Xiao-Jun Ma

Gene expression profiles of human breast cancer progression

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.

Gene expression profiling of the tumor microenvironment during breast cancer progression.

IntroductionThe importance of the tumor microenvironment in breast cancer has been increasingly recognized. Critical molecular changes in the tumor stroma accompanying cancer progression, however, remain largely unknown. We conducted a comparative analysis of global gene expression changes in the stromal and epithelial compartments during breast cancer progression from normal to preinvasive to invasive ductal carcinoma.MethodsWe combined laser capture microdissection and gene expression microarrays to analyze 14 patient-matched normal epithelium, normal stroma, tumor epithelium and tumor-associated stroma specimens. Differential gene expression and gene ontology analyses were performed.ResultsTumor-associated stroma undergoes extensive gene expression changes during cancer progression, to a similar extent as that seen in the malignant epithelium. Highly upregulated genes in the tumor-associated stroma include constituents of the extracellular matrix and matrix metalloproteases, and cell-cycle-related genes. Decreased expression of cytoplasmic ribosomal proteins and increased expression of mitochondrial ribosomal proteins were observed in both the tumor epithelium and the stroma. The transition from preinvasive to invasive growth was accompanied by increased expression of several matrix metalloproteases (MMP2, MMP11 and MMP14). Furthermore, as observed in malignant epithelium, a gene expression signature of histological tumor grade also exists in the stroma, with high-grade tumors associated with increased expression of genes involved in immune response.ConclusionsOur results suggest that the tumor microenvironment participates in tumorigenesis even before tumor cells invade into stroma, and that it may play important roles in the transition from preinvasive to invasive growth. The immune cells in the tumor stroma may be exploited by the malignant epithelial cells in high-grade tumors for aggressive invasive growth.

A five-gene molecular grade index and HOXB13:IL17BR are complementary prognostic factors in early stage breast cancer.

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 others 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 (∼30%) of early stage estrogen receptor–positive breast cancer patients with very poor outcome despite endocrine therapy.

The HOXB13:IL17BR Expression Index Is a Prognostic Factor in Early-Stage Breast Cancer

PURPOSE We previously identified three genes, HOXB13, IL17BR and CHDH, and the HOXB13:IL17BR ratio index in particular, that strongly predicted clinical outcome in breast cancer patients receiving tamoxifen monotherapy. Confirmation in larger independent patient cohorts was needed to fully validate their clinical utility. PATIENTS AND METHODS Expression of HOXB13, IL17BR, CHDH, estrogen receptor (ER) and progesterone receptor (PR) were quantified by real-time polymerase chain reaction in 852 formalin-fixed, paraffin-embedded primary breast cancers from 566 untreated and 286 tamoxifen-treated breast cancer patients. Gene expression and clinical variables were analyzed for association with relapse-free survival (RFS) by Cox proportional hazards regression models. RESULTS ER and PR mRNA measurements were in close agreement with immunohistochemistry. In the entire cohort, expression of HOXB13 was associated with shorter RFS (P = .008), and expression of IL17BR and CHDH was associated with longer RFS (P < .0001 for IL17BR and P = .0002 for CHDH). In ER+ patients, the HOXB13:IL17BR index predicted clinical outcome independently of treatment, but more strongly in node-negative patients. In multivariate analysis of the ER+ node-negative subgroup including age, PR status, tumor size, S phase fraction, and tamoxifen treatment, the two-gene index remained a significant predictor of RFS (hazard ratio = 3.9; 95% CI, 1.5 to 10.3; P = .007). CONCLUSION This tumor bank study demonstrated HOXB13:IL17BR index is a strong independent prognostic factor for ER+ node-negative patients irrespective of tamoxifen therapy.

Molecular Classification of Human Cancers Using a 92‐Gene Real-Time Quantitative Polymerase Chain Reaction Assay

CONTEXT Correct diagnosis of the tissue origin of a metastatic cancer is the first step in disease management, but it is frequently difficult using standard pathologic methods. Microarray-based gene expression profiling has shown great promise as a new tool to address this challenge. OBJECTIVE Adoption of microarray technologies in the clinic remains limited. We aimed to bridge this technological gap by developing a real-time quantitative polymerase chain reaction (RT-PCR) assay. DESIGN We constructed a microarray database of 466 frozen and 112 formalin-fixed, paraffin-embedded (FFPE) samples of both primary and metastatic tumors, measuring expression of 22,000 genes. From the microarray database, we used a genetic algorithm to search for gene combinations optimal for multitumor classification. A 92-gene RT-PCR assay was then designed and used to generate a database for 481 frozen and 119 FFPE tumor samples. RESULTS The microarray-based K-nearest neighbor classifier demonstrated 84% accuracy in classifying 39 tumor types via cross-validation and 82% accuracy in predicting 112 independent FFPE samples. We successfully translated the microarray database to the RT-PCR platform, which allowed an overall success rate of 87% in classifying 32 different tumor classes in the validation set of 119 FFPE tumor samples. CONCLUSIONS The RT-PCR-based expression assay involving 92 genes represents a powerful tool for accurately and objectively identifying the site of origin for metastatic tumors, especially in the cases of cancer of unknown primary. The assay uses RT-PCR and routine FFPE samples, making it suitable for rapid clinical adoption.

Molecular Profiling in Unknown Primary Cancer: Accuracy of Tissue of Origin Prediction

INTRODUCTION This retrospective, multi-institutional study evaluated the accuracy of tissue-of-origin prediction by molecular profiling in patients with carcinoma of unknown primary site (CUP). METHODS Thirty-eight of 501 patients (7.6%) with CUP, seen in 2000-2008, had their latent primary site tumor subsequently identified during life. Twenty-eight of these patients (73.7%) had adequate initial tissue biopsies available for molecular profiling with a reverse transcriptase-polymerase chain reaction (RT-PCR) assay (Cancer Type ID; bioTheranostics, Inc., San Diego, CA). The assay was performed on formalin-fixed paraffin-embedded biopsy specimens in a blinded fashion, and the assay results were compared with clinicopathologic data and the actual latent primary sites. RESULTS Twenty of the 28 (71.4%) RT-PCR assays were successfully completed (eight biopsies had either insufficient tumor or poorly preserved RNA). Fifteen of the 20 assay predictions (75%) were correct (95% confidence interval, 60%-85%), corresponding to the actual latent primary sites identified after the initial diagnosis of CUP. Primary sites correctly identified included breast (four patients), ovary/primary peritoneal (four patients), non-small cell lung (three patients), colorectal (two patients), gastric (one patient), and melanoma (one patient). Three predictions were incorrect (intestinal, testicular, sarcoma) in patients with gastroesophageal, pancreatic, and non-small cell lung cancer, respectively, and two were unclassifiable in patients with non-small cell lung cancer. Clinicopathologic findings were helpful in suggesting the correct primary site in some patients and appear to complement the molecular assay findings. CONCLUSIONS These data validate the reliability of this assay in predicting the primary site in CUP patients and may form the basis for more successful site-directed therapy, when used in concert with clinicopathologic data.

Ligand-Dependent Platelet-Derived Growth Factor Receptor (PDGFR)-α Activation Sensitizes Rare Lung Cancer and Sarcoma Cells to PDGFR Kinase Inhibitors

Platelet-derived growth factor (PDGF) receptors (PDGFR) and their ligands play critical roles in several human malignancies. Sunitinib is a clinically approved multitargeted tyrosine kinase inhibitor that inhibits vascular endothelial growth factor receptor, c-KIT, and PDGFR, and has shown clinical activity in various solid tumors. Activation of PDGFR signaling has been described in gastrointestinal stromal tumors (PDGFRA mutations) as well as in chronic myeloid leukemia (BCR-PDGFRA translocation), and sunitinib can yield clinical benefit in both settings. However, the discovery of PDGFR activating mutations or gene rearrangements in other tumor types could reveal additional patient populations who might benefit from treatment with anti-PDGFR therapies, such as sunitinib. Using a high-throughput cancer cell line screening platform, we found that only 2 of 637 tested human tumor-derived cell lines show significant sensitivity to single-agent sunitinib exposure. These two cell lines [a non-small-cell lung cancer (NSCLC) and a rhabdomyosarcoma] showed expression of highly phosphorylated PDGFRA. In the sunitinib-sensitive adenosquamous NSCLC cell line, PDGFRA expression was associated with focal PFGRA gene amplification, which was similarly detected in a small fraction of squamous cell NSCLC primary tumor specimens. Moreover, in this NSCLC cell line, focal amplification of the gene encoding the PDGFR ligand PDGFC was also detected, and silencing PDGFRA or PDGFC expression by RNA interference inhibited proliferation. A similar codependency on PDGFRA and PDGFC was observed in the sunitinib-sensitive rhabdomyosarcoma cell line. These findings suggest that, in addition to gastrointestinal stromal tumors, rare tumors that show PDGFC-mediated PDGFRA activation may also be clinically responsive to pharmacologic PDGFRA or PDGFC inhibition.

The HOXB7 protein renders breast cancer cells resistant to tamoxifen through activation of the EGFR pathway.

Multiple factors including long-term treatment with tamoxifen are involved in the development of selective estrogen receptor (ER) modulator resistance in ERα-positive breast cancer. Many underlying molecular events that confer resistance are known but a unifying theme is yet to be revealed. In this report, we provide evidence that HOXB7 overexpression renders MCF-7 cells resistant to tamoxifen via cross-talk between receptor tyrosine kinases and ERα signaling. HOXB7 is an ERα-responsive gene. Extended treatment of MCF-7 cells with tamoxifen resulted in progressively increasing levels of HOXB7 expression, along with EGFR and EGFR ligands. Up-regulation of EGFR occurs through direct binding of HOXB7 to the EGFR promoter, enhancing transcriptional activity. Finally, higher expression levels of HOXB7 in the tumor significantly correlated with poorer disease-free survival in ERα-positive patients with breast cancer on adjuvant tamoxifen monotherapy. These studies suggest that HOXB7 acts as a key regulator, orchestrating a major group of target molecules in the oncogenic hierarchy. Functional antagonism of HOXB7 could circumvent tamoxifen resistance.

The prognostic biomarkers HOXB13, IL17BR, and CHDH are regulated by estrogen in breast cancer.

Purpose: We previously identified three genes, HOXB13, IL17BR, and CHDH, that strongly predict clinical outcome in estrogen receptor (ER)–positive breast cancer patients receiving tamoxifen monotherapy. The biological mechanisms linking these genes to estrogen signaling and tamoxifen response in breast cancer remain to be determined. Experimental Design: In a consecutive series of 148 ER-positive and ER-negative breast cancers, HOXB13, IL17BR, and CHDH gene expression was measured by quantitative real-time PCR and correlated with ER, PR, and HER2 expression. The role of estrogen and ER in the regulation of these three genes was assessed in several ER-positive and ER-negative breast cancer cell lines. Results: In primary breast tumors, HOXB13 expression correlated negatively, and IL17BR and CHDH expression correlated positively, with ER status, and all three genes exhibited an ER-dependent correlation pattern with HER2 status that differs from PR and PS2, two canonical estrogen-regulated genes. Results using breast cancer cell lines show that these genes are regulated by estradiol in an ER-dependent manner, and that this regulation is abrogated by tamoxifen. Conclusions:HOXB13, IL17BR, and CHDH are estrogen-regulated genes, but their pattern of correlation with known positive (ER, PR) and negative (HER2) predictors of tamoxifen response differs from canonical ER signature genes. These results provide a biological rationale for the prognostic utility of these three genes in early-stage ER-positive breast cancer and for their potential to predict anti-estrogen resistance.

Prognostic utility of the breast cancer index and comparison to Adjuvant! Online in a clinical case series of early breast cancer

IntroductionBreast Cancer Index (BCI) combines two independent biomarkers, HOXB13:IL17BR (H:I) and the 5-gene molecular grade index (MGI), that assess estrogen-mediated signalling and tumor grade, respectively. BCI stratifies early-stage estrogen-receptor positive (ER+), lymph-node negative (LN-) breast cancer patients into three risk groups and provides a continuous assessment of individual risk of distant recurrence. Objectives of the current study were to validate BCI in a clinical case series and to compare the prognostic utility of BCI and Adjuvant!Online (AO).MethodsTumor samples from 265 ER+LN- tamoxifen-treated patients were identified from a single academic institutions cancer research registry. The BCI assay was performed and scores were assigned based on a pre-determined risk model. Risk was assessed by BCI and AO and correlated to clinical outcomes in the patient cohort.ResultsBCI was a significant predictor of outcome in a cohort of 265 ER+LN- patients (median age: 56-y; median follow-up: 10.3-y), treated with adjuvant tamoxifen alone or tamoxifen with chemotherapy (32%). BCI categorized 55%, 21%, and 24% of patients as low, intermediate and high-risk, respectively. The 10-year rates of distant recurrence were 6.6%, 12.1% and 31.9% and of breast cancer-specific mortality were 3.8%, 3.6% and 22.1% in low, intermediate, and high-risk groups, respectively. In a multivariate analysis including clinicopathological factors, BCI was a significant predictor of distant recurrence (HR for 5-unit increase = 5.32 [CI 2.18-13.01; P = 0.0002]) and breast cancer-specific mortality (HR for a 5-unit increase = 9.60 [CI 3.20-28.80; P < 0.0001]). AO was significantly associated with risk of recurrence. In a separate multivariate analysis, both BCI and AO were significantly predictive of outcome. In a time-dependent (10-y) ROC curve accuracy analysis of recurrence risk, the addition of BCI+AO increased predictive accuracy in all patients from 66% (AO only) to 76% (AO+BCI) and in tamoxifen-only treated patients from 65% to 81%.ConclusionsThis study validates the prognostic performance of BCI in ER+LN- patients. In this characteristically low-risk cohort, BCI classified high versus low-risk groups with ~5-fold difference in 10-year risk of distant recurrence and breast cancer-specific death. BCI and AO are independent predictors with BCI having additive utility beyond standard of care parameters that are encompassed in AO.