Myeloid sarcomas: a histologic, immunohistochemical, and cytogenetic study

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Evaluation of lung flute in sputum samples for molecular analysis of lung cancer

BACKGROUND: Molecular analysis of sputum provides a promising approach for lung cancer diagnosis, yet is limited by the difficulty in collecting the specimens from individuals who can’t spontaneously expectorate sputum. Lung Flute is a small self-powered audio device that can induce sputum by generating sound waves and vibrating in the airways of the lungs. Here we propose to evaluate the usefulness of Lung Flute for sputum sampling to assist diagnosis of lung cancer. METHODS: Forty-three stage I lung cancer patients and 47 cancer-free individuals who couldn’t spontaneously cough sputum were instructed to use Lung Flute for sputum sampling. Expressions of two microRNAs, miRs-31 and 210, were determined in the specimens by qRT-PCR. The results were compared with sputum cytology. RESULTS: Sputum was easily collected from 39 of 43 (90.7%) lung cancer patients and 42 of 47 (89.4%) controls with volume ranges from 1 to 5 ml (median, 2.6 ml). The specimens had less than 4% oral squamous cells, indicating that sputum was obtained from low respiratory tract. Expressions of miRs-31 and 210 in sputum were considerably higher in cancer patients than cancer-free individuals (8.990 vs. 4.514; 0.6847 vs. 0.3317; all P <0.001). Combined use of the two miRNAs produced a significantly higher sensitivity (61.5% vs. 35.9%, P = 0.002) and a slightly lower specificity (90.5% vs. 95.2%, p = 0.03) compared with cytology for lung cancer diagnosis. CONCLUSION: Lung Flute could potentially be useful in convenient and efficient collection of sputum for molecular diagnosis of lung cancer

Summarizing performance for genome scale measurement of miRNA: reference samples and metrics

Background: The potential utility of microRNA as biomarkers for early detection of cancer and other diseases is being investigated with genome-scale profiling of differentially expressed microRNA. Processes for measurement assurance are critical components of genome-scale measurements. Here, we evaluated the utility of a set of total RNA samples, designed with between-sample differences in the relative abundance of miRNAs, as process controls. Results: Three pure total human RNA samples (brain, liver, and placenta) and two different mixtures of these components were evaluated as measurement assurance control samples on multiple measurement systems at multiple sites and over multiple rounds. In silico modeling of mixtures provided benchmark values for comparison with physical mixtures. Biomarker development laboratories using next-generation sequencing (NGS) or genome-scale hybridization assays participated in the study and returned data from the samples using their routine workflows. Multiplexed and single assay reverse-transcription PCR (RT-PCR) was used to confirm in silico predicted sample differences. Data visualizations and summary metrics for genome-scale miRNA profiling assessment were developed using this dataset, and a range of performance was observed. These metrics have been incorporated into an online data analysis pipeline and provide a convenient dashboard view of results from experiments following the described design. The website also serves as a repository for the accumulation of performance values providing new participants in the project an opportunity to learn what may be achievable with similar measurement processes. Conclusions: The set of reference samples used in this study provides benchmark values suitable for assessing genome-scale miRNA profiling processes. Incorporation of these metrics into an online resource allows laboratories to periodically evaluate their performance and assess any changes introduced into their measurement process

Summarizing performance for genome scale measurement of miRNA: reference samples and metrics

Background: The potential utility of microRNA as biomarkers for early detection of cancer and other diseases is being investigated with genome-scale profiling of differentially expressed microRNA. Processes for measurement assurance are critical components of genome-scale measurements. Here, we evaluated the utility of a set of total RNA samples, designed with between-sample differences in the relative abundance of miRNAs, as process controls. Results: Three pure total human RNA samples (brain, liver, and placenta) and two different mixtures of these components were evaluated as measurement assurance control samples on multiple measurement systems at multiple sites and over multiple rounds. In silico modeling of mixtures provided benchmark values for comparison with physical mixtures. Biomarker development laboratories using next-generation sequencing (NGS) or genome-scale hybridization assays participated in the study and returned data from the samples using their routine workflows. Multiplexed and single assay reverse-transcription PCR (RT-PCR) was used to confirm in silico predicted sample differences. Data visualizations and summary metrics for genome-scale miRNA profiling assessment were developed using this dataset, and a range of performance was observed. These metrics have been incorporated into an online data analysis pipeline and provide a convenient dashboard view of results from experiments following the described design. The website also serves as a repository for the accumulation of performance values providing new participants in the project an opportunity to learn what may be achievable with similar measurement processes. Conclusions: The set of reference samples used in this study provides benchmark values suitable for assessing genome-scale miRNA profiling processes. Incorporation of these metrics into an online resource allows laboratories to periodically evaluate their performance and assess any changes introduced into their measurement process

Utilizing MiSeq Sequencing to Detect Circulating microRNAs in Plasma for Improved Lung Cancer Diagnosis

Non-small cell lung cancer (NSCLC) is a major contributor to cancer-related deaths, but early detection can reduce mortality. NSCLC comprises mainly adenocarcinoma (AC) and squamous cell carcinoma (SCC). Circulating microRNAs (miRNAs) in plasma have emerged as promising biomarkers for NSCLC. However, existing techniques for analyzing miRNAs have limitations, such as restricted target detection and time-consuming procedures. The MiSeqDx System has been shown to overcome these limitations, making it a promising tool for routine clinical settings. We investigated whether the MiSeqDx could profile cell-free circulating miRNAs in plasma and diagnose NSCLC. We sequenced RNA from the plasma of patients with AC and SCC and from cancer-free smokers using the MiSeqDx to profile and compare miRNA expressions. The MiSeqDx exhibits high speed and accuracy when globally analyzing plasma miRNAs. The entire workflow, encompassing RNA to data analysis, was completed in under three days. We also identified panels of plasma miRNA biomarkers that can diagnose NSCLC with 67% sensitivity and 68% specificity, and detect SCC with 90% sensitivity and 94% specificity, respectively. This study is the first to demonstrate that rapid profiling of plasma miRNAs using the MiSeqDx has the potential to offer a straightforward and effective method for the early detection and classification of NSCLC

Rapid and Sensitive Detection of SARS-CoV-2 Using Clustered Regularly Interspaced Short Palindromic Repeats

Rapid and accurate detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is essential for controlling the pandemic of coronavirus disease 2019. Polymerase chain reaction (PCR)-based technique is the standard test for detection of SARS-CoV-2, which, however, requires complicated sample manipulation (e.g., RNA extraction) and is time-consuming. We previously demonstrated that clustered regularly interspaced short palindromic repeats (CRISPR) could precisely detect Human papillomavirus and somatic mutations of Epidermal growth factor receptor gene and Kirsten rat sarcoma viral oncogene homolog gene in plasma. The objective of this study was to develop CRISPR as a rapid test for sensitive detection of SARS-CoV-2. We first combined reverse transcription-isothermal recombinase polymerase amplification and CRSIPR to detect SARS-CoV-2 in genomic RNA of cells infected with the virus. The CRISPR assay with guide RNA against the M gene of SARS-CoV-2 had a sensitivity of 0.1 copies per µL for detection of the virus. We then used the CRSIPR assay to directly analyze raw SARS-CoV-2 samples. The CRISPR assay could sensitively detect SARS-CoV-2 in one hour without RNA extraction. This assay can be performed at a single temperature and with minimal equipment. The results were immediately visualized either by a UV light illuminator or paper strips. The diagnostic value of the test was confirmed in nasopharyngeal swab specimens. Altogether, we have developed a rapid CRISPR test for sensitive detection of SARS-CoV-2