A critical view on autoantibodies in lupus nephritis: Concrete knowledge based on evidence.

Deposition of autoantibodies in glomeruli is a key factor in the development of lupus nephritis (LN). For a long time, anti-dsDNA and anti-C1q antibodies were thought to be the main cause of the kidney damage. However, recent studies have shown that the list of autoantibidies that have renal tropism and deposit in the kidney in LN is increasing and the link between anti-dsDNA and renal pathology is weak due to potential confounders. Aspecific bindings of dsDNA with cationic antibodies and of anti-dsDNA with several renal antigens such as actinin, laminin, entactin, and annexinA2 raised doubts about the specific target of these antibodies in the kidney. Moreover, the isotype of anti-dsDNA in SLE and LN has never received adequate interest until the recent observation that IgG2 are preponderant over IgG1, IgG3 and IgG4. Based on the above background, recent studies investigated the involvement of anti-dsDNA IgG2 and of other antibodies in LN. It was concluded that circulating anti-dsDNA IgG2 levels do not distinguish between LN versus non-renal SLE, and, in patients with LN, their levels do not change over time. Circulating levels of other antibodies such as anti-ENO1 and anti-H2 IgG2 were, instead, higher in LN vs non-renal SLE at the time of diagnosis and decreased following therapies. Finally, new classes of renal antibodies that potentially modify the anti-inflammatory response in the kidney are emerging as new co-actors in the pathogenetic scenario. They have been defined as 'second wave antibodies' for the link with detoxifying mechanisms limiting the oxidative stress in glomeruli that are classically stimulated in a second phase of inflammation. These findings have important clinical implications that may modify the laboratory approach to LN. Serum levels of anti-ENO1 and anti-H2 IgG2 should be measured in the follow up of patients for designing the length of therapies and identify those patients who respond to treatments. Anti-SOD2 could help to monitor and potentiate the anti-inflammatory response in the kidney.

Discovery of anti-Formin-like 1 protein (FMNL1) antibodies in membranous nephropathy and other glomerular diseases.

Evidence has shown that podocyte-directed autoantibodies can cause membranous nephropathy (MN). In the present work we investigated sera of MN patients using a high-density peptide array covering the whole coding sequences of the human genome encompassing 7,499,126 tiled peptides. A panel of 21 proteins reactive to MN sera were identified. We focused our attention on Formin-like 1 (FMNL1), a protein expressed by macrophages in MN patients tissues. High levels of anti-FMNL1 IgG4 were demonstrated in sera of MN patients with an orthogonal methodology (ELISA) contemporary demonstrating FMNL1 positive cells in kidney co-staining with CD68 in glomeruli. High levels of circulating anti-FMNL1 IgG4 were associated with lack of remission of proteinuria, potentially indicating that autoantibodies directed against cells other than podocytes, involved in tissue repair, might play a role in MN disease progression. High serum levels of anti-FMNL1 IgGs were also observed in other non-autoimmune glomerolonephrites, i.e. idiopathic and genetic FSGS, IgAGN. These findings are suggestive of a broader role of those autoantibodies in other glomerular disease conditions.

Comprehensive Profiling of the Rheumatoid Arthritis Antibody Repertoire.

OBJECTIVE: Autoantibodies against citrullinated proteins are found in 64-89% of rheumatoid arthritis (RA) patients, with 88-99% specificity. This study was undertaken to create an unbiased, comprehensive profile of serum antibodies against the human proteome, including the citrullinome and the homocitrullinome, in RA patients, using a high-density peptide array. METHODS: Our high-density peptide array, consisting of >4.6 million peptides, contained the entire annotated human proteome. The 20,246 proteins were represented as overlapping 16-mer peptides. In addition to native peptides, citrullinated and homocitrullinated peptides were included, as substitutions for arginine and lysine, and provided a comprehensive screen against all possible epitopes. Twenty-six serum samples (from 8 controls and 18 RA patients) were profiled on the high-density peptide array. Using RA-specific epitopes, we constructed an 8-epitope diagnostic biomarker on a Gyrolab xPlore instrument with a cohort of 92 serum samples (from 29 controls and 63 RA patients). The diagnostic biomarker was further validated with an independent cohort of 181 serum samples (from 54 controls and 127 RA patients). RESULTS: In the initial cohort the diagnostic performance of the 8-epitope biomarker yielded 96.6% specificity and 92.1% sensitivity. The overall diagnostic performance in the validation cohort was 94.4% specificity and 85% sensitivity. In both cohorts, the performance of the 8-epitope diagnostic biomarker compared favorably against the Abnova cyclic citrullinated peptide 2 (CCP2) assay. Using data from the peptide array, we identified novel RA-specific epitopes and formed the basis of a new RA diagnostic assay. CONCLUSION: Comprehensive antibody profiling using a high-density peptide array not only identified novel RA-specific epitopes but also allowed us to construct a novel diagnostic biomarker that is as specific as and more sensitive than the Abnova CCP2 assay.

Whole Genome-Derived Tiled Peptide Arrays Detect Prediagnostic Autoantibody Signatures in Non-Small-Cell Lung Cancer.

The majority of non-small-cell lung cancer (NSCLC) cases are diagnosed at advanced stages, primarily because earlier stages of the disease are either asymptomatic or may be attributed to other causes such as infection or long-term effects from smoking. Therefore, early detection of NSCLC would likely increase response and survival rates due to timely intervention. Here, we utilize a novel approach based on whole genome-derived tiled peptide arrays to identify epitopes associated with autoantibody reactivity in NSCLC as a potential means for early detection. Arrays consisted of 2,781,902 tiled peptides representing 20,193 proteins encoded in the human genome. Analysis of 86 prediagnostic samples and 86 matched normal controls from a high-risk cohort revealed 48 proteins with three or more reactive epitopes in NSCLC samples relative to controls. Independent mass spectrometry analysis identified 40 of the 48 proteins in prediagnostic sera from NSCLC samples, of which, 21 occurred in the immunoglobulin-bound fraction. In addition, 63 and 34 proteins encompassed three or more epitopes that were distinct for squamous cell lung cancer and lung adenocarcinoma, respectively. Collectively, these data show that tiled peptide arrays provide a means to delineate epitopes encoded across the genome that trigger an autoantibody response associated with tumor development. SIGNIFICANCE: This study provides a modality for early diagnosis of NSCLC for precision oncology that can be applied to other cancer types.

Identification of somatic mutations in non-small cell lung carcinomas using whole-exome sequencing.

Lung cancer is the leading cause of cancer-related death, with non-small cell lung cancer (NSCLC) being the predominant form of the disease. Most lung cancer is caused by the accumulation of genomic alterations due to tobacco exposure. To uncover its mutational landscape, we performed whole-exome sequencing in 31 NSCLCs and their matched normal tissue samples. We identified both common and unique mutation spectra and pathway activation in lung adenocarcinomas and squamous cell carcinomas, two major histologies in NSCLC. In addition to identifying previously known lung cancer genes (TP53, KRAS, EGFR, CDKN2A and RB1), the analysis revealed many genes not previously implicated in this malignancy. Notably, a novel gene CSMD3 was identified as the second most frequently mutated gene (next to TP53) in lung cancer. We further demonstrated that loss of CSMD3 results in increased proliferation of airway epithelial cells. The study provides unprecedented insights into mutational processes, cellular pathways and gene networks associated with lung cancer. Of potential immediate clinical relevance, several highly mutated genes identified in our study are promising druggable targets in cancer therapy including ALK, CTNNA3, DCC, MLL3, PCDHIIX, PIK3C2B, PIK3CG and ROCK2.

Interpreting aCGH-defined karyotypic changes in gliomas using copy number status, loss of heterozygosity and allelic ratios.

We have used SNP mapping arrays to simultaneously record copy number changes, loss of heterozygosity and allele ratios (ploidy) in a series of 13 gliomas. This combined analysis has defined novel amplification events in this tumor type involving chr1:241544532-243005121 and chr18:54716681-54917277 which contain the AKT3 and ZNF532 genes, respectively. The high resolution of this analysis has also identified homozygous deletions involving chr17:25600031-26490848 and Chr19:53883612-55061878. Throughout the karyotypes of these tumors, the combined analysis revealed counter intuitive relationships between copy number and LOH that requires reinterpretation of the significance of copy number gains and losses. It was not uncommon to observe copy number gains that were associated with loss of heterozygosity as well as copy number losses that were not. These events appeared to be related to ploidy status in the tumors as determined using allelic ratio calculations. Overall, this analysis of gliomas provides evidence for the need to perform more comprehensive interpretation of the CGH data beyond copy number analysis alone to evaluate the significance of individual events in the karyotypes.

Application of oligonucleotides arrays for coincident comparative genomic hybridization, ploidy status and loss of heterozygosity studies in human cancers.

Many oligonucleotide arrays comprise of spotted short oligonucleotides from throughout the genome under study. Hybridization of tumor DNA samples to these arrays will provide copy number estimates at each reference point with varying degrees of accuracy. In addition to copy number changes, however, tumors often undergo loss of heterozygosity for specific regions of the genome without copy number changes and these genetic changes can only be identified using arrays that identify polymorphic alleles at each reference point. In addition, because the hybridization intensity can be measured at each of the allelic variants, allelic ratios can be established which give indications of ploidy status in the tumor which is not generally possible using most other oligonucleotide array designs. The only arrays currently available that simultaneously report copy number, ploidy, and loss of heterozygosity are the Affymetrix SNP mapping arrays. In this review, the features of the SNP mapping arrays are described and computational tools explored which allow the maximum genetic information to be extracted from the experiment. Although the methodologies to generate the SNP data are now well established, approaches to interpret the data are only just being developed. From our experience using these arrays, we provide insights into how to evaluate the SNP data to report copy number changes, loss of heterozygosity, and ploidy in the same tumor samples using a single array.

Ploidy status and copy number aberrations in primary glioblastomas defined by integrated analysis of allelic ratios, signal ratios and loss of heterozygosity using 500K SNP Mapping Arrays.

BACKGROUND: Genomic hybridization platforms, including BAC-CGH and genotyping arrays, have been used to estimate chromosome copy number (CN) in tumor samples by detecting the relative strength of genomic signal. The methods rely on the assumption that the predominant chromosomal background of the samples is diploid, an assumption that is frequently incorrect for tumor samples. In addition to generally greater resolution, an advantage of genotyping arrays over CGH arrays is the ability to detect signals from individual alleles, allowing estimation of loss-of-heterozygosity (LOH) and allelic ratios to enhance the interpretation of copy number alterations. Copy number events associated with LOH potentially have the same genetic consequences as deletions. RESULTS: We have utilized allelic ratios to detect patterns that are indicative of higher ploidy levels. An integrated analysis using allelic ratios, total signal and LOH indicates that many or most of the chromosomes from 24 glioblastoma tumors are in fact aneuploid. Some putative whole-chromosome losses actually represent trisomy, and many apparent sub-chromosomal losses are in fact relative losses against a triploid or tetraploid background. CONCLUSION: These results suggest a re-interpretation of previous findings based only on total signal ratios. One interesting observation is that many single or multiple-copy deletions occur at common putative tumor suppressor sites subsequent to chromosomal duplication; these losses do not necessarily result in LOH, but nonetheless occur in conspicuous patterns. The 500 K Mapping array was also capable of detecting many sub-mega base losses and gains that were overlooked by CGH-BAC arrays, and was superior to CGH-BAC arrays in resolving regions of complex CN variation.

Array comparative genome hybridization analysis of acute lymphoblastic leukaemia and acute megakaryoblastic leukaemia in patients with Down syndrome.

Twenty-five cases of B-cell precursor acute lymphoblastic leukaemia (ALL) from Down syndrome (DS) patients were analyzed using array comparative genomic hybridization (aCGH) and compared with two other subgroups of non-DS patients with ALL; five cases with high-hyperdiploidy (HH) and nine cases with ETV6-RUNX1 positive clones. Seven cases of DS-acute megakaryoblastic leukaemia (AMKL) were also included, DS-ALL cases showed relatively stable karyotypes with cryptic losses and gains that most frequently involved chromosomes X, 1, 2, 9, 11, 16, and 17. The most consistent change involved a deletion in 2p, spanning region Chr2:88273220-91084234, which in some cases appeared to be homozygous. ALL from non-DS patients showed a similar overall karyotypic stability, although gains of chromosome 21 were infrequent in the ETV6-RUNX1 positive cases. The most consistent change in this group involved a 12p deletion, where Chr12:10383878-16017619 defined the common region of overlap. All HH-ALL karyotypes showed variable gains of chromosome 21. This overall analysis supports the suggestion that, although constitutional trisomy 21 predisposes to ALL/AMKL, the cytogenetic changes associated with DS-ALL in particular, are most similar to those found in non-DS ETV6-RUNX1 positive ALL. The HH-ALL group, however, undergoes distinct karyotypic evolution not dependent on chromosome translocation/deletion events.

Comprehensive analysis of loss of heterozygosity events in glioblastoma using the 100K SNP mapping arrays and comparison with copy number abnormalities defined by BAC array comparative genomic hybridization.

We have undertaken an extensive high-resolution analysis of loss of heterozygosity (LOH) in 30 high grade gliomas using the Affymetrix 100K SNP mapping array. Only 70% of LOH events were accompanied by a copy number loss (CNA(loss)), and of the other 30%, the distal region of 17p preferentially showed copy number neutral (CNN)-associated LOH. Combined analysis of CNA(loss) and LOH using MergeLevels analysis software predicts whether the observed losses occurred on a diploid or tetraploid background. In a side-by-side comparison between SNP and bacterial artificial chromosome (BAC) arrays, the overall identification of CNAs was similar on both platforms. The resolution provided by the SNP arrays, however, allowed a considerably more accurate definition of breakpoints as well as defining small events within the cancer genomes, which could not be detected on BAC arrays. CNN LOH was only detected by the SNP arrays, as was ploidy prediction. From our analysis, therefore, it is clear that simultaneously defining CNAs and CNN-LOH using the SNP platform provides a higher resolution and more complete analysis of the genetic events that have occurred within tumor cells. Our extensive analysis of SNP array data has also allowed an objective assessment of threshold LOH scores that can accurately predict LOH. This capability has important implications for interpretation of LOH events since they have consistently been used to localize potential tumor suppressor genes within the cancer genome.

Identification of genes involved in squamous cell carcinoma of the lung using synchronized data from DNA copy number and transcript expression profiling analysis.

Lung cancer is the leading cause of cancer deaths in the world and squamous cell carcinoma (SqCC) is the second most common in this group. Genomic DNA copy number alterations are fundamental genetic events in the development and progression of SqCC as well as other epithelial-derived cancers. The ability to identify tumor suppressor genes (TSGs) and oncogenes that are affected during tumor initiation and progression could facilitate the identification of novel molecular targets for therapeutic intervention and provide diagnostic biomarkers. Despite the association of many genetic alterations in lung cancer the molecular mechanisms of tumor progression remain ambiguous since often too many candidates are revealed using conventional genetic microarray analysis. To overcome this limitation, we have identified genes in SqCC which show concordant gene expression changes defined using microarray analysis with DNA copy number alterations defined by BAC-array comparative genomic hybridization (aCGH) in the same tumors. An in-house overlay algorithm was used to synchronize the data resulting from the two analyses. Although the expression levels of many genes were altered when compared to normal controls, those which correlated with copy number changes were far fewer, providing a manageable number for biological studies. We identified over 2000 genes which displayed both gene expression alterations and mapped to BACs which demonstrated a corresponding loss or gain. A further stringent statistical analysis identified minimal regions of overlap for losses or gains which displayed a coincident decrease or increase in the expression of genes mapping to those regions. Consistent gains involved 3q23-q29, 5p15.1-q11.1 and chromosomes 18 and 20, while consistent losses involved 3p26.3-p12.3, 9p24.3-q34.3, and chromosomes 17 and 19. The concordance finding between these two approaches suggests that DNA copy number alterations can directly influence gene expression patterns that impact on tumorigenesis in SqCC of the lung.

Gain of 1q is a potential univariate negative prognostic marker for survival in medulloblastoma.

PURPOSE: Tumor risk stratification during diagnosis is paramount for children with medulloblastomas, primarily because very young patients (<3 years) suffer cognitive deficits from radio- and chemotherapy sequelae. Thus, distinguishing tumors that are biologically more aggressive is essential for medulloblastoma management to maximize the delay in radiation treatment without adversely affecting survival outcome. In this context, current strategies for risk assessment, which are based on clinical parameters, remain unsatisfactory. EXPERIMENTAL DESIGN: Array-based comparative genomic hybridization (aCGH) was used to identify chromosomal copy number abnormalities in a cohort of 49 medulloblastoma tumors. Based on the karyotypes generated from aCGH analysis, each tumor was scored for copy number abnormalities, and the log-rank test was used to evaluate whether any cytogenetic events were associated with survival. RESULTS: A single copy gain of 1q was shown to be a negative prognostic marker for survival in medulloblastomas with high statistical significance (P < 0.0001, log-rank test). CONCLUSION: A gain of 1q provides a potential means of predicting overall survival in medulloblastoma.

Candidate glioblastoma development gene identification using concordance between copy number abnormalities and gene expression level changes.

Copy number abnormalities (CNAs) in tumor cells are presumed to affect expression levels of genes located in region of abnormality. To investigate this relationship we have surveyed the losses, gains and amplifications in 30 glioblastomas using array comparative genome hybridization and compared these data with gene expression changes in the same tumors using the Affymetrix U133Plus2.0 oligonucleotide arrays. The two datasets were overlaid using our in-house overlay tool which highlights concordance between CNAs and expression level changes for the same tumors. In this survey we have highlighted genes frequently overexpressed in amplified regions on chromosomes 1, 4, 11, and 12 and have identified novel amplicons on these chromosomes. Deletions of specific regions on chromosomes 9, 10, 11, 14, and 15 have also been correlated with reduced gene expression in the regions of minimal overlap. In addition we describe a novel approach for comparing gene expression levels between tumors based on the presence or absence of chromosome CNAs. This genome wide screen provides an efficient and comprehensive survey of genes which potentially serve as the drivers for the CNAs in GBM.

Genome wide copy number abnormalities in pediatric medulloblastomas as assessed by array comparative genome hybridization.

Array-based comparative genomic hybridization was used to characterize 22 medulloblastomas in order to precisely define genetic alterations in these malignant childhood brain tumors. The 17p(-)/17q(+) copy number abnormality (CNA), consistent with the formation of isochromosome 17q, was the most common event (8/22). Amplifications in this series included MYCL, MYCN and MYC previously implicated in medulloblastoma pathogenesis, as well as novel amplicons on chromosomes 2, 4, 11 and 12. Losses involving chromosomes 1, 2, 8, 10, 11, 16 and 19 and gains of chromosomes 4, 7, 8, 9 and 18 were seen in greater than 20% of tumors in this series. A homozygous deletion in 11p15 defines the minimal region of loss on this chromosome arm. In order to map the minimal regions involved in losses, gains and amplifications, we combined aCGH data from this series with that of two others obtained using the same RPCI BAC arrays. As a result of this combined analysis of 72 samples, we have defined specific regions on chromosomes 1, 8p, 10q, 11p and 16q which are frequently involved in CNAs in medulloblastomas. Using high density oligonucleotide expression arrays, candidate genes were identified within these consistently involved regions in a subset of the tumors.

Overlay tool for aCGHViewer: an analysis module built for aCGHViewer used to perform comparisons of data derived from different microarray platforms.

The Overlay Tool has been developed to combine high throughput data derived from various microarray platforms. This tool analyzes high-resolution correlations between gene expression changes and either copy number abnormalities (CNAs) or loss of heterozygosity events detected using array comparative genomic hybridization (aCGH). Using an overlay analysis which is designed to be performed using data from multiple microarray platforms on a single biological sample, the Overlay Tool identifies potentially important genes whose expression profiles are changed as a result of losses, gains and amplifications in the cancer genome. In addition, the Overlay Tool will incorporate loss of heterozygosity (LOH) probability data into this overlay procedure. To facilitate this analysis, we developed an application which computationally combines two or more high throughput datasets (e.g. aCGH/expression) into a single categorized dataset for visualization and interrogation using a gene-centric approach. As such, data from virtually any microarray platform can be incorporated without the need to remap entire datasets individually. The resultant categorized (overlay) data set can be conveniently viewed using our in-house visualization tool, aCGHViewer (Shankar et al. 2006), which serves as a conduit to public databases such as UCSC and NCBI, to rapidly investigate genes of interest.

Overlay analysis of the oligonucleotide array gene expression profiles and copy number abnormalities as determined by array comparative genomic hybridization in medulloblastomas.

Combined analysis of gene expression array data and array-based comparative genomic hybridization data have been used in a series of 26 pediatric brain tumors to define up- and downregulated genes that coincide with losses, gains, and amplifications involving specific chromosome regions. Frequent losses were defined in chromosome arms 3q, 6q, 8p, 10q, 16q, 17p, and gains were identified in chromosome 7, and chromosome arms 9p and 17q. Amplification of a 2p region was seen in only one tumor, which corresponded to increased expression of the MYCN and DDX1 genes. To facilitate the analysis of the two data sets, we have developed a custom overlay tool that defines genes that are underexpressed in regions of deletions and overexpressed in regions of gain, across the genome and specifically within regions showing recurrent involvement in medulloblastomas.