Abstract

Oncotype DX(TM) is an RT-PCR-based assay used to predict chemotherapy benefit in patients with estrogen receptor (ER) positive breast cancers. We were interested if routinely available pathologic parameters could predict Oncotype DX Recurrence Scores (RS) in subsets of patients. We identified 173 breast cancers with available RSs and used 104 of these as a test set and 69 cases as a validation set. Pathologic characteristics including size, histologic type, Nottingham grade, and lymphatic invasion were recorded. Test set cases were stained for ER, progesterone receptor (PR), HER2, Ki67, CyclinD1, BCL2, D2-40, and P53. Statistical correlations with RS and regression tree analysis were performed. The validation set was subjected to analysis on the basis of grade, PR, and Ki67. In the test set, grade, PR levels and Ki67 had the strongest correlation with RS (P = 0.0002-0.0007). Regression tree analysis showed grade and PR as factors that could segregate cases into RS categories, with Ki67 adding value in certain subsets. A subset of cancers with a high likelihood of having a low RS (0-18) was identified with the following characteristics: grade 1, strong PR expression (Allred score ≥ 5) and Ki67 ≤ 10%. No cases with these characteristics had a high RS (≥ 31) and 73% had a low RS. Cancers highly likely to have a high RS were grade 3, low to absent PR expression (Allred score <5) and Ki67 > 10%. 80% of cases with these characteristics had a high RS and no cases had a low RS. Our validation set had similar findings in these two subsets. In conclusion, When cost and time are a consideration and the added value of Oncotype DX(TM) testing is in question, it may be reasonable to assume the results of this test in two specific subsets of breast cancers: (1) grade 1, high PR, low Ki67 cancers (low RS), and (2) grade 3, low PR, high Ki67 cancers (high RS).

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