A Noninvasive Blood-based Combinatorial Proteomic Biomarker Assay to Detect Breast Cancer in Women over age 50 with BI-RADS 3, 4, or 5 Assessment.

PURPOSE: With improvements in breast cancer imaging, there has been a corresponding increase in false-positives and avoidable biopsies. There is a need to better differentiate when a breast biopsy is warranted and determine appropriate follow-up. This study describes the design and clinical performance of a combinatorial proteomic biomarker assay (CPBA), Videssa Breast, in women over age 50 years. EXPERIMENTAL DESIGN: A BI-RADS 3, 4, or 5 assessment was required for clinical trial enrollment. Serum was collected prior to breast biopsy and subjects were followed for 6-12 months and clinically relevant outcomes were recorded. Samples were split into training (70%) and validation (30%) cohorts with an approximate 1:4 case:control ratio in both arms. RESULTS: A CPBA that combines biomarker data with patient clinical data was developed using a training cohort (469 women, cancer incidence: 18.5%), resulting in 94% sensitivity and 97% negative predictive value (NPV). Independent validation of the final algorithm in 194 subjects (breast cancer incidence: 19.6%) demonstrated a sensitivity of 95% and a NPV of 97%. When combined with previously published data for women under age 50, Videssa Breast achieves a comprehensive 93% sensitivity and 98% NPV in a population of women ages 25-75. Had Videssa Breast results been incorporated into the clinical workflow, approximately 45% of biopsies might have been avoided. CONCLUSIONS: Videssa Breast combines serum biomarkers with clinical patient characteristics to provide clinicians with additional information for patients with indeterminate breast imaging results, potentially reducing false-positive breast biopsies.

A Combinatorial Proteomic Biomarker Assay to Detect Ovarian Cancer in Women.

Ovarian cancer is often fatal and incidence in the general population is low, underscoring the necessity (and the challenges) for advancements in screening and early detection. The goal of this study was to design a serum-based biomarker panel and corresponding multivariate algorithm that can be used to accurately detect ovarian cancer. A combinatorial protein biomarker assay (CPBA) that uses CA125, HE4, and 3 tumor-associated autoantibodies resulted in an area under the curve of 0.98. The CPBA Ov algorithm was trained using subjects who were suspected to have gynecological cancer and were scheduled for surgery. As a surgical rule-out test, the clinical performance achieves 100% sensitivity and 83.7% specificity. Although sample size (n = 60) is a limiting factor, the CPBA Ov algorithm performed better than either CA-125 alone or the Risk of Ovarian Malignancy Algorithm.

Breast density does not impact the ability of Videssa® Breast to detect breast cancer in women under age 50.

Breast density is associated with reduced imaging resolution in the detection of breast cancer. A biochemical approach that is not affected by density would provide an important tool to healthcare professionals who are managing women with dense breasts and suspicious imaging findings. Videssa® Breast is a combinatorial proteomic biomarker assay (CPBA), comprised of Serum Protein Biomarkers (SPB) and Tumor Associated Autoantibodies (TAAb) integrated with patient-specific clinical data to produce a diagnostic score that reliably detects breast cancer (BC) as an adjunctive tool to imaging. The performance of Videssa® Breast was evaluated in the dense (a and b) and non-dense (c and d) groups in a population of n = 545 women under age 50. The sensitivity and specificity in the dense breast group were calculated to be 88.9% and 81.2%, respectively, and 92.3% and 86.6%, respectively, for the non-dense group. No significant differences were observed in the sensitivity (p = 1.0) or specificity (p = 0.18) between these groups. The NPV was 99.3% and 99.1% in non-dense and dense groups, respectively. Unlike imaging, Videssa® Breast does not appear to be impacted by breast density; it can effectively detect breast cancer in women with dense and non-dense breasts alike. Thus, Videssa® Breast provides a powerful tool for healthcare providers when women with dense breasts present with challenging imaging findings. In addition, Videssa® Breast provides assurance to women with dense breasts that they do not have breast cancer, reducing further anxiety in this higher risk patient population.

A Noninvasive Blood-based Combinatorial Proteomic Biomarker Assay to Detect Breast Cancer in Women Under the Age of 50 Years.

BACKGROUND: Despite significant advances in breast imaging, the ability to detect breast cancer (BC) remains a challenge. To address the unmet needs of the current BC detection paradigm, 2 prospective clinical trials were conducted to develop a blood-based combinatorial proteomic biomarker assay (Videssa Breast) to accurately detect BC and reduce false positives (FPs) from suspicious imaging findings. PATIENTS AND METHODS: Provista-001 and Provista-002 (cohort one) enrolled Breast Imaging Reporting and Data System 3 or 4 women aged under 50 years. Serum was evaluated for 11 serum protein biomarkers and 33 tumor-associated autoantibodies. Individual biomarker expression, demographics, and clinical characteristics data from Provista-001 were combined to develop a logistic regression model to detect BC. The performance was tested using Provista-002 cohort one (validation set). RESULTS: The training model had a sensitivity and specificity of 92.3% and 85.3% (BC prevalence, 7.7%), respectively. In the validation set (BC prevalence, 2.9%), the sensitivity and specificity were 66.7% and 81.5%, respectively. The negative predictive value was high in both sets (99.3% and 98.8%, respectively). Videssa Breast performance in the combined training and validation set was 99.1% negative predictive value, 87.5% sensitivity, 83.8% specificity, and 25.2% positive predictive value (BC prevalence, 5.87%). Overall, imaging resulted in 341 participants receiving follow-up procedures to detect 30 cancers (90.6% FP rate). Videssa Breast would have recommended 111 participants for follow-up, a 67% reduction in FPs (P < .00001). CONCLUSIONS: Videssa Breast can effectively detect BC when used in conjunction with imaging and can substantially reduce unnecessary medical procedures, as well as provide assurance to women that they likely do not have BC.

Integration of Serum Protein Biomarker and Tumor Associated Autoantibody Expression Data Increases the Ability of a Blood-Based Proteomic Assay to Identify Breast Cancer.

Despite significant advances in breast imaging, the ability to accurately detect Breast Cancer (BC) remains a challenge. With the discovery of key biomarkers and protein signatures for BC, proteomic technologies are currently poised to serve as an ideal diagnostic adjunct to imaging. Research studies have shown that breast tumors are associated with systemic changes in levels of both serum protein biomarkers (SPB) and tumor associated autoantibodies (TAAb). However, the independent contribution of SPB and TAAb expression data for identifying BC relative to a combinatorial SPB and TAAb approach has not been fully investigated. This study evaluates these contributions using a retrospective cohort of pre-biopsy serum samples with known clinical outcomes collected from a single site, thus minimizing potential site-to-site variation and enabling direct assessment of SPB and TAAb contributions to identify BC. All serum samples (n = 210) were collected prior to biopsy. These specimens were obtained from 18 participants with no evidence of breast disease (ND), 92 participants diagnosed with Benign Breast Disease (BBD) and 100 participants diagnosed with BC, including DCIS. All BBD and BC diagnoses were based on pathology results from biopsy. Statistical models were developed to differentiate BC from non-BC (i.e., BBD and ND) using expression data from SPB alone, TAAb alone, and a combination of SPB and TAAb. When SPB data was independently used for modeling, clinical sensitivity and specificity for detection of BC were 74.7% and 77.0%, respectively. When TAAb data was independently used, clinical sensitivity and specificity for detection of BC were 72.2% and 70.8%, respectively. When modeling integrated data from both SPB and TAAb, the clinical sensitivity and specificity for detection of BC improved to 81.0% and 78.8%, respectively. These data demonstrate the benefit of the integration of SPB and TAAb data and strongly support the further development of combinatorial proteomic approaches for detecting BC.

High-throughput RNAi screening for the identification of novel targets.

Gene silencing through RNA interference has provided researchers with an effective way to study gene function. High-throughput RNA interference (HT-RNAi) screening has further permitted researchers to identify functionally relevant mediators of cellular response on a large scale. These screens have greatly expedited the discovery of novel targets and pathway mediators. Here, we describe the methodology for performing HT-RNAi screening of HeLa cells transfected with short interfering RNA (siRNA) libraries in 384-well microplate format. Using this plate format, the HT-RNAi assay can be easily adapted to semi-automated or fully automated platforms. The library siRNA are introduced into the cells through reverse transfection using cationic lipids. HT-RNAi screening for modulators of cell proliferation can be accomplished using a single read out reagent. This type of RNAi screening can be used with most plate-based cellular assays and can be optimized for most cultured cells lines, thus becoming a powerful tool to identify specific gene modulators and targets for drug discovery.

The genomic and proteomic content of cancer cell-derived exosomes.

Exosomes are secreted membrane vesicles that have been proposed as an effective means to detect a variety of disease states, including cancer. The properties of exosomes, including stability in biological fluids, allow for their efficient isolation and make them an ideal vehicle for studies on early disease detection and evaluation. Much data has been collected over recent years regarding the messenger RNA, microRNA, and protein contents of exosomes. In addition, many studies have described the functional role that exosomes play in disease initiation and progression. Tumor cells have been shown to secrete exosomes, often in increased amounts compared to normal cells, and these exosomes can carry the genomic and proteomic signatures characteristic of the tumor cells from which they were derived. While these unique signatures make exosomes ideal for cancer detection, exosomes derived from cancer cells have also been shown to play a functional role in cancer progression. Here, we review the unique genomic and proteomic contents of exosomes originating from cancer cells as well as their functional effects to promote tumor progression.

High-throughput RNAi screening identifies a role for TNK1 in growth and survival of pancreatic cancer cells.

To identify novel targets in pancreatic cancer cells, we used high-throughput RNAi (HT-RNAi) to select genes that, when silenced, would decrease viability of pancreatic cancer cells. The HT-RNAi screen involved reverse transfecting the pancreatic cancer cell line BxPC3 with a siRNA library targeting 572 kinases. From replicate screens, approximately 32 kinases were designated as hits, of which 22 kinase targets were selected for confirmation and validation. One kinase identified as a hit from this screen was tyrosine kinase nonreceptor 1 (TNK1), a kinase previously identified as having tumor suppressor-like properties in embryonic stem cells. Silencing of TNK1 with siRNA showed reduced proliferation in a panel of pancreatic cancer cell lines. Furthermore, we showed that silencing of TNK1 led to increased apoptosis through a caspase-dependent pathway and that targeting TNK1 with siRNA can synergize with gemcitabine treatment. Despite previous reports that TNK1 affects Ras and NF-κB signaling, we did not find similar correlations with these pathways in pancreatic cancer cells. Our results suggest that TNK1 in pancreatic cancer cells does not possess the same tumor suppressor properties seen in embryonic cells but seems to be involved in growth and survival. The application of functional genomics by using HT-RNAi screens has allowed us to identify TNK1 as a growth-associated kinase in pancreatic cancer cells.

NCI60 cancer cell line panel data and RNAi analysis help identify EAF2 as a modulator of simvastatin and lovastatin response in HCT-116 cells.

Simvastatin and lovastatin are statins traditionally used for lowering serum cholesterol levels. However, there exists evidence indicating their potential chemotherapeutic characteristics in cancer. In this study, we used bioinformatic analysis of publicly available data in order to systematically identify the genes involved in resistance to cytotoxic effects of these two drugs in the NCI60 cell line panel. We used the pharmacological data available for all the NCI60 cell lines to classify simvastatin or lovastatin resistant and sensitive cell lines, respectively. Next, we performed whole-genome single marker case-control association tests for the lovastatin and simvastatin resistant and sensitive cells using their publicly available Affymetrix 125K SNP genomic data. The results were then evaluated using RNAi methodology. After correction of the p-values for multiple testing using False Discovery Rate, our results identified three genes (NRP1, COL13A1, MRPS31) and six genes (EAF2, ANK2, AKAP7, STEAP2, LPIN2, PARVB) associated with resistance to simvastatin and lovastatin, respectively. Functional validation using RNAi confirmed that silencing of EAF2 expression modulated the response of HCT-116 colon cancer cells to both statins. In summary, we have successfully utilized the publicly available data on the NCI60 cell lines to perform whole-genome association studies for simvastatin and lovastatin. Our results indicated genes involved in the cellular response to these statins and siRNA studies confirmed the role of the EAF2 in response to these drugs in HCT-116 colon cancer cells.

Characterization of novel diaryl oxazole-based compounds as potential agents to treat pancreatic cancer.

A series of diaryl- and fluorenone-based analogs of the lead compound UA-62784 [4-(5-(4-methoxyphenyl)oxazol-2-yl)-9H-fluoren-9-one] was synthesized with the intention of improving upon the selective cytotoxicity of UA-62784 against human pancreatic cancer cell lines with a deletion of the tumor suppressor gene deleted in pancreas cancer locus 4 (DPC-4, SMAD-4). Over 80 analogs were synthesized and tested for antitumor activity against pancreatic cancer (PC) cell lines (the PC series). Despite a structural relationship to UA-62784, which inhibits the mitotic kinesin centromere protein E (CENP-E), none of the analogs was selective for DPC-4-deleted pancreatic cancer cell lines. Furthermore, none of the analogs was a potent or selective inhibitor of four different mitotic kinesins (mitotic kinesin-5, CENP-E, mitotic kinesin-like protein-1, and mitotic centromere-associated kinesin). Therefore, other potential mechanisms of action were evaluated. A diaryl oxazole lead analog from this series, PC-046 [5-(4-methoxyphenyl)-2-(3-(3-methoxyphenyl)pyridin-4-yl) oxazole], was shown to potently inhibit several protein kinases that are overexpressed in human pancreatic cancers, including tyrosine receptor kinase B, interleukin-1 receptor-associated kinase-4, and proto-oncogene Pim-1. Cells exposed to PC-046 exhibit a cell cycle block in the S-phase followed by apoptotic death and necrosis. PC-046 effectively reduced MiaPaca-2 tumor growth in severe combined immunodeficiency mice by 80% compared with untreated controls. The plasma half-life was 7.5 h, and cytotoxic drug concentrations of >3 muM were achieved in vivo in mice. The diaryl oxazole series of compounds represent a new chemical class of anticancer agents that inhibit several types of cancer-relevant protein kinases.

Synthetic lethal RNAi screening identifies sensitizing targets for gemcitabine therapy in pancreatic cancer.

BACKGROUND: Pancreatic cancer retains a poor prognosis among the gastrointestinal cancers. It affects 230,000 individuals worldwide, has a very high mortality rate, and remains one of the most challenging malignancies to treat successfully. Treatment with gemcitabine, the most widely used chemotherapeutic against pancreatic cancer, is not curative and resistance may occur. Combinations of gemcitabine with other chemotherapeutic drugs or biological agents have resulted in limited improvement. METHODS: In order to improve gemcitabine response in pancreatic cancer cells, we utilized a synthetic lethal RNAi screen targeting 572 known kinases to identify genes that when silenced would sensitize pancreatic cancer cells to gemcitabine. RESULTS: Results from the RNAi screens identified several genes that, when silenced, potentiated the growth inhibitory effects of gemcitabine in pancreatic cancer cells. The greatest potentiation was shown by siRNA targeting checkpoint kinase 1 (CHK1). Validation of the screening results was performed in MIA PaCa-2 and BxPC3 pancreatic cancer cells by examining the dose response of gemcitabine treatment in the presence of either CHK1 or CHK2 siRNA. These results showed a three to ten-fold decrease in the EC50 for CHK1 siRNA-treated cells versus control siRNA-treated cells while treatment with CHK2 siRNA resulted in no change compared to controls. CHK1 was further targeted with specific small molecule inhibitors SB 218078 and PD 407824 in combination with gemcitabine. Results showed that treatment of MIA PaCa-2 cells with either of the CHK1 inhibitors SB 218078 or PD 407824 led to sensitization of the pancreatic cancer cells to gemcitabine. CONCLUSION: These findings demonstrate the effectiveness of synthetic lethal RNAi screening as a tool for identifying sensitizing targets to chemotherapeutic agents. These results also indicate that CHK1 could serve as a putative therapeutic target for sensitizing pancreatic cancer cells to gemcitabine.

UA62784, a novel inhibitor of centromere protein E kinesin-like protein.

Pancreatic carcinoma is the fourth leading cause of death from cancer. Novel targets and therapeutic options are needed to aid in the treatment of pancreatic cancer. The compound UA62784 is a novel fluorenone with inhibitory activity against the centromere protein E (CENP-E) kinesin-like protein. UA62784 was isolated due to its selectivity in isogenic pancreatic carcinoma cell lines with a deletion of the DPC4 gene. UA62784 causes mitotic arrest by inhibiting chromosome congression at the metaphase plate likely through inhibition of the microtubule-associated ATPase activity of CENP-E. Furthermore, CENP-E binding to kinetochores during mitosis is not affected by UA62784, suggesting that the target lies within the motor domain of CENP-E. UA62784 is a novel specific inhibitor of CENP-E and its activity suggests a potential role for antimitotic drugs in treating pancreatic carcinomas.