Breast cancer histologic grading using digital microscopy: concordance and outcome association

Aims: Virtual microscopy utilising digital whole slide imaging (WSI) is increasingly used in breast pathology. Histologic grade is one of the strongest prognostic factors in breast cancer (BC). This study aims at investigating the agreement between BC grading using traditional light microscopy (LM) and digital whole slide imaging (WSI) with consideration of reproducibility and impact on outcome prediction. Methods: A large (n=1675) well-characterised cohort of BC originally graded by LM was re-graded using WSI. Two separate virtual-based grading sessions (V1 and V2) were performed with a three months washout period. Outcome was assessed using breast cancer specific and distant metastasis free survival. Results: The concordance between LM grading and WSI was strong (LM/SWI Cramer’s V: V1=0.576, and V2=0.579). The agreement regarding grade components was as follows: Tubule formation=0.538, Pleomorphism=0.422 and Mitosis=0.514. Greatest discordance was observed between adjacent grades whereas high/low grade discordance was uncommon (1.5%). The intra-observer agreement for the two WSI sessions was substantial for grade (V1/V2 Cramer’s V=0.676; kappa=0.648) and grade components (Cramer’s V T=0.628, P=0.573 and M=0.580). Grading using both platforms showed strong association with outcome (All p-value <0.001). Although mitotic scores assessed using both platforms were strongly associated with outcome, WSI tends to underestimate mitotic counts. Conclusions: Virtual microscopy is a reliable and reproducible method for assessing BC histologic grade. Regardless of the observer or assessment platform, histologic grade is a significant predictor of outcome. Continuing advances in imaging technology could potentially provide improved performance of WSI BC grading and in particular mitotic count assessment

FEN1 Blockade for Platinum Chemo-Sensitization and Synthetic Lethality in Epithelial Ovarian Cancers

\ua9 2021 by the authors. Licensee MDPI, Basel, Switzerland.FEN1 plays critical roles in long patch base excision repair (LP-BER), Okazaki fragment maturation, and rescue of stalled replication forks. In a clinical cohort, FEN1 overexpression is associated with aggressive phenotype and poor progression-free survival after platinum chemother-apy. Pre-clinically, FEN1 is induced upon cisplatin treatment, and nuclear translocation of FEN1 is dependent on physical interaction with importin β. FEN1 depletion, gene inactivation, or inhibition re-sensitizes platinum-resistant ovarian cancer cells to cisplatin. BRCA2 deficient cells exhibited synthetic lethality upon treatment with a FEN1 inhibitor. FEN1 inhibitor-resistant PEO1R cells were generated, and these reactivated BRCA2 and overexpressed the key repair proteins, POLβ and XRCC1. FEN1i treatment was selectively toxic to POLβ deficient but not XRCC1 deficient ovarian cancer cells. High throughput screening of 391,275 compounds identified several FEN1 inhibitor hits that are suitable for further drug development. We conclude that FEN1 is a valid target for ovarian cancer therapy

Targeting Mre11 overcomes platinum resistance and induces synthetic lethality in XRCC1 deficient epithelial ovarian cancers

\ua9 2022, The Author(s). Platinum resistance is a clinical challenge in ovarian cancer. Platinating agents induce DNA damage which activate Mre11 nuclease directed DNA damage signalling and response (DDR). Upregulation of DDR may promote chemotherapy resistance. Here we have comprehensively evaluated Mre11 in epithelial ovarian cancers. In clinical cohort that received platinum- based chemotherapy (n = 331), Mre11 protein overexpression was associated with aggressive phenotype and poor progression free survival (PFS) (p = 0.002). In the ovarian cancer genome atlas (TCGA) cohort (n = 498), Mre11 gene amplification was observed in a subset of serous tumours (5%) which correlated highly with Mre11 mRNA levels (p &lt; 0.0001). Altered Mre11 levels was linked with genome wide alterations that can influence platinum sensitivity. At the transcriptomic level (n = 1259), Mre11 overexpression was associated with poor PFS (p = 0.003). ROC analysis showed an area under the curve (AUC) of 0.642 for response to platinum-based chemotherapy. Pre-clinically, Mre11 depletion by gene knock down or blockade by small molecule inhibitor (Mirin) reversed platinum resistance in ovarian cancer cells and in 3D spheroid models. Importantly, Mre11 inhibition was synthetically lethal in platinum sensitive XRCC1 deficient ovarian cancer cells and 3D-spheroids. Selective cytotoxicity was associated with DNA double strand break (DSB) accumulation, S-phase cell cycle arrest and increased apoptosis. We conclude that pharmaceutical development of Mre11 inhibitors is a viable clinical strategy for platinum sensitization and synthetic lethality in ovarian cancer

A novel prognostic two-gene signature for triple negative breast cancer

The absence of a robust risk stratification tool for triple negative breast cancer (TNBC) underlies imprecise and non-selective treatment of these patients with cytotoxic chemotherapy. This study aimed to interrogate transcriptomes of TNBC resected samples using next generation sequencing to identify novel biomarkers associated with disease outcomes. A subset of cases (n=112) from a large, well-characterized cohort of primary TNBC (n=333) were subjected to RNA-sequencing. Reads were aligned to the human reference genome (GRCH38.83) using the STAR aligner and gene expression quantified using HTSEQ. We identified genes associated with distant metastasis-free survival and breast cancer-specific survival by applying supervised artificial neural network analysis with gene selection to the RNA-sequencing data. The prognostic ability of these genes was validated using the Breast Cancer Gene-Expression Miner v4. 0 and Genotype 2 outcome datasets. Multivariate Cox regression analysis identified a prognostic gene signature that was independently associated with poor prognosis. Finally, we corroborated our results from the two-gene prognostic signature by their protein expression using immunohistochemistry. Artificial neural network identified two gene panels that strongly predicted distant metastasis-free survival and breast cancer-specific survival. Univariate Cox regression analysis of 21 genes common to both panels revealed that the expression level of eight genes was independently associated with poor prognosi

Potential quality pitfalls of digitalized whole slide image of breast pathology in routine practice.

Using digitalized whole slide images (WSI) in routine histopathology practice is a revolutionary technology. This study aims to assess the clinical impacts of WSI quality and representation of the corresponding glass slides. 40,160 breast WSIs were examined and compared with their corresponding glass slides. The presence, frequency, location, tissue type, and the clinical impacts of missing tissue were assessed. Scanning time, type of the specimens, time to WSIs implementation, and quality control (QC) measures were also considered. The frequency of missing tissue ranged from 2% to 19%. The area size of the missed tissue ranged from 1-70%. In most cases (>75%), the missing tissue area size was <10% and peripherally located. In all cases the missed tissue was fat with or without small entrapped normal breast parenchyma. No missing tissue was identified in WSIs of the core biopsy specimens. QC measures improved images quality and reduced WSI failure rates by seven-fold. A negative linear correlation between the frequency of missing tissue and both the scanning time and the image file size was observed (p < 0.05). None of the WSI with missing tissues resulted in a change in the final diagnosis. Missing tissue on breast WSI is observed but with variable frequency and little diagnostic consequence. Balancing between WSI quality and scanning time/image file size should be considered and pathology laboratories should undertake their own assessments of risk and provide the relevant mitigations with the appropriate level of caution

The clinical and biological significance of HER2 over-expression in breast ductal carcinoma in situ: a large study from a single institution

BACKGROUND: Previous studies have reported up to 50% of ductal carcinoma in situ (DCIS), is HER2 positive, but the frequency of HER2-positive invasive breast cancer (IBC) is lower. The aim of this study is to characterise HER2 status in DCIS and assess its prognostic value. METHODS: HER2 status was evaluated in a large series of DCIS (n = 868), including pure DCIS and DCIS associated with IBC, prepared as tissue microarrays (TMAs). HER2 status was assessed using immunohistochemistry (IHC) and chromogenic in situ hybridisation (CISH). RESULTS: In pure DCIS, HER2 protein was over-expressed in 9% of DCIS (3+), whereas 15% were HER2 equivocal (2+). Using CISH, the final HER2 status was positive in 20%. In mixed DCIS, HER2 amplification of the DCIS component was detected in 15% with amplification in the invasive component of only 12%. HER2-positive DCIS was associated with features of aggressiveness (p < 0.0001) and more frequent local recurrence (p = 0.03). On multivariate analysis, combined HER2+/Ki67+ profile was an independent predictor of local recurrence (p = 0.006). CONCLUSIONS: The frequency of HER2 positivity in DCIS is comparable to IBC- and HER2-positive DCIS is associated with features of poor prognosis. The majority of HER2 over-expression in DCIS is driven by gene amplification

Prolyl-4-hydroxylase A subunit 2 (P4HA2) expression is a predictor of poor outcome in breast ductal carcinoma in situ (DCIS)

BACKGROUND: Extracellular matrix (ECM) plays a crucial role in tumour behaviour. Prolyl-4-hydroxlase-A2 (P4HA2) is a key enzyme in ECM remodelling. This study aims to evaluate the prognostic significance of P4HA2 in breast ductal carcinoma in situ (DCIS). METHODS: P4HA2 expression was assessed immunohistochemically in malignant cells and surrounding stroma of a large DCIS cohort comprising 481 pure DCIS and 196 mixed DCIS and invasive carcinomas. Outcome analysis was evaluated using local recurrence free interval (LRFI). RESULTS: High P4HA2 expression was detected in malignant cells of half of pure DCIS whereas its expression in stroma was seen in 25% of cases. Higher P4HA2 expression was observed in mixed DCIS cases compared to pure DCIS both in tumour cells and in stroma. High P4HA2 was associated with features of high risk DCIS including younger age, higher grade, comedo necrosis, triple negative and HER2-positive phenotypes. Interaction between P4HA2 and radiotherapy was also observed regarding the outcome. High P4HA2 expression was an independent prognostic factor in predicting shorter LRFI. CONCLUSION: P4HA2 plays a role in DCIS progression and can potentially be used to predict DCIS outcome. Incorporation of P4HA2 with other clinicopathological parameters could refine DCIS risk stratification that can potentially guide management decisions

Prognostic significance of nucleolar assessment in invasive breast cancer

Aims: Nucleolar morphometric features have a potential role in the assessment of aggressiveness of many cancers. However, the role of nucleoli in invasive breast cancer (IBC) is still unclear. This study aimed to investigate the optimal scoring method of nucleoli in IBC and their prognostic significance, and refine the grading of BC by incorporating the nucleolar score.Methods and results: Digital images acquired from hematoxylin and eosin (H&E) stained sections from a large IBC cohort were divided into training (n=400) and validation (n=1200) sets were used in this study. Four different assessment methods including 1) modified Helpap’s method, and counting prominent nucleoli (size ≥2.5μm) in 2) 10 field views (10 FVs), 3) 5 FVs and 4) 1 FV were evaluated in the training set to identify the optimal method associated with the best performance and significant prognostic value. The optimal method was applied to the validation set and to an external validation set the Cancer Genome Atlas (TCGA) data (n=743). Scoring prominent nucleoli in 5 FVs, showed the highest inter-observer concordance rate (intraclass correlation coefficient = 0.8) and significant association with breast cancer specific survival (BCSS) (