Variability of predictive markers (hormone receptors, Her2, Ki67) and intrinsic subtypes of breast cancer in four consecutive years 2015-2018

The effect of total size, area, and volume of lesions in multifocal/multicentric breast cancers and unifocal breast cancers on survival: An observational study

In this study, we aimed to investigate the prognostic effect of the classifications made according to the stage of the largest lesion diameter (T-max stage) and of the sum of the longest diameters of the lesions (T-sum stage), the largest area stage (A-max stage), the sum of the largest areas (A-sum stage), the highest volume stage (V-max stage), the sum of the highest volume (V-sum stage) on disease-free survival, and overall survival (OS) in multifocal/multicentric breast cancers (MMBCs) and unifocal breast cancers (UBCs). The study included a total of 769 patients either with MMBC (n = 128) or UBC (n = 641) who underwent surgery between 2006 and 2015. In the analysis, the median age of 769 patients was 53.0 (20.0-94.0) years, and 16.6% of these 769 patients were MMBC and 83.4% were UBC. In multivariate analysis, lymphovascular invasion (LVİ), estrogen receptor, and nodal status were common independent prognostic factors, whereas T-max stage [(HR: 1.17) (CI 95%: 1.03-1.33) (P = .018)] was a prognostic factor for OS. In multivariate analysis, the T-max stage is an independent risk factor for OS. Therefore, T-max should be continued to be used for measurement and T-stage should be used for classification in MMBCs/UBCs.

External Quality Assurance Helps Improve Infrastructure for Testing Breast Biomarkers Across a Lower- and Middle-Income Country: Our Experience With Breast Biomarker Testing in the National Cancer Grid External Quality Assurance System in India

CONTEXT.—

Biomarkers in breast cancer need strict monitoring given their role in patient management.

OBJECTIVE.—

To study the impact that regular participation in the National Cancer Grid (NCG) external quality assurance (EQA) system has on concordance rates for biomarkers in breast carcinoma.

DESIGN.—

Tissue microarrays (TMAs) containing breast carcinomas were circulated to participating laboratories that performed immunohistochemistry for breast biomarkers. The returned TMAs were then assessed for test concordance.

RESULTS.—

A total of 105 laboratories participated in the estrogen receptor (ER) and progesterone receptor (PR) EQA system cycles, and 99 centers participated in the human epidermal growth factor 2 (HER2) EQA system. In the ER EQA in the first cycle only 1 laboratory had a 100% concordance rate, which improved to 59 of 77 (76.6%) and 85 of 97 (87.6%) in the fourth and fifth cycles, respectively. In the PR EQA the 100% pass rate jumped from zero to 52 of 76 (68.4%) in the fourth cycle and 86 of 97 (88.6%) in the last cycle. For HER2 EQA, the 100% pass rates were seen in 7 of 23 laboratories (30.4%) in the first cycle, 49 of 78 laboratories (62.8%) in the fourth cycle, and 48 of 94 laboratories (51.1%) in fifth cycle of EQA. Centers that participated in the NCG EQA system for a longer period often changed testing methodology, with consequent improvement in their laboratory concordance rates. An increasing trend for the use of automated platforms and of the US Food and Drug Administration-approved antibody for HER2 testing was observed.

CONCLUSIONS.—

Our experience demonstrates that laboratory performance improves with participation in an EQA system even in less perfect settings, and this drives the placement of more proficient practices across the country.

Molecular pathology in breast disease: diagnostic, prognostic, and therapeutic tools

Molecular testing in breast cancer gained increasing attention and importance as specific molecular results can tailor not only oncological decisions on systemic adjuvant or neoadjuvant or in metastatic setting, but increasingly serve in diagnostic routine histopathological services to differentiate between morphologically overlapping or ambiguous histological pictures. Diagnostic tools involve in most cases a broad spectrum of immunohistochemical panels, followed by entity-specific in situ hybridization probes and in given cases NGS-based sequencing. Workflow of which methodology is applied and in which order depends on the specific entity resp. on the given differential diagnosis in question. Regarding prognostic/predictive molecular testing, the choice of assay and the workflow are based on clinical algorithms and on the evidence of targeted therapies following the molecular alterations. In this review paper, we aim to address the use of molecular technics in [1] the histological diagnostic setting (such as subtyping of invasive carcinomas/malignant spindle cell tumors and sarcomas and some B3 lesions) and [2] in the context of adjuvant or neoadjuvant or other clinical settings with special focus of targeted therapies.

Whole-Tumor ADC Texture Analysis Is Able to Predict Breast Cancer Receptor Status

There are different breast cancer molecular subtypes with differences in incidence, treatment response and outcome. They are roughly divided into estrogen and progesterone receptor (ER and PR) negative and positive cancers. In this retrospective study, we included 185 patients augmented with 25 SMOTE patients and divided them into two groups: the training group consisted of 150 patients and the validation cohort consisted of 60 patients. Tumors were manually delineated and whole-volume tumor segmentation was used to extract first-order radiomic features. The ADC-based radiomics model reached an AUC of 0.81 in the training cohort and was confirmed in the validation set, which yielded an AUC of 0.93, in differentiating ER/PR positive from ER/PR negative status. We also tested a combined model using radiomics data together with ki67% proliferation index and histological grade, and obtained a higher AUC of 0.93, which was also confirmed in the validation group. In conclusion, whole-volume ADC texture analysis is able to predict hormonal status in breast cancer masses.

Comparison of HercepTest™ mAb pharmDx (Dako Omnis, GE001) with Ventana PATHWAY anti-HER-2/neu (4B5) in breast cancer: correlation with HER2 amplification and HER2 low status

Performance of the new CE-IVD-marked HercepTest™ mAb pharmDx (Dako Omnis) assay (HercepTest (mAb)) was compared against the PATHWAY® anti-HER-2/neu (4B5) (PATHWAY 4B5) assay using 119 pre-selected breast cancer samples covering the entire range of HER2 immunohistochemistry (IHC) expression scores (0, 1 + , 2 + , 3 +). The sensitivity and specificity of both assays were assessed based on consensus IHC scores and amplification status, as determined by fluorescence in situ hybridization (FISH) according to 2018 ASCO/CAP testing guidelines. There was a high concordance between results from the HercepTest (mAb) and PATHWAY 4B5 assays for HER2-negative (IHC 0, 1 + , 2 + and FISH negative) and HER2-positive (IHC 3 + , 2 + and FISH positive) breast carcinomas (98.2%). Regarding individual IHC scores, complete agreement was achieved in 69.7% (83/119) of cases, and all but one of the discordant cases were due to higher HER2-status scoring using the HercepTest (mAb). Thus, more tumors were overscored as IHC 2 + by HercepTest (mAb) (27 versus 15) as evidenced by their lower FISH positivity rate (48.1% versus 80%). However, two amplified tumors identified as IHC 2 + by HercepTest (mAb) were missed by PATHWAY 4B5 (IHC 1 +). Four additional cases identified as IHC 2 + by HercepTest (mAb), with FISH ratio < 2 but elevated gene counts (≥ 4 to < 6), were recorded negative by PATHWAY 4B5. The HercepTest (mAb) detects HER2 expression with higher sensitivity in tumors with gene amplification (ISH group 1) and increased gene counts (ISH group 4) as well as in HER2-low tumors (HER2 IHC2 + /FISH negative or IHC 1 +). Future studies will demonstrate whether this translates into improved patient selection especially for new HER2-directed therapies.

Assessment of Predictive Biomarkers in Breast Cancer: Challenges and Updates

The management of patients with breast cancer (BC) relies on the assessment of a defined set of well-established prognostic and predictive markers. Despite overlap, prognostic markers are used to assess the risk of recurrence and the likely benefit of systemic therapy, whereas predictive markers are used to determine the type of systemic therapy to be offered to an individual patient. In this review, we provide an update and present some challenges in the assessment of the main BC-specific molecular predictive markers, namely hormone receptors (oestrogen receptor [ER] and progesterone receptor [PR]), human epidermal growth factor receptor 2 (HER2), and KI67. As the main platform for assessing these markers in BC is immunohistochemistry (IHC), we address the cut-off values used to define positivity, the ER-low subgroup, the existence and significance of the ER-/PR+ phenotype, the use of PR in routine practice, and the role of hormone receptors in ductal carcinoma in situ. We discuss the newly introduced HER2-low class of BC and the clinical/biological difference between different HER2 groups (e.g., HER2 IHC score 3+ BCs vs. those with a HER2 IHC score 2+ with HER2 gene amplification). The review concludes with an update on the applications of KI67 assessment in BC and observations on the role of immune checkpoint identification in BC.

Knockdown of circ_0067934 inhibits gastric cancer cell proliferation, migration and invasion via the miR‑1301‑3p/KIF23 axis

In recent years, circular RNAs (circRNAs/circs) have attracted significant attention due to their potentially important functions in a variety of human cancer types. circ_0067934 is a newly identified circRNA, the role of which in gastric cancer (GC) has yet to be reported, to the best of our knowledge. In the present study, the expression levels of circ_0067934, microRNA (miR)‑1301‑3p and kinesin family member 23 (KIF23) in GC cells were detected via reverse transcription‑quantitative PCR. Cell proliferation was measured using Cell Counting Kit‑8 assays and EdU staining. Wound healing and Transwell assays were performed to assess cell migration and invasion, respectively. Western blotting was performed to measure the protein expression levels of Ki67, proliferating cell nuclear antigen, MMP2, MMP9 and KIF23. The starBase database and luciferase reporter assays were used to predict and verify the binding between circ_0067934 and miR‑1301‑3p, as well as KIF23, in GC cells. The results demonstrated that circ_0067934 expression was upregulated in GC cells, and circ_0067934 silencing significantly inhibited GC cell proliferation, migration and invasion. In addition, miR‑1301‑3p was regulated by circ_0067934, and miR‑1301‑3p overexpression suppressed GC cell migration, invasion and proliferation. miR‑1301‑3p was found to target KIF23, and KIF23 overexpression reversed the effects of circ_0067934 silencing and miR‑1301‑3p overexpression on cell proliferation, migration and invasion. In conclusion, circ_0067934 may regulate the proliferation, invasion and migration of GC cells via the miR‑1301‑3p/KIF23 signaling axis, which may represent a novel therapeutic target for GC metastasis.

Biomarker dynamics and prognosis in breast cancer after neoadjuvant chemotherapy

Breast cancer is a biologically diverse disease with treatment modalities selected based on tumor stage and tumor biology. Distinct intrinsic subtypes and surrogate biomarker profiles play a major role for therapeutic decisions. Response rates to systemic and local treatments as well as the interaction with epidemiological risk factors have been validated in clinical trials and translational studies. This retrospective study addresses the question how biomarker profiles and treatment modalities in the neoadjuvant chemotherapy setting have changed during the past 15 years and what prognostic impact these changes implicate. 342 female breast cancer stage I-IV patients receiving neoadjuvant chemotherapy between 2003 and 2017 were analyzed. Overall survival (OS) was correlated with preoperative clinical stage, postoperative pathological stage, treatment modalities and tumor biology before and after chemotherapy. Two subgroups were separated using an arbitrary cut-off year at 2009/2010, due to 2010 when platinum containing regimens were first administered. Median follow-up was 54 months. 57 (17%) patients died; recurrences occurred in 103 of 342 (30%) patients. Nodal stage and intrinsic subtypes (pre- and postoperative) significantly correlated with OS (p < 0.001). Preoperative histological grading lacked prognostic power. When comparing the patient characteristics of the subgroups, we found significant difference in the following characteristics: cT, ypT, ypN, pCR and chemotherapy regimens (p < 0.001). There was no difference in OS when comparing the two subgroups. Pathological complete response (pCR) rates had a significant impact on OS and disease-free survival (DFS) in HER2+ and triple negative subtypes (p = 0.03). In multivariate analysis, high proliferation index (> 30%), clinical metastatic stage and pathological tumor stage had prognostic impact on OS (p < 0.001, p = 0.0001, p = 0.002). Clinico-pathological factors and distinct therapy regiments especially in triple negative and HER2+ subtypes have prognostic impact on pCR, OS and DFS after neoadjuvant chemotherapy.

Glioblastoma stem cell (GSC)-derived PD-L1-containing exosomes activates AMPK/ULK1 pathway mediated autophagy to increase temozolomide-resistance in glioblastoma

Temozolomide (TMZ)-resistance hampers the therapeutic efficacy of this drug for glioblastoma (GBM) treatment in clinic, and emerging evidences suggested that exosomes from GBM-derived stem cells (GSCs) contributed to this process, but the detailed mechanisms are still largely unknown. In the present study, we reported that GSCs derived programmed death-ligand 1 (PD-L1) containing exosomes activated AMPK/ULK1 pathway mediated protective autophagy enhanced TMZ-resistance in GBM in vitro and in vivo. Specifically, we noticed that continuous low-dose TMZ stimulation promoted GSCs generation and PD-L1 containing exosomes (PD-L1-ex) secretion in GBM cells, and that PD-L1-ex inhibited cell apoptosis and promoted cell autophagy to increased TMZ-resistance in GBM cells, which were reversed by co-treating cells with the autophagy inhibitor 3-methyladenine (3-MA). Consistently, upregulation of PD-L1 also increased TMZ-resistance in TS-GBM cells, and silencing of PD-L1 sensitized TR-GBM cells to TMZ. In addition, PD-L1-ex activated AMPK/ULK1 pathway to induce autophagy in TMZ treated GBM cells, and the inhibitors for AMPK (compound C) and ULK1 (SBI-0206965) promoted cell apoptosis in GBM cells co-treated with PD-L1-ex and high-dose TMZ. Finally, we evidenced that PD-L1-ex promoted tumor growth and Ki67 protein expressions to increase TMZ-resistance in GBM in vivo. Collectively, we concluded that GSCs-derived PD-L1-ex activated AMPK1/ULK1 signaling cascade mediated autophagy to increase TMZ-resistance in GBM, and this study provided potential strategies to improve the therapeutic efficacy of TMZ in GBM.

Prognostic potential of automated Ki67 evaluation in breast cancer: different hot spot definitions versus true global score

PURPOSE

The proliferation-associated biomarker Ki67 has potential utility in breast cancer, including aiding decisions based on prognosis, but has unacceptable inter- and intralaboratory variability. The aim of this study was to compare the prognostic potential for Ki67 hot spot scoring and global scoring using different digital image analysis (DIA) platforms.

METHODS

An ER+/HER2- breast cancer cohort (n = 139) with whole slide images of sequential sections stained for hematoxylin-eosin, pancytokeratin and Ki67, was analyzed using two DIA platforms. For hot spot analysis virtual dual staining was applied, aligning pancytokeratin and Ki67 images and 22 hot spot algorithms with different features were designed. For global Ki67 scoring an automated QuPath algorithm was applied on Ki67-stained whole slide images. Clinicopathological data included overall survival (OS) and recurrence-free survival (RFS) along with PAM50 molecular subtypes.

RESULTS

We show significant variations in Ki67 hot spot scoring depending on number of included tumor cells, hot spot size, shape and location. The higher the number of scored tumor cells, the higher the reproducibility of Ki67 proliferation values. Hot spot scoring had greater prognostic potential for RFS in high versus low Ki67 subgroups (hazard ratio (HR) 6.88, CI 2.07-22.87, p = 0.002), compared to global scoring (HR 3.13, CI 1.41-6.96, p = 0.005). Regarding OS, global scoring (HR 7.46, CI 2.46-22.58, p < 0.001) was slightly better than hot spot scoring (HR 6.93, CI 1.61-29.91, p = 0.009). In adjusted multivariate analysis, only global scoring was an independent prognostic marker for both RFS and OS. In addition, global Ki67-based surrogate subtypes reached higher concordance with PAM50 molecular subtype for luminal A and B tumors (66.3% concordance rate, κ = 0.345), than using hot spot scoring (55.8% concordance rate, κ = 0.250).

CONCLUSIONS

We conclude that the automated global Ki67 scoring is feasible and shows clinical validity, which, however, needs to be confirmed in a larger cohort before clinical implementation.

Accuracy and efficiency of an artificial intelligence tool when counting breast mitoses

BACKGROUND

The mitotic count in breast carcinoma is an important prognostic marker. Unfortunately substantial inter- and intra-laboratory variation exists when pathologists manually count mitotic figures. Artificial intelligence (AI) coupled with whole slide imaging offers a potential solution to this problem. The aim of this study was to accordingly critique an AI tool developed to quantify mitotic figures in whole slide images of invasive breast ductal carcinoma.

METHODS

A representative H&E slide from 320 breast invasive ductal carcinoma cases was scanned at 40x magnification. Ten expert pathologists from two academic medical centers labeled mitotic figures in whole slide images to train and validate an AI algorithm to detect and count mitoses. Thereafter, 24 readers of varying expertise were asked to count mitotic figures with and without AI support in 140 high-power fields derived from a separate dataset. Their accuracy and efficiency of performing these tasks were calculated and statistical comparisons performed.

RESULTS

For each experience level the accuracy, precision and sensitivity of counting mitoses by users improved with AI support. There were 21 readers (87.5%) that identified more mitoses using AI support and 13 reviewers (54.2%) that decreased the quantity of falsely flagged mitoses with AI. More time was spent on this task for most participants when not provided with AI support. AI assistance resulted in an overall time savings of 27.8%.

CONCLUSIONS

This study demonstrates that pathology end-users were more accurate and efficient at quantifying mitotic figures in digital images of invasive breast carcinoma with the aid of AI. Higher inter-pathologist agreement with AI assistance suggests that such algorithms can also help standardize practice. Not surprisingly, there is much enthusiasm in pathology regarding the prospect of using AI in routine practice to perform mundane tasks such as counting mitoses.

Do YOU know the Ki-67 index of your breast cancer patients? Knowledge of your institution's Ki-67 index distribution and its robustness is essential for decision-making in early breast cancer

OBJECTIVES

The proliferative activity of the Ki-67 index is important in decision-making of adjuvant treatments in early breast cancer. Its reliability can be reduced by inter-observer variability. This analysis' objective is to evaluate the robustness of Ki-67 values within one center over 5 years and to compare its distribution with a published dataset.

MATERIALS AND METHODS

Ki-67 indices of early breast cancers treated at St. Gallen Breast Center were collected (2010-2014; 1154 patients). Distribution of Ki-67 values was analyzed for each year, along with histologic subtype and grading. Tumors were classified into intrinsic subtypes using two definitions: 2013 St. Gallen Consensus and the refined definition by Maisonneuve ("Milano Group"). Our institution's Ki-67 cut-off value was adjusted to obtain the same distribution of luminal subtypes as published data of the Milano Group.

RESULTS

Ki-67 index frequency distributions were comparable between years (mean 26-30%, median 22-26%). Shape and position of the distribution curves were nearly identical. Ki-67 values correlated with tumor grade (median Ki-67: G1: 12.0%, G2: 21%, G3: 38%). Standard deviation of Ki-67 increased with higher grading (G1: 6.9; G2: 9.2; G3: 18.2; p < 0.001). According to the 2013 definition (and refined definition respectively), there were 35% (41%) luminal A-like and 65% (59%) luminal B-like tumors. To obtain the same distribution as the Milano group, Ki-67 cut-off needed to be elevated to 22%.

CONCLUSIONS

Ki-67 index assessment was comparable over many years. Knowledge of one's institution's Ki-67 value distribution is essential for clinical decision-making of adjuvant therapies in early breast cancer.