Purpose PAM50 profiling assigns each breast cancer to a single intrinsic subtype based on a bulk tissue sample. However, individual cancers may show evidence of admixture with an alternate subtype that could affect prognosis and treatment response. We developed a method to model subtype admixture using semi-supervised non-negative matrix factorization (ssNMF) of whole transcriptome data and associated it with tumor, molecular, and survival characteristics for Luminal A (LumA) samples. Methods We combined TCGA and METABRIC cohorts and obtained transcriptome, molecular, and clinical data, which yielded 11,379 gene transcripts in common, and 1,179 cases assigned to LumA. We used ssNMF to compute the subtype admixture proportions of the four major subtypes - pLumA, pLumB, pHER2 and pBasal - for each case and measured associations with tumor characteristics, molecular features, and survival. Results Luminal A cases with low pLumA transcriptomic proportion were likelier to have non-luminal pathology, higher clinical and genomic risk factors, and lower overall survival (log rank P < 10-5), independent of age, stage, and tumor size. We found positive associations between pHER2 and HER2-positivity by IHC or FISH; between pLumB and PR negativity; and between pBasal and younger age, node positivity, TP53 mutation, and EGFR expression. Predominant basal admixture, in contrast to predominant LumB or HER2 admixture, was not associated with shorter survival. Conclusions Bulk sampling for genomic analyses provides an opportunity to expose intratumor heterogeneity, as reflected by subtype admixture. Our results elucidate the striking extent of diversity among LumA cancers and suggest that determining the extent and type of admixture holds promise for refining individualized therapy. LumA cancers with a high degree of basal admixture appear to have distinct biological characteristics that warrant further study.

The authors have declared no competing interest.

This study was partly supported by funding from the Breast Cancer Alliance.

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TCGA, METABRIC

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