Genome-wide combination profiling of copy number and methylation offers an approach for deciphering misregulation and development in cancer cells

Understanding the cellular roles of Fyn-related kinase (FRK): implications in cancer biology

The non-receptor tyrosine kinase Fyn-related kinase (FRK) is a member of the BRK family kinases (BFKs) and is distantly related to the Src family kinases (SFKs). FRK was first discovered in 1993, and studies pursued thereafter attributed a potential tumour-suppressive function to the enzyme. In recent years, however, further functional characterization of the tyrosine kinase in diverse cancer types suggests that FRK may potentially play an oncogenic role as well. Specifically, while ectopic expression of FRK suppresses cell proliferation and migration in breast and brain cancers, knockdown or catalytic inhibition of FRK suppresses these cellular processes in pancreatic and liver cancer. Such functional paradox is therefore evidently exhibited in a tissue-specific context. This review sheds light on the recent developments emerged from investigations on FRK which include: (a) a review of the expression pattern of the protein in mammalian cells/tissues, (b) underlying genomic perturbations and (c) a mechanistic function of the enzyme across different cellular environments. Given its functional heterogeneity observed across different cancers, we also discuss the therapeutic significance of FRK.

Genomic alterations on 8p21-p23 are the most frequent genetic events in stage I squamous cell carcinoma of the lung

Genetic alterations in the early stages of cancer have a close correlation with tumor initiation and potentially activate downstream pathways implicated in tumor progression; however, the method of initiation in sporadic neoplasias is largely unknown. In this study, whole-genome microarray-comparative genomic hybridization was performed to identify the early genetic alterations that define the prognosis of patients with stage I squamous cell carcinoma (SCC) of the lung. The most striking finding was the high frequency of copy number losses and hemizygous deletions on chromosome 8p, which occurred in 94.7% (18/19) and 63.2% (12/19) of the cases, respectively, with a delineated minimal common region of 8p21.1-p23.3. More specifically, three loci of homozygous deletions at 8p23.1 were noted in 21.1% (4/19) of the cases. This region contains the following possible target genes, which have previously not been implicated to play a pathogenic role in stage I SCCs: MSRA, MFHAS1, CLDN23, DEFB106A, DEFB105A, LOC441316, FAM90A7P and LOC441318. These findings indicate that genetic alterations on chromosome 8p may be the first step in the initiation of genomic instability in early SCCs, and the newly identified genes in the 8p23.1 chromosomal region might be of interest for the study of the pathophysiology of stage I SCC, as potential targets for therapeutic measures.

A Single-Array-Based Method for Detecting Copy Number Variants Using Affymetrix High Density SNP Arrays and its Application to Breast Cancer

Cumulative evidence has shown that structural variations, due to insertions, deletions, and inversions of DNA, may contribute considerably to the development of complex human diseases, such as breast cancer. High-throughput genotyping technologies, such as Affymetrix high density single-nucleotide polymorphism (SNP) arrays, have produced large amounts of genetic data for genome-wide SNP genotype calling and copy number estimation. Meanwhile, there is a great need for accurate and efficient statistical methods to detect copy number variants. In this article, we introduce a hidden-Markov-model (HMM)-based method, referred to as the PICR-CNV, for copy number inference. The proposed method first estimates copy number abundance for each single SNP on a single array based on the raw fluorescence values, and then standardizes the estimated copy number abundance to achieve equal footing among multiple arrays. This method requires no between-array normalization, and thus, maintains data integrity and independence of samples among individual subjects. In addition to our efforts to apply new statistical technology to raw fluorescence values, the HMM has been applied to the standardized copy number abundance in order to reduce experimental noise. Through simulations, we show our refined method is able to infer copy number variants accurately. Application of the proposed method to a breast cancer dataset helps to identify genomic regions significantly associated with the disease.

Genome-wide combination profiling of DNA copy number and methylation for deciphering biomarkers in non-small cell lung cancer patients

Early detection of lung cancer provides the highest potential for saving lives. To date, no routine screening method enabling early detection is available, which is a key factor in the disease's high mortality rate. Copy number changes and DNA methylation alterations are good indicators of carcinogenesis and cancer prognosis. In this study, we attempted to combine profiles of DNA copy number and methylation patterns in 20 paired cancerous and noncancerous tissue samples from non-small cell lung cancer (NSCLC) patients, and we detected several clinically important genes with genetic and epigenetic relationships. Using array comparative genomic hybridization (aCGH), statistically significant differences were observed across the histological subtypes for gains at 1p31.1, 3q26.1, and 3q26.31-3q29 as well as for losses at 1p21.1, 2q33.3, 2q37.3, 3p12.3, 4q35.2, and 13q34 in squamous cell carcinoma (SQ) patients, and losses at 12q24.33 were measured in adenocarcinoma (AD) patients (p < 0.05). In an analysis of DNA methylation at 1505 autosomal CpG loci that are associated with 807 cancer-related genes, we identified six and nine loci with higher and lower DNA methylation levels, respectively, in tumor tissue compared to non-tumor lung tissues from AD patients. In addition, three loci with higher and seven loci with lower DNA methylation levels were identified in tumor tissue from SQ patients compared to non-tumor lung tissue. Subsequently, we searched for regions exhibiting concomitant hypermethylation and genomic loss in both ADs and SQs. One clone representing 7p15.2 (which includes candidate genes such as HOXA9 and HOXA11) and one target ID representing HOXA9_E252_R were detected. Quantitative real-time PCR identified the potential candidate gene HOXA9 as being down-regulated in the majority of NSCLC patients. Moreover, following HOXA9 over-expression, the invasion of representative cell lines, A549 and HCC95, were significantly inhibited. Taken together, our results show that the combined profiling analysis technique is a useful tool for identifying biomarkers in lung cancer and that HOXA9 might be a potential candidate gene for the pathogenesis and diagnosis of NSCLC patients.

Genetic and epigenetic somatic alterations in head and neck squamous cell carcinomas are globally coordinated but not locally targeted

Background

Solid tumors, including head and neck squamous cell carcinomas (HNSCC), arise as a result of genetic and epigenetic alterations in a sustained stress environment. Little work has been done that simultaneously examines the spectrum of both types of changes in human tumors on a genome-wide scale and results so far have been limited and mixed. Since it has been hypothesized that epigenetic alterations may act by providing the second carcinogenic hit in gene silencing, we sought to identify genome-wide DNA copy number alterations and CpG dinucleotide methylation events and examine the global/local relationships between these types of alterations in HNSCC.

Methodology/Principal Findings

We have extended a prior analysis of 1,413 cancer-associated loci for epigenetic changes in HNSCC by integrating DNA copy number alterations, measured at 500,000 polymorphic loci, in a case series of 19 primary HNSCC tumors. We have previously demonstrated that local copy number does not bias methylation measurements in this array platform. Importantly, we found that the global pattern of copy number alterations in these tumors was significantly associated with tumor methylation profiles (p<0.002). However at the local level, gene promoter regions did not exhibit a correlation between copy number and methylation (lowest q = 0.3), and the spectrum of genes affected by each type of alteration was unique.

Conclusion/Significance

This work, using a novel and robust statistical approach demonstrates that, although a “second hit” mechanism is not likely the predominant mode of action for epigenetic dysregulation in cancer, the patterns of methylation events are associated with the patterns of allele loss. Our work further highlights the utility of integrative genomics approaches in exploring the driving somatic alterations in solid tumors.

Identification of novel candidate target genes, including EPHB3, MASP1 and SST at 3q26.2-q29 in squamous cell carcinoma of the lung

Background

The underlying genetic alterations for squamous cell carcinoma (SCC) and adenocarcinoma (AC) carcinogenesis are largely unknown.

Methods

High-resolution array- CGH was performed to identify the differences in the patterns of genomic imbalances between SCC and AC of non-small cell lung cancer (NSCLC).

Results

On a genome-wide profile, SCCs showed higher frequency of gains than ACs (p = 0.067). More specifically, statistically significant differences were observed across the histologic subtypes for gains at 2q14.2, 3q26.2–q29, 12p13.2–p13.33, and 19p13.3, as well as losses at 3p26.2–p26.3, 16p13.11, and 17p11.2 in SCC, and gains at 7q22.1 and losses at 15q22.2–q25.2 occurred in AC (P < 0.05). The most striking difference between SCC and AC was gains at the 3q26.2–q29, occurring in 86% (19/22) of SCCs, but in only 21% (3/14) of ACs. Many significant genes at the 3q26.2–q29 regions previously linked to a specific histology, such as EVI1,MDS1, PIK3CA and TP73L, were observed in SCC (P < 0.05). In addition, we identified the following possible target genes (> 30% of patients) at 3q26.2–q29: LOC389174 (3q26.2),KCNMB3 (3q26.32),EPHB3 (3q27.1), MASP1 and SST (3q27.3), LPP and FGF12 (3q28), and OPA1,KIAA022,LOC220729, LOC440996,LOC440997, and LOC440998 (3q29), all of which were significantly targeted in SCC (P < 0.05). Among these same genes, high-level amplifications were detected for the gene, EPHB3, at 3q27.1, and MASP1 and SST, at 3q27.3 (18, 18, and 14%, respectively). Quantitative real time PCR demonstrated array CGH detected potential candidate genes that were over expressed in SCCs.

Conclusion

Using whole-genome array CGH, we have successfully identified significant differences and unique information of chromosomal signatures prevalent between the SCC and AC subtypes of NSCLC. The newly identified candidate target genes may prove to be highly attractive candidate molecular markers for the classification of NSCLC histologic subtypes, and could potentially contribute to the pathogenesis of the squamous cell carcinoma of the lung.