Quantification of Normal Cell Fraction and Copy Number Neutral LOH in Clinical Lung Cancer Samples Using SNP Array Data

Background

Technologies based on DNA microarrays have the potential to provide detailed information on genomic aberrations in tumor cells. In practice a major obstacle for quantitative detection of aberrations is the heterogeneity of clinical tumor tissue. Since tumor tissue invariably contains genetically normal stromal cells, this may lead to a failure to detect aberrations in the tumor cells.

Principal Finding

Using SNP array data from 44 non-small cell lung cancer samples we have developed a bioinformatic algorithm that accurately models the fractions of normal and tumor cells in clinical tumor samples. The proportion of normal cells in combination with SNP array data can be used to detect and quantify copy number neutral loss-of-heterozygosity (CNNLOH) in the tumor cells both in crude tumor tissue and in samples enriched for tumor cells by laser capture microdissection.

Conclusion

Genome-wide quantitative analysis of CNNLOH using the CNNLOH Quantifier method can help to identify recurrent aberrations contributing to tumor development in clinical tumor samples. In addition, SNP-array based analysis of CNNLOH may become important for detection of aberrations that can be used for diagnostic and prognostic purposes.     

Binomial mitotic segregation of MYCN-carrying double minutes in neuroblastoma illustrates the role of randomness in oncogene amplification

Background

Amplification of the oncogene MYCN in double minutes (DMs) is a common finding in neuroblastoma (NB). Because DMs lack centromeric sequences it has been unclear how NB cells retain and amplify extrachromosomal MYCN copies during tumour development.

Principal Findings

We show that MYCN-carrying DMs in NB cells translocate from the nuclear interior to the periphery of the condensing chromatin at transition from interphase to prophase and are preferentially located adjacent to the telomere repeat sequences of the chromosomes throughout cell division. However, DM segregation was not affected by disruption of the telosome nucleoprotein complex and DMs readily migrated from human to murine chromatin in human/mouse cell hybrids, indicating that they do not bind to specific positional elements in human chromosomes. Scoring DM copy-numbers in ana/telophase cells revealed that DM segregation could be closely approximated by a binomial random distribution. Colony-forming assay demonstrated a strong growth-advantage for NB cells with high DM (MYCN) copy-numbers, compared to NB cells with lower copy-numbers. In fact, the overall distribution of DMs in growing NB cell populations could be readily reproduced by a mathematical model assuming binomial segregation at cell division combined with a proliferative advantage for cells with high DM copy-numbers.

Conclusion

Binomial segregation at cell division explains the high degree of MYCN copy-number variability in NB. Our findings also provide a proof-of-principle for oncogene amplification through creation of genetic diversity by random events followed by Darwinian selection.     

Down-regulation of serum/glucocorticoid regulated kinase 1 in colorectal tumours is largely independent of promoter hypermethylation

Background

We have previously shown that serum/glucocorticoid regulated kinase 1 (SGK1) is down-regulated in colorectal cancers (CRC) with respect to normal tissue. As hyper-methylation of promoter regions is a well-known mechanism of gene silencing in cancer, we tested whether the SGK1 promoter region was methylated in colonic tumour samples.

Methodology/Principal Findings

We investigated the methylation profile of the two CpG islands present in the promoter region of SGK1 in a panel of 5 colorectal cancer cell lines by sequencing clones of bisulphite-treated DNA samples. We further confirmed our findings in a panel of 10 normal and 10 tumour colonic tissue samples of human origin. We observed CpG methylation only in the smaller and more distal CpG island in the promoter region of SGK1 in both normal and tumour samples of colonic origin. We further identified a single nucleotide polymorphism (SNP, rs1743963) which affects methylation of the corresponding CpG.

Conclusions/Significance

Our results show that even though partial methylation of the promoter region of SGK1 is present, this does not account for the different expression levels seen between normal and tumour tissue.     

Assessing agreement between multiple raters with missing rating information, applied to breast cancer tumour grading

Background

We consider the problem of assessing inter-rater agreement when there are missing data and a large number of raters. Previous studies have shown only ‘moderate’ agreement between pathologists in grading breast cancer tumour specimens. We analyse a large but incomplete data-set consisting of 24177 grades, on a discrete 1–3 scale, provided by 732 pathologists for 52 samples.

Methodology/Principal Findings

We review existing methods for analysing inter-rater agreement for multiple raters and demonstrate two further methods. Firstly, we examine a simple non-chance-corrected agreement score based on the observed proportion of agreements with the consensus for each sample, which makes no allowance for missing data. Secondly, treating grades as lying on a continuous scale representing tumour severity, we use a Bayesian latent trait method to model cumulative probabilities of assigning grade values as functions of the severity and clarity of the tumour and of rater-specific parameters representing boundaries between grades 1–2 and 2–3. We simulate from the fitted model to estimate, for each rater, the probability of agreement with the majority. Both methods suggest that there are differences between raters in terms of rating behaviour, most often caused by consistent over- or under-estimation of the grade boundaries, and also considerable variability in the distribution of grades assigned to many individual samples. The Bayesian model addresses the tendency of the agreement score to be biased upwards for raters who, by chance, see a relatively ‘easy’ set of samples.

Conclusions/Significance

Latent trait models can be adapted to provide novel information about the nature of inter-rater agreement when the number of raters is large and there are missing data. In this large study there is substantial variability between pathologists and uncertainty in the identity of the ‘true’ grade of many of the breast cancer tumours, a fact often ignored in clinical studies.     

Using the realized relationship matrix to disentangle confounding factors for the estimation of genetic variance components of complex traits

Background

In the analysis of complex traits, genetic effects can be confounded with non-genetic effects, especially when using full-sib families. Dominance and epistatic effects are typically confounded with additive genetic and non-genetic effects. This confounding may cause the estimated genetic variance components to be inaccurate and biased.

Methods

In this study, we constructed genetic covariance structures from whole-genome marker data, and thus used realized relationship matrices to estimate variance components in a heterogenous population of ~ 2200 mice for which four complex traits were investigated. These mice were genotyped for more than 10,000 single nucleotide polymorphisms (SNP) and the variances due to family, cage and genetic effects were estimated by models based on pedigree information only, aggregate SNP information, and model selection for specific SNP effects.

Results and conclusions

We show that the use of genome-wide SNP information can disentangle confounding factors to estimate genetic variances by separating genetic and non-genetic effects. The estimated variance components using realized relationship were more accurate and less biased, compared to those based on pedigree information only. Models that allow the selection of individual SNP in addition to fitting a relationship matrix are more efficient for traits with a significant dominance variance.     

qpure: A Tool to Estimate Tumor Cellularity from Genome-Wide Single-Nucleotide Polymorphism Profiles

Tumour cellularity, the relative proportion of tumour and normal cells in a sample, affects the sensitivity of mutation detection, copy number analysis, cancer gene expression and methylation profiling. Tumour cellularity is traditionally estimated by pathological review of sectioned specimens; however this method is both subjective and prone to error due to heterogeneity within lesions and cellularity differences between the sample viewed during pathological review and tissue used for research purposes. In this paper we describe a statistical model to estimate tumour cellularity from SNP array profiles of paired tumour and normal samples using shifts in SNP allele frequency at regions of loss of heterozygosity (LOH) in the tumour. We also provide qpure, a software implementation of the method. Our experiments showed that there is a medium correlation 0.42 (-value = 0.0001) between tumor cellularity estimated by qpure and pathology review. Interestingly there is a high correlation 0.87 (-value 2.2e-16) between cellularity estimates by qpure and deep Ion Torrent sequencing of known somatic KRAS mutations; and a weaker correlation 0.32 (-value = 0.004) between IonTorrent sequencing and pathology review. This suggests that qpure may be a more accurate predictor of tumour cellularity than pathology review. qpure can be downloaded from https://sourceforge.net/projects/qpure/.     

Fatty Acid Amide Hydrolase in Prostate Cancer: Association with Disease Severity and Outcome,CB1 Receptor Expression and Regulation by IL-4

Background

Recent data have indicated that there may be a dysregulation of endocannabinoid metabolism in cancer. Here we have investigated the expression of the endocannabinoid metabolising enzyme fatty acid amide hydrolase (FAAH) in a well characterised tissue microarray from patients diagnosed with prostate cancer at transurethral resection for voiding problems.

Methodology/Principal Findings

FAAH immunoreactivity (FAAH-IR) was assessed in formalin-fixed paraffin-embedded non-malignant and tumour cores from 412 patients with prostate cancer. CB₁ receptor immunoreactivity (CB₁IR) scores were available for this dataset. FAAH-IR was seen in epithelial cells and blood vessel walls but not in the stroma. Tumour epithelial FAAH-IR was positively correlated with the disease severity at diagnosis (Gleason score, tumour stage, % of the specimen that contained tumour) for cases with mid-range CB₁IR scores, but not for those with high CB₁IR scores. For the 281 cases who only received palliative therapy at the end stages of the disease, a high tumour epithelial FAAH-IR was associated with a poor disease-specific survival. Multivariate Cox proportional-hazards regression analyses indicated that FAAH-IR gave additional prognostic information to that provided by CB₁IR when a midrange, but not a high CB₁IR cutoff value was used. Interleukin-4 (IL-4) receptor IR was found on tumour epithelial cells and incubation of prostate cancer PC-3 and R3327 AT1 cells with IL-4 increased their FAAH activity.

Conclusions/Significance

Tumour epithelial FAAH-IR is associated with prostate cancer severity and outcome at mid-range, but not high, CB₁IR scores. The correlation with CB₁IR in the tumour tissue may be related to a common local dysregulation by a component of the tumour microenvironment.     

Long noncoding RNA LINC00978 promotes cancer growth and acts as a diagnostic biomarker in gastric cancer

Objectives

Long noncoding RNAs (lncRNAs) play important roles in cancer development and progression. The deregulated expression of LINC00978 has been reported in human cancers. However, the expression pattern and biological roles of LINC00978 in gastric cancer (GC) remain unclear. In this study, we investigated the potential roles and clinical value of LINC00978 in gastric cancer.

Materials and methods

QRT‐PCR was performed to investigate the expression of LINC00978 in gastric cancer cell lines, tissues and serum samples. Cell counting, colony formation, transwell migration and matrigel invasion assays were performed to determine the effects of shRNA‐mediated knockdown of LINC00978 on gastric cancer cell functions. In vivo tumour growth assay was also conducted. Flow cytometry, immunohistochemistry, western blot and qRT‐PCR were used for potential mechanism study.

Results

LINC00978 expression level was elevated in GC tumour tissues, serum samples and cell lines. The expression level of LINC00978 was significantly correlated with tumour size (P = 0.02), lymphatic metastasis (P = 0.009) and TNM stage (P = 0.009). LINC00978 knockdown inhibited the proliferation of GC cells by suppressing cell cycle progression and inducing apoptosis. LINC00978 knockdown also inhibited the migration and invasion of GC cells. In addition, LINC00978 knockdown inhibited the activation of TGF‐β/SMAD signalling pathway and the process of epithelial‐mesenchymal transition (EMT) in GC cells. Moreover, the in vivo tumorigenicity of LINC00978 knockdown GC cells in mice was significantly decreased.

Conclusions

LINC00978 promotes gastric cancer progression and may serve as a potential biomarker for GC.     

Gamma-Smooth Muscle Actin Expression Is Associated with Epithelial-Mesenchymal Transition and Stem-Like Properties in Hepatocellular Carcinoma

Background and Aims

The prognosis of hepatocellular carcinoma (HCC) is hampered by frequent tumour recurrence and metastases. Epithelial-Mesenchymal Transition (EMT) is now recognized as a key process in tumour invasion, metastasis and the generation of cancer initiating cells. The morphological identification of EMT in tumour samples from the expression of novel mesenchymal markers could provide relevant prognostic information and aid in understanding the metastatic process.

Methods

The expression of Smooth Muscle Actins was studied using immunofluorescence and immunohistochemistry assays in cultured liver cells during an induced EMT process and in liver specimens from adult and paediatric HCC series.

Results

We report here that in HCC cell lines treated with TGF-β and in HCC specimens, the expression of αSMA, a known mesenchymal marker of EMT, could never be detected. In addition, our in vitro studies identified the enteric form of SMA, γSMA, as being a marker of EMT. Moreover, this SMA isoform was expressed in 46% of 58 tumours from 42 adult HCC patients and in 90% of 16 tumours from 12 paediatric HCC patients. Interestingly, this expression was significantly correlated with poor tumour differentiation and progenitor cell features characterized by the expression of EpCAM and K19.

Conclusion

Taken together, our results support the conclusion that γSMA expression in HCC is strongly correlated with the EMT process, HCC aggressiveness and the identification of cancer stem cells. This correlation suggests that γSMA represents a novel and powerful marker to predict HCC progression.     

A forward-backward fragment assembling algorithm for the identification of genomic amplification and deletion breakpoints using high-density single nucleotide polymorphism (SNP) array

Background  

DNA copy number aberration (CNA) is one of the key characteristics of cancer cells. Recent studies demonstrated the feasibility of utilizing high density single nucleotide polymorphism (SNP) genotyping arrays to detect CNA. Compared with the two-color array-based comparative genomic hybridization (array-CGH), the SNP arrays offer much higher probe density and lower signal-to-noise ratio at the single SNP level. To accurately identify small segments of CNA from SNP array data, segmentation methods that are sensitive to CNA while resistant to noise are required.     

Rapid Detection of SNP (c.309T>G) in the MDM2 Gene by the Duplex SmartAmp Method

Background

Genetic polymorphisms in the human MDM2 gene are suggested to be a tumor susceptibility marker and a prognostic factor for cancer. It has been reported that a single nucleotide polymorphism (SNP) c.309T>G in the MDM2 gene attenuates the tumor suppressor activity of p53 and accelerates tumor formation in humans.

Methodology

In this study, to detect the SNP c.309T>G in the MDM2 gene, we have developed a new SNP detection method, named “Duplex SmartAmp,” which enabled us to simultaneously detect both 309T and 309G alleles in one tube. To develop this new method, we introduced new primers i.e., nBP and oBPs, as well as two different fluorescent dyes that separately detect those genetic polymorphisms.

Results and Conclusions

By the Duplex SmartAmp method, the genetic polymorphisms of the MDM2 gene were detected directly from a small amount of genomic DNA or blood samples. We used 96 genomic DNA and 24 blood samples to validate the Duplex SmartAmp by comparison with results of the conventional PCR-RFLP method; consequently, the Duplex SmartAmp results agreed totally with those of the PCR-RFLP method. Thus, the new SNP detection method is considered useful for detecting the SNP c.309T>G in the MDM2 gene so as to judge cancer susceptibility against some cellular stress in the clinical setting, and also to handle a large number of samples and enable rapid clinical diagnosis.     

Are online prediction tools a valid alternative to genomic profiling in the context of systemic treatment of ER-positive breast cancer?

Background

Clinicians use clinical and pathological parameters, such as tumour size, grade and nodal status, to make decisions on adjuvant treatments for breast cancer. However, therapeutic decisions based on these features tend to vary due to their subjectivity. Computational and mathematical algorithms were developed using clinical outcome data from breast cancer registries, such as Adjuvant! Online and NHS PREDICT. More recently, assessments of molecular profiles have been applied in the development of better prognostic tools.

Methods

Based on the available literature on online registry-based tools and genomic assays, we evaluated whether these online tools could be valid and accurate alternatives to genomic and molecular profiling of the individual breast tumour in aiding therapeutic decisions, particularly in patients with early ER-positive breast cancer.

Results and conclusions

Early breast cancer is currently considered a systemic disease and a complex ecosystem with behaviour determined by the complex genetic and molecular signatures of the tumour cells, mammary stem cells, microenvironment and host immune system. We anticipate that molecular profiling will continue to evolve, expanding beyond the primary tumour to include the tumour microenvironment, cancer stem cells and host immune system. This should further refine therapeutic decisions and optimise clinical outcome.This article was specially invited by the editors and represents work by leading researchers.

     

Multivariate meta-analysis of proteomics data from human prostate and colon tumours

Background  

There is a vast need to find clinically applicable protein biomarkers as support in cancer diagnosis and tumour classification. In proteomics research, a number of methods can be used to obtain systemic information on protein and pathway level on cells and tissues. One fundamental tool in analysing protein expression has been two-dimensional gel electrophoresis (2DE). Several cancer 2DE studies have reported partially redundant lists of differently expressed proteins. To be able to further extract valuable information from existing 2DE data, the power of a multivariate meta-analysis will be evaluated in this work.     

Similar Source of Differential Blood mRNAs in Lung Cancer and Pulmonary Inflammatory Diseases: Calls for Improved Strategy for Identifying Cancer-Specific Biomarkers

Background

Many studies try to identify cancer diagnostic biomarkers by comparing peripheral whole blood (PWB) of cancer samples and healthy controls, explicitly or implicitly assuming that such biomarkers are potential candidate biomarkers for distinguishing cancer from nonmalignant inflammation-associated diseases.

Methods

Multiple PWB gene expression profiles for lung cancer/inflammation-associated pulmonary diseases were used for differential mRNAs identification and comparison and for proportion estimation of PWB cell subtypes.

Results

The differentially expressed genes (DE genes) between lung cancer/inflammation-associated pulmonary patients and healthy controls were reproducibly identified in different datasets. For these DE genes observed in lung cancer/inflammation-associated pulmonary diseases, more than 90.2% were differentially expressed between myeloid cells and lymphoid cells, with at least 96.8% having consistent directions of regulation (up- or down-regulations) in myeloid cells compared to lymphoid cells, explainable by the shifted populations of PWB cell subtypes under the disease conditions. The comparison of DE genes for lung cancer and inflammation-associated pulmonary diseases showed that the overlapping genes were 100% consistent in the sense of direction of regulation.

Conclusions

The differential blood mRNAs observed in lung cancer and in inflammation-associated pulmonary diseases were similar, both mainly reflecting the difference between myeloid cells and lymphoid cells predominantly determined by PWB cell population shifts. Thus, the strategy of comparing cancer with healthy controls may provide little information of the ability of the identified candidate biomarkers in discriminating cancer from inflammation-associated pulmonary diseases.     

High fragmentation characterizes tumour-derived circulating DNA

Background

Circulating DNA (ctDNA) is acknowledged as a potential diagnostic tool for various cancers including colorectal cancer, especially when considering the detection of mutations. Certainly due to lack of normalization of the experimental conditions, previous reports present many discrepancies and contradictory data on the analysis of the concentration of total ctDNA and on the proportion of tumour-derived ctDNA fragments.

Methodology

In order to rigorously analyse ctDNA, we thoroughly investigated ctDNA size distribution. We used a highly specific Q-PCR assay and athymic nude mice xenografted with SW620 or HT29 human colon cancer cells, and we correlated our results by examining plasma from metastatic CRC patients.

Conclusion/Significance

Fragmentation and concentration of tumour-derived ctDNA is positively correlated with tumour weight. CtDNA quantification by Q-PCR depends on the amplified target length and is optimal for 60–100 bp fragments. Q-PCR analysis of plasma samples from xenografted mice and cancer patients showed that tumour-derived ctDNA exhibits a specific amount profile based on ctDNA size and significant higher ctDNA fragmentation. Metastatic colorectal patients (n = 12) showed nearly 5-fold higher mean ctDNA fragmentation than healthy individuals (n = 16).     

Phospho-Akt Immunoreactivity in Prostate Cancer: Relationship to Disease Severity and Outcome,Ki67 and Phosphorylated EGFR Expression

Background

In the present study, we have investigated the prognostic usefulness of phosphorylated Akt immunoreactivity (pAkt-IR) in prostate cancer using a well-characterised tissue microarray from men who had undergone transurethral resection due to lower urinary tract symptoms.

Methodology/Principal Findings

pAkt-IR in prostate epithelial and tumour cells was assessed using a monoclonal anti-pAkt (Ser⁴⁷³) antibody. Immunoreactive intensity was determined for 282 (tumour) and 240 (non-mlignant tissue) cases. Tumour pAkt-IR scores correlated with Gleason score, tumour Ki67-IR (a marker of cell proliferation) and tumour phosphorylated epidermal growth factor receptor (pEGFR)-IR. For cases followed with expectancy, a high tumour pAkt-IR was associated with a poor disease-specific survival, and the prognostic information provided by this biomarker was additive to that provided by either (but not both) tumour pEFGR-IR or Ki67-IR. Upon division of the cases with respect to their Gleason scores, the prognostic value of pAkt-IR was seen for patients with Gleason score 8–10, but not for patients with Gleason score 6–7.

Conclusions/Significance

Tumour pAkt-IR is associated with both disease severity and disease-specific survival. However, its clinical use as a biomarker is limited, since it does not provide prognostic information in patients with Gleason scores 6–7.     

ErbB2 Receptor Immunoreactivity in Prostate Cancer: Relationship to the Androgen Receptor,Disease Severity at Diagnosis and Disease Outcome

Background

ErbB2 is a member of the epidermal growth factor family of tyrosine kinases that is centrally involved in the pathogenesis of prostate cancer and several studies have reported that a high expression of this protein has prognostic value. In the present study, we have investigated whether tumour ErbB2 immunoreactivity (ErbB2-IR) has clinically useful prognostic value, i.e. that it provides additional prognostic information to that provided by routine clinical tests (Gleason score, tumour stage).

Methodology/Principal Findings

ErbB2-IR was measured in a well-characterised tissue microarray of tumour and non-malignant samples obtained at diagnosis. Additionally, mRNA levels of ErbB2-IR in the prostate were determined in the rat following manipulation of circulating androgen levels. Tumour ErbB2-IR was significantly associated with the downstream signalling molecule phosphorylated-Akt and with the cell proliferation marker Ki-67. The significant association of tumour ErbB2-IR with the Gleason score at diagnosis was lost when controlled for the association of both parameters with Ki-67. In the rat prostate, mRNA for ErbB2 was inversely associated with circulating androgen levels. There was no association between ErbB2-IR and the androgen receptor (AR)-IR in the tumours, but an interaction between the two parameters was seen with respect to their association with the tumour stage. Tumour ErbB2-IR was confirmed to be a prognostic marker for disease-specific survival, but it did not provide significant additive information to the Gleason score or to Ki-67.

Conclusions/Significance

It is concluded that tumour ErbB2-IR is of limited clinical value as a prognostic marker to aid treatment decisions, but could be of pathophysiological importance in prostate cancer.     

The Use of Exome Genotyping to Predict Pathological Gleason Score Upgrade after Radical Prostatectomy in Low-Risk Prostate Cancer Patients

Background

Active surveillance (AS) is a promising option for patients with low-risk prostate cancer (PCa), however current criteria could not select the patients correctly, many patients who fulfilled recent AS criteria experienced pathological Gleason score upgrade (PGU) after radical prostatectomy (RP). In this study, we aimed to develop an accurate model for predicting PGU among low-risk PCa patients by using exome genotyping.

Methods

We genotyped 242,221 single nucleotide polymorphisms (SNP)s on a custom HumanExome BeadChip v1.0 (Illuminam Inc.) in blood DNA from 257 low risk PCa patients (PSA <10 ng/ml, biopsy Gleason score (GS) ≤6 and clinical stage ≤T2a) who underwent radical prostatectomy. Genetic data were analyzed using an unconditional logistic regression to calculate an odds ratio as an estimate of relative risk of PGU, which defined pathologic GS above 7. Among them, we selected persistent SNPs after multiple testing using FDR method, and we compared accuracies from the multivariate logistic model incorporating clinical factors between included and excluded selected SNP information.

Results

After analysis of exome genotyping, 15 SNPs were significant to predict PGU in low risk PCa patients. Among them, one SNP – rs33999879 remained significant after multiple testing. When a multivariate model incorporating factors in Epstein definition – PSA density, biopsy GS, positive core number, tumor per core ratio and age was devised for the prediction of PGU, the predictive accuracy of the multivariate model was 78.4% (95%CI: 0.726–0.834). By addition the factor of rs33999879 in aforementioned multivariate model, the predictive accuracy was 82.9%, which was significantly increased (p = 0.0196).

Conclusion

The rs33999879 SNP is a predictor for PGU. The addition of genetic information from the exome sequencing effectively enhanced the predictive accuracy of the multivariate model to establish suitable active surveillance criteria.     

Power in pairs: assessing the statistical value of paired samples in tests for differential expression

Background

When genomics researchers design a high-throughput study to test for differential expression, some biological systems and research questions provide opportunities to use paired samples from subjects, and researchers can plan for a certain proportion of subjects to have paired samples. We consider the effect of this paired samples proportion on the statistical power of the study, using characteristics of both count (RNA-Seq) and continuous (microarray) expression data from a colorectal cancer study.

Results

We demonstrate that a higher proportion of subjects with paired samples yields higher statistical power, for various total numbers of samples, and for various strengths of subject-level confounding factors. In the design scenarios considered, the statistical power in a fully-paired design is substantially (and in many cases several times) greater than in an unpaired design.

Conclusions

For the many biological systems and research questions where paired samples are feasible and relevant, substantial statistical power gains can be achieved at the study design stage when genomics researchers plan on using paired samples from the largest possible proportion of subjects. Any cost savings in a study design with unpaired samples are likely accompanied by underpowered and possibly biased results.