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.

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.

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.

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.

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.

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.

ALDH1A1 is a marker for malignant prostate stem cells and predictor of prostate cancer patients' outcome.

Prostate cancer (PCa) contains a small population of cancer stem cells (CSCs) that contribute to its initiation and progression. The development of specific markers for identification of the CSCs may lead to new diagnostic strategies of PCa. Increased aldehyde dehydrogenase 1A1 (ALDH1A1) activity has been found in the stem cell populations of leukemia and some solid tumors. The aim of the study was to investigate the stem-cell-related function and clinical significance of the ALDH1A1 in human PCa. ALDEFLUOR assay was used to isolate ALDH1A1(+) cells from PCa cell lines. Stem cell characteristics of the ALDH1A1(+) cells were then investigated by in vitro and in vivo approaches. The ALDH1A1 expression was also analyzed by immunohistochemistry in 18 normal prostate and 163 PCa tissues. The ALDH1A1(+) PCa cells showed high clonogenic and tumorigenic capacities, and serially reinitiated transplantable tumors that resembled histopathologic characteristics and heterogeneity of the parental PCa cells in mice. Immunohistochemical analysis of human prostate tissues showed that ALDH1A1(+) cells were sparse and limited to the basal component in normal prostates. However, in tumor specimens, increased ALDH1A1 immunopositivity was found not only in secretory type cancer epithelial cells but also in neuroendocrine tumor populations. Furthermore, the high ALDH1A1 expression in PCa was positively correlated with Gleason score (P=0.01) and pathologic stage (P=0.01), and inversely associated with overall survival and cancer-specific survival of the patients (P=0.00093 and 0.00017, respectively). ALDH1A1 could be a prostate CSC-related marker. Measuring its expression might provide a potential approach to study tumorigenesis of PCa and predict outcome of the disease.

Aldehyde dehydrogenase 1 is a tumor stem cell-associated marker in lung cancer.

Tumor contains small population of cancer stem cells (CSC) that are responsible for its maintenance and relapse. Analysis of these CSCs may lead to effective prognostic and therapeutic strategies for the treatment of cancer patients. We report here the identification of CSCs from human lung cancer cells using Aldefluor assay followed by fluorescence-activated cell sorting analysis. Isolated cancer cells with relatively high aldehyde dehydrogenase 1 (ALDH1) activity display in vitro features of CSCs, including capacities for proliferation, self-renewal, and differentiation, resistance to chemotherapy, and expressing CSC surface marker CD133. In vivo experiments show that the ALDH1-positive cells could generate tumors that recapitulate the heterogeneity of the parental cancer cells. Immunohistochemical analysis of 303 clinical specimens from three independent cohorts of lung cancer patients and controls show that expression of ALDH1 is positively correlated with the stage and grade of lung tumors and related to a poor prognosis for the patients with early-stage lung cancer. ALDH1 is therefore a lung tumor stem cell-associated marker. These findings offer an important new tool for the study of lung CSCs and provide a potential prognostic factor and therapeutic target for treatment of the patients with lung cancer.

Phospho-p70S6K/p85S6K and cdc2/cdk1 are novel targets for diffuse large B-cell lymphoma combination therapy.

PURPOSE: This study aimed to identify and evaluate molecular targets for the development of a novel combination chemotherapy to treat refractory and recurrent diffuse large B-cell lymphoma (DLBCL). EXPERIMENTAL DESIGN: Lymphoma samples from 38 cases of primary and recurrent DLBCL were analyzed using real-time quantitative PCR of the RPS6KB1 and CDC2 genes, and immunohistochemistry for their gene products p70S6K/p85S6K and cdc2/cdk1. The Farage, Karpas422, Pfeiffer, and Toledo DLBCL cell lines were subsequently treated with rapamycin and UCN-01 alone or in combination. Cell proliferation, apoptosis, and cell cycle progression were analyzed after the drug treatment. In addition, the levels of several key protein kinases involved in the phosphoinositide 3'-kinase (PI3K)/Akt/mammalian target of rapamycin (mTOR) pathway, apoptosis, and cell cycle progression were analyzed in the presence and absence of the drugs. RESULTS: Amplification of the RPS6KB1 and CDC2 genes was found in both primary and recurrent DLBCL. Moreover, the vast majority of these lymphomas (approximately 94%) were strongly positive for phospho-p70S6K and cdc2/cdk1 proteins. The combination of rapamycin and UCN-01 synergistically inhibited the DLBCL cell proliferation by inducing G1 arrest as well as apoptosis by suppressing the phosphorylation of p70S6K/p85S6K and CDC2 expression. CONCLUSION: RPS6KB1 and CDC2 overexpression is common in DLBCL. Simultaneously targeting the RPS6KB1 and CDC2 products phospho-p70S6K/p85S6K and cdc2/cdk1 is very effective in inhibiting DLBCL proliferation and overcoming drug resistance. This work suggests that multilevel inhibition of the PI3K/Akt/mTOR pathway and double-block of cell cycle progression are effective strategies for DLBCL therapy.

Up-regulation of 14-3-3zeta in lung cancer and its implication as prognostic and therapeutic target.

A functional genomic approach integrating microarray and proteomic analyses done in our laboratory has identified 14-3-3zeta as a putative oncogene whose activation was common and driven by its genomic amplification in lung adenocarcinomas. 14-3-3zeta is believed to function in cell signaling, cycle control, and apoptotic death. Following our initial finding, here, we analyzed its expression in lung tumor tissues obtained from 205 patients with various histologic and stage non-small cell lung cancers (NSCLC) using immunohistochemistry and then explored the effects of specific suppression of the gene in vitro and in a xenograft model using small interfering RNA. The increased 14-3-3zeta expression was positively correlated with a more advanced pathologic stage and grade of NSCLCs (P = 0.001 and P = 0.006, respectively) and was associated with overall and cancer-specific survival rates of the patients (P = 0.022 and P = 0.018, respectively). Down-regulation of 14-3-3zeta in lung cancer cells led to a dose-dependent increased sensitivity to cisplatin-induced cell death, which was associated with the inhibition of cell proliferation and increased G2-M arrest and apoptosis. The result was further confirmed in the animal model, which showed that the A549 lung cancer cells with reduced 14-3-3zeta grew significantly slower than the wild-type A549 cells after cisplatin treatment (P = 0.008). Our results suggest that 14-3-3zeta is a potential target for developing a prognostic biomarker and therapeutics that can enhance the antitumor activity of cisplatin for NSCLC.

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.

Genetic deletions in sputum as diagnostic markers for early detection of stage I non-small cell lung cancer.

PURPOSE: Analysis of molecular genetic markers in biological fluids has been proposed as a powerful tool for cancer diagnosis. We have characterized in detail the genetic signatures in primary non-small cell lung cancer, which provided potential diagnostic biomarkers for lung cancer. The aim of this study was to determine whether the genetic changes can be used as markers in sputum specimen for the early detection of lung cancer. EXPERIMENTAL DESIGN: Genetic aberrations in the genes HYAL2, FHIT, and SFTPC were evaluated in paired tumors and sputum samples from 38 patients with stage I non-small cell lung cancer and in sputum samples from 36 cancer-free smokers and 28 healthy nonsmokers by using fluorescence in situ hybridization. RESULTS: HYAL2 and FHIT were deleted in 84% and 79% tumors and in 45% and 40% paired sputum, respectively. SFTPC was deleted exclusively in tumor tissues (71%). There was concordance of HYAL2 or FHIT deletions in matched sputum and tumor tissues from lung cancer patients (r = 0.82, P = 0.04; r = 0.84, P = 0.03), suggesting that the genetic changes in sputum might indicate the presence of the same genetic aberrations in lung tumors. Furthermore, abnormal cells were found in 76% sputum by detecting combined HYAL2 and FHIT deletions whereas in 47% sputum by cytology, of the cancer cases, implying that detecting the combination of HYAL2 and FHIT deletions had higher sensitivity than that of sputum cytology for lung cancer diagnosis. In addition, HYAL2 and FHIT deletions in sputum were associated with smoking history of cancer patients and smokers (both P < 0.05). CONCLUSIONS: Tobacco-related HYAL2 and FHIT deletions in sputum may constitute diagnostic markers for early-stage lung cancer.

Detecting genomic aberrations by fluorescence in situ hybridization with quantum dots-labeled probes.

Detection of genomic alterations of cancer genes by fluorescent in situ hybridization (FISH) will provide important information for cancer diagnosis and therapy. To effectively and reliably detect the genomic changes, we prepared novel FISH probes by directly conjugating genomic DNA of genes to semiconductor quantum dot fluorophores (QDs). The generated QD-genomic probes are substantially more photostable than the probes labeled with organic dye and show high intensity in both metaphase and interphase cell. The directly labeling probes allow detection of genomic targets in a fast and simple FISH procedure with high sensitivity and specificity. Furthermore, application of the QD-genomic probes in lung cancer specimens can reliably visualize gene amplification in cancer cells. These results suggest that the QD-FISH probes may offer an effective approach to analyze cancer-related genomic aberrations in basic research and clinical applications.

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.

Angiogenic inhibition mediated by a DNAzyme that targets vascular endothelial growth factor receptor 2.

The vascular endothelial growth factor receptor (VEGFR) is an important angiogenic target for cancer gene therapy. In this study, we designed an mRNA-cleaving oligodeoxynucleotide that targets the VEGF receptor 2 (VEGFR2) transcript (VEGFR2 DNAzyme). This DNAzyme was found to digest efficiently mRNA substrates of VEGFR2 in a concentration- and time-dependent manner. We also showed that the DNAzyme induces apoptosis and markedly inhibits endothelial cell growth compared with a disabled DNAzyme and untreated controls. In contrast, the DNAzyme did not inhibit the growth of MDA-MB-435 cells in vitro. The DNAzyme in complex with a nonviral carrier also significantly inhibited tumor growth in vivo. After the fourth injection, there was nearly a 75% reduction of tumor size in the DNAzyme-treated group compared with the saline-injected control group (P = 0.024). Marked cell death in the peripheral regions of the tumor accompanied by a reduction in blood vessel density is consistent with the antiangiogenic mechanism of the DNAzyme. This study indicates that DNAzymes, targeting angiogenic growth factors of tumors, show promise as antitumor agents.

An unsupervised approach to identify molecular phenotypic components influencing breast cancer features.

To discover a biological basis for clinical subgroupings within breast cancers, we applied principal components (PCs) analysis to cDNA microarray data from 36 breast cancers. We correlated the resulting PCs with clinical features. The 35 PCs discovered were ranked in order of their impact on gene expression patterns. Interestingly, PC 7 identified a unique subgroup consisting of estrogen receptor (ER); (+) African-American patients. This group exhibited global molecular phenotypes significantly different from both ER (-) African-American women and ER (+) or ER (-) Caucasian women (P < 0.001). Additional significant PCs included PC 4, correlating with lymph node metastasis (P = 0.04), and PC 10, with tumor stage (stage 2 versus stage 3; P = 0.007). These results provide a molecular phenotypic basis for the existence of a biologically unique subgroup comprising ER (+) breast cancers from African-American patients. Moreover, these findings illustrate the potential of PCs analysis to detect molecular phenotypic bases for relevant clinical or biological features of human tumors in general.

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.