Engineered Platelet for In Situ Natural Killer Cell Activation to Inhibit Tumor Recurrence.

Natural killer (NK) cells offer profound advantages against tumor recurrence due to their unique immunological behavior. NK cell therapies associated with the antibody-dependent cell-mediated cytotoxicity (ADCC) effect have made remarkable progress while being limited by insufficient antibody binding and the exhausted state of NK cells in the postsurgical immunosuppressive microenvironment. Leveraging the adherence of PLT to tumor cells, we developed an exogenously implanted platelet (PLT)-based NK cell-driven system (PLT-IgG-IL15) to improve the identifiability of residual tumors with IgG antibody labeling for NK cells catching and engaging, which consequently restored the ADCC effect and promoted the recovery of their killing function. Furthermore, interleukin-15 (IL-15) participated in the augmentation of NK cell function. Collectively, PLT-IgG-IL15 served as an NK cell tumor cell engager as well as an NK cell charger, achieving a <40% recurrence rate in mouse tumor models.

Site-Specific Polyplex on CCR7 Down-Regulation and T Cell Elevation for Lymphatic Metastasis Blocking on Breast Cancer.

Tumor metastasis contributes to high cancer mortality. Tumor cells in lymph nodes (LNs) are difficult to eliminate but underlie uncontrollable systemic metastasis. The CC chemokine receptor 7 (CCR7) is overexpressed in tumor cells and interacts with CC chemokine ligand 21 (CCL21) secreted from LNs, potentiating their lymphatic migration. Here, a site-specific polyplex is developed to block the CCR7-CCL21 signal and kill tumor cells toward LNs, greatly limiting their lymphatic infiltration. A CCR7-targeting small interfering RNA (siCCR7) is condensed by mPEG-poly-(lysine) with chlorin e6 (Ce6) modification (PPLC) to form PPLC/siCCR7. The knockdown of CCR7 by siCCR7 in tumor cells significantly reduced their response on CCL21 and LN tropism. Additionally, photodynamic therapy-mediated immune activation precisely targets and kills tumor cells released from the primary foci before they reaches the LNs, reducing the number of tumor cells entering the LNs. Consequently, the PPLC/siCCR7 polyplexes inhibited up to 92% of lung metastasis in 4T1 tumor bearing mice and reduced tumor cell migration to LNs by up to 80%. This site-specific strategy optimized anti-metastasis efficacy and promotes the clinical translational development of anti-metastatic therapy.

AMG487 inhibits PRRSV replication and ameliorates lung injury in pig lung xenografts by down-regulating the expression of ANXA2.

Porcine reproductive and respiratory syndrome (PRRS) is a pig disease caused by the PRRS virus (PRRSV) that is characterized with diffuse interstitial pneumonia and lung edema. High expressions of chemokine CXCL10 and its receptor CXCR3 are reported in infected porcine lungs. Since CXCR3 is a key player in host inflammatory response, it might be a therapeutic target to treat lung damage caused by PRRSV infection. The size of pigs has long hampered research into molecular mechanisms of PRRS and validating the potential pharmaceutical targets. In this study, a porcine lung xenograft model with PRRSV infection was generated in immunodeficient mice to evaluate the therapeutic effects of the CXCR3 antagonist AMG487 on PRRSV infection-induced lung injury. The porcine lung tissues developed normally two weeks after xeno-transplantation in the mouse kidney capsule. Infection of PRRSV resulted in its efficient replication in the xenografts and histological damage to the porcine lung tissue structure, with no or little effects on mouse lungs. AMG487 administration dramatically reduced the number of PRRSV genome copies and significantly alleviated the porcine lung injury. Furthermore, treatment of AMG487 in cultured porcine macrophages consistently suppressed PRRSV replication with significant downregulation of Annexin A2 (ANXA2), a cellular protein facilitating viral replication. These findings provide a suitable model for evaluating new antiviral therapies as well as a possible therapeutic option for virus infection-induced lung injury.

MNK as a potential pharmacological target for suppressing LPS-induced acute lung injury in mice.

Acute lung injury (ALI) or its more severe form, known as acute respiratory distress syndrome (ARDS), is characterized by an initial exudative phase, expression of proinflammatory mediators, activation of inflammatory leukocytes, and impairment of the lung endothelium and epithelium. Despite numerous, novel therapeutic strategies have been developed regarding the pathophysiology of ALI, current treatment is mainly supportive, as specific therapies have not been established in the past few decades. The MAP kinase-interacting kinases (MNK1 and MNK2) are serine threonine kinases which are activated by mitogen-activated protein kinases (MAPKs), regulate protein synthesis by phosphroylating eukaryotic translation initiation factor 4E (eIF4E). Although studies have shown that MAPKs pathway is involved in anti-inflammatory and preventing tissue injury processes, the role of MNKs in ALI has, until now, remained relatively unexplored. Here, we investigated whether partial inhibition of MAPKs pathway by targeting MNKs was effective in the prevention and treatment of ALI. C57BL6 mice were pretreated with MNK1 and MNK2 inhibitor (CGP57380, 30 mg/kg) for 30 min and then challenged with 5 mg/kg LPS for 6 h. The results showed that pretreatment with CGP57380 not only significantly attenuated LPS-induced lung wet/dry ratio, as well as protein content, total cells and neutrophils in bronchoalveolar lavage fluid (BALF), but also decreased the production of pro-inflammatory mediators such as interleukin-6 (IL-6), tumor necrosis factor alpha (TNF-α) and keratinocyte-derived chemoattractant (KC). In addition, CGP57380 was observed to significantly suppress LPS-stimulated phosphorylation of eIF4E and MAPKs in the mouse bone marrow-derived macrophages (BMDMs). The involvement of MNK2 in lung injury was further evident by MNK2 knockout mice. MNK2 deficiency resulted in the attenuated lung histopathological changes, as also reflected by reductions in neutrophil counts, and the less LPS-induced the production of IL-6, TNF-α and KC in mouse BALF. Taken together, these findings demonstrated for the first time that MNK inhibition could effectively reduce the LPS-induced ALI in mice, suggesting a novel and potential application for MNK-based therapy to treat this serious disease.

International guidelines for the flow cytometric evaluation of peripheral blood for suspected Sézary syndrome or mycosis fungoides: Assay development/optimization, validation, and ongoing quality monitors.

Introducing a sensitive and specific peripheral blood flow cytometric assay for Sézary syndrome and mycosis fungoides (SS/MF) requires careful selection of assay design characteristics, and translation into a laboratory developed assay through development/optimization, validation, and continual quality monitoring. As outlined in a previous article in this series, the recommended design characteristics of this assay include at a minimum, evaluation of CD7, CD3, CD4, CD8, CD26, and CD45, analyzed simultaneously, requiring at least a 6 color flow cytometry system, with both quantitative and qualitative components. This article provides guidance from an international group of cytometry specialists in implementing an assay to those design specifications, outlining specific considerations, and best practices. Key points presented in detail are: (a) Pre-analytic components (reagents, specimen processing, and acquisition) must be optimized to: (i) identify and characterize an abnormal population of T-cells (qualitative component) and (ii) quantitate the abnormal population (semi/quasi-quantitative component). (b)Analytic components (instrument set-up/acquisition/analysis strategy and interpretation) must be optimized for the identification of SS/MF populations, which can vary widely in phenotype. Comparison with expert laboratories is strongly encouraged in order to establish competency. (c) Assay performance must be validated and documented through a validation plan and report, which covers both qualitative and semi/quasi-quantitative assay components (example template provided). (d) Ongoing assay-specific quality monitoring should be performed to ensure consistency.

The tissue specific regulation of miR22 expression in the lung and brain by ribosomal protein L29.

Endogenous miR22 is associated with a diverse range of biological processes through post-translational modification of gene expression and its deregulation results in various diseases including cancer. Its expression is usually tissue or cell-specific, however, the reasons behind this tissue or cell specificity are not clearly outlined till-date. Therefore, our keen interest was to investigate the mechanisms of tissue or cell-specific expression of miR22. In the current study, miR22 expression showed a tissues-specific difference in the poly(I:C) induced inflammatory mouse lung and brain tissues. The cell-specific different expression of miR22 was also observed in inflammatory glial cells and endothelial cells. The pattern of RPL29 expression was also similar to miR22 in these tissues and cells under the same treatment. Interestingly, the knockdown of RPL29 exerted an inhibitory effect on miR22 and its known transcription factors including Fos-B and c-Fos. Fos-B and c-Fos were also differentially expressed in the two cell lines transfected with poly(I:C). The knockdown of c-Fos also exerted its negative effects on miR22 expression in both cells. These findings suggest that RPL29 might have regulatory roles on tissue or cell-specific expression of miR22 through the transcription activities of c-Fos and also possibly through Fos-B.

FTO promotes SREBP1c maturation and enhances CIDEC transcription during lipid accumulation in HepG2 cells.

The fat mass and obesity-associated (FTO) gene is tightly related to body weight and fat mass, and plays a pivotal role in regulating lipid accumulation in hepatocytes. However, the mechanisms underlying its function are poorly understood. Sterol regulatory element binding protein-1c (SREBP1c) is a transcription factor that regulates lipogenesis. Cell death-inducing DFFA (DNA fragmentation factor-α)-like effector c (CIDEC) plays a crucial role in lipid droplets (LDs) size controlling and lipid accumulation. In this report, we first observed that FTO overexpression in HepG2 cells resulted in an increase of lipogenesis and up-regulation of SREBP1c and CIDEC, two key regulatory factors in lipogenesis. In contrast, FTO knockdown in HepG2 cells resulted in a decrease of lipogenesis and down-regulation of SREBP1c and CIDEC expression. Moreover, SREBP1c knockdown resulted in a decrease of lipogenesis in HepG2 cells with FTO overexpression. In addition, FTO demethylation defect mutant presented less transcription of the key genes, and less nuclear translocation and maturation of SREBP1c. Further investigation demonstrated that overexpression of SREBP1c in HepG2 cells also promoted high CIDEC expression. Luciferase reporter assays showed that SREBP1c significantly stimulated CIDEC gene promoter activity. Finally, CIDEC knockdown reduced SREBP1c-induced lipogenesis. In conclusion, our studies suggest that FTO increased the lipid accumulation in hepatocytes by increasing nuclear translocation of SREBP1c and SREBP1c maturation, thus improving the transcriptional activity of LD-associated protein CIDEC. Our studies may provide new mechanistic insight into nonalcoholic fatty liver disease (NAFLD) mediated by FTO.

AMPK promotes the survival of colorectal cancer stem cells.

BACKGROUND: Colorectal cancer (CRC) is the third most commonly diagnosed cancer in males and the second in females worldwide in 2012. In the past 20 years, strong evidence suggests that cancer stem cells are the main culprit of cancer metastasis, chemotherapy resistance, and relapse. METHODS: To further understand the unique biological properties of cancer stem cells and uncover novel molecular targets to eradicate them, we first established a panel of patient-derived xenograft (PDX) tumor models using tumors surgically removed from human colorectal cancer patients. We then isolated CRC cancer stem cells based on their ALDH activity using fluorescent-activated cell sorting (FACS) and characterized their metabolic properties. RESULTS: Interestingly, we found that the CRC cancer stem cells (ie, CRC cells with higher ALDH activity, or ALDH+) express higher level of antioxidant genes and have lower level of reactive oxygen species (ROS) than non-CRC cancer stem cells (ie, CRC cells with lower ALDH activity, or ALDH-). The CRC cancer stem cells also possess more mitochondria mass and show higher mitochondrial activity. More intriguingly, we observed higher AMP-activated protein kinase (AMPK) activities in these CRC cancer stem cells. Inhibition of the AMPK activity using 2 AMPK inhibitors, Compound C and Iodotubercidin, preferentially induces cell death in CRC cancer stem cells. CONCLUSION: We propose that AMPK inhibitors may help to eradicate the CRC cancer stem cells and prevent the relapse of CRCs.

Testosterone regulates 3T3-L1 pre-adipocyte differentiation and epididymal fat accumulation in mice through modulating macrophage polarization.

Low testosterone levels are strongly related to obesity in males. The balance between the classically M1 and alternatively M2 polarized macrophages also plays a critical role in obesity. It is not clear whether testosterone regulates macrophage polarization and then affects adipocyte differentiation. In this report, we demonstrate that testosterone strengthens interleukin (IL) -4-induced M2 polarization and inhibits lipopolysaccharide (LPS)-induced M1 polarization, but has no direct effect on adipocyte differentiation. Cellular signaling studies indicate that testosterone regulates macrophage polarization through the inhibitory regulative G-protein (Gαi) mainly, rather than via androgen receptors, and phosphorylation of Akt. Moreover, testosterone inhibits pre-adipocyte differentiation induced by M1 macrophage medium. Lowering of serum testosterone in mice by injecting a luteinizing hormone receptor (LHR) peptide increases epididymal white adipose tissue. Testosterone supplementation reverses this effect. Therefore, our findings indicate that testosterone inhibits pre-adipocyte differentiation by switching macrophages to M2 polarization through the Gαi and Akt signaling pathways.

MicroRNA-486 as a Biomarker for Early Diagnosis and Recurrence of Non-Small Cell Lung Cancer.

BACKGROUND: Non-small cell lung cancer (NSCLC) is a leading cause of cancer death worldwide. Early diagnosis is essential for improvements of prognosis and survival of the patients. Currently, there is no effective biomarker available in clinical settings for early detection of lung cancer. Altered expressions in many cancer types including NSCLC and stable existence in plasma make microRNAs (miRNAs) a group of potentially useful biomarkers for clinical assessments of patients with NSCLC. OBJECTIVES: To evaluate the potential values of miRNAs as blood-based biomarkers for early diagnosis and prognosis in NSCLC patients. METHODS: Peripheral blood samples from healthy volunteers and early-staged NSCLC patients before and after surgery were collected, and plasma was separated. Expression of ten miRNAs in the plasma and tumor sections of the patients was detected by quantitative real-time polymerase chain reaction. RESULTS: MiRNA (miR)-486 and miR-150 were found to significantly distinguish lung cancer patients from healthy volunteers. Area under curve of miR-486 and miR-150 were 0.926 (sensitivity, 0.909; specificity, 0.818) and 0.752 (sensitivity, 0.818; specificity, 0.818), respectively. In response to therapy, patients with down-regulated miR-486 expression showed prolonged recurrence-free survival than those with un-reduced miR-486 expression (median, unreached vs. 19 months; hazard ratio, 0.1053; 95% confidence interval, 0.01045 to 1.060; P=0.056). CONCLUSIONS: The results suggest that miR-486 and miR-150 could be potential blood-based biomarkers for early diagnosis of NSCLC. Monitoring change of miR-486 expression in plasma might be an effective and non-invasive method for recurrence prediction of early-staged NSCLC patients.

Analytical Performance of a 15-Gene Prognostic Assay for Early-Stage Non-Small-Cell Lung Carcinoma Using RNA-Stabilized Tissue.

A 15-gene prognostic signature for early-stage, completely resected, non-small-cell lung carcinoma, (which distinguishes between patients with good and poor prognoses) was clinically validated in prior studies. To achieve operational efficiencies, this study was designed to evaluate the assay's performance in RNA-stabilized tissue as an alternative to the fresh-frozen tissue format originally used to develop the assay. The percent concordance between matched tissue formats was 84% (95% Wilson CI, 70%-92%), a level of agreement comparable to the inherent reproducibility of the assay observed within biological replicates of fresh-frozen tissue. Furthermore, the analytical performance of the assay using the RNA-stabilized tissue format was evaluated. When compared to an accredited reference laboratory, the clinical laboratory achieved a concordance of 94% (95% Wilson CI, 81%-98%), and there was no evidence of bias between the laboratories. The lower limit of quantitation for the target RNA concentration was confirmed to be, at most, 12.5 ng/µL. The assay reportable range defined in terms of risk score units was determined to be -4.295 to 4.210. In a large-scale precision study, the assay showed high reproducibility and repeatability. When subjected to a maximal amount of genomic DNA, a potential contaminant, the assay still produced the expected results. The 15-gene signature was confirmed to produce reliable results and, thus, is suitable for its intended use.

Analytical performance of a formalin-fixed paraffin-embedded tissue-based 634-probe prognostic assay for predicting outcome of patients with stage II colon cancer.

A formalin-fixed paraffin-embedded tissue-based prognostic assay to assess the risk for recurrence in stage II colon cancer has recently been clinically validated. This study describes the analytical performance and quality control measures of the assay. The reportable range was determined to be [-1.129, 1.414] in risk score units. The accuracy was evaluated with a split sample comparison within the production lab and between the production lab and a reference lab. The concordance between the replicates within the production lab was 79% (95% confidence interval, 64%-91%). There was no evidence of bias, and the concordance was 78% (95% confidence interval, 61%-90%) between the labs. The lab-to-lab concordance was further evaluated by simulating risk scores from the full reportable range. The simulation suggested a higher concordance. The sensitivity study demonstrated that the percentage of tumor tissue did not impact the risk score and that RNA concentration of 9.5 ng/µL was a conservative determination of the analyte lower limit of quantification. From the precision study, the repeatability and reproducibility estimates were 0.1267 and 0.0548 in risk score units, respectively. Furthermore, multifaceted quality control measures were implemented, such as proper tissue processing steps, high-risk and low-risk controls, nontemplate control, and a gene expression-based classifier to evaluate the cDNA amplification kit, a key reagent in the assay. In conclusion, this study demonstrates the strong analytical performance of the assay and further supports its use as an objective standardized prognostic test for stage II colon cancer.

Comparing statistical methods for quantifying drug sensitivity based on in vitro dose-response assays.

In vitro chemosensitivity assays are invaluable for assessing chemotherapeutic agents' effects on cancer cells. Yet the dose-response curves generated by those assays, usually approximated by four-parameter logistic (4PL) models, are oftentimes difficult to interpret, with no clear indication of which metric should be used to compare them. Here, five commonly used metrics, absolute and relative half-maximal inhibitory concentration (IC(50)), area under the dose-response curve (AUC) based on trapezoidal rule and a parametric approach, and the effect at the maximal concentrations (E(max)), were compared in both simulations and real-life scenarios to evaluate their use with 4PL curves. Despite the fact that IC(50) is the most widely used metric to analyze dose-response curves, this study demonstrated that it was not the most reliable of the metrics tested. Fitted AUC showed the best overall performance in both the simulation and real-life scenarios; trapezoidal AUC showed similar performance to fitted AUC in most cases.

Delineation of a cellular hierarchy in lung cancer reveals an oncofetal antigen expressed on tumor-initiating cells.

Poorly differentiated tumors in non-small cell lung cancer (NSCLC) have been associated with shorter patient survival and shorter time to recurrence following treatment. Here, we integrate multiple experimental models with clinicopathologic analysis of patient tumors to delineate a cellular hierarchy in NSCLC. We show that the oncofetal protein 5T4 is expressed on tumor-initiating cells and associated with worse clinical outcome in NSCLC. Coexpression of 5T4 and factors involved in the epithelial-to-mesenchymal transition were observed in undifferentiated but not in differentiated tumor cells. Despite heterogeneous expression of 5T4 in NSCLC patient-derived xenografts, treatment with an anti-5T4 antibody-drug conjugate resulted in complete and sustained tumor regression. Thus, the aggressive growth of heterogeneous solid tumors can be blocked by therapeutic agents that target a subpopulation of cells near the top of the cellular hierarchy.

Identification of a gene signature in cell cycle pathway for breast cancer prognosis using gene expression profiling data.

BACKGROUND: Numerous studies have used microarrays to identify gene signatures for predicting cancer patient clinical outcome and responses to chemotherapy. However, the potential impact of gene expression profiling in cancer diagnosis, prognosis and development of personalized treatment may not be fully exploited due to the lack of consensus gene signatures and poor understanding of the underlying molecular mechanisms. METHODS: We developed a novel approach to derive gene signatures for breast cancer prognosis in the context of known biological pathways. Using unsupervised methods, cancer patients were separated into distinct groups based on gene expression patterns in one of the following pathways: apoptosis, cell cycle, angiogenesis, metastasis, p53, DNA repair, and several receptor-mediated signaling pathways including chemokines, EGF, FGF, HIF, MAP kinase, JAK and NF-kappaB. The survival probabilities were then compared between the patient groups to determine if differential gene expression in a specific pathway is correlated with differential survival. RESULTS: Our results revealed expression of cell cycle genes is strongly predictive of breast cancer outcomes. We further confirmed this observation by building a cell cycle gene signature model using supervised methods. Validated in multiple independent datasets, the cell cycle gene signature is a more accurate predictor for breast cancer clinical outcome than the previously identified Amsterdam 70-gene signature that has been developed into a FDA approved clinical test MammaPrint. CONCLUSION: Taken together, the gene expression signature model we developed from well defined pathways is not only a consistently powerful prognosticator but also mechanistically linked to cancer biology. Our approach provides an alternative to the current methodology of identifying gene expression markers for cancer prognosis and drug responses using the whole genome gene expression data.

High-content imaging characterization of cell cycle therapeutics through in vitro and in vivo subpopulation analysis.

Although the cycling of eukaryotic cells has long been a primary focus for cancer therapeutics, recent advances in imaging and data analysis allow even further definition of cellular events as they occur in individual cells and cellular subpopulations in response to treatment. High-content imaging (HCI) has been an effective tool to elucidate cellular responses to a variety of agents; however, these data were most frequently observed as averages of the entire captured population, unnecessarily decreasing the resolution of each assay. Here, we dissect the eukaryotic cell cycle into individual cellular subpopulations using HCI in conjunction with unsupervised K-means clustering. We generate distinct phenotypic fingerprints for each major cell cycle and mitotic compartment and use those fingerprints to screen a library of 310 commercially available chemotherapeutic agents. We determine that the cell cycle arrest phenotypes caused by these agents are similar to, although distinct from, those found in untreated cells and that these distinctions frequently suggest the mechanism of action. We then show via subpopulation analysis that these arrest phenotypes are similar in both mouse models and in culture. HCI analysis of cell cycle using data obtained from individual cells under a broad range of research conditions and grouped into cellular subpopulations represents a powerful method to discern both cellular events and treatment effects. In particular, this technique allows for a more accurate means of assessing compound selectivity and leads to more meaningful comparisons between so-called targeted therapeutics.

Modification of Kolmogorov-Smirnov test for DNA content data analysis through distribution alignment.

The Kolmogorov-Smirnov (K-S) test is a statistical method often used for comparing two distributions. In high-throughput screening (HTS) studies, such distributions usually arise from the phenotype of independent cell populations. However, the K-S test has been criticized for being overly sensitive in applications, and it often detects a statistically significant difference that is not biologically meaningful. One major reason is that there is a common phenomenon in HTS studies that systematic drifting exists among the distributions due to reasons such as instrument variation, plate edge effect, accidental difference in sample handling, etc. In particular, in high-content cellular imaging experiments, the location shift could be dramatic since some compounds themselves are fluorescent. This oversensitivity of the K-S test is particularly overpowered in cellular assays where the sample sizes are very big (usually several thousands). In this paper, a modified K-S test is proposed to deal with the nonspecific location-shift problem in HTS studies. Specifically, we propose that the distributions are "normalized" by density curve alignment before the K-S test is conducted. In applications to simulation data and real experimental data, the results show that the proposed method has improved specificity.

Analysis of pathway activity in primary tumors and NCI60 cell lines using gene expression profiling data.

To determine cancer pathway activities in nine types of primary tumors and NCI60 cell lines, we applied an in silica approach by examining gene signatures reflective of consequent pathway activation using gene expression data. Supervised learning approaches predicted that the Ras pathway is active in approximately 70% of lung adenocarcinomas but inactive in most squamous cell carcinomas, pulmonary carcinoids, and small cell lung carcinomas. In contrast, the TGF-beta, TNF-alpha, Src, Myc, E2F3, and beta-catenin pathways are inactive in lung adenocarcinomas. We predicted an active Ras, Myc, Src, and/or E2F3 pathway in significant percentages of breast cancer, colorectal carcinoma, and gliomas. Our results also suggest that Ras may be the most prevailing oncogenic pathway. Additionally, many NCI60 cell lines exhibited a gene signature indicative of an active Ras, Myc, and/or Src, but not E2F3, beta-catenin, TNF-alpha, or TGF-beta pathway. To our knowledge, this is the first comprehensive survey of cancer pathway activities in nine major tumor types and the most widely used NCI60 cell lines. The "gene expression pathway signatures" we have defined could facilitate the understanding of molecular mechanisms in cancer development and provide guidance to the selection of appropriate cell lines for cancer research and pharmaceutical compound screening.

Comparative analysis and integrative classification of NCI60 cell lines and primary tumors using gene expression profiling data.

BACKGROUND: NCI60 cell lines are derived from cancers of 9 tissue origins and have been invaluable in vitro models for cancer research and anti-cancer drug screen. Although extensive studies have been carried out to assess the molecular features of NCI60 cell lines related to cancer and their sensitivities to more than 100,000 chemical compounds, it remains unclear if and how well these cell lines represent or model their tumor tissues of origin. Identification and confirmation of correct origins of NCI60 cell lines are critical to their usage as model systems and to translate in vitro studies into clinical potentials. Here we report a direct comparison between NCI60 cell lines and primary tumors by analyzing global gene expression profiles. RESULTS: Comparative analysis suggested that 51 of 59 cell lines we analyzed represent their presumed tumors of origin. Taking advantage of available clinical information of primary tumor samples used to generate gene expression profiling data, we further classified those cell lines with the correct origins into different subtypes of cancer or different stages in cancer development. For example, 6 of 7 non-small cell lung cancer cell lines were classified as lung adenocarcinomas and all of them were classified into late stages in tumor progression. CONCLUSION: Taken together, we developed and applied a novel approach for systematic comparative analysis and integrative classification of NCI60 cell lines and primary tumors. Our results could provide guidance to the selection of appropriate cell lines for cancer research and pharmaceutical compound screenings. Moreover, this gene expression profile based approach can be generally applied to evaluate experimental model systems such as cell lines and animal models for human diseases.