Meredith C. Henderson

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

BackgroundPancreatic 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.MethodsIn 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.ResultsResults 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.ConclusionThese 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.

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. Mol Cancer Res; 9(6); 724–32. ©2011 AACR.

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.

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.

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. Micro‐Abstract: To improve breast cancer diagnosis, 2 prospective clinical trials were conducted to test (n = 351) and validate (n = 210) Videssa Breast. If used in conjunction with imaging, Videssa Breast could have reduced unnecessary biopsies by up to 67%. These results support the joint use of breast imaging and Videssa Breast to better inform clinical decisions for women under age 50.

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.

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.

Abstract P4-01-07: A liquid biopsy test for breast cancer detection provides consistent diagnostic results in patients over six months

Current methods of breast cancer detection are often confounded by imaging limitations, such as lesion size, benign breast tissue, and dense breasts. These limitations result in unnecessary biopsies due to false positive findings based on imaging. Despite the increased ability to detect early breast cancer, the over-use of biopsy remains an issue. There is a critical need for new approaches to breast cancer detection that improve diagnostic accuracy when clinical assessment is challenging. Provista Diagnostics has developed Videssa® Breast - a blood-based proteomic test that measures serum protein biomarkers (SPBs) and tumor-associated autoantibodies (TAAbs). Patient biochemical data is combined with clinical data to generate a diagnostic score that correlates with either the absence or presence of breast cancer (Grades I through III). The ability of Videssa® breast to detect cancer (Invasive Breast Cancer and Ductal Carcinoma in situ) was evaluated using prospective, multi-center clinical trials. The Provista-001 study enrolled 351 women ages 25-49 and included a follow-up visit at 6 months with an additional blood draw. Eligible patients included women assessed as ACR BIRADS® 3 or 4 on imaging with no history of breast cancer or prior breast biopsy. Serum samples from the initial visit and 6 month follow-up visit of Provista-001 were analyzed using Videssa® Breast to determine if diagnostic results for benign subjects were similar over the course of the study. Samples were analyzed for SPBs and TAAbs in order to determine whether analyte levels and diagnostic scores change over a 6-month period in patients diagnosed with a benign breast condition. Linear regression data for analytes shows overall high fidelity between the initial visit and follow-up. In addition, samples that were TAAb-positive for a given target at the initial visit tended to remain positive at follow-up. Sample background, deriving from unidentified immunological factors, can confound the analytical output when measuring TAAbs in serum. Interestingly, sample background was highly reproducible between both visits, suggesting that these values are related to inherent patient-specific factors. Overall, these data demonstrate high analytical reproducibility for in expression of independent Videssa® Breast biomarkers in patients diagnosed with a benign breast condition over the course of six months. Data for 236 women were compared between visits and demonstrated greater than 80% concordance in diagnostic status. The ability of Videssa® breast to provide consistent diagnostic results over 6 months further supports use of the test as an adjunct to imaging for the early detection of breast cancer and provides physicians with an additional tool that can be used to inform the decision to biopsy or increase vigilance through active monitoring. Citation Format: Benson KL, Henderson MC, Silver M, Gordon K, Borman S, Letsios E, Tran Q, Mulpuri R, Reese DE. A liquid biopsy test for breast cancer detection provides consistent diagnostic results in patients over six months [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P4-01-07.

Abstract 4964: High-throughput genomic analysis of platinum and taxane resistance in ovarian cancer cells

Proceedings: AACR 102nd Annual Meeting 2011‐‐ Apr 2‐6, 2011; Orlando, FL Ovarian cancer is the fifth-leading cause of death from cancer in women. The five-year survival rate for ovarian cancer remains low at approximately 45%. Ovarian cancer patients are often treated with a combination of a platinum agent plus a taxane and despite initial success, up to 75% of responders relapse within 18-28 months. We have previously utilized high-throughput siRNA screening to identify gene modulators of cisplatin resistance in ovarian cancer cell lines. Here, we identify genomic characteristics of paclitaxel-resistant and cisplatin-resistant ovarian cancer cells. Combined with our previous cisplatin-resistance studies, we hope to obtain a more complete picture of platinum/taxane resistance in ovarian cancer. We have developed a variant of the A2780 cell line (A2780-pacli) that exhibits a four-log increase in paclitaxel IC50. Array based comparative genomic hybridization (aCGH) has demonstrated a small number of focal chromosomal aberrations between the parent and isogenic derivative cell lines suggesting drug-specific evolutionary changes to the A2780 genome. We also utilized expression microarrays to identify genes that may contribute to drug-resistant phenotypes. cRNA probes generated from A2780-pacli cells or a commercial cisplatin-resistant A2780 cell line (A2780-cis) and were hybridized against cRNA from wild-type A2780 cells (A2780-WT). Differential gene expression analysis identified overlapping and individual drug-specific patterns of gene expression, including 1519 genes over- or under-expressed in both the cis- and pacli-resistant lines. Additionally, we have completed a high-throughput RNA interference (HT-RNAi) screen on A2780-pacli cells involving 572 kinase genes in order to determine mediators of paclitaxel resistance in this cell line. The HT-RNAi assay was developed to quantify the growth inhibition of A2780-pacli cells transfected with siRNA and treated with an EC50 dose of paclitaxel. Cell viability was assessed after 72 hours of drug exposure. The HT-RNAi screening data was normalized and log 2 ratios of drug-treated/vehicle-treated wells were determined to show drug potentiation. Following data analysis, we generated a list of gene targets that, upon silencing, lead to potentiation of cell viability in response to paclitaxel. Validation of these genes will identify potential therapeutic targets for novel paclitaxel combinations in order to improve clinical efficacy. These findings further demonstrate the effectiveness of using HT-RNAi as a tool for identifying sensitizing targets to chemotherapeutic agents. Taken together, the integrated application of genomic survey methods provides insight into mechanisms of drug resistance in ovarian cancer cells. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4964. doi:10.1158/1538-7445.AM2011-4964