HER2 Status in Advanced or Metastatic Gastric, Esophageal, or Gastroesophageal Adenocarcinoma for Entry to the TRIO-013/LOGiC Trial of Lapatinib.

HER2/ERBB2 status is used to select patients for HER2-targeted therapy. HER2/ERBB2 amplification/overexpression of upper gastrointestinal (UGI) adenocarcinomas was determined locally or in two central laboratories to select patients for the TRIO-013/LOGiC trial of chemotherapy with or without lapatinib. Patients selected locally had central laboratory confirmation of HER2 amplification for inclusion in the primary efficacy population. HER2 was assessed with PathVysion or IQ PharmDx FISH and HercepTest immunohistochemistry assays. Associations with outcomes were retrospectively evaluated. Overall, HER2 status was determined in UGI cancers from 4,674 patients in a central laboratory for eligibility (1,995 cases) and for confirmation of local HER2 results (333 cases). Of 1,995 adenocarcinomas screened centrally, 322 (16.1%) had HER2-amplified disease with 29 (1.5%) showing HER2 genomic heterogeneity. Men and older patients had higher rates of amplification. Of 545 patients accrued to the trial (gastric, 87.3%; GEJ, 8.3% and esophageal cancer, 4.4%), 487 patients (89%) were centrally confirmed as having HER2-amplified disease. Concordance between central and local HER2 testing was 83%. Concordance between PathVysion and IQ PharmDx FISH assays was 99% and FISH in the two central laboratories was 95%. Lapatinib-treated Asian participants and those less than 60 years had significant improvement in progression-free survival (PFS), particularly among those whose cancers had 5.01-10.0 and >10.0-fold amplification of HER2 In conclusion, HER2 is commonly amplified in UGI adenocarcinomas with amplification highly correlated to overexpression, and HER2 amplification levels correlated with PFS. While HER2 genomic heterogeneity occurs, its prevalence is low. Mol Cancer Ther; 16(1); 228-38. ©2016 AACR.

Correlative Analysis of Genetic Alterations and Everolimus Benefit in Hormone Receptor-Positive, Human Epidermal Growth Factor Receptor 2-Negative Advanced Breast Cancer: Results From BOLERO-2.

PURPOSE: To explore the genetic landscape of tumors from patients enrolled on the BOLERO-2 trial to identify potential correlations between genetic alterations and efficacy of everolimus treatment. The BOLERO-2 trial has previously demonstrated that the addition of everolimus to exemestane prolonged progression-free survival by more than twofold in patients with hormone receptor-positive, human epidermal growth factor receptor 2-negative, advanced breast cancer previously treated with nonsteroidal aromatase inhibitors. PATIENTS AND METHODS: Next-generation sequencing was used to analyze genetic status of cancer-related genes in 302 archival tumor specimens from patients representative of the BOLERO-2 study population. Correlations between the most common somatic alterations and degree of chromosomal instability, and treatment effect of everolimus were investigated. RESULTS: Progression-free survival benefit with everolimus was maintained regardless of alteration status of PIK3CA, FGFR1, and CCND1 or the pathways of which they are components. However, quantitative differences in everolimus benefit were observed between patient subgroups defined by the exon-specific mutations in PIK3CA (exon 20 v 9) or by different degrees of chromosomal instability in the tumor tissues. CONCLUSION: The data from this exploratory analysis suggest that the efficacy of everolimus was largely independent of the most commonly altered genes or pathways in hormone receptor-positive, human epidermal growth factor receptor 2-negative breast cancer. The potential impact of chromosomal instabilities and low-frequency genetic alterations on everolimus efficacy warrants further investigation.

A five-gene hedgehog signature developed as a patient preselection tool for hedgehog inhibitor therapy in medulloblastoma.

PURPOSE: Distinct molecular subgroups of medulloblastoma, including hedgehog (Hh) pathway-activated disease, have been reported. We identified and clinically validated a five-gene Hh signature assay that can be used to preselect patients with Hh pathway-activated medulloblastoma. EXPERIMENTAL DESIGN: Gene characteristics of the Hh medulloblastoma subgroup were identified through published bioinformatic analyses. Thirty-two genes shown to be differentially expressed in fresh-frozen and formalin-fixed paraffin-embedded tumor samples and reproducibly analyzed by RT-PCR were measured in matched samples. These data formed the basis for building a multi-gene logistic regression model derived through elastic net methods from which the five-gene Hh signature emerged after multiple iterations. On the basis of signature gene expression levels, the model computed a propensity score to determine Hh activation using a threshold set a priori. The association between Hh activation status and tumor response to the Hh pathway inhibitor sonidegib (LDE225) was analyzed. RESULTS: Five differentially expressed genes in medulloblastoma (GLI1, SPHK1, SHROOM2, PDLIM3, and OTX2) were found to associate with Hh pathway activation status. In an independent validation study, Hh activation status of 25 medulloblastoma samples showed 100% concordance between the five-gene signature and Affymetrix profiling. Further, in medulloblastoma samples from 50 patients treated with sonidegib, all 6 patients who responded were found to have Hh-activated tumors. Three patients with Hh-activated tumors had stable or progressive disease. No patients with Hh-nonactivated tumors responded. CONCLUSIONS: This five-gene Hh signature can robustly identify Hh-activated medulloblastoma and may be used to preselect patients who might benefit from sonidegib treatment.

Quantifying the impact of protein tertiary structure on molecular evolution.

To investigate the evolutionary impact of protein structure, the experimentally determined tertiary structure and the protein-coding DNA sequence were collected for each of 1,195 genes. These genes were studied via a model of sequence change that explicitly incorporates effects on evolutionary rates due to protein tertiary structure. In the model, these effects act via the solvent accessibility environments and pairwise amino acid interactions that are induced by tertiary structure. To compare the hypotheses that structure does and does not have a strong influence on evolution, Bayes factors were estimated for each of the 1,195 sequences. Most of the Bayes factors strongly support the hypothesis that protein structure affects protein evolution. Furthermore, both solvent accessibility and pairwise interactions among amino acids are inferred to have important roles in protein evolution. Our results also indicate that the strength of the relationship between tertiary structure and evolution has a weak but real correlation to the annotation information in the Gene Ontology database. Although their influences on rates of evolution vary among protein families, we find that the mean impacts of solvent accessibility and pairwise interactions are about the same.

Protein evolution with dependence among codons due to tertiary structure.

Markovian models of protein evolution that relax the assumption of independent change among codons are considered. With this comparatively realistic framework, an evolutionary rate at a site can depend both on the state of the site and on the states of surrounding sites. By allowing a relatively general dependence structure among sites, models of evolution can reflect attributes of tertiary structure. To quantify the impact of protein structure on protein evolution, we analyze protein-coding DNA sequence pairs with an evolutionary model that incorporates effects of solvent accessibility and pairwise interactions among amino acid residues. By explicitly considering the relationship between nonsynonymous substitution rates and protein structure, this approach can lead to refined detection and characterization of positive selection. Analyses of simulated sequence pairs indicate that parameters in this evolutionary model can be well estimated. Analyses of lysozyme c and annexin V sequence pairs yield the biologically reasonable result that amino acid replacement rates are higher when the replacements lead to energetically favorable proteins than when they destabilize the proteins. Although the focus here is evolutionary dependence among codons that is associated with protein structure, the statistical approach is quite general and could be applied to diverse cases of evolutionary dependence where surrogates for sequence fitness can be measured or modeled.