Integrative analysis of DNA copy number and gene expression in metastatic oral squamous cell carcinoma identifies genes associated with poor survival

Whole-exome sequencing identifies cancer-associated variants of the endo-lysosomal ion transport channels in the Saudi population

Background

Although national efforts are underway to document the genomic variability of the Saudi population relative to other populations, such variability remains largely unexplored. Genetic variability is known to impact the fate of cells and increase or decrease the risk of a variety of complex diseases including cancer forms. Therefore, the identification of variants associated with cancer susceptibility in Saudi population may protect individuals from cancer or aid in patient-tailored therapies. The endo-lysosomal ion transport genes responsible for cationic ion homeostasis within the cell. We screened 703 single-nucleotide polymorphisms (SNPs) of the endo-lysosomal ion transporter genes in the Saudi population and identified cancer-associated variants that have been reported in other populations.

Methods

Utilizing previously derived local data of Whole-Exome Sequencing (WES), we examined SNPs of TPCN1, TPCN2, P2RX4, TRPM7, TRPV4, TRPV4, and TRPV6 genes. The SNPs were identified for those genes by our in-house database. We predicted the pathogenicity of these variants using in silico tools CADD, Polyphen-2, SIFT, PrimateAI, and FATHMM-XF. Then, we validated our findings by exploring the genetics database (VarSome, dbSNP NCB, OMIM, ClinVar, Ensembl, and GWAS Catalog) to further link cancer risk.

Results

The WES database yielded 703 SNPs found in TPCN2, P2RX4, TRPM7, TRPV4, and TRPV6 genes in 1,144 subjects. The number of variants that were found to be common in our population was 150 SNPs. We identified 13 coding-region non-synonymous variants of the endo-lysosomal genes that were most common with a minor allele frequency (MAF) of ≥ 1 %. Twelve of these variants are rs2376558, rs3750965, rs61746574, rs35264875, rs3829241, rs72928978, rs25644, rs8042919, rs17881456, rs4987682, rs4987667, and rs4987657 that were classified as cancer-associated genes.

Conclusion

Our study highlighted cancer-associated SNPs in the endo-lysosomal genes among Saudi individuals. The allelic frequencies on polymorphic variants confer susceptibility to complex diseases that are comparable to other populations. There is currently insufficient clinical data supporting the link between these SNPs and cancer risk in the Saudi population. Our data argues for initiating future cohort studies in which individuals with the identified SNPs are monitored and assessed for their likelihood of developing malignancies and therapy outcomes.

Gene dosage compensation: Origins, criteria to identify compensated genes, and mechanisms including sensor loops as an emerging systems-level property in cancer

The gene dosage compensation hypothesis presents a mechanism through which the expression of certain genes is modulated to compensate for differences in the dose of genes when additional chromosomes are present. It is one of the means through which cancer cells actively cope with the potential damaging effects of aneuploidy, a hallmark of most cancers. Dosage compensation arises through several processes, including downregulation or overexpression of specific genes and the relocation of dosage-sensitive genes. In cancer, a majority of compensated genes are generally thought to be regulated at the translational or post-translational level, and include the basic components of a compensation loop, including sensors of gene dosage and modulators of gene expression. Post-translational regulation is mostly undertaken by a general degradation or aggregation of remaining protein subunits of macromolecular complexes. An increasingly important role has also been observed for transcriptional level regulation. This article reviews the process of targeted gene dosage compensation in cancer and other biological conditions, along with the mechanisms by which cells regulate specific genes to restore cellular homeostasis. These mechanisms represent potential targets for the inhibition of dosage compensation of specific genes in aneuploid cancers. This article critically examines the process of targeted gene dosage compensation in cancer and other biological contexts, alongside the criteria for identifying genes subject to dosage compensation and the intricate mechanisms by which cells orchestrate the regulation of specific genes to reinstate cellular homeostasis. Ultimately, our aim is to gain a comprehensive understanding of the intricate nature of a systems-level property. This property hinges upon the kinetic parameters of regulatory motifs, which we have termed "gene dosage sensor loops." These loops have the potential to operate at both the transcriptional and translational levels, thus emerging as promising candidates for the inhibition of dosage compensation in specific genes. Additionally, they represent novel and highly specific therapeutic targets in the context of aneuploid cancer.

Mitochondrial DNA content as a biomarker for oral carcinogenesis: correlation with clinicopathologic parameters

BACKGROUND

Mitochondrial genome (mtDNA) exhibits greater vulnerability to mutations and/or copy number variations than nuclear counterpart (nDNA) in both normal and cancer cells due to oxidative stress generated by inflammation, viral infections, physical, mechanical, and chemical load. The study was designed to evaluate the mtDNA content in oral potentially malignant disorders (OPMDs) and oral squamous cell carcinoma (OSCC). Various parameters were analyzed including its variation with human papillomavirus (HPV) during oral carcinogenesis.

METHODS

The present cross-sectional study comprised of two hundred patients (100 OPMDs and 100 OSCCs) and 100 healthy controls. PCR amplifications were done for mtDNA content and HPV in OPMDs and OSCC using real-time and conventional PCR respectively.

RESULTS

The relative mtDNA content was assessed quantitatively and it was observed that mtDNA was greater in OSCC (7.60±0.94) followed by OPMDs (5.93±0.92) and controls (5.37±0.95). It showed a positive linear correlation with habits and increasing histopathological grades. Total HPV-positive study groups showed higher mtDNA content (7.06±1.64) than HPV-negative counterparts (6.21±1.29).

CONCLUSIONS

An elevated mutant mtDNA may be attributed to increased free radicals and selective cell clonal proliferation in test groups. Moreover, sustained HPV infection enhances tumorigenesis through mitochondria mediated apoptosis. Since, mtDNA content is directly linked to oxidative DNA damage, these quantifications might serve as a surrogate measure for invasiveness in dysplastic lesions and typify their malignant potential.

Liprin-α1 Expression in Tumor-Infiltrating Lymphocytes Associates with Improved Survival in Patients with HPV-Positive Oropharyngeal Squamous Cell Carcinoma

BACKGROUND

Liprin-α1 is a scaffold protein involved in cell adhesion, motility, and invasion in malignancies. Liprin-α1 inhibits the expression of metastatic suppressor CD82 in cancers such as oral carcinoma, and the expression of these proteins has been known to correlate negatively. The role of these proteins has not been previously studied in human papillomavirus (HPV)-related head and neck cancers. Our aim was to assess the clinical and prognostic role of liprin-α1 and CD82 in HPV-positive oropharyngeal squamous cell carcinoma (OPSCC) in comparison to HPV-negative OPSCC.

METHODS

The data included 139 OPSCC patients treated at the Helsinki University Hospital (HUS) during 2012-2016. Immunohistochemistry was utilized in HPV determination and in biomarker assays. Overall survival (OS) was used in the survival analysis.

RESULTS

Stronger expression of liprin-α1 in tumor-infiltrating lymphocytes (TILs) was linked to lower cancer stage (p < 0.001) and HPV positivity (p < 0.001). Additionally, we found an association between elevated expression of liprin-α1 and weak expression of CD82 in tumor cells (p = 0.029). In survival analysis, we found significant correlation between favorable OS and stronger expression of liprin-α1 in TILs among the whole patient cohort (p < 0.001) and among HPV-positive patients (p = 0.042).

CONCLUSIONS

Increased liprin-α1 expression in the TILs is associated with favorable prognosis in OPSCC, especially among HPV-positive patients.

The Structural Dynamics, Complexity of Interactions, and Functions in Cancer of Multi-SAM Containing Proteins

SAM domains are crucial mediators of diverse interactions, including those important for tumorigenesis or metastasis of cancers, and thus SAM domains can be attractive targets for developing cancer therapies. This review aims to explore the literature, especially on the recent findings of the structural dynamics, regulation, and functions of SAM domains in proteins containing more than one SAM (multi-SAM containing proteins, MSCPs). The topics here include how intrinsic disorder of some SAMs and an additional SAM domain in MSCPs increase the complexity of their interactions and oligomerization arrangements. Many similarities exist among these MSCPs, including their effects on cancer cell adhesion, migration, and metastasis. In addition, they are all involved in some types of receptor-mediated signaling and neurology-related functions or diseases, although the specific receptors and functions vary. This review also provides a simple outline of methods for studying protein domains, which may help non-structural biologists to reach out and build new collaborations to study their favorite protein domains/regions. Overall, this review aims to provide representative examples of various scenarios that may provide clues to better understand the roles of SAM domains and MSCPs in cancer in general.

MYC dosage compensation is mediated by miRNA-transcription factor interactions in aneuploid cancer

We hypothesize that dosage compensation of critical genes arises from systems-level properties for cancer cells to withstand the negative effects of aneuploidy. We identified several candidate genes in cancer multiomics data and developed a biocomputational platform to construct a mathematical model of their interaction network with micro-RNAs and transcription factors, where the property of dosage compensation emerged for MYC and was dependent on the kinetic parameters of its feedback interactions with three micro-RNAs. These circuits were experimentally validated using a genetic tug-of-war technique to overexpress an exogenous MYC, leading to overexpression of the three microRNAs involved and downregulation of endogenous MYC. In addition, MYC overexpression or inhibition of its compensating miRNAs led to dosage-dependent cytotoxicity in MYC-amplified colon cancer cells. Finally, we identified negative correlation of MYC dosage compensation with patient survival in TCGA breast cancer patients, highlighting the potential of this mechanism to prevent aneuploid cancer progression.

Liprins in oncogenic signaling and cancer cell adhesion

Liprins are a multifunctional family of scaffold proteins, identified by their involvement in several important neuronal functions related to signaling and organization of synaptic structures. More recently, the knowledge on the liprin family has expanded from neuronal functions to processes relevant to cancer progression, including cell adhesion, cell motility, cancer cell invasion, and signaling. These proteins consist of regions, which by prediction are intrinsically disordered, and may be involved in the assembly of supramolecular structures relevant for their functions. This review summarizes the current understanding of the functions of liprins in different cellular processes, with special emphasis on liprins in tumor progression. The available data indicate that liprins may be potential biomarkers for cancer progression and may have therapeutic importance.

Pan-cancer evaluation of gene expression and somatic alteration data for cancer prognosis prediction

BACKGROUND

Over the past decades, approaches for diagnosing and treating cancer have seen significant improvement. However, the variability of patient and tumor characteristics has limited progress on methods for prognosis prediction. The development of high-throughput omics technologies now provides multiple approaches for characterizing tumors. Although a large number of published studies have focused on integration of multi-omics data and use of pathway-level models for cancer prognosis prediction, there still exists a gap of knowledge regarding the prognostic landscape across multi-omics data for multiple cancer types using both gene-level and pathway-level predictors.

METHODS

In this study, we systematically evaluated three often available types of omics data (gene expression, copy number variation and somatic point mutation) covering both DNA-level and RNA-level features. We evaluated the landscape of predictive performance of these three omics modalities for 33 cancer types in the TCGA using a Lasso or Group Lasso-penalized Cox model and either gene or pathway level predictors.

RESULTS

We constructed the prognostic landscape using three types of omics data for 33 cancer types on both the gene and pathway levels. Based on this landscape, we found that predictive performance is cancer type dependent and we also highlighted the cancer types and omics modalities that support the most accurate prognostic models. In general, models estimated on gene expression data provide the best predictive performance on either gene or pathway level and adding copy number variation or somatic point mutation data to gene expression data does not improve predictive performance, with some exceptional cohorts including low grade glioma and thyroid cancer. In general, pathway-level models have better interpretative performance, higher stability and smaller model size across multiple cancer types and omics data types relative to gene-level models.

CONCLUSIONS

Based on this landscape and comprehensively comparison, models estimated on gene expression data provide the best predictive performance on either gene or pathway level. Pathway-level models have better interpretative performance, higher stability and smaller model size relative to gene-level models.

Sjögren syndrome/scleroderma autoantigen 1 is a direct Tankyrase binding partner in cancer cells

Sjögren syndrome/scleroderma autoantigen 1 (SSSCA1) was first described as an auto-antigen over-expressed in Sjögren’s syndrome and in scleroderma patients. SSSCA1 has been linked to mitosis and centromere association and as a potential marker candidate in diverse solid cancers. Here we characterize SSSCA1 for the first time, to our knowledge, at the molecular, structural and subcellular level. We have determined the crystal structure of a zinc finger fold, a zinc ribbon domain type 2 (ZNRD2), at 2.3 Å resolution. We show that the C-terminal domain serves a dual function as it both behaves as the interaction site to Tankyrase 1 (TNKS1) and as a nuclear export signal. We identify TNKS1 as a direct binding partner of SSSCA1, map the binding site to TNKS1 ankyrin repeat cluster 2 (ARC2) and thus define a new binding sequence. We experimentally verify and map a new nuclear export signal sequence in SSSCA1.

Perdreau-Dahl et al. systematically characterise Sjögren syndrome/scleroderma autoantigen 1 at the molecular, structural and subcellular level. They show that the C-terminal domain serves a dual function as it both behaves as the interaction site to Tankyrase 1 and as a nuclear export signal.

Aneuploidy and gene expression: is there dosage compensation?

Aneuploidy (i.e., abnormal chromosome number) is the leading cause of miscarriage and congenital defects in humans. Moreover, aneuploidy is ubiquitous in cancer. The deleterious phenotypes associated with aneuploidy are likely a result of the imbalance in the levels of gene products derived from the additional chromosome(s). Here, we summarize the current knowledge on how the presence of extra chromosomes impacts gene expression. We describe studies that have found a strict correlation between gene dosage and transcript levels as wells as studies that have found a less stringent correlation, hinting at the possible existence of dosage compensation mechanisms. We conclude by peering into the epigenetic changes found in aneuploid cells and outlining current knowledge gaps and potential areas of future investigation.

Identification of Cancer Dysfunctional Subpathways by Integrating DNA Methylation, Copy Number Variation, and Gene-Expression Data

A subpathway is defined as the local region of a biological pathway with specific biological functions. With the generation of large-scale sequencing data, there are more opportunities to study the molecular mechanisms of cancer development. It is necessary to investigate the potential impact of DNA methylation, copy number variation (CNV), and gene-expression changes in the molecular states of oncogenic dysfunctional subpathways. We propose a novel method, Identification of Cancer Dysfunctional Subpathways (ICDS), by integrating multi-omics data and pathway topological information to identify dysfunctional subpathways. We first calculated gene-risk scores by integrating the three following types of data: DNA methylation, CNV, and gene expression. Second, we performed a greedy search algorithm to identify the key dysfunctional subpathways within pathways for which the discriminative scores were locally maximal. Finally, a permutation test was used to calculate the statistical significance level for these key dysfunctional subpathways. We validated the effectiveness of ICDS in identifying dysregulated subpathways using datasets from liver hepatocellular carcinoma (LIHC), head-neck squamous cell carcinoma (HNSC), cervical squamous cell carcinoma, and endocervical adenocarcinoma. We further compared ICDS with methods that performed the same subpathway identification algorithm but only considered DNA methylation, CNV, or gene expression (defined as ICDS_M, ICDS_CNV, or ICDS_G, respectively). With these analyses, we confirmed that ICDS better identified cancer-associated subpathways than the three other methods, which only considered one type of data. Our ICDS method has been implemented as a freely available R-based tool (https://cran.r-project.org/web/packages/ICDS).

Transcriptional Aneuploidy Responses of Brassica rapa-oleracea Monosomic Alien Addition Lines (MAALs) Derived From Natural Allopolyploid B. napus

Establishing the whole set of aneuploids, for one naturally evolved allopolyploid species, provides a unique opportunity to elucidate the transcriptomic response of the constituent subgenomes to serial aneuploidy. Previously, the whole set of monosomic alien addition lines (MAALs, C1-C9) with each of the nine C subgenome chromosomes, added to the extracted A subgenome, was developed in the context of the allotetraploid Brassica napus donor “Oro,” after the restitution of the ancestral B. rapa (RBR Oro) was realized. Herein, transcriptomic analysis using high-throughput technology was conducted to detect gene expression alterations in these MAALs and RBR. Compared to diploid RBR, the genes of all of the MAALs showed various degrees of dysregulated expressions that resulted from cis effects and more prevailing trans effects. In addition, the trans-effect on gene expression in MAALs increased with higher levels of homology between the recipient A subgenome and additional C subgenome chromosomes, instead of gene numbers of extra chromosomes. A total of 10 trans-effect dysregulated genes, among all pairwise comparisons, were mainly involved in the function of transporter activity. Furthermore, highly expressed genes were more prone to downregulation and vice-versa, suggesting a common trend for transcriptional pattern responses to aneuploidy. These results provided a comprehensive insight of the impact of gene expression of individual chromosomes, in one subgenome, on another intact subgenome for one allopolyploid with a long evolutionary history.

Liprin-α1 modulates cancer cell signaling by transmembrane protein CD82 in adhesive membrane domains linked to cytoskeleton

Background

PPFIA1 is located at the 11q13 region commonly amplified in cancer. The protein liprin-α1 encoded by PPF1A1 contributes to the adhesive and invasive structures of cytoskeletal elements and is located at the invadosomes in cancer cells. However, the precise mechanism of liprin-α1 function in cancer progression has remained elusive.

Methods

Invasion regulating activity of liprin-α1 was examined by analyzing the functions of squamous cell carcinoma of head and neck (HNSCC) cell lines in three-dimensional collagen I after RNAi mediated gene knockdown. Transcriptome profiling and Gene Set Enrichment Analysis from HNSCC and breast cancer cells were used to identify expression changes relevant to specific cellular localizations, biological processes and signaling pathways after PPFIA1 knockdown. The significance of the results was assessed by relevant statistical methods (Wald and Benjamini-Hochberg). Localization of proteins associated to liprin-α1 was studied by immunofluorescence in 2D and 3D conditions. The association of PPFIA1 amplification to HNSCC patient survival was explored using The Cancer Genome Atlas data.

Results

In this study, we show that liprin-α1 regulates biological processes related to membrane microdomains in breast carcinoma, as well as protein trafficking, cell-cell and cell-substrate contacts in HNSCC cell lines cultured in three-dimensional matrix. Importantly, we show that in all these cancer cells liprin-α1 knockdown leads to the upregulation of transmembrane protein CD82, which is a suppressor of metastasis in several solid tumors.

Conclusions

Our results provide novel information regarding the function of liprin-α1 in biological processes essential in cancer progression. The results reveal liprin-α1 as a novel regulator of CD82, linking liprin-α1 to the cancer cell invasion and metastasis pathways.

Electronic supplementary material

The online version of this article (10.1186/s12964-018-0253-y) contains supplementary material, which is available to authorized users.

Two-pore channels and disease

Two-pore channels (TPCs) are Ca²⁺-permeable endo-lysosomal ion channels subject to multi-modal regulation. They mediate their physiological effects through releasing Ca²⁺ from acidic organelles in response to cues such as the second messenger, NAADP. Here, we review emerging evidence linking TPCs to disease. We discuss how perturbing both local and global Ca²⁺ changes mediated by TPCs through chemical and/or molecular manipulations can induce or reverse disease phenotypes. We cover evidence from models of Parkinson's disease, non-alcoholic fatty liver disease, Ebola infection, cancer, cardiac dysfunction and diabetes. A need for more drugs targeting TPCs is identified.

Integrated miRNA-mRNA spatial signature for oral squamous cell carcinoma: a prospective profiling study of Narrow Band Imaging guided resection

Oral squamous cell carcinoma (OSCC) is a common malignancy for which there is poor prognosis and limited therapeutic options. The objective was to identify mRNA targets of dysregulated miRNAs in OSCC using integrated analysis and understand molecular abnormality in surgical margins. We used biopsies along the spatial axis from normal tissue defined by narrow band imaging (NBI) through conventional white light (WL) margins to tumour from 18 patients undergoing surgical resection for OSCC. Overall 119 miRNA and 4794 mRNA were differentially expressed along the adjacent normal tissue to tumour axis. Analysis of miRNA profiles demonstrated the NBI margins were molecularly distinct from both the tumour and WL margin. Integrated analysis identified 193 miRNA-mRNA interactions correlated to the spatial axis of NBI-WL-T. We used cross-validation analysis to derive a spatial interactome signature of OSCC comprising 100 putative miRNA-mRNA interactions between 40 miRNA and 96 mRNA. Bioinformatic analysis suggests that miRNA dysregulation in OSCC may contribute to activation of the oncostatin M, BDNF and TGF-β pathways. Our data demonstrates that surgical margins defined by NBI leave less potentially malignant residual tissue. The miRNA-mRNA interactome provides insight into dysregulated miRNA signalling in OSCC and supports molecular definition of tumour margins.

Assisted clustering of gene expression data using ANCut

BACKGROUND

In biomedical research, gene expression profiling studies have been extensively conducted. The analysis of gene expression data has led to a deeper understanding of human genetics as well as practically useful models. Clustering analysis has been a critical component of gene expression data analysis and can reveal the (previously unknown) interconnections among genes. With the high dimensionality of gene expression data, many of the existing clustering methods and results are not as satisfactory. Intuitively, this is caused by "a lack of information". In recent profiling studies, a prominent trend is to collect data on gene expressions as well as their regulators (copy number alteration, microRNA, methylation, etc.) on the same subjects, making it possible to borrow information from other types of omics measurements in gene expression analysis.

METHODS

In this study, an ANCut approach is developed, which is built on the regularized estimation and NCut techniques. An effective R code that implements this approach is developed.

RESULTS

Simulation shows that the proposed approach outperforms direct competitors. The analysis of TCGA (The Cancer Genome Atlas) data further demonstrates its satisfactory performance.

CONCLUSIONS

We propose a more effective clustering analysis of gene expression data, with the assistance of information from regulators. It provides a new venue for analyzing gene expression data based on the assisted analysis strategy.

In silico analysis of pathways activation landscape in oral squamous cell carcinoma and oral leukoplakia

A subset of patients with oral squamous cell carcinoma (OSCC), the most common subtype of head and neck squamous cell carcinoma (HNSCC), harbor dysplastic lesions (often visually identified as leukoplakia) prior to cancer diagnosis. Although evidence suggest that leukoplakia represents an initial step in the progression to cancer, signaling networks driving this progression are poorly understood. Here, we applied in silico Pathway Activation Network Decomposition Analysis (iPANDA), a new bioinformatics software suite for qualitative analysis of intracellular signaling pathway activation using transcriptomic data, to assess a network of molecular signaling in OSCC and pre-neoplastic oral lesions. In tumor samples, our analysis detected major conserved mitogenic and survival signaling pathways strongly associated with HNSCC, suggesting that some of the pathways identified by our algorithm, but not yet validated as HNSCC related, may be attractive targets for future research. While pathways activation landscape in the majority of leukoplakias was different from that seen in OSCC, a subset of pre-neoplastic lesions has demonstrated some degree of similarity to the signaling profile seen in tumors, including dysregulation of the cancer-driving pathways related to survival and apoptosis. These results suggest that dysregulation of these signaling networks may be the driving force behind the early stages of OSCC tumorigenesis. While future studies with larger leukoplakia data sets are warranted to further estimate the values of this approach for capturing signaling features that characterize relevant lesions that actually progress to cancers, our platform proposes a promising new approach for detecting cancer-promoting pathways and tailoring the right therapy to prevent tumorigenesis.

Genome wide profiling in oral squamous cell carcinoma identifies a four genetic marker signature of prognostic significance

BACKGROUND

Cancers of the oral cavity are primarily oral squamous cell carcinomas (OSCCs). Many of the OSCCs present at late stages with an exceptionally poor prognosis. A probable limitation in management of patients with OSCC lies in the insufficient knowledge pertaining to the linkage between copy number alterations in OSCC and oral tumourigenesis thereby resulting in an inability to deliver targeted therapy.

OBJECTIVES

The current study aimed to identify copy number alterations (CNAs) in OSCC using array comparative genomic hybridization (array CGH) and to correlate the CNAs with clinico-pathologic parameters and clinical outcomes.

MATERIALS AND METHODS

Using array CGH, genome-wide profiling was performed on 75 OSCCs. Selected genes that were harboured in the frequently amplified and deleted regions were validated using quantitative polymerase chain reaction (qPCR). Thereafter, pathway and network functional analysis were carried out using Ingenuity Pathway Analysis (IPA) software.

RESULTS

Multiple chromosomal regions including 3q, 5p, 7p, 8q, 9p, 10p, 11q were frequently amplified, while 3p and 8p chromosomal regions were frequently deleted. These findings were in confirmation with our previous study using ultra-dense array CGH. In addition, amplification of 8q, 11q, 7p and 9p and deletion of 8p chromosomal regions showed a significant correlation with clinico-pathologic parameters such as the size of the tumour, metastatic lymph nodes and pathological staging. Co-amplification of 7p, 8q, 9p and 11q regions that harbored amplified genes namely CCND1, EGFR, TPM2 and LRP12 respectively, when combined, continues to be an independent prognostic factor in OSCC.

CONCLUSION

Amplification of 3q, 5p, 7p, 8q, 9p, 10p, 11q and deletion of 3p and 8p chromosomal regions were recurrent among OSCC patients. Co-alteration of 7p, 8q, 9p and 11q was found to be associated with clinico-pathologic parameters and poor survival. These regions contain genes that play critical roles in tumourigenesis pathways.

DNA copy number alterations, gene expression changes and disease-free survival in patients with colorectal cancer: a 10 year follow-up

BACKGROUND

DNA copy number alterations (CNAs) and gene expression changes have amply been encountered in colorectal cancers (CRCs), but the extent at which CNAs affect gene expression, as well as their relevance for tumor development, are still poorly defined. Here we aimed at assessing the clinical relevance of these parameters in a 10 year follow-up study.

METHODS

Tumors and normal adjacent colon mucosa, obtained at primary surgery from 21 CRC patients, were subjected to (i) high-resolution array CGH (a-CGH) for the detection of CNAs and (ii) microarray-based transcriptome profiling for the detection of gene expression (GE) changes. Correlations between these genomic and transcriptomic changes and their associations with clinical and histopathological parameters were assessed with the aim to identify molecular signatures associated with disease-free survival of the CRC patients during a 10 year follow-up.

RESULTS

DNA copy number gains were frequently detected in chromosomes 7, 8q, 13, 19, 20q and X, whereas DNA copy number losses were frequently detected in chromosomes 1p, 4, 8p, 15, 17p, 18, 19 and 22q. None of these alterations were observed in all samples. In addition, we found that 2,498 genes were up- and that 1,094 genes were down-regulated in the tumor samples compared to their corresponding normal mucosa (p < 0.01). The expression of 65 genes was found to be significantly associated with prognosis (p < 0.01). Specifically, we found that up-regulation of the IL17RA, IGF2BP2 and ABCC2 genes, and of genes acting in the mTOR and cytokine receptor pathways, were strongly associated with a poor survival. Subsequent integrated analyses revealed that increased expression levels of the MMP9, BMP7, UBE2C, I-CAM, NOTCH3, NOTCH1, PTGES2, HMGB1 and ERBB3 genes were associated with copy number gains, whereas decreased expression levels of the MUC1, E2F2, HRAS and SIRT3 genes were associated with copy number losses. Pathways related to cell cycle progression, eicosanoid metabolism, and TGF-β and apoptosis signaling, were found to be most significantly affected.

CONCLUSIONS

Our results suggest that CNAs in CRC tumor tissues are associated with concomitant changes in the expression of cancer-related genes. In other genes epigenetic mechanism may be at work. Up-regulation of the IL17RA, IGF2BP2 and ABCC2 genes, and of genes acting in the mTOR and cytokine receptor pathways, appear to be associated with a poor survival. These alterations may, in addition to Dukes' staging, be employed as new prognostic biomarkers for the prediction of clinical outcome in CRC patients.

A network medicine approach to build a comprehensive atlas for the prognosis of human cancer

The Cancer Genome Atlas project has generated multi-dimensional and highly integrated genomic data from a large number of patient samples with detailed clinical records across many cancer types, but it remains unclear how to best integrate the massive amount of genomic data into clinical practice. We report here our methodology to build a multi-dimensional subnetwork atlas for cancer prognosis to better investigate the potential impact of multiple genetic and epigenetic (gene expression, copy number variation, microRNA expression and DNA methylation) changes on the molecular states of networks that in turn affects complex cancer survivorship. We uncover an average of 38 novel subnetworks in the protein-protein interaction network that correlate with prognosis across four prominent cancer types. The clinical utility of these subnetwork biomarkers was further evaluated by prognostic impact evaluation, functional enrichment analysis, drug target annotation, tumor stratification and independent validation. Some pathways including the dynactin, cohesion and pyruvate dehydrogenase-related subnetworks are identified as promising new targets for therapy in specific cancer types. In conclusion, this integrative analysis of existing protein interactome and cancer genomics data allows us to systematically dissect the molecular mechanisms that underlie unexpected outcomes for cancer, which could be used to better understand and predict clinical outcomes, optimize treatment and to provide new opportunities for developing therapeutics related to the subnetworks identified.

Liprin-α1 is a regulator of vimentin intermediate filament network in the cancer cell adhesion machinery

PPFIA1 is located at the 11q13 region, which is one of the most commonly amplified regions in several epithelial cancers including head and neck squamous cell carcinoma and breast carcinoma. Considering the location of PPFIA1 in this amplicon, we examined whether protein encoded by PPFIA1, liprin-α1, possesses oncogenic properties in relevant carcinoma cell lines. Our results indicate that liprin-α1 localizes to different adhesion and cytoskeletal structures to regulate vimentin intermediate filament network, thereby altering the invasion and growth properties of the cancer cells. In non-invasive cells liprin-α1 promotes expansive growth behavior with limited invasive capacity, whereas in invasive cells liprin-α1 has significant impact on mesenchymal cancer cell invasion in three-dimensional collagen. Current results identify liprin-α1 as a novel regulator of the tumor cell intermediate filaments with differential oncogenic properties in actively proliferating or motile cells.

JAK kinase inhibition abrogates STAT3 activation and head and neck squamous cell carcinoma tumor growth

Aberrant activation of the Janus kinase (JAK)/signal transducer and activator of transcription (STAT) 3 has been implicated in cell proliferation and survival of many cancers including head and neck squamous cell carcinoma (HNSCC). AZD1480, an orally active pharmacologic inhibitor of JAK1/JAK2, has been tested in several cancer models. In the present study, the in vitro and in vivo effects of AZD1480 were evaluated in HNSCC preclinical models to test the potential use of JAK kinase inhibition for HNSCC therapy. AZD1480 treatment decreased HNSCC proliferation in HNSCC cell lines with half maximal effective concentration (EC₅₀) values ranging from 0.9 to 4 μM in conjunction with reduction of pSTAT3_Tyr705 expression. In vivo antitumor efficacy of AZD1480 was demonstrated in patient-derived xenograft (PDX) models derived from two independent HNSCC tumors. Oral administration of AZD1480 reduced tumor growth in conjunction with decreased pSTAT3_Tyr705 expression that was observed in both PDX models. These findings suggest that the JAK1/2 inhibitors abrogate STAT3 signaling and may be effective in HNSCC treatment approaches.

Functional kinomics identifies candidate therapeutic targets in head and neck cancer

PURPOSE

To identify novel therapeutic drug targets for p53-mutant head and neck squamous cell carcinoma (HNSCC).

EXPERIMENTAL DESIGN

RNAi kinome viability screens were performed on HNSCC cells, including autologous pairs from primary tumor and recurrent/metastatic lesions, and in parallel on murine squamous cell carcinoma (MSCC) cells derived from tumors of inbred mice bearing germline mutations in Trp53, and p53 regulatory genes: Atm, Prkdc, and p19(Arf). Cross-species analysis of cell lines stratified by p53 mutational status and metastatic phenotype was used to select 38 kinase targets. Both primary and secondary RNAi validation assays were performed on additional HNSCC cell lines to credential these kinase targets using multiple phenotypic endpoints. Kinase targets were also examined via chemical inhibition using a panel of kinase inhibitors. A preclinical study was conducted on the WEE1 kinase inhibitor, MK-1775.

RESULTS

Our functional kinomics approach identified novel survival kinases in HNSCC involved in G2-M cell-cycle checkpoint, SFK, PI3K, and FAK pathways. RNAi-mediated knockdown and chemical inhibition of the WEE1 kinase with a specific inhibitor, MK-1775, had a significant effect on both viability and apoptosis. Sensitivity to the MK-1775 kinase inhibitor is in part determined by p53 mutational status, and due to unscheduled mitotic entry. MK-1775 displays single-agent activity and potentiates the efficacy of cisplatin in a p53-mutant HNSCC xenograft model.

CONCLUSIONS

WEE1 kinase is a potential therapeutic drug target for HNSCC. This study supports the application of a functional kinomics strategy to identify novel therapeutic targets for cancer.

Consequences of Aneuploidy in Cancer: Transcriptome and Beyond

Cancer cells differ from normal healthy cells in multiple aspects ranging from altered cellular signaling through metabolic changes to aberrant chromosome content, so called aneuploidy. The large-scale changes in copy numbers of chromosomes or large chromosomal regions due to aneuploidy alter significantly the gene expression, as several hundreds of genes are gained or lost. Comparison of quantitative genome, transcriptome and proteome data enables dissection of the molecular causes that underlie the gene expression changes observed in cancer cells and provides a new perspective on the molecular consequences of aneuploidy. Here, we will map to what degree aneuploidy affects the expression of genes located on the affected chromosomes. We will also address the effects of aneuploidy on global gene expression in cancer cells as well as whether and how it may contribute to the physiology of cancer cells.

Potential therapeutic targets for oral cancer: ADM, TP53, EGFR, LYN, CTLA4, SKIL, CTGF, CD70

In India, oral cancer has consistently ranked among top three causes of cancer-related deaths, and it has emerged as a top cause for the cancer-related deaths among men. Lack of effective therapeutic options is one of the main challenges in clinical management of oral cancer patients. We interrogated large pool of samples from oral cancer gene expression studies to identify potential therapeutic targets that are involved in multiple cancer hallmark events. Therapeutic strategies directed towards such targets can be expected to effectively control cancer cells. Datasets from different gene expression studies were integrated by removing batch-effects and was used for downstream analyses, including differential expression analysis. Dependency network analysis was done to identify genes that undergo marked topological changes in oral cancer samples when compared with control samples. Causal reasoning analysis was carried out to identify significant hypotheses, which can explain gene expression profiles observed in oral cancer samples. Text-mining based approach was used to detect cancer hallmarks associated with genes significantly expressed in oral cancer. In all, 2365 genes were detected to be differentially expressed genes, which includes some of the highly differentially expressed genes like matrix metalloproteinases (MMP-1/3/10/13), chemokine (C-X-C motif) ligands (IL8, CXCL-10/-11), PTHLH, SERPINE1, NELL2, S100A7A, MAL, CRNN, TGM3, CLCA4, keratins (KRT-3/4/13/76/78), SERPINB11 and serine peptidase inhibitors (SPINK-5/7). XIST, TCEAL2, NRAS and FGFR2 are some of the important genes detected by dependency and causal network analysis. Literature mining analysis annotated 1014 genes, out of which 841 genes were statistically significantly annotated. The integration of output of various analyses, resulted in the list of potential therapeutic targets for oral cancer, which included targets such as ADM, TP53, EGFR, LYN, CTLA4, SKIL, CTGF and CD70.

Combining multidimensional genomic measurements for predicting cancer prognosis: observations from TCGA

With accumulating research on the interconnections among different types of genomic regulations, researchers have found that multidimensional genomic studies outperform one-dimensional studies in multiple aspects. Among many sources of multidimensional genomic data, The Cancer Genome Atlas (TCGA) provides the public with comprehensive profiling data on >30 cancer types, making it an ideal test bed for conducting and comparing different analyses. In this article, the analysis goal is to apply several existing methods and associate multidimensional genomic measurements with cancer outcomes in particular prognosis, with special focus on the predictive power of genomic signatures. We exploit clinical data and four types of genomic measurement including mRNA gene expression, DNA methylation, microRNA and copy number alterations for breast invasive carcinoma, glioblastoma multiforme, acute myeloid leukemia and lung squamous cell carcinoma collected by TCGA. To accommodate the high dimensionality, we extract important features using Principal Component Analysis, Partial Least Squares and Least Absolute Shrinkage and Selection Operator (Lasso), which are representative of dimension reduction and variable selection techniques and have been extensively adopted, and fit Cox survival models with combined important features. We calibrate the predictive power of each type of genomic measurement for the prognosis of four cancer types and find that the results vary across cancers. Our analysis also suggests that for most of the cancers in our study and the adopted methods, there is no substantial improvement in prediction when adding other genomic measurement after gene expression and clinical covariates have been included in the model. This is consistent with the findings that molecular features measured at the transcription level affect clinical outcomes more directly than those measured at the DNA/epigenetic level.

Integration of cancer genomics with treatment selection: from the genome to predictive biomarkers

The field of cancer genomics is rapidly advancing as new technology provides detailed genetic and epigenetic profiling of human cancers. The amount of new data available describing the genetic make-up of tumors is paralleled by rapid advances in drug discovery and molecular therapy currently under investigation to treat these diseases. This review summarizes the challenges and approaches associated with the integration of genomic data into the development of new biomarkers in the management of cancer.

Voting-based cancer module identification by combining topological and data-driven properties

Recently, computational approaches integrating copy number aberrations (CNAs) and gene expression (GE) have been extensively studied to identify cancer-related genes and pathways. In this work, we integrate these two data sets with protein-protein interaction (PPI) information to find cancer-related functional modules. To integrate CNA and GE data, we first built a gene-gene relationship network from a set of seed genes by enumerating all types of pairwise correlations, e.g. GE-GE, CNA-GE, and CNA-CNA, over multiple patients. Next, we propose a voting-based cancer module identification algorithm by combining topological and data-driven properties (VToD algorithm) by using the gene-gene relationship network as a source of data-driven information, and the PPI data as topological information. We applied the VToD algorithm to 266 glioblastoma multiforme (GBM) and 96 ovarian carcinoma (OVC) samples that have both expression and copy number measurements, and identified 22 GBM modules and 23 OVC modules. Among 22 GBM modules, 15, 12, and 20 modules were significantly enriched with cancer-related KEGG, BioCarta pathways, and GO terms, respectively. Among 23 OVC modules, 19, 18, and 23 modules were significantly enriched with cancer-related KEGG, BioCarta pathways, and GO terms, respectively. Similarly, we also observed that 9 and 2 GBM modules and 15 and 18 OVC modules were enriched with cancer gene census (CGC) and specific cancer driver genes, respectively. Our proposed module-detection algorithm significantly outperformed other existing methods in terms of both functional and cancer gene set enrichments. Most of the cancer-related pathways from both cancer data sets found in our algorithm contained more than two types of gene-gene relationships, showing strong positive correlations between the number of different types of relationship and CGC enrichment -values (0.64 for GBM and 0.49 for OVC). This study suggests that identified modules containing both expression changes and CNAs can explain cancer-related activities with greater insights.

Integrative genomics analysis identifies candidate drivers at 3q26-29 amplicon in squamous cell carcinoma of the lung

PURPOSE

Chromosome 3q26-29 is a critical region of genomic amplification in lung squamous cell carcinomas (SCC). Identification of candidate drivers in this region could help uncover new mechanisms in the pathogenesis and potentially new targets in SCC of the lung.

EXPERIMENTAL DESIGN

We conducted a meta-analysis of seven independent datasets containing a total of 593 human primary SCC samples to identify consensus candidate drivers in 3q26-29 amplicon. Through integrating protein-protein interaction network information, we further filtered for candidates that may function together in a network. Computationally predicted candidates were validated using RNA interference (RNAi) knockdown and cell viability assays. Clinical relevance of the experimentally supported drivers was evaluated in an independent cohort of 52 lung SCC patients using survival analysis.

RESULTS

The meta-analysis identified 20 consensus candidates, among which four (SENP2, DCUN1D1, DVL3, and UBXN7) are involved in a small protein-protein interaction network. Knocking down any of the four proteins led to cell growth inhibition of the 3q26-29-amplified SCC. Moreover, knocking down of SENP2 resulted in the most significant cell growth inhibition and downregulation of DCUN1D1 and DVL3. Importantly, a gene expression signature composed of SENP2, DCUN1D1, and DVL3 stratified patients into subgroups with different response to adjuvant chemotherapy.

CONCLUSION

Together, our findings show that SENP2, DCUN1D1, and DVL3 are candidate driver genes in the 3q26-29 amplicon of SCC, providing novel insights into the molecular mechanisms of disease progression and may have significant implication in the management of SCC of the lung.

Genomic profiling of oral squamous cell carcinoma by array-based comparative genomic hybridization

We designed a study to investigate genetic relationships between primary tumors of oral squamous cell carcinoma (OSCC) and their lymph node metastases, and to identify genomic copy number aberrations (CNAs) related to lymph node metastasis. For this purpose, we collected a total of 42 tumor samples from 25 patients and analyzed their genomic profiles by array-based comparative genomic hybridization. We then compared the genetic profiles of metastatic primary tumors (MPTs) with their paired lymph node metastases (LNMs), and also those of LNMs with non-metastatic primary tumors (NMPTs). Firstly, we found that although there were some distinctive differences in the patterns of genomic profiles between MPTs and their paired LNMs, the paired samples shared similar genomic aberration patterns in each case. Unsupervised hierarchical clustering analysis grouped together 12 of the 15 MPT-LNM pairs. Furthermore, similarity scores between paired samples were significantly higher than those between non-paired samples. These results suggested that MPTs and their paired LNMs are composed predominantly of genetically clonal tumor cells, while minor populations with different CNAs may also exist in metastatic OSCCs. Secondly, to identify CNAs related to lymph node metastasis, we compared CNAs between grouped samples of MPTs and LNMs, but were unable to find any CNAs that were more common in LNMs. Finally, we hypothesized that subpopulations carrying metastasis-related CNAs might be present in both the MPT and LNM. Accordingly, we compared CNAs between NMPTs and LNMs, and found that gains of 7p, 8q and 17q were more common in the latter than in the former, suggesting that these CNAs may be involved in lymph node metastasis of OSCC. In conclusion, our data suggest that in OSCCs showing metastasis, the primary and metastatic tumors share similar genomic profiles, and that cells in the primary tumor may tend to metastasize after acquiring metastasis-associated CNAs.

Genome wide analysis of chromosomal alterations in oral squamous cell carcinomas revealed over expression of MGAM and ADAM9

Despite the advances in diagnosis and treatment of oral squamous cell carcinoma (OSCC), mortality and morbidity rates have not improved over the past decade. A major drawback in diagnosis and treatment of OSCC is the lack of knowledge relating to how genetic instability in oral cancer genomes affects oral carcinogenesis. Hence, the key aim of this study was to identify copy number alterations (CNAs) that may be cancer associated in OSCC using high-resolution array comparative genomic hybridization (aCGH). To our knowledge this is the first study to use ultra-high density aCGH microarrays to profile a large number of OSCC genomes (n = 46). The most frequently amplified CNAs were located on chromosome 11q11(52%), 2p22.3(52%), 1q21.3-q22(54%), 6p21.32(59%), 20p13(61%), 7q34(52% and 72%),8p11.23-p11.22(80%), 8q11.1-q24.4(54%), 9q13-q34.3(54%), 11q23.3-q25(57%); 14q21.3-q31.1(54%); 14q31.3-q32.33(57%), 20p13-p12.3(54%) and 20q11.21-q13.33(52%). The most frequently deleted chromosome region was located on 3q26.1 (54%). In order to verify the CNAs from aCGH using quantitative polymerase chain reaction (qPCR), the three top most amplified regions and their associated genes, namely ADAM5P (8p11.23-p11.22), MGAM (7q34) and SIRPB1 (20p13.1), were selected in this study. The ADAM5P locus was found to be amplified in 39 samples and deleted in one; MGAM (24 amplifications and 3 deletions); and SIRPB1 (12 amplifications, others undetermined). On the basis of putative cancer-related annotations, two genes, namely ADAM metallopeptidase domain 9 (ADAM9) and maltase-glucoamylase alpha-glucosidase (MGAM), that mapped to CNA regions were selected for further evaluation of their mRNA expression using reverse transcriptase qPCR. The over-expression of MGAM was confirmed with a 6.6 fold increase in expression at the mRNA level whereas the fold change in ADAM9 demonstrated a 1.6 fold increase. This study has identified significant regions in the OSCC genome that were amplified and resulted in consequent over-expression of the MGAM and ADAM9 genes that may be utilized as biological markers for OSCC.

Identifying in-trans process associated genes in breast cancer by integrated analysis of copy number and expression data

Genomic copy number alterations are common in cancer. Finding the genes causally implicated in oncogenesis is challenging because the gain or loss of a chromosomal region may affect a few key driver genes and many passengers. Integrative analyses have opened new vistas for addressing this issue. One approach is to identify genes with frequent copy number alterations and corresponding changes in expression. Several methods also analyse effects of transcriptional changes on known pathways. Here, we propose a method that analyses in-cis correlated genes for evidence of in-trans association to biological processes, with no bias towards processes of a particular type or function. The method aims to identify cis-regulated genes for which the expression correlation to other genes provides further evidence of a network-perturbing role in cancer. The proposed unsupervised approach involves a sequence of statistical tests to systematically narrow down the list of relevant genes, based on integrative analysis of copy number and gene expression data. A novel adjustment method handles confounding effects of co-occurring copy number aberrations, potentially a large source of false positives in such studies. Applying the method to whole-genome copy number and expression data from 100 primary breast carcinomas, 6373 genes were identified as commonly aberrant, 578 were highly in-cis correlated, and 56 were in addition associated in-trans to biological processes. Among these in-trans process associated and cis-correlated (iPAC) genes, 28% have previously been reported as breast cancer associated, and 64% as cancer associated. By combining statistical evidence from three separate subanalyses that focus respectively on copy number, gene expression and the combination of the two, the proposed method identifies several known and novel cancer driver candidates. Validation in an independent data set supports the conclusion that the method identifies genes implicated in cancer.

Integrative genomics in combination with RNA interference identifies prognostic and functionally relevant gene targets for oral squamous cell carcinoma

In oral squamous cell carcinoma (OSCC), metastasis to lymph nodes is associated with a 50% reduction in 5-year survival. To identify a metastatic gene set based on DNA copy number abnormalities (CNAs) of differentially expressed genes, we compared DNA and RNA of OSCC cells laser-microdissected from non-metastatic primary tumors (n = 17) with those from lymph node metastases (n = 20), using Affymetrix 250K Nsp single-nucleotide polymorphism (SNP) arrays and U133 Plus 2.0 arrays, respectively. With a false discovery rate (FDR)<5%, 1988 transcripts were found to be differentially expressed between primary and metastatic OSCC. Of these, 114 were found to have a significant correlation between DNA copy number and gene expression (FDR<0.01). Among these 114 correlated transcripts, the corresponding genomic regions of each of 95 transcripts had CNAs differences between primary and metastatic OSCC (FDR<0.01). Using an independent dataset of 133 patients, multivariable analysis showed that the OSCC–specific and overall mortality hazards ratio (HR) for patients carrying the 95-transcript signature were 4.75 (95% CI: 2.03–11.11) and 3.45 (95% CI: 1.84–6.50), respectively. To determine the degree by which these genes impact cell survival, we compared the growth of five OSCC cell lines before and after knockdown of over-amplified transcripts via a high-throughput siRNA–mediated screen. The expression-knockdown of 18 of the 26 genes tested showed a growth suppression ≥30% in at least one cell line (P<0.01). In particular, cell lines derived from late-stage OSCC were more sensitive to the knockdown of G3BP1 than cell lines derived from early-stage OSCC, and the growth suppression was likely caused by increase in apoptosis. Further investigation is warranted to examine the biological role of these genes in OSCC progression and their therapeutic potentials.

Neck lymph node metastasis is the most important prognostic factor in oral squamous cell carcinoma (OSCC). To identify genes associated with this critical step of OSCC progression, we compared DNA copy number aberrations and gene expression differences between tumor cells found in metastatic lymph nodes versus those in non-metastatic primary tumors. We identified 95 transcripts (87 genes) with metastasis-specific genome abnormalities and gene expression. Tested in an independent cohort of 133 OSCC patients, the 95 gene signature was an independent risk factor of disease-specific and overall death, suggesting a disease progression phenotype. We knocked down the expression of over-amplified genes in five OSCC cell lines. Knockdown of 18 of the 26 tested genes suppressed the cell growth in at least one cell line. Interestingly, cell lines derived from late-stage OSCC were more sensitive to the knockdown of G3BP1 than cell lines derived from early-stage OSCC. The knockdown of G3BP1 increased programmed cell death in the p53-mutant but not wild-type OSCC cell lines. Taken together, we demonstrate that CNA–associated transcripts differentially expressed in carcinoma cells with an aggressive phenotype (i.e., metastatic to lymph nodes) can be biomarkers with both prognostic information and functional relevance. Moreover, results suggest that G3BP1 is a potential therapeutic target against late-stage p53-negative OSCC.

Integrative analysis in oral squamous cell carcinoma reveals DNA copy number-associated miRNAs dysregulating target genes

OBJECTIVE

To better understand possible mechanisms involved in the dysregulation of gene expression unique to oral squamous cell carcinoma (OSCC) metastasis, the investigators examined the differential expression of microRNAs (miRNAs) in OSCC metastasis and their functional impact on target gene expression.

STUDY DESIGN

Observational assessment of DNA copy number, miRNA, and RNA expression in primary and metastatic OSCC.

SETTING

University of Washington Medical Center and affiliated hospitals.

SUBJECTS

Tumor samples were taken from patients with primary incident OSCC; cells were laser-capture microdissected from 17 nonmetastatic primary tumors and 20 metastatic lymph nodes.

METHODS

DNA copy number aberrations and gene expression profiles were previously determined using Affymetrix 250K Nsp I SNP arrays and HU133 plus 2.0 expression arrays. miRNAs were interrogated with Exiqon's Ready-to-Use PCR Panels assessing the expression of 368 human miRNAs.

RESULTS

Investigators found 31 miRNAs differentially expressed between metastatic and nonmetastatic samples (false discovery rate <0.4; 26 overexpressed and 5 underexpressed in metastatic samples). Expression of 7 of these miRNAs was significantly associated with their DNA copy numbers, and expressions of 8 of these miRNAs were significantly associated with their target genes. Among these unique miRNAs, miR-140-3p, miR-29c, and miR-29a were differentially expressed in metastasis versus nonmetastatic samples and had a strong positive correlation with their DNA copy numbers and a negative correlation with the expression of their target genes.

CONCLUSION

Results suggest that DNA copy number aberration may play a role in the dysregulation of some differentially expressed miRNAs in OSCC metastasis, warranting further investigation.

New insights into the troubles of aneuploidy

Deviation from a balanced genome by either gain or loss of entire chromosomes is generally tolerated poorly in all eukaryotic systems studied to date. Errors in mitotic or meiotic cell division lead to aneuploidy, which places a burden of additional or insufficient gene products from the missegregated chromosomes on the daughter cells. The burden of aneuploidy often manifests itself as impaired fitness of individual cells and whole organisms, in which abnormal development is also characteristic. However, most human cancers, noted for their rapid growth, also display various levels of aneuploidy. Here we discuss the detrimental, potentially beneficial, and sometimes puzzling effects of aneuploidy on cellular and organismal fitness and tissue function as well as its role in diseases such as cancer and neurodegeneration.

The consequences of chromosomal aneuploidy on the transcriptome of cancer cells

Chromosomal aneuploidies are a defining feature of carcinomas, i.e., tumors of epithelial origin. Such aneuploidies result in tumor specific genomic copy number alterations. The patterns of genomic imbalances are tumor specific, and to a certain extent specific for defined stages of tumor development. Genomic imbalances occur already in premalignant precursor lesions, i.e., before the transition to invasive disease, and their distribution is maintained in metastases, and in cell lines derived from primary tumors. These observations are consistent with the interpretation that tumor specific genomic imbalances are drivers of malignant transformation. Naturally, this precipitates the question of how such imbalances influence the expression of resident genes. A number of laboratories have systematically integrated copy number alterations with gene expression changes in primary tumors and metastases, cell lines, and experimental models of aneuploidy to address the question as to whether genomic imbalances deregulate the expression of one or few key genes, or rather affect the cancer transcriptome more globally. The majority of these studies showed that gene expression levels follow genomic copy number. Therefore, gross genomic copy number changes, including aneuploidies of entire chromosome arms and chromosomes, result in a massive deregulation of the transcriptome of cancer cells. This article is part of a Special Issue entitled: Chromatin in time and space.

Copy number changes of CRISP3 in oral squamous cell carcinoma

The aim of this study was to identify tumor suppressor genes (TSGs) in oral squamous cell carcinoma (OSCC) using whole-genome analysis of microarray technology and real-time quantitative polymerase chain reaction (QPCR). We applied whole-genome analysis of TSGs in the specimens from 3 patients of OSCC by microarray technology. A total of 11 genes, CRISP3, SCGB3A1, AGR2, PIP, C20orf114, TFF1, STATH, AZGP1, MUC7, DMBT1 and LOC389429, were found to be down-regulated, and 2, matrix metallopeptidase (MMP) 1 and MMP3, were found to be up-regulated in the 3 OSCC patients using microarray technology. In this study, we selected the CRISP3 gene. CRISP3 belongs to the cystein-rich secretary protein gene family in chromosome 6p12.3. CRISP3 has been found in the salivary gland, spleen and prostate gland and is a prominent biomarker in the gene expression of prostate cancer. Down-regulation of this gene was previously observed in OSCC. No studies examining the DNA copy number of CRISP3 in detail exist. We analyzed the DNA copy number of CRISP3 in 5 OSCC-derived cell lines (SAS, Ca9-22, KON, HSC2 and HSC4) and 60 OSCC tissues by real-time QPCR. The DNA copy number loss of CRISP3 was observed in 2 of the 5 OSCC-derived cell lines (SAS, HSC2) and in 24 of 60 patients (40.0%) using real-time QPCR. A significant statistical correlation between the copy number loss and gender and T classification was observed. These results indicate that the inactivation of CRISP3 is an early event in OSCC, since the T1/T2 classification is correlated with DNA copy number loss of CRISP3, whereas T3/T4 classification is not. We conclude that CRISP3 may be involved in the carcinogenesis of OSCC.

Genome-wide expression and copy number analysis identifies driver genes in gingivobuccal cancers

The molecular mechanisms contributing to the development and progression of gingivobuccal complex (GBC) cancers-a sub-site of oral cancer, comprising the buccal mucosa, the gingivobuccal sulcus, the lower gingival region, and the retromolar trigone-remain poorly understood. Identifying the GBC cancer-related gene expression signature and the driver genes residing on the altered chromosomal regions is critical for understanding the molecular basis of its pathogenesis. Genome-wide expression profiling of 27 GBC cancers with known chromosomal alterations was performed to reveal differentially expressed genes. Putative driver genes were identified by integrating copy number and gene expression data. A total of 315 genes were found differentially expressed (P ≤ 0.05, logFC > 2.0) of which 11 genes were validated by real-time quantitative reverse transcriptase-PCR (qRT-PCR) in tumors (n = 57) and normal GBC tissues (n = 18). Overexpression of LY6K, in chromosome band 8q24.3, was validated by immunohistochemical (IHC) analysis. We found that 78.5% (2,417/3,079) of the genes located in regions of recurrent chromosomal alterations show copy number dependent expression indicating that copy number alteration has a direct effect on global gene expression. The integrative analysis revealed BIRC3 in 11q22.2 as a candidate driver gene associated with poor clinical outcome. Our study identified previously unreported differentially expressed genes in a homogeneous subtype of oral cancer and the candidate driver genes that may contribute to the development and progression of the disease. © 2011 Wiley Periodicals, Inc.

Stochastic modeling of the relationship between copy number and gene expression based on transcriptional logic

DNA copy number alterations (CNAs) can cause genetic diseases, and studies have revealed a relationship between CNAs and gene expression; however, the manner in which CNAs relate to gene expression and what regulatory mechanisms underlying the relationship remain unclear. In many instances, real data have revealed a nonlinear relationship between copy number and gene expression. In this paper, queueing theory is used to model this relationship, with the basic structural parameters involving transcription factor (TF) arrival and departure rates. A key finding is that the ratio of TF arrival rate to TF departure rate is critical: small and large ratios corresponding to nonlinear and linear relationships, respectively. Indeed, copy number amplifications do not necessarily lead to expression increases: when one of the regulatory TFs exists in a small amount, copy number gains can cause a down regulation. Using the concept of mutual information, we show that the TF with minimum activation probability can have maximum dependence in regulation: a TF in small amount could result in a nonlinear copy-number-gene-expression relationship and play a major role in regulation. The expectation-maximization algorithm is used to estimate the ratio of TF arrival rate to TF departure rate. The theoretical results are illustrated via simulations.

A novel molecular signature identified by systems genetics approach predicts prognosis in oral squamous cell carcinoma

Molecular methods for predicting prognosis in patients with oral cavity squamous cell carcinoma (OSCC) are urgently needed, considering its high recurrence rate and tendency for metastasis. The present study investigated the genetic basis of variations in gene expression associated with poor prognosis in OSCC using Affymetrix SNP 6.0 and Affymetrix GeneChip Human Gene 1.0 ST arrays. We identified recurrent DNA amplifications scattered from 8q22.2 to 8q24.3 in 112 OSCC specimens. These amplicons demonstrated significant associations with increased incidence of extracapsular spread, development of second primary malignancies, and poor survival. Fluorescence in situ hybridization, in a validation panel consisting of 295 cases, confirmed these associations. Assessment of the effects of copy number variations (CNVs) on genome-wide variations in gene expression identified a total of 85 CNV-associated transcripts enriched in the MYC-centered regulatory network. Twenty-four transcripts associated with increased risk of second primary malignancies, tumor relapse, and poor survival. Besides MYC itself, a novel dysregulated MYC module plays a key role in OSCC carcinogenesis. This study identified a candidate molecular signature associated with poor prognosis in OSCC patients, which may ultimately facilitate patient-tailored selection of therapeutic strategies.

Comprehensive exon array data processing method for quantitative analysis of alternative spliced variants

Alternative splicing of pre-mRNA generates protein diversity. Dysfunction of splicing machinery and expression of specific transcripts has been linked to cancer progression and drug response. Exon microarray technology enables genome-wide quantification of expression levels of the majority of exons and facilitates the discovery of alternative splicing events. Analysis of exon array data is more challenging than the analysis of gene expression data and there is a need for reliable quantification of exons and alternatively spliced variants. We introduce a novel, computationally efficient methodology, Multiple Exon Array Preprocessing (MEAP), for exon array data pre-processing, analysis and visualization. We compared MEAP with existing pre-processing methods, and validation of six exons and two alternatively spliced variants with qPCR corroborated MEAP expression estimates. Analysis of exon array data from head and neck squamous cell carcinoma (HNSCC) cell lines revealed several transcripts associated with 11q13 amplification, which is related with decreased survival and metastasis in HNSCC patients. Our results demonstrate that MEAP produces reliable expression values at exon, alternatively spliced variant and gene levels, which allows generating novel experimentally testable predictions.

Robust linear regression methods in association studies

MOTIVATION

It is well known that data deficiencies, such as coding/rounding errors, outliers or missing values, may lead to misleading results for many statistical methods. Robust statistical methods are designed to accommodate certain types of those deficiencies, allowing for reliable results under various conditions. We analyze the case of statistical tests to detect associations between genomic individual variations (SNP) and quantitative traits when deviations from the normality assumption are observed. We consider the classical analysis of variance tests for the parameters of the appropriate linear model and a robust version of those tests based on M-regression. We then compare their empirical power and level using simulated data with several degrees of contamination.

RESULTS

Data normality is nothing but a mathematical convenience. In practice, experiments usually yield data with non-conforming observations. In the presence of this type of data, classical least squares statistical methods perform poorly, giving biased estimates, raising the number of spurious associations and often failing to detect true ones. We show through a simulation study and a real data example, that the robust methodology can be more powerful and thus more adequate for association studies than the classical approach.

AVAILABILITY

The code of the robustified version of function lmekin() from the R package kinship is provided as Supplementary Material.