Serum microRNA expression as an early marker for breast cancer risk in prospectively collected samples from the Sister Study cohort

The Sister Study [22] is a prospective cohort study of 50,884 women and was designed to examine the environmental and genetic determinants of breast cancer. The cohort has been previously described [23]; briefly, women from the US or Puerto Rico were eligible to enroll if they themselves had never had breast cancer but had a full or half-sister who had breast cancer. At baseline interview, all participants provided extensive information, including family history, reproductive history, and information about potential risk factors. Informed consent and blood samples were obtained during a home visit. For women who subsequently developed breast cancer, detailed information on diagnosis was collected from medical records and self-report. Pathology reports were abstracted for tumor grade, stage, and other information, including status for ER, PR, and HER-2 (human epidermal growth factor receptor 2) expression. The study was approved by the Institutional Review Board of the National Institute of Environmental Health Sciences, National Institutes of Health, and the Copernicus Group Institutional Review Board.

To minimize possible processing and chip lot effects, samples were assigned to processing batches of seven to nine pairs, and batches had similar distributions of age, race, and date of enrollment. For array hybridization, each batch was assigned to one of two different chip lots ('A' and 'B') in a manner designed to ensure a balance of these same characteristics. The nine replicates (described above) were assigned to the same batch and chip lot. Laboratory personnel were blind to case control status and other phenotype information.

Total RNA was extracted in batches by using a Total RNA purification kit (cat. no. 17200; Norgen Biotek Corp., Thorold, ON, Canada). In accordance with the manufacturer's recommendation not to exceed 200 µL per column, 400 µL of total serum from each individual was split into two equal 200-µL aliquots and then processed separately following the manufacturer's recommended protocol for total RNA purification from serum. An on-column DNase digestion was added before sample elution by using an RNase-Free DNase I Kit (cat. no. 25710; Norgen Biotek Corp.), and the two aliquots were subsequently pooled. Fixed volumes rather than fixed amounts of RNA were used in accordance with other studies [24].

Total RNA (8 µL) was directly labeled by using Flash Tag Biotin HSR Labeling kits (cat. no. HSR30FTA; Genisphere, LLC, Hatfield, PA, USA) in accordance with the instructions of the manufacturer. RNA was heated to 80°C for 10 minutes before labeling to inactivate any residual DNase activity. RNA was hybridized for 42 hours to the GeneChip miRNA 2.0 array (cat. no. 901755; Affymetrix Inc., Santa Clara, CA, USA [25]). The GeneChip miRNA 2.0 arrays contain 100% miRBase version 15 coverage of 131 organisms and contain probes for 3,439 human non-coding RNAs (ncRNAs), including 1,105 miRNAs and 2,334 other ncRNAs (including scaRNAs and snoRNAs). The arrays were washed and stained by using standard Affymetrix protocols and scanned by using an Affymetrix GCS 3000 7G Scanner. Feature intensities were extracted by using miRNA 2.0 array library files. Array hybridization and scanning were completed by Precision Biomarker Resources, Inc. (Evanston, IL, USA). The average Spearman correlation coefficient values for three sets of three technical replicates were all above 0.8 (Additional file 1). Array data were deposited into the NCBI Gene Expression Omnibus (GSE44281).

An independent set of 10 women were used to validate selected miRNAs via quantitative reverse transcription-polymerase chain reaction (qRT-PCR). Five women who provided consent and blood samples but who developed breast cancer prior to completing enrollment were selected as cases, along with five controls who also provided consent and blood samples and who were cancer-free but did not complete enrollment. Total RNA was extracted from serum samples of these women as described above with the addition of Synthetic C. elegans miScript miRNA Mimic (cat. no. MSY0000010; Qiagen, Valencia, CA, USA). Synthetic cel-39 was spiked-in at a final concentration of 0.25 fmol/µL prior to extraction and used as a PCR normalization control. The RNA concentration, reverse transcription, and pre-PCR steps were carried out in accordance with a previously published protocol [26]. ExoSAP-IT (cat. no. 78250; Affymetrix Inc.) treatment followed by column purification (cat. no. 28004; Qiagen) in accordance with the protocol of the manufacturer was used to purify the pre-PCR product. Individual PCR was run in triplicate by using 1 µL of purified pre-PCR product. The reaction contained the following components: 2x Taqman universal master mix (cat. no. 4324018; ABI, Carlsbad, CA, USA), 1 µM forward primer, 1 µM universal reverse primer, and 0.2 µM probe. The reaction was run on a Bio-Rad CFX 384 Real-Time System (Bio-Rad Laboratories, Inc., Hercules, CA, USA) by using the following parameters: 55°C for 2 minutes, 95°C for 10 minutes, followed by 40 cycles of 95°C for 15 seconds and 55°C for 1 minute. PCR cycle threshold (Ct) values were recorded for each target gene and for normalization controls and were averaged across three independent runs. Primers for miR-222, miR-181a, miR-1825, and miR-18a were custom-ordered from IDT (San Diego, CA, USA) by using previously published sequences [26]. Primers for cel-39 were designed in the same fashion as above and custom-ordered from IDT.

To determine the best candidate miRNA for PCR normalization in our data set, we ran the array expression data from the 47 miRNAs expressed in almost all individuals through the NormFinder software [27]. NormFinder uses a model-based variance estimation approach [28]. Using these results, we selected as a qRT-PCR normalization control miR-1825, which showed one of the highest stability values across the 410 cases and controls and had blood levels that were similar to those of the three target miRNAs. We used the average of miR-1825 and an external spike-in cel-39 control, a strategy shown to be effective for controlling both technical and biologic variability in qRT-PCR assays from serum [17, 24]. The efficiency of the four PCR assays (for miR-181a, miR-18a, miR-222, and miR-1825) was similar for all four assays (Additional file 2). Normalized relative expression was based on Ct values and calculated as 1/(Ct_gene−Ct_norm).

miRNA expression intensity values were background-corrected and normalized across arrays by using the robust multichip average method [29]. The intensity data used in all analysis were log (2)-transformed.

For each array, the miRNA probe set signals were compared with the distribution of signals for anti-genomic probes that had matching GC content (miRNA QC Tool, version 1.0.33.0), and in accordance with the recommendation of the manufacturer, Wilcoxon rank-sum test of P value of less than 0.06 was used to identify miRNAs above background. Subsequent analysis was restricted to 414 miRNAs that exceeded background levels in at least 50 women. Conditional logistic regression was used to identify differentially expressed miRNA probes between cases and controls for those 414 probes. Because analysis of circulating miRNAs in prospectively collected samples is still exploratory, we - like some other investigators of circulating miRNAs [30, 31] - regard these results as descriptive and not as tests of hypotheses and so provide P values that are unadjusted for multiple comparisons.

The association between miRNAs and the tumor characteristics of hormone receptor status (ER, PR, and HER-2) and lymph node status was tested in a case-only logistic analysis, in which race was adjusted for. Chip lot and batch were specified as random effect variables. All statistical analyses were performed by using R 2.15.

miRNAs found to be significantly associated with case control status were further analyzed with ingenuity pathway analysis (IPA) [32]. Using IPA's microRNA target filter, we generated a list of predicted mRNA targets for each of the 21 significant miRNAs. The list was then restricted to the mRNAs listed in the IPA database as experimentally verified targets of any of the 21 miRNAs. This mRNA target list was then used to run a canonical pathway analysis.

In total, 410 serum samples from breast cancer cases (n = 205) and controls (n = 205) were analyzed in this study; baseline characteristics of the cases and controls are summarized in Table 1. Of the 1,105 human miRNAs, 414 miRNAs were detected above background threshold levels in at least 50 women. Forty-seven miRNAs were detected above background in 400 or more women (Table 2), and miR-16 showed the highest average expression. Even though expression of miRNAs showed considerable inter-individual variation, several miRNAs, including miR-1825 and miR-1228, were relatively constant among women (Figure 1).

When paired case control analysis of the 414 miRNAs expressed above background was used, 21 miRNAs showed significantly different levels in cases and controls (P ≤0.05) (Table 3). The differences were small, ranging from 4% to 19%. Higher miRNA expression in women destined to become cases was significantly more common (16 of 21 miRNAs) than would be expected by chance alone (binomial test, two-tailed P <0.05). Differential miRNA expression was not stronger in women close to their time of diagnosis, but sample size was small and all cases were diagnosed within 18 months of blood draw (data not shown). Using qRT-PCR on a small independent replication set of five cases and five controls, we further examined the three miRNAs (miR-18a, miR-181a, and miR-222) with the highest expression in cases. As predicted, all three miRNAs showed higher levels in cases, although none was statistically significant in this small set of women (Additional file 3).

To explore potential biological associations, we ran IPA on the 82 experimentally verified mRNA targets of the 21 differentially expressed miRNAs. Sixteen IPA canonical pathways, including molecular mechanisms of cancer, were enriched as were other cancer-related pathways, including p53 signaling, cyclins and cell cycle regulation, and Myc-mediated apoptosis signaling (Additional file 4).

To investigate the potential association of serum miRNA expression with tumor characteristics in the 205 women who later developed breast cancer, we subclassified them into groups based on tumor characteristics (Table 4) and performed a case-case comparison. There was no evidence of significant differences in serum miRNA levels based on tumor ER or PR staining characteristics. In comparisons of serum samples from the 25 women who developed HER-2-positive tumors with 147 samples from women who developed HER-2-negative tumors, there were seven miRNAs with significantly differential expression (P ≤0.05); one miRNA was overexpressed and six miRNAs were underexpressed in the HER-2-positive tumors (Figure 2A and Additional file 5). Case-case comparison of serum from women who subsequently developed lymph node-negative tumors (pN0, n = 153) with that of women who developed lymph node-positive tumors (pN1, pN2, or pN3, n = 52) revealed 10 differentially expressed miRNAs (P ≤0.05); five were overexpressed and five were underexpressed in node-positive tumors (Figure 2B and Additional file 6).