Signature Panel Research Articles

Biomarkers for Immunotherapy: Current Developments and Challenges.

Immunotherapy has revolutionized cancer therapy and has been named the cancer advance of the year for 2016. Checkpoint inhibitors have demonstrated unprecedented rates of durable responses in some of the most difficult-to-treat cancers; however, many treated patients do not respond, and the potential for serious side effects exists. There is a growing need to identify biomarkers that will improve the selection of patients who will best respond to therapy, further elucidate drug mechanisms of action, and help tailor therapy regimens. Biomarkers are being explored at the soluble, cellular, and genomic levels, and examples in immunotherapy include serum proteins, tumor-specific receptor expression patterns, factors in the tumor microenvironment, circulating immune and tumor cells, and host genomic factors. The search for reliable biomarkers is limited by our incomplete understanding of how immunotherapies modify the already complex immune response to cancer, as well as the contribution of immuno-editing to a dynamic and inducible tumor microenvironment and immune milieu. Furthermore, there has been little extension of any candidate assay into large, prospective studies, and the lack of standardization in measurement and interpretation restricts their validity. Both tumor-infiltrating lymphocytes and PD-L1 expression within the tumor microenvironment have been recognized as having both prognostic and predictive value for patients treated with immunotherapy. Alternately, a larger panel of gene signatures, chemokines, and other factors that correlate with response has been proposed. In this article, we will explore the status of current biomarker candidates.

Biomarkers for Immunotherapy: Current Developments and Challenges

Immunotherapy has revolutionized cancer therapy and has been named the cancer advance of the year for 2016. Checkpoint inhibitors have demonstrated unprecedented rates of durable responses in some of the most difficult-to-treat cancers; however, many treated patients do not respond, and the potential for serious side effects exists. There is a growing need to identify biomarkers that will improve the selection of patients who will best respond to therapy, further elucidate drug mechanisms of action, and help tailor therapy regimens. Biomarkers are being explored at the soluble, cellular, and genomic levels, and examples in immunotherapy include serum proteins, tumor-specific receptor expression patterns, factors in the tumor microenvironment, circulating immune and tumor cells, and host genomic factors. The search for reliable biomarkers is limited by our incomplete understanding of how immunotherapies modify the already complex immune response to cancer, as well as the contribution of immuno-editing to a dynamic and inducible tumor microenvironment and immune milieu. Furthermore, there has been little extension of any candidate assay into large, prospective studies, and the lack of standardization in measurement and interpretation restricts their validity. Both tumor-infiltrating lymphocytes and PD-L1 expression within the tumor microenvironment have been recognized as having both prognostic and predictive value for patients treated with immunotherapy. Alternately, a larger panel of gene signatures, chemokines, and other factors that correlate with response has been proposed. In this article, we will explore the status of current biomarker candidates.

Ataxin-10 is part of a cachexokine cocktail triggering cardiac metabolic dysfunction in cancer cachexia

ObjectivesCancer cachexia affects the majority of tumor patients and significantly contributes to high mortality rates in these subjects. Despite its clinical importance, the identity of tumor-borne signals and their impact on specific peripheral organ systems, particularly the heart, remain mostly unknown.Methods and resultsBy combining differential colon cancer cell secretome profiling with large-scale cardiomyocyte phenotyping, we identified a signature panel of seven “cachexokines”, including Bridging integrator 1, Syntaxin 7, Multiple inositol-polyphosphate phosphatase 1, Glucosidase alpha acid, Chemokine ligand 2, Adamts like 4, and Ataxin-10, which were both sufficient and necessary to trigger cardiac atrophy and aberrant fatty acid metabolism in cardiomyocytes. As a prototypical example, engineered secretion of Ataxin-10 from non-cachexia-inducing cells was sufficient to induce cachexia phenotypes in cardiomyocytes, correlating with elevated Ataxin-10 serum levels in murine and human cancer cachexia models.ConclusionsAs Ataxin-10 serum levels were also found to be elevated in human cachectic cancer patients, the identification of Ataxin-10 as part of a cachexokine cocktail now provides a rational approach towards personalized predictive, diagnostic and therapeutic measures in cancer cachexia.

A qPCR ScoreCard quantifies the differentiation potential of human pluripotent stem cells.

Research on human pluripotent stem cells has been hampered by the lack of a standardized, quantitative, scalable assay of pluripotency. We have previously described an assay called ScoreCard that used gene expression signatures to quantify differentiation efficiency. Here we report an improved version of the assay based on qPCR that enables faster, more quantitative assessment of functional pluripotency. We provide an in-depth characterization of the revised signature panel through embryoid body and directed differentiation experiments as well as a detailed comparison to the teratoma assay. We also show that the improved ScoreCard enables applications such as screening of small molecules, genetic perturbations and assessment of culture conditions. Beyond stem cell applications, this approach can in principle be extended to other cell types and lineages.

Molecular portraits revealing the heterogeneity of breast tumor subtypes defined using immunohistochemistry markers.

Breast cancer is highly heterogeneous. The subtypes defined using immunohistochemistry markers and gene expression profilings (GEP) are related but not equivalent, with inter-connections under investigated. Our previous study revealed a set of differentially expressed genes (diff-genes), containing 1015 mRNAs and 69 miRNAs, which characterize the immunohistochemistry-defined breast tumor subtypes at the GEP level. However, they may convey redundant information due to the large amount of genes included. By reducing the dimension of the diff-genes, we identified 119 mRNAs and 20 miRNAs best explaining breast tumor heterogeneity with the most succinct number of genes found using hierarchical clustering and nearest-to-center principle. The final signature panel contains 119 mRNAs, whose superiority over diff-genes was replicated in two independent public datasets. The comparison of our signature with two pioneering signatures, the Sorlie’s signature and PAM50, suggests a novel marker, FOXA1, in breast cancer classification. Subtype-specific feature genes are reported to characterize each immunohistochemistry-defined subgroup. Pathway and network analysis reveal the critical roles of Notch signalings in [ER+|PR+]HER2− and cell cycle in [ER+|PR+]HER2+ tumors. Our study reveals the primary differences among the four immunohistochemistry-defined breast tumors at the mRNA and miRNA levels, and proposes a novel signature for breast tumor subtyping given GEP data.

Abstract 531: lncRNA profiling and its potential usage as thyroid cancer biomarker

Abstract Thyroid nodules are detected in as high as 67% of the population. Distinguishing thyroid cancers from benign lesions is crucial for determining appropriate and timely treatment. Fast and accurate detection using a simple screening method could greatly contribute to minimizing unnecessary surgery while increasing the accuracy of cancer detection. Several long non-coding RNAs (lncRNAs) have been linked to cancer development as either oncogenes or tumor suppressors, and their potential use as cancer biomarkers has been suggested. Unfortunately, limited analyses have been performed on the expression of lncRNA in thyroid cancer. Here, we explored the possible use of lncRNA as a specific thyroid cancer biomarker. The expression of 84 human cancer-related lncRNAs were evaluated in RNA samples from 9 thyroid cancer (PTC and FVPTC) patients and 13 non-cancer controls (NH and FA) with a simple real-time RT-PCR strategy. PTCSC1, an lncRNA previously linked to thyroid cancer, was found to be down regulated in patient 3.4 fold (p<0.005). In addition, we observed dysregulation of other lncRNA such as BANCR (down 3 fold, p<0.005) and SNHG16 (down 2 fold, p<0.005). We next used the lncRNA expression data for signature panel development to classify benign and malignant thyroid patient tissue samples. With a random forest classification model, a fine tuned classification signature of 16 target genes was reasonably successful (Accuracy 95%, sensitivity 92%, PPV = 90% and NPV = 100%). Our results suggested that in addition to the role that lncRNA plays in thyroid cancer, analysis of lncRNA expression represents a promising path towards a simple test for thyroid cancer detection. Citation Format: Song Tian, Samuel Rulli, Thomas J. Fahey, Eric Lader. lncRNA profiling and its potential usage as thyroid cancer biomarker. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 531. doi:10.1158/1538-7445.AM2015-531

MP68-15 LYMPH NODE STROMAL CELLS PROMOTE HIGH GRADE UROTHELIAL CELL CARCINOMA CANCER IMPLANTATION, GROWTH, ANGIOGENESIS, AND METASTASIS IN AN ORTHOTOPIC PATIENT-DERIVED XENOGRAFT MODEL

INTRODUCTION AND OBJECTIVES: Extracellular vesicles (EV) are small membrane vesicles secreted by most cell types. They are first found in reticulocytes and play important roles in cell-to-cell communication. Recent studies suggest that EV secreted by tumor cells containing tumor specific proteins and miRNAs. Previous study shows that EV purified from muscle invasive bladder cancer promote cancer progression. This study aims to characterize the genetic contents, such as proteins and nucleic acids and establish the bladder cancer specific EV biomarkers METHODS: EV were purified from bladder cancers, immortalized bladder cells, and urine of healthy volunteers and muscle invasive bladder cancer patients. The protein contents were analyzed by mass spectrometry. To prioritize the proteins of interest, we performed gene expression profile analysis of proteins via public microarray repositories from NCBI Gene Expression Omnibus profile #GDS1479 (carcinoma in situ lesions of the urinary bladder) that consists of 5 categories: normal urothelium, Non-muscle invasive BC with cancer in situ (CIS), superficial TCC without CIS, Muscle invasive bladder cancer, and CIS. In addition to protein, we also performed miRNA expression profiling microarray on EV from high grade bladder cancer cells, and immortalized bladder cells (LC Sciences). RESULTS: More than 400 proteins were found in bladder EV. Among them, we found 9 cancer-associated EV proteins that are particularly interesting because their gene expression levels are significantly elevated in cancer stages as compared to normal urothelium. Those proteins are subjected to further functional characterization via gene knockdown/overexpression strategies. The differences in miRNA expression were compared and differences were determined by a student T test (P<0.05). Results showed significant difference miRNAs between cancer cells vs normal cells. Some of cancer-specific miRNAs which have shown to play critical roles in tumorigenesis and cancer progression will be study priority CONCLUSIONS: Our study enables us to establish a panel of EV protein and miRNA signatures that can be further developed into a urine-based method for rapid detection of stage-specific biomarkers which will be valuable for detecting and managing bladder cancer.

Spontaneous Preterm Delivery, Particularly with Reduced Fetal Growth, is Associated with DNA Hypomethylation of Tumor Related Genes.

BackgroundPreterm delivery and sub-optimal fetal growth are associated with each other and affect both mother and infant. Our aim was to determine (i) whether there are detectable differences in DNA methylation between early and late gestation and (ii) whether changes in DNA methylation from entry are associated with spontaneous preterm delivery with and without reduced fetal growth.MethodsWe conducted a case-control study nested within a large prospective cohort. Gene specific methylation was measured by Methyl-Profiler PCR Array in a Human Breast Cancer Signature Panel of 24 genes from maternal peripheral leukocytes genomic DNA at entry and 3rd trimester (sampled at 16 and 30 weeks of gestation, respectively). Clonal bisulfite DNA sequencing was performed to confirm the changes in selected genes (CYP1B1, GADD45A and CXCL12). Multivariable analysis was used for data analysis.ResultsThere was significantly decrease in DNA methylation in 15 of 24 genes during the 3rd trimester in cases of spontaneous preterm delivery (n=23) as compared to the controls (n=19) (p<0.05–p<0.01 for each gene). Similar results were observed by bisulfite sequencing for 3 genes. The change in DNA methylation between late and early gestation was significantly different in cases (overall decrease in methylation was −4.0 ± 1.5%) compared to the controls (overall increase in methylation was 12.6 ± 2.19%, p<0.0001). A graded pattern of DNA methylation was observed in 15 genes. Cases who delivered preterm with reduced fetal growth had the lowest level of methylation, cases delivering preterm without reduced fetal growth were next and term controls were highest in methylation (p for trend <0.05 to p<0.01 for each gene). Cases of preterm delivery also had significantly lower dietary choline intake.ConclusionsThese data suggest that epigenetic modification is associated with an increased risk of spontaneous preterm delivery, spontaneous preterm delivery with reduced fetal growth in particular.

A pilot study to develop a diagnostic test for pancreatic ductal adenocarcinoma based on differential expression of select miRNA in plasma and bile.

OBJECTIVES:Accurate peripheral markers for the diagnosis of pancreatic ductal adenocarcinoma (PDAC) are lacking. We measured the differential expression of select microRNAs (miRNAs) in plasma and bile among patients with PDAC, chronic pancreatitis (CP), and controls.METHODS:We identified patients (n=215) with treatment-naive PDAC (n=77), CP with bile/pancreatic duct pathology (n=67), and controls (n=71) who had been prospectively enrolled in a Pancreatobiliary Biorepository at the time of endoscopic retrograde cholangiopancreatography or endoscopic ultrasound. Controls were patients with choledocholithiasis but normal pancreata. The sample was separated into training (n=95) and validation (n=120) cohorts to establish and then test the performance of PDAC Signature Panels in diagnosing PDAC. The training cohort (n=95) included age-matched patients with PDAC, CP, and controls. Panels were derived from the differential expression of 10 candidate miRNAs in plasma or bile. We selected miRNAs having excellent accuracy for inclusion in regression models.RESULTS:Using the training cohort, we confirmed the differential expression of 9/10 miRNAs in plasma (miR-10b, -30c, -106b, -132, -155, -181a, -181b, -196a, and -212) and 7/10 in bile (excluding miR-21, -132, and -181b). Of these, five (miR-10b, -155, -106b, -30c, and -212) had excellent accuracy for distinguishing PDAC. In the training and validation cohorts, the sensitivity/specificity for a PDAC Panel derived from plasma was 95/100% and 100/100%, respectively; in bile, these were 96/100% and 100/100%.CONCLUSIONS:Increased expression of miRNA-10b, -155, and -106b in plasma appears highly accurate in diagnosing PDAC. Additional studies are needed to confirm this Panel and explore its value as a prognostic test.

A preoperative serum signature of CEA+/CA125+/CA19-9 ≥ 1000 U/mL indicates poor outcome to pancreatectomy for pancreatic cancer.

Pancreatectomy is associated with significant morbidity and unpredictable outcome, with few diagnostic tools to determine, which patients gain the most benefit from this treatment, especially before the operation. This study aimed to define a preoperative signature panel of serum markers to indicate response to pancreatectomy for pancreatic cancer. Over 1000 patients with pancreatic cancer treated at two independent high-volume institutions were included in this study and were divided into three groups, including resected, locally advanced and metastatic. Eight serum tumor markers most commonly used in gastrointestinal cancers were analyzed for patient outcome. Preoperative CA19-9 independently indicated surgical response in pancreatic cancer. Patients with CA19-9 ≥1000 U/mL generally had a poor surgical benefit. However, a subset of these patients still achieved a survival advantage when CA19-9 levels decreased postoperatively. CEA and CA125 in the presence of CA19-9 ≥1000 U/mL could independently predict the non-decrease of CA19-9 postoperatively. The combination of the three markers was useful for predicting a worse surgical outcome with a median survival of 5.1 months vs. 23.0 months (p < 0.001) for the training cohort and 7.0 months vs. 18.2 months (p < 0.001) for the validation cohort and also suggested a higher prevalence of early distant metastasis after surgery. Resected patients with this proposed signature showed no survival advantage over patients in the locally advanced group who did not receive pancreatectomy. Therefore, a preoperative serum signature of CEA(+)/CA125(+)/CA19-9 ≥1000 U/mL is associated with poor surgical outcome and can be used to select appropriate patients with pancreatic cancer for pancreatectomy.

Evaluation of novel diagnostic and prognostic miRNA signatures in triple negative breast cancer

Introduction: We focus on the expression analysis of non-coding microRNAs (miRNAs) with regulatory functions in breast cancer (BC), especially on the intrinsic subgroup characterized as triple negative (TNBC). Objective of the interdisciplinary collaboration is the establishment of a distinct miRNA signature panel as a diagnostic and prognostic tool in TNBC management.

Global Transcriptome Analysis of Formalin-Fixed Prostate Cancer Specimens Identifies Biomarkers of Disease Recurrence

Prostate cancer remains the second leading cause of cancer death in American men and there is an unmet need for biomarkers to identify patients with aggressive disease. In an effort to identify biomarkers of recurrence, we performed global RNA sequencing on 106 formalin-fixed, paraffin-embedded prostatectomy samples from 100 patients at three independent sites, defining a 24-gene signature panel. The 24 genes in this panel function in cell-cycle progression, angiogenesis, hypoxia, apoptosis, PI3K signaling, steroid metabolism, translation, chromatin modification, and transcription. Sixteen genes have been associated with cancer, with five specifically associated with prostate cancer (BTG2, IGFBP3, SIRT1, MXI1, and FDPS). Validation was performed on an independent publicly available dataset of 140 patients, where the new signature panel outperformed markers published previously in terms of predicting biochemical recurrence. Our work also identified differences in gene expression between Gleason pattern 4 + 3 and 3 + 4 tumors, including several genes involved in the epithelial-to-mesenchymal transition and developmental pathways. Overall, this study defines a novel biomarker panel that has the potential to improve the clinical management of prostate cancer.

Abstract S4-01: An integrated genomics approach identifies novel drivers of oncogenic pathway activity in human breast cancer

Abstract Background: Breast cancer is not a single disease, but rather is a collection of unique diseases with distinct molecular mechanisms and clinical characteristics. Although substantial progress has been made in the development and directed administration of new cancer therapies, the reality is that most patients with advanced tumors will succumb to their disease. Since recent studies have suggested that the activity of altered oncogenic pathways may be an important determinant of the biology of the tumor and potential response to therapy, identifying mechanisms driving key oncogenic pathways is paramount to understanding the transformation process and ultimately enabling the development of therapeutic regimens that can match the complexity of a given patient's tumor. Methods: A series of gene expression signatures (n = 52) that measure oncogenic pathway activity in human breast tumors were utilized as a conceptual framework to integrate genome-wide level expression and DNA copy number data in order to identify genetic drivers of oncogenic pathway activity. Results: A panel of pathway-based gene expression signatures was applied to a collection of nearly 500 breast tumor samples from the TCGA project. In addition to expression data, each tumor had matched DNA copy number data that were used to identify chromosomal alterations associated with each pathway signature. This strategy was validated by identifying associations between pathway activity and copy number alterations (CNA) of core pathway components including the correlation between ERBB2, cMYC, and E2F1 amplification and the Her2, Myc, and E2F1 signatures, respectively. These results were further confirmed by analyzing Reverse Phase Protein Array (RPPA) data to identify functional activation of the pathway as illustrated by changes in protein expression including increased phosphorylated (p) AKT, Myc and pEGFR relative to the PI3K, Myc, and EGFR signatures, respectively. Finally, to identify those amplified genes that are essential for cell viability in a pathway-dependent manner, we analyzed a dataset of breast cancer cell lines with available mRNA expression and genome-wide shRNA proliferation data. By integrating DNA copy number and shRNA analyses, we identified SOX4 as a novel regulator of PI3K signaling in basal-like breast cancers. We determined that SOX4 is amplified in approximately 40% of basal-like breast tumors with high PI3K signaling, which is comparable to the frequency of PIK3CA or PTEN alterations. By analyzing RPPA data, we demonstrate that tumors with SOX4 amplification have increased expression of core PI3K protein components including pAKT, thus further confirming the association between SOX4 amplification and aberrant PI3K/AKT signaling. Conclusions: In this study, we used a panel of pathway-based gene expression signatures as a means to integrate four disparate forms of genomic data to identify drivers of oncogenic pathway activity, including SOX4 amplification as a novel modulator of PI3K signaling in basal-like breast cancers. This novel strategy is able to identify oncogenic events in a context specific manner, which is essential for understanding mechanisms driving tumorigenesis and for the development of personalized therapeutic strategies. Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr S4-01.

Novel approaches for the identification of biomarkers of aggressive prostate cancer

The ability to distinguish indolent from aggressive prostate tumors remains one of the greatest challenges in the management of this disease. Ongoing efforts to establish a panel of molecular signatures, comprising gene expression profiles, proteins, epigenetic patterns, or a combination of these alterations, are being propelled by rapid advancements in 'omics' technologies. The identification of such biomarkers in biological fluids is an especially attractive goal for clinical applications. Here, we summarize recent progress in the identification of candidate prognostic biomarkers of prostate cancer using biological fluid samples.

The Distinctive MicroRNA Signature of Acute Myeloid Leukemia with Translocation t(8;16)(p11;p13)/MYST3-CREBBP Is Responsible for RET Overexpression and Is Regulated by Epigenetic Mechanisms

Abstract 2434 IntroductionAcute myeloid leukemia (AML) with t(8;16)(p11;p13) and MYST3-CREBBP rearrangement [t(8;16) AML] is an infrequent leukemia subtype with specific clinical and biological characteristics including a specific gene expression profile with overexpression of RET protooncogene. Our group has previously described a specific signature of microRNAs (miRNAs), most of which were downregulated, and found an inverse correlation between RET mRNA expression and the expression of several of these miRNAs. Since MYST3 and CREBBP are chromatin-modifying proteins, we have now investigated the role of epigenetic mechanisms in the downregulation of the miRNAs in our signature and examined RET as a potential target of some of these miRNAs. MethodsTo analyze the possible epigenetic regulation of microRNA signature of t(8;16) AML, we first selected those miRNA genes with CpG islands in the promoter regions according to UCSC Genome Browser (http://genome.ucsc.edu). Changes in the expression of selected miRNA levels were studied in cryopreserved cells from a t(8;16) AML patient and in the K562 cell line after treatment for 72 hours with demethylating agent 5-aza-2'-deoxycytidine (5-aza-dC, decitabine) and histone deacetylase inhibitor trichostatin A (TSA). Expression of selected miRNAs after treatment with 5-aza-dC and TSA was analyzed using TaqMan MicroRNA Assays (Applied Biosystems). In addition, the degree of quantitative methylation in the promoter region of these miRNA genes was measured with Human Cancer miRNA Genes, Signature Panel Methyl-Profiler DNA Methylation PCR Array (Qiagen). For the validation of RET as the target of specific miRNAs, we performed a Renilla/Luciferase assay with a modified expression vector psiCHECK-2 containing the 3'UTR region of RET cloned in the 3'UTR region of Renilla gene. Modulation of RET expression by selected miRNAs was analyzed after transfection of the corresponding pre-miRNAs in the K-562 cell line, and luminescence was read at 24 hours. ResultsSince methylation is a common mechanism of the regulation of miRNA expression, we performed a bioinformatic analysis which showed that 40% of the miRNAs in our t(8;16) AML signature harbored CpG islands in their promoter gene region, making them susceptible to silencing by methylation. After treatment with 5-AZA-dc, 60% of these miRNAs were re-expressed more than two fold-change. Interestingly, TSA induced a greater re-expression in 75% of these miRNAs. The degree of methylation status was analyzed in 8 of these miRNAs using the DNA methylation PCR Array. CpG hypermethylation was present to a certain degree in three miRNAs (22% in let-7g, 29% in miR-1, and 56% in miR-126) and to a greater extent (99%) in the miR-23b cluster, which comprises miR-23b, miR-24 and miR-27b.Due to the strong inverse correlation of several miRNAs of the t(8;16) AML signature and RET mRNA levels, we then focused on miRNA target validation of RET. The analysis of the 3’UTR region of RET with TargetScan v5.1 revealed the presence of target sites for 9 miRNAs of the signature (miR-15b, miR-195, miR-218, miR-15a, miR-34a, miR-424, miR-128, and miR-27a/b), including 2 putative binding sites for miR-218. The Renilla/Luciferase assay, performed with the modified psicheck2 vector containing the 3’UTR of the RET gene, showed that 6 of these 9 miRNAs (miR-218, miR-128, miR-27b, miR-15a, miR-195, and miR-424) produced a significant downregulation of Renilla translation (41–49%), confirming our hypothesis that RET is a target of some of the miRNAs of our t(8;16) AML signature. Interestingly, 4 of the miRNAs targeting RET (miR-218, miR-27b, miR-15a and miR-424) were re-expressed after treatment with 5-AZA-dc and TSA. ConclusionsOur findings provide greater insight into the genetic and epigenetic abnormalities in t(8;16) AML. Here we have shown that our t(8,16) AML-specific miRNA signature could be a functional consequence of impaired epigenetic mechanisms, including hypermethylation and abnormal histone acetylation. In addition, we provide the first validation of RET as a target of several miRNAs in this t(8;16) AML miRNA signature. Disclosures:No relevant conflicts of interest to declare.

A RNA signature with high sensitivity and specificity discriminating between responder and nonresponder to cetuximab monotherapy in colorectal cancer.

e14049 Background: Patients (pts) with advanced, metastatic colorectal cancer (CRC) and wild-type KRAS mutation status benefit from anti EGFR antibodies cetuximab (CE) and panitumumab. Pts with CRC of UICC stage III do not benefit from CE plus FOLFOX irrespectively of the KRAS mutation status. There is a high medical need for new biomarkers that can differentiate between responder (R) and non-responder (NR) to CE therapy in the adjuvant setting. Methods: We established a panel of 148 stable, passagable CRC xenografts from 240 primary CRC tumors of all four stages (Becker et al. EORTC-NCI-AACR meeting, Berlin Nov. 2010). All xenografts were characterized by histological and molecular methods including Affymetrix array profiling and KRAS, BRAF, PIK3CA mutation analysis. Pharmacological experiments were carried out with 68 models (8 stage I, 22 stage II, 29 stage III, 9 stage IV tumors) testing therapy response to CE. In the CE group 18/68 animals responded to treatment of 50mg/kg/d given over 14 days. T/C <20 responders, T/C>20 non-responder. We isolated RNA from all 18 R and 18 NR control tumors. Labeled and amplified cDNAs (Ambion) was hybridized onto Affymetrix U133 Plus 2.0 arrays. Raw cel files were condensed (FARMS). Feature selection and classification was performed using the random forest algorithm and SVM in a nested bootstrap approach. Results: We identified a panel of signatures containing between 20 to 300 RNA markers discriminating between R and NR. The best signature containing 300 probesets showed a prospective sensitivity (S+) of 82.78% and a prospective specificity (S-) of 84.0%. A signature of 21 probesets has a S+ of 79% and a S- of 77.78%. We also assigned the response data of the mouse models to the original human tumors and developed corresponding RNA signatures that discriminated successfully the two human tumor groups and proving our model. Conclusions: We have developed highly accurate RNA signatures predicting response to CE in xenograft models carrying human CRC tumors of all four stages. This signature, if successfully validated in a larger cohort, could be applied to pts with CRC stage II and III for predicting response to CE with a PPV of 64% and a NPV of 93%.

Abstract 3210: Profiling of DNA methylation signature for different phases of prostate cancer development

Abstract Prostate cancer is the third most common cancer in Singaporean men. Compared to Western countries, the prostate cancer incidence is lower in Asian countries but recent data suggest that incidence is increasing, especially in rapidly urbanized countries. Recent studies provide evidence that methylated genes can be useful and promising molecular biomarkers for detection of prostate cancers. The aim of our study is to identify a panel of global gene methylation signatures that are unique and specific for different phases of prostate cancer development and different prostate cancer phenotypes. This may thus differentiate cancers from non-cancers, and aggressive cancers from indolent ones. We have profiled methylation of genes using the Illumina's GoldenGate Methylation System. The Standard GoldenGate Methylation Cancer Panel I (Illumina Inc, San Diego, CA) spans 1,505 CpG loci selected from 807 genes that have been shown in literature to play important roles in cancer. Methylation levels of candidate genes were quantified in 28 benign tissues without prostate cancer, 52 tissues of Gleason score 3+3, 66 tissues of Gleason score 4+x and 37 tissues of Gleason score 5+x. DNA used for the assays were obtained from laser capture microdissected paraffin embedded archival tissues. Interestingly, our results showed that 28 different CpG loci were methylated in Gleason 3+3 prostate cancer tissues compared to benign prostatic hyperplasia tissues that were used as controls. In addition, methylation levels in prostate cancer samples of high Gleason index (4+x and 5+x) were significantly higher than the paired prostate cancer samples of low Gleason index (3+3) in at least 10 candidate genes. These genes include VIM (p-value 3.59E-08), ASCL2 (p-value 1.71E-09), DAB2IP (p-value 6.55E-08) and FRZB (p-value 6.44E-08). Together with bioinformatics and quantitative methylation-specific PCR, we identified a set of potentially phenotype-specific gene methylation signatures in Asian men. Our studies contributed to the improvement of diagnostic capability for prostate cancer beyond available tumour markers such as PSA as it is a more sensitive molecular correlate. 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 3210. doi:10.1158/1538-7445.AM2011-3210

A Migration Signature and Plasma Biomarker Panel for Pancreatic Adenocarcinoma

Pancreatic ductal adenocarcinoma is a disease of extremely poor prognosis for which there are no reliable markers of asymptomatic disease. To identify pancreatic cancer biomarkers, we focused on a genomic interval proximal to the most common fragile site in the human genome, chromosome 3p12, which undergoes smoking-related breakage, loss of heterozygosity, and homozygous deletion as an early event in many epithelial tumors, including pancreatic cancers. Using a functional genomic approach, we identified a seven-gene panel (TNC, TFPI, TGFBI, SEL-1L, L1CAM, WWTR1, and CDC42BPA) that was differentially expressed across three different expression platforms, including pancreatic tumor/normal samples. In addition, Ingenuity Pathways Analysis (IPA) and literature searches indicated that this seven-gene panel functions in one network associated with cellular movement/morphology/development, indicative of a "migration signature" of the 3p pathway. We tested whether two secreted proteins from this panel, tenascin C (TNC) and tissue factor pathway inhibitor (TFPI), could serve as plasma biomarkers. Plasma ELISA assays for TFPI/TNC resulted in a combined area under the curve (AUC) of 0.88 and, with addition of CA19-9, a combined AUC for the three-gene panel (TNC/TFPI/CA19-9), of 0.99 with 100% specificity at 90% sensitivity and 97.22% sensitivity at 90% specificity. Validation studies using TFPI only in a blinded sample set increased the performance of CA19-9 from an AUC of 0.84 to 0.94 with the two-gene panel. Results identify a novel 3p pathway-associated migration signature and plasma biomarker panel that has utility for discrimination of pancreatic cancer from normal controls and promise for clinical application.

Profiling the human response to physical exercise: a computational strategy for the identification and kinetic analysis of metabolic biomarkers

BackgroundIn metabolomics, biomarker discovery is a highly data driven process and requires sophisticated computational methods for the search and prioritization of novel and unforeseen biomarkers in data, typically gathered in preclinical or clinical studies. In particular, the discovery of biomarker candidates from longitudinal cohort studies is crucial for kinetic analysis to better understand complex metabolic processes in the organism during physical activity.FindingsIn this work we introduce a novel computational strategy that allows to identify and study kinetic changes of putative biomarkers using targeted MS/MS profiling data from time series cohort studies or other cross-over designs. We propose a prioritization model with the objective of classifying biomarker candidates according to their discriminatory ability and couple this discovery step with a novel network-based approach to visualize, review and interpret key metabolites and their dynamic interactions within the network. The application of our method on longitudinal stress test data revealed a panel of metabolic signatures, i.e., lactate, alanine, glycine and the short-chain fatty acids C2 and C3 in trained and physically fit persons during bicycle exercise.ConclusionsWe propose a new computational method for the discovery of new signatures in dynamic metabolic profiling data which revealed known and unexpected candidate biomarkers in physical activity. Many of them could be verified and confirmed by literature. Our computational approach is freely available as R package termed BiomarkeR under LGPL via CRAN http://cran.r-project.org/web/packages/BiomarkeR/.

Highlights from Recent Cancer Literature

Highlights from Recent Cancer Literature