Gene Expression-Based Approaches in Differentiation of Metastases and Second Primary Tumour

A 64-year-old male patient was diagnosed with 3 consecutive non-small cell lung carcinomas (NSCLC). In the current study, we applied whole-genome gene expression analysis to control, primary and locally recurrent cancer, and supposed metastasis samples of a single patient. According to our knowledge, there are no published papers describing the gene expression profiles of a single patient's squamous cell lung cancers. As the histology and differentiation grade of the primary cancer and the supposed metastasis differed minimally, but local recurrence was poorly differentiated, molecular profiling of the samples was carried out in order to confirm or reject the hypothesis of second primary cancer. Principal component analysis of the gene expression data revealed distinction of the local recurrence. Gene ontology analysis showed no molecular characteristics of metastasis in the supposed metastasis. Gene expression analysis is valuable and can be supportive in decision-making of diagnostically complicated cancer cases

g:Profiler—a web server for functional interpretation of gene lists (2011 update)

Functional interpretation of candidate gene lists is an essential task in modern biomedical research. Here, we present the 2011 update of g:Profiler (http://biit.cs.ut.ee/gprofiler/), a popular collection of web tools for functional analysis. g:GOSt and g:Cocoa combine comprehensive methods for interpreting gene lists, ordered lists and list collections in the context of biomedical ontologies, pathways, transcription factor and microRNA regulatory motifs and protein–protein interactions. Additional tools, namely the biomolecule ID mapping service (g:Convert), gene expression similarity searcher (g:Sorter) and gene homology searcher (g:Orth) provide numerous ways for further analysis and interpretation. In this update, we have implemented several features of interest to the community: (i) functional analysis of single nucleotide polymorphisms and other DNA polymorphisms is supported by chromosomal queries; (ii) network analysis identifies enriched protein–protein interaction modules in gene lists; (iii) functional analysis covers human disease genes; and (iv) improved statistics and filtering provide more concise results. g:Profiler is a regularly updated resource that is available for a wide range of species, including mammals, plants, fungi and insects

Methylation Markers of Early-Stage Non-Small Cell Lung Cancer

Despite of intense research in early cancer detection, there is a lack of biomarkers for the reliable detection of malignant tumors, including non-small cell lung cancer (NSCLC). DNA methylation changes are common and relatively stable in various types of cancers, and may be used as diagnostic or prognostic biomarkers.We performed DNA methylation profiling of samples from 48 patients with stage I NSCLC and 18 matching cancer-free lung samples using microarrays that cover the promoter regions of more than 14,500 genes. We correlated DNA methylation changes with gene expression levels and performed survival analysis.We observed hypermethylation of 496 CpGs in 379 genes and hypomethylation of 373 CpGs in 335 genes in NSCLC. Compared to adenocarcinoma samples, squamous cell carcinoma samples had 263 CpGs in 223 hypermethylated genes and 513 CpGs in 436 hypomethylated genes. 378 of 869 (43.5%) CpG sites discriminating the NSCLC and control samples showed an inverse correlation between CpG site methylation and gene expression levels. As a result of a survival analysis, we found 10 CpGs in 10 genes, in which the methylation level differs in different survival groups.We have identified a set of genes with altered methylation in NSCLC and found that a minority of them showed an inverse correlation with gene expression levels. We also found a set of genes that associated with the survival of the patients. These newly-identified marker candidates for the molecular screening of NSCLC will need further analysis in order to determine their clinical utility

Influence of common genetic variation on lung cancer risk: meta-analysis of 14 900 cases and 29 485 controls

Recent genome-wide association studies (GWASs) have identified common genetic variants at 5p15.33, 6p21-6p22 and 15q25.1 associated with lung cancer risk. Several other genetic regions including variants of CHEK2 (22q12), TP53BP1 (15q15) and RAD52 (12p13) have been demonstrated to influence lung cancer risk in candidate- or pathway-based analyses. To identify novel risk variants for lung cancer, we performed a meta-analysis of 16 GWASs, totaling 14 900 cases and 29 485 controls of European descent. Our data provided increased support for previously identified risk loci at 5p15 (P = 7.2 × 10−16), 6p21 (P = 2.3 × 10−14) and 15q25 (P = 2.2 × 10−63). Furthermore, we demonstrated histology-specific effects for 5p15, 6p21 and 12p13 loci but not for the 15q25 region. Subgroup analysis also identified a novel disease locus for squamous cell carcinoma at 9p21 (CDKN2A/p16INK4A/p14ARF/CDKN2B/p15INK4B/ANRIL; rs1333040, P = 3.0 × 10−7) which was replicated in a series of 5415 Han Chinese (P = 0.03; combined analysis, P = 2.3 × 10−8). This large analysis provides additional evidence for the role of inherited genetic susceptibility to lung cancer and insight into biological differences in the development of the different histological types of lung cance

Mitteväikerakulise kopsuvähi histoloogiliste alatüüpide molekulaarsed erinevused ja sarnasused

Väitekirja elektrooniline versioon ei sisalda publikatsioone.Uuringuks kasutati 147 mitteväikerakulise kopsuvähi tõttu opereeritud patsiendi koematerjali ning fenotüübi ja elulemuse andmeid. Geeniekspressiooni katse viidi läbi Illumina Human-6 ülegenoomi kiibiga mis sisaldab rohkem kui 48000 transkripti. Leitud markerite arvu vähendamiseks säilitati geenid mis näitasid vähemalt kahekordset ekspressiooni erinevust vähivabast normkoest. Erinevate vähitüüpide ja staadiumite molekulaarsete profiilide erinevuste visualiseerimiseks kasutati peakomponentanalüüsi. Metageeni leidmiseks piirati andmestiku suurust, klasterdades sarnase ekspressiooniga geene hierarhiliselt täieliku aheldatuse meetodil, kasutades sarnasusmõõduna Pearsoni korrelatsiooni. I b staadiumi patsientide geeniekspressiooni andmed jagati 500 gruppi ning iga klastri profiili keskmine moodustas metageeni. Uuringu tulemusena leiti mitteväikerakulises kopsuvähis normaalsest kopsukoest vähemalt kahekordse ekspressiooni erinevusega 672 alla- ja 1103 üles reguleeritud geeni. Lisaks leiti 18 uut potentsiaalset biomarkerit edasisteks kopsuvähi uuringuteks. Geeniekspressiooni profiili peakomponentanalüüs aitas eristada erinevaid vähitüüpe teineteisest ja mõnel juhul ka algkollet metastaasist. Samas ei eristu mitteväikerakulise kopsuvähi geeniekspressiooni profiilil ega ka selle peakomponentanalüüsil TNM il põhinevad vähkide kliinilised staadiumid. Kasutades p väärtust 10-6 ei õnnestunud veenvalt leida adenokartsinoomi ja bronhioloalveolaarset vähki eristavaid markereid. Ib staadiumi patsientide prognoosi hindamiseks leiti kaks statistilise olulisuse ja aktsepteeritava veapiiriga metageeni mis jaotas haigusjuhud ekspressiooni profiilide järgi kahte prognostilisse gruppi elulemusega vastavalt 1225 päeva. Kahe grupi eristamiseks valisime kokkuleppeliselt 1000 päeva piiri.In this thesis, 48,000 known transcripts of the human genome were analyzed in comparison with 147 patients NSCLC and corresponding cancer-free lung tissue. An Illumina BeadChip platform and a HumanWG-6_V2 Expression Bead Chip containing 48,000 transcript probes were used for microarray gene expression experiments. For genes exhibiting at least a 2-fold change in expression, and a p-value of at least 10-6, 1,775 markers were identified that distinguished NSCLC tissue from normal tissue. In addition, 18 potentially novel biomarkers were identified for NSCLC. Two metagenes, associated with a prognostic value for stage Ib patients, were able to distinguish the entire cohort into two different survival groups; those surviving > 1000 days, and those surviving < 1000 days. The contribution of this thesis to cancer biology includes the potential identification of novel biomarkers for NSCLC, and an improved understanding of the NSCLC microenvironment. The results of this thesis also have clinical value in that the design of array-based diagnostic, prognostic, and predictive tests were demonstrated for NSCLC. Integration of the gene expression data obtained with data regarding environmental risk factors, epidemiologic data, and clinical course (including prognostic and predictive data) will further help to elucidate mechanistic details of NSCLC, and these will need to be confirmed with additional studies

Mutation analysis and copy number alterations of KIF23 in non-small-cell lung cancer exhibiting KIF23 over-expression

KIF23 was recently suggested to be a potential molecular target for the treatment of lung cancer. This proposal is based on elevated expression of KIF23 in several tumors affecting breast, lung, brain, and liver, and also on the presence of KIF23 mutations in melanoma and colorectal cancer. Recently, we identified a mutation in the KIF23 gene causing a rare hereditary form of dyserythropoietic anemia (CDA III) with predisposition to blood cancer. We suggested that KIF23 overexpression in tumors might be due to the presence of activating somatic mutations, and therefore, mutation screening of the KIF23 in 15 non-small-cell lung cancer (NSCLC) cases with elevated expression level of KIF23 was undertaken. Eight sequence variants were found in all samples. Furthermore, one variant was present in two cases, and one variant was case specific. Nine variants were previously reported while one variant lacks frequency information. Nine of ten cases available for single nucleotide polymorphism-array analysis demonstrated aberrant karyotypes with additional copy of entire chromosome 15. Thus, no activating somatic mutations in coding regions of the KIF23 were found. Furthermore, no mutations were detected in cell cycle genes homology region in KIF23 promoter responsible for p53-dependent repression of KIF23 expression. We showed that the elevated level of KIF23 could be due to additional copy of chromosome 15 demonstrated in 90% of NSCLC cases analyzed in this study. Considering the crucial role of KIF23 in the final step of mitosis, the gene is a potential molecular marker, and for better understanding of its role in cancer development, more tumors should be analyzed

Identification of MiR-374a as a prognostic marker for survival in patients with early-stage nonsmall cell lung cancer

Lung cancer is one of the deadliest types of cancer proven by the poor survival and high relapse rates after surgery. Recently discovered microRNAs (miRNAs), small noncoding RNA molecules, play a crucial role in modulating gene expression networks and are directly involved in the progression of a number of human cancers. In this study, we analyzed the expression profile of 858 miRNAs in 38 Estonian nonsmall cell lung cancer (NSCLC) samples (Stage I and II) and 27 adjacent nontumorous tissue samples using Illumina miRNA arrays. We found that 39 miRNAs were up-regulated and 33 down-regulated significantly in tumors compared with normal lung tissue. We observed aberrant expression of several well-characterized tumorigenesis-related miRNAs, as well as a number of miRNAs whose function is currently unknown. We show that low expression of miR-374a in early-stage NSCLC is associated with poor patient survival. The combinatorial effect of the up- and down-regulated miRNAs is predicted to most significantly affect pathways associated with cell migration, differentiation and growth, and several signaling pathways that contribute to tumorigenesis. In conclusion, our results demonstrate that expression of miR-374a at early stages of NSCLC progression can serve as a prognostic marker for patient risk stratification and may be a promising therapeutic target for the treatment of lung cancer