A PRRX1 Signature Identifies TIM-3 and VISTA as Potential Immune Checkpoint Targets in a Subgroup of Microsatellite Stable Colorectal Cancer Liver Metastases.

Disease recurrence and drug resistance are major challenges in the clinical management of patients with colorectal cancer liver metastases (CLM), and because tumors are generally microsatellite stable (MSS), responses to immune therapies are poor. The mesenchymal phenotype is overrepresented in treatment-resistant cancers and is associated with an immunosuppressed microenvironment. The aim of this work was to molecularly identify and characterize a mesenchymal subgroup of MSS CLM to identify novel therapeutic approaches. We here generated a mesenchymal gene expression signature by analysis of resection specimens from 38 patients with CLM using ranked expression level of the epithelial-to-mesenchymal transition-related transcription factor PRRX1. Downstream pathway analysis based on the resulting gene signature was performed and independent, publicly available datasets were used to validate the findings. A subgroup comprising 16% of the analyzed CLM samples were classified as mesenchymal, or belonging to the PRRX1 high group. Analysis of the PRRX1 signature genes revealed a distinct immunosuppressive phenotype with high expression of immune checkpoints HAVCR2/TIM-3 and VISTA, in addition to the M2 macrophage marker CD163. The findings were convincingly validated in datasets from three external CLM cohorts. Upregulation of immune checkpoints HAVCR2/TIM-3 and VISTA in the PRRX1 high subgroup is a novel finding, and suggests immune evasion beyond the PD-1/PD-L1 axis, which may contribute to poor response to PD-1/PD-L1-directed immune therapy in MSS colorectal cancer. Importantly, these checkpoints represent potential novel opportunities for immune-based therapy approaches in a subset of MSS CLM. Significance: CLM is an important cause of colorectal cancer mortality where the majority of patients have yet to benefit from immunotherapies. In this study of gene expression profiling analyses, we uncovered novel immune checkpoint targets in a subgroup of patients with MSS CLMs harboring a mesenchymal phenotype.

Novel human melanoma brain metastasis models in athymic nude fox1nu mice: Site-specific metastasis patterns reflecting their clinical origin.

BACKGROUND: Malignant melanomas frequently metastasize to the brain, but metastases in the cerebellum are underrepresented compared with metastases in the cerebrum. METHODS: We established animal models by injecting intracardially in athymic nude fox1nu mice two human melanoma cell lines, originating from a cerebral metastasis (HM19) and a cerebellar metastasis (HM86). RESULTS: Using magnetic resonance imaging (MRI), metastases were first detected after a mean of 34.5 days. Mean survival time was 59.6 days for the mice in the HM86 group and significantly shorter (43.7 days) for HM19-injected animals (p < 0.001). In the HM86 group, the first detectable metastasis was located in the cerebellum in 15/55 (29%) mice compared with none in the HM19 group (p < 0.001). At sacrifice, cerebellar metastases were found in 34/55 (63%) HM86-injected mice compared with 1/53 (2%) in the HM19-injected (p < 0.001) mice. At that time, all mice in both groups had detectable metastases in the cerebrum. Comparing macroscopic and histologic appearances of the brain metastases with their clinical counterparts, the cell line-based tumors had kept their original morphologic characteristics. CONCLUSIONS: The present work demonstrates that human brain-metastatic melanoma cells injected intracardially in mice had retained inherent characteristics also in reproducing interaction with subtle microenvironmental brain tissue compartment-specific features. The models offer new possibilities for investigating tumor- and host-associated factors involved in determining tissue specificity of brain metastasis.

Molecularly matched therapy in the context of sensitivity, resistance, and safety; patient outcomes in end-stage cancer - the MetAction study.

Background: In precision cancer medicine, the challenge is to prioritize DNA driver events, account for resistance markers, and procure sufficient information for treatment that maintains patient safety. The MetAction project, exploring how tumor molecular vulnerabilities predict therapy response, first established the required workflow for DNA sequencing and data interpretation (2014-2015). Here, we employed it to identify molecularly matched therapy and recorded outcome in end-stage cancer (2016-2019).Material and methods: Metastatic tissue from 26 patients (16 colorectal cancer cases) was sequenced by the Oncomine assay. The study tumor boards interpreted called variants with respect to sensitivity or resistance to matched therapy and recommended single-agent or combination treatment if considered tolerable. The primary endpoint was the rate of progression-free survival 1.3-fold longer than for the most recent systemic therapy. The objective response rate and overall survival were secondary endpoints.Results: Both common and rare actionable alterations were identified. Thirteen patients were found eligible for therapy following review of tumor sensitivity and resistance variants and patient tolerability. The interventions were inhibitors of ALK/ROS1-, BRAF-, EGFR-, FGFR-, mTOR-, PARP-, or PD-1-mediated signaling for 2-3 cases each. Among 10 patients who received treatment until radiologic evaluation, 6 (46% of the eligible cases) met the primary endpoint. Four colorectal cancer patients (15% of the total study cohort) had objective response. The only serious adverse event was a transient colitis, which appeared in 1 of the 2 patients given PD-1 inhibitor with complete response. Apart from those two, overall survival was similar for patients who did and did not receive study treatment.Conclusions: The systematic MetAction approach may point forward to a refined framework for how to interpret the complexity of sensitivity versus resistance and patient safety that resides in tumor sequence data, for the possibly improved outcome of precision cancer medicine in future studies. ClinicalTrials.gov, identifier: NCT02142036.

A Three-dimensional Ex Vivo Viability Assay Reveals a Strong Correlation Between Response to Targeted Inhibitors and Mutation Status in Melanoma Lymph Node Metastases.

Although clinical management of melanoma has changed considerably in recent years, intrinsic treatment resistance remains a severe problem and strategies to design personal treatment regimens are highly warranted. We have applied a three-dimensional (3D) ex vivo drug efficacy assay, exposing disaggregated cells from 38 freshly harvested melanoma lymph node metastases and 21 patient derived xenografts (PDXs) to clinical relevant drugs for 7 days, and examined its potential to evaluate therapy response. A strong association between Vemurafenib response and BRAF mutation status was achieved (P < .0001), while enhanced viability was seen in some NRAS mutated tumors. BRAF and NRAS mutated tumors responded comparably to the MEK inhibitor Cobimetinib. Based on the ex vivo results, two tumors diagnosed as BRAF wild-type by routine pathology examinations had to be re-evaluated; one was subsequently found to have a complex V600E mutation, the other a double BRAF mutation (V600E/K601 N). No BRAF inhibitor resistance mechanisms were identified, but PIK3CA and NF1 mutations were identified in two highly responsive tumors. Concordance between ex vivo drug responses using tissue from PDXs and corresponding patient tumors demonstrate that PDX models represent an indefinite source of tumor material that may allow ex vivo evaluation of numerous drugs and combinations, as well as studies of underlying molecular mechanisms. In conclusion, we have established a rapid and low cost ex vivo drug efficacy assay applicable on tumor tissue from patient biopsies. The 3D/spheroid format, limiting the influence from normal adjacent cells and allowing assessment of drug sensitivity to numerous drugs in one week, confirms its potential as a supplement to guide clinical decision, in particular in identifying non-responding patients.

Responsiveness to PD-1 Blockade in End-Stage Colon Cancer with Gene Locus 9p24.1 Copy-Number Gain.

Most patients whose large bowel cancer has spread to other organs do not respond to immune therapy. We detected a rare gene mutation, termed 9p24.1 copy-number gain (CNG), in an otherwise incurable colorectal cancer that provoked an immune therapy response. We identified this gene mutation by gene-panel sequencing of DNA from a liver metastasis biopsy from a patient who had disease refractory to standard therapies. Following immune checkpoint blockade (ICB) with pembrolizumab (anti-PD-1), the patient experienced conversion of the tumor phenotype from one with epithelial features to that of an inflamed microenvironment, detected by high-resolution RNA sequencing. Circulating tumor DNA disappeared over the first weeks of therapy. As assessed by standard radiographic measurement, the patient had a partial response that was durable. This patient's response may support the use of histology-agnostic ICB in solid tumors that carry the rare 9p24.1 CNG.

Molecular signatures reflecting microenvironmental metabolism and chemotherapy-induced immunogenic cell death in colorectal liver metastases.

Background: Metastatic colorectal cancer (CRC) is associated with highly variable clinical outcome and response to therapy. The recently identified consensus molecular subtypes (CMS1-4) have prognostic and therapeutic implications in primary CRC, but whether these subtypes are valid for metastatic disease is unclear. We performed multi-level analyses of resectable CRC liver metastases (CLM) to identify molecular characteristics of metastatic disease and evaluate the clinical relevance. Methods: In this ancillary study to the Oslo-CoMet trial, CLM and tumor-adjacent liver tissue from 46 patients were analyzed by profiling mutations (targeted sequencing), genome-wide copy number alteration (CNAs), and gene expression. Results: Somatic mutations and CNAs detected in CLM were similar to reported primary CRC profiles, while CNA profiles of eight metastatic pairs suggested intra-patient divergence. A CMS classifier tool applied to gene expression data, revealed the cohort to be highly enriched for CMS2. Hierarchical clustering of genes with highly variable expression identified two subgroups separated by high or low expression of 55 genes with immune-related and metabolic functions. Importantly, induction of genes and pathways associated with immunogenic cell death (ICD) was identified in metastases exposed to neoadjuvant chemotherapy (NACT). Conclusions: The uniform classification of CLM by CMS subtyping may indicate that novel class discovery approaches need to be explored to uncover clinically useful stratification of CLM. Detected gene expression signatures support the role of metabolism and chemotherapy in shaping the immune microenvironment of CLM. Furthermore, the results point to rational exploration of immune modulating strategies in CLM, particularly by exploiting NACT-induced ICD.

Implementing precision cancer medicine in the public health services of Norway: the diagnostic infrastructure and a cost estimate.

OBJECTIVE: Through the conduct of an individual-based intervention study, the main purpose of this project was to build and evaluate the required infrastructure that may enable routine practice of precision cancer medicine in the public health services of Norway, including modelling of costs. METHODS: An eligible patient had end-stage metastatic disease from a solid tumour. Metastatic tissue was analysed by DNA sequencing, using a 50-gene panel and a study-generated pipeline for analysis of sequence data, supplemented with fluorescence in situ hybridisation to cover relevant biomarkers. Cost estimations compared best supportive care, biomarker-agnostic treatment with a molecularly targeted agent and biomarker-based treatment with such a drug. These included costs for medication, outpatient clinic visits, admission from adverse events and the biomarker-based procedures. RESULTS: The diagnostic procedures, which comprised sampling of metastatic tissue, mutation analysis and data interpretation at the Molecular Tumor Board before integration with clinical data at the Clinical Tumor Board, were completed in median 18 (8-39) days for the 22 study patients. The 23 invasive procedures (12 from liver, 6 from lung, 5 from other sites) caused a single adverse event (pneumothorax). Per patient, 0-5 mutations were detected in metastatic tumours; however, no actionable target case was identified for the current single-agent therapy approach. Based on the cost modelling, the biomarker-based approach was 2.5-fold more costly than best supportive care and 2.5-fold less costly than the biomarker-agnostic option. CONCLUSIONS: The first project phase established a comprehensive diagnostic infrastructure for precision cancer medicine, which enabled expedite and safe mutation profiling of metastatic tumours and data interpretation at multidisciplinary tumour boards for patients with end-stage cancer. Furthermore, it prepared for protocol amendments, recently approved by the designated authorities for the second study phase, allowing more comprehensive mutation analysis and opportunities to define therapy targets.

Fibroblast-induced switching to the mesenchymal-like phenotype and PI3K/mTOR signaling protects melanoma cells from BRAF inhibitors.

The knowledge on how tumor-associated stroma influences efficacy of anti-cancer therapy just started to emerge. Here we show that lung fibroblasts reduce melanoma sensitivity to the BRAF inhibitor (BRAFi) vemurafenib only if the two cell types are in close proximity. In the presence of fibroblasts, the adjacent melanoma cells acquire de-differentiated mesenchymal-like phenotype. Upon treatment with BRAFi, such melanoma cells maintain high levels of phospho ribosomal protein S6 (pS6), i.e. active mTOR signaling, which is suppressed in the BRAFi sensitive cells without stromal contacts. Inhibitors of PI3K/mTOR in combination with BRAFi eradicate pS6high cell subpopulations and potentiate anti-cancer effects in melanoma protected by the fibroblasts. mTOR and BRAF co-inhibition also delayed the development of early-stage lung metastases in vivo. In conclusion, we demonstrate that upon influence from fibroblasts, melanoma cells undergo a phenotype switch to the mesenchymal state, which can support PI3K/mTOR signaling. The lost sensitivity to BRAFi in such cells can be overcome by co-targeting PI3K/mTOR. This knowledge could be explored for designing BRAFi combination therapies aiming to eliminate both stroma-protected and non-protected counterparts of metastases.

Metabolic reprogramming supports the invasive phenotype in malignant melanoma.

Invasiveness is a hallmark of aggressive cancer like malignant melanoma, and factors involved in acquisition or maintenance of an invasive phenotype are attractive targets for therapy. We investigated melanoma phenotype modulation induced by the metastasis-promoting microenvironmental protein S100A4, focusing on the relationship between enhanced cellular motility, dedifferentiation and metabolic changes. In poorly motile, well-differentiated Melmet 5 cells, S100A4 stimulated migration, invasion and simultaneously down-regulated differentiation genes and modulated expression of metabolism genes. Metabolic studies confirmed suppressed mitochondrial respiration and activated glycolytic flux in the S100A4 stimulated cells, indicating a metabolic switch toward aerobic glycolysis, known as the Warburg effect. Reversal of the glycolytic switch by dichloracetate induced apoptosis and reduced cell growth, particularly in the S100A4 stimulated cells. This implies that cells with stimulated invasiveness get survival benefit from the glycolytic switch and, therefore, become more vulnerable to glycolysis inhibition. In conclusion, our data indicate that transition to the invasive phenotype in melanoma involves dedifferentiation and metabolic reprogramming from mitochondrial oxidation to glycolysis, which facilitates survival of the invasive cancer cells. Therapeutic strategies targeting the metabolic reprogramming may therefore be effective against the invasive phenotype.

Metastasis-associated protein S100A4 induces a network of inflammatory cytokines that activate stromal cells to acquire pro-tumorigenic properties.

Tumor cells have the ability to exploit stromal cells to facilitate metastasis. By using malignant melanoma as a model, we show that the stroma adjacent to metastatic lesions is enriched in the known metastasis-promoting protein S100A4. S100A4 stimulates cancer cells to secrete paracrine factors, such as inflammatory cytokines IL8, CCL2 and SAA, which activate stromal cells (endothelial cells and monocytes) so that they acquire tumor-supportive properties. Our data establishes S100A4 as an inducer of a cytokine network enabling tumor cells to engage angiogenic and inflammatory stromal cells, which might contribute to pro-metastatic activity of S100A4.

Melanoma brain colonization involves the emergence of a brain-adaptive phenotype.

The brain offers a unique microenvironment that plays an important role in the establishment and progression of metastasis. However, the molecular determinants that promote development of melanoma brain metastases are largely unknown. Utilizing two species of immune-compromised animals, with in vivo cultivated metastatic tissues along with their corresponding host tissues in a metastasis model, we here identify molecular events associated with melanoma brain metastases. We find that the transcriptional changes in the melanoma cells, as induced by the brain-microenvironment in both host species, reveal the opportunistic nature of melanoma in this biological context in rewiring the molecular framework of key molecular players with their associated biological processes. Specifically, we identify the existence of a neuron-like melanoma phenotype, which includes synaptic characteristics and a neurotransmission-like circuit involving glutamate. Regulation of gene transcription and neuron-like plasticity by Ca(2+)-dependent signaling appear to occur through glutamate receptor activation. The brain-adaptive phenotype was found as more prominent in the early metastatic growth phases compared to a later phase, emphasizing a temporal requirement of critical events in the successful colonization of the brain. Analysis of the host tissue uncovered a cooperative inflammatory microenvironment formed by activated host cells that permitted melanoma growth at the expense of the host organism. Combined experimental and computational approaches clearly highlighted genes and signaling pathways being shared with neurodegenerative diseases. Importantly, the identification of essential molecular networks that operate to promote the brain-adaptive phenotype is of clinical relevance, as they represent leads to urgently needed therapeutic targets.

Methods for quantitation of gene expression.

Gene expression of protein encoding genes can be quantitatively measured at the transcriptional level by a number of low- to high-throughput methods. The sensitivity of each method is dependent on both the intrinsic properties of the respective technology and the absolute number of each mRNA molecule to be measured. For these reasons, the correlation of measurements between technological platforms may be variable. Due to the complexity of the transcriptome, the purpose of a gene expression study dictates the choice of method as each is connected to a set of advantages and disadvantages. Strategies such as global mRNA amplification of small samples, have been implemented to overcome previous limitations. However, stochastic events will limit quantitative measurements of any tool when in-put levels are extremely low. Due to the versatile nature of microarray technology, this method will likely persist as a highly applied tool to query the levels of non-coding transcripts, a new expansion in the field of gene expression analysis although possible advances of the technology may occur.

Validation of oligoarrays for quantitative exploration of the transcriptome.

BACKGROUND: Oligoarrays have become an accessible technique for exploring the transcriptome, but it is presently unclear how absolute transcript data from this technique compare to the data achieved with tag-based quantitative techniques, such as massively parallel signature sequencing (MPSS) and serial analysis of gene expression (SAGE). By use of the TransCount method we calculated absolute transcript concentrations from spotted oligoarray intensities, enabling direct comparisons with tag counts obtained with MPSS and SAGE. The tag counts were converted to number of transcripts per cell by assuming that the sum of all transcripts in a single cell was 5.105. Our aim was to investigate whether the less resource demanding and more widespread oligoarray technique could provide data that were correlated to and had the same absolute scale as those obtained with MPSS and SAGE. RESULTS: A number of 1,777 unique transcripts were detected in common for the three technologies and served as the basis for our analyses. The correlations involving the oligoarray data were not weaker than, but, similar to the correlation between the MPSS and SAGE data, both when the entire concentration range was considered and at high concentrations. The data sets were more strongly correlated at high transcript concentrations than at low concentrations. On an absolute scale, the number of transcripts per cell and gene was generally higher based on oligoarrays than on MPSS and SAGE, and ranged from 1.6 to 9,705 for the 1,777 overlapping genes. The MPSS data were on same scale as the SAGE data, ranging from 0.5 to 3,180 (MPSS) and 9 to1,268 (SAGE) transcripts per cell and gene. The sum of all transcripts per cell for these genes was 3.8.105 (oligoarrays), 1.1.105 (MPSS) and 7.6.104 (SAGE), whereas the corresponding sum for all detected transcripts was 1.1.106 (oligoarrays), 2.8.105 (MPSS) and 3.8.105 (SAGE). CONCLUSION: The oligoarrays and TransCount provide quantitative transcript concentrations that are correlated to MPSS and SAGE data, but, the absolute scale of the measurements differs across the technologies. The discrepancy questions whether the sum of all transcripts within a single cell might be higher than the number of 5.105 suggested in the literature and used to convert tag counts to transcripts per cell. If so, this may explain the apparent higher transcript detection efficiency of the oligoarrays, and has to be clarified before absolute transcript concentrations can be interchanged across the technologies. The ability to obtain transcript concentrations from oligoarrays opens up the possibility of efficient generation of universal transcript databases with low resource demands.

Options available for profiling small samples: a review of sample amplification technology when combined with microarray profiling.

The possibility of performing microarray analysis on limited material has been demonstrated in a number of publications. In this review we approach the technical aspects of mRNA amplification and several important implicit consequences, for both linear and exponential procedures. Amplification efficiencies clearly allow profiling of extremely small samples. The conservation of transcript abundance is the most important issue regarding the use of sample amplification in combination with microarray analysis, and this aspect has generally been found to be acceptable, although demonstrated to decrease in highly diluted samples. The fact that variability and discrepancies in microarray profiles increase with minute sample sizes has been clearly documented, but for many studies this does appear to have affected the biological conclusions. We suggest that this is due to the data analysis approach applied, and the consequence is the chance of presenting misleading results. We discuss the issue of amplification sensitivity limits in the light of reports on fidelity, published data from reviewed articles and data analysis approaches. These are important considerations to be reflected in the design of future studies and when evaluating biological conclusions from published microarray studies based on extremely low input RNA quantities.

Limitations of mRNA amplification from small-size cell samples.

BACKGROUND: Global mRNA amplification has become a widely used approach to obtain gene expression profiles from limited material. An important concern is the reliable reflection of the starting material in the results obtained. This is especially important with extremely low quantities of input RNA where stochastic effects due to template dilution may be present. This aspect remains under-documented in the literature, as quantitative measures of data reliability are most often lacking. To address this issue, we examined the sensitivity levels of each transcript in 3 different cell sample sizes. ANOVA analysis was used to estimate the overall effects of reduced input RNA in our experimental design. In order to estimate the validity of decreasing sample sizes, we examined the sensitivity levels of each transcript by applying a novel model-based method, TransCount. RESULTS: From expression data, TransCount provided estimates of absolute transcript concentrations in each examined sample. The results from TransCount were used to calculate the Pearson correlation coefficient between transcript concentrations for different sample sizes. The correlations were clearly transcript copy number dependent. A critical level was observed where stochastic fluctuations became significant. The analysis allowed us to pinpoint the gene specific number of transcript templates that defined the limit of reliability with respect to number of cells from that particular source. In the sample amplifying from 1000 cells, transcripts expressed with at least 121 transcripts/cell were statistically reliable and for 250 cells, the limit was 1806 transcripts/cell. Above these thresholds, correlation between our data sets was at acceptable values for reliable interpretation. CONCLUSION: These results imply that the reliability of any amplification experiment must be validated empirically to justify that any gene exists in sufficient quantity in the input material. This finding has important implications for any experiment where only extremely small samples such as single cell analyses or laser captured microdissected cells are available.

Constitutive expression of the AP-1 transcription factors c-jun, junD, junB, and c-fos and the marginal zone B-cell transcription factor Notch2 in splenic marginal zone lymphoma.

Splenic marginal zone lymphoma (SMZL) is a lymphoma type of putative marginal zone B-cell origin. No specific genetic alterations have yet been demonstrated in SMZL. Clinically, SMZL is a low-grade B-cell non-Hodgkin lymphoma. However, the presence of p53 mutation, 7q22-7q32 deletion or the absence of somatic hypermutations of immunoglobulin genes has been correlated with a worse prognosis. In this study, we analyzed genome-wide gene expression of 24 cases of SMZL using the microarray technique. The AP-1 transcription factors c-jun, junD, junB, and c-fos as well as Notch2 were found to be specifically up-regulated. These data were confirmed by real-time PCR and immunohistochemical staining of tissue sections. The absence of concordant high expression of the MAP kinases, the signaling cascade leading to AP-1 up-regulation, suggests autoregulation of the AP-1 transcription factors and an important role in SMZL oncogenesis. High expression of Notch2, a transcription factor that induces marginal zone B-cell differentiation, is highly suggestive for a marginal zone B-cell origin of SMZL. In addition, SMZL with the 7q deletion showed high expression of TGF-beta1 and low expression of the DNA helicase XPB, a crucial part of the nucleotide excision repair complex, possibly explaining the more aggressive clinical course of those cases.

Seed 1-cysteine peroxiredoxin antioxidants are not involved in dormancy, but contribute to inhibition of germination during stress.

Peroxiredoxins (Prx) are thiol-dependent antioxidants containing one (1-cysteine [-Cys]) or two (2-Cys) conserved Cys residues that protect lipids, enzymes, and DNA against reactive oxygen species. In plants, the 1-Cys Prxs are highly expressed during late seed development, and the expression pattern is dormancy related in mature seeds. We have expressed the Arabidopsis 1-Cys Prx AtPER1 in Escherichia coli and show that this protein has antioxidant activity in vitro and protects E. coli in vivo against the toxic oxidant cumene hydroperoxide. Although some 1-Cys Prxs are targeted to the nucleus, a green fluorescent protein-AtPER1 fusion protein was also localized to the cytoplasm in an onion epidermis subcellular localization assay. It has been proposed that seed Prxs are involved in maintenance of dormancy and/or protect the embryo and aleurone layer surviving desiccation against damage caused by reactive oxygen species. These hypotheses were tested using transgenic Arabidopsis lines overexpressing the barley (Hordeum vulgare) 1-Cys PER1 protein and lines with reduced levels of AtPER1 due to antisensing or RNA interference. We found no correlation between Prx levels and the duration of the after-ripening period required before germination. Thus, Prxs are unlikely to contribute to maintenance of dormancy. RNA interference lines almost devoid of AtPER1 protein developed and germinated normally under standard growth room conditions. However, seeds from lines overexpressing PER1 were less inclined to germinate than wild-type seeds in the presence of NaCl, mannitol, and methyl viologen, suggesting that Prx can sense harsh environmental surroundings and play a part in the inhibition of germination under unfavorable conditions.

Effects of mRNA amplification on gene expression ratios in cDNA experiments estimated by analysis of variance.

BACKGROUND: A limiting factor of cDNA microarray technology is the need for a substantial amount of RNA per labeling reaction. Thus, 20-200 micro-grams total RNA or 0.5-2 micro-grams poly (A) RNA is typically required for monitoring gene expression. In addition, gene expression profiles from large, heterogeneous cell populations provide complex patterns from which biological data for the target cells may be difficult to extract. In this study, we chose to investigate a widely used mRNA amplification protocol that allows gene expression studies to be performed on samples with limited starting material. We present a quantitative study of the variation and noise present in our data set obtained from experiments with either amplified or non-amplified material. RESULTS: Using analysis of variance (ANOVA) and multiple hypothesis testing, we estimated the impact of amplification on the preservation of gene expression ratios. Both methods showed that the gene expression ratios were not completely preserved between amplified and non-amplified material. We also compared the expression ratios between the two cell lines for the amplified material with expression ratios between the two cell lines for the non-amplified material for each gene. With the aid of multiple t-testing with a false discovery rate of 5%, we found that 10% of the genes investigated showed significantly different expression ratios. CONCLUSION: Although the ratios were not fully preserved, amplification may prove to be extremely useful with respect to characterizing low expressing genes.