Although counting mitoses is part of breast cancer grading, concordance studies showed low agreement. Refining the criteria for mitotic counting can improve concordance, particularly when using whole ...slide images (WSIs). This study aims to refine the methodology for optimal mitoses counting on WSI. Digital images of 595 hematoxylin and eosin stained sections were evaluated. Several morphological criteria were investigated and applied to define mitotic hotspots. Reproducibility, representativeness, time, and association with outcome were the criteria used to evaluate the best area size for mitoses counting. Three approaches for scoring mitoses on WSIs (single and multiple annotated rectangles and multiple digital high-power (×40) screen fields (HPSFs)) were evaluated. The relative increase in tumor cell density was the most significant and easiest parameter for identifying hotspots. Counting mitoses in 3 mm2 area was the most representative regarding saturation and concordance levels. Counting in area <2 mm2 resulted in a significant reduction in mitotic count (P = 0.02), whereas counting in area ≥4 mm2 was time-consuming and did not add a significant rise in overall mitotic count (P = 0.08). Using multiple HPSF, following calibration, provided the most reliable, timesaving, and practical method for mitoses counting on WSI. This study provides evidence-based methodology for defining the area and methodology of visual mitoses counting using WSI. Visual mitoses scoring on WSI can be performed reliably by adjusting the number of monitor screens.
The use of proliferation markers provides valuable information about the rate of tumor growth, which can guide treatment decisions. However, there is still a lack of consensus regarding the optimal ...molecular markers or tests to use in clinical practice. Integrating gene expression data with clinical and histopathologic parameters enhances our understanding of disease processes, facilitates the identification of precise prognostic predictors, and supports the development of effective therapeutic strategies. The purpose of this study was to apply an integrated approach that combines morphologic, clinical, and bioinformatic data to reveal effective regulators of proliferation. Whole-slide images generated from hematoxylin-and-eosin–stained sections of The Cancer Genome Atlas (TCGA) breast cancer (BC) database (n = 1053) alongside their transcriptomic and clinical data were used to identify genes differentially expressed between tumors with high and low mitotic scores. Genes enriched in the cell-cycle pathway were used to predict the protein-protein interaction (PPI) network. Ten hub genes (ORC6, SKP2, SMC1B, CDKN2A, CDC25B, E2F1, E2F2, ORC1, PTTG1, and CDC25A) were identified using CytoHubba a Cytoscape plugin. In a multivariate Cox regression model, ORC6 and SKP2 were predictors of survival independent of existing methods of proliferation assessment including mitotic score and Ki67. The prognostic ability of these genes was validated using the Molecular Taxonomy of Breast Cancer International Consortium, Nottingham cohort, Uppsala cohort, and a combined multicentric cohort. The protein expression of these 2 genes was investigated on a large cohort of BC cases, and they were significantly associated with poor prognosis and patient outcome. A positive correlation between ORC6 and SKP2 mRNA and protein expression was observed. Our study has identified 2 gene signatures, ORC6 and SKP2, which play a significant role in BC proliferation. These genes surpassed both mitotic scores and Ki67 in multivariate analysis. Their identification provides potential opportunities for the development of targeted treatments for patients with BC.
Background
Mitotic count in breast cancer is an important prognostic marker. Unfortunately, substantial inter‐ and intraobserver variation exists when pathologists manually count mitotic figures. To ...alleviate this problem, we developed a new technique incorporating both haematoxylin and eosin (H&E) and phosphorylated histone H3 (PHH3), a marker highly specific to mitotic figures, and compared it to visual scoring of mitotic figures using H&E only.
Methods
Two full‐face sections from 97 cases were cut, one stained with H&E only, and the other was stained with PHH3 and counterstained with H&E (PHH3–H&E). Counting mitoses using PHH3–H&E was compared to traditional mitoses scoring using H&E in terms of reproducibility, scoring time, and the ability to detect mitosis hotspots. We assessed the agreement between manual and image analysis‐assisted scoring of mitotic figures using H&E and PHH3–H&E‐stained cells. The diagnostic performance of PHH3 in detecting mitotic figures in terms of sensitivity and specificity was measured. Finally, PHH3 replaced the mitosis score in a multivariate analysis to assess its significance.
Results
Pathologists detected significantly higher mitotic figures using the PHH3–H&E (median ± SD, 20 ± 33) compared with H&E alone (median ± SD, 16 ± 25), P < 0.001. The concordance between pathologists in identifying mitotic figures was highest when using the dual PHH3–H&E technique; in addition, it highlighted mitotic figures at low power, allowing better agreement on choosing the hotspot area (k = 0.842) in comparison with standard H&E (k = 0.625). A better agreement between image analysis‐assisted software and the human eye was observed for PHH3‐stained mitotic figures. When the mitosis score was replaced with PHH3 in a Cox regression model with other grade components, PHH3 was an independent predictor of survival (hazard ratio HR 5.66, 95% confidence interval CI 1.92–16.69; P = 0.002), and even showed a more significant association with breast cancer‐specific survival (BCSS) than mitosis (HR 3.63, 95% CI 1.49–8.86; P = 0.005) and Ki67 (P = 0.27).
Conclusion
Using PHH3–H&E‐stained slides can reliably be used in routine scoring of mitotic figures and integrating both techniques will compensate for each other's limitations and improve diagnostic accuracy, quality, and precision.
Table 1. Correlation between PHH3 expression with clinicopathological variables; Table 2. Correlation between MAI, with PHH3 and Ki67; Table 3. Multivariate cox regression analysis results for (A) adding PHH3 to predictors of survival (grade and stage), (B) adding PHH3 to mitosis and Ki67 score (C) components of grade (D) components of grade with the replacement of mitosis score with PHH3 score (E) components of grade with the replacement of mitosis score with Ki67 score.
Background
KN motif and ankyrin repeat domains 1 (KANK1) plays an important role in cytoskeleton maintenance and contributes to the regulation of cell proliferation, adhesion and apoptosis. KANK1 is ...involved in progression of a variety of solid tumours; however, its role in invasive breast cancer (BC) remains unknown. This study aims to evaluate the clinicopathological and prognostic value of KANK1 expression in operable BC.
Methods
KANK1 expression was assessed at the transcriptomic level using multiple BC cohorts; the Molecular Taxonomy of BC International Consortium cohort (METABRIC;
n
= 1980), The Cancer Genome Atlas BC cohort (TCGA;
n
= 949) and the publicly available BC transcriptomic data hosted by BC Gene-Expression Miner (bc-GenExMiner v4.0) and Kaplan–Meier plotter?. The Nottingham BC cohort (
n
= 1500) prepared as tissue microarrays was used to assess KANK1 protein expression using immunohistochemistry (IHC). The association between clinicopathological variables and patient outcome was investigated.
Results
In the METABRIC cohort, high expression of
KANK1
mRNA was associated with characteristics of good prognosis including lower grade, absence of lymphovascular invasion and HER2 negativity (all;
p
< 0.001) and with better outcome
p
= 0.006, Hazards ratio, (HR) 0.70, 95% CI 0.54–0.91. High KANK1 protein expression was correlated with smaller tumour size and HER2 negativity, and better outcome in terms of longer breast cancer-specific survival
p
= 0.013, HR 0.7, 95% CI 0.536–0.893 and time to distant metastasis
p
= 0.033, HR 0.65, 95% CI 0.51–0.819.
Conclusion
These results supported that upregulation of KANK1 works as a tumour suppressor gene in BC and is associated with improved patients’ outcomes.
Purpose
CD133/ prominin 1 is a cancer stem cell marker associated with cancer progression and patient outcome in a variety of solid tumours, but its role in invasive breast cancer (BC) remains ...obscure. The current study aims to assess the prognostic value of CD133 expression in early invasive BC.
Methods
CD133
mRNA was assessed in the METABRIC cohort and at the proteomic level using immunohistochemistry utilising a large well-characterised BC cohort. Association with clinicopathological characteristics, expression of other stem cell markers and patient outcome were evaluated.
Results
High expression of CD133 either in mRNA or protein levels was associated with characteristics of poor prognosis including high tumour grade, larger tumour size, high Nottingham Prognostic Index, HER2 positivity and hormonal receptor negativity (all;
p
< 0.001). High CD133 expression was positively associated with proliferation biomarkers including p16, Cyclin E and Ki67 (
p
< 0.01). Tumours expressing CD133 showed higher expression of other stem cell markers including CD24, CD44, SOX10, ALDHA3 and ITGA6. High expression of CD133 protein was associated with shorter BC-specific survival (
p
= 0.026). Multivariate analysis revealed that CD133 protein expression was an independent risk factor for shorter BC-specific survival (
p
= 0.038).
Conclusion
This study provides evidence for the prognostic value of CD133 in invasive BC. A strong positive association of BC stem cell markers is observed at the protein level. Further studies to assess the value of stem cell markers individually or in combination in BC is warranted.
Purpose
Nucleolar protein 10 (NOP10) is required for ribosome biogenesis and telomere maintenance and plays a key role in carcinogenesis. This study aims to evaluate the clinical and prognostic ...significance of NOP10 in breast cancer (BC).
Methods
NOP10
expression was assessed at mRNA level employing the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) (
n
= 1980) and Cancer Genome Atlas (TCGA) BC cohorts (
n
= 854). Protein expression was evaluated on tissue microarray of a large BC cohort (
n
= 1081) using immunohistochemistry. The correlation between NOP10 expression, clinicopathological parameters and patient outcome was assessed.
Results
NOP10 expression was detected in the nucleus and nucleolus of the tumour cells. At the transcriptomic and proteomic levels, NOP10 was significantly associated with aggressive BC features including high tumour grade, high nucleolar score and poor Nottingham Prognostic Index. High NOP10 protein expression was an independent predictor of poor outcome in the whole cohort and in triple-negative BC (TNBC) class (
p
= 0.002 &
p
= 0.014, respectively). In chemotherapy- treated patients, high NOP10 protein expression was significantly associated with shorter survival (
p
= 0.03) and was predictive of higher risk of death (
p
= 0.028) and development of distant metastasis (
p
= 0.02) independent of tumour size, nodal stage and tumour grade.
Conclusion
High NOP10 expression is a poor prognostic biomarker in BC and its expression can help in predicting chemotherapy resistance. Functional assessments are necessary to decipher the underlying mechanisms and to reveal its potential therapeutic values in various BC subtypes especially in the aggressive TNBC class.
Background
The routine assessment of progesterone receptor (PR) expression in breast cancer (BC) remains controversial. This study aimed to evaluate the role of PR expression in luminal BC, with ...emphasis on the definition of positivity and its prognostic significance as compared to Ki67 expression.
Methods
A large cohort (n = 1924) of estrogen receptor (ER)‐positive/HER2‐negative BC was included. PR was immunohistochemically (IHC) stained on full face sections and core needle biopsies (CNB) where the optimal scoring cutoff was evaluated. In addition, the association of PR with other clinicopathological factors, cellular proliferation, disease outcome, and response to adjuvant therapy were analyzed.
Results
Although several cutoffs showed prognostic significance, the optimal cutoff to categorize PR expression into two clinically distinct prognostic groups on CNB was 10%. PR negativity showed a significant association with features of aggressive tumor behavior and poor outcome. Multivariate analyses indicated that the association between PR negativity and poor outcome was independent of tumor grade, size, node stage, and Ki67. PR negativity showed independent association with shorter survival in patients who received endocrine therapy whereas Ki67did not.
Conclusion
PR IHC expression provides independent prognostic value superior to Ki67. Routine assessment of PR expression in BC using 10% cutoff in the clinical setting is recommended.
Plain Language Summary
In this study, we have established an optimal approach to determine the prognostic value of progesterone receptor expression in estrogen receptor‐positive breast cancer patients.
To do this, the levels of progesterone receptor were measured in a large cohort of estrogen receptor‐positive breast cancer patients.
We have refined the definition of progesterone receptor positivity in estrogen receptor‐positive breast cancer.
We show that progesterone receptor expression adds prognostic and predictive value of endocrine therapy in estrogen receptor‐positive breast cancer patients, and our results show that the absence of progesterone receptor is associated with poorer outcomes independent of tumor grade, size, node stage, and Ki67 expression.
This study provides further evidence that assessment of progesterone receptor status in the luminal breast cancer can provide valuable prognostic and predictive information independent of other clinicopathological variables comparable to that provided by Ki67 and can outperform it in certain situations. Using a 10% rather than a 1% cutoff for progesterone receptor expression provides the optimal prognostic significance.
The ASCO/CAP guidance on HER2 testing in breast cancer (BC) has recently changed. Group 2 tumours with immunohistochemistry score 2+ and HER2/CEP17 ratio ≥2.0 and HER2 copy number <4.0 signals/cell ...were re-classified as HER2 negative. This study aims to examine the response of Group 2 tumours to neoadjuvant chemotherapy (NACT).
749 BC cases were identified from 11 institutions. The association between HER2 groups and pathological complete response (pCR) was assessed.
54% of immunohistochemistry HER2 positive (score 3+) BCs showed pCR, compared to 19% of immunohistochemistry 2+ FISH amplified cases. 27% of Group 2 treated with HER2 targeted therapy achieved pCR, compared to 19 and 11% in the combined Groups 1 + 3 and Groups 4 + 5, respectively. No difference in pCR rates was identified between Group 2 and Group 1 or combined Groups 1 + 3. However, Group 2 response rate was higher than Groups 4 + 5 (p = 0.017).
No difference in pCR was detected in tumours with a HER2/CEP17 ratio ≥2.0 and a HER2 score 2+ by IHC when stratified by HER2 gene copy number. Our data suggest that ASCO/CAP HER2 Group 2 carcinomas should be evaluated further with respect to eligibility for HER2 targeted therapy.
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