Molecular pathology, especially immunohistochemistry, plays an important role in evaluating hormone receptor status along with diagnosis of breast cancer. Time-consumption and inter-/intraobserver variability are major hindrances for evaluating the receptor score. In view of this, the paper proposes an automated Allred Scoring methodology for estrogen receptor (ER). White balancing is used to normalize the colour image taking into consideration colour variation during staining in different labs. Markov random field model with expectation-maximization optimization is employed to segment the ER cells. The proposed segmentation methodology is found to have F-measure 0.95. Artificial neural network is subsequently used to obtain intensity-based score for ER cells, from pixel colour intensity features. Simultaneously, proportion score - percentage of ER positive cells is computed via cell counting. The final ER score is computed by adding intensity and proportion scores - a standard Allred scoring system followed by pathologists. The classification accuracy for classification of cells by classifier in terms of F-measure is 0.9626. The problem of subjective interobserver ability is addressed by quantifying ER score from two expert pathologist and proposed methodology. The intraclass correlation achieved is greater than 0.90. The study has potential advantage of assisting pathologist in decision making over manual procedure and could evolve as a part of automated decision support system with other receptor scoring/analysis procedure.

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Purpose: Triple-negative breast cancer (TNBC) has a poor outcome compared to other subtypes, even in those with early disease. Immune checkpoint inhibitors (ICIs) have been approved in metastatic diseases and are being tested as a neoadjuvant strategy also. The response to ICIs is largely determined by the programmed death ligand 1 (PDL1) score, which also acts as a prognostic marker for outcomes. Here, we report the proportion of PDL1 expression in non-metastatic TNBC and its correlation with response to chemotherapy and outcomes. Methods:We included all patients who had non-metastatic TNBC treated with neoadjuvant chemotherapy, followed by surgery with/without adjuvant radiotherapy between September 2011 and November 2017. PDL1 testing was carried out on pre-treatment tumour cells with immunohistochemistry (Ventana SP142) and was correlated with pathological response, relapse-free survival (RFS) and overall survival (OS). PDL1 staining was interpreted as negative or positive (more than 1% staining).Results: A total of 107 patients were included for analysis with a median age of 47 years (28-65 yrs). The PDL1 expression of more than 1% was seen in 31 (28.97%) patients. After a median follow-up of 55 months (range: 4-93 months), median RFS and OS were not reached. PDL1 expression did not affect the achievement of pathological complete response (pCR). However, PDL1 expression improved OS (p = 0.016) and trend towards RFS (p = 0.05). Patients who achieved pCR had better RFS and OC compared to those who did not. Conclusion:Our study shows PDL1 expression in 29% of the cases. PDL1 expression leads to better RFS and OS. Also, pCR improves survival.

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