Dafydd G. Thomas

Gene Expression Signatures for Predicting Prognosis of Squamous Cell and Adenocarcinomas of the Lung

Non-small-cell lung cancers (NSCLC) compose 80% of all lung carcinomas with squamous cell carcinomas (SCC) and adenocarcinoma representing the majority of these tumors. Although patients with early-stage NSCLC typically have a better outcome, 35% to 50% will relapse within 5 years after surgical treatment. We have profiled primary squamous cell lung carcinomas from 129 patients using Affymetrix U133A gene chips. Unsupervised analysis revealed two clusters of SCC that had no correlation with tumor stage but had significantly different overall patient survival (P = 0.036). The high-risk cluster was most significantly associated with down-regulation of epidermal development genes. Cox proportional hazard models identified an optimal set of 50 prognostic mRNA transcripts using a 5-fold cross-validation procedure. Quantitative reverse transcription-PCR and immunohistochemistry using tissue microarrays were used to validate individual gene candidates. This signature was tested in an independent set of 36 SCC samples and achieved 84% specificity and 41% sensitivity with an overall predictive accuracy of 68%. Kaplan-Meier analysis showed clear stratification of high-risk and low-risk patients [log-rank P = 0.04; hazard ratio (HR), 2.66; 95% confidence interval (95% CI), 1.01-7.05]. Finally, we combined the SCC classifier with our previously identified adenocarcinoma prognostic signature and showed that the combined classifier had a predictive accuracy of 71% in 72 NSCLC samples also showing significant differences in overall survival (log-rank P = 0.0002; HR, 3.54; 95% CI, 1.74-7.19). This prognostic signature could be used to identify patients with early-stage high-risk NSCLC who might benefit from adjuvant therapy following surgery.

Distinct Transcriptional Profiles of Adrenocortical Tumors Uncovered by DNA Microarray Analysis

Comprehensive expression profiling of tumors using DNA microarrays has been used recently for molecular classification and biomarker discovery, as well as a tool to identify and investigate genes involved in tumorigenesis. Application of this approach to a cohort of benign and malignant adrenocortical tissues would be potentially informative in all of these aspects. In this study, we generated transcriptional profiles of 11 adrenocortical carcinomas (ACCs), 4 adrenocortical adenomas (ACAs), 3 normal adrenal cortices (NCs), and 1 macronodular hyperplasia (MNH) using Affymetrix HG_U95Av2 oligonucleotide arrays representing approximately 10,500 unique genes. The expression data set was used for unsupervised hierarchical cluster analysis as well as principal component analysis to visually represent the expression data. An analysis of variance on the three classes (NC, ACA plus MNH, and ACC) revealed 91 genes that displayed at least threefold differential expression between the ACC cohort and both the NC and ACA cohorts at a significance level of P < 0.01. Included in these 91 genes were those known to be up-regulated in adrenocortical tumors, such as insulin-like growth factor (IGF2), as well as novel differentially expressed genes such as osteopontin (SPP) and serine threonine kinase 15 (STK15). Increased expression of IGF2 was identified in 10 of 11 ACCs (90.9%) and was verified by quantitative reverse transcriptase-polymerase chain reaction. Select proliferation-related genes (TOP2A and Ki-67) were validated at the protein level using immunohistochemistry and adrenocortical tissue microarrays. Our results demonstrated significant and consistent gene expression changes in ACCs compared to benign adrenocortical lesions. Moreover, we identified several genes that represent potential diagnostic markers and may play a role in the pathogenesis of ACC.

Aldehyde Dehydrogenase in Combination with CD133 Defines Angiogenic Ovarian Cancer Stem Cells That Portend Poor Patient Survival

Markers that reliably identify cancer stem cells (CSC) in ovarian cancer could assist prognosis and improve strategies for therapy. CD133 is a reported marker of ovarian CSC. Aldehyde dehydrogenase (ALDH) activity is a reported CSC marker in several solid tumors, but it has not been studied in ovarian CSC. Here we report that dual positivity of CD133 and ALDH defines a compelling marker set in ovarian CSC. All human ovarian tumors and cell lines displayed ALDH activity. ALDH(+) cells isolated from ovarian cancer cell lines were chemoresistant and preferentially grew tumors, compared with ALDH(-) cells, validating ALDH as a marker of ovarian CSC in cell lines. Notably, as few as 1,000 ALDH(+) cells isolated directly from CD133(-) human ovarian tumors were sufficient to generate tumors in immunocompromised mice, whereas 50,000 ALDH(-) cells were unable to initiate tumors. Using ALDH in combination with CD133 to analyze ovarian cancer cell lines, we observed even greater growth in the ALDH(+)CD133(+) cells compared with ALDH(+)CD133(-) cells, suggesting a further enrichment of ovarian CSC in ALDH(+)CD133(+) cells. Strikingly, as few as 11 ALDH(+)CD133(+) cells isolated directly from human tumors were sufficient to initiate tumors in mice. Like other CSC, ovarian CSC exhibited increased angiogenic capacity compared with bulk tumor cells. Finally, the presence of ALDH(+)CD133(+) cells in debulked primary tumor specimens correlated with reduced disease-free and overall survival in ovarian cancer patients. Taken together, our findings define ALDH and CD133 as a functionally significant set of markers to identify ovarian CSCs.

Molecular classification of papillary thyroid carcinoma: distinct BRAF , RAS , and RET/PTC mutation-specific gene expression profiles discovered by DNA microarray analysis

Thyroid cancer poses a significant clinical challenge, and our understanding of its pathogenesis is incomplete. To gain insight into the pathogenesis of papillary thyroid carcinoma, transcriptional profiles of four normal thyroids and 51 papillary carcinomas (PCs) were generated using DNA microarrays. The tumors were genotyped for their common activating mutations: BRAF V600E point mutation, RET/PTC1 and 3 rearrangement and point mutations of KRAS, HRAS and NRAS. Principal component analysis based on the entire expression data set separated the PCs into three groups that were found to reflect tumor morphology and mutational status. By combining expression profiles with mutational status, we defined distinct expression profiles for the BRAF, RET/PTC and RAS mutation groups. Using small numbers of genes, a simple classifier was able to classify correctly the mutational status of all 40 tumors with known mutations. One tumor without a detectable mutation was predicted by the classifier to have a RET/PTC rearrangement and was shown to contain one by fluorescence in situ hybridization analysis. Among the mutation-specific expression signatures were genes whose differential expression was a direct consequence of the mutation, as well as genes involved in a variety of biological processes including immune response and signal transduction. Expression of one mutation-specific differentially expressed gene, TPO, was validated at the protein level using immunohistochemistry and tissue arrays containing an independent set of tumors. The results demonstrate that mutational status is the primary determinant of gene expression variation within these tumors, a finding that may have clinical and diagnostic significance and predicts success for therapies designed to prevent the consequences of these mutations.

Protein profiles associated with survival in lung adenocarcinoma

Morphologic assessment of lung tumors is informative but insufficient to adequately predict patient outcome. We previously identified transcriptional profiles that predict patient survival, and here we identify proteins associated with patient survival in lung adenocarcinoma. A total of 682 individual protein spots were quantified in 90 lung adenocarcinomas by using quantitative two-dimensional polyacrylamide gel electrophoresis analysis. A leave-one-out cross-validation procedure using the top 20 survival-associated proteins identified by Cox modeling indicated that protein profiles as a whole can predict survival in stage I tumor patients (P = 0.01). Thirty-three of 46 survival-associated proteins were identified by using mass spectrometry. Expression of 12 candidate proteins was confirmed as tumor-derived with immunohistochemical analysis and tissue microarrays. Oligonucleotide microarray results from both the same tumors and from an independent study showed mRNAs associated with survival for 11 of 27 encoded genes. Combined analysis of protein and mRNA data revealed 11 components of the glycolysis pathway as associated with poor survival. Among these candidates, phosphoglycerate kinase 1 was associated with survival in the protein study, in both mRNA studies and in an independent validation set of 117 adenocarcinomas and squamous lung tumors using tissue microarrays. Elevated levels of phosphoglycerate kinase 1 in the serum were also significantly correlated with poor outcome in a validation set of 107 patients with lung adenocarcinomas using ELISA analysis. These studies identify new prognostic biomarkers and indicate that protein expression profiles can predict the outcome of patients with early-stage lung cancer.

Molecular Classification and Prognostication of Adrenocortical Tumors by Transcriptome Profiling

Purpose: Our understanding of adrenocortical carcinoma (ACC) has improved considerably, yet many unanswered questions remain. For instance, can molecular subtypes of ACC be identified? If so, what is their underlying pathogenetic basis and do they possess clinical significance? Experimental Design: We did a whole genome gene expression study of a large cohort of adrenocortical tissues annotated with clinicopathologic data. Using Affymetrix Human Genome U133 Plus 2.0 oligonucleotide arrays, transcriptional profiles were generated for 10 normal adrenal cortices (NC), 22 adrenocortical adenomas (ACA), and 33 ACCs. Results: The overall classification of adrenocortical tumors was recapitulated using principal component analysis of the entire data set. The NC and ACA cohorts showed little intragroup variation, whereas the ACC cohort revealed much greater variation in gene expression. A robust list of 2,875 differentially expressed genes in ACC compared with both NC and ACA was generated and used in functional enrichment analysis to find pathways and attributes of biological significance. Cluster analysis of the ACCs revealed two subtypes that reflected tumor proliferation, as measured by mitotic counts and cell cycle genes. Kaplan-Meier analysis of these ACC clusters showed a significant difference in survival (P < 0.020). Multivariate Cox modeling using stage, mitotic rate, and gene expression data as measured by the first principal component for ACC samples showed that gene expression data contains significant independent prognostic information (P < 0.017). Conclusions: This study lays the foundation for the molecular classification and prognostication of adrenocortical tumors and also provides a rich source of potential diagnostic and prognostic markers.

Response of extraabdominal desmoid tumors to therapy with imatinib mesylate

Desmoid tumor represents a rare monoclonal neoplasm arising from deep musculoaponeurotic structures and may occur sporadically or in association with the familial adenomatous polyposis and Gardner syndromes. Desmoid tumors do not appear to demonstrate metastatic potential; however, local infiltrative growth results in significant morbidity and potential mortality. Although the delineation of optimal therapy for desmoid tumors has been confounded by several factors, surgical resection with adjuvant radiotherapy for a positive surgical margin remains the standard approach. Responses have been demonstrated to nonsteroidal antiinflammatory agents, antiestrogen compounds, and a variety of other agents in small series. Imatinib mesylate appears to demonstrate inhibitory activity against multiple class 3 receptor tyrosine kinases, including platelet‐derived growth factor receptor (PDGFR)‐α and PDGFR‐β, as well as c‐kit.

HER2 Drives Luminal Breast Cancer Stem Cells in the Absence of HER2 Amplification: Implications for Efficacy of Adjuvant Trastuzumab

Although current breast cancer treatment guidelines limit the use of HER2-blocking agents to tumors with HER2 gene amplification, recent retrospective analyses suggest that a wider group of patients may benefit from this therapy. Using breast cancer cell lines, mouse xenograft models and matched human primary and metastatic tissues, we show that HER2 is selectively expressed in and regulates self-renewal of the cancer stem cell (CSC) population in estrogen receptor-positive (ER(+)), HER2(-) luminal breast cancers. Although trastuzumab had no effects on the growth of established luminal breast cancer mouse xenografts, administration after tumor inoculation blocked subsequent tumor growth. HER2 expression is increased in luminal tumors grown in mouse bone xenografts, as well as in bone metastases from patients with breast cancer as compared with matched primary tumors. Furthermore, this increase in HER2 protein expression was not due to gene amplification but rather was mediated by receptor activator of NF-κB (RANK)-ligand in the bone microenvironment. These studies suggest that the clinical efficacy of adjuvant trastuzumab may relate to the ability of this agent to target the CSC population in a process that does not require HER2 gene amplification. Furthermore, these studies support a CSC model in which maximal clinical benefit is achieved when CSC targeting agents are administered in the adjuvant setting. Cancer Res; 73(5); 1635-46. ©2012 AACR.

Genomic amplification of MET with boundaries within fragile site FRA7G and upregulation of MET pathways in esophageal adenocarcinoma

Esophageal adenocarcinoma (EA) is characterized by a poor prognosis making the identification of clinically targetable proteins essential for improving patient outcome. We report the involvement of multiple alterations of the MET pathway in EA development and progression. Microarray analysis of Barretts metaplasia, dysplasia, and EA revealed overexpression of the MET oncogene in EAs but only those with MET gene amplification. STS-amplification mapping revealed that the boundary of the MET amplicon in these EAs is defined by fragile site FRA7G. We also identified an amplicon at 11p13 that resulted in amplification and overexpression of CD44, a gene involved in MET autophosphorylation upon HGF stimulation. Tissue microarrays with phospho-MET-specific antibodies demonstrated a uniformly high abundance of MET activation in primary EA and cells metastatic to lymph nodes but to a lesser extent in a subset of metaplastic and dysplastic Barretts samples. Increased expression of multiple genes in the MET pathway associated with invasive growth, for example, many MMPs and osteopontin, also was found in EAs. Treatment of EA-derived cell lines with geldanamycin, an inhibitor for tyrosine kinases including MET receptor kinase, reduced cell migration and induced EA cell apoptosis. The data indicate that upregulation of the MET pathway may contribute to the poor outcome of EA patients and that therapeutic agents targeting this pathway may help improve patient survival.

Preclinical Targeting of the Type I Insulin-Like Growth Factor Receptor in Adrenocortical Carcinoma

CONTEXT Drug therapy for adrenocortical carcinoma (ACC), a rare and lethal malignancy, is largely empirical and ineffective. New treatments directed at molecular targets critical to the pathophysiology of ACC may prove more efficacious. OBJECTIVE The objective of the study was to profile human adrenal tumors and ACC cell lines to assess activated IGF signaling and determine the efficacy of two IGF receptor (IGF-1R) antagonists alone and in combination with mitotane. EXPERIMENTAL DESIGN ACC cell lines that display or lack activated IGF signaling are used to assess the effects of two IGF-1R antagonists in cultured cells and ACC xenograft tumors. RESULTS Transcriptional profiling data derived from DNA microarray analysis of human adrenal tumors implicate IGF2 as the single highest up-regulated transcript in the vast majority of carcinomas. We show that the majority of ACC cell lines tested display constitutive IGF ligand production and activation of downstream effector pathways. Both IGF-1R antagonists cause significant dose-dependent growth inhibition in ACC cell lines. Furthermore, we observe that mitotane, the first-line adrenolytic drug used in patients with ACC, results in enhanced growth inhibition when used in combination with the IGF-1R antagonists. We next examined the activity of IGF-1R antagonists against ACC xenografts in athymic nude mice. IGF inhibition markedly reduced tumor growth greater than that observed with mitotane treatment, and combination therapy with mitotane significantly enhanced tumor growth suppression. CONCLUSION These findings establish a critical role of IGF signaling in ACC pathophysiology and provide rationale for use of targeted IGF-1R antagonists to treat adrenocortical carcinoma in future clinical trials.