Do serum biomarkers really measure breast cancer?

Background Because screening mammography for breast cancer is less effective for premenopausal women, we investigated the feasibility of a diagnostic blood test using serum proteins. Methods This study used a set of 98 serum proteins and chose diagnostically relevant subsets via various feature-selection techniques. Because of significant noise in the data set, we applied iterated Bayesian model averaging to account for model selection uncertainty and to improve generalization performance. We assessed generalization performance using leave-one-out cross-validation (LOOCV) and receiver operating characteristic (ROC) curve analysis. Results The classifiers were able to distinguish normal tissue from breast cancer with a classification performance of AUC = 0.82 ± 0.04 with the proteins MIF, MMP-9, and MPO. The classifiers distinguished normal tissue from benign lesions similarly at AUC = 0.80 ± 0.05. However, the serum proteins of benign and malignant lesions were indistinguishable (AUC = 0.55 ± 0.06). The classification tasks of normal vs. cancer and normal vs. benign selected the same top feature: MIF, which suggests that the biomarkers indicated inflammatory response rather than cancer. Conclusion Overall, the selected serum proteins showed moderate ability for detecting lesions. However, they are probably more indicative of secondary effects such as inflammation rather than specific for malignancy.United States. Dept. of Defense. Breast Cancer Research Program (Grant No. W81XWH-05-1-0292)National Institutes of Health (U.S.) (R01 CA-112437-01)National Institutes of Health (U.S.) (NIH CA 84955

Genetic engineering of TNF family protein-based vaccines for antitumor immunotherapy

The interaction between tumor cells and dendritic cells (DC) is a critical event for both initiation and regulation of specific antitumor immune responses. Based on the unique ability to present tumor antigen to and stimulate clonal expansion of naïve T cells, DC have been widely used to induce antitumor immunity in both preclinical animal models and human clinical trials. However, a growing body of clinical data and experimental evidence demonstrate that tumor exhibits a variety of inhibitory effects on the immune system and the DC system, in particular. It is well documented to date that tumor-derived factors influence DC generation, maturation, activity, and survival both in vitro and in vivo. Therefore, DC dysfunction in the tumor-bearing hosts could be largely responsible for the ability of tumor cells to escape from immune recognition or induce tumor specific tolerance. However, understanding the suppressive effect of tumor on the immune system, in particular on DC, and the protection of DC from tumor-induced dysfunction has not been studied. Therefore, the goals of this research project were (i) the understanding of DC immunobiology in the tumor microenvironment, revealing cellular and molecular mechanisms involved in tumor escape from immune recognition and elimination, (ii) the generation of novel antitumor vaccines which protect DC from tumor-mediated suppression, and (iii) the identification of primary mechanisms involved in vaccine-mediated antitumor immunity. The Tumor Necrosis Factor Ligand (TNFL) family is a group of cytokines, which through the interaction with corresponding receptors, regulate cell functions and activities. In this project we had examined three proteins which belong to the TNFL family: CD40L, RANKL, and 4-1BBL. Importantly, the receptors for these cytokines are found on activated DC. CD40L, RANKL and 4-1BBL were shown to influence DC activation and cytokine secretion. It also has been demonstrated that CD40L and 4-1BBL have a strong antitumor effect, whereas, the role of RANKL in antitumor immunity has not yet been examined. CD40L is a well studied cytokine, shown to play an important role in the development of both humoral and cell-mediated immunity. However, the mechanisms of action of all these three cytokines on immune effectors are not fully understood. Here, we have evaluated the ability of local adenoviral gene transfer of CD40L, RANKL and 4-1BBL to elicit an antitumor immune response to established tumors in mice. Adenoviruses encoding these genes (Ad-CD40L, Ad-RANKL and Ad-4-1BBL) were constructed and tested in murine MC38 colon and TS/A breast adenocarcinoma therapy models. Our results demonstrate that intratumoral administration of all three tested vectors resulted in a significant inhibition of MC38 and TS/A tumor growth when compared with control groups treated with either saline or control adenovirus. In addition, a single intratumoral injection of DC transduced with the adenoviral vectors also resulted in a significant inhibition of MC38 and TS/A tumor growth. Furthermore, treatment of TS/A tumors with DC transduced with Ad-CD40L induced a complete tumor rejection with the generation of a tumor-specific immune memory. Thus, these results demonstrate that DC genetically modified to express CD40L immunotherapy displays the strongest antitumor effect compare to Ad-CD40L or RANKL- and 4-1BBL-based therapeutic approaches. Next, we have observed that DC generated from tumor-bearing mice, in addition to expressing low levels of CD80 and CD86 and producing decreased amounts of IL-12, exhibit decreased expression of CD40 molecules. Moreover, we have detected that MC38 tumor suppressed CD40 expression on DC isolated from spleens of tumor bearers. These data suggest that tumors induce suppression of CD40 expression on DC, and, thus, result in dysfunction and inhibition of maturation of these cells. Subsequently, we have demonstrated that CD40L, in addition to generating a strong antitumor immunity, was able to protect DC from tumor-induced dysfunction. CD40L stimulates DC to express higher levels of co-stimulatory molecules, produce significantly higher levels of IL-12 protein, survive longer in cultures, efficiently stimulate T cells, induce high cytotoxic T lymphocyte activity, present tumor antigens to T cells more efficiently, and migrate to the lymphoid organs faster then control DC. We have shown that by up-regulating DC activity and function, CD40L rescues DC from tumor-induced suppression. In summary, our data demonstrate that CD40L-based immunotherapy is an effective approach for inducing antitumor immunity and rescuing DC from tumor-induced dysfunction. These results should guide the development of novel therapies for prevention of immunosuppression in cancer patients and design of novel effective immunotherapeutic strategies for cancer

Do serum biomarkers really measure breast cancer?

Abstract Background Because screening mammography for breast cancer is less effective for premenopausal women, we investigated the feasibility of a diagnostic blood test using serum proteins. Methods This study used a set of 98 serum proteins and chose diagnostically relevant subsets via various feature-selection techniques. Because of significant noise in the data set, we applied iterated Bayesian model averaging to account for model selection uncertainty and to improve generalization performance. We assessed generalization performance using leave-one-out cross-validation (LOOCV) and receiver operating characteristic (ROC) curve analysis. Results The classifiers were able to distinguish normal tissue from breast cancer with a classification performance of AUC = 0.82 ± 0.04 with the proteins MIF, MMP-9, and MPO. The classifiers distinguished normal tissue from benign lesions similarly at AUC = 0.80 ± 0.05. However, the serum proteins of benign and malignant lesions were indistinguishable (AUC = 0.55 ± 0.06). The classification tasks of normal vs. cancer and normal vs. benign selected the same top feature: MIF, which suggests that the biomarkers indicated inflammatory response rather than cancer. Conclusion Overall, the selected serum proteins showed moderate ability for detecting lesions. However, they are probably more indicative of secondary effects such as inflammation rather than specific for malignancy.</p

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. © 2007 Elsevier Inc. All rights reserved