Hanna Göransson

Screening for copy-number alterations and loss of heterozygosity in chronic lymphocytic leukemia-A comparative study of four differently designed, high resolution microarray platforms.

Screening for gene copy‐number alterations (CNAs) has improved by applying genome‐wide microarrays, where SNP arrays also allow analysis of loss of heterozygozity (LOH). We here analyzed 10 chronic lymphocytic leukemia (CLL) samples using four different high‐resolution platforms: BAC arrays (32K), oligonucleotide arrays (185K, Agilent), and two SNP arrays (250K, Affymetrix and 317K, Illumina). Cross‐platform comparison revealed 29 concordantly detected CNAs, including known recurrent alterations, which confirmed that all platforms are powerful tools when screening for large aberrations. However, detection of 32 additional regions present in 2–3 platforms illustrated a discrepancy in detection of small CNAs, which often involved reported copy‐number variations. LOH analysis using dChip revealed concordance of mainly large regions, but showed numerous, small nonoverlapping regions and LOH escaping detection. Evaluation of baseline variation and copy‐number ratio response showed the best performance for the Agilent platform and confirmed the robustness of BAC arrays. Accordingly, these platforms demonstrated a higher degree of platform‐specific CNAs. The SNP arrays displayed higher technical variation, although this was compensated by high density of elements. Affymetrix detected a higher degree of CNAs compared to Illumina, while the latter showed a lower noise level and higher detection rate in the LOH analysis. Large‐scale studies of genomic aberrations are now feasible, but new tools for LOH analysis are requested.

Segmentation-based detection of allelic imbalance and loss-of-heterozygosity in cancer cells using whole genome SNP arrays

We present a strategy for detection of loss-of-heterozygosity and allelic imbalance in cancer cells from whole genome single nucleotide polymorphism genotyping data. Using a dilution series of a tumor cell line mixed with its paired normal cell line and data generated on Affymetrix and Illumina platforms, including paired tumor-normal samples and tumors characterized by fluorescent in situ hybridization, we demonstrate a high sensitivity and specificity of the strategy for detecting both minute and gross allelic imbalances in heterogeneous tumor samples.

Cross-validation and bootstrapping are unreliable in small sample classification

The interest in statistical classification for critical applications such as diagnoses of patient samples based on supervised learning is rapidly growing. To gain acceptance in applications where the subsequent decisions have serious consequences, e.g. choice of cancer therapy, any such decision support system must come with a reliable performance estimate. Tailored for small sample problems, cross-validation (CV) and bootstrapping (BTS) have been the most commonly used methods to determine such estimates in virtually all branches of science for the last 20 years. Here, we address the often overlooked fact that the uncertainty in a point estimate obtained with CV and BTS is unknown and quite large for small sample classification problems encountered in biomedical applications and elsewhere. To avoid this fundamental problem of employing CV and BTS, until improved alternatives have been established, we suggest that the final classification performance always should be reported in the form of a Bayesian confidence interval obtained from a simple holdout test or using some other method that yields conservative measures of the uncertainty.

Array-based genomic screening at diagnosis and during follow-up in chronic lymphocytic leukemia

Background High-resolution genomic microarrays enable simultaneous detection of copy-number aberrations such as the known recurrent aberrations in chronic lymphocytic leukemia [del(11q), del(13q), del(17p) and trisomy 12], and copy-number neutral loss of heterozygosity. Moreover, comparison of genomic profiles from sequential patients’ samples allows detection of clonal evolution. Design and Methods We screened samples from 369 patients with newly diagnosed chronic lymphocytic leukemia from a population-based cohort using 250K single nucleotide polymorphism-arrays. Clonal evolution was evaluated in 59 follow-up samples obtained after 5–9 years. Results At diagnosis, copy-number aberrations were identified in 90% of patients; 70% carried known recurrent alterations, including del(13q) (55%), trisomy 12 (10.5%), del(11q) (10%), and del(17p) (4%). Additional recurrent aberrations were detected on chromosomes 2 (1.9%), 4 (1.4%), 8 (1.6%) and 14 (1.6%). Thirteen patients (3.5%) displayed recurrent copy-number neutral loss of heterozygosity on 13q, of whom 11 had concurrent homozygous del(13q). Genomic complexity and large 13q deletions correlated with inferior outcome, while the former was linked to poor-prognostic aberrations. In the follow-up study, clonal evolution developed in 8/24 (33%) patients with unmutated IGHV, and in 4/25 (16%) IGHV-mutated and treated patients. In contrast, untreated patients with mutated IGHV (n=10) did not acquire additional aberrations. The most common secondary event, del(13q), was detected in 6/12 (50%) of all patients with acquired alterations. Interestingly, aberrations on, for example, chromosome 6q, 8p, 9p and 10q developed exclusively in patients with unmutated IGHV. Conclusions Whole-genome screening revealed a high frequency of genomic aberrations in newly diagnosed chronic lymphocytic leukemia. Clonal evolution was associated with other markers of aggressive disease and commonly included the known recurrent aberrations.

Molecular Markers for Discrimination of Benign and Malignant Follicular Thyroid Tumors

Objective: To identify molecular markers useful for the diagnostic discrimination of benign and malignant follicular thyroid tumors. Methods: A panel of thyroid tumors was characterized with expression profiling using cDNA microarrays. A robust algorithm for gene selection was developed to identify molecular markers useful for the classification of heterogeneous tumor classes. The study included tumor tissue specimens from 10 patients with benign follicular adenomas and from 10 with malignant tumors. The malignant tumors mainly consisted of clinically relevant minimally invasive follicular carcinomas. The mRNA expression level of a candidate gene, FHL1, was evaluated in an independent series of 61 tumors. Results: 22 gene expression markers were identified as differentially expressed. Several of the identified genes, for example DIO1, CITED1, CA12 and FN1, have previously been observed as differentially expressed in various thyroid tumors. FHL1 was significantly underexpressed in carcinomas compared to adenomas in the independent panel of tumors. The results indicate that a small number of genes can be useful to distinguish follicular adenomas from follicular carcinomas. Conclusions: Our findings clearly corroborate previous studies and identify novel candidate molecular markers. These genes have the potential for molecular classification of follicular thyroid tumors and for providing improved understanding of the molecular mechanisms involved in thyroid malignancies.

STAT1 signaling is associated with acquired crossresistance to doxorubicin and radiation in myeloma cell lines

The myeloma cell line RPMI 8226/S and its doxorubicin resistant subline 8226/Dox40 were used as models to explore the potential importance of the STAT1 signaling pathway in drug and radiation resistance. The 40‐fold doxorubicin resistant subline 8226/Dox40 was found to be crossresistant to single doses of 4 and 8 Gy of radiation. A genome‐wide mRNA expression study comparing the 8226/Dox40 cell line to its parental line was performed to identify the underlying molecular mechanisms. Seventeen of the top 50 overexpressed genes have previously been implicated in the STAT1 signaling pathway. STAT1 was over expressed both at the mRNA and protein level. Moreover, analyses of nuclear extracts showed higher abundance of phosphorylated STAT1 (Tyr 701) in the resistant subline. Preexposure of the crossresistant cells to the STAT1 inhibiting drug fludarabine reduced expression of overexpressed genes and enhanced the effects of both doxorubicin and radiation. These results show that resistance to doxorubicin and radiation is associated with increased STAT1 signaling and can be modulated by fludarabine. The data support further development of therapies combining fludarabine and radiation.

High-density Screening Reveals a Different Spectrum of Genomic Aberrations in Chronic Lymphocytic Leukemia Patients with ‘Stereotyped’ IGHV3-21 and IGHV4-34 B-cell Receptors

Background The existence of multiple subsets of chronic lymphocytic leukemia expressing ‘stereotyped’ B-cell receptors implies the involvement of antigen(s) in leukemogenesis. Studies also indicate that ‘stereotypy’ may influence the clinical course of patients with chronic lymphocytic leukemia, for example, in subsets with stereotyped IGHV3-21 and IGHV4-34 B-cell receptors; however, little is known regarding the genomic profile of patients in these subsets. Design and Methods We applied 250K single nucleotide polymorphism-arrays to study copy-number aberrations and copy-number neutral loss-of-heterozygosity in patients with stereotyped IGHV3-21 (subset #2, n=29), stereotyped IGHV4-34 (subset #4, n=17; subset #16, n=8) and non-subset #2 IGHV3-21 (n=13) and non-subset #4/16 IGHV4-34 (n=34) patients. Results Over 90% of patients in subset #2 and non-subset #2 carried copy-number aberrations, whereas 75–76% of patients in subset #4 and subset #16 showed copy-number aberrations. Subset #2 and non-subset #2 patients also displayed a higher average number of aberrations compared to patients in subset #4. Deletion of 13q was the only known recurrent aberration detected in subset #4 (35%); this aberration was even more frequent in subset #2 (79%). del(11q) was more frequent in subset #2 and non-subset #2 (31% and 23%) patients than in subset #4 and non-subset #4/16 patients. Recurrent copy-number neutral loss-of-heterozygosity was mainly detected on chromosome 13q, independently of B-cell receptor stereotypy. Conclusions Genomic aberrations were more common in subset #2 and non-subset #2 than in subset #4. The particularly high frequency of del(11q) in subset #2 may be linked to the adverse outcome reported for patients in this subset. Conversely, the lower prevalence of copy-number aberrations and the absence of poor-prognostic aberrations in subset #4 may reflect an inherently low-proliferative disease, which would prevent accumulation of genomic alterations.

Quantification of Normal Cell Fraction and Copy Number Neutral LOH in Clinical Lung Cancer Samples Using SNP Array Data

Background Technologies based on DNA microarrays have the potential to provide detailed information on genomic aberrations in tumor cells. In practice a major obstacle for quantitative detection of aberrations is the heterogeneity of clinical tumor tissue. Since tumor tissue invariably contains genetically normal stromal cells, this may lead to a failure to detect aberrations in the tumor cells. Principal Finding Using SNP array data from 44 non-small cell lung cancer samples we have developed a bioinformatic algorithm that accurately models the fractions of normal and tumor cells in clinical tumor samples. The proportion of normal cells in combination with SNP array data can be used to detect and quantify copy number neutral loss-of-heterozygosity (CNNLOH) in the tumor cells both in crude tumor tissue and in samples enriched for tumor cells by laser capture microdissection. Conclusion Genome-wide quantitative analysis of CNNLOH using the CNNLOH Quantifier method can help to identify recurrent aberrations contributing to tumor development in clinical tumor samples. In addition, SNP-array based analysis of CNNLOH may become important for detection of aberrations that can be used for diagnostic and prognostic purposes.

Distinct gene expression profiles in subsets of chronic lymphocytic leukemia expressing stereotyped IGHV4-34 B-cell receptors

Background Numerous subsets of patients with chronic lymphocytic leukemia display similar immunoglobulin gene usage with almost identical complementarity determining region 3 sequences. Among IGHV4-34 cases, two such subsets with “stereotyped” B-cell receptors were recently identified, i.e. subset #4 (IGHV4-34/IGKV2-30) and subset #16 (IGHV4-34/IGKV3-20). Subset #4 patients appear to share biological and clinical features, e.g. young age at diagnosis and indolent disease, whereas little is known about subset #16 at a clinical level. Design and Methods We investigated the global gene expression pattern in sorted chronic lymphocytic leukemia cells from 25 subset/non-subset IGHV4-34 patients using Affymetrix gene expression arrays. Results Although generally few differences were found when comparing subset to non-subset 4/16 IGHV4-34 cases, distinct gene expression profiles were revealed for subset #4 versus subset #16. The differentially expressed genes, predominantly with lower expression in subset #4 patients, are involved in important cell regulatory pathways including cell-cycle control, proliferation and immune response, which may partly explain the low-proliferative disease observed in subset #4 patients. Conclusions Our novel data demonstrate distinct gene expression profiles among patients with stereotyped IGHV4-34 B-cell receptors, providing further evidence for biological differences in the pathogenesis of these subsets and underscoring the functional relevance of subset assignment based on B-cell receptor sequence features.

High-resolution genomic screening in mantle cell lymphoma—specific changes correlate with genomic complexity, the proliferation signature and survival

Mantle cell lymphoma (MCL) is characterized by the t(11;14)(q13;q32) and numerous copy number aberrations (CNAs). Recently, gene expression profiling defined a proliferation gene expression signature in MCL where high scores predict shorter survival. We investigated 31 MCL cases using high‐density single nucleotide polymorphism arrays and correlated CNA patterns with the proliferation signature and with clinical data. Many recurrent CNAs typical of MCL were detected, including losses at 1p (55%), 8p (29%), 9q (29%), 11q (55%), 13q (42%) and 17p (32%), and gains at 3q (39%), 8q (26%), 15q (23%) and 18q (23%). A novel deleted region at 20q (16%) contained only one candidate gene, ZFP64, a putative tumor suppressor. Unsupervised clustering identified subgroups with different patterns of CNAs, including a subset (19%) characterized by the presence of 11q loss in all cases and by the absence of 13q loss, and 3q and 7p gains. Losses at 1p, 8p, 13q and 17p were associated with increased genomic complexity. High proliferation signature scores correlated with increased number of large (>15 Mbp) CNAs (P = 0.03) as well as copy number gains at 7p (P = 0.02) and losses at 9q (P = 0.04). Furthermore, large/complex 13q losses were associated with improved survival (P < 0.05) as were losses/copy number neutral LOH at 19p13 (P = 0.01). In summary, this high‐resolution genomic analysis identified novel aberrations and revealed that several CNAs correlated with genomic complexity, the proliferation status and survival.