and endocrine therapy (but no other systemic therapy), supporting the safe omission of radiation in these women. Here we describe the protocol for Ki67 assessment, the companion diagnostic used to guide omission of adjuvant radiotherapy.

METHODS

Ki67 immunohistochemistry was performed on full-face sections at one of three regional labs. Pathologists trained in the International Ki67 in Breast Cancer Working Group (IKWG) method demarcated tumour areas on scanned slides and scored 100 nuclei from each of at least five randomly selected 1-mm fields. For cases with high Ki67 heterogeneity, further virtual cores were selected and scored in order to confidently assign a case as luminal A (≤13.25%) or B (>13.25%). Interlaboratory variability was assessed through an annual quality assurance programme during the study period.

RESULTS

From the quality assurance programme, the mean Ki67 index across all cases/labs was 13%. The observed intraclass correlation coefficient (ICC) and kappa statistics were ≥0.9 and ≥0.7, respectively, indicating a substantial level of agreement. Median scoring time was 4 min per case. The IKWG-recommended scoring method, performed directly from slides, requiring up to four scored fields, is concordant with the LUMINA scoring method (ICC ≥ 0.9).

CONCLUSION

Ki67 is a practical, reproducible, and inexpensive biomarker that can identify low-risk luminal A breast cancers as potential candidates for radiation de-escalation.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov number, NCT01791829.

A risk-based subgroup analysis of the effect of adjuvant S-1 in estrogen receptor-positive, HER2-negative early breast cancer

PURPOSE

The Phase III POTENT trial demonstrated the efficacy of adding S-1 to adjuvant endocrine therapy for estrogen receptor-positive, HER2-negative early breast cancer. We investigated the efficacy of S-1 across different recurrence risk subgroups.

METHODS

This was a post-hoc exploratory analysis of the POTENT trial. Patients in the endocrine-therapy-only arm were divided into three groups based on composite risk values calculated from multiple prognostic factors. The effects of S-1 were estimated using the Cox model in each risk group. The treatment effects of S-1 in patients meeting the eligibility criteria of the monarchE trial were also estimated.

RESULTS

A total of 1,897 patients were divided into three groups: group 1 (≤ lower quartile of the composite values) (N = 677), group 2 (interquartile range) (N = 767), and group 3 (> upper quartile) (N = 453). The addition of S-1 to endocrine therapy resulted in 49% (HR: 0.51, 95% CI: 0.33-0.78) and 29% (HR: 0.71, 95% CI 0.49-1.02) reductions in invasive disease-free survival (iDFS) events in groups 2 and 3, respectively. We could not identify any benefit from the addition of S-1 in group 1. The addition of S-1 showed an improvement in iDFS in patients with one to three positive nodes meeting the monarchE cohort 1 criteria (N = 290) (HR: 0.47, 95% CI: 0.29-0.74).

CONCLUSIONS

The benefit of adding adjuvant S-1 was particularly marked in group 2. Further investigations are warranted to explore the optimal usage of adjuvant S-1.

Evaluation of the relationship between Ki67 expression level and neoadjuvant treatment response and prognosis in breast cancer based on the Neo-Bioscore staging system

BACKGROUND

Neoadjuvant chemotherapy (NAC) is widely used in the treatment of primary breast cancer. Different staging systems have been developed to evaluate the residual tumor after NAC and classify patients into different prognostic groups. Ki67, a proliferation marker, has been shown to be useful in predicting treatment response and prognosis. We aimed to investigate the prognostic importance Neo-Bioscore stage and pretreatment and posttreatment Ki67 levels in breast cancer patients who received NAC and correlations between Neo-Bioscore stage and pretreatment and posttreatment Ki67 levels.

METHODS

A total of 176 invasive breast carcinoma patients who underwent NAC were included in the study. Ki67 levels were evaluated by immunohistochemical methods in Trucut biopsy and surgical excision specimens. Patients were classified into prognostic groups using the Neo-Bioscore staging system.

RESULTS

Patients with high pretreatment Ki67 score were more likely to be in the higher Neo-Bioscore risk group (p < 0.001). Patients with a high posttreatment Ki67 score were more likely to be in the higher Neo-Bioscore prognostic risk group (p < 0.001). Overall survival (OS) and disease-free survival (DFS) were shorter in patients with high posttreatment Ki67 scores and in patients in the higher Neo-Bioscore risk group. We also determined a cutoff 37% for pathological complete response.

CONCLUSION

Neo-Bioscore staging system is found to be important in predicting survival. The posttreatment Ki67 level is more important than pretreatment Ki67 level in predicting survival.

Pretreatment carcinoembryonic antigen combined with cancer antigen-125 for predicting lymph node metastasis in endometrial carcinoma: a retrospective cohort study

PURPOSE

To investigate whether the cost-effective, pretreatment tumor markers carcinoembryonic antigen (CEA) and carbohydrate antigen-125 (CA-125) can be used to predict lymph node metastasis (LNM) in endometrioid-type endometrial cancer (EC) and to develop a predictive model.

METHODS

This was a single-center retrospective study of patients with endometrioid-type EC who underwent complete staging surgery between January 2015 and June 2022. We identified the optimal cut-off values of CEA and CA-125 for predicting LNM using receiver operating characteristic (ROC) curves. Stepwise multivariate logistic regression analysis was used to identify independent predictors. A nomogram for predicting LNM was constructed and validated by bootstrap resampling.

RESULTS

The optimal cut-off values of CEA and CA-125 were 1.4 ng/mL (area under the ROC curve (AUC) 0.62) and 40 U/mL (AUC 0.75), respectively. Multivariate analysis showed that CEA (odds ratio (OR) 1.94; 95% confidence interval (CI) 1.01-3.74) and CA-125 (OR 8.75; 95% CI 4.42-17.31) were independent predictors of LNM. Our nomogram showed adequate discrimination with a concordance index of 0.78. Calibration curves for the probability of LNM showed optimal agreement between the predicted and actual probabilities. The risk of LNM for markers below the cut-offs was 3.6%. The negative predictive value and negative likelihood ratio were 96.6% and 0.26, respectively, with moderate ability to rule out the possibility of LNM.

CONCLUSION

We report a cost-effective method of using pretreatment CEA and CA-125 levels to identify patients with endometrioid-type EC who are at a low risk for LNM, which may guide decision-making regarding aborting lymphadenectomy.

Applications of Artificial Intelligence in Breast Pathology

CONTEXT.—

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

OBJECTIVE.—

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

DATA SOURCES.—

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

CONCLUSIONS.—

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

Triple-negative Breast Carcinoma With Apocrine and Histiocytoid Features: A Clinicopathologic and Molecular Study of 18 Cases

Triple-negative breast cancer (TNBC) is a heterogenous group of tumors. Most TNBCs are high-grade aggressive tumors, but a minority of TNBCs are not high grade, with relatively indolent behavior and specific morphologic and molecular features. We performed a clinicopathologic and molecular assessment of 18 non-high-grade TNBCs with apocrine and/or histiocytoid features. All were grade I or II with low Ki-67 (≤20%). Thirteen (72%) showed apocrine features, and 5 (28%) showed histiocytoid and lobular features. In all, 17/18 expressed the androgen receptor, and 13/13 expressed gross cystic disease fluid protein 15. Four (22.2%) patients were treated with neoadjuvant chemotherapy, but none achieved a pathologic complete response. In all, 2/18 patients (11%) had lymph node metastasis at the time of surgery. None of the cases had a recurrence or disease-specific death, with an average follow-up time of 38 months. Thirteen cases were profiled by targeted capture-based next-generation DNA sequencing. Genomic alterations (GAs) were most significant for PI3K-PKB/Akt pathway (69%) genes, including PIK3R1 (23%), PIK3CA (38%), and PTEN (23%), and RTK-RAS pathway (62%) including FGFR4 (46%) and ERBB2 (15%). TP53 GA was seen in only 31% of patients. Our findings support those on high-grade TNBCs with apocrine and/or histiocytoid features as a clinicopathologic and genetically distinct subgroup of TNBC. They can be defined by features including tubule formation, rare mitosis, low Ki-67 (≤20%), triple-negative status, expression of androgen receptor and/or gross cystic disease fluid protein 15, and GA in the PI3K-PKB/Akt and/or RTK-RAS pathway. These tumors are not sensitive to chemotherapy but have favorable clinical behavior. Tumor subtype definitions are the first step to implementing future trial designs to select these patients.

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

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

Identifying the optimal cutoff point of Ki-67 in breast cancer: a single-center experience

OBJECTIVE

Ki-67 is associated with breast cancer subtypes, but the optimal cutoff point of Ki-67 has not been established in our center. We evaluated the cutoff point of Ki-67 in breast cancer and analyzed the associations among Ki-67, clinicopathological features, and prognosis.

METHODS

The clinicopathological data and prognostic information of patients with breast cancer treated in our center were retrospectively collected, and the optimal cutoff point of Ki-67 was determined by univariate and multivariate survival risk analyses. The cutoff point was used to group the patients, and the differences in the clinicopathological features and prognosis were analyzed between the two groups.

RESULTS

In total, 609 patients with estrogen receptor-positive and human epidermal growth factor receptor 2-negative primary breast cancer were enrolled. The mean Ki-67 value was 22.3% ± 15.4%, the median was 20%, and a cutoff point of 30% was an independent factor influencing recurrence-free survival. When 30% was used as the cutoff point, patients with a Ki-67 value of ≤30% had a better prognosis and lower tumor malignancy.

CONCLUSION

The optimal cutoff point of Ki-67 in breast cancer in our center is 30%.

The Story of the Magee Equations: The Ultimate in Applied Immunohistochemistry

Magee equations (MEs) are a set of multivariable models that were developed to estimate the actual Onco type DX (ODX) recurrence score in invasive breast cancer. The equations were derived from standard histopathologic factors and semiquantitative immunohistochemical scores of routinely used biomarkers. The 3 equations use slightly different parameters but provide similar results. ME1 uses Nottingham score, tumor size, and semiquantitative results for estrogen receptor (ER), progesterone receptor, HER2, and Ki-67. ME2 is similar to ME1 but does not require Ki-67. ME3 includes only semiquantitative immunohistochemical expression levels for ER, progesterone receptor, HER2, and Ki-67. Several studies have validated the clinical usefulness of MEs in routine clinical practice. The new cut-off for ODX recurrence score, as reported in the Trial Assigning IndividuaLized Options for Treatment trial, necessitated the development of Magee Decision Algorithm (MDA). MEs, along with mitotic activity score can now be used algorithmically to safely forgo ODX testing. MDA can be used to triage cases for molecular testing and has the potential to save an estimated $300,000 per 100 clinical requests. Another potential use of MEs is in the neoadjuvant setting to appropriately select patients for chemotherapy. Both single and multi-institutional studies have shown that the rate of pathologic complete response (pCR) to neoadjuvant chemotherapy in ER+/HER2-negative patients can be predicted by ME3 scores. The estimated pCR rates are 0%, <5%, 14%, and 35 to 40% for ME3 score <18, 18 to 25, >25 to <31, and 31 or higher, respectively. This information is similar to or better than currently available molecular tests. MEs and MDA provide valuable information in a time-efficient manner and are available free of cost for anyone to use. The latter is certainly important for institutions in resource-poor settings but is also valuable for large institutions and integrated health systems.

An emerging generation of endocrine therapies in breast cancer: a clinical perspective

Anti-estrogen therapy is a key component of the treatment of both early and advanced-stage hormone receptor (HR)-positive breast cancer. This review discusses the recent emergence of several anti-estrogen therapies, some of which were designed to overcome common mechanisms of endocrine resistance. The new generation of drugs includes selective estrogen receptor modulators (SERMs), orally administered selective estrogen receptor degraders (SERDs), as well as more unique agents such as complete estrogen receptor antagonists (CERANs), proteolysis targeting chimeric (PROTACs), and selective estrogen receptor covalent antagonists (SERCAs). These drugs are at various stages of development and are being evaluated in both early and metastatic settings. We discuss the efficacy, toxicity profile, and completed and ongoing clinical trials for each drug and highlight key differences in their activity and study population that have ultimately influenced their advancement.

Prediction of Oncotype DX Recurrence Score Using Clinicopathological Variables in Estrogen Receptor-Positive/Human Epidermal Growth Factor Receptor 2-Negative Breast Cancer

PURPOSE

Oncotype DX (ODX) is a well-validated multigene assay that is increasingly used in Korean clinical practice. This study aimed to develop a clinicopathological prediction (CPP) model for the ODX recurrence scores (RSs).

METHODS

A total of 297 patients (study group, n = 175; external validation group, n = 122) with estrogen receptor-positive, human epidermal growth factor receptor 2 (HER2)-negative, T1-3N0-1M0 breast cancer, and available ODX test results were included in the study. Risk categorization as determined by ODX RSs concurred with the TAILORx study (low-risk, RS ≤ 25; high-risk, RS > 25). Univariate and multivariate logistic regression analyses were used to assess the relationships between clinicopathological variables and risk stratified by the ODX RSs. A CPP model was constructed based on regression coefficients (β values) for clinicopathological variables significant by multivariate regression analysis.

RESULTS

Progesterone receptor (PR) negativity, high Ki-67 index, and nuclear grade (NG) 3 independently predicted high-risk RS, and these variables were used to construct the CPP model. The C-index, which represented the discriminatory ability of our CPP model for predicting a high-risk RS, was 0.915 (95% confidence interval [CI], 0.859-0.971). When the CPP model was applied to the external validation group, the C-index was 0.926 (95% CI, 0.873-0.978).

CONCLUSION

Our CPP model based on PR, Ki-67 index, and NG could aid in the selection of patients with breast cancer requiring an ODX test.

ELISA-like QDB method to meet the emerging need of Her2 assessment for breast cancer patients

Inherent issues of subjectivity and inconsistency have long plagued immunohistochemistry (IHC)-based Her2 assessment, leading to the repeated issuance of guidelines by the American Society of Clinical Oncology/College of American Pathologists (ASCO/CAP) for its standardization for breast cancer patients. Yet, all these efforts may prove insufficient with the advent of Trastuzumab deruxtecan (T-Dxd), a drug with the promise to expand to tumors traditionally defined as Her2 negative (Her2−). In this study, we attempted to address these issues by exploring an ELISA-like quantitative dot blot (QDB) method as an alternative to IHC. The QDB method has been used to measure multiple protein biomarkers including ER, PR, Ki67, and cyclin D1 in breast cancer specimens. Using an independent cohort (cohort 2) of breast cancer formalin-fixed paraffin-embedded (FFPE) specimens, we validated cutoffs developed in cohort 1 (Yu et al., Scientific Reports 2020 10:10502) with overall 100% specificity (95% CI: 100–100) and 97.56% sensitivity (95% CI: 92.68–100) in cohort 2 against standard practice with the dichotomized absolutely quantitated values. Using the limit of detection (LOD) of the QDB method as the putative cutoff point, tumors with no Her2 expression were identified with the number comparable to those of IHC 0. Our results support further evaluation of the QDB method as an alternative to IHC to meet the emerging need of identifying tumors with low Her2 expression (Her2-low) in daily clinical practice.

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

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

Noninferiority of Artificial Intelligence-Assisted Analysis of Ki-67 and Estrogen/Progesterone Receptor in Breast Cancer Routine Diagnostics

Image analysis assistance with artificial intelligence (AI) has become one of the great promises over recent years in pathology, with many scientific studies being published each year. Nonetheless, and perhaps surprisingly, only few image AI systems are already in routine clinical use. A major reason for this is the missing validation of the robustness of many AI systems: beyond a narrow context, the large variability in digital images due to differences in preanalytical laboratory procedures, staining procedures, and scanners can be challenging for the subsequent image analysis. Resulting faulty AI analysis may bias the pathologist and contribute to incorrect diagnoses and, therefore, may lead to inappropriate therapy or prognosis. In this study, a pretrained AI assistance tool for the quantification of Ki-67, estrogen receptor (ER), and progesterone receptor (PR) in breast cancer was evaluated within a realistic study set representative of clinical routine on a total of 204 slides (72 Ki-67, 66 ER, and 66 PR slides). This represents the cohort with the largest image variance for AI tool evaluation to date, including 3 staining systems, 5 whole-slide scanners, and 1 microscope camera. These routine cases were collected without manual preselection and analyzed by 10 participant pathologists from 8 sites. Agreement rates for individual pathologists were found to be 87.6% for Ki-67 and 89.4% for ER/PR, respectively, between scoring with and without the assistance of the AI tool regarding clinical categories. Individual AI analysis results were confirmed by the majority of pathologists in 95.8% of Ki-67 cases and 93.2% of ER/PR cases. The statistical analysis provides evidence for high interobserver variance between pathologists (Krippendorff's α, 0.69) in conventional immunohistochemical quantification. Pathologist agreement increased slightly when using AI support (Krippendorff α, 0.72). Agreement rates of pathologist scores with and without AI assistance provide evidence for the reliability of immunohistochemical scoring with the support of the investigated AI tool under a large number of environmental variables that influence the quality of the diagnosed tissue images.

Triple-Negative Apocrine Carcinomas: Toward a Unified Group With Shared Molecular Features and Clinical Behavior

Triple-negative apocrine carcinomas (TNACs) are rare breast tumors with limited studies evaluating their molecular characteristics and clinical behavior. We performed a histologic, immunohistochemical, genetic, and clinicopathologic assessment of 42 invasive TNACs (1 with a focal spindle cell component) from 41 patients, 2 pure apocrine ductal carcinomas in situ (A-DCIS), and 1 A-DCIS associated with spindle cell metaplastic carcinoma (SCMBC). All TNACs had characteristic apocrine morphology and expressed androgen receptor (42/42), gross cystic disease fluid protein 15 (24/24), and CK5/6 (16/16). GATA3 was positive in most cases (16/18, 89%), and SOX10 was negative (0/22). TRPS1 was weakly expressed in a minority of tumors (3/14, 21%). Most TNACs had low Ki67 proliferation (≤10% in 67%, 26/39), with a median index of 10%. Levels of tumor infiltrating lymphocytes were low (≤10% in 93%, 39/42, and 15% in 7%, 3/42). Eighteen percent of TNACs presented with axillary nodal metastasis (7/38). No patients treated with neoadjuvant chemotherapy achieved pathologic complete response (0%, 0/10). Nearly all patients with TNAC (97%, n = 32) were without evidence of disease at the time of study (mean follow-up of 62 months). Seventeen invasive TNACs and 10 A-DCIS (7 with paired invasive TNAC) were profiled by targeted capture-based next-generation DNA sequencing. Pathogenic mutations in phosphatidylinositol 3-kinase pathway genes PIK3CA (53%) and/or PIK3R1 (53%) were identified in all TNACs (100%), including 4 (24%) with comutated PTEN. Ras-MAPK pathway genes, including NF1 (24%), and TP53 were mutated in 6 tumors each (35%). All A-DCIS shared mutations, such as phosphatidylinositol 3-kinase aberrations and copy number alterations with paired invasive TNACs or SCMBC, and a subset of invasive carcinomas showed additional mutations in tumor suppressors (NF1, TP53, ARID2, and CDKN2A). Divergent genetic profiles between A-DCIS and invasive carcinoma were identified in 1 case. In summary, our findings support TNAC as a morphologically, immunohistochemically, and genetically homogeneous subgroup of triple-negative breast carcinomas and suggest overall favorable clinical behavior.

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

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

Neoadjuvant endocrine therapy in postmenopausal women with HR+/HER2- breast cancer

INTRODUCTION

While endocrine therapy is the standard-of-care adjuvant treatment for hormone receptor-positive (HR+) breast cancers, there is also extensive evidence for the role of pre-operative (or neoadjuvant) endocrine therapy (NET) in HR+ postmenopausal women.

AREAS COVERED

We conducted a thorough review of the published literature, to summarize the evidence to date, including studies of how NET compares to neoadjuvant chemotherapy, which NET agents are preferable, and the optimal duration of NET. We describe the importance of on-treatment assessment of response, the different predictors available (including Ki67, PEPI score, and molecular signatures) and the research opportunities the pre-operative setting offers. We also summarize recent combination trials and discuss how the COVID-19 pandemic led to increases in NET use for safe management of cases with deferred surgery and adjuvant treatments.

EXPERT OPINION

NET represents a safe and effective tool for the management of postmenopausal women with HR+/HER2- breast cancer, enabling disease downstaging and a wider range of surgical options. Aromatase inhibitors are the preferred NET, with evidence suggesting that longer regimens might yield optimal results. However, NET remains currently underutilised in many territories and institutions. Further validation of predictors for treatment response and benefit is needed to help standardise and fully exploit the potential of NET in the clinic.

Impact of automated methods for quantitative evaluation of immunostaining: Towards digital pathology

Introduction

We sought to develop a novel method for a fully automated, robust quantification of protein biomarker expression within the epithelial component of high-grade serous ovarian tumors (HGSOC). Rather than defining thresholds for a given biomarker, the objective of this study in a small cohort of patients was to develop a method applicable to the many clinical situations in which immunomarkers need to be quantified. We aimed to quantify biomarker expression by correlating it with the heterogeneity of staining, using a non-subjective choice of scoring thresholds based on classical mathematical approaches. This could lead to a universal method for quantifying other immunohistochemical markers to guide pathologists in therapeutic decision-making.

Methods

We studied a cohort of 25 cases of HGSOC for which three biomarkers predictive of the response observed ex vivo to the BH3 mimetic molecule ABT-737 had been previously validated by a pathologist. We calibrated our algorithms using Stereology analyses performed by two experts to detect immunohistochemical staining and epithelial/stromal compartments. Immunostaining quantification within Stereology grids of hexagons was then performed for each histological slice. To define thresholds from the staining distribution histograms and to classify staining within each hexagon as low, medium, or high, we used the Gaussian Mixture Model (GMM).

Results

Stereology analysis of this calibration process produced a good correlation between the experts for both epithelium and immunostaining detection. There was also a good correlation between the experts and image processing. Image processing clearly revealed the respective proportions of low, medium, and high areas in a single tumor and showed that this parameter of heterogeneity could be included in a composite score, thus decreasing the level of discrepancy. Therefore, agreement with the pathologist was increased by taking heterogeneity into account.

Conclusion and discussion

This simple, robust, calibrated method using basic tools and known parameters can be used to quantify and characterize the expression of protein biomarkers within the different tumor compartments. It is based on known mathematical thresholds and takes the intratumoral heterogeneity of staining into account. Although some discrepancies need to be diminished, correlation with the pathologist’s classification was satisfactory. The method is replicable and can be used to analyze other biological and medical issues. This non-subjective technique for assessing protein biomarker expression uses a fully automated choice of thresholds (GMM) and defined composite scores that take the intra-tumor heterogeneity of immunostaining into account. It could help to avoid the misclassification of patients and its subsequent negative impact on therapeutic care.

Systematically higher Ki67 scores on core biopsy samples compared to corresponding resection specimen in breast cancer: a multi-operator and multi-institutional study

Ki67 has potential clinical importance in breast cancer but has yet to see broad acceptance due to inter-laboratory variability. Here we tested an open source and calibrated automated digital image analysis (DIA) platform to: (i) investigate the comparability of Ki67 measurement across corresponding core biopsy and resection specimen cases, and (ii) assess section to section differences in Ki67 scoring. Two sets of 60 previously stained slides containing 30 core-cut biopsy and 30 corresponding resection specimens from 30 estrogen receptor-positive breast cancer patients were sent to 17 participating labs for automated assessment of average Ki67 expression. The blocks were centrally cut and immunohistochemically (IHC) stained for Ki67 (MIB-1 antibody). The QuPath platform was used to evaluate tumoral Ki67 expression. Calibration of the DIA method was performed as in published studies. A guideline for building an automated Ki67 scoring algorithm was sent to participating labs. Very high correlation and no systematic error (p = 0.08) was found between consecutive Ki67 IHC sections. Ki67 scores were higher for core biopsy slides compared to paired whole sections from resections (p ≤ 0.001; median difference: 5.31%). The systematic discrepancy between core biopsy and corresponding whole sections was likely due to pre-analytical factors (tissue handling, fixation). Therefore, Ki67 IHC should be tested on core biopsy samples to best reflect the biological status of the tumor.

Correlation of the Ki67 Working Group prognostic risk categories with the Oncotype DX Recurrence Score in early breast cancer

BACKGROUND

The relationship between Ki67 assessed by immunohistochemistry (IHC) and the Oncotype DX Recurrence Score (RS) is unclear. The objective of this study was to determine the correlation between the 21-gene RS and IHC-measured Ki67 with the prognostic classification groups recommended by the International Ki67 Working Group (IKWG).

METHODS

The authors performed a retrospective chart review of women who had hormone receptor (HR)-positive, human epidermal growth factor receptor 2-negative early breast cancer with zero to three positive lymph nodes and both Ki67 and the 21-gene RS performed at their institution from 2013 to 2021. Patients were categorized into low (≤5%), intermediate (6%-29%), and high Ki67 groups (≥30%) according to IKWG recommendations. Overall agreement and risk-stratified agreement between Ki67 and RS were assessed with the proportion of agreement and the κ statistic.

RESULTS

The study included 525 patients with HR-positive breast cancer. Among the 49% of patients with intermediate Ki67 values of 6%-29%, the distribution of low (0-10), intermediate (11-25), and high RS (26-100) was 19%, 66%, and 15%, respectively. There was slight agreement (κ = 0.01-0.20) between Ki67 and RS (κ = 0.027) in the overall population, although this was not significant (p = .1985). There was fair agreement (κ = 0.21-0.40) between high Ki67 and RS values (κ = 0.280; p < .0001). A higher progesterone receptor percentage was associated with lower RS values (p > .0001) but not lower Ki67 values. A positive nodal status and a larger tumor size were associated with higher Ki67 values (p = .0059 and p < .0001) but not with RS.

CONCLUSIONS

In this group of patients selected to have a 21-gene RS, there was no significant correlation between Ki67 and RS in the overall population, and there was fair agreement between high Ki67 and high RS values.

LAY SUMMARY

In patients with early-stage, hormone receptor-positive breast cancer, decisions on adjuvant chemotherapy are based on certain biological features of the cancer and genomic assays such as the Oncotype DX Recurrence Score (RS). The goal of this study was to determine the correlation between Ki67, a marker of proliferation, and the Oncotype DX RS, a 21-gene assay demonstrated to be predictive of an adjuvant chemotherapy benefit in patients with early-stage breast cancer. In 525 patients, the authors did not find a significant correlation between Ki67 and RS.

Relationship between ER expression by IHC or mRNA with Ki67 response to aromatase inhibition: a POETIC study

BACKGROUND

In clinical practice, oestrogen receptor (ER) analysis is almost entirely by immunohistochemistry (IHC). ASCO/CAP recommends cut-offs of < 1% (negative) and 1-10% (low) cells positive. There is uncertainty whether patients with ER low tumours benefit from endocrine therapy. We aimed to assess IHC and mRNA cut-points for ER versus biological response of primary breast cancer to 2 weeks' aromatase inhibitor treatment as measured by change in Ki67.

METHODS

Cases were selected from the aromatase inhibitor treatment group of POETIC. We selected the 15% with the poorest Ki67 response (PR, < 40% Ki67 suppression, n = 230) and a random 30% of the remainder categorised as intermediate (IR, 40-79% Ki67 suppression, n = 150) and good-responders (GR, ≥ 80% Ki67 suppression, n = 230) from HER2 - group. All HER2 + cases available were selected irrespective of their response category (n = 317). ER expression was measured by IHC and qPCR.

RESULTS

ER IHC was available from 515 HER2 - and 186 HER2 + tumours and ER qPCR from 367 HER2 - and 171 HER2 + tumours. Ninety-one percentage of patients with ER IHC < 10% were PRs with similar rates in HER2 - and HER2 + cases. At or above ER IHC 10% substantial numbers of patients showed IR or GR. Similar proportions of patients were defined by cut-points of ER IHC < 10% and ER mRNA < 5 units. In addition, loss of PgR expression altered ER anti-proliferation response with 92% of PgR - cases with ER IHC < 40% being PRs.

CONCLUSIONS

There was little responsiveness at IHC < 10% and no distinction between < 1% and 1-10% cells positive. Similar separation of PRs from IR/GRs was achieved by IHC and mRNA.

Comparison of immunohistochemistry and RT-qPCR for assessing ER, PR, HER2, and Ki67 and evaluating subtypes in patients with breast cancer

PURPOSE

Currently, the most commonly applied method for the determination of breast cancer subtypes is to test estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and Ki67 by immunohistochemistry (IHC). However, the IHC method has substantial intraobserver and interobserver variability. ESR1, PGR, ERBB2, and MKi67 mRNA tests by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) assay may improve the diagnostic objectivity and efficiency. Here, we compared the concordance between RT-qPCR and IHC for assessment of the same biomarkers and evaluated the subtypes.

METHODS

A total of 265 eligible cases were divided into a training cohort and a validation cohort, and the expressions of ER/ESR1, PR/PGR, HER2/ERBB2, and Ki67/MKI67 were tested by IHC and RT-qPCR. Then, the appropriate cutoff of RT-qPCR was calculated in the training cohort. The concordance between RT-qPCR and IHC was calculated for individual marker. In addition, we investigated the subtypes based on the RT-qPCR results.

RESULTS

The Spearman correlation coefficients between ER/ESR1, PR/PGR, HER2/ERBB2, and Ki67/MKI67 by IHC and RT-qPCR were 0.768, 0.699, 0.762, and 0.387, respectively. The cutoff values for the RT-qPCR assay of ESR1 (1%), PGR (1%), ERBB2, and MKi67 (14%) were 35.539, 32.139, 36.398, and 29.176, respectively. The overall percent agreement (OPA) between ER/ESR1, PR/PGR, HER2/ERBB2, and Ki67/MKI67 by IHC and RT-qPCR was 92.48%, 73.68%, 92.80%, and 74.44%, respectively. A total of 224 (84.53%) specimens were concordant for the breast cancer subtypes (IHC-based type) by RT-qPCR.

CONCLUSION

Evaluation of breast cancer biomarker status by RT-qPCR was highly concordant with IHC. RT-qPCR can be used as a supplementary method to detect molecular markers of breast cancer.

Comparison of manual and automated digital image analysis systems for quantification of cellular protein expression

OBJECTIVE

Quantifying protein expression in immunohistochemically stained histological slides is an important tool for oncologic research. The use of computer-aided evaluation of IHC-stained slides significantly contributes to objectify measurements. Manual digital image analysis (mDIA) requires a user-dependent annotation of the region of interest (ROI). Others have built-in machine learning algorithms with automated digital image analysis (aDIA) and can detect the ROIs automatically. We aimed to investigate the agreement between the results obtained by aDIA and those derived from mDIA systems.

METHODS

We quantified chromogenic intensity (CI) and calculated the positive index (PI) in cohorts of tissue microarrays (TMA) using mDIA and aDIA. To consider the different distributions of staining within cellular sub-compartments and different tumor architecture our study encompassed nuclear and cytoplasmatic stainings in adenocarcinomas and squamous cell carcinomas.

RESULTS

Within all cohorts, we were able to show a high correlation between mDIA and aDIA for the CI (p<0.001) along with high agreement for the PI. Moreover, we were able to show that the cell detections of the programs were comparable as well and both proved to be reliable when compared to manual counting.

CONCLUSION

mDIA and aDIA show a high correlation in acquired IHC data. Both proved to be suitable to stratify patients for evaluation with clinical data. As both produce the same level of information, aDIA might be preferable as it is time-saving, can easily be reproduced, and enables regular and efficient output in large studies in a reasonable time period.

Determination of the number of observers needed to evaluate a subjective test and its application in two PD-L1 studies

In pathological studies, subjective assays, especially companion diagnostic tests, can dramatically affect treatment of cancer. Binary diagnostic test results (ie, positive vs negative) may vary between pathologists or observers who read the tumor slides. Some tests have clearly defined criteria resulting in highly concordant outcomes, even with minimal training. Other tests are more challenging. Observers may achieve poor concordance even with training. While there are many statistically rigorous methods for measuring concordance between observers, we are unaware of a method that can identify how many observers are needed to determine whether a test can reach an acceptable concordance, if at all. Here we introduce a statistical approach to the assessment of test performance when the test is read by multiple observers, as would occur in the real world. By plotting the number of observers against the estimated overall agreement proportion, we can obtain a curve that plateaus to the average observer concordance. Diagnostic tests that are well-defined and easily judged show high concordance and plateau with few interobserver comparisons. More challenging tests do not plateau until many interobserver comparisons are made, and typically reach a lower plateau or even 0. We further propose a statistical test of whether the overall agreement proportion will drop to 0 with a large number of pathologists. The proposed analytical framework can be used to evaluate the difficulty in the interpretation of pathological test criteria and platforms, and to determine how pathology-based subjective tests will perform in the real world. The method could also be used outside of pathology, where concordance of a diagnosis or decision point relies on the subjective application of multiple criteria. We apply this method in two recent PD-L1 studies to test whether the curve of overall agreement proportion will converge to 0 and determine the minimal sufficient number of observers required to estimate the concordance plateau of their reads.

Interobserver variability in the assessment of stromal tumor-infiltrating lymphocytes (sTILs) in triple-negative invasive breast carcinoma influences the association with pathological complete response: the IVITA study

High stromal tumor-infiltrating lymphocytes (sTILs) in triple-negative breast cancer (TNBC) are associated with pathological complete response (pCR) after neoadjuvant chemotherapy (NAC). Histopathological assessment of sTILs in TNBC biopsies is characterized by substantial interobserver variability, but it is unknown whether this affects its association with pCR. Here, we aimed to investigate the degree of interobserver variability in an international study, and its impact on the relationship between sTILs and pCR. Forty pathologists assessed sTILs as a percentage in digitalized biopsy slides, originating from 41 TNBC patients who were treated with NAC followed by surgery. Pathological response was quantified by the MD Anderson Residual Cancer Burden (RCB) score. Intraclass correlation coefficients (ICCs) were calculated per pathologist duo and Bland-Altman plots were constructed. The relation between sTILs and pCR or RCB class was investigated. The ICCs ranged from -0.376 to 0.947 (mean: 0.659), indicating substantial interobserver variability. Nevertheless, high sTILs scores were significantly associated with pCR for 36 participants (90%), and with RCB class for eight participants (20%). Post hoc sTILs cutoffs at 20% and 40% resulted in variable associations with pCR. The sTILs in TNBC with RCB-II and RCB-III were intermediate to those of RCB-0 and RCB-I, with lowest sTILs observed in RCB-I. However, the limited number of RCB-I cases precludes any definite conclusions due to lack of power, and this observation therefore requires further investigation. In conclusion, sTILs are a robust marker for pCR at the group level. However, if sTILs are to be used to guide the NAC scheme for individual patients, the observed interobserver variability might substantially affect the chance of obtaining a pCR. Future studies should determine the 'ideal' sTILs threshold, and attempt to fine-tune the patient selection for sTILs-based de-escalation of NAC regimens. At present, there is insufficient evidence for robust and reproducible sTILs-guided therapeutic decisions.

Quantitative proteomics revealed the molecular characteristics of distinct types of granulated somatotroph adenomas

PURPOSE

Somatotroph adenomas are obviously heterogeneous in clinical characteristics, imaging performance, pathological diagnosis and therapeutic effect. The heterogeneity of the tumors, especially for SG and DG type adenomas, have attracted great interest in identifying the specific pathological markers and therapeutic targets of them. However, previous analyses of the molecular characteristics of the subtypes of somatotroph adenomas were performed at genomic and transcriptome level. The proteomic differences between the two subtypes of somatotroph adenomas are still unknown.

METHODS

Tumor samples were surgically removed from 10 sporadic pituitary somatotroph adenoma patients and grouped according to the pathological type. Tandem mass tag (TMT)-based quantitative proteomic analysis was employed to analyze the proteomic differences between SG and DG tumors.

RESULTS

In total, 228 differentially expressed proteins were identified between SG adenomas and DG adenomas. They were enriched mainly in extracellular matrix (ECM)-receptor interaction, leukocyte transendothelial migration, arrhythmogenic right ventricular cardiomyopathy and DNA replication pathways. Protein-protein interaction (PPI) network analysis indicated that Cadherin-1 and Catenin beta-1 were the most important key proteins in the differences between SG and DG adenomas. Immunohistochemistry (IHC) confirmed the expression levels of the key proteins.

CONCLUSIONS

This study provides large-scale proteome molecular characteristics of distinct granulation subtypes of somatotroph adenomas. Compared with DG adenomas, The differential protein of SG adenomas mostly enrich in invasive and proliferative functions and pathways at the proteomic level. Cadherin-1 and Catenin beta-1 play key roles in the different biological characteristics of the two tumor subtypes.

Independent Clinical Validation of the Automated Ki67 Scoring Guideline from the International Ki67 in Breast Cancer Working Group

Ki67 is an important biomarker with prognostic and potential predictive value in breast cancer. However, the lack of standardization hinders its clinical applicability. In this study, we aimed to investigate the reproducibility among pathologists following the guidelines of the International Ki67 in Breast Cancer Working Group (IKWG) for Ki67 scoring and to evaluate the prognostic potential of this platform in an independent cohort. Four algorithms were independently built by four pathologists based on our study cohort using an open-source digital image analysis (DIA) platform (QuPath) following the detailed guideline of the IKWG. The algorithms were applied on an ER+ breast cancer study cohort of 157 patients with 15 years of follow-up. The reference Ki67 score was obtained by a DIA algorithm trained on a subset of the study cohort. Intraclass correlation coefficient (ICC) was used to measure reproducibility. High interobserver reliability was reached with an ICC of 0.938 (CI: 0.920-0.952) among the algorithms and the reference standard. Comparing each machine-read score against relapse-free survival, the hazard ratios were similar (2.593-4.165) and showed independent prognostic potential (p ≤ 0.018, for all comparisons). In conclusion, we demonstrate high reproducibility and independent prognostic potential using the IKWG DIA instructions to score Ki67 in breast cancer. A prospective study is needed to assess the clinical utility of the IKWG DIA Ki67 instructions.

The LncRNA MIR503HG/miR-224-5p/TUSC3 Signaling Cascade Suppresses Gastric Cancer Development via Modulating ATF6 Branch of Unfolded Protein Response

Background

Unfolded protein response (UPR)-mediated tumor-promoting functions have been identified in multiple cancers, and this study focused on investigating the role and molecular mechanisms of UPR in modulating gastric cancer (GC) pathogenesis.

Methods

The bioinformatics analysis was performed to examine the expression status of cancer associated genes in patients with stomach adenocarcinoma (STAD) and predict the targeting sites of miR-224-5p with LncRNA MIR503HG and TUSC3. Genes expressions were quantified by Real-Time qPCR, Western Blot and immunohistochemistry (IHC). Cell proliferation, viability, apoptosis and mobility were evaluated by MTT assay, trypan blue staining assay, flow cytometer and transwell assay, respectively. The binding sites were validated by dual-luciferase reporter gene system assay.

Results

LncRNA MIR503HG and TUSC3 were downregulated, but miR-224-5p was upregulated in GC tissues and cells, in contrast with their normal counterparts. Further gain- and loss-of-function experiments validated that the malignant phenotypes in GC cells, including cell proliferation, invasion, epithelial-mesenchymal transition (EMT) and tumorigenesis, were negatively regulated by LncRNA MIR503HG. Mechanistically, LncRNA MIR503HG upregulated TUSC3 in GC cells through sponging miR-224-5p, resulting in the repression of GC progression. Finally, we validated that knock-down of ATF6, but not other two branches of UPR (PERK1 and IRE1), partially rescued cell proliferation and EMT in the GC cells with LncRNA MIR503HG overexpression.

Conclusions

Targeting the LncRNA MIR503HG/miR-224-5p/TUSC3 signaling cascade suppressed ATF6-mediated UPR, resulting in the blockage of GC development.

Breast tumour volume and blood flow measured by MRI after one cycle of epirubicin and cyclophosphamide-based neoadjuvant chemotherapy as predictors of pathological response

OBJECTIVES

Better markers of early response to neoadjuvant chemotherapy (NACT) in patients with breast cancer are required to enable the timely identification of non-responders and reduce unnecessary treatment side-effects. Early functional imaging may better predict response to treatment than conventional measures of tumour size. The purpose of this study was to test the hypothesis that the change in tumour blood flow after one cycle of NACT would predict pathological response.

METHODS

In this prospective cohort study, dynamic contrast-enhanced MRI was performed in 35 females with breast cancer before and after one cycle of epirubicin and cyclophosphamide-based NACT (EC90). Estimates of tumour blood flow and tumour volume were compared with pathological response obtained at surgery following completion of NACT.

RESULTS

Tumour blood flow at baseline (mean ± SD; 0.32 ± 0.17 ml/min/ml) reduced slightly after one cycle of NACT (0.28 ± 0.18 ml/min/ml). Following treatment 15 patients were identified as pathological responders and 20 as non-responders. There were no relationships found between tumour blood flow and pathological response. Conversely, tumour volume was found to be a good predictor of pathological response (smaller tumours did better) at both baseline (area under the receiver operating characteristic curve 0.80) and after one cycle of NACT (area under the receiver operating characteristic curve 0.81).

CONCLUSION & ADVANCES IN KNOWLEDGE

The change in breast tumour blood flow following one cycle of EC90 did not predict pathological response. Tumour volume may be a better early marker of response with such agents.

Investigations on the Role of the MicroRNA-338-5p/Wnt Family Member 2B (WNT2B) Axis in Regulating the Pathogenesis of Nasopharyngeal Carcinoma (NPC)

Background

The involvement of microRNA-338-5p in modulating NPC pathogenesis is still largely unknown, and this study aimed to investigate this issue.

Methods

The expressions of cancer associated genes were determined by Real-Time qPCR and Western Blot, and cell apoptosis was determined by flow cytometer (FCM). CCK-8 assay and colony formation assay were respectively used to determine cell proliferation and colony formation abilities. Transwell assay was used to evaluate cell migration. The expression levels of Ki67 protein in mice tissues were measured by Immunohistochemistry (IHC) assay.

Results

The present study found that microRNA-338-5p suppressed NPC progression by degrading its downstream target, Wnt family member 2B (WNT2B). Specifically, microRNA-338-5p tended to be low-expressed in NPC tissues and cell lines, compared to the non-tumor nasopharyngeal mucosa tissues and normal nasopharyngeal cell line (NP69). Upregulation of microRNA-338-5p inhibited proliferation, mobility, and epithelial-mesenchymal transition (EMT) in NPC cells in vitro, while silencing of microRNA-338-5p had opposite effects. Consistently, microRNA-338-5p suppressed tumorigenesis of NPC cells in vivo. In addition, microRNA-338-5p targeted WNT2B for degradation and inhibition, and the inhibiting effects of microRNA-338-5p overexpression on NPC development were reversed by upregulating WNT2B.

Conclusions

Taken together, we concluded that microRNA-338-5p targeted WNT2B to hinder NPC development.

Reliability of Ki67 visual scoring app compared to eyeball estimate and digital image analysis and its prognostic significance in hormone receptor-positive breast cancer

We analysed the reproducibility of Ki67 labelling index (LI) between two scorers using the International Ki67 Working Group (IKWG) global methods on an Android application (APP), correlated the APP and eyeball estimate (EBE) with digital image analysis (DIA) scores and determined the prognostic significance of Ki67LI. Global weighted (GW) and global unweighted (GUW) Ki67 app scores of hormone receptor-positive and HER2 (human epidermal growth factor receptor 2)-negative breast cancer patients were obtained. Reproducibility of Ki67LI between 2 scorers and correlation of APP and EBE scores with DIA scores were performed. The prognostic significance of APP scores and its correlation with other clinico-pathologic variables were evaluated. The intra-class correlation coefficient (ICC) between 2 scorers showed excellent reliability with both GW and GUW methods. ICC between DIA and APP scores was significantly greater than DIA versus EBE. The three categories of APP scores based on median value and cut points of 10%, 18% and 38% were significantly associated with poor DFS. On multivariate analysis, significant association between Ki67LI, tumour size, nodal involvement and DFS was noted. Our study shows that the visual Ki67 scoring app is effective in bringing consistency to KI67LI and APP scores showed significant correlation with DFS.

Prognostic relevance of Ki67 expression in primary male breast cancer: determination of cut-off points by different evaluation methods and statistical examinations

PURPOSE

1% of all breast cancer cases occur in men. There are significant differences regarding clinical behaviour and genetic profiles between female (FBC) and male breast cancer (MBC). Parameters for decision-making on treatment and prognosis are derived from FBC. Ki67 has a high value as a prognostic and predictive factor in FBC, but accurate Ki67 cut-off points for MBC are missing. In this study, we aimed to evaluate adequate examination methods and reliable cut-off points for Ki67 to assess the highest prognostic value for patient's overall survival (OS).

METHODS

In this multicentric retrospective study, histological specimens were obtained from 104 male patients who were diagnosed and treated for primary invasive breast cancer. We applied three methods of Ki67 analysis: Tumor average scoring (TA), tumor border scoring (TB) and hot-spot scoring (HS). Calculated Ki67 cut-off points for each method were assessed as a threshold for patients' overall survival (OS).

RESULTS

Ki67 cut-off points were 13.5 for the TA group, 22.5 for the HS group and 17.5 for the TB group. Only Ki67 TA cut-off calculations demonstrated statistical significance (p = 0.04). Ki67 expression analysis of TA showed that more than 90% of patients with low Ki67 levels (< 13.5) were alive after 5-year follow-up.

CONCLUSION

Our findings demonstrate that determination of Ki67 expression in TA is the most reliable to define a cut-off point with high prognostic value. A Ki67 cut-off point of 13.5 shows highest statistical power to define luminal A subgroup and OS.

A simple digital image analysis system for automated Ki67 assessment in primary breast cancer

AIMS

Ki67 is a well-established immunohistochemical marker associated with cell proliferation that has prognostic and predictive value in breast cancer. Quantitative evaluation of Ki67 is traditionally performed by assessing stained tissue slides with light microscopy. Automated image analysis systems have become available and, if validated, could provide greater standardisation and improved precision of Ki67 scoring. Here, we aimed to evaluate the use of the Cognition Master Professional Suite (CogM) image analysis software, which is a simple system for scoring Ki67 in primary breast cancer samples.

METHODS AND RESULTS

Sections from 94 core-cut biopsies, 20 excision specimens and 29 pairs of core-cut biopsies and excision specimens were stained for Ki67 with MIB1 antibody and the Dako EnVision FLEX Detection System. Stained slides were scanned to convert them to digital data. Computer-based Ki67 scoring was performed with CogM. Manual Ki67 scoring assessment was conducted on previously stained sections from the same biopsies with a clinically validated system that had been calibrated against the risk of recurrence. A high correlation between manual and digital scores was observed [r_Cores  = 0.92, 95% confidence interval (CI) 0.87-0.94, P < 0.0001; r_Excisions  = 0.95, 95% CI 0.86-0.98, P < 0.0001] and there was no significant bias between them (P = 0.45). There was also a high correlation of Ki67 scores between paired core-cut biopsies and excision specimens when CogM was used (r = 0.78, 95% CI 0.59-0.89, P < 0.0001).

CONCLUSIONS

CogM image analysis allows for standardised automated Ki67 scoring that accurately replicates previously clinically validated and calibrated manual scores.

Ki-67 Proliferation Index Assessment in Gastroenteropancreatic Neuroendocrine Tumors by Digital Image Analysis With Stringent Case and Hotspot Level Concordance Requirements

OBJECTIVES

The Ki-67 proliferation index is integral to gastroenteropancreatic neuroendocrine tumor (GEP-NET) assessment. Automated Ki-67 measurement would aid clinical workflows, but adoption has lagged owing to concerns of nonequivalency. We sought to address this concern by comparing 2 digital image analysis (DIA) platforms to manual counting with same-case/different-hotspot and same-hotspot/different-methodology concordance assessment.

METHODS

We assembled a cohort of GEP-NETs (n = 20) from 16 patients. Two sets of Ki-67 hotspots were manually counted by three observers and by two DIA platforms, QuantCenter and HALO. Concordance between methods and observers was assessed using intraclass correlation coefficient (ICC) measures. For each comparison pair, the number of cases within ±0.2xKi-67 of its comparator was assessed.

RESULTS

DIA Ki-67 showed excellent correlation with manual counting, and ICC was excellent in both within-hotspot and case-level assessments. In expert-vs-DIA, DIA-vs-DIA, or expert-vs-expert comparisons, the best-performing was DIA Ki-67 by QuantCenter, which showed 65% cases within ±0.2xKi-67 of manual counting.

CONCLUSIONS

Ki-67 measurement by DIA is highly correlated with expert-assessed values. However, close concordance by strict criteria (>80% within ±0.2xKi-67) is not seen with DIA-vs-expert or expert-vs-expert comparisons. The results show analytic noninferiority and support widespread adoption of carefully optimized and validated DIA Ki-67.

Interobserver concordance in visual assessment of Ki67 immunohistochemistry in surgical excision specimens from patients with lymph node-negative breast cancer

PURPOSE

This study aimed to determine the interobserver concordance of two methods for proliferation assessment in breast cancer using Ki67 immunohistochemistry.

METHODS

Ki67 was independently assessed in randomly selected tumour samples from patients with lymph node-negative breast cancer using two different methods: either cell counting or visual estimation of hot spot areas. For hot spot cell counting, positive and negative cell numbers were recorded for total cell counts of 300-500, 500-800 and 800-1000 cells. Visual estimation involved allocation of a score from 1 to 5 using a visual scale to estimate percentage positivity. Interobserver agreement for hot spot counting was calculated using a two-way fixed effects intraclass correlation model, and by using Cohen's kappa measure for visual assessment. Prognostic concordance between the two methods was also calculated using Cohen's kappa.

RESULTS

Samples from 96 patients were included in this analysis. Interobserver agreement for hot spot cell counting was excellent (> 0.75) across all three cell count ranges, with correlation coefficients of 0.88 (95% CI 0.84-0.92), 0.87 (95% CI 0.82-0.91) and 0.89 (95% CI 0.85-0.92), respectively. Interobserver agreement with visual estimation was greatest for hot spots compared with areas of intermediate or low proliferation, with kappa scores of 0.49, 0.42 and 0.40, respectively. Both assessment methods demonstrated excellent prognostic agreement.

CONCLUSIONS

Interobserver and prognostic concordance in Ki67 immunohistochemistry assessments was high using either hot spot cell counting or visual estimation, further supporting the utility and reproducibility of these cost-efficient methods to assess proliferation.

Multi-protein spatial signatures in ductal carcinoma in situ (DCIS) of breast

BACKGROUND

There is limited knowledge about DCIS cellular composition and relationship with breast cancer events (BCE).

METHODS

Immunofluorescence multiplexing (MxIF) was used to image and quantify 32 cellular biomarkers in FFPE DCIS tissue microarrays. Over 75,000 DCIS cells from 51 patients (median 9 years follow-up for non-BCE cases) were analysed for profiles predictive of BCE. K-means clustering was used to evaluate cellular co-expression of epithelial markers with ER and HER2.

RESULTS

Only ER, PR and HER2 significantly correlated with BCE. Cluster analysis identified 6 distinct cell groups with different levels of ER, Her2, cMET and SLC7A5. Clusters 1 and 3 were not significant. Clusters 2 and 4 (high ER/low HER2 and SLC7A5/mixed cMET) significantly correlated with low BCE risk (P = 0.001 and P = 0.034), while cluster 6 (high HER2/low ER, cMET and SLC7A5) correlated with increased risk (P = 0.018). Cluster 5 (similar to cluster 6, except high SLC7A5) trended towards significance (P = 0.072). A continuous expression score (Escore) based on these 4 clusters predicted likelihood of BCE (AUC = 0.79, log-rank test P = 5E-05; LOOCV AUC = 0.74, log-rank test P = 0.006).

CONCLUSION

Multiplexed spatial analysis of limited tissue is a novel method for biomarker analysis and predicting BCEs. Further validation of Escore is needed in a larger cohort.