Christer Halldén

Combined Gene Expression and Genomic Profiling Define Two Intrinsic Molecular Subtypes of Urothelial Carcinoma and Gene Signatures for Molecular Grading and Outcome

In the present investigation, we sought to refine the classification of urothelial carcinoma by combining information on gene expression, genomic, and gene mutation levels. For these purposes, we performed gene expression analysis of 144 carcinomas, and whole genome array-CGH analysis and mutation analyses of FGFR3, PIK3CA, KRAS, HRAS, NRAS, TP53, CDKN2A, and TSC1 in 103 of these cases. Hierarchical cluster analysis identified two intrinsic molecular subtypes, MS1 and MS2, which were validated and defined by the same set of genes in three independent bladder cancer data sets. The two subtypes differed with respect to gene expression and mutation profiles, as well as with the level of genomic instability. The data show that genomic instability was the most distinguishing genomic feature of MS2 tumors, and that this trait was not dependent on TP53/MDM2 alterations. By combining molecular and pathologic data, it was possible to distinguish two molecular subtypes of T(a) and T(1) tumors, respectively. In addition, we define gene signatures validated in two independent data sets that classify urothelial carcinoma into low-grade (G(1)/G(2)) and high-grade (G(3)) tumors as well as non-muscle and muscle-invasive tumors with high precisions and sensitivities, suggesting molecular grading as a relevant complement to standard pathologic grading. We also present a gene expression signature with independent prognostic effect on metastasis and disease-specific survival. We conclude that the combination of molecular and histopathologic classification systems might provide a strong improvement for bladder cancer classification and produce new insights into the development of this tumor type.

Competition as a source of errors in RAPD analysis.

We have used artificial 1∶1 DNA mixtures of all pairwise combinations of four doubled haploid Brassica napus lines to test the ability of RAPDs to function as reliable dominant genetic markers. In situations where a specific RAPD band is present in one homozygous line but absent in the other, the band is expected in the artificial heterozygote, i.e. in the 1∶1 DNA mixture. In 84 of all 613 heterozygous situations analysed, the expected band failed to amplify in the RAPD reaction. Thus, RAPD markers will lead to an erroneous genetic interpretation in 14% of all cases. In contrast, the formation of non-parental heteroduplex bands was found at a frequency of only 0.2%. Analysis of 1∶ 1 mixtures using (1) a different set of optimized reaction conditions and (2) a material with low genomic complexity (Bacillus cereus) gave identical results. Serial dilutions of one genome into another, in steps of 10%, showed that all of the polymorphic bands decreased in intensity as a linear function of their respective proportion in the mixture. In dilutions with water no differences in band intensity were detected. Thus, competition occurs in the amplification of all RAPD fragments and is a major source of genotyping errors in RAPD analysis.

Evaluation of RFLP and RAPD markers in a comparison of Brassica napus breeding lines

RFLP and RAPD markers were evaluated and compared for their ability to determine genetic relationships in a set of three B. napus breeding lines. Using a total of 50 RFLP and 92 RAPD markers, the relatedness between the lines was determined. In total, the RFLP and the RAPD analysis revealed more than 500 and 400 bands, respectively. The relative frequencies of loci with allele differences were estimated from the band data. The RFLP and RAPD marker sets detected very similar relationships among the three lines, consistent with known pedigree data. Bootstrap analyses showed that the use of approximately 30 probes or primers would have been sufficient to achieve these relationships. This indicates that RAPD markers have the same resolving power as RFLP markers when used on exactly the same set of B. napus genotypes. Since RAPD markers are easier and quicker to use, these markers may be preferred in applications where the relationships between closely-related breeding lines are of interest. The use of RAPD markers in fingerprinting applications may, however, not be warranted, and this is discussed in relation to the reliability of RAPD markers.

Important research questions in allergy and related diseases: 3-chronic rhinosinusitis and nasal polyposis - a GALEN study.

Chronic rhinosinusitis is one of the most common health care challenges, with significant direct medical costs and severe impact on lower airway disease and general health outcomes. The diagnosis of chronic rhinosinusitis (CRS) currently is based on clinical signs, nasal endoscopy and CT scanning, and therapeutic recommendations are focussing on 2 classes of drugs, corticosteroids and antibiotics. A better understanding of the pathogenesis and the factors amplifying mucosal inflammation therefore seems to be crucial for the development of new diagnostic and therapeutic tools. In an effort to extend knowledge in this area, the WP 2.7.2 of the GA2LEN network of excellence currently collects data and samples of 1000 CRS patients and 250 control subjects. The main objective of this project is to characterize patients with upper airway disease on the basis of clinical parameters, infectious agents, inflammatory mechanisms and remodeling processes. This collaborative research will result in better knowledge on patient phenotypes, pathomechanisms, and subtypes in chronic rhinosinusitis. This review summarizes the state of the art on chronic rhinosinusitis and nasal polyposis in different aspects of the disease. It defines potential gaps in the current research, and points to future research perspectives and targets.

A Systematic Study of Gene Mutations in Urothelial Carcinoma; Inactivating Mutations in TSC2 and PIK3R1.

Background Urothelial carcinoma (UC) is characterized by frequent gene mutations of which activating mutations in FGFR3 are the most frequent. Several downstream targets of FGFR3 are also mutated in UC, e.g., PIK3CA, AKT1, and RAS. Most mutation studies of UCs have been focused on single or a few genes at the time or been performed on small sample series. This has limited the possibility to investigate co-occurrence of mutations. Methodology/Principal Findings We performed mutation analyses of 16 genes, FGFR3, PIK3CA, PIK3R1 PTEN, AKT1, KRAS, HRAS, NRAS, BRAF, ARAF, RAF1, TSC1, TSC2, APC, CTNNB1, and TP53, in 145 cases of UC. We show that FGFR3 and PIK3CA mutations are positively associated. In addition, we identified PIK3R1 as a target for mutations. We demonstrate a negative association at borderline significance between FGFR3 and RAS mutations, and show that these mutations are not strictly mutually exclusive. We show that mutations in BRAF, ARAF, RAF1 rarely occurs in UC. Our data emphasize the possible importance of APC signaling as 6% of the investigated tumors either showed inactivating APC or activating CTNNB1 mutations. TSC1, as well as TSC2, that constitute the mTOR regulatory tuberous sclerosis complex were found to be mutated at a combined frequency of 15%. Conclusions/Significance Our data demonstrate a significant association between FGFR3 and PIK3CA mutations in UC. Moreover, the identification of mutations in PIK3R1 further emphasizes the importance of the PI3-kinase pathway in UC. The presence of TSC2 mutations, in addition to TSC1 mutations, underlines the involvement of mTOR signaling in UC.

Susceptibility Loci Associated with Prostate Cancer Progression and Mortality

Purpose: Prostate cancer is a heterogenous disease with a variable natural history that is not accurately predicted by currently used prognostic tools. Experimental Design: We genotyped 798 prostate cancer cases of Ashkenazi Jewish ancestry treated for localized prostate cancer between June 1988 and December 2007. Blood samples were prospectively collected and de-identified before being genotyped and matched to clinical data. The survival analysis was adjusted for Gleason score and prostate-specific antigen. We investigated associations between 29 single nucleotide polymorphisms (SNP) and biochemical recurrence, castration-resistant metastasis, and prostate cancer–specific survival. Subsequently, we did an independent analysis using a high-resolution panel of 13 SNPs. Results: On univariate analysis, two SNPs were associated (P < 0.05) with biochemical recurrence, three SNPs were associated with clinical metastases, and one SNP was associated with prostate cancer–specific mortality. Applying a Bonferroni correction (P < 0.0017), one association with biochemical recurrence (P = 0.0007) was significant. Three SNPs showed associations on multivariable analysis, although not after correcting for multiple testing. The secondary analysis identified an additional association with prostate cancer–specific mortality in KLK3 (P < 0.0005 by both univariate and multivariable analysis). Conclusions: We identified associations between prostate cancer susceptibility SNPs and clinical end points. The rs61752561 in KLK3 and rs2735839 in the KLK2-KLK3 intergenic region were strongly associated with prostate cancer–specific survival, and rs10486567 in the 7JAZF1 gene were associated with biochemical recurrence. A larger study will be required to independently validate these findings and determine the role of these SNPs in prognostic models. Clin Cancer Res; 16(10); 2819–32. ©2010 AACR.

Chloroplast DNA indicates a single origin of the allotetraploid Arabidopsis suecica.

DNA sequencing was performed on up to 12 chloroplast DNA regions [giving a total of 4288 base pairs (bp) in length] from the allopolyploid Arabidopsis suecica (48 accessions) and its two parental species, A. thaliana (25 accessions) and A. arenosa (seven accessions). Arabidopsis suecica was identical to A. thaliana at all 93 sites where A. thaliana and A. arenosa differed, thus showing that A. thaliana is the maternal parent of A. suecica. Under the assumption that A. thaliana and A. arenosa separated 5 million years ago, we estimated a substitution rate of 2.9 × 10−9 per site per year in noncoding single copy sequence. Within A. thaliana we found 12 substitution (single bp) and eight insertion/deletion (indel) polymorphisms, separating the 25 accessions into 15 haplotypes. Eight of the A. thaliana accessions from central Sweden formed one cluster, which was separated from a cluster consisting of central European and extreme southern Swedish accessions. This latter cluster also included the A. suecica accessions, which were all identical except for one 5 bp indel. We interpret this low level of variation as a strong indication that A. suecica effectively has a single origin, which we dated at 20 000 years ago or more.

Blood biomarker levels to aid discovery of cancer-related single-nucleotide polymorphisms: kallikreins and prostate cancer.

Polymorphisms associated with prostate cancer include those in three genes encoding major secretory products of the prostate: KLK2 (encoding kallikrein-related peptidase 2; hK2), KLK3 (encoding prostate-specific antigen; PSA), and MSMB (encoding β-microseminoprotein). PSA and hK2, members of the kallikrein family, are elevated in sera of men with prostate cancer. In a comprehensive analysis that included sequencing of all coding, flanking, and 2 kb of putative promoter regions of all 15 kallikrein (KLK) genes spanning ≈280 kb on chromosome 19q, we identified novel single-nucleotide polymorphisms (SNP) and genotyped 104 SNPs in 1,419 cancer cases and 736 controls in Cancer Prostate in Sweden 1, with independent replication in 1,267 cases and 901 controls in Cancer Prostate in Sweden 2. This verified prior associations of SNPs in KLK2 and in MSMB (but not in KLK3) with prostate cancer. Twelve SNPs in KLK2 and KLK3 were associated with levels of PSA forms or hK2 in plasma of control subjects. Based on our comprehensive approach, this is likely to represent all common KLK variants associated with these phenotypes. A T allele at rs198977 in KLK2 was associated with increased cancer risk and a striking decrease of hK2 levels in blood. We also found a strong interaction between rs198977 genotype and hK2 levels in blood in predicting cancer risk. Based on this strong association, we developed a model for predicting prostate cancer risk from standard biomarkers, rs198977 genotype, and rs198977 × hK2 interaction; this model had greater accuracy than did biomarkers alone (area under the receiver operating characteristic curve, 0.874 versus 0.866), providing proof in principle to clinical application for our findings. Cancer Prev Res; 3(5); 611–9. ©2010 AACR.

Evaluation of Multiple Risk-Associated Single Nucleotide Polymorphisms Versus Prostate-Specific Antigen at Baseline to Predict Prostate Cancer in Unscreened Men

BACKGROUND Although case-control studies have identified numerous single nucleotide polymorphisms (SNPs) associated with prostate cancer, the clinical role of these SNPs remains unclear. OBJECTIVE Evaluate previously identified SNPs for association with prostate cancer and accuracy in predicting prostate cancer in a large prospective population-based cohort of unscreened men. DESIGN, SETTING, AND PARTICIPANTS This study used a nested case-control design based on the Malmö Diet and Cancer cohort with 943 men diagnosed with prostate cancer and 2829 matched controls. Blood samples were collected between 1991 and 1996, and follow-up lasted through 2005. MEASUREMENTS We genotyped 50 SNPs, analyzed prostate-specific antigen (PSA) in blood from baseline, and tested for association with prostate cancer using the Cochran-Mantel-Haenszel test. We further developed a predictive model using SNPs nominally significant in univariate analysis and determined its accuracy to predict prostate cancer. RESULTS AND LIMITATIONS Eighteen SNPs at 10 independent loci were associated with prostate cancer. Four independent SNPs at four independent loci remained significant after multiple test correction (p<0.001). Seven SNPs at five independent loci were associated with advanced prostate cancer defined as clinical stage≥T3 or evidence of metastasis at diagnosis. Four independent SNPs were associated with advanced or aggressive cancer defined as stage≥T3, metastasis, Gleason score≥8, or World Health Organization grade 3 at diagnosis. Prostate cancer risk prediction with SNPs alone was less accurate than with PSA at baseline (area under the curve of 0.57 vs 0.79), with no benefit from combining SNPs with PSA. This study is limited by our reliance on clinical diagnosis of prostate cancer; there are likely undiagnosed cases among our control group. CONCLUSIONS Only a few previously reported SNPs were associated with prostate cancer risk in the large prospective Diet and Cancer cohort in Malmö, Sweden. SNPs were less useful in predicting prostate cancer risk than PSA at baseline.

Error Rates and Polymorphism Frequencies for Three RAPD Protocols

Three amplification protocols were analyzed for error rate and generation of polymorphisms during RAPD analysis. Using a set of 240 primers, the protocols detected similar frequencies of polymorphisms in two inbred sugar beet lines. The error rate was investigated by including a 1:1 mixture of DNA from the two lines in all analyses. Similar error rates, approximately 18%, were detected by the three protocols. Thus, altered amplification conditions did not substantially affect the error rate during RAPD analysis. For each of the three possible pairs of protocols, a positive correlation was obtained for primer and number of polymorphisms. Thus, a set of highly polymorphic RAPD primers can be used effectively, without prior screening, to detect polymorphisms for each protocol.