Although distinct pathological stages of breast cancer have been described, the molecular differences among these stages are largely unknown. Here, through the combined use of laser capture microdissection and DNA microarrays, we have generated in situ gene expression profiles of the premalignant, preinvasive, and invasive stages of human breast cancer. Our data reveal extensive similarities at the transcriptome level among the distinct stages of progression and suggest that gene expression alterations conferring the potential for invasive growth are already present in the preinvasive stages. In contrast to tumor stage, different tumor grades are associated with distinct gene expression signatures. Furthermore, a subset of genes associated with high tumor grade is quantitatively correlated with the transition from preinvasive to invasive growth.

Tamoxifen significantly reduces tumor recurrence in certain patients with early-stage estrogen receptor-positive breast cancer, but markers predictive of treatment failure have not been identified. Here, we generated gene expression profiles of hormone receptor-positive primary breast cancers in a set of 60 patients treated with adjuvant tamoxifen monotherapy. An expression signature predictive of disease-free survival was reduced to a two-gene ratio, HOXB13 versus IL17BR, which outperformed existing biomarkers. Ectopic expression of HOXB13 in MCF10A breast epithelial cells enhances motility and invasion in vitro, and its expression is increased in both preinvasive and invasive primary breast cancer. The HOXB13:IL17BR expression ratio may be useful for identifying patients appropriate for alternative therapeutic regimens in early-stage breast cancer.

Gene expression profiles of thousands of genes can now be examined en masse through cDNA and oligonucleotide microarrays 1-3 . Recently, studies have been reported that examined gene expression changes in yeast 4,5 , as well as in mammalian cell lines 6 , primary cells 7 and tissues 8 . However, present applications of microarray technology do not include the study of gene expression from individual cell types residing in a given tissue/organ (that is, in situ). Such studies would greatly facilitate our understanding of the complex interactions that exist in vivo between neighboring cell types in normal and disease states. We demonstrate here that gene expression profiles from adjacent cell types can be successfully obtained by integrating the technologies of laser capture microdissection 9 (LCM) and T7-based RNA amplification 10 with cDNA microarrays 11 . Neighboring small and large neurons are individually capturedTo demonstrate this integration of technologies, we examined the differential gene expression between large-and small-sized neurons in the dorsal root ganglia (DRG). In general, large DRG neurons are myelinated, fast-conducting and transmit mechanosensory information, whereas small neurons are unmyelinated, slow-conducting and transmit nociceptive information 12 . We chose this system because numerous differentially expressed genes (small versus large) have been reported, thus the success of this experiment could be assessed; and because many small and large neurons are adjacent to each other, thus we could test whether individual neurons can be cleanly captured. Large (diameter of >40 µm) and small (diameter <25 µm and with identified nuclei) neurons were cleanly and individually captured by LCM from sections (10 µm in thickness) of Nissl-stained rat DRG (Fig. 1). For this study, two sets of 1,000 large neurons and three sets of 1,000 small neurons were captured for cDNA microarray analysis. RNA amplification is reproducible between individual capturesRNA was extracted from each set of neurons and linearly amplified (independently) an estimated 10 6 -fold using T7 RNA polymerase. After being amplified, one fluorescently labeled probe was synthesized from an individually amplified RNA (aRNA), divided equally into three parts and hybridized in triplicate to a microarray ('chip') containing 477 cDNAs (see Methods for chip design) plus 30 cDNAs encoding plant genes (for the determination of non-specific nucleic acid hybridization). Expression in each neuronal set (called S1, S2 and S3 for small and L1 and L2 for large neurons) was thus monitored in triplicate, requiring a total of 15 microarrays. The quality of the microarray data is demonstrated by pseudocolor arrays, one resulting from hybridization to probes derived from neuronal set S1 and the other from neuronal set L1 (Fig. 2a). In Fig. 2a, the enlarged part of the chip shows some differences in fluorescence intensity (that is, expression levels) for particular cDNAs and demonstrates that spots containing the different cDNAs are relatively uniform ...

Purpose: Histologic tumor grade is a well-established prognostic factor for breast cancer, and tumor grade^associated genes are the common denominator of many prognostic gene signatures. The objectives of this study are as follows: (a) to develop a simple gene expression index for tumor grade (molecular grade index or MGI), and (b) to determine whether MGI and our previously described HOXB13:IL17BR index together provide improved prognostic information. Experimental Design: From our previously published list of genes whose expression correlates with both tumor grade and tumor stage progression, we selected five cell cycle^related genes to build MGI and evaluated MGI in two publicly available microarray data sets totaling 410 patients. Using two additional cohorts (n = 323), we developed a real-time reverse transcription PCR assay for MGI, validated its prognostic utility, and examined its interaction with HOXB13:IL17BR. Results: MGI performed consistently as a strong prognostic factor and was comparable with a more complex 97-gene genomic grade index in multiple data sets. In patients treated with endocrine therapy, MGI and HOXB13:IL17BR modified each other's prognostic performance. High MGI was associated with significantly worse outcome only in combination with high HOXB13:IL17BR, and likewise, high HOXB13:IL17BR was significantly associated with poor outcome only in combination with high MGI. Conclusions: We developed and validated a five-gene reverse transcription PCR assay for MGI suitable for analyzing routine formalin-fixed paraffin-embedded clinical samples. The combination of MGI and HOXB13:IL17BR outperforms either alone and identifies a subgroup (f30%) of early stage estrogen receptor^positive breast cancer patients with very poor outcome despite endocrine therapy.The most recent (2005) St. Gallen consensus guidelines for treatment selection for early stage breast cancer consider both risk of recurrence and endocrine responsiveness to better balance risk and benefit of systemic adjuvant therapies (1). To better define risk stratification, genome-wide expression profiling studies have created multiple prognostic gene signatures for breast cancer (2, 3). An important issue is whether these signatures overlap in their prognostic information and whether combining several of these signatures would provide more accurate prognosis. In one comparative study, four signatures (the intrinsic subtypes, 70-gene signature, wound response signature, and Recurrence Score) were found to be highly concordant in classifying patients into low and high-risk groups (4). Notably, combining these signatures did not yield significant improvement in predictive accuracy, suggesting that the prognostic information provided by these signatures is largely overlapping (4). Sotiriou et al. (5) showed that a 97-gene tumor grade signature was comparable with the 70-gene signature and the Recurrence Score algorithm (6) in independent cohorts, and they hypothesized that most of the prognostic power of these signatures comes f...

Laser capture microdissection in combination with microarrays allows for the expression analysis of thousands of genes in selected cells. Here we describe single-cell gene expression profiling of CA1 neurons in the rat hippocampus using a combination of laser capture, T7 RNA amplification, and cDNA microarray analysis. Subsequent cluster analysis of the microarray data identified two different cell types: pyramidal neurons and an interneuron. Cluster analysis also revealed differences among the pyramidal neurons, indicating that even a single cell type in vivo is not a homogeneous population of cells at the gene expression level. Microarray data were confirmed by quantitative RT-PCR and in situ hybridization. We also report on the reproducibility and sensitivity of this combination of methods. Single-cell gene expression profiling offers a powerful tool to tackle the complexity of the mammalian brain.

Background:A dichotomous index combining two gene expression assays, HOXB13 : IL17BR (H : I) and molecular grade index (MGI), was developed to assess risk of recurrence in breast cancer patients. The study objective was to demonstrate the prognostic utility of the combined index in early-stage breast cancer.Methods:In a blinded retrospective analysis of 588 ER-positive tamoxifen-treated and untreated breast cancer patients from the randomised prospective Stockholm trial, H : I and MGI were measured using real-time RT–PCR. Association with patient outcome was evaluated by Kaplan–Meier analysis and Cox proportional hazard regression. A continuous risk index was developed using Cox modelling.Results:The dichotomous H : I+MGI was significantly associated with distant recurrence and breast cancer death. The >50% of tamoxifen-treated patients categorised as low-risk had <3% 10-year distant recurrence risk. A continuous risk model (Breast Cancer Index (BCI)) was developed with the tamoxifen-treated group and the prognostic performance tested in the untreated group was 53% of patients categorised as low risk with an 8.3% 10-year distant recurrence risk.Conclusion:Retrospective analysis of this randomised, prospective trial cohort validated the prognostic utility of H : I+MGI and was used to develop and test a continuous risk model that enables prediction of distant recurrence risk at the patient level.

BackgroundExtending the duration of adjuvant endocrine therapy reduces the risk of recurrence in a subset of women with early-stage hormone receptor-positive (HR+) breast cancer. Validated predictive biomarkers of endocrine response could significantly improve patient selection for extended therapy. Breast cancer index (BCI) [HOXB13/IL17BR ratio (H/I)] was evaluated for its ability to predict benefit from extended endocrine therapy in patients previously randomized in the Adjuvant Tamoxifen—To Offer More? (aTTom) trial.Patients and methodsTrans-aTTom is a multi-institutional, prospective–retrospective study in patients with available formalin-fixed paraffin-embedded primary tumor blocks. BCI testing and central determination of estrogen receptor (ER) and progesterone receptor (PR) status by immunohistochemistry were carried out blinded to clinical outcome. Survival endpoints were evaluated using Kaplan–Meier analysis and Cox regression with recurrence-free interval (RFI) as the primary endpoint. Interaction between extended endocrine therapy and BCI (H/I) was assessed using the likelihood ratio test.ResultsOf 583 HR+, N+ patients analyzed, 49% classified as BCI (H/I)-High derived a significant benefit from 10 versus 5 years of tamoxifen treatment [hazard ratio (HR): 0.35; 95% confidence interval (CI) 0.15–0.86; 10.2% absolute risk reduction based on RFI, P = 0.027]. BCI (H/I)-low patients showed no significant benefit from extended endocrine therapy (HR: 1.07; 95% CI 0.69–1.65; −0.2% absolute risk reduction; P = 0.768). Continuous BCI (H/I) levels predicted the magnitude of benefit from extended tamoxifen, whereas centralized ER and PR did not. Interaction between extended tamoxifen treatment and BCI (H/I) was statistically significant (P = 0.012), adjusting for clinicopathological factors.ConclusionBCI by high H/I expression was predictive of endocrine response and identified a subset of HR+, N+ patients with significant benefit from 10 versus 5 years of tamoxifen therapy. These data provide further validation, consistent with previous MA.17 data, establishing level 1B evidence for BCI as a predictive biomarker of benefit from extended endocrine therapy.Trial registrationISRCTN17222211; NCT00003678.

Accurate determination of cancer origin is necessary to guide optimal treatment but remains a diagnostic challenge. Gene expression profiling technologies have aided the classification of tumors and, therefore, could be applied in conjunction with clinicopathologic correlates to improve accuracy. We report an expanded version of the previously