Larissa A. Pikor

The detection and implication of genome instability in cancer

Genomic instability is a hallmark of cancer that leads to an increase in genetic alterations, thus enabling the acquisition of additional capabilities required for tumorigenesis and progression. Substantial heterogeneity in the amount and type of instability (nucleotide, microsatellite, or chromosomal) exists both within and between cancer types, with epithelial tumors typically displaying a greater degree of instability than hematological cancers. While high-throughput sequencing studies offer a comprehensive record of the genetic alterations within a tumor, detecting the rate of instability or cell-to-cell viability using this and most other available methods remains a challenge. Here, we discuss the different levels of genomic instability occurring in human cancers and touch on the current methods and limitations of detecting instability. We have applied one such approach to the surveying of public tumor data to provide a cursory view of genome instability across numerous tumor types.

Genetic alterations defining NSCLC subtypes and their therapeutic implications

Lung cancer is the leading cause of cancer death worldwide, accounting for more deaths than breast, prostate and colon cancer combined. While treatment decisions are determined primarily by stage, therapeutically non small cell lung cancer (NSCLC) has traditionally been treated as a single disease. However, recent findings have led to the recognition of histology and molecular subtypes as important determinants in treatment selection. Identifying the genetic differences that define these molecular and histological subtypes has the potential to impact treatment and as such is currently the focus of much research. Microarray and genomic sequencing efforts have provided unparalleled insight into the genomes of lung cancer subtypes, specifically adenocarcinoma (AC) and squamous cell carcinoma (SqCC), revealing subtype specific genomic alterations and molecular subtypes as well as differences in cell signaling pathways. In this review, we discuss the recurrent genomic alterations characteristic of AC and SqCC (including molecular subtypes), their therapeutic implications and emerging clinical practices aimed at tailoring treatments based on a tumors molecular alterations with the hope of improving patient response and survival.

DNA Extraction from Paraffin Embedded Material for Genetic and Epigenetic Analyses

Disease development and progression are characterized by frequent genetic and epigenetic aberrations including chromosomal rearrangements, copy number gains and losses and DNA methylation. Advances in high-throughput, genome-wide profiling technologies, such as microarrays, have significantly improved our ability to identify and detect these specific alterations. However as technology continues to improve, a limiting factor remains sample quality and availability. Furthermore, follow-up clinical information and disease outcome are often collected years after the initial specimen collection. Specimens, typically formalin-fixed and paraffin embedded (FFPE), are stored in hospital archives for years to decades. DNA can be efficiently and effectively recovered from paraffin-embedded specimens if the appropriate method of extraction is applied. High quality DNA extracted from properly preserved and stored specimens can support quantitative assays for comparisons of normal and diseased tissues and generation of genetic and epigenetic signatures 1. To extract DNA from paraffin-embedded samples, tissue cores or microdissected tissue are subjected to xylene treatment, which dissolves the paraffin from the tissue, and then rehydrated using a series of ethanol washes. Proteins and harmful enzymes such as nucleases are subsequently digested by proteinase K. The addition of lysis buffer, which contains denaturing agents such as sodium dodecyl sulfate (SDS), facilitates digestion 2. Nucleic acids are purified from the tissue lysate using buffer-saturated phenol and high speed centrifugation which generates a biphasic solution. DNA and RNA remain in the upper aqueous phase, while proteins, lipids and polysaccharides are sequestered in the inter- and organic-phases respectively. Retention of the aqueous phase and repeated phenol extractions generates a clean sample. Following phenol extractions, RNase A is added to eliminate contaminating RNA. Additional phenol extractions following incubation with RNase A are used to remove any remaining enzyme. The addition of sodium acetate and isopropanol precipitates DNA, and high speed centrifugation is used to pellet the DNA and facilitate isopropanol removal. Excess salts carried over from precipitation can interfere with subsequent enzymatic assays, but can be removed from the DNA by washing with 70% ethanol, followed by centrifugation to re-pellet the DNA 3. DNA is re-suspended in distilled water or the buffer of choice, quantified and stored at -20°C. Purified DNA can subsequently be used in downstream applications which include, but are not limited to, PCR, array comparative genomic hybridization 4 (array CGH), methylated DNA Immunoprecipitation (MeDIP) and sequencing, allowing for an integrative analysis of tissue/tumor samples.

Divergent Genomic and Epigenomic Landscapes of Lung Cancer Subtypes Underscore the Selection of Different Oncogenic Pathways during Tumor Development

For therapeutic purposes, non-small cell lung cancer (NSCLC) has traditionally been regarded as a single disease. However, recent evidence suggest that the two major subtypes of NSCLC, adenocarcinoma (AC) and squamous cell carcinoma (SqCC) respond differently to both molecular targeted and new generation chemotherapies. Therefore, identifying the molecular differences between these tumor types may impact novel treatment strategy. We performed the first large-scale analysis of 261 primary NSCLC tumors (169 AC and 92 SqCC), integrating genome-wide DNA copy number, methylation and gene expression profiles to identify subtype-specific molecular alterations relevant to new agent design and choice of therapy. Comparison of AC and SqCC genomic and epigenomic landscapes revealed 778 altered genes with corresponding expression changes that are selected during tumor development in a subtype-specific manner. Analysis of >200 additional NSCLCs confirmed that these genes are responsible for driving the differential development and resulting phenotypes of AC and SqCC. Importantly, we identified key oncogenic pathways disrupted in each subtype that likely serve as the basis for their differential tumor biology and clinical outcomes. Downregulation of HNF4α target genes was the most common pathway specific to AC, while SqCC demonstrated disruption of numerous histone modifying enzymes as well as the transcription factor E2F1. In silico screening of candidate therapeutic compounds using subtype-specific pathway components identified HDAC and PI3K inhibitors as potential treatments tailored to lung SqCC. Together, our findings suggest that AC and SqCC develop through distinct pathogenetic pathways that have significant implication in our approach to the clinical management of NSCLC.

Unique somatic and malignant expression patterns implicate PIWI-interacting RNAs in cancer-type specific biology

Human PIWI-interacting RNAs (piRNAs) are known to be expressed in germline cells, functionally silencing LINEs and SINEs. Their expression patterns in somatic tissues are largely uncharted. We analyzed 6,260 human piRNA transcriptomes derived from non-malignant and tumour tissues from 11 organs. We discovered that only 273 of the 20,831 known piRNAs are expressed in somatic non-malignant tissues. However, expression patterns of these piRNAs were able to distinguish tissue-of-origin. A total of 522 piRNAs are expressed in corresponding tumour tissues, largely distinguishing tumour from non-malignant tissues in a cancer-type specific manner. Most expressed piRNAs mapped to known transcripts, contrary to “piRNA clusters” reported in germline cells. We showed that piRNA expression can delineate clinical features, such as histological subgroups, disease stages, and survival. PiRNAs common to many cancer types might represent a core gene-set that facilitates cancer growth, while piRNAs unique to individual cancer types likely contribute to cancer-specific biology.

Genetic Disruption of KEAP1/CUL3 E3 Ubiquitin Ligase Complex Components is a Key Mechanism of NF-KappaB Pathway Activation in Lung Cancer

Introduction: Inhibitor of kappa light polypeptide gene enhancer in B-cells, kinase beta (IKBKB) (IKK-&bgr;/IKK-2), which activates NF-&kgr;B, is a substrate of the KEAP1-CUL3-RBX1 E3-ubiquitin ligase complex, implicating this complex in NF-&kgr;B pathway regulation. We investigated complex component gene disruption as a novel genetic mechanism of NF-&kgr;B activation in non-small cell lung cancer. Methods: A total of 644 tumor- and 90 cell-line genomes were analyzed for gene dosage status of the individual complex components and IKBKB. Gene expression of these genes and NF-&kgr;B target genes were analyzed in 48 tumors. IKBKB protein levels were assessed in tumors with and without complex or IKBKB genetic disruption. Complex component knockdown was performed to assess effects of the E3-ligase complex on IKBKB and NF-&kgr;B levels, and phenotypic importance of IKBKB expression was measured by pharmacological inhibition. Results: We observed strikingly frequent genetic disruption (42%) and aberrant expression (63%) of the E3-ligase complex and IKBKB in the samples examined. Although both adenocarcinomas and squamous cell carcinomas showed complex disruption, the patterns of gene disruption differed. IKBKB levels were elevated with complex disruption, knockdown of complex components increased activated forms of IKBKB and NF-&kgr;B proteins, and IKBKB inhibition detriments cell viability, highlighting the biological significance of complex disruption. NF-&kgr;B target genes were overexpressed in samples with complex disruption, further demonstrating the effect of complex disruption on NF-&kgr;B activity. Conclusions: Gene dosage alteration is a prominent mechanism that disrupts each component of the KEAP1-CUL3-RBX1 complex and its NF-&kgr;B stimulating substrate, IKBKB. Herein, we show that, multiple component disruption of this complex represents a novel mechanism of NF-&kgr;B activation in non-small cell lung cancer.

Mechanistic Roles of Noncoding RNAs in Lung Cancer Biology and Their Clinical Implications

Lung cancer biology has traditionally focused on genomic and epigenomic deregulation of protein-coding genes to identify oncogenes and tumor suppressors diagnostic and therapeutic targets. Another important layer of cancer biology has emerged in the form of noncoding RNAs (ncRNAs), which are major regulators of key cellular processes such as proliferation, RNA splicing, gene regulation, and apoptosis. In the past decade, microRNAs (miRNAs) have moved to the forefront of ncRNA cancer research, while the role of long noncoding RNAs (lncRNAs) is emerging. Here we review the mechanisms by which miRNAs and lncRNAs are deregulated in lung cancer, the technologies that can be applied to detect such alterations, and the clinical potential of these RNA species. An improved comprehension of lung cancer biology will come through the understanding of the interplay between deregulation of non-coding RNAs, the protein-coding genes they regulate, and how these interactions influence cellular networks and signalling pathways.

A sequence-based approach to identify reference genes for gene expression analysis

BackgroundAn important consideration when analyzing both microarray and quantitative PCR expression data is the selection of appropriate genes as endogenous controls or reference genes. This step is especially critical when identifying genes differentially expressed between datasets. Moreover, reference genes suitable in one context (e.g. lung cancer) may not be suitable in another (e.g. breast cancer). Currently, the main approach to identify reference genes involves the mining of expression microarray data for highly expressed and relatively constant transcripts across a sample set. A caveat here is the requirement for transcript normalization prior to analysis, and measurements obtained are relative, not absolute. Alternatively, as sequencing-based technologies provide digital quantitative output, absolute quantification ensues, and reference gene identification becomes more accurate.MethodsSerial analysis of gene expression (SAGE) profiles of non-malignant and malignant lung samples were compared using a permutation test to identify the most stably expressed genes across all samples. Subsequently, the specificity of the reference genes was evaluated across multiple tissue types, their constancy of expression was assessed using quantitative RT-PCR (qPCR), and their impact on differential expression analysis of microarray data was evaluated.ResultsWe show that (i) conventional references genes such as ACTB and GAPDH are highly variable between cancerous and non-cancerous samples, (ii) reference genes identified for lung cancer do not perform well for other cancer types (breast and brain), (iii) reference genes identified through SAGE show low variability using qPCR in a different cohort of samples, and (iv) normalization of a lung cancer gene expression microarray dataset with or without our reference genes, yields different results for differential gene expression and subsequent analyses. Specifically, key established pathways in lung cancer exhibit higher statistical significance using a dataset normalized with our reference genes relative to normalization without using our reference genes.ConclusionsOur analyses found NDUFA1, RPL19, RAB5C, and RPS18 to occupy the top ranking positions among 15 suitable reference genes optimal for normalization of lung tissue expression data. Significantly, the approach used in this study can be applied to data generated using new generation sequencing platforms for the identification of reference genes optimal within diverse contexts.

Methylation analysis by DNA immunoprecipitation.

DNA methylation regulates gene expression primarily through modification of chromatin structure. Global methylation studies have revealed biologically relevant patterns of DNA methylation in the human genome affecting sequences such as gene promoters, gene bodies, and repetitive elements. Disruption of normal methylation patterns and subsequent gene expression changes have been observed in several diseases especially in human cancers. Immunoprecipitation (IP)‐based methods to evaluate methylation status of DNA have been instrumental in such genome‐wide methylation studies. This review describes techniques commonly used to identify and quantify methylated DNA with emphasis on IP based platforms. In an effort to consolidate the wealth of information and highlight critical aspects of methylated DNA analysis, sample considerations, experimental and bioinformatic approaches for analyzing genome‐wide methylation profiles, and the benefit of integrating DNA methylation data with complementary dimensions of genomic data are discussed. J. Cell. Physiol. 222: 522–531, 2010.

Macrophages, Inflammation, and Lung Cancer

Lung cancer is the leading cause of cancer mortality worldwide, and at only 18%, it has one of the lowest 5-year survival rates of all malignancies. With its highly complex mutational landscape, treatment strategies against lung cancer have proved largely ineffective. However with the recent success of immunotherapy trials in lung cancer, there is renewed enthusiasm in targeting the immune component of tumors. Macrophages make up the majority of the immune infiltrate in tumors and are a key cell type linking inflammation and cancer. Although the mechanisms through which inflammation promotes cancer are not fully understood, two connected hypotheses have emerged: an intrinsic pathway, driven by genetic alterations that lead to neoplasia and inflammation, and an extrinsic pathway, driven by inflammatory conditions that increase cancer risk. Here, we discuss the contribution of macrophages to these pathways and subsequently their roles in established tumors. We highlight studies investigating the association of macrophages with lung cancer prognosis and discuss emerging therapeutic strategies for targeting macrophages in the tumor microenvironment.