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This study was conducted to develop a novel algorithm for determining the origin of tumors by combining analysis of cluster patterns with immunocytochemistry (ICC) for markers in cells from fine-needle aspirates of ascites. We used LBC, based on SurePathTM (BD Diagnostics) technology, to screen 96 peritoneal fluid samples from patients with known malignancies and from 10 control patients with cirrhosis. Following dual ICC staining for cytokeratin 7 (CK7) and paired box gene 8 (PAX8), we developed an algorithm using immunoreactivity and three-dimensional (3D) cluster patterns to correlate staining and 3D cluster patterns with common primary origins that included stomach, ovarian, pancreatobiliary tract, colon, lung, and breast cancers. With the application of an automatic digitalized image analyzer, competence performance was analyzed using receiver operating characteristics (ROC) curve analysis. CK7 and PAX8 staining and 3D cluster patterns were used to differentiate primary origins. Samples from patients with stomach cancer were no 3D cluster /CK7+/PAX8- with area under the curve (AUC) of 0.8699 in ROC curve analysis. Samples from ovarian cancer patients were large 3D cluster/CK7+/PAX8+ with AUC of 0.9812. Samples from pancreatobiliary tract cancer patients were small 3D cluster/CK7+/PAX8- with AUC of 0.8772. The remaining cancer samples, including breast, lung and colon cancer samples, had similar patterns of large 3D clusters/CK7+/PAX8- with AUC of 0.882, especially for lung cancer. SurePathTM technology, using 3D cluster patterns and dual ICC for CK7 and PAX8 in peritoneal fluid samples, can provide important information for determining specific primary origins in cases of unknown primary carcinoma., Competing Interests: The authors have declared that no competing interests exist.

Objective: To determine the utility of novel combinations of biomarkers, using both a one-step and two-step assay format, to distinguish serum of early ovarian cancer patients from that of healthy controls and to discern the utility of these biomarkers in a monitoring capacity., Methods: For ovarian cancer detection, HE4, Glycodelin, MMP7, SLPI, Plau-R, MUC1, Inhibin A, PAI-1, and CA125 were evaluated in a cohort of 200 women with ovarian cancer and 396 healthy age-matched controls. Each biomarker was assessed by serum-based immunoassays utilizing novel monoclonal antibody pairs or commercial kits. For detection of disease recurrence, HE4, Glycodelin, MMP7 and CA125 were evaluated in 260 samples from 30 patients with OC monitored longitudinally after diagnosis., Results: Based upon ROC curve analysis, the sensitivity/specificity of specific biomarker combination algorithms ranged from 59.0%/99.7% to 80.5%/96.5% for detection of early stage ovarian cancer and 76.9%/99.7% to 89.2%/97.2% for detection of late stage cancer. In monitoring evaluation of 27 patients who experienced recurrence of OC, sensitivity for predicting recurrence was 100% for the biomarker panel and 96% for CA125. At least one of the panel biomarkers was elevated earlier (range 6-69 weeks) than CA125 and prior to clinical evidence of recurrence in 14/27 (52%) patients., Conclusions: We have developed and demonstrated the utility of several one- and two-step multi-marker combinations with acceptable test characteristics for possible use in an ovarian cancer screening population. A subset of this panel may also provide adjunctive information to rising CA125 levels in disease monitoring.

In recent years, the application of genomic and proteomic technologies to the problem of breast cancer prognosis and the prediction of therapy response have begun to yield encouraging results. Independent studies employing transcriptional profiling of primary breast cancer specimens using DNA microarrays have identified gene expression profiles that correlate with clinical outcome in primary breast biopsy specimens. Recent advances in microarray technology have demonstrated reproducibility, making clinical applications more achievable. In this regard, one such DNA microarray device based upon a 70-gene expression signature was recently cleared by the US FDA for application to breast cancer prognosis. These DNA microarrays often employ at least 70 gene targets for transcriptional profiling and prognostic assessment in breast cancer. The use of PCR-based methods utilizing a small subset of genes has recently demonstrated the ability to predict the clinical outcome in early-stage breast cancer. Furthermore, protein-based immunohistochemistry methods have progressed from using gene clusters and gene expression profiling to smaller subsets of expressed proteins to predict prognosis in early-stage breast cancer. Beyond prognostic applications, DNA microarray-based transcriptional profiling has demonstrated the ability to predict response to chemotherapy in early-stage breast cancer patients. In this review, recent advances in the use of multiple markers for prognosis of disease recurrence in early-stage breast cancer and the prediction of therapy response will be discussed.

The screening for cervical carcinoma and its malignant precursors (cervical neoplasia) currently employs morphology-based detection methods (Papanicolaou [Pap] smear) in addition to the detection of high-risk human papillomavirus. The combination of the Pap smear with human papillomavirus testing has achieved significant improvements in sensitivity for the detection of cervical disease. Diagnosis of cervical neoplasia is dependent upon histology assessment of cervical biopsy specimens. Attempts to improve the specificity of cervical disease screening have focused on the investigation of molecular biomarkers for adjunctive use in combination with the Pap smear. Active research into the genomic and proteomic alterations that occur during human papillomavirus-induced neoplastic transformation have begun to characterize some of the basic mechanisms inherent to the disease process of cervical cancer development. This research continues to demonstrate the complexity of multiple genomic and proteomic alterations that accumulate during the tumorigenesis process. Despite this diversity, basic patterns of uncontrolled signal transduction, cell cycle deregulation, activation of DNA replication and altered extracellular matrix interactions are beginning to emerge as common features inherent to cervical cancer development. Some of these gene or protein expression alterations have been investigated as potential biomarkers for screening and diagnostics applications. The contribution of multiple gene alterations in the development of cervical cancer suggests that the application of multiple biomarker panels has the potential to develop clinically useful molecular diagnostics. In this review, the application of biomarkers for the improvement of sensitivity and specificity of the detection of cervical neoplasia within cytology specimens will be discussed.

The accurate detection and diagnosis of cervical carcinoma and its malignant precursors (collectively referred to as high-grade cervical disease) represents one of the current challenges in clinical medicine and cytopathology. The advent of molecular diagnostics and the use of whole-genome profiling using DNA microarrays promises to yield improved understanding of the disease process with the subsequent development of more accurate diagnostic procedures based upon these discoveries. Recent reports describing a variety of experimental approaches have identified a series of candidate genes that are overexpressed in cervical carcinoma. In this article, representative examples of these markers and the resulting translational research will be reviewed within the context of improved cervical disease detection. An emerging class of markers, the minichromosome maintenance protein family of DNA licensing factors (MCM-2, MCM-6, MCM-7), shows promise for the specific detection of high-grade cervical disease using simple antibody-based immunochemistry formats. These proteins are overexpressed in cervical disease as a result of infection by oncogenic strains of human papillomavirus (HPV) and subsequent uncontrolled activation of gene transcription and aberrant S-phase induction, mediated through the E2F transcription factor pathway. This behavior appears to be a hallmark of high-grade cervical disease and provides the link between oncogenic HPV infections and the molecular behavior of cervical neoplasia (CN). The use of these molecular descriptors of CN in simple immunochemistry formats compatible with conventional cytology preparations is anticipated to improve the screening and detection of cervical disease within the healthcare system.