A computational index derived from whole-genome copy number analysis is a novel tool for prognosis in early stage lung squamous cell carcinoma

Sparse modelling of cancer patients' survival based on genomic copy number alterations

Copy number alterations (CNA) are structural variation in the genome, in which some regions exhibit more or less than the normal two chromosomal copies. This genomic CNA profile provides critical information in tumour progression and is therefore informative for patients' survival. It is currently a statistical challenge to model patients' survival using their genomic CNA profiles while at the same time identify regions in the genome that are associated with patients' survival. Some methods have been proposed, including Cox proportional hazard (PH) model with ridge, lasso, or elastic net penalties. However, these methods do not take the general dependencies between genomic regions into account and produce results that are difficult to interpret. In this paper, we extend the elastic net penalty by introducing additional penalty that takes into account general dependencies between genomic regions. This new model produces smooth parameter estimates while simultaneously performs variable selection via sparse solution. The results indicate that the proposed method shows a better prediction performance than other models in our simulation study, while enabling us to investigate regions in the genome that are associated with the patients' survival with sensible interpretation. We illustrate the method using a real dataset from a lung cancer cohort and simulated data.

Somatic Alteration Burden Involving Non-Cancer Genes Predicts Prognosis in Early-Stage Non-Small Cell Lung Cancer

The burden of somatic mutations and neoantigens has been associated with improved survival in cancer treated with immunotherapies, especially non-small cell lung cancer (NSCLC). However, there is uncertainty about their effect on outcome in early-stage untreated cases. We posited that the burden of mutations in a specific set of genes may also contribute to the prognosis of early NSCLC patients. From a small cohort of 36 NSCLC cases, we were able to identify somatic mutations and copy number alterations in 865 genes that contributed to patient overall survival. Simply, the number of altered genes (NAG) among these 865 genes was associated with longer disease-free survival (hazard ratio (HR) = 0.153, p = 1.48 × 10^-4). The gene expression signature distinguishing patients with high/low NAG was also prognostic in three independent datasets. Patients with a high NAG could be further stratified based on the presence of immunogenic mutations, revealing a further subgroup of stage I NSCLC with even better prognosis (85% with >5 years survival), and associated with cytotoxic T-cell expression. Importantly, 95% of the highly-altered genes lacked direct relation to cancer, but were implicated in pathways regulating cell proliferation, motility and immune response.

High-Resolution Copy Number Patterns From Clinically Relevant FFPE Material

Systematic tumour profiling is essential for biomarker research and clinically for assessing response to therapy. Solving the challenge of delivering informative copy number (CN) profiles from formalin-fixed paraffin embedded (FFPE) material, the only likely readily available biospecimen for most cancers, involves successful processing of small quantities of degraded DNA. To investigate the potential for analysis of such lesions, whole-genome CNVseq was applied to 300 FFPE primary tumour samples, obtained from a large-scale epidemiological study of melanoma. The quality and the discriminatory power of CNVseq was assessed. Libraries were successfully generated for 93% of blocks, with input DNA quantity being the only predictor of success (success rate dropped to 65% if <20 ng available); 3% of libraries were dropped because of low sequence alignment rates. Technical replicates showed high reproducibility. Comparison with targeted CN assessment showed consistency with the Next Generation Sequencing (NGS) analysis. We were able to detect and distinguish CN changes with a resolution of ≤10 kb. To demonstrate performance, we report the spectrum of genomic CN alterations (CNAs) detected at 9p21, the major site of CN change in melanoma. This successful analysis of CN in FFPE material using NGS provides proof of principle for intensive examination of population-based samples.

Prevalence of Mutations in Discoidin Domain-Containing Receptor Tyrosine Kinase 2 (DDR2) in Squamous Cell Lung Cancers in Korean Patients

Purpose

The discoidin domain-containing receptor tyrosine kinase 2 (DDR2) is known to contain mutations in a small subset of patients with squamous cell carcinomas (SCC) of the lung. Studying the DDR2 mutations in patients with SCC of the lung would advance our understanding and guide the development of therapeutic strategies against lung cancer.

Materials and Methods

We selected 100 samples through a preliminary genetic screen, including specimens from biopsies and surgical resection, and confirmed SCC by histologic examination. DDR2 mutations on exons 6, 15, 16, and 18 were analyzed by Sanger sequencing of formalin-fixed, paraffin-embedded tissue samples. The functional effects of novel DDR2 mutants were confirmed by in vitro assays.

Results

We identified novel somatic mutations of DDR2 in two of the 100 SCC samples studied. One mutation was c.1745T>A (p.V582E) and the other was c.1784T>C (p.L595P), and both were on exon 15. Both patients were smokers and EGFR/KRAS/ALK-triple negative. The expression of the mutant DDR2 induced activation of DDR2 by the collagen ligand and caused enhanced cell growth and tumor progression. Moreover, dasatinib, a DDR2 inhibitor, showed potential efficacy against DDR2 L595P mutant–bearing cells.

Conclusion

Our results suggest that a mutation in DDR2 occurs naturally with a frequency of about 2% in Korean lung SCC patients. In addition, we showed that each of the novel DDR2 mutations were located in a kinase domain and induced an increase in cell proliferation rate.

[Personalized targeted therapy for lung cancer]

由于每一肺癌患者在临床特征、预后、治疗反应和耐受性方面的进展都是独特的，所以肺癌被认为是异质性疾病。个体化用药是指运用标志物来预测哪些患者更易获益于某种治疗。对于肺癌而言，日趋完善的表皮生长因子受体(epidermal growth factor receptor, EGFR)和新发现的棘皮动物微管相关蛋白样4-间变淋巴瘤激酶(echinoderm microtubule associated protein like 4-anaplastic lymphoma kinase, EML4-ALK)是重要的治疗靶标。本综述包括EGFR和EML4-ALK活化的机制、预测性生物标记物、耐药的机理和已有的靶向性酪氨酸激酶抑制剂。本文将通过总结基于生物标记物筛选患者而进行的前瞻性临床试验来探讨EGFR和ALK靶向治疗的疗效。此外，由于革命性的测序和系统生物学技术会为癌症的分子特征提供一个全面的理解，有助于为更适宜靶向治疗的患者提供更精确的区分从而提供更有前景的个体化治疗，本综述也将包括这些技术。同时，非亚裔人群中EGFR和ALK相对较低的突变发生率和突变患者反应的缺乏限制了靶向于EGFR或ALK的治疗的应用。测序和系统生物学策略则可能为这些患者提供新的解决方案。

Molecular classification of non-small-cell lung cancer: diagnosis, individualized treatment, and prognosis

Non-small-cell lung cancer (NSCLC) is the most common cause of premature death among the malignant diseases worldwide. The current staging criteria do not fully capture the complexity of this disease. Molecular biology techniques, particularly gene expression microarrays, proteomics, and next-generation sequencing, have recently been developed to facilitate effectively its molecular classification. The underlying etiology, pathogenesis, therapeutics, and prognosis of NSCLC based on an improved molecular classification scheme may promote individualized treatment and improve clinical outcomes. This review focuses on the molecular classification of NSCLC based on gene expression microarray technology reported during the past decade, as well as their applications for improving the diagnosis, staging and treatment of NSCLC, including the discovery of prognostic markers or potential therapeutic targets. We highlight some of the recent studies that may refine the identification of NSCLC subtypes using novel techniques such as epigenetics, proteomics, or deep sequencing.

The transcriptional consequences of somatic amplifications, deletions, and rearrangements in a human lung squamous cell carcinoma

Lung cancer causes more deaths, worldwide, than any other cancer. Several histologic subtypes exist. Currently, there is a dearth of targeted therapies for treating one of the main subtypes: squamous cell carcinoma (SCC). As for many cancers, lung SCC karyotypes are often highly anomalous owing to large somatic structural variants, some of which are seen repeatedly in lung SCC, indicating a potential causal association for genes therein. We chose to characterize a lung SCC genome to unprecedented detail and integrate our findings with the concurrently characterized transcriptome. We aimed to ascertain how somatic structural changes affected gene expression within the cell in ways that could confer a pathogenic phenotype. We sequenced the genomes of a lung SCC cell line (LUDLU-1) and its matched lymphocyte cell line (AGLCL) to more than 50x coverage. We also sequenced the transcriptomes of LUDLU-1 and a normal bronchial epithelium cell line (LIMM-NBE1), resulting in more than 600 million aligned reads per sample, including both coding and non-coding RNA (ncRNA), in a strand-directional manner. We also captured small RNA (<30 bp). We discovered significant, but weak, correlations between copy number and expression for protein-coding genes, antisense transcripts, long intergenic ncRNA, and microRNA (miRNA). We found that miRNA undergo the largest change in overall expression pattern between the normal bronchial epithelium and the tumor cell line. We found evidence of transcription across the novel genomic sequence created from six somatic structural variants. For each part of our integrated analysis, we highlight candidate genes that have undergone the largest expression changes.

Personalized targeted therapy for lung cancer

Lung cancer has long been recognized as an extremely heterogeneous disease, since its development is unique in every patient in terms of clinical characterizations, prognosis, response and tolerance to treatment. Personalized medicine refers to the use of markers to predict which patient will most likely benefit from a treatment. In lung cancer, the well-developed epidermal growth factor receptor (EGFR) and the newly emerging EML4-anaplastic lymphoma kinase (ALK) are important therapeutic targets. This review covers the basic mechanism of EGFR and EML4-ALK activation, the predictive biomarkers, the mechanism of resistance, and the current targeted tyrosine kinase inhibitors. The efficacy of EGFR and ALK targeted therapies will be discussed in this review by summarizing the prospective clinical trials, which were performed in biomarker-based selected patients. In addition, the revolutionary sequencing and systems strategies will also be included in this review since these technologies will provide a comprehensive understanding in the molecular characterization of cancer, allow better stratification of patients for the most appropriate targeted therapies, eventually resulting in a more promising personalized treatment. The relatively low incidence of EGFR and ALK in non-Asian patients and the lack of response in mutant patients limit the application of the therapies targeting EGFR or ALK. Nevertheless, it is foreseeable that the sequencing and systems strategies may offer a solution for those patients.

Novel tumor subgroups of urothelial carcinoma of the bladder defined by integrated genomic analysis

PURPOSE

There is a need for improved subclassification of urothelial carcinoma (UC) at diagnosis. A major aim of this study was to search for novel genomic subgroups.

EXPERIMENTAL DESIGN

We assessed 160 tumors for genome-wide copy number alterations and mutation in genes implicated in UC. These comprised all tumor grades and stages and included 49 high-grade stage T1 (T1G3) tumors.

RESULTS

Our findings point to the existence of genomic subclasses of the "gold-standard" grade/stage groups. The T1G3 tumors separated into 3 major subgroups that differed with respect to the type and number of copy number events and to FGFR3 and TP53 mutation status. We also identified novel regions of copy number alteration, uncovered relationships between molecular events, and elucidated relationships between molecular events and clinico-pathologic features. FGFR3 mutant tumors were more chromosomally stable than their wild-type counterparts and a mutually exclusive relationship between FGFR3 mutation and overrepresentation of 8q was observed in non-muscle-invasive tumors. In muscle-invasive (MI) tumors, metastasis was positively associated with losses of regions on 10q (including PTEN), 16q and 22q, and gains on 10p, 11q, 12p, 19p, and 19q. Concomitant copy number alterations positively associated with TP53 mutation in MI tumors were losses on 16p, 2q, 4q, 11p, 10q, 13q, 14q, 16q, and 19p, and gains on 1p, 8q, 10q, and 12q. Significant complexity was revealed in events affecting chromosome 9.

CONCLUSIONS

These findings may lead to improved biologic understanding and the development of prognostic biomarkers. Novel regions of copy number alteration may reveal potential therapeutic targets.

Molecular profiling to optimize treatment in non-small cell lung cancer: a review of potential molecular targets for radiation therapy by the translational research program of the radiation therapy oncology group

Therapeutic decisions in non-small cell lung cancer (NSCLC) have been mainly based on disease stage, performance status, and co-morbidities, and rarely on histological or molecular classification. Rather than applying broad treatments to unselected patients that may result in survival increase of only weeks to months, research efforts should be, and are being, focused on identifying predictive markers for molecularly targeted therapy and determining genomic signatures that predict survival and response to specific therapies. The availability of such targeted biologics requires their use to be matched to tumors of corresponding molecular vulnerability for maximum efficacy. Molecular markers such as epidermal growth factor receptor (EGFR), K-ras, vascular endothelial growth factor (VEGF), mammalian target of rapamycin (mTOR), and anaplastic lymphoma kinase (ALK) represent potential parameters guide treatment decisions. Ultimately, identifying patients who will respond to specific therapies will allow optimal efficacy with minimal toxicity, which will result in more judicious and effective application of expensive targeted therapy as the new paradigm of personalized medicine develops.

Identification of high-confidence somatic mutations in whole genome sequence of formalin-fixed breast cancer specimens

The utilization of archived, formalin-fixed paraffin-embedded (FFPE) tumor samples for massive parallel sequencing has been challenging due to DNA damage and contamination with normal stroma. Here, we perform whole genome sequencing of DNA isolated from two triple-negative breast cancer tumors archived for >11 years as 5 µm FFPE sections and matched germline DNA. The tumor samples show differing amounts of FFPE damaged DNA sequencing reads revealed as relatively high alignment mismatch rates enriched for C · G > T · A substitutions compared to germline samples. This increase in mismatch rate is observable with as few as one million reads, allowing for an upfront evaluation of the sample integrity before whole genome sequencing. By applying innovative quality filters incorporating global nucleotide mismatch rates and local mismatch rates, we present a method to identify high-confidence somatic mutations even in the presence of FFPE induced DNA damage. This results in a breast cancer mutational profile consistent with previous studies and revealing potentially important functional mutations. Our study demonstrates the feasibility of performing genome-wide deep sequencing analysis of FFPE archived tumors of limited sample size such as residual cancer after treatment or metastatic biopsies.