Pretreatment gene expression profiles can be used to predict response to neoadjuvant chemoradiotherapy in esophageal cancer.

BACKGROUND: The use of neoadjuvant therapy, in particular chemoradiotherapy (CRT), in the treatment of esophageal cancer (EC) remains controversial. The ability to predict treatment response in an individual EC patient would greatly aid therapeutic planning. Gene expression profiles of EC were measured and relationship to therapeutic response assessed. METHODS: Tumor biopsy samples taken from 46 EC patients before neoadjuvant CRT were analyzed on 10.5K cDNA microarrays. Response to treatment was assessed and correlated to gene expression patterns by using a support vector machine learning algorithm. RESULTS: Complete clinical response at conclusion of CRT was achieved in 6 of 21 squamous cell carcinoma (SCC) and 11 of 25 adenocarcinoma (AC) patients. CRT response was an independent prognostic factor for survival (P < .001). A range of support vector machine models incorporating 10 to 1000 genes produced a predictive performance of tumor response to CRT peaking at 87% in SCC, but a distinct positive prediction profile was unobtainable for AC. A 32-gene classifier was produced, and by means of this classifier, 10 of 21 SCC patients could be accurately identified as having disease with an incomplete response to therapy, and thus unlikely to benefit from neoadjuvant CRT. CONCLUSIONS: Our study identifies a 32-gene classifier that can be used to predict response to neoadjuvant CRT in SCC. However, because of the molecular diversity between the two histological subtypes of EC, when considering the AC and SCC samples as a single cohort, a predictive profile could not be resolved, and a negative predictive profile was observed for AC.

Gene expression profiling of esophageal cancer: comparative analysis of Barrett's esophagus, adenocarcinoma, and squamous cell carcinoma.

Esophageal cancer is a particularly aggressive tumor with poor prognosis, however, our current knowledge of the genes and pathways involved in tumorigenesis of the esophagus are limited. To obtain insight into the molecular processes underlying tumorigenesis of the esophagus, we have used cDNA microarrays to compare the gene expression profiles of 128 tissue samples representing the major histological subtypes of esophageal cancer (squamous cell carcinoma and adenocarcinoma (ADC)) as well as Barrett's esophagus (BE), the precursor lesion to ADC, and normal esophageal epithelium. Linear discriminant analysis and unsupervised hierarchical clustering show the separation of samples into 4 distinct groups consistent with their histological subtype. Differentially expressed genes were identified between each of the tissue types. Comparison of gene ontologies and gene expression profiles identified gene profiles specific to esophageal cancer, as well as BE. "Esophageal cancer clusters," representing proliferation, immune response, and extracellular matrix genes were identified, as well as digestion, hydrolase, and transcription factor clusters specific to the columnar phenotype observed during BE and esophageal ADC. These clusters provide valuable insight into the molecular and functional differences between normal esophageal epithelium, BE, and the 2 histologically distinct forms of esophageal cancers. Our thorough, unbiased analysis provides a rich source of data for further studies into the molecular basis of tumorigenesis of the esophagus, as well as identification of potential biomarkers for early detection of progression.

Mutation analysis of PIK3CA and PIK3CB in esophageal cancer and Barrett's esophagus.

Mutation of PIK3CA, the gene coding for the p110alpha catalytic subunit of phosphoinositide 3-kinase (PI3K), has been reported in a limited range of human tumors. We now report that PIK3CA is also mutated in esophageal tumors. Single-strand conformational polymorphism (SSCP) and denaturing high-performance liquid chromatography (DHPLC) were used to screen all 20 exons of PIK3CA in 101 samples from 95 individuals with esophageal cancer and/or Barrett's esophagus. Somatic mutation of PIK3CA was detected in 4 of 35 (11.8%) of esophageal squamous cell carcinomas (SCC) and 3 of 50 (6%) adenocarcinomas. No mutations were detected in any of 17 samples of Barrett's esophagus. For PIK3CB, we screened exons 11 and 22, which code for the regions corresponding to the exon 9 and 20 mutational 'hotspots' of PIK3CA. No somatic changes were detected in PIK3CB This study extends previous observations in other tumor types by demonstrating the presence of somatic PIK3CA mutations in both SCC and adenocarcinoma of the esophagus, thus implicating the PI3K pathway in the initiation and/or progression of esophageal cancers.

Mutation of the PIK3CA gene in ovarian and breast cancer.

Phosphatidylinositol 3'-kinases are lipid kinases with important roles in neoplasia. Recently, a very high frequency of somatic mutations in PIK3CA has been reported among a large series of colorectal cancers. However, the relevance of PIK3CA mutation in other cancer types remains unclear because of the limited number of tumors investigated. We have screened a total of 284 primary human tumors for mutations in all coding exons of PIK3CA using a combination of single stranded conformational polymorphism and denaturing high-performance liquid chromatography analysis. Among 70 primary breast cancers, 40% (28 of 70) harbored mutations in PIK3CA, making it the most common mutation described to date in this cancer type. Mutations were not associated with histologic subtype, estrogen receptor status, grade or presence of tumor in lymph nodes. Among the primary epithelial ovarian cancers only 11 of 167 (6.6%) contain somatic mutations, but there was a clear histologic subtype bias in their distribution. Only 2 of 88 (2.3%) of serous carcinomas had PIK3CA mutations compared with 8 of 40 (20.0%) endometrioid and clear cell cancers, which was highly significant (P = 0.001). In contrast, PIK3CA gene amplification (>7-fold) was common among all histologic subtypes (24.5%) and was inversely associated with the presence of mutations. Overall, PIK3CA mutation or gene amplification was detected in 30.5% of all ovarian cancers and 45% of the endometrioid and clear cell subtypes. Our study is the first direct evidence that PIK3CA is an oncogene in ovarian cancer and greatly extends recent findings in breast cancer.