Differential Non-Coding RNA Profiles for Lung Cancer Early Detection in African and White Americans.

Introduction: Lung cancer leads in cancer-related deaths. Disparities are observed in lung cancer rates, with African Americans (AAs) experiencing disproportionately higher incidence and mortality compared to other ethnic groups. Non-coding RNAs (ncRNAs) play crucial roles in lung tumorigenesis. Our objective was to identify ncRNA biomarkers associated with the racial disparity in lung cancer. Methods: Using droplet digital PCR, we examined 93 lung-cancer-associated ncRNAs in the plasma and sputum samples from AA and White American (WA) participants, which included 118 patients and 92 cancer-free smokers. Subsequently, we validated our results with a separate cohort comprising 56 cases and 72 controls. Results: In the AA population, plasma showed differential expression of ten ncRNAs, while sputum revealed four ncRNAs when comparing lung cancer patients to the control group. In the WA population, the plasma displayed eleven ncRNAs, and the sputum had five ncRNAs showing differential expression between the lung cancer patients and the control group. For AAs, we identified a three-ncRNA panel (plasma miRs-147b, 324-3p, 422a) diagnosing lung cancer in AAs with 86% sensitivity and 89% specificity. For WAs, a four-ncRNA panel was developed, comprising sputum miR-34a-5p and plasma miRs-103-3p, 126-3p, 205-5p, achieving 88% sensitivity and 87% specificity. These panels remained effective across different stages and histological types of lung tumors and were validated in the independent cohort. Conclusions: The ethnicity-related ncRNA signatures have promise as biomarkers to address the racial disparity in lung cancer.

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.

Streptococcus pneumoniae promotes lung cancer development and progression.

Streptococcus pneumoniae (SP) is associated with lung cancer, yet its role in the tumorigenesis remains uncertain. Herein we find that SP attaches to lung cancer cells via binding pneumococcal surface protein C (PspC) to platelet-activating factor receptor (PAFR). Interaction between PspC and PAFR stimulates cell proliferation and activates PI3K/AKT and nuclear factor kB (NF-kB) signaling pathways, which trigger a pro-inflammatory response. Lung cancer cells infected with SP form larger tumors in BALB/C mice compared to untreated cells. Mice treated with tobacco carcinogen and SP develop more lung tumors and had shorter survival period than mice treated with the carcinogen alone. Mutating PspC or PAFR abolishes tumor-promoting effects of SP. Overabundance of SP is associated with the survival. SP may play a driving role in lung tumorigenesis by activating PI3K/AKT and NF-kB pathways via binding PspC to PAFR and provide a microbial target for diagnosis and treatment of the disease.

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.

Sputum long non-coding RNA biomarkers for diagnosis of lung cancer.

BACKGROUND: Analysis of molecular changes in sputum may help diagnose lung cancer. Long non-coding RNAs (lncRNAs) play vital roles in various biological processes, and their dysregulations contribute to the development and progression of lung tumorigenesis. Herein, we determine whether aberrant lncRNAs could be used as potential sputum biomarkers for lung cancer. METHODS: Using reverse transcription PCR, we measure expressions of lung cancer-associated lncRNAs in sputum of a discovery cohort of 67 lung cancer patients and 65 cancer-free smokers with benign diseases and a validation cohort of 59 lung cancer patients and 60 cancer-free smokers with benign diseases. RESULTS: In the discovery cohort, four of the lncRNAs displayed a significantly different level in sputum of lung cancer patients vs.cancer-free smokers with benign diseases (all P< 0.001). From the four lncRNAs, three lncRNAs (SNHG1, H19, and HOTAIR) are identified as a biomarker panel, producing 82.09% sensitivity and 89.23% specificity for diagnosis of lung cancer. Furthermore, the biomarker panel has a higher sensitivity (82.09% vs. 52.24%, P= 0.02) and a similar specificity compared with sputum cytology (89.23% vs. 90.77%, P= 0.45). In addition, the lncRNA biomarker panel had a higher sensitivity (87.50% vs. 70.07%, p= 0.03) for diagnosis of squamous cell carcinoma compared with adenocarcinoma of the lung, while maintaining the same specificity (89.23%). The potential of the sputum lncRNA biomarkers for lung cancer detection is confirmed in the validation cohort. CONCLUSION: We have for the first time shown that the analysis of lncRNAs in sputum might be a noninvasive approach for 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.

Cell-based reference samples designed with specific differences in microRNA biomarkers.

BACKGROUND: We demonstrate the feasibility of creating a pair of reference samples to be used as surrogates for clinical samples measured in either a research or clinical laboratory setting. The reference sample paradigm presented and evaluated here is designed to assess the capability of a measurement process to detect true differences between two biological samples. Cell-based reference samples can be created with a biomarker signature pattern designed in silico. Clinical laboratories working in regulated applications are required to participate in proficiency testing programs; research laboratories doing discovery typically do not. These reference samples can be used in proficiency tests or as process controls that allow a laboratory to evaluate and optimize its measurement systems, monitor performance over time (process drift), assess changes in protocols, reagents, and/or personnel, maintain standard operating procedures, and most importantly, provide evidence for quality results. RESULTS: The biomarkers of interest in this study are microRNAs (miRNAs), small non-coding RNAs involved in the regulation of gene expression. Multiple lung cancer associated cell lines were determined by reverse transcription (RT)-PCR to have sufficiently different miRNA profiles to serve as components in mixture designs as reference samples. In silico models based on the component profiles were used to predict miRNA abundance ratios between two different cell line mixtures, providing target values for profiles obtained from in vitro mixtures. Two reference sample types were tested: total RNA mixed after extraction from cell lines, and intact cells mixed prior to RNA extraction. MicroRNA profiling of a pair of samples composed of extracted RNA derived from these cell lines successfully replicated the target values. Mixtures of intact cells from these lines also approximated the target values, demonstrating potential utility as mimics for clinical specimens. Both designs demonstrated their utility as reference samples for inter- or intra-laboratory testing. CONCLUSIONS: Cell-based reference samples can be created for performance assessment of a measurement process from biomolecule extraction through quantitation. Although this study focused on miRNA profiling with RT-PCR using cell lines associated with lung cancer, the paradigm demonstrated here should be extendable to genome-scale platforms and other biomolecular endpoints.

A Plasma Biomarker Panel to Identify Surgically Resectable Early-Stage Pancreatic Cancer.

Background: Blood-based biomarkers for early detection of pancreatic ductal adenocarcinoma (PDAC) are urgently needed. Current biomarkers lack high sensitivity and specificity for population screening. The gold-standard biomarker, CA 19-9, also fails to demonstrate the predictive value necessary for early detection. Methods: To validate a functional genomics-based plasma migration signature biomarker panel, plasma tissue factor pathway inhibitor (TFPI), tenascin C (TNC-FN III-C), and CA 19-9 levels were measured by enzyme-linked immunosorbent assays in three early-stage PDAC plasma cohorts, including two independent blinded validation cohorts containing a total of 43 stage I, 163 stage II, 86 chronic pancreatitis, 31 acute biliary obstruction, and 108 controls. Logistic regression models developed classification rules combining TFPI and/or TNC-FN III-C with CA 19-9 for patient cases and control subjects, with or without adjustment for age and diabetes status. Model classification performance was evaluated and analyses repeated among subpopulations without diabetes and pancreatitis history. Two-sided P values were calculated using bootstrap method. Results: The TFPI/TNC-FN III-C/CA 19-9 panel improved CA 19-9 performance in all early-stage cohorts, including discriminating stage IA/IB/IIA, stage IIB, and all early-stage cancer from healthy controls. Statistical significance was reached for a number of subcohorts, including for all early-stage cancer vs healthy controls (cohort 1 AUC = 0.92, 95% CI = 0.86 to 0.96, P = .04; cohort 3 AUC = 0.83, 95% CI = 0.76 to 0.89, P = .045). Among subcohorts without diabetes and pancreatitis history, the panel approaches potential clinical utility for early detection to discriminate early-stage PDAC from healthy controls including an area under the curve (AUC) of 0.87 (95% CI = 0.77 to 0.95) for stage I/IIA, an AUC of 0.93 (95% CI = 0.87 to 0.98) for stage IIB, and a statistically significant AUC of 0.89 (95% CI = 0.82 to 0.95) for all early-stage cancer ( P = .03). Conclusions: TFPI/TNC-FN III-C migration signature adds statistically significantly to CA 19-9's predictive power to detect early-stage PDAC and may have clinical utility for early detection of surgically resectable PDAC, as well as for enhanced survival from this routinely lethal cancer.

Analysis of small nucleolar RNAs in sputum for lung cancer diagnosis.

Molecular analysis of sputum presents a noninvasive approach for diagnosis of lung cancer. We have shown that dysregulation of small nucleolar RNAs (snoRNAs) plays a vital role in lung tumorigenesis. We have also identified six snoRNAs whose changes are associated with lung cancer. Here we investigated if analysis of the snoRNAs in sputum could provide a potential tool for diagnosis of lung cancer. Using qRT-PCR, we determined expressions of the six snoRNAs in sputum of a training set of 59 lung cancer patients and 61 cancer-free smokers to develop a biomarker panel, which was validated in a testing set of 67 lung cancer patients and 69 cancer-free smokers for the diagnostic performance. The snoRNAs were robustly measurable in sputum. In the training set, a panel of two snoRNA biomarkers (snoRD66 and snoRD78) was developed, producing 74.58% sensitivity and 83.61% specificity for identifying lung cancer. The snoRNA biomarkers had a significantly higher sensitivity (74.58%) compared with sputum cytology (45.76%) (P < 0.05). The changes of the snoRNAs were not associated with stage and histology of lung cancer (All P >0.05). The performance of the biomarker panel was confirmed in the testing cohort. We report for the first time that sputum snoRNA biomarkers might be useful to improve diagnosis of lung cancer.

Analysis of Lung Flute-collected Sputum for Lung Cancer Diagnosis.

Molecular analysis of sputum can help diagnose lung cancer. We have demonstrated that Lung Flute can be used to collect sputum from individuals who cannot spontaneously expectorate sputum. The objective of this study is to further evaluate the performance of the Lung Flute by comparing the characteristics of parallel samples collected with and without the Lung Flute and the usefulness for diagnosis of lung cancer. Fifty-six early-stage lung cancer patients (40 current smokers and 16 former smokers) and 73 cancer-free individuals (52 current smokers and 21 former smokers) were instructed to spontaneously cough and use Lung Flute for sputum sampling. Sputum cytology and polymerase chain reaction analysis of three miRNAs (miRs-21, 31, and 210) were performed in the specimens. All 92 current smokers and 11 (28.7%) of 37 former smokers spontaneously expectorated sputum and also produced sputum when using the Lung Flute. Twenty-seven former smokers (70.3%) who could not spontaneously expectorate sputum, however, were able to produce sputum when using the Lung Flute. The specimens were of low respiratory origin without contamination from other sources, eg, saliva. There was no difference of sputum volume and cell populations, diagnostic efficiency of cytology, and analysis of the miRNAs in the specimens collected by the two approaches. Analysis of the sputum miRNAs produced 83.93% sensitivity and 87.67% specificity for identifying lung cancer. Therefore, sputum collected by the Lung Flute has comparable features as spontaneously expectorated sputum. Using the Lung Flute enables former smokers who cannot spontaneously expectorate to provide adequate sputum to improve sputum collection for lung cancer diagnosis.

Differential miRNA expressions in peripheral blood mononuclear cells for diagnosis of lung cancer.

Tremendous efforts have been made to develop cancer biomarkers by detecting circulating extracellular miRNAs directly released from tumors. Yet, none of the cell-free biomarkers has been accepted to be used for early detection of non-small cell lung cancer (NSCLC). Peripheral blood mononucleated cells (PBMCs) act as the first line of defense against malignancy in immune system, their dysfunction may occur as an early event in cancer immunogenicity or immune evasion. We proposed to investigate whether analysis of miRNA expressions of PBMCs has diagnostic value for NSCLC. We first used a microarray to analyze PBMCs of 16 stage I NSCLC patients and 16 cancer-free smokers, and identified seven PBMC miRNAs with a significantly altered expression level in NSCLC patients. In a training set of 84 NSCLC patients and 69 cancer-free smokers, a panel of two miRNAs (miRs-19b-3p and -29b-3p) were developed from the seven PBMC miRNAs, producing 72.62% sensitivity and 82.61% specificity in identifying NSCLC. Furthermore, the miRNAs could identify squamous cell lung carcinoma (SCC), a major type of NSCLC, with 80.00% sensitivity and 89.86% specificity. The expression levels of the miRNAs were independent of disease stage. In a testing set of 56 NSCLC patients and 46 controls, the performance of the biomarkers was reproducibly confirmed. The study presents the first in-depth analysis of PBMC miRNA profile of NSCLC patients. The assessment of PBMC miRNAs may provide a new diagnostic approach for the early detection of NSCLC.

Sputum microRNA biomarkers for identifying lung cancer in indeterminate solitary pulmonary nodules.

PURPOSE: The early detection of lung cancer in heavy smokers by low-dose CT (LDCT) can reduce the mortality. However, LDCT screening increases the number of indeterminate solitary pulmonary nodules (SPN) in asymptomatic individuals, leading to overdiagnosis. Making a definitive preoperative diagnosis of malignant SPNs has been a clinical challenge. We have demonstrated that sputum miRNAs could provide potential biomarkers for lung cancer. Here, we aimed to develop sputum miRNA biomarkers for diagnosis of malignant SPNs. EXPERIMENTAL DESIGN: Using quantitative RT-PCR, we evaluated expressions of 13 sputum miRNAs, previously identified sputum miRNA signatures of lung cancer, in a training set of 122 patients with either malignant (n = 60) or benign SPNs (n = 62) to define a panel of biomarkers. We then validated the biomarker panel in an internal testing set of 136 patients with either malignant (n = 67) or benign SPNs (n = 69), and an external testing cohort of 155 patients with either malignant (n = 76) or benign SPNs (n = 79). RESULTS: In the training set, a panel of three miRNA biomarkers (miRs21, 31, and 210) was developed, producing 82.93% sensitivity and 87.84% specificity for identifying malignant SPNs. The sensitivity and specificity of the biomarkers in the two independent testing cohorts were 82.09% and 88.41%, 80.52% and 86.08%, respectively, confirming the diagnostic value. CONCLUSIONS: Sputum miRNA biomarkers may improve LDCT screening for lung cancer in heavy smokers by preoperatively diagnosing malignant SPNs. Nevertheless, a prospective study in a large population to validate the biomarkers is needed.

Genome-wide small nucleolar RNA expression analysis of lung cancer by next-generation deep sequencing.

Emerging evidence indicates that small nucleolar RNAs (snoRNAs), a class of small noncoding RNAs, may play important function in tumorigenesis. Nonsmall-cell lung cancer (NSCLC) is the number one cancer killer for men and women. Systematically characterizing snoRNAs in NSCLC will develop biomarkers for its early detection and prognostication. We used next-generation deep sequencing to comprehensively characterize snoRNA profiles in 12 NSCLC tissues. We used quantitative reverse transcription polymerase chain reaction (qRT-PCR) to verify the findings in 40 surgical Stage I NSCLC specimens and 126 frozen NSCLC tissues of different stages. The 126 NSCLC tissues were divided into a training set and a testing set. Deep sequencing identified 458 snoRNAs, of which, 29 had a ≥3.0-fold expression level change in Stage I NSCLC tissues versus normal tissues. qRT-PCR analysis showed that 16 of 29 snoRNAs exhibited consistent changes with deep sequencing data. The 16 snoRNAs exhibited 0.75-0.94 area under receiver-operator characteristic curve values in distinguishing lung tumor from normal lung tissues (all ≤0.0001) with 70.0-95.0% sensitivity and 70.0-95.0% specificity. Six genes (snoRA47, snoRA68, snoRA78, snoRA21, snoRD28 and snoRD66) were identified whose expressions were associated with overall survival of the NSCLC patients. A prediction model consisting of three genes (snoRA47, snoRA68 and snoRA78) was developed in the training set of 77 cases, which could significantly predict overall survival of the NSCLC patients (p < 0.0001). The prognostic performance of the prediction model was confirmed in the testing set of 49 NSCLC patients. The identified snoRNA signatures may provide potential biomarkers for the early detection and prognostication of NSCLC.

Characterization of microRNA transcriptome in lung cancer by next-generation deep sequencing.

Non-small cell lung cancer (NSCLC) is the leading cause of cancer death. Systematically characterizing miRNAs in NSCLC will help develop biomarkers for its diagnosis and subclassification, and identify therapeutic targets for the treatment. We used next-generation deep sequencing to comprehensively characterize miRNA profiles in eight lung tumor tissues consisting of two major types of NSCLC, squamous cell carcinoma (SCC) and adenocarcinoma (AC). We used quantitative PCR (qPCR) to verify the findings in 40 pairs of stage I NSCLC tissues and the paired normal tissues, and 60 NSCLC tissues of different types and stages. We also investigated the function of identified miRNAs in lung tumorigenesis. Deep sequencing identified 896 known miRNAs and 14 novel miRNAs, of which, 24 miRNAs displayed dysregulation with fold change ≥4.5 in either stage I ACs or SCCs or both relative to normal tissues. qPCR validation showed that 14 of 24 miRNAs exhibited consistent changes with deep sequencing data. Seven miRNAs displayed distinctive expressions between SCC and AC, from which, a panel of four miRNAs (miRs-944, 205-3p, 135a-5p, and 577) was identified that cold differentiate SCC from AC with 93.3% sensitivity and 86.7% specificity. Manipulation of miR-944 expression in NSCLC cells affected cell growth, proliferation, and invasion by targeting a tumor suppressor, SOCS4. Evaluating miR-944 in 52 formalin-fixed paraffin-embedded SCC tissues revealed that miR-944 expression was associated with lymph node metastasis. This study presents the earliest use of deep sequencing for profiling miRNAs in lung tumor specimens. The identified miRNA signatures may provide biomarkers for early detection, subclassification, and predicting metastasis, and potential therapeutic targets of NSCLC.

Analysis of MicroRNAs in sputum to improve computed tomography for lung cancer diagnosis.

INTRODUCTION: Computed tomography (CT) plays a central role in lung cancer diagnosis. However, CT has relatively low specificity, presenting a challenge in clinical settings. We previously identified 12 microRNAs (miRNAs) whose expressions in tumor tissues were associated with lung cancer. METHODS: Using quantitative reverse transcriptase polymerase chain reaction, we aimed to identify miRNA biomarkers in sputum that could complement CT for diagnosis of lung cancer. RESULTS: In a training set consisting of 66 lung cancer patients and 68 cancer-free smokers, 10 of the 12 miRNAs were differentially expressed between the cases and controls (p ≤ 0.01). From the miRNAs, a logistic regression model was built on the basis of miR-31 and miR-210, both of which had the best prediction for lung cancer, producing an area under receiver operating characteristic curve of 0.83. Combined use of the two miRNAs yielded 65.2% sensitivity and 89.7% specificity, CT had 93.9% sensitivity and 83.8% specificity for lung cancer diagnosis. Notably, combined analysis of the miRNA biomarkers and CT produced a higher specificity than does CT used alone (91.2% versus 83.8%; p < 0.05). The diagnostic performance of the biomarkers was confirmed in a testing set comprising 64 lung cancer patients and 73 cancer-free smokers. CONCLUSION: The sputum miRNA biomarkers might be useful in improving CT for diagnosis of lung cancer, but further independent validation on an external and prospective cohort of patients is required.

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.

Amplified RPS6KB1 and CDC2 genes are potential biomarkers for aggressive HIV+/EBV+ diffuse large B-cell lymphomas.

RPS6KB1 encodes p70S6K/p85S6K, which plays a role in the PI3K/Akt/mTOR signal transduction pathway. CDC2 gene encodes cdc2, which is critical for G2/M cell cycle progression. We had previously shown that amplified RPS6KB1 and CDC2 are commonly detected in the EBV+ diffuse large B-cell lymphoma (DLBCL) in HIV patients. In current study, we further evaluated the amplified RPS6KB1 and CDC2 genes in 12 HIV-related aggressive B-cell lymphomas and 10 non-HIV-related DLBCL using real time quantitative PCR. The cases were divided into 4 groups: 1) HIV-/EBV-; 2) HIV-/EBV+; 3) HIV+/EBV-; and 4) HIV+/EBV+. Receiver operating characteristic (ROC) curve and the area under the curve (AUC) was used to assess the ability of each gene to distinguish non-HIV+/EBV+ cases from HIV+/EBV+ cases. The AUC was estimated to be 0.76 for RPS6KB1 and 0.74 for CDC2 by using the Mann-Whitney statistic. Amplified RPS6KB1 and CDC2 genes were more frequently detected in common variants of DLBCL associated with HIV infection. Taken together, amplified RPS6KB1 and CDC2 are potential biomarkers for the aggressive DLBCL, particularly in HIV+/EBV+ patients. This study also suggests that the HIV+/EBV+ aggressive DLBCL could be potentially treated by targeting RPS6KB1 and CDC2 genes.

MicroRNAs as potential biomarkers in human solid tumors.

MicroRNAs (miRNAs) regulate the expression of approximately 30% of protein-coding genes. Functions of miRNAs are essential to maintain a steady state of cellular machinery. Dysregulations of miRNAs play pivotal roles in the initiation and progression of malignancies. Abnormal miRNA expressions have been found in a variety of human solid tumors. Furthermore, extracellular miRNAs could circulate in body fluids, and hence show great promise for refining diagnosis and prognosis of cancer. Here we review the progress of analysis of microRNAs as a potential approach for diagnosis and prognosis of solid cancer. We will also discuss obstacles in developing miRNAs as circulating biomarkers.

A panel of sputum-based genomic marker for early detection of lung cancer.

Non-small cell lung cancer (NSCLC) is the leading cause of cancer death. Early detection of NSCLC will improve its outcome. We previously identified genetic signatures whose genomic copy number aberrations were associated with early stage NSCLC. Here, we aimed to develop a panel of genes that could be detected in sputum for NSCLC early detection. We first optimized a panel of genes by using an in situ minichip for measuring changes of the signatures in sputum of a case-control cohort of 49 NSCLC patients, 49 patients with chronic obstructive pulmonary disease (COPD), and 49 healthy smokers. We then validated the genes in an independent cohort of 69 NSCLC patients and 65 noncancer subjects. The results were compared with those of sputum cytology. Fifteen genes showed significant differences of their copy number changes in sputum between NSCLC and both COPD and healthy subjects. A logistic regression model with the best prediction was built on the basis of 6 genes, ENO1, FHIT, HYAL2, SKP2, p16, and 14-3-3zeta. The composite of the 6 genes produced 86.7% sensitivity and 93.9% specificity in distinguishing stage I NSCLC patients from the noncancer individuals. Furthermore, the genes had higher sensitivity (86.9%) in identification of squamous cell carcinoma (SCC) than in adenocarcinoma of the lungs (80.8%; P < 0.05). Validation of the genes in the independent cohort confirmed their diagnostic power that also showed higher accuracy for lung SCCs than for sputum cytology. The gene panel could provide sputum-based markers that have the potential to improve early detection of lung SCCs.