Simple Method To Prepare Oligonucleotide-Conjugated Antibodies and Its Application in Multiplex Protein Detection in Single Cells.

The diversity of nucleic acid sequences enables genomics studies in a highly multiplexed format. Since multiplex protein detection is still a challenge, it would be useful to use genomics tools for this purpose. This can be accomplished by conjugating specific oligonucleotides to antibodies. Upon binding of the oligonucleotide-conjugated antibodies to their targets, the protein levels can be converted to oligonucleotide levels. In this report we describe a simple method for preparing oligonucleotide-conjugated antibodies and discuss this method's application in oligonucleotide extension reaction (OER) for multiplex protein detection. Conjugation is based on strain-promoted alkyne-azide cycloaddition (the Cu-free click reaction), in which the antibody is activated with a dibenzocyclooctyne (DBCO) moiety and subsequently linked covalently with an azide-modified oligonucleotide. In the functional test, the reaction conditions and purification processes were optimized to achieve maximum yield and best performance. The OER assay employs a pair of antibody binders (two antibodies, each conjugated with its own oligonucleotide) developed for each protein target. The two oligonucleotides contain unique six-base complementary regions at their 3' prime ends to allow annealing and extension by DNA synthesis enzymes to form a DNA template. Following preamplification, the DNA template is detected by qPCR. Distinct oligonucleotide sequences are assigned to different antibody binders to enable multiplex protein detection. When tested using recombinant proteins, some antibody binders, such as those specific to CSTB, MET, EpCAM, and CASP3, had dynamic ranges of 5-6 logs. The antibody binders were also used in a multiplexed format in OER assays, and the binders successfully detected their protein targets in cell lysates, and in single cells in combination with the C1 system. This click reaction-based antibody conjugation procedure is cost-effective, needs minimal hands-on time, and is well-suited for the development of affordable multiplex protein assays, which provides the potential to accelerate proteomics research.

The eSNV-detect: a computational system to identify expressed single nucleotide variants from transcriptome sequencing data.

Rapid development of next generation sequencing technology has enabled the identification of genomic alterations from short sequencing reads. There are a number of software pipelines available for calling single nucleotide variants from genomic DNA but, no comprehensive pipelines to identify, annotate and prioritize expressed SNVs (eSNVs) from non-directional paired-end RNA-Seq data. We have developed the eSNV-Detect, a novel computational system, which utilizes data from multiple aligners to call, even at low read depths, and rank variants from RNA-Seq. Multi-platform comparisons with the eSNV-Detect variant candidates were performed. The method was first applied to RNA-Seq from a lymphoblastoid cell-line, achieving 99.7% precision and 91.0% sensitivity in the expressed SNPs for the matching HumanOmni2.5 BeadChip data. Comparison of RNA-Seq eSNV candidates from 25 ER+ breast tumors from The Cancer Genome Atlas (TCGA) project with whole exome coding data showed 90.6-96.8% precision and 91.6-95.7% sensitivity. Contrasting single-cell mRNA-Seq variants with matching traditional multicellular RNA-Seq data for the MD-MB231 breast cancer cell-line delineated variant heterogeneity among the single-cells. Further, Sanger sequencing validation was performed for an ER+ breast tumor with paired normal adjacent tissue validating 29 out of 31 candidate eSNVs. The source code and user manuals of the eSNV-Detect pipeline for Sun Grid Engine and virtual machine are available at http://bioinformaticstools.mayo.edu/research/esnv-detect/.

Benchmarking Single-Cell mRNA-Sequencing Technologies Uncovers Differences in Sensitivity and Reproducibility in Cell Types With Low RNA Content.

Single-cell RNA sequencing (scRNA-seq) has the ability to classify each cell and determine the transcriptomic profile of specific cell types and cells of a given disease state; however, sensitivity of the gene count for each cell can be a critical component to the success of a single-cell study. The recently introduced SMART-Seq Single Cell PLUS Kit (SSsc PLUS) claims to provide higher sensitivity and reproducibility versus popular methods for the sequencing analysis of single cells. Here, the cDNA-generation component of the kit, SMART-Seq Single Cell Kit (SSsc), was compared with the popular homebrew protocol, Smart-seq2, and its update, Smart-seq3. The SMART-Seq Library Prep Kit from SSsc PLUS was benchmarked against a commonly used scRNA-seq library preparation method, Illumina Nextera XT. Finally, the SSsc chemistry was tested in both full and fractional volumes on 2 popular liquid-handler devices to investigate whether the high sensitivity was maintained in miniaturization. We demonstrate that SSsc PLUS outperforms these other full-length methods in convenience, sensitivity, gene identification, and reproducibility while also offering full compatibility with automation platforms.

Single-cell protein-mRNA correlation analysis enabled by multiplexed dual-analyte co-detection.

We have investigated the correlation between proteins and mRNAs in single cells employing an integrated workflow for dual-analyte co-detection. This is achieved by combining the oligo extension reaction (OER), which converts protein levels to DNA levels, with reverse transcription for mRNA detection. Unsupervised gene expression profiling analysis, including principal component analysis and hierarchical clustering, revealed different aspects of the protein-mRNA relationship. Violin plot analysis showed that some genes exhibited similar distribution patterns for proteins and mRNAs. We also demonstrate that cells can be separated into subpopulations based on their protein-mRNA expression profiles, and that different subpopulations have distinct correlation coefficient values. Our results demonstrated that integrated investigations of mRNA and protein levels in single cells allows comprehensive analysis not attainable at bulk levels.

Corrigendum: Fluidic Logic Used in a Systems Approach to Enable Integrated Single-Cell Functional Analysis.

[This corrects the article on p. 70 in vol. 4, PMID: 27709111.].

Array comparative genomic hybridization analysis of genomic alterations in breast cancer subtypes.

In this study, we performed high-resolution array comparative genomic hybridization with an array of 4153 bacterial artificial chromosome clones to assess copy number changes in 44 archival breast cancers. The tumors were flow sorted to exclude non-tumor DNA and increase our ability to detect gene copy number changes. In these tumors, losses were more frequent than gains, and gains in 1q and loss in 16q were the most frequent alterations. We compared gene copy number changes in the tumors based on histologic subtype and estrogen receptor (ER) status, i.e., ER-negative infiltrating ductal carcinoma, ER-positive infiltrating ductal carcinoma, and ER-positive infiltrating lobular carcinoma. We observed a consistent association between loss in regions of 5q and ER-negative infiltrating ductal carcinoma, as well as more frequent loss in 4p16, 8p23, 8p21, 10q25, and 17p11.2 in ER-negative infiltrating ductal carcinoma compared with ER-positive infiltrating ductal carcinoma (adjusted P values < or = 0.05). We also observed high-level amplifications in ER-negative infiltrating ductal carcinoma in regions of 8q24 and 17q12 encompassing the c-myc and c-erbB-2 genes and apparent homozygous deletions in 3p21, 5q33, 8p23, 8p21, 9q34, 16q24, and 19q13. ER-positive infiltrating ductal carcinoma showed a higher frequency of gain in 16p13 and loss in 16q21 than ER-negative infiltrating ductal carcinoma. Correlation analysis highlighted regions of change commonly seen together in ER-negative infiltrating ductal carcinoma. ER-positive infiltrating lobular carcinoma differed from ER-positive infiltrating ductal carcinoma in the frequency of gain in 1q and loss in 11q and showed high-level amplifications in 1q32, 8p23, 11q13, and 11q14. These results indicate that array comparative genomic hybridization can identify significant differences in the genomic alterations between subtypes of breast cancer.

Prostate stem cell antigen as therapy target: tissue expression and in vivo efficacy of an immunoconjugate.

We conducted an expression analysis of prostate stem cell antigen (PSCA)in normal urogenital tissues, benign prostatic hyperplasia (n = 21), prostatic intraepithelial neoplasia (n = 33), and primary (n = 137) and metastatic (n = 42) prostate adenocarcinoma, using isotopic in situ hybridization on tissue microarrays. In normal prostate, we observe PSCA expression in the terminally differentiated, secretory epithelium; strong expression was also seen in normal urothelium. Forty-eight percent of primary and 64% of metastatic prostatic adenocarcinomas expressed PSCA RNA. Our studies did not confirm a positive correlation between level of PSCA RNA expression and high Gleason grade. We characterized monoclonal anti-PSCA antibodies that recognize PSCA expressed on the surface of live cells, are efficiently internalized after antigen recognition, and kill tumor cells in vitro in an antigen-specific fashion upon conjugation with maytansinoid. Unconjugated anti-PSCA antibodies demonstrated efficacy against PSCA-positive tumors by delaying progressive tumor growth in vivo. Maytansinoid-conjugated antibodies caused complete regression of established tumors in a large proportion of animals. Our results strongly suggest that maytansinoid-conjugated anti-PSCA monoclonal antibodies should be evaluated as a therapeutic modality for patients with advanced prostate cancer.

Fluidic Logic Used in a Systems Approach to Enable Integrated Single-Cell Functional Analysis.

The study of single cells has evolved over the past several years to include expression and genomic analysis of an increasing number of single cells. Several studies have demonstrated wide spread variation and heterogeneity within cell populations of similar phenotype. While the characterization of these populations will likely set the foundation for our understanding of genomic- and expression-based diversity, it will not be able to link the functional differences of a single cell to its underlying genomic structure and activity. Currently, it is difficult to perturb single cells in a controlled environment, monitor and measure the response due to perturbation, and link these response measurements to downstream genomic and transcriptomic analysis. In order to address this challenge, we developed a platform to integrate and miniaturize many of the experimental steps required to study single-cell function. The heart of this platform is an elastomer-based integrated fluidic circuit that uses fluidic logic to select and sequester specific single cells based on a phenotypic trait for downstream experimentation. Experiments with sequestered cells that have been performed include on-chip culture, exposure to various stimulants, and post-exposure image-based response analysis, followed by preparation of the mRNA transcriptome for massively parallel sequencing analysis. The flexible system embodies experimental design and execution that enable routine functional studies of single cells.

Clustering-Based Method for Developing a Genomic Copy Number Alteration Signature for Predicting the Metastatic Potential of Prostate Cancer.

The transition of cancer from a localized tumor to a distant metastasis is not well understood for prostate and many other cancers, partly, because of the scarcity of tumor samples, especially metastases, from cancer patients with long-term clinical follow-up. To overcome this limitation, we developed a semi-supervised clustering method using the tumor genomic DNA copy number alterations to classify each patient into inferred clinical outcome groups of metastatic potential. Our data set was comprised of 294 primary tumors and 49 metastases from 5 independent cohorts of prostate cancer patients. The alterations were modeled based on Darwin's evolutionary selection theory and the genes overlapping these altered genomic regions were used to develop a metastatic potential score for a prostate cancer primary tumor. The function of the proteins encoded by some of the predictor genes promote escape from anoikis, a pathway of apoptosis, deregulated in metastases. We evaluated the metastatic potential score with other clinical predictors available at diagnosis using a Cox proportional hazards model and show our proposed score was the only significant predictor of metastasis free survival. The metastasis gene signature and associated score could be applied directly to copy number alteration profiles from patient biopsies positive for prostate cancer.

DIAPH3 governs the cellular transition to the amoeboid tumour phenotype.

Therapies for most malignancies are generally ineffective once metastasis occurs. While tumour cells migrate through tissues using diverse strategies, the signalling networks controlling such behaviours in human tumours are poorly understood. Here we define a role for the Diaphanous-related formin-3 (DIAPH3) as a non-canonical regulator of metastasis that restrains conversion to amoeboid cell behaviour in multiple cancer types. The DIAPH3 locus is close to RB1, within a narrow consensus region of deletion on chromosome 13q in prostate, breast and hepatocellular carcinomas. DIAPH3 silencing in human carcinoma cells destabilized microtubules and induced defective endocytic trafficking, endosomal accumulation of EGFR, and hyperactivation of EGFR/MEK/ERK signalling. Silencing also evoked amoeboid properties, increased invasion and promoted metastasis in mice. In human tumours, DIAPH3 down-regulation was associated with aggressive or metastatic disease. DIAPH3-silenced cells were sensitive to MEK inhibition, but showed reduced sensitivity to EGFR inhibition. These findings have implications for understanding mechanisms of metastasis, and suggest that identifying patients with chromosomal deletions at DIAPH3 may have prognostic value.

Comparative genomic hybridization to detect variation in the copy number of large DNA segments.

Array comparative genomic hybridization (CGH) is an excellent tool to scan the genome for copy number variations (CNVs) when used conscientiously. This article is intended to provide an understanding of the basic principles of array CGH and the different options available to the user to design their array CGH experiments. Specifically, the six subsections discuss the different array platforms available, test and reference DNA preparation, reference DNA choice, the basics of hybridization, data processing, and our current understanding of CNVs in the human genome.

Genomic instability in breast cancer: pathogenesis and clinical implications.

Breast cancer is a heterogeneous disease, appreciable by molecular markers, gene-expression profiles, and most recently, patterns of genomic alteration. In particular, genomic profiling has revealed three distinct patterns of DNA copy-number alteration: a "simple" type with few gains or losses of whole chromosome arms, an "amplifier" type with focal high-level DNA amplifications, and a "complex" type marked by numerous low-amplitude changes and copy-number transitions. The three patterns are associated with distinct gene-expression subtypes, and preferentially target different loci in the genome (implicating distinct cancer genes). Moreover, the different patterns of alteration imply distinct underlying mechanisms of genomic instability. The amplifier pattern may arise from transient telomere dysfunction, although new data suggest ongoing "amplifier" instability. The complex pattern shows similarity to breast cancers with germline BRCA1 mutation, which also exhibit "basal-like" expression profiles and complex-pattern genomes, implicating a possible defect in BRCA1-associated repair of DNA double-strand breaks. As such, targeting presumptive DNA repair defects represents a promising area of clinical investigation. Future studies should clarify the pathogenesis of breast cancers with amplifier and complex-pattern genomes, and will likely identify new therapeutic opportunities.

Variability in the androgen response of prostate epithelium to 5alpha-reductase inhibition: implications for prostate cancer chemoprevention.

Inhibitors of 5alpha-reductase (SRD5A) that lower intraprostatic levels of dihydrotestosterone (DHT) reduce the overall incidence of prostate cancer (PCa), but there is significant variation in chemopreventive activity between individual men. In seeking molecular alterations that might underlie this variation, we compared gene expression patterns in patients with localized PCa who were randomized to prostatectomy alone versus treatment with two different doses of the SRD5A inhibitor dutasteride. Prostatic levels of DHT were decreased by >90% in both dutasteride-treated patient groups versus the untreated patient group. Despite significant and uniform suppression of tissue DHT, unsupervised clustering based on prostatic gene expression did not discriminate these groups. However, subjects could be resolved into distinct cohorts characterized by high or low expression of genes regulated by the androgen receptor (AR), based solely on AR transcript expression. The higher-dose dutasteride treatment group was found to include significantly fewer cancers with TMPRSS2-ERG genetic fusions. Dutasteride treatment was associated with highly variable alterations in benign epithelial gene expression. Segregating subjects based on expression of AR and androgen-regulated genes revealed that patients are differentially sensitive to SRD5A inhibition. Our findings suggest that AR levels may predict the chemopreventive efficacy of SRD5A inhibitors.

Comparative analyses of chromosome alterations in soft-tissue metastases within and across patients with castration-resistant prostate cancer.

Androgen deprivation is the mainstay of therapy for progressive prostate cancer. Despite initial and dramatic tumor inhibition, most men eventually fail therapy and die of metastatic castration-resistant (CR) disease. Here, we characterize the profound degree of genomic alteration found in CR tumors using array comparative genomic hybridization (array CGH), gene expression arrays, and fluorescence in situ hybridization (FISH). Bycluster analysis, we show that the similarity of the genomic profiles from primary and metastatic tumors is driven by the patient. Using data adjusted for this similarity, we identify numerous high-frequency alterations in the CR tumors, such as 8p loss and chromosome 7 and 8q gain. By integrating array CGH and expression array data, we reveal genes whose correlated values suggest they are relevant to prostate cancer biology. We find alterations that are significantly associated with the metastases of specific organ sites, and others with CR tumors versus the tumors of patients with localized prostate cancer not treated with androgen deprivation. Within the high-frequency sites of loss in CR metastases, we find an overrepresentation of genes involved in cellular lipid metabolism, including PTEN. Finally, using FISH, we verify the presence of a gene fusion between TMPRSS2 and ERG suggested by chromosome 21 deletions detected by array CGH. We find the fusion in 54% of our CR tumors, and 81% of the fusion-positive tumors contain cells with multiple copies of the fusion. Our investigation lays the foundation for a better understanding of and possible therapeutic targets for CR disease, the poorly responsive and final stage of prostate cancer.

Genomic alterations indicate tumor origin and varied metastatic potential of disseminated cells from prostate cancer patients.

Disseminated epithelial cells can be isolated from the bone marrow of a far greater fraction of prostate-cancer patients than the fraction of patients who progress to metastatic disease. To provide a better understanding of these cells, we have characterized their genomic alterations. We first present an array comparative genomic hybridization method capable of detecting genomic changes in the small number of disseminated cells (10-20) that can typically be obtained from bone marrow aspirates of prostate-cancer patients. We show multiple regions of copy-number change, including alterations common in prostate cancer, such as 8p loss, 8q gain, and gain encompassing the androgen-receptor gene on Xq, in the disseminated cell pools from 11 metastatic patients. We found fewer and less striking genomic alterations in the 48 pools of disseminated cells from patients with organ-confined disease. However, we identify changes shared by these samples with their corresponding primary tumors and prostate-cancer alterations reported in the literature, evidence that these cells, like those in advanced disease, are disseminated tumor cells (DTC). We also show that DTCs from patients with advanced and localized disease share several abnormalities, including losses containing cell-adhesion genes and alterations reported to associate with progressive disease. These shared alterations might confer the capability to disseminate or establish secondary disease. Overall, the spectrum of genomic deviations is evidence for metastatic capacity in advanced-disease DTCs and for variation in that capacity in DTCs from localized disease. Our analysis lays the foundation for elucidation of the relationship between DTC genomic alterations and progressive prostate cancer.