Integrative analysis of non-small cell lung cancer patient-derived xenografts identifies distinct proteotypes associated with patient outcomes.

Non-small cell lung cancer (NSCLC) is the leading cause of cancer deaths worldwide. Only a fraction of NSCLC harbor actionable driver mutations and there is an urgent need for patient-derived model systems that will enable the development of new targeted therapies. NSCLC and other cancers display profound proteome remodeling compared to normal tissue that is not predicted by DNA or RNA analyses. Here, we generate 137 NSCLC patient-derived xenografts (PDXs) that recapitulate the histology and molecular features of primary NSCLC. Proteome analysis of the PDX models reveals 3 adenocarcinoma and 2 squamous cell carcinoma proteotypes that are associated with different patient outcomes, protein-phosphotyrosine profiles, signatures of activated pathways and candidate targets, and in adenocarcinoma, stromal immune features. These findings portend proteome-based NSCLC classification and treatment and support the PDX resource as a viable model for the development of new targeted therapies.

Targeting the CDK4/6-Rb Pathway Enhances Response to PI3K Inhibition in PIK3CA-Mutant Lung Squamous Cell Carcinoma.

PURPOSE: Lung squamous cell carcinoma (LUSC) is a major subtype of non-small cell lung cancer characterized by multiple genetic alterations, particularly PI3K pathway alterations which have been identified in over 50% of LUSC cases. Despite being an attractive target, single-agent PI3K inhibitors have demonstrated modest response in LUSC. Thus, novel combination therapies targeting LUSC are needed. EXPERIMENTAL DESIGN: PI3K inhibitors alone and in combination with CDK4/6 inhibitors were evaluated in previously established LUSC patient-derived xenografts (PDX) using an in vivo screening method. Screening results were validated with in vivo expansion to 5 to 8 mice per arm. Pharmacodynamics studies were performed to confirm targeted inhibition of compounds. RESULTS: Consistent with results from The Cancer Genome Atlas analysis of LUSC, genomic profiling of our large cohort of LUSC PDX models identified PI3K pathway alterations in over 50% of the models. In vivo screening using PI3K inhibitors in 12 of these models identified PIK3CA mutation as a predictive biomarker of response (<20% tumor growth compared with baseline/vehicle). Combined inhibition of PI3K and CDK4/6 in models with PIK3CA mutation resulted in greater antitumor effects compared with either monotherapy alone. In addition, the combination of the two drugs achieved targeted inhibition of the PI3K and cell-cycle pathways. CONCLUSIONS: PIK3CA mutations predict response to PI3K inhibitors in LUSC. Combined PI3K and CDK4/6 inhibition enhances response to either single agents alone. Our findings provide a rationale for clinical testing of combined PI3K and CDK4/6 inhibitors in PIK3CA-mutant LUSC.

Helicase-like transcription factor expression is associated with a poor prognosis in Non-Small-Cell Lung Cancer (NSCLC).

BACKGROUND: The relapse rate in early stage non-small cell lung cancer (NSCLC) after surgical resection is high. Prognostic biomarkers may help identify patients who may benefit from additional therapy. The Helicase-like Transcription Factor (HLTF) is a tumor suppressor, altered in cancer either by gene hypermethylation or mRNA alternative splicing. This study assessed the expression and the clinical relevance of wild-type (WT) and variant forms of HLTF RNAs in NSCLC. METHODS: We analyzed online databases (TCGA, COSMIC) for HLTF alterations in NSCLC and assessed WT and spliced HLTF mRNAs expression by RT-ddPCR in 39 lung cancer cell lines and 171 patients with resected stage I-II NSCLC. RESULTS: In silico analyses identified HLTF gene alterations more frequently in lung squamous cell carcinoma than in adenocarcinoma. In cell lines and in patients, WT and I21R HLTF mRNAs were detected, but the latter at lower level. The subgroup of 25 patients presenting a combined low WT HLTF expression and a high I21R HLTF expression had a significantly worse disease-free survival than the other 146 patients in univariate (HR 1.96, CI 1.17-3.30; p = 0.011) and multivariate analyses (HR 1.98, CI 1.15-3.40; p = 0.014). CONCLUSION: A low WT HLTF expression with a high I21R HLTF expression is associated with a poor DFS.

Use of Sequenom sample ID Plus® SNP genotyping in identification of FFPE tumor samples.

Short tandem repeat (STR) analysis, such as the AmpFlSTR® Identifiler® Plus kit, is a standard, PCR-based human genotyping method used in the field of forensics. Misidentification of cell line and tissue DNA can be costly if not detected early; therefore it is necessary to have quality control measures such as STR profiling in place. A major issue in large-scale research studies involving archival formalin-fixed paraffin embedded (FFPE) tissues is that varying levels of DNA degradation can result in failure to correctly identify samples using STR genotyping. PCR amplification of STRs of several hundred base pairs is not always possible when DNA is degraded. The Sample ID Plus® panel from Sequenom allows for human DNA identification and authentication using SNP genotyping. In comparison to lengthy STR amplicons, this multiplexing PCR assay requires amplification of only 76-139 base pairs, and utilizes 47 SNPs to discriminate between individual samples. In this study, we evaluated both STR and SNP genotyping methods of sample identification, with a focus on paired FFPE tumor/normal DNA samples intended for next-generation sequencing (NGS). The ability to successfully validate the identity of FFPE samples can enable cost savings by reducing rework.

Robust global microRNA expression profiling using next-generation sequencing technologies.

miRNAs are a class of regulatory molecules involved in a wide range of cellular functions, including growth, development and apoptosis. Given their widespread roles in biological processes, understanding their patterns of expression in normal and diseased states will provide insights into the consequences of aberrant expression. As such, global miRNA expression profiling of human malignancies is gaining popularity in both basic and clinically driven research. However, to date, the majority of such analyses have used microarrays and quantitative real-time PCR. With the introduction of digital count technologies, such as next-generation sequencing (NGS) and the NanoString nCounter System, we have at our disposal many more options. To make effective use of these different platforms, the strengths and pitfalls of several miRNA profiling technologies were assessed, including a microarray platform, NGS technologies and the NanoString nCounter System. Overall, NGS had the greatest detection sensitivity, largest dynamic range of detection and highest accuracy in differential expression analysis when compared with gold-standard quantitative real-time PCR. Its technical reproducibility was high, with intrasample correlations of at least 0.95 in all cases. Furthermore, miRNA analysis of formalin-fixed, paraffin-embedded (FFPE) tissue was also evaluated. Expression profiles between paired frozen and FFPE samples were similar, with Spearman's ρ>0.93. These results show the superior sensitivity, accuracy and robustness of NGS for the comprehensive profiling of miRNAs in both frozen and FFPE tissues.