Statistical Issues in the Design and Analysis of nCounter Projects

Time of day bias for biological sampling in studies of mammary cancer

Despite its demonstrated biological significance, time of day is a broadly overlooked biological variable in preclinical and clinical studies. How time of day affects the influence of peripheral tumors on central (brain) function remains unspecified. Thus, we tested the hypothesis that peripheral mammary cancer tumors alter the transcriptome of immune responses in the brain and that these responses vary based on time of day; we predicted that time of day sampling bias would alter the interpretation of the results. Brain tissues collected at mid dark and mid light from mammary tumor-bearing and vehicle injected mice were analyzed using the Nanostring nCounter immune panel. Peripheral mammary tumors significantly affected expression within the brain of over 100 unique genes of the 770 represented in the panel, and fewer than 25% of these genes were affected similarly across the day. Indeed, between 65 and 75% of GO biological processes represented by the differentially expressed genes were dependent upon time of day of sampling. The implications of time-of-day sampling bias in interpretation of research studies cannot be understated. We encourage considering time of day as a significant biological variable in studies and to appropriately control for it and clearly report time of day in findings.

Metabolism-Based Gene Differences in Neurons Expressing Hyperphosphorylated AT8- Positive (AT8+) Tau in Alzheimer's Disease

Metabolic adaptations in the brain are critical to the establishment and maintenance of normal cellular functions and to the pathological responses to disease processes. Here, we have focused on specific metabolic pathways that are involved in immune-mediated neuronal processes in brain using isolated neurons derived from human autopsy brain sections of normal individuals and individuals diagnosed as Alzheimer's disease (AD). Laser capture microscopy was used to select specific cell types in immune-stained thin brain sections followed by NanoString technology to identify and quantify differences in mRNA levels between age-matched control and AD neuronal samples. Comparisons were also made between neurons isolated from AD brain sections expressing pathogenic hyperphosphorylated AT8- positive (AT8+) tau and non-AT8+ AD neurons using double labeling techniques. The mRNA expression data showed unique patterns of metabolic pathway expression between the subtypes of captured neurons that involved membrane based solute transporters, redox factors, and arginine and methionine metabolic pathways. We also identified the expression levels of a novel metabolic gene, Radical-S-Adenosyl Domain1 (RSAD1) and its corresponding protein, Rsad1, that impact methionine usage and radical based reactions. Immunohistochemistry was used to identify specific protein expression levels and their cellular location in NeuN+ and AT8+ neurons. APOE4 vs APOE3 genotype-specific and sex-specific gene expression differences in these metabolic pathways were also observed when comparing neurons from individuals with AD to age-matched individuals.

Multiplexed Detection and Quantitation of Extracellular Vesicle RNA Expression Using NanoString

Several different types of RNA molecules such as microRNAs (miRNAs) have been detected within extracellular vesicles in the circulation. The detection and potential utility of these as disease biomarkers requires the ability to detect their presence with adequate sensitivity and to quantitate their expression. The potential for circulating miRNA to serve as biomarkers can be evaluated through their detection in association with specific disease states. Multiplexed detection of several miRNA simultaneously can be useful for discovery studies. We describe the analysis of miRNA from biological fluids like plasma and serum using the Nanostring nCounter platform. Assays can be used to quantitate the expression of miRNA using direct detection based on hybridization to target specific color-coded probes followed by counting each color-coded barcode digitally.

Quantitating the effect of prosthesis design on femoral remodeling using high-resolution region-free densitometric analysis (DXA-RFA)

Dual energy X-ray absorptiometry (DXA) is the reference standard method used to study bone mineral density (BMD) after total hip arthroplasty (THA). However, the subtle, spatially complex changes in bone mass due to strain-adaptive bone remodeling relevant to different prosthesis designs are not readily resolved using conventional DXA analysis. DXA region free analysis (DXA RFA) is a novel computational image analysis technique that provides a high-resolution quantitation of periprosthetic BMD. Here, we applied the technique to quantitate the magnitude and areal size of periprosthetic BMD changes using scans acquired during two previous randomized clinical trials (2004 to 2009); one comparing three cemented prosthesis design geometries, and the other comparing a hip resurfacing versus a conventional cementless prosthesis. DXA RFA resolved subtle differences in magnitude and area of bone remodeling between prosthesis designs not previously identified in conventional DXA analyses. A mean bone loss of 10.3%, 12.1%, and 11.1% occurred for the three cemented prostheses within a bone area fraction of 14.8%, 14.4%, and 6.2%, mostly within the lesser trochanter (p < 0.001). For the cementless prosthesis, a diffuse pattern of bone loss (-14.3%) was observed at the shaft of femur in a small area fraction of 0.6% versus no significant bone loss for the hip resurfacing prosthesis (p < 0.001). BMD increases were observed consistently at the greater trochanter for all prostheses except the hip-resurfacing prosthesis, where BMD increase was widespread across the metaphysis (p < 0.001). DXA RFA provides high-resolution insights into the effect of prosthesis design on the local strain environment in bone. © 2017 The Authors Journal of Orthopaedic Research published by Wiley Periodicals, Inc. on behalf of Orthopaedic Research Society. J Orthop Res 35:2203-2210, 2017.

Detection of ALK fusion transcripts in FFPE lung cancer samples by NanoString technology

Background

ALK-rearranged lung cancers exhibit specific pathologic and clinical features and are responsive to anti-ALK therapies. Therefore, the detection of ALK-rearrangement is fundamental for personalized lung cancer therapy. Recently, new molecular techniques, such as NanoString nCounter, have been developed to detect ALK fusions with more accuracy and sensitivity.

Methods

In the present study, we intended to validate a NanoString nCounter ALK-fusion panel in routine biopsies of FFPE lung cancer patients. A total of 43 samples were analyzed, 13 ALK-positive and 30 ALK-negative, as previously detected by FISH and/or immunohistochemistry.

Results

The NanoString panel detected the presence of the EML4-ALK, KIF5B-ALK and TFG-ALK fusion variants. We observed that all the 13 ALK-positive cases exhibited genetic aberrations by the NanoString methodology. Namely, six cases (46.15%) presented EML-ALK variant 1, two (15.38%) presented EML-ALK variant 2, two (15.38%) presented EML-ALK variant 3a, and three (23.07%) exhibited no variant but presented unbalanced expression between 5’/3’ exons, similar to other positive samples. Importantly, for all these analyses, the initial input of RNA was 100 ng, and some cases displayed poor RNA quality measurements.

Conclusions

In this study, we reported the great utility of NanoString technology in the assessment of ALK fusions in routine lung biopsies of FFPE specimens.

Electronic supplementary material

The online version of this article (doi:10.1186/s12890-017-0428-0) contains supplementary material, which is available to authorized users.