Urinary protein biomarkers in the early detection of lung cancer.

The early detection of lung cancer has the potential to greatly impact disease burden through the timely identification and treatment of affected individuals at a manageable stage of development. The insufficient specificity demonstrated by currently used screening and diagnostic techniques has led to intense investigation into biomarkers as diagnostic tools. Urine may represent a noninvasive alternative matrix for diagnostic biomarker development. We performed an analysis of 242 biomarkers in urines obtained from 83 patients with non-small cell lung carcinomas (NSCLC), 74 patients diagnosed with benign pulmonary conditions, and 77 healthy donors. A large number of significant alterations were observed between the NSCLC and control groups. A multivariate analysis identified a three-biomarker panel consisting of IGFBP-1, sIL-1Ra, CEACAM-1, which discriminated NSCLC from healthy controls with a sensitivity/specificity of 84/95 in an initial training set and 72/100 in an independent validation set. This panel performed well among multiple subtypes of NSCLC and early-stage disease but demonstrated only limited efficacy for the discrimination of NSCLC from benign controls and limited specificity for patients with several other cancers and tuberculosis. These findings demonstrate that urine biomarkers may provide screening and diagnostic properties which exceed those reported for serum biomarkers and approach a level necessary for further clinical development.

An extensive targeted proteomic analysis of disease-related protein biomarkers in urine from healthy donors.

The analysis of protein biomarkers in urine is expected to lead to advances in a variety of clinical settings. Several characteristics of urine including a low-protein matrix, ease of testing and a demonstrated proteomic stability offer distinct advantages over current widely used biofluids, serum and plasma. Improvements in our understanding of the urine proteome and in methods used in its evaluation will facilitate the clinical development of urinary protein biomarkers. Multiplexed bead-based immunoassays were utilized to evaluate 211 proteins in urines from 103 healthy donors. An additional 25 healthy donors provided serial urine samples over the course of two days in order to assess temporal variation in selected biomarkers. Nearly one-third of the evaluated biomarkers were detected in urine at levels greater than 1 ng/ml, representing a diverse panel of proteins with respect to structure, function and biological role. The presence of several biomarkers in urine was confirmed by western blot. Several methods of data normalization were employed to assess impact on biomarker variability. A complex pattern of correlations with urine creatinine, albumin and beta-2-microglobulin was observed indicating the presence of highly specific mechanisms of renal filtration. Further investigation of the urinary protein biomarkers identified in this preliminary study along with a consideration of the underlying proteomic trends suggested by these findings should lead to an improved capability to identify candidate biomarkers for clinical development.

Circulating prolactin levels and risk of epithelial ovarian cancer.

PURPOSE: Indirect evidence from experimental and epidemiological studies suggests that prolactin may be involved in ovarian cancer development. However, the relationship between circulating prolactin levels and risk of ovarian cancer is unknown. METHODS: We conducted a nested case-control study of 230 cases and 432 individually matched controls within three prospective cohorts to evaluate whether pre-diagnostic circulating prolactin is associated with subsequent risk of ovarian cancer. We also assessed whether lifestyle and reproductive factors are associated with circulating prolactin among controls. RESULTS: Prolactin levels were significantly lower among post- versus pre-menopausal women, parous versus nulliparous women, and past versus never users of oral contraceptives in our cross-sectional analysis of controls. In our nested case-control study, we observed a non-significant positive association between circulating prolactin and ovarian cancer risk (OR(Q4vsQ1) 1.56, 95 % CI 0.94, 2.63, p trend 0.15). Our findings were similar in multivariate-adjusted models and in the subgroup of women who donated blood ≥5 years prior to diagnosis. We observed a significant positive association between prolactin and risk for the subgroup of women with BMI ≥25 kg/m(2) (OR(Q4vsQ1) 3.10, 95 % CI 1.39, 6.90), but not for women with BMI <25 kg/m(2) (OR(Q4vsQ1) 0.81, 95 % CI 0.40, 1.64). CONCLUSIONS: Our findings suggest that prolactin may be associated with increased risk of ovarian cancer, particularly in overweight/obese women. Factors associated with reduced risk of ovarian cancer, such as parity and use of oral contraceptives, were associated with lower prolactin levels, which suggests that modulation of prolactin may be a mechanism underlying their association with risk.

Oxidants and not alkylating agents induce rapid mtDNA loss and mitochondrial dysfunction.

Mitochondrial DNA (mtDNA) is essential for proper mitochondrial function and encodes 22 tRNAs, 2 rRNAs and 13 polypeptides that make up subunits of complex I, III, IV, in the electron transport chain and complex V, the ATP synthase. Although mitochondrial dysfunction has been implicated in processes such as premature aging, neurodegeneration, and cancer, it has not been shown whether persistent mtDNA damage causes a loss of oxidative phosphorylation. We addressed this question by treating mouse embryonic fibroblasts with either hydrogen peroxide (H(2)O(2)) or the alkylating agent methyl methanesulfonate (MMS) and measuring several endpoints, including mtDNA damage and repair rates using QPCR, levels of mitochondrial- and nuclear-encoded proteins using antibody analysis, and a pharmacologic profile of mitochondria using the Seahorse Extracellular Flux Analyzer. We show that a 60min treatment with H(2)O(2) causes persistent mtDNA lesions, mtDNA loss, decreased levels of a nuclear-encoded mitochondrial subunit, a loss of ATP-linked oxidative phosphorylation and a loss of total reserve capacity. Conversely, a 60min treatment with 2mM MMS causes persistent mtDNA lesions but no mtDNA loss, no decrease in levels of a nuclear-encoded mitochondrial subunit, and no mitochondrial dysfunction. These results suggest that persistent mtDNA damage is not sufficient to cause mitochondrial dysfunction.

Factors associated with inflammation markers, a cross-sectional analysis.

Epidemiological studies have reported associations between circulating inflammation markers and risk of chronic diseases. It is of interest to examine whether risk factors for these diseases are associated with inflammation. We conducted a cross-sectional analysis to evaluate whether reproductive and lifestyle factors and circulating vitamin D were associated with inflammation markers, including C-reactive protein, cytokines (IL-1ß, IL-2, IL-4, IL-5, IL-6, IL-10, IL-12p40, IL-12p70, IL-13, TNFα), and cytokine modulators (IL-1RA, sIL-1RII, sIL-2Ra, sIL-4R, sIL-6R, sTNF-R1/R2), among 616 healthy women. We confirmed associations of several inflammation markers with age and BMI. We also observed significantly higher levels of certain inflammation markers in postmenopausal vs. premenopausal women (TNFα, sIL-1RII, sIL-2Ra), with increasing parity (IL-12p40), and with higher circulating 25(OH) vitamin D (IL-13) and lower levels among current users of non-steroidal anti-inflammatory drugs (NSAIDs) (IL-1ß, IL-2, IL-10, IL-12p70, and IL-12p40), current smokers (IL-4, IL-13, IL-12p40), and women with a family history of breast or ovarian cancer (IL-4, IL-10, IL-13). Our findings suggest that risk factors for chronic diseases (age, BMI, menopausal status, parity, NSAID use, family history of breast and ovarian cancer, and smoking) are associated with inflammation markers in healthy women.

Circulating inflammation markers and risk of epithelial ovarian cancer.

BACKGROUND: Factors contributing to chronic inflammation appear to be associated with increased risk of ovarian cancer. The purpose of this study was to assess the association between circulating levels of inflammation mediators and subsequent risk of ovarian cancer. METHODS: We conducted a case-control study of 230 cases and 432 individually matched controls nested within three prospective cohorts to evaluate the association of prediagnostic circulating levels of inflammation-related biomarkers (IL-1ß, IL-2, IL-4, IL-5, IL-6, IL-10, IL-12p40, IL-12p70, IL-13, TNFα, IL-1Ra, sIL-1RII, sIL-2Ra, sIL-4R, sIL-6R, sTNF-R1, and sTNF-R2) measured using Luminex xMap technology with risk of ovarian cancer. RESULTS: We observed a trend across quartiles for IL-2 (OR(Q4 vs. Q1): 1.57, 95% CI: 0.98-2.52, P = 0.07), IL-4 (OR(Q4 vs. Q1): 1.50, 95% CI: 0.95-2.38, P = 0.06), IL-6 (OR(Q4 vs. Q1): 1.63, 95% CI: 1.03-2.58, P = 0.03), IL-12p40 (OR(Q4 vs. Q1): 1.60, 95% CI: 1.02-2.51, P = 0.06), and IL-13 (OR(Q4 vs. Q1): 1.42, 95% CI: 0.90-2.26, P = 0.11). Trends were also observed when cytokines were modeled on the continuous scale for IL-4 (P trend = 0.01), IL-6 (P trend = 0.01), IL-12p40 (P trend = 0.01), and IL-13 (P trend = 0.04). ORs were not materially different after excluding cases diagnosed less than 5 years after blood donation or when limited to serous tumors. CONCLUSIONS AND IMPACT: This study provides the first direct evidence that multiple inflammation markers, specifically IL-2, IL-4, IL-6, IL-12, and IL-13, may be associated with risk of epithelial ovarian cancer, and adds to the evidence that inflammation is involved in the development of this disease.

A framework for evaluating biomarkers for early detection: validation of biomarker panels for ovarian cancer.

A panel of biomarkers may improve predictive performance over individual markers. Although many biomarker panels have been described for ovarian cancer, few studies used prediagnostic samples to assess the potential of the panels for early detection. We conducted a multisite systematic evaluation of biomarker panels using prediagnostic serum samples from the Prostate, Lung, Colorectal, and Ovarian Cancer (PLCO) screening trial. Using a nested case-control design, levels of 28 biomarkers were measured laboratory-blinded in 118 serum samples obtained before cancer diagnosis and 951 serum samples from matched controls. Five predictive models, each containing 6 to 8 biomarkers, were evaluated according to a predetermined analysis plan. Three sequential analyses were conducted: blinded validation of previously established models (step 1); simultaneous split-sample discovery and validation of models (step 2); and exploratory discovery of new models (step 3). Sensitivity, specificity, sensitivity at 98% specificity, and AUC were computed for the models and CA125 alone among 67 cases diagnosed within one year of blood draw and 476 matched controls. In step 1, one model showed comparable performance to CA125, with sensitivity, specificity, and AUC at 69.2%, 96.6%, and 0.892, respectively. Remaining models had poorer performance than CA125 alone. In step 2, we observed a similar pattern. In step 3, a model derived from all 28 markers failed to show improvement over CA125. Thus, biomarker panels discovered in diagnostic samples may not validate in prediagnostic samples; utilizing prediagnostic samples for discovery may be helpful in developing validated early detection panels.

Serum biomarker profiles as diagnostic tools in lung cancer.

BACKGROUND: Computed tomography (CT) scanning has emerged as an effective means of early detection for lung cancer. Despite marked improvement over earlier methodologies, the low level of specificity demonstrated by CT scanning has limited its clinical implementation as a screening tool. A minimally-invasive biomarker-based test that could further characterize CT-positive patients based on risk of malignancy would greatly enhance its clinical efficacy. METHODS: We performed an analysis of 81 serum proteins in 92 patients diagnosed with lung cancer and 172 CT-screened control individuals. We utilize a series of bioinformatics algorithms including Metropolis-Monte Carlo, artificial neural networks, Naïve Bayes, and additive logistic regression to identify multimarker panels capable of discriminating cases from controls with high levels of sensitivity and specificity in distinct training and independent validation sets. RESULTS: A three-biomarker panel comprised of MIF, prolactin, and thrombospondin identified using the Metropolis-Monte Carlo algorithm provided the best classification with a %Sensitivity/Specificity/Accuracy of 74/90/86 in the training set and 70/93/82 in the validation set. This panel was effective in the classification of control individuals demonstrating suspicious pulmonary nodules and stage I lung cancer patients. CONCLUSIONS: The selected serum biomarker panel demonstrated a high diagnostic utility in the current study and performance characteristics which compare favorably with previous reports. Further advancements may lead to the development of a diagnostic tool useful as an adjunct to CT-scanning.

Temporal reliability of cytokines and growth factors in EDTA plasma.

BACKGROUND: Cytokines are involved in the development of chronic diseases, including cancer. It is important to evaluate the temporal reproducibility of cytokines in plasma prior to conducting epidemiologic studies utilizing these markers. FINDINGS: We assessed the temporal reliability of CRP, 22 cytokines and their soluble receptors (IL-1α, IL-1ß, IL-1RA, IL-2, sIL-2R, IL-4, IL-5, IL-6, sIL-6R, IL-7, IL-8, IL-10, IL-12p40, IL-12p70, IL-13, IL-15, IL-17, TNFα, sTNF-R1, sTNF-R2, IFNα, IFNγ) and eight growth factors (GM-CSF, EGF, bFGF, G-CSF, HGF, VEGF, EGFR, ErbB2) in repeated EDTA plasma samples collected an average of two years apart from 18 healthy women (age range: 42-62) enrolled in a prospective cohort study. We also estimated the correlation between serum and plasma biomarker levels using 18 paired clinical samples from postmenopausal women (age range: 75-86).Twenty-six assays were able to detect their analytes in at least 70% of samples. Of those 26 assays, we observed moderate to high intra-class correlation coefficients (ICCs)(ranging from 0.53-0.89) for 22 assays, and low ICCs (0-0.47) for four assays. Serum and plasma levels were highly correlated (r > 0.6) for most markers, except for seven assays (r < 0.5). CONCLUSIONS: For 22 of the 31 biomarkers, a single plasma measurement is a reliable estimate of a woman's average level over a two-year period.

Serum biomarker panels for the discrimination of benign from malignant cases in patients with an adnexal mass.

OBJECTIVES: The diagnosis of an adnexal mass is a prevalent issue among women in the United States, although current methods of identifying those at high risk of malignancy remain insufficient. Ineffective triage of women with malignant masses is associated with delayed or inappropriate treatment and a negative effect on disease outcome. METHODS: We performed an evaluation of 65 ovarian cancer-related biomarkers in the circulation of women diagnosed with an adnexal mass. Our subject group consisted of women diagnosed with benign masses and early- and late-stage ovarian cancer. RESULTS: More than half of the biomarkers tested were found to differ significantly between benign and malignant cases. As individual markers, HE4 and CA-125 provided the greatest level of discrimination between benign and malignant cases, and the combination of these two biomarkers provided a higher level of discriminatory power than either marker considered alone. Multivariate statistical analysis identified several multimarker panels that could discriminate early-stage, late-stage, and combined ovarian cancers from benign cases with similar or slightly improved SN/SP levels to the CA-125/HE4 combination; however, these larger panels could not outperform the 2-biomarker panel in an independent validation set. We also identified a 3-biomarker panel with particular utility in premenopausal women. CONCLUSIONS: Our findings serve to advance the development of blood-based screening methods for the discrimination of benign and malignant ovarian masses by confirming and expanding upon the superior utility of the CA-125/HE4 combination.

Elimination of human lung cancer stem cells through targeting of the stem cell factor-c-kit autocrine signaling loop.

Cancer stem cells (CSC) are thought to be responsible for tumor initiation and tumor regeneration after chemotherapy. Previously, we showed that chemotherapy of non-small cell lung cancer (NSCLC) cells lines can select for outgrowth of highly tumorigenic and metastatic CSCs. The high malignancy of lung CSCs was associated with an efficient cytokine network. In this study, we provide evidence that blocking stem cell factor (SCF)-c-kit signaling is sufficient to inhibit CSC proliferation and survival promoted by chemotherapy. CSCs were isolated from NSCLC cell lines as tumor spheres under CSC-selective conditions and their stem properties were confirmed. In contrast to other tumor cells, CSCs expressed c-kit receptors and produced SCF. Proliferation of CSCs was inhibited by SCF-neutralizing antibodies or by imatinib (Gleevec), an inhibitor of c-kit. Although cisplatin treatment eliminated the majority of tumor cells, it did not eliminate CSCs, whereas imatinib or anti-SCF antibody destroyed CSCs. Significantly, combining cisplatin with imatinib or anti-SCF antibody prevented the growth of both tumor cell subpopulations. Our findings reveal an important role for the SCF-c-kit signaling axis in self-renewal and proliferation of lung CSCs, and they suggest that SCF-c-kit signaling blockade could improve the antitumor efficacy of chemotherapy of human NSCLC.

Role of eotaxin-1 signaling in ovarian cancer.

PURPOSE: Tumor cell growth and migration can be directly regulated by chemokines. In the present study, the association of CCL11 with ovarian cancer has been investigated. EXPERIMENTAL DESIGN AND RESULTS: Circulating levels of CCL11 in sera of patients with ovarian cancer were significantly lower than those in healthy women or women with breast, lung, liver, pancreatic, or colon cancer. Cultured ovarian carcinoma cells absorbed soluble CCL11, indicating that absorption by tumor cells could be responsible for the observed reduction of serum level of CCL11 in ovarian cancer. Postoperative CCL11 levels in women with ovarian cancer negatively correlated with relapse-free survival. Ovarian tumors overexpressed three known cognate receptors of CCL11, CC chemokine receptors (CCR) 2, 3, and 5. Strong positive correlation was observed between expression of individual receptors and tumor grade. CCL11 potently stimulated proliferation and migration/invasion of ovarian carcinoma cell lines, and these effects were inhibited by neutralizing antibodies against CCR2, CCR3, and CCR5. The growth-stimulatory effects of CCL11 were likely associated with activation of extracellular signal-regulated kinase 1/2, MEK1, and STAT3 phosphoproteins and with increased production of multiple cytokines, growth factors, and angiogenic factors. Inhibition of CCL11 signaling by the combination of neutralizing antibodies against the ligand and its receptors significantly increased sensitivity to cisplatin in ovarian carcinoma cells. CONCLUSION: We conclude that CCL11 signaling plays an important role in proliferation and invasion of ovarian carcinoma cells and CCL11 pathway could be targeted for therapy in ovarian cancer. Furthermore, CCL11 could be used as a biomarker and a prognostic factor of relapse-free survival in ovarian cancer.

Aberrant tumor-associated antigen autoantibody profiles in healthy controls detected by multiplex bead-based immunoassay.

There is an increasing amount of emphasis being placed on serological biomarkers as tools for early detection of various cancers. In addition to the tumor-related circulating antigens under current investigation, autoantibodies to tumor-associated antigens are emerging as alternative candidates due to their potential high sensitivity and specificity. Already a number of specific autoantibodies have been identified and several groups have reported on the ability of panels of autoantibodies to discriminate malignant from non-malignant conditions. In this investigation we evaluate tumor-associated antigen autoantibody profiles in a group of healthy individuals. We identify a subset of individuals that demonstrate high levels of autoantibody production across the spectrum of tumor-associated antigens tested. We conclude that this observation is a result of undefined non-malignant autoimmune stimulation. Our findings may be an indication of factors present in the general population that may confound multiplex autoantibody-based diagnostic tests by reducing assay specificity. Such factors will require further characterization and the development of adequate controls in order to improve the performance of diagnostic tests.

Reliability of tumor markers, chemokines, and metastasis-related molecules in serum.

There is a growing interest in the role that cancer biomarkers, metastasis-related molecules, and chemokines may play in the development and progression of various cancers. However, few studies have addressed the reliability of such biomarkers in healthy individuals over time. The objective of this study was to investigate the temporal reliability of multiple proteins in serum samples from healthy women who donated blood over successive years. Thirty five, postmenopausal women with two, repeated annual visits, and thirty, premenopausal women with three, repeated annual visits were randomly selected among eligible subjects from an existing, prospective cohort. Multiplexing Luminex xMAPTM technology was used to measure the levels of 55 serum proteins representing cancer antigens, chemokines, angiogenic and anti-angiogenic factors, proteases, adipokines, apoptotic molecules, and other markers in these women. The biomarkers with high detection rates (> 60%) and acceptable reliability (intraclass correlation coefficient, ICCs > or = 0.55) using xMAPTM method were: cancer antigens: AFP, CA 15-3, CEA, CA-125, SCC, SAA; growth factors/related molecules: ErbB2, IGFBP-1; proteases and adhesion molecules: MMP-1, 8, 9, sE-selectin, human kallikreins (KLK) 8,10, ICAM-1, VCAM-1, chemokines: fractalkine, MCP-1,2, RANTES, MIP-1alpha, MIP-1beta, Eotaxin, GRO-alpha, IP-10; inhibitors of angiogenesis: angiostatin and endostatin; adipokines leptin and resistin; apoptotic factor: Fas, and other proteins mesothelin, myeloperoxidase (MPO), and PAI-1. The rest of the biomarkers under investigation either had ICCs less than 0.55 or had low levels of detection (< 60%). These included cancer antigens: CA 19-9, CA 72-4, MICA, S100, TTR, ULBP1, ULBP2, ULBP3; proteases: MMP 2, 3, 7, 12, 13; chemokines: MCP-3, MIF, MIG; adipokines: leptin and resistin; apoptotic factors: FasL, DR5, Cyfra 21-1; and inhibitors of angiogenesis and other markers: thrombospondin and heat shock protein (HSP) 27. In conclusion, 34 out of the 55 biomarkers investigated were present in detectable levels in > 60% of the samples, and with an ICC > or = 0.55, indicating that a single serum measurement can be used in prospective epidemiological studies using the xMAPTM method.

Reproducibility of serum cytokines and growth factors.

BACKGROUND: In most studies, circulating biomarkers are usually assessed from a single sample, assuming that this single measurement represents the long-term biomarker status of the individual. Such an assumption is rarely tested although it may not be valid for all biomarkers. The objective of this study was to investigate the temporal reproducibility of a panel of cytokines and growth factors. METHODS: Thirty-five postmenopausal women with two annual visits and 30 premenopausal women with three annual visits were randomly selected from the participants in an existing prospective cohort. A total of 23 serum cytokines, nine growth factors and C-reactive protein (CRP) were measured using the Luminex xMap technology. In addition, for eight biomarkers, regular and high sensitivity (hs) assays were compared. RESULTS: The biomarkers with adequate (>60%) detection rates and acceptable (> or =0.55) intra-class correlation coefficients (ICCs) were: hsIL-1beta, IL-1RA, hsIL-2, hsIL-4, hsIL-5, hsIL-6, hsIL-10, IL-12p40, hsIL-12p70, hsTNF-alpha, TNF-R1, TNF-R2, CRP, HGF, NGF, and EGFR. The remaining biomarkers either had low temporal reproducibility or were undetectable in more than 40% of samples. CONCLUSIONS: The results suggest that 16 of the 41 biomarkers measured with Luminex technology showed sufficient sensitivity and temporal reproducibility in sera.

A serum based analysis of ovarian epithelial tumorigenesis.

OBJECTIVES: Ovarian epithelial carcinoma can be subdivided into separate histological subtypes including clear cell, endometrioid, mucinous, and serous. These carcinoma subtypes may represent distinctive pathways of tumorigenesis and disease development. This distinction could potentially be reflected in the levels of tumor produced factors that enter into the circulation and serve as biomarkers of malignant growth. Here, we analyze levels of circulating biomarkers from a diverse set of patients diagnosed with ovarian carcinoma to identify biomarker trends and relationships associated with distinct carcinoma histotypes and divergent tumorigenic pathways. METHODS: We utilize multiplexed bead-based immunoassays to measure serum levels of a diverse array of fifty-eight biomarkers from the sera of patients diagnosed with various histological subtypes of ovarian carcinoma and benign lesions. The biomarkers studied include cancer antigens, oncogenes, cytokines, chemokines, receptors, growth and angiogenic factors, proteases, hormones, and apoptosis and adhesion related molecules. Levels of each biomarker are compared statistically across carcinoma subtypes as well as with benign cases. RESULTS: A total of 21 serum biomarkers differ significantly between patients diagnosed with ovarian carcinomas and benign cases. Nine of these biomarkers are specific for carcinomas identified as clear cell, endometrioid, or mucinous in histology, while two biomarkers are specific for the serous histology. In a direct comparison of the histology groups, ten biomarkers are found to be subtype specific. Identified biomarkers include traditional and emerging tumor markers, cytokines and receptors, hormones, and adhesion- and metastasis-related proteins. CONCLUSIONS: We demonstrate here that the divergent histology-based tumorigenic pathways proposed for ovarian epithelial carcinomas are associated with distinct profiles of circulating biomarkers. Continued investigation into the relationships between these factors should reveal new insights into the complex mechanisms underlying ovarian epithelial tumorigenesis.

Drug-selected human lung cancer stem cells: cytokine network, tumorigenic and metastatic properties.

BACKGROUND: Cancer stem cells (CSCs) are thought to be responsible for tumor regeneration after chemotherapy, although direct confirmation of this remains forthcoming. We therefore investigated whether drug treatment could enrich and maintain CSCs and whether the high tumorogenic and metastatic abilities of CSCs were based on their marked ability to produce growth and angiogenic factors and express their cognate receptors to stimulate tumor cell proliferation and stroma formation. METHODOLOGY/FINDINGS: Treatment of lung tumor cells with doxorubicin, cisplatin, or etoposide resulted in the selection of drug surviving cells (DSCs). These cells expressed CD133, CD117, SSEA-3, TRA1-81, Oct-4, and nuclear beta-catenin and lost expression of the differentiation markers cytokeratins 8/18 (CK 8/18). DSCs were able to grow as tumor spheres, maintain self-renewal capacity, and differentiate. Differentiated progenitors lost expression of CD133, gained CK 8/18 and acquired drug sensitivity. In the presence of drugs, differentiation of DSCs was abrogated allowing propagation of cells with CSC-like characteristics. Lung DSCs demonstrated high tumorogenic and metastatic potential following inoculation into SCID mice, which supported their classification as CSCs. Luminex analysis of human and murine cytokines in sonicated lysates of parental- and CSC-derived tumors revealed that CSC-derived tumors contained two- to three-fold higher levels of human angiogenic and growth factors (VEGF, bFGF, IL-6, IL-8, HGF, PDGF-BB, G-CSF, and SCGF-beta). CSCs also showed elevated levels of expression of human VEGFR2, FGFR2, CXCR1, 2 and 4 receptors. Moreover, human CSCs growing in SCID mice stimulated murine stroma to produce elevated levels of angiogenic and growth factors. CONCLUSIONS/SIGNIFICANCE: These findings suggest that chemotherapy can lead to propagation of CSCs and prevention of their differentiation. The high tumorigenic and metastatic potentials of CSCs are associated with efficient cytokine network production that may represent a target for increased efficacy of cancer therapy.

Multiple effects of TRAIL in human carcinoma cells: induction of apoptosis, senescence, proliferation, and cytokine production.

TRAIL is a death ligand that induces apoptosis in malignant but not normal cells. Recently the ability of TRAIL to induce proliferation in apoptosis-resistant normal and malignant cells was reported. In this study, we analyzed TRAIL effects in apoptosis sensitive MCF7, OVCAR3 and H460 human tumor cell lines. TRAIL at low concentrations preferentially induced cell proliferation. At 100 ng/ml, apoptotic death was readily observed, however surviving cells acquired higher proliferative capacity. TRAIL-stimulated production of several cytokines, IL-8, RANTES, MCP-1 and bFGF, and activation of caspases 1 and 8 was essential for this effect. Antibodies to IL-8, RANTES, and bFGF blocked TRAIL-induced cell proliferation and further stimulated apoptosis. For the first time, we report that high TRAIL concentrations induced cell senescence as determined by the altered morphology and expression of several senescence markers: SA-beta-gal, p21Waf1/Cip1, p16INK4a, and HMGA. Caspase 9 inhibition protected TRAIL-treated cells from senescence, whereas inhibition of caspases 1 and 8 increased the yield of SLP cells. In conclusion, in cultured human carcinoma cells, TRAIL therapy results in three functional outcomes, apoptosis, proliferation and senescence. TRAIL-induced proapoptotic and prosurvival responses correlate with the strength of signaling. TRAIL-induced cytokine production is responsible for its proliferative and prosurvival effects.

Multiplex analysis of cytokines as biomarkers that differentiate benign and malignant thyroid diseases.

Thyroid cancer incidence is increasing, and its diagnosis can be challenging. Fine needle biopsy, the principal clinical tool to make a tissue diagnosis, leads to inconclusive diagnoses in up to 30% of the cases, leading to surgery. Advances in proteomics are improving abilities to diagnose malignant conditions using small samples of tissue or body fluids. We hypothesized that analysis of serum growth factors would uncover diagnostically informative differences between benign and malignant thyroid conditions. Using xMAP profiling, we evaluated concentrations of 19 cytokines, chemokines, and growth factors. We used sera from 23 patients with cancer (Malignant group), 24 patients with benign nodular thyroid disease (Benign group), and 23 healthy subjects (Normal group). In univariate analysis, five factors (epithelial growth factor, hepatocyte growth factor, Interleukins-5 and -8, and regulated upon activation, normally T-expressed and presumably secreted (RANTES) distinguished subjects with thyroid disease from the Normal group. In multivariate analysis, the set {Interleukin-8, hepatocyte growth factor, monocyte-induced γ interferon, interleukin-12 p40} achieved noteworthy discrimination between Benign and Malignant groups (area under the receiver operating characteristics curve was 0.81 (95% confidence interval: 0.65-0.90)). Multiplex panels of serum biomarkers may be promising tools to diagnose cancer in patients presenting with evidence of nodular thyroid disease.

Development of multimarker panel for early detection of endometrial cancer. High diagnostic power of prolactin.

OBJECTIVE: Endometrial carcinoma is the most common gynecologic cancer. Although the prognosis for endometrial cancer is generally good, cancers identified at late stages are associated with high levels of morbidity and mortality. Therefore, prevention and early detection may further reduce the burden of this challenging disease. METHODS: A panel of 64 serum biomarkers was analyzed in sera of patients with stages I-III endometrial cancer and age-matched healthy women, utilizing a multiplex xMAP bead-based immunoassay. For multivariate analysis, four different statistical classification methods were used: logistic regression (LR), separating hyperplane (SHP), k nearest neighbors (KNN), and classification tree (CART). For each of these classifiers, a diagnostic model was created based on the cross-validation set consisting of sera from 115 patients with endometrial cancer and 135 healthy women. RESULTS: Our data have demonstrated that patients with endometrial cancer have significantly different expression patterns of several serum biomarkers as compared to healthy controls. Prolactin was the strongest discriminative biomarker for endometrial cancer providing 98.3% sensitivity and 98.0% specificity alone. Our results have revealed that serum concentration of cancer antigens, including CA 125, CA 15-3, and CEA are higher in patients with Stage III endometrial cancer as compared to those with Stage I. In addition, we have shown that the expression of CA 125, AFP, and ACTH is elevated in women with tumor grade 3 vs. grade 1. Furthermore, five-biomarker panel (prolactin, GH, Eotaxin, E-selectin, and TSH) identified in this study was able to discriminate endometrial cancer from ovarian and breast cancers with high sensitivity and specificity. CONCLUSIONS: The ability of prolactin to accurately discriminate between cancer and control groups indicates that this biomarker could potentially be used for development of blood-based test for the early detection of endometrial cancer in high-risk populations. Combining the information on multiple serum markers using flexible statistical methods allows for achieving high cancer selectivity.