Mutational profile and prognostic significance of TP53 in diffuse large B-cell lymphoma patients treated with R-CHOP: report from an International DLBCL Rituximab-CHOP Consortium Program Study.

TP53 mutation is an independent marker of poor prognosis in patients with diffuse large B-cell lymphoma (DLBCL) treated with cyclophosphamide, hydroxydaunorubicin, vincristine, and prednisone (CHOP) therapy. However, its prognostic value in the rituximab immunochemotherapy era remains undefined. In the present study of a large cohort of DLBCL patients treated with rituximab plus CHOP (R-CHOP), we show that those with TP53 mutations had worse overall and progression-free survival compared with those without. Unlike earlier studies of patients treated with CHOP, TP53 mutation has predictive value for R-CHOP-treated patients with either the germinal center B-cell or activated B-cell DLBCL subtypes. Furthermore, we identified the loop-sheet-helix and L3 motifs in the DNA-binding domain to be the most critical structures for maintaining p53 function. In contrast, TP53 deletion and loss of heterozygosity did not confer worse survival. If gene mutation data are not available, immunohistochemical analysis showing > 50% cells expressing p53 protein is a useful surrogate and was able to stratify patients with significantly different prognoses. We conclude that assessment of TP53 mutation status is important for stratifying R-CHOP-treated patients into distinct prognostic subsets and has significant value in the design of future therapeutic strategies.

Patients with diffuse large B-cell lymphoma of germinal center origin with BCL2 translocations have poor outcome, irrespective of MYC status: a report from an International DLBCL rituximab-CHOP Consortium Program Study.

Diffuse large B-cell lymphoma can be classified by gene expression profiling into germinal center and activated B-cell subtypes with different prognoses after rituximab-CHOP. The importance of previously recognized prognostic markers, such as Bcl-2 protein expression and BCL2 gene abnormalities, has been questioned in the new therapeutic era. We analyzed Bcl-2 protein expression, and BCL2 and MYC gene abnormalities by interphase fluorescence in situ hybridization in 327 patients with de novo disease treated with rituximab-CHOP. Isolated BCL2 and MYC rearrangements were not predictive of outcome in our patients as a whole, but only in those with the germinal center subtype of lymphoma. The prognostic relevance of isolated MYC rearrangements was weaker than that of BCL2 isolated translocations, but was probably limited by the rarity of the rearrangements. Seven of eight patients with double hit lymphoma had the germinal center subtype with poor outcome. The germinal center subtype patients with isolated BCL2 translocations had significantly worse outcome than the patients without BCL2 rearrangements (P=0.0002), and their outcome was similar to that of patients with the activated B-cell subtype (P=0.30), but not as bad as the outcome of patients with double hit lymphoma (P<0.0001). Bcl-2 protein overexpression was associated with inferior outcome in patients with germinal center subtype lymphoma, but multivariate analysis showed that this was dependent on BCL2 translocations. The gene expression profiling of patients with BCL2 rearrangements was unique, showing activation of pathways that were silent in the negative counterpart. BCL2 translocated germinal center subtype patients have worse prognosis after rituximab-CHOP, irrespective of MYC status, but the presence of combined gene breaks significantly overcomes the prognostic relevance of isolated lesions.

Copy number alterations in prostate tumors and disease aggressiveness.

Detecting genomic alterations that result in more aggressive prostate cancer may improve clinical treatment and our understanding of the biology underlying this common but complex disease. To this end, we undertook a genome-wide copy number alterations (CNAs) study of clinicopathological characteristics of 62 prostate tumors using the Illumina 1M single nucleotide polymorphism array. The highest overall frequencies of CNAs were on chromosomes 8q (gains), 8p (loss and copy-neutral), and 6q (copy-loss). Combined loss and copy-neutral events were associated with increasing disease grade (P = 0.03), stage (P = 0.01), and diagnostic prostate specific antigen (PSA) (P = 0.01). Further evaluation of CNAs using gene ontology identified pathways involved with disease aggressiveness. The "regulation of apoptosis" pathway was associated with stage of disease (P = 0.004), while the "reproductive cellular process" pathway was associated with diagnostic PSA (P = 0.00038). Specific genes within these pathways exhibited strong associations with clinical characteristics; for example, in the apoptosis pathway BNIP3L was associated with increasing prostate tumor stage (P = 0.007). These findings confirm known regions of CNAs in prostate cancer and localize additional regions and possible genes (e.g., BNIP3L, WWOX, and GATM) that may help to clarify the genetic basis of prostate cancer aggressiveness.

Molecular Subtyping of Diffuse Large B-Cell Lymphoma Using a Novel Quantitative RT-PCR Assay.

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease. Cell-of-origin classification in DLBCL has identified activated B cell (ABC) and germinal center B cell (GCB) as two major subtypes. Patients with the ABC subtype show reduced overall survival with standard therapies. Development of a quantitative RT-PCR-based lymphoma cell-of-origin (LCOO) assay to determine ABC, GCB, and unclassifiable subtypes in formalin-fixed, paraffin-embedded tissue (FFPET) DLBCL samples is reported. The LCOO classifier was trained on two DLBCL cohorts with validation performed by using an analytical grade assay in an independent cohort of 60 FFPET DLBCL samples. In the validation cohort, LCOO classification was 88.1%, 84.7%, and 84.7% concordant with microarray, immunohistochemistry (Hans classification), and Lymphoma Subtyping Test, respectively. Importantly, LCOO and Lymphoma Subtyping Test assays commonly assigned subtypes in 17 (94.4%) of 18 ABC samples and 34 (89.5%) of 38 GCB DLBCL samples from this cohort. Progression-free survival and overall survival of ABC and GCB subtypes, as classified by all platforms, were not significantly different in the validation cohort. LCOO classification using publicly available microarray gene expression from two independent data sets (414 fresh frozen and 474 FFPET DLBCL biopsies) revealed a significantly worse outcome for the ABC subtype compared with that of the GCB subtype. Thus, a sensitive, reproducible, LCOO assay developed on an easy to standardize quantitative RT-PCR platform may be an important clinical tool for DLBCL cell-of-origin classification.

Segmentation and estimation for SNP microarrays: a Bayesian multiple change-point approach.

High-density single-nucleotide polymorphism (SNP) microarrays provide a useful tool for the detection of copy number variants (CNVs). The analysis of such large amounts of data is complicated, especially with regard to determining where copy numbers change and their corresponding values. In this article, we propose a Bayesian multiple change-point model (BMCP) for segmentation and estimation of SNP microarray data. Segmentation concerns separating a chromosome into regions of equal copy number differences between the sample of interest and some reference, and involves the detection of locations of copy number difference changes. Estimation concerns determining true copy number for each segment. Our approach not only gives posterior estimates for the parameters of interest, namely locations for copy number difference changes and true copy number estimates, but also useful confidence measures. In addition, our algorithm can segment multiple samples simultaneously, and infer both common and rare CNVs across individuals. Finally, for studies of CNVs in tumors, we incorporate an adjustment factor for signal attenuation due to tumor heterogeneity or normal contamination that can improve copy number estimates.

Ultra-high throughput single-cell analysis of proteins and RNAs by split-pool synthesis.

Single-cell omics provide insight into cellular heterogeneity and function. Recent technological advances have accelerated single-cell analyses, but workflows remain expensive and complex. We present a method enabling simultaneous, ultra-high throughput single-cell barcoding of millions of cells for targeted analysis of proteins and RNAs. Quantum barcoding (QBC) avoids isolation of single cells by building cell-specific oligo barcodes dynamically within each cell. With minimal instrumentation (four 96-well plates and a multichannel pipette), cell-specific codes are added to each tagged molecule within cells through sequential rounds of classical split-pool synthesis. Here we show the utility of this technology in mouse and human model systems for as many as 50 antibodies to targeted proteins and, separately, >70 targeted RNA regions. We demonstrate that this method can be applied to multi-modal protein and RNA analyses. It can be scaled by expansion of the split-pool process and effectively renders sequencing instruments as versatile multi-parameter flow cytometers.

Author Correction: Ultra-high throughput single-cell analysis of proteins and RNAs by split-pool synthesis.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

On gene ranking using replicated microarray time course data.

Consider the ranking of genes using data from replicated microarray time course experiments, where there are multiple biological conditions, and the genes of interest are those whose temporal profiles differ across conditions. We derive a multisample multivariate empirical Bayes' statistic for ranking genes in the order of differential expression, from both longitudinal and cross-sectional replicated developmental microarray time course data. Our longitudinal multisample model assumes that time course replicates are independent and identically distributed multivariate normal vectors. On the other hand, we construct a cross-sectional model using a normal regression framework with any appropriate basis for the design matrices. In both cases, we use natural conjugate priors in our empirical Bayes' setting which guarantee closed form solutions for the posterior odds. The simulations and two case studies using published worm and mouse microarray time course datasets indicate that the proposed approaches perform satisfactorily.

Functional genomic analysis of oligodendrocyte differentiation.

To better understand the molecular mechanisms governing oligodendrocyte (OL) differentiation, we have used gene profiling to quantitatively analyze gene expression in synchronously differentiating OLs generated from pure oligodendrocyte precursor cells in vitro. By comparing gene expression in these OLs to OLs generated in vivo, we discovered that the program of OL differentiation can progress normally in the absence of heterologous cell-cell interactions. In addition, we found that OL differentiation was unexpectedly prolonged and occurred in at least two sequential stages, each characterized by changes in distinct complements of transcription factors and myelin proteins. By disrupting the normal dynamic expression patterns of transcription factors regulated during OL differentiation, we demonstrated that these sequential stages of gene expression can be independently controlled. We also uncovered several genes previously uncharacterized in OLs that encode transmembrane, secreted, and cytoskeletal proteins that are as highly upregulated as myelin genes during OL differentiation. Last, by comparing genomic loci associated with inherited increased risk of multiple sclerosis (MS) to genes regulated during OL differentiation, we identified several new positional candidate genes that may contribute to MS susceptibility. These findings reveal a previously unexpected complexity to OL differentiation and suggest that an intrinsic program governs successive phases of OL differentiation as these cells extend and align their processes, ensheathe, and ultimately myelinate axons.

Analysis of gene expression during neurite outgrowth and regeneration.

BACKGROUND: The ability of a neuron to regenerate functional connections after injury is influenced by both its intrinsic state and also by extrinsic cues in its surroundings. Investigations of the transcriptional changes undergone by neurons during in vivo models of injury and regeneration have revealed many transcripts associated with these processes. Because of the complex milieu of interactions in vivo, these results include not only expression changes directly related to regenerative outgrowth and but also unrelated responses to surrounding cells and signals. In vitro models of neurite outgrowth provide a means to study the intrinsic transcriptional patterns of neurite outgrowth in the absence of extensive extrinsic cues from nearby cells and tissues. RESULTS: We have undertaken a genome-wide study of transcriptional activity in embryonic superior cervical ganglia (SCG) and dorsal root ganglia (DRG) during a time course of neurite outgrowth in vitro. Gene expression observed in these models likely includes both developmental gene expression patterns and regenerative responses to axotomy, which occurs as the result of tissue dissection. Comparison across both models revealed many genes with similar gene expression patterns during neurite outgrowth. These patterns were minimally affected by exposure to the potent inhibitory cue Semaphorin3A, indicating that this extrinsic cue does not exert major effects at the level of nuclear transcription. We also compared our data to several published studies of DRG and SCG gene expression in animal models of regeneration, and found the expression of a large number of genes in common between neurite outgrowth in vitro and regeneration in vivo. CONCLUSION: Many gene expression changes undergone by SCG and DRG during in vitro outgrowth are shared between these two tissue types and in common with in vivo regeneration models. This suggests that the genes identified in this in vitro study may represent new candidates worthy of further study for potential roles in the therapeutic regrowth of neuronal connections.

Temporal global expression data reveal known and novel salicylate-impacted processes and regulators mediating powdery mildew growth and reproduction on Arabidopsis.

Salicylic acid (SA) is a critical mediator of plant innate immunity. It plays an important role in limiting the growth and reproduction of the virulent powdery mildew (PM) Golovinomyces orontii on Arabidopsis (Arabidopsis thaliana). To investigate this later phase of the PM interaction and the role played by SA, we performed replicated global expression profiling for wild-type and SA biosynthetic mutant isochorismate synthase1 (ics1) Arabidopsis from 0 to 7 d after infection. We found that ICS1-impacted genes constitute 3.8% of profiled genes, with known molecular markers of Arabidopsis defense ranked very highly by the multivariate empirical Bayes statistic (T(2) statistic). Functional analyses of T(2)-selected genes identified statistically significant PM-impacted processes, including photosynthesis, cell wall modification, and alkaloid metabolism, that are ICS1 independent. ICS1-impacted processes include redox, vacuolar transport/secretion, and signaling. Our data also support a role for ICS1 (SA) in iron and calcium homeostasis and identify components of SA cross talk with other phytohormones. Through our analysis, 39 novel PM-impacted transcriptional regulators were identified. Insertion mutants in one of these regulators, PUX2 (for plant ubiquitin regulatory X domain-containing protein 2), results in significantly reduced reproduction of the PM in a cell death-independent manner. Although little is known about PUX2, PUX1 acts as a negative regulator of Arabidopsis CDC48, an essential AAA-ATPase chaperone that mediates diverse cellular activities, including homotypic fusion of endoplasmic reticulum and Golgi membranes, endoplasmic reticulum-associated protein degradation, cell cycle progression, and apoptosis. Future work will elucidate the functional role of the novel regulator PUX2 in PM resistance.

Breast cancer risk among male BRCA1 and BRCA2 mutation carriers.

Men who carry germline mutations in the BRCA2 gene have a higher risk of developing breast carcinoma than men in the general population. Men who carry germline mutations in the BRCA1 gene may also be at a higher risk for breast carcinoma, but this association is not as well established. We evaluated the risks of developing breast carcinoma for male BRCA1 and BRCA2 mutation carriers in the US population based on data from 1939 families with 97 male subjects with breast carcinoma that were collected from eight centers across the National Cancer Institute's Cancer Genetics Network. At all ages, the cumulative risks of male breast cancer were higher in both BRCA1 and BRCA2 mutation carriers than in noncarriers. The relative risks of developing breast cancer were highest for men in their 30s and 40s and decreased with increasing age. Both the relative and cumulative risks were higher for BRCA2 mutation carriers than for BRCA1 mutation carriers. The estimated cumulative risk of breast carcinoma for male BRCA1 mutation carriers at age 70 years was 1.2% (95% confidence interval [CI] = 0.22% to 2.8%) and for BRCA2 mutation carriers, 6.8% (95% CI = 3.2% to 12%).

Spotted long oligonucleotide arrays for human gene expression analysis.

DNA microarrays produced by deposition (or 'spotting')of a single long oligonucleotide probe for each gene may be an attractive alternative to other types of arrays. We produced spotted oligonucleotide arrays using two large collections of approximately 70-mer probes, and used these arrays to analyze gene expression in two dissimilar human RNA samples. These samples were also analyzed using arrays produced by in situ synthesis of sets of multiple short (25-mer) oligonucleotides for each gene (Affymetrix GeneChips). We compared expression measurements for 7344 genes that were represented in both long oligonucleotide probe collections and the in situ-synthesized 25-mer arrays. We found strong correlations (r = 0.8-0.9) between relative gene expression measurements made with spotted long oligonucleotide probes and in situ-synthesized 25-mer probe sets. Spotted long oligonucleotide arrays were suitable for use with both unamplified cDNA and amplified RNA targets, and are a cost-effective alternative for many functional genomics applications. Most previously reported evaluations of microarray technologies have focused on expression measurements made on a relatively small number of genes. The approach described here involves far more gene expression measurements and provides a useful method for comparing existing and emerging techniques for genome-scale expression analysis.