Aleksandra Pfeifer

Impact of SNPs on methylation readouts by Illumina Infinium HumanMethylation450 BeadChip Array: implications for comparative population studies

BackgroundInfinium HumanMethylation 450 BeadChip Arrays by Illumina (Illumina HM450K) are among the most popular CpG microarray platforms widely used in biological and medical research. Several recent studies highlighted the potentially confounding impact of the genomic variation on the results of methylation studies performed using Illumina’s Infinium methylation probes. However, the complexity of SNPs impact on the methylation level measurements (β values) has not been comprehensively described.ResultsIn our comparative study of European and Asian populations performed using Illumina HM450K, we found that the majority of Infinium probes, which differentiated two examined groups, had SNPs in their target sequence. Characteristic tri-modal or bi-modal patterns of β values distribution among individual samples were observed for CpGs with SNPs in the first and second position, respectively. To better understand how SNPs affect methylation readouts, we investigated their impact in the context of SNP position and type, and of the Illumina probe type (Infinium I or II).ConclusionsOur study clearly demonstrates that SNP variation existing in the genome, if not accounted for, may lead to false interpretation of the methylation signal differences suggested by some of the Illumina Infinium probes. In addition, it provides important practical clues for discriminating between differences due to the methylation status and to the genomic polymorphisms, based on the inspection of methylation readouts in individual samples. This approach is of special importance when Illumina Infinium assay is used for any comparative population studies, whether related to cancer, disease, ethnicity where SNP frequencies differentiate the studied groups.

Molecular signature of cell cycle exit induced in human T lymphoblasts by IL-2 withdrawal

BackgroundThe molecular mechanisms of cell cycle exit are poorly understood. Studies on lymphocytes at cell cycle exit after growth factor deprivation have predominantly focused on the initiation of apoptosis. We aimed to study gene expression profile of primary and immortalised IL-2-dependent human T cells forced to exit the cell cycle by growth factor withdrawal, before apoptosis could be evidenced.ResultsBy the Affymetrix microarrays HG-U133 2.0 Plus, 53 genes were distinguished as differentially expressed before and soon after IL-2 deprivation. Among those, PIM1, BCL2, IL-8, HBEGF, DUSP6, OSM, CISH, SOCS2, SOCS3, LIF and IL13 were down-regulated and RPS24, SQSTM1, TMEM1, LRRC8D, ECOP, YY1AP1, C1orf63, ASAH1, SLC25A46 and MIA3 were up-regulated. Genes linked to transcription, cell cycle, cell growth, proliferation and differentiation, cell adhesion, and immune functions were found to be overrepresented within the set of the differentially expressed genes.ConclusionCell cycle exit of the growth factor-deprived T lymphocytes is characterised by a signature of differentially expressed genes. A coordinate repression of a set of genes known to be induced during T cell activation is observed. However, growth arrest following exit from the cell cycle is actively controlled by several up-regulated genes that enforce the non-dividing state. The identification of genes involved in cell cycle exit and quiescence provides new hints for further studies on the molecular mechanisms regulating the non-dividing state of a cell, the mechanisms closely related to cancer development and to many biological processes.

Molecular differential diagnosis of follicular thyroid carcinoma and adenoma based on gene expression profiling by using formalin-fixed paraffin-embedded tissues

BackgroundDifferential diagnosis between malignant follicular thyroid cancer (FTC) and benign follicular thyroid adenoma (FTA) is a great challenge for even an experienced pathologist and requires special effort. Molecular markers may potentially support a differential diagnosis between FTC and FTA in postoperative specimens. The purpose of this study was to derive molecular support for differential post-operative diagnosis, in the form of a simple multigene mRNA-based classifier that would differentiate between FTC and FTA tissue samples.MethodsA molecular classifier was created based on a combined analysis of two microarray datasets (using 66 thyroid samples). The performance of the classifier was assessed using an independent dataset comprising 71 formalin-fixed paraffin-embedded (FFPE) samples (31 FTC and 40 FTA), which were analysed by quantitative real-time PCR (qPCR). In addition, three other microarray datasets (62 samples) were used to confirm the utility of the classifier.ResultsFive of 8 genes selected from training datasets (ELMO1, EMCN, ITIH5, KCNAB1, SLCO2A1) were amplified by qPCR in FFPE material from an independent sample set. Three other genes did not amplify in FFPE material, probably due to low abundance. All 5 analysed genes were downregulated in FTC compared to FTA. The sensitivity and specificity of the 5-gene classifier tested on the FFPE dataset were 71% and 72%, respectively.ConclusionsThe proposed approach could support histopathological examination: 5-gene classifier may aid in molecular discrimination between FTC and FTA in FFPE material.

Somatic mutation profiling of follicular thyroid cancer by next generation sequencing

The molecular etiology of follicular thyroid tumors is largely unknown, rendering the diagnostics of these tumors challenging. The somatic alterations present in these tumors apart from RAS gene mutations and PAX8/PPARG translocations are not well described. To evaluate the profile of somatic alteration in follicular thyroid tumors, a total of 82 thyroid tissue samples derived from 48 patients were subjected to targeted Illumina HiSeq next generation sequencing of 372 cancer-related genes. New somatic alterations were identified in oncogenes (MDM2, FLI1), transcription factors and repressors (MITF, FLI1, ZNF331), epigenetic enzymes (KMT2A, NSD1, NCOA1, NCOA2), and protein kinases (JAK3, CHEK2, ALK). Single nucleotide and large structural variants were most and least frequently identified, respectively. A novel translocation in DERL/COX6C was detected. Many somatic alterations in non-coding gene regions with high penetrance were observed. Thus, follicular thyroid tumor somatic alterations exhibit complex patterns. Most tumors contained distinct somatic alterations, suggesting previously unreported heterogeneity.

The prevalence of somatic RAS mutations in medullary thyroid cancer — a Polish population study

INTRODUCTION Somatic RET mutations are detectable in two-thirds of sporadic cases of medullary thyroid cancer (MTC). Recent studies reported a high proportion of RAS somatic mutations in RET negative tumours, which may indicate RAS mutation as a possible alternative genetic event in sporadic MTC tumorigenesis. Thus, the aim of the study was to evaluate the frequency of somatic RAS mutations in sporadic medullary thyroid cancer in the Polish population and to relate the obtained data to the presence of somatic RET mutations. MATERIAL AND METHODS Somatic mutations (RET, RAS genes) were evaluated in 78 snap-frozen MTC samples (57 sporadic and 21 hereditary) by direct sequencing. Next, three randomly selected RET-negative MTC samples were analysed by the next generation sequencing. RESULTS RAS mutation was detected in 26.5% of 49 sporadic MTC tumours. None of all the analysed samples showed N-RAS mutation. When only RET-negative samples were considered, the prevalence of RAS mutation was 68.7%, compared to 6% observed in RET-positive samples. Most of these mutations were located in H-RAS codon 61 (72%). None of 21 hereditary MTC samples showed any RAS mutations. CONCLUSIONS RAS mutations constitute a frequent molecular event in RET-negative sporadic medullary thyroid carcinoma in Polish patients. However, their role in MTC tumorigenesis remains unclear.

Brain Metastasis Prediction by Transcriptomic Profiling in Triple-Negative Breast Cancer

Background Triple‐negative breast cancer (TNBC) lacks expression of steroid hormone receptors (estrogen receptor &agr; and progesterone) and epidermal growth factor receptor type 2. This phenotype shows high metastatic potential, with particular predilection to lungs and brain. Determination of TNBC transcriptomic profiles associated with high risk of brain metastasis (BM) might identify patients requiring alternative, more aggressive, or specific preventive and therapeutic approaches. Patients and Methods Using a cDNA‐mediated annealing, selection, extension, and ligation assay, we investigated expression of 29,369 gene transcripts in primary TNBC tumor samples from 119 patients—71 in discovery cohort A and 48 in independent cohort B—that included best discriminating genes. Expression of mRNA was correlated with the occurrence of symptomatic BM. Results In cohort A, the difference at the noncorrected P < .005 was found for 64 transcripts (P = .23 for global test), but none showed significant difference at a preset level of false‐discovery rate of < 10%. Of the 30 transcripts with the largest differences between patients with and without BM in cohort A, none was significantly associated with BM in cohort B. Conclusion Analysis based on the primary tumor gene transcripts alone is unlikely to predict BM development in advanced TNBC. Despite its negative findings, the study adds to the knowledge on the biology of TNBC and paves the way for future projects using more advanced molecular assays. Micro‐Abstract We investigated expression of 29,369 gene transcripts in primary tumor samples from 119 patients with advanced triple‐negative breast cancer to identify genes with different expression between patients with and without brain metastases (BM). Our results indicate that analysis based on expression of gene transcripts from primary tumor does not allow prediction of BM development in this population.

Gene Expression (mRNA) Markers for Differentiating between Malignant and Benign Follicular Thyroid Tumours

Distinguishing between follicular thyroid cancer (FTC) and follicular thyroid adenoma (FTA) constitutes a long-standing diagnostic problem resulting in equivocal histopathological diagnoses. There is therefore a need for additional molecular markers. To identify molecular differences between FTC and FTA, we analyzed the gene expression microarray data of 52 follicular neoplasms. We also performed a meta-analysis involving 14 studies employing high throughput methods (365 follicular neoplasms analyzed). Based on these two analyses, we selected 18 genes differentially expressed between FTA and FTC. We validated them by quantitative real-time polymerase chain reaction (qRT-PCR) in an independent set of 71 follicular neoplasms from formaldehyde-fixed paraffin embedded (FFPE) tissue material. We confirmed differential expression for 7 genes (CPQ, PLVAP, TFF3, ACVRL1, ZFYVE21, FAM189A2, and CLEC3B). Finally, we created a classifier that distinguished between FTC and FTA with an accuracy of 78%, sensitivity of 76%, and specificity of 80%, based on the expression of 4 genes (CPQ, PLVAP, TFF3, ACVRL1). In our study, we have demonstrated that meta-analysis is a valuable method for selecting possible molecular markers. Based on our results, we conclude that there might exist a plausible limit of gene classifier accuracy of approximately 80%, when follicular tumors are discriminated based on formalin-fixed postoperative material.

Unsupervised analysis of follicular thyroid tumours transcriptome by oligonucleotide microarray gene expression profiling.

INTRODUCTION Mechanisms driving the invasiveness of follicular thyroid cancer (FTC) are not fully understood. In our study, we undertook an unsupervised analysis of the set of follicular thyroid tumours (adenomas (FTA) and carcinomas) to verify whether the malignant phenotype influences major sources of variability in our dataset. MATERIAL AND METHODS The core set of samples consisted of 52 tumours (27 FTC, 25 FTA). Total RNA was analysed by oligonucleotide microarray (HG-U133 Plus 2.0). Principal Component Analysis (PCA) was applied as a main method of unsupervised analysis. RESULTS An analysis of biological character of genes correlated to the first six PCs was performed. When genes correlated to the first PC were used to cluster FTC and FTA, they appeared in two branches; one, relatively enriched in adenomas, with homogenous expression of subset of genes, and the other containing mainly carcinomas, with down-regulation of these genes and heterogeneous up-regulation in a smaller cluster of transcripts. Genes highly up-regulated in adenomas included some thyroid-specific transcripts. The second cluster of genes, up-regulated in carcinomas, contained mainly immunity-related transcripts. Immune response genes were found in the first, third and sixth principal components, improving the discrimination between carcinomas and adenomas. CONCLUSIONS Our unsupervised analysis indicates that invasiveness of follicular tumours might be considered as the major source of variability in transcriptome analysis. However, the distance between both groups is small and the clusters are overlapping, thus, unsupervised analysis is not sufficient to properly classify them.

EurEAs_Gplex—A new SNaPshot assay for continental population discrimination and gender identification

Assays that allow analysis of the biogeographic origin of biological samples in a standard forensic laboratory have to target a small number of highly differentiating markers. Such markers should be easy to multiplex and the assay must perform well in the degraded and scarce biological material. SNPs localized in the genome regions, which in the past were subjected to differential selective pressure in various populations, are the most widely used markers in the studies of biogeographic affiliation. SNPs reflecting biogeographic differences not related to any phenotypic traits are not sufficiently explored. The goal of our study was to identify a small set of SNPs not related to any known pigmentation/phenotype-specific genes, which would allow efficient discrimination between populations of Europe and East Asia. The selection of SNPs was based on the comparative analysis of representative European and Chinese/Japanese samples (B-lymphocyte cell lines), genotyped using the Infinium HumanOmniExpressExome microarray (Illumina). The classifier, consisting of 24 unlinked SNPs (24-SNP classifier), was selected. The performance of a 14-SNP subset of this classifier (14-SNP subclassifier) was tested using genotype data from several populations. The 14-SNP subclassifier differentiated East Asians, Europeans and Africans with ∼100% accuracy; Palestinians, representative of the Middle East, clustered with Europeans, while Amerindians and Pakistani were placed between East Asian and European populations. Based on these results, we have developed a SNaPshot assay (EurEAs_Gplex) for genotyping SNPs from the 14-SNP subclassifier, combined with an additional marker for gender identification. Forensic utility of the EurEAs_Gplex was verified using degraded and low quantity DNA samples. The performance of the EurEAs_Gplex was satisfactory when using degraded DNA; tests using low quantity DNA samples revealed a previously not described source of genotyping errors, potentially important for any SNaPshot-based assays.

Transcriptional profiles of pilocytic astrocytoma are related to their three different locations, but not to radiological tumor features.

BackgroundPilocytic astrocytoma is the most common type of brain tumor in the pediatric population, with a generally favorable prognosis, although recurrences or leptomeningeal dissemination are sometimes also observed. For tumors originating in the supra-or infratentorial location, a different molecular background was suggested, but plausible correlations between the transcriptional profile and radiological features and/or clinical course are still undefined. The purpose of this study was to identify gene expression profiles related to the most frequent locations of this tumor, subtypes based on various radiological features, and the clinical pattern of the disease.MethodsEighty six children (55 males and 31 females) with histologically verified pilocytic astrocytoma were included in this study. Their age at the time of diagnosis ranged from fourteen months to seventeen years, with a mean age of seven years. There were 40 cerebellar, 23 optic tract/hypothalamic, 21 cerebral hemispheric, and two brainstem tumors. According to the radiological features presented on MRI, all cases were divided into four subtypes: cystic tumor with a non-enhancing cyst wall; cystic tumor with an enhancing cyst wall; solid tumor with central necrosis; and solid or mainly solid tumor. In 81 cases primary surgical resection was the only and curative treatment, and in five cases progression of the disease was observed. In 47 cases the analysis was done by using high density oligonucleotide microarrays (Affymetrix HG-U133 Plus 2.0) with subsequent bioinformatic analyses and confirmation of the results by independent RT-qPCR (on 39 samples).ResultsBioinformatic analyses showed that the gene expression profile of pilocytic astrocytoma is highly dependent on the tumor location. The most prominent differences were noted for IRX2, PAX3, CXCL14, LHX2, SIX6, CNTN1 and SIX1 genes expression even within different compartments of the supratentorial region. Analysis of the genes potentially associated with radiological features showed much weaker transcriptome differences. Single genes showed association with the tendency to progression.ConclusionsHere we have shown that pilocytic astrocytomas of three different locations can be precisely differentiated on the basis of their gene expression level, but their transcriptional profiles does not strongly reflect the radiological appearance of the tumor or the course of the disease.