Computer-Aided Scoring Of () Gene Amplification Status In Breast Cancer

Image analysis for bright-field HER2 in situ hybridization: validation for clinical use

The aim of the present study was to develop and validate a quantitative image analysis (IA) algorithm to aid pathologists in assessing bright-field HER2 in situ hybridization (ISH) tests in solid cancers. A cohort of 80 sequential cases (40 HER2-negative and 40 HER2-positive) were evaluated for HER2 gene amplification with bright-field ISH. We developed an IA algorithm using the ISH Module from HALO software to automatically quantify HER2 and CEP17 copy numbers per cell as well as the HER2/CEP17 ratio. We observed a high correlation of HER2/CEP17 ratio, an average of HER2 and CEP17 copy number per cell between visual and IA quantification (Pearson's correlation coefficient of 0.842, 0.916, and 0.765, respectively). IA was able to count from 124 cells to 47,044 cells (median of 5565 cells). The margin of error for the visual quantification of the HER2/CEP17 ratio and of the average of HER2 copy number per cell decreased from a median of 0.23 to 0.02 and from a median of 0.49 to 0.04, respectively, in IA. Curve estimation regression models showed that a minimum of 469 or 953 invasive cancer cells per case is needed to reach an average margin of error below 0.1 for the HER2/CEP17 ratio or for the average of HER2 copy number per cell, respectively. Lastly, on average, a case took 212.1 s to execute the IA, which means that it evaluates about 130 cells/s and requires 6.7 s/mm2. The concordance of the IA software with the visual scoring was 95%, with a sensitivity of 90% and a specificity of 100%. All four discordant cases were able to achieve concordant results after the region of interest adjustment. In conclusion, this validation study underscores the usefulness of IA in HER2 ISH testing, displaying excellent concordance with visual scoring and significantly reducing margins of error.

Advantages of automated immunostain analyses for complex membranous immunostains: An exemplar investigating loss of E-cadherin expression in colorectal cancer

As pathology moves towards digitisation, biomarker profiling through automated image analysis provides potentially objective and time-efficient means of assessment. This study set out to determine how a complex membranous immunostain, E-cadherin, assessed using an automated digital platform fares in comparison to manual evaluation in terms of clinical correlations and prognostication. Tissue microarrays containing 1000 colorectal cancer samples, stained with clinical E-cadherin antibodies were assessed through both manual scoring and automated image analysis. Both manual and automated scores were correlated to clinicopathological and survival data. E-cadherin data generated through digital image analysis was superior to manual evaluation when investigating for clinicopathological correlations in colorectal cancer. Loss of membranous E-cadherin, assessed on automated platforms, correlated with: right sided tumours (p = <0.001), higher T-stage (p = <0.001), higher grade (p = <0.001), N2 nodal stage (p = <0.001), intramural lymphovascular invasion (p = 0.006), perineural invasion (p = 0.028), infiltrative tumour edge (p = 0.001) high tumour budding score (p = 0.038), distant metastasis (p = 0.035), and poorer 5-year (p= 0.042) survival status. Manual assessment was only correlated with higher grade tumours, though other correlations become apparent only when assessed for morphological expression pattern (circumferential, basolateral, parallel) irrespective of intensity. Digital assessment of E-cadherin is effective for prognostication of colorectal cancer and may potentially offer benefits of improved objectivity, accuracy, and economy of time. Incorporating tools to assess patterns of staining may further improve such digital assessment in the future.

Prognostic impact of HER2 biomarker levels in trastuzumab-treated early HER2-positive breast cancer

BACKGROUND

Overexpression of human epidermal growth factor receptor 2 (HER2) caused by HER2 gene amplification is a driver in breast cancer tumorigenesis. We aimed to investigate the prognostic significance of manual scoring and digital image analysis (DIA) algorithm assessment of HER2 copy numbers and HER2/CEP17 ratios, along with ERBB2 mRNA levels among early-stage HER2-positive breast cancer patients treated with trastuzumab.

METHODS

This retrospective study comprised 371 early HER2-positive breast cancer patients treated with adjuvant trastuzumab, with HER2 re-testing performed on whole tumor sections. Digitized tumor tissue slides were manually scored and assessed with uPath HER2 Dual ISH image analysis, breast algorithm. Targeted ERBB2 mRNA levels were assessed by the Xpert® Breast Cancer STRAT4 Assay. HER2 copy number and HER2/CEP17 ratio from in situ hybridization assessment, along with ERBB2 mRNA levels, were explored in relation to recurrence-free survival (RFS).

RESULTS

The analysis showed that patients with tumors with the highest and lowest manually counted HER2 copy number levels had worse RFS than those with intermediate levels (HR = 2.7, CI 1.4-5.3, p = 0.003 and HR = 2.1, CI 1.1-3.9, p = 0.03, respectively). A similar trend was observed for HER2/CEP17 ratio, and the DIA algorithm confirmed the results. Moreover, patients with tumors with the highest and the lowest values of ERBB2 mRNA had a significantly worse prognosis (HR = 2.7, CI 1.4-5.1, p = 0.003 and HR = 2.8, CI 1.4-5.5, p = 0.004, respectively) compared to those with intermediate levels.

CONCLUSIONS

Our findings suggest that the association between any of the three HER2 biomarkers and RFS was nonlinear. Patients with tumors with the highest levels of HER2 gene amplification or ERBB2 mRNA were associated with a worse prognosis than those with intermediate levels, which is of importance to investigate in future clinical trials studying HER2-targeted therapy.

Think "HER2" different: integrative diagnostic approaches for HER2-low breast cancer

This work explores the complex field of HER2 testing in the HER2-low breast cancer era, with a focus on methodological aspects. We aim to propose clear positions to scientific societies, institutions, pathologists, and oncologists to guide and shape the appropriate diagnostic strategies for HER2-low breast cancer. The fundamental question at hand is whether the necessary tools to effectively translate our knowledge about HER2 into practical diagnostic schemes for the lower spectrum of expression are available. Our investigation is centered on the significance of distinguishing between an immunohistochemistry (IHC) score 0 and score 1+ in light of the clinical implications now apparent, as patients with HER2-low breast cancer become eligible for trastuzumab-deruxtecan treatment. Furthermore, we discuss the definition of HER2-low beyond its conventional boundaries and assess the reliability of established diagnostic procedures designed at a time when therapeutic perspectives were non-existent for these cases. In this regard, we examine potential complementary technologies, such as gene expression analysis and liquid biopsy. Ultimately, we consider the potential role of artificial intelligence (AI) in the field of digital pathology and its integration into HER2 testing, with a particular emphasis on its application in the context of HER2-low breast cancer.

Improved concordance of challenging human epidermal growth factor receptor 2 dual in-situ hybridisation cases with the use of a digital image analysis algorithm in breast cancer

AIMS

Accurate assessment of human epidermal growth factor receptor 2 (HER2) expression by HER2 immunohistochemistry and in-situ hybridisation (ISH) is critical for the management of patients with breast cancer. The revised 2018 ASCO/CAP guidelines define 5 groups based on HER2 expression and copy number. Manual pathologist quantification by light microscopy of equivocal and less common HER2 ISH groups (groups 2-4) can be challenging, and there are no data on interobserver variability in reporting of these cases. We sought to determine whether a digital algorithm could improve interobserver variability in the assessment of difficult HER2 ISH cases.

METHODS AND RESULTS

HER2 ISH was evaluated in a cohort enriched for less common HER2 patterns using standard light microscopy versus analysis of whole slide images using the Roche uPath HER2 dual ISH image analysis algorithm. Standard microscopy demonstrated significant interobserver variability with a Fleiss's kappa value of 0.471 (fair-moderate agreement) improving to 0.666 (moderate-good) with the use of the algorithm. For HER2 group designation (groups 1-5), there was poor-moderate reliability between pathologists by microscopy [intraclass correlation coefficient (ICC) = 0.526], improving to moderate-good agreement (ICC = 0.763) with the use of the algorithm. In subgroup analysis, the algorithm improved concordance particularly in groups 2, 4 and 5. Time to enumerate cases was also significantly reduced.

CONCLUSION

This work demonstrates the potential of a digital image analysis algorithm to improve the concordance of pathologist HER2 amplification status reporting in less common HER2 groups. This has the potential to improve therapy selection and outcomes for patients with HER2-low and borderline HER2-amplified breast cancers.