Diagnostic value of combining tumor and inflammatory biomarkers in detecting common cancers in Korea.

BACKGROUND: The ultimate goal of cancer screening is to diagnose invasive cancers early, while they are still curable. We aimed to validate the diagnostic value of blood-derived protein biomarkers that we developed for six common cancer in Korea. METHODS: We have discovered 12 protein biomarkers that are useful in differentiating cancer patients from healthy controls using two-dimensional gel electrophoresis (2-DE), surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS), and literature review. Cancer patients (stomach, colon, liver, lung, breast, and prostate) and control subjects were collected and tested data sets were used to generate predictive models that identify risk scores for each cancer. The validation study was done in serum samples of an independent patient cohort Receiver operating characteristic (ROC) analyses were conducted to evaluate the diagnostic performance of the biomarkercombinations. RESULTS: The AUCs of the model in the test set were 0.971, 0.960, 0.969, 0.942, 0.834, and 0.985 for stomach, colon, liver, lung, breast, and prostate cancer, respectively. CONCLUSIONS: Combining multiple tumor and systemic inflammatory biomarkers proved to be a valid strategy in the diagnosis of six common cancers in Korea. Further validation of appropriate screening populations through large-scale clinical trials are warranted.

Biomarker Panel for the Diagnosis of Pancreatic Ductal Adenocarcinoma.

A single tumor marker has a low diagnostic value in pancreatic cancer. Combinations of multiple biomarkers and unique analysis algorithms can be applied to overcome these limitations. This study sought to develop diagnostic algorithms using multiple biomarker panels and to validate their performance in the diagnosis of pancreatic ductal adenocarcinoma (PDAC). We used blood samples from 180 PDAC patients and 573 healthy controls. Candidate markers consisted of 11 markers that are commonly expressed in various cancers and which have previously demonstrated increased expression in pancreatic cancer. Samples were divided into training and validation sets. Five linear or non-linear classification methods were used to determine the optimal model. Differences were identified in 10 out of the 11 markers tested. We identified 2047 combinations, all of which were applied to 5 separate algorithms. The new biomarker combination consisted of 6 markers (ApoA1, CA125, CA19-9, CEA, ApoA2, and TTR). The area under the curve, specificity, and sensitivity were 0.992, 95%, and 96%, respectively, in the training set. Meanwhile, the measures were 0.993, 96%, and 93% in the validation set. This study demonstrated the utility of multiple biomarker combinations in the early detection of PDAC. A diagnostic panel of 6 biomarkers was developed and validated. These algorithms will assist in the early diagnosis of PDAC.

3-Dimensional micropillar drug screening identifies FGFR2-IIIC overexpression as a potential target in metastatic giant cell tumor.

We established two patient derived tumor cells (PDCs) from right and left pulmonary metastatic lesions respectively of a patient with giant cell tumor. At that time, patient-derived tumor cells from right and left surgical specimens were collected and cultured. High-throughput screening (HTS) for 24 drugs was conducted with a micropillar/microwell chip platform using giant cell tumor PDCs. Using 6 doses per drug in 6 replicates for giant cell tumor PDCs, the dose response curves and corresponding IC50 values were calculated from the scanned images using the S+ Chip Analyzer. A sensitive response was more significantly achieved for AZD4547 (FGFR2 inhibitor) in giant cell tumor PDCs originated from the right pulmonary nodule under the micropillar/microwell chip platform using 3D culture. This sensitivity was consistent with the target expression patterns of giant cell tumor PDCs (FGFR2-IIIC mRNA expression in giant cell tumor PDCs originated from the right pulmonary nodule was increased significantly as compared to those originated from left). However, in a conventional 2D cultured MTT assay, there was no difference for IC50 values of AZD4547 between giant cell tumor PDCs originated from right and left pulmonary nodules. An HTS platform based on 3D culture on micropillar/microwell chips and PDC models could be applied as a useful preclinical tool to evaluate the intrapatient tumor/response heterogeneity. This platform based on 3D culture might reflect far better the relation between the tumor-biology and the matched targeted agent as compared to a conventional 2D cultured MTT assay.

Diagnostic Value of Combining Tumor and Inflammatory Markers in Lung Cancer.

BACKGROUND: Despite major advances in lung cancer treatment, early detection remains the most promising way of improving outcomes. To detect lung cancer in earlier stages, many serum biomarkers have been tested. Unfortunately, no single biomarker can reliably detect lung cancer. We combined a set of 2 tumor markers and 4 inflammatory or metabolic markers and tried to validate the diagnostic performance in lung cancer. METHODS: We collected serum samples from 355 lung cancer patients and 590 control subjects and divided them into training and validation datasets. After measuring serum levels of 6 biomarkers (human epididymis secretory protein 4 [HE4], carcinoembryonic antigen [CEA], regulated on activation, normal T cell expressed and secreted [RANTES], apolipoprotein A2 [ApoA2], transthyretin [TTR], and secretory vascular cell adhesion molecule-1 [sVCAM-1]), we tested various sets of biomarkers for their diagnostic performance in lung cancer. RESULTS: In a training dataset, the area under the curve (AUC) values were 0.821 for HE4, 0.753 for CEA, 0.858 for RANTES, 0.867 for ApoA2, 0.830 for TTR, and 0.552 for sVCAM-1. A model using all 6 biomarkers and age yielded an AUC value of 0.986 and sensitivity of 93.2% (cutoff at specificity 94%). Applying this model to the validation dataset showed similar results. The AUC value of the model was 0.988, with sensitivity of 93.33% and specificity of 92.00% at the same cutoff point used in the validation dataset. Analyses by stages and histologic subtypes all yielded similar results. CONCLUSIONS: Combining multiple tumor and systemic inflammatory markers proved to be a valid strategy in the diagnosis of lung cancer.

Erratum: Diagnostic Value of Combining Tumor and Inflammatory Markers in Lung Cancer.

[This corrects the article on p. 187 in vol. 21, PMID: 27722145.].

Crosstalk with cancer-associated fibroblasts induces resistance of non-small cell lung cancer cells to epidermal growth factor receptor tyrosine kinase inhibition.

Although lung cancers with activating mutations in the epidermal growth factor receptor (EGFR) are highly sensitive to selective EGFR tyrosine kinase inhibitors (TKIs), these tumors invariably develop acquired drug resistance. Host stromal cells have been found to have a considerable effect on the sensitivity of cancer cells to EGFR TKIs. Little is known, however, about the signaling mechanisms through which stromal cells contribute to the response to EGFR TKI in non-small cell lung cancer. This work examined the role of hedgehog signaling in cancer-associated fibroblast (CAF)-mediated resistance of lung cancer cells to the EGFR TKI erlotinib. PC9 cells, non-small cell lung cancer cells with EGFR-activating mutations, became resistant to the EGFR TKI erlotinib when cocultured in vitro with CAFs. Polymerase chain reaction and immunocytochemical assays showed that CAFs induced epithelial to mesenchymal transition phenotype in PC9 cells, with an associated change in the expression of epithelial to mesenchymal transition marker proteins including vimentin. Importantly, CAFs induce upregulation of the 7-transmembrane protein smoothened, the central signal transducer of hedgehog, suggesting that the hedgehog signaling pathway is active in CAF-mediated drug resistance. Indeed, downregulation of smoothened activity with the smoothened antagonist cyclopamine induces remodeling of the actin cytoskeleton independently of Gli-mediated transcriptional activity in PC9 cells. These findings indicate that crosstalk with CAFs plays a critical role in resistance of lung cancer to EGFR TKIs through induction of the epithelial to mesenchymal transition and may be an ideal therapeutic target in lung cancer.

Establishment and characterization of a lung cancer cell line, SMC-L001, from a lung adenocarcinoma.

Lung cancer cell lines are a valuable tool for elucidating lung tumorigenesis and developing novel therapies. However, the majority of cell lines currently available were established from tumors in patients of Caucasian origin, limiting our ability to investigate how cancers in patients of different ethnicities differ from one another in terms of tumor biology and drug responses. In this study, we established a human non-small cell lung carcinoma cell line, SMC-L001, and characterized its genome and tumorigenic potential. SMC-L001 cells were isolated from a Korean lung adenocarcinoma patient (male, pStage IIb) and were propagated in culture. SMC-L001 cells were adherent. DNA fingerprinting analysis indicated that the SMC-L001 cell line originated from parental tumor tissue. Comparison of the genomic profile of the SMC-L001 cell line and the original tumor revealed an identical profile with 739 mutations in 46 cancer-related genes, including mutations in TP53 and KRAS. Furthermore, SMC-L001 cells were highly tumorigenic, as evidenced by the induction of solid tumors in immunodeficient mice. In summary, we established a new lung cancer cell line with point mutations in TP53 and KRAS from a Korean lung adenocarcinoma patient that will be useful for investigating ethnic differences in lung cancer biology and drug response.

Tumor-stromal interactions with direct cell contacts enhance motility of non-small cell lung cancer cells through the hedgehog signaling pathway.

The metastatic potential of non-small cell lung cancer (NSCLC) has been shown to be associated with interactions with the tumor microenvironment, which primarily comprises of cancer-associated fibroblasts (CAFs). Heterotypic cell-cell interactions occur via released signaling molecules and direct physical contact. To investigate the differential contribution of direct cell-cell contact and paracrine signaling factors to NSCLC metastasis, we performed two types of co-cultures: direct co-cultures of the NSCLC cell line H358 with primary cultures of CAFs from patients with resected NSCLC; and indirect co-cultures across a separable membrane. We showed that CAFs more potently induce epithelial-to-mesenchymal transition (EMT) in NSCLC H358 cells through direct contacts than through indirect interactions, as indicated by an elongated and disseminated appearance. Immunocytochemical experiments show that EMT accompanies the expression of mesenchymal cytoskeletal proteins, including vimentin. However, H358 cells proliferate more slowly in direct co-culture than in indirect co-culture. Real-time reverse transcription-polymerase chain reaction (RT-PCR) revealed that H358 cells in direct contact with CAFs up-regulate the expression of the pan-mesenchymal markers α-smooth muscle actin (α-SMA), fibroblast activation protein (FAP), transforming growth factor-ß (TGFß) signaling effector SMAD family number-3 (SMAD3), and hedgehog signaling effector GLI family zinc finger-1 (GLI1), compared with the indirect co-culture system. Furthermore, we found that the direct GLI1 transcription targets snail family zinc finger-1 (SNAI1) and SNAI2 are up-regulated, suggesting that the hedgehog signaling pathway is active in direct co-culture. A scratch wound assay showed that direct contact co-culture increases the motility of H358 cells. In conclusion, these findings provide evidence that paracrine factors and direct physical contact between NSCLC cells and CAFs might control the metastatic potential of NSCLC through the hedgehog signaling pathway.

Serum des-R prothrombin activation peptide fragment 2: a novel prognostic marker for disseminated intravascular coagulation.

INTRODUCTION: Disseminated intravascular coagulation (DIC) is diagnosed based on the combination of predisposing underlying conditions and laboratory tests for plasma coagulation markers. Because the collection of blood plasma samples is a fastidious procedure, the serum sample method may be preferred for measurement of coagulation markers when feasible. MATERIALS AND METHODS: The novel serum marker des-R prothrombin activation peptide fragment 2 (des-R F2) was measured using a sandwich enzyme-linked immunosorbent assay in 181 patients suspected of having DIC. Thrombin generation potential was estimated with a calibrated automated thrombogram. RESULTS: Serum des-R F2 was generated with an in vitro clotting process within a serum separation tube after blood collection. Carboxypeptidase inhibitor inhibited the formation of des-R F2 during in vitro clotting. Low levels of prothrombin and thrombin generation potential resulted in low serum des-R F2 levels. Serum des-R F2 was significantly decreased in overt DIC. Levels of des-R F2 correlated with DIC severity and other coagulation markers. Of note, the decrease in serum des-R F2 levels was a significant marker for predicting mortality. CONCLUSIONS: The serum marker, des-R F2, can be used for the investigation of DIC severity and prognosis. It should be considered a useful marker, especially when only serum samples are available.

Human lung cancer-associated fibroblasts enhance motility of non-small cell lung cancer cells in co-culture.

The metastatic potential of non-small cell lung cancer (NSCLC) cells has been shown to be associated with the tumor microenvironment. Cancer-associated fibroblasts (CAFs) are a major component of the tumor microenvironment, regulating tumor cell function by secreting growth factors, chemokines, and extracellular matrix (ECM). In this study, we examined the role of CAFs in the tumor progression of NSCLC. Firstly, we established primary cultures of CAFs and matched normal fibroblasts (NFs) from patients with resected NSCLC. CAFs exhibited greater expression of the pan-mesenchymal marker α-smooth muscle actin (α-SMA) than did NFs, although they displayed similar morphology. Furthermore, we employed a direct co-culture assay with human NSCLC A549 and H358 cells, and found that CAFs were more potent in inducing the epithelial-to-mesenchymal transition (EMT) phenotype than NFs, as indicated by an elongated and disseminated appearance. CAF-induced EMT led to an increase in motility and a decrease in proliferation of NSCLC cells through SMAD family number-3 (SMAD3)-dependent up-regulation of the growth inhibitory gene p21(CIP1) [cyclin-dependent kinase inhibitor-1A (CDKN1A)] and α-SMA. Taken together, these findings provide evidence that lung CAFs have tumor-promoting capacity distinct from NFs and might play a significant role in the metastatic potential of NSCLC.

A novel detection method of non-small cell lung cancer using multiplexed bead-based serum biomarker profiling.

OBJECTIVES: Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related mortality. Development of an early diagnosis method may improve survivals. We aimed to develop a new diagnostic model for NSCLC using serum biomarkers. METHODS: We set up a patient group diagnosed with NSCLC (n = 122) and a healthy control group (n = 225). Thirty serum analytes were selected on the basis of previous studies and a literature search. An antibody-bead array of 30 markers was constructed using the Luminex bead array platform (Luminex Inc, Austin, Tex) and was analyzed. Each marker was ranked by importance using the random forest method and then selected. Using selected markers, multivariate classification algorithms were constructed and were validated by application to independent validation cohort of 21 NSCLC and 28 control subjects. RESULTS: There was no difference in demographics between patients and the control population except for age (64.8 ± 10.0 for patients vs 53.0 ± 7.6 years for the control group). Among the 30 serum proteins, 23 showed a difference between the 2 groups (12 increased and 11 decreased in the patient group). We found the highest accuracy of multivariate classification algorithms when using the 5 highest-ranked biomarkers (A1AT, CYFRA 21-1, IGF-1, RANTES, AFP). When we applied the algorithms on a validation cohort, each method recognized the patients from the controls with high accuracy (89.8% with random forest, 91.8% with support vector machine, 88.2% with linear discriminant analysis, and 90.5% with logistic regression). CONCLUSIONS: We confirmed that a new diagnostic method using 5 serum biomarkers profiling constructed by multivariate classification algorithms could distinguish NSCLC from healthy controls with high accuracy.

The multiplex bead array approach to identifying serum biomarkers associated with breast cancer.

INTRODUCTION: Breast cancer is the most common type of cancer seen in women in western countries. Thus, diagnostic modalities sensitive to early-stage breast cancer are needed. Antibody-based array platforms of a data-driven type, which are expected to facilitate more rapid and sensitive detection of novel biomarkers, have emerged as a direct, rapid means for profiling cancer-specific signatures using small samples. In line with this concept, our group constructed an antibody bead array panel for 35 analytes that were selected during the discovery step. This study was aimed at testing the performance of this 35-plex array panel in profiling signatures specific for primary non-metastatic breast cancer and validating its diagnostic utility in this independent population. METHODS: Thirty-five analytes were selected from more than 50 markers through screening steps using a serum bank consisting of 4,500 samples from various types of cancer. An antibody-bead array of 35 markers was constructed using the Luminex bead array platform. A study population consisting of 98 breast cancer patients and 96 normal subjects was analysed using this panel. Multivariate classification algorithms were used to find discriminating biomarkers and validated with another independent population of 90 breast cancer and 79 healthy controls. RESULTS: Serum concentrations of epidermal growth factor, soluble CD40-ligand and proapolipoprotein A1 were increased in breast cancer patients. High-molecular-weight-kininogen, apolipoprotein A1, soluble vascular cell adhesion molecule-1, plasminogen activator inhibitor-1, vitamin-D binding protein and vitronectin were decreased in the cancer group. Multivariate classification algorithms distinguished breast cancer patients from the normal population with high accuracy (91.8% with random forest, 91.5% with support vector machine, 87.6% with linear discriminant analysis). Combinatorial markers also detected breast cancer at an early stage with greater sensitivity. CONCLUSIONS: The current study demonstrated the usefulness of the antibody-bead array approach in finding signatures specific for primary non-metastatic breast cancer and illustrated the potential for early, high sensitivity detection of breast cancer. Further validation is required before array-based technology is used routinely for early detection of breast cancer.