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RNA-Seq of Circulating Tumor Cells in Stage II–III Breast Cancer

Annals of Surgical Oncology Aims and scope Submit manuscript

Abstract

Background

We characterized the whole transcriptome of circulating tumor cells (CTCs) in stage II–III breast cancer to evaluate correlations with primary tumor biology.

Methods

CTCs were isolated from peripheral blood (PB) via immunomagnetic enrichment followed by fluorescence-activated cell sorting (IE/FACS). CTCs, PB, and fresh tumors were profiled using RNA-seq. Formalin-fixed, paraffin-embedded (FFPE) tumors were subjected to RNA-seq and NanoString PAM50 assays with risk of recurrence (ROR) scores.

Results

CTCs were detected in 29/33 (88%) patients. We selected 21 cases to attempt RNA-seq (median number of CTCs = 9). Sixteen CTC samples yielded results that passed quality-control metrics, and these samples had a median of 4,311,255 uniquely mapped reads (less than PB or tumors). Intrinsic subtype predicted by comparing estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) versus PAM50 for FFPE tumors was 85% concordant. However, CTC RNA-seq subtype assessed by the PAM50 classification genes was highly discordant, both with the subtype predicted by ER/PR/HER2 and by PAM50 tumors. Two patients died of metastatic disease, both of whom had high ROR scores and high CTC counts. We identified significant genes, canonical pathways, upstream regulators, and molecular interaction networks comparing CTCs by various clinical factors. We also identified a 75-gene signature with highest expression in CTCs and tumors taken together that was prognostic in The Cancer Genome Atlas and Molecular Taxonomy of Breast Cancer International Consortium datasets.

Conclusion

It is feasible to use RNA-seq of CTCs in non-metastatic patients to discover novel tumor biology characteristics.

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Acknowledgement

This project was supported by a Society of Surgical Oncology Clinical Investigator Award, a California Breast Cancer Research Program IDEA award, and a STOP Cancer Marni Levine Memorial Seed Grant (JL). The project was also supported in part by grant UL1TR001855 from the National Center for Advancing Translational Science (NCATS) and grant P30CA014089 from the National Cancer Institute of the US National Institutes of Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute or the National Institutes of Health. Magnetic cell separators were kindly made by the laboratory of Maciej Zborowski (Cleveland Clinic) based on the design provided by BD Biosciences.

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Correspondence to Julie E. Lang MD.

Additional information

Julie E. Lang and Alexander Ring served as co-first authors.

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ELECTRONIC SUPPLEMENTARY Fig.

 1 (a–d) Differential gene expression in CTCs based on hormone receptor expression in primary tumors. Heatmaps showing unsupervised hierarchical clustering of individual samples (CTCs or PTs) and volcano plots showing grouped (n = 16 CTCs and n = 12 PTs for a–c, n = 4 CTCs and PTs each for d) differential gene expression (p < 0.05) for: (a) TN samples vs. others (ER-positive or HER2-positive) [n = 512]; (b) ER-positive vs. others (HER2-positive or TNBC) [n = 115 genes]; (c) HER2-positive vs. others (ER-positive or TNBC) [n = 245 genes]; (d) pCR vs. no pCR (n = 65 genes) [color legend: maroon indicates TNBC, orange indicates ER-positive samples, teal indicates HER2-positive samples, green indicates pCR yes, gray indicates remaining samples in each comparison] (TIFF 2881 kb)

Supplementary material 6 (PDF 52 kb)

ELECTRONIC SUPPLEMENTARY Fig.

 2 xCell gene signature-based classification of sample cellular composition. The cell type probability for each sample is shown in heatmap format. A score was calculated using the xCell script based on RNA-seq normalized gene expression (logRPKM + 1) in each sample (CTCs, PTs and PB) [color coding: blue indicates high score = high probability, white indicates low score = low probability] (TIFF 2702 kb)

ELECTRONIC SUPPLEMENTARY Fig.

 3 NanoString results for ER (ESR1), PR (PGR), HER2 (ERBB2), and Ki67 (MKI67). A heatmap shows results for n = 13 FFPE tumors subjected to NanoString assays to characterize their biomarker profiles (PDF 113 kb)

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Lang, J.E., Ring, A., Porras, T. et al. RNA-Seq of Circulating Tumor Cells in Stage II–III Breast Cancer. Ann Surg Oncol 25, 2261–2270 (2018). https://doi.org/10.1245/s10434-018-6540-4

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