Timothy Davison

Development and Independent Validation of a Prognostic Assay for Stage II Colon Cancer Using Formalin-Fixed Paraffin-Embedded Tissue

PURPOSE Current prognostic factors are poor at identifying patients at risk of disease recurrence after surgery for stage II colon cancer. Here we describe a DNA microarray-based prognostic assay using clinically relevant formalin-fixed paraffin-embedded (FFPE) samples. PATIENTS AND METHODS A gene signature was developed from a balanced set of 73 patients with recurrent disease (high risk) and 142 patients with no recurrence (low risk) within 5 years of surgery. RESULTS The 634-probe set signature identified high-risk patients with a hazard ratio (HR) of 2.62 (P < .001) during cross validation of the training set. In an independent validation set of 144 samples, the signature identified high-risk patients with an HR of 2.53 (P < .001) for recurrence and an HR of 2.21 (P = .0084) for cancer-related death. Additionally, the signature was shown to perform independently from known prognostic factors (P < .001). CONCLUSION This gene signature represents a novel prognostic biomarker for patients with stage II colon cancer that can be applied to FFPE tumor samples.

Accurate Molecular Characterization of Formalin-Fixed, Paraffin-Embedded Tissues by microRNA Expression Profiling

Formalin-fixed, paraffin-embedded tissues are an invaluable tool for biomarker discovery and validation. As these archived specimens are not always compatible with modern genomic techniques such as gene expression arrays, we assessed the use of microRNA (miRNA) as an alternative means for the reliable molecular characterization of formalin-fixed, paraffin-embedded tissues. Expression profiling using two different microarray platforms and multiple mouse and human formalin-fixed, paraffin-embedded tissue types resulted in the correlation ratios of miRNA expression levels between frozen and fixed tissue pairs ranging from 0.82 to 0.99, depending on the cellular heterogeneity of the tissue type. The same miRNAs were identified as differentially expressed between tissues using both fixed and frozen specimens. While formalin fixation time had only marginal effects on microarray performance, extended storage times for tissue blocks (up to 11 years) resulted in a gradual loss of detection of miRNAs expressed at low levels. Method reproducibility and accuracy were also evaluated in two different tissues stored for different lengths of time. The technical variation between full process replicates, including independent RNA isolation methods, was approximately 5%, and the correlation of expression levels between microarray and real-time quantitative reverse transcriptase polymerase chain reaction was 0.98. Together, these data demonstrate that miRNA expression profiling is an accurate and robust method for the molecular analysis of archived clinical specimens, potentially extending the use of miRNAs as new diagnostic, prognostic, and treatment response biomarkers.

Identification and Validation of an Anthracycline/Cyclophosphamide–Based Chemotherapy Response Assay in Breast Cancer

Background There is no method routinely used to predict response to anthracycline and cyclophosphamide–based chemotherapy in the clinic; therefore patients often receive treatment for breast cancer with no benefit. Loss of the Fanconi anemia/BRCA (FA/BRCA) DNA damage response (DDR) pathway occurs in approximately 25% of breast cancer patients through several mechanisms and results in sensitization to DNA-damaging agents. The aim of this study was to develop an assay to detect DDR-deficient tumors associated with loss of the FA/BRCA pathway, for the purpose of treatment selection. Methods DNA microarray data from 21 FA patients and 11 control subjects were analyzed to identify genetic processes associated with a deficiency in DDR. Unsupervised hierarchical clustering was then performed using 60 BRCA1/2 mutant and 47 sporadic tumor samples, and a molecular subgroup was identified that was defined by the molecular processes represented within FA patients. A 44-gene microarray-based assay (the DDR deficiency assay) was developed to prospectively identify this subgroup from formalin-fixed, paraffin-embedded samples. All statistical tests were two-sided. Results In a publicly available independent cohort of 203 patients, the assay predicted complete pathologic response vs residual disease after neoadjuvant DNA-damaging chemotherapy (5-fluorouracil, anthracycline, and cyclophosphamide) with an odds ratio of 3.96 (95% confidence interval [Cl] =1.67 to 9.41; P = .002). In a new independent cohort of 191 breast cancer patients treated with adjuvant 5-fluorouracil, epirubicin, and cyclophosphamide, a positive assay result predicted 5-year relapse-free survival with a hazard ratio of 0.37 (95% Cl = 0.15 to 0.88; P = .03) compared with the assay negative population. Conclusions A formalin-fixed, paraffin-embedded tissue-based assay has been developed and independently validated as a predictor of response and prognosis after anthracycline/cyclophosphamide–based chemotherapy in the neoadjuvant and adjuvant settings. These findings warrant further validation in a prospective clinical study.

Association Between Results of a Gene Expression Signature Assay and Recurrence-Free Interval in Patients With Stage II Colon Cancer in Cancer and Leukemia Group B 9581 (Alliance)

PURPOSE Conventional staging methods are inadequate to identify patients with stage II colon cancer (CC) who are at high risk of recurrence after surgery with curative intent. ColDx is a gene expression, microarray-based assay shown to be independently prognostic for recurrence-free interval (RFI) and overall survival in CC. The objective of this study was to further validate ColDx using formalin-fixed, paraffin-embedded specimens collected as part of the Alliance phase III trial, C9581. PATIENTS AND METHODS C9581 evaluated edrecolomab versus observation in patients with stage II CC and reported no survival benefit. Under an initial case-cohort sampling design, a randomly selected subcohort (RS) comprised 514 patients from 901 eligible patients with available tissue. Forty-nine additional patients with recurrence events were included in the analysis. Final analysis comprised 393 patients: 360 RS (58 events) and 33 non-RS events. Risk status was determined for each patient by ColDx. The Self-Prentice method was used to test the association between the resulting ColDx risk score and RFI adjusting for standard prognostic variables. RESULTS Fifty-five percent of patients (216 of 393) were classified as high risk. After adjustment for prognostic variables that included mismatch repair (MMR) deficiency, ColDx high-risk patients exhibited significantly worse RFI (multivariable hazard ratio, 2.13; 95% CI, 1.3 to 3.5; P < .01). Age and MMR status were marginally significant. RFI at 5 years for patients classified as high risk was 82% (95% CI, 79% to 85%), compared with 91% (95% CI, 89% to 93%) for patients classified as low risk. CONCLUSION ColDx is associated with RFI in the C9581 subsample in the presence of other prognostic factors, including MMR deficiency. ColDx could be incorporated with the traditional clinical markers of risk to refine patient prognosis.

Implications for Powering Biomarker Discovery Studies

This study examined variations in gene expression between FFPE blocks within tumors of individual patients. Microarray data were used to measure tumor heterogeneity within and between patients and disease states. Data were used to determine the number of samples needed to power biomarker discovery studies. Bias and variation in gene expression were assessed at the intrapatient and interpatient levels and between adenocarcinoma and squamous samples. A mixed-model analysis of variance was fitted to gene expression data and model signatures to assess the statistical significance of observed variations within and between samples and disease states. Sample size analysis, adjusted for sample heterogeneity, was used to determine the number of samples required to support biomarker discovery studies. Variation in gene expression was observed between blocks taken from a single patient. However, this variation was considerably less than differences between histological characteristics. This degree of block-to-block variation still permits biomarker discovery using either macrodissected tumors or whole FFPE sections, provided that intratumor heterogeneity is taken into account. Failure to consider intratumor heterogeneity may result in underpowered biomarker studies that may result in either the generation of longer gene signatures or the inability to identify a viable biomarker. Moreover, the results of this study indicate that a single biopsy sample is suitable for applying a biomarker in non-small-cell lung cancer.

Prior knowledge transfer across transcriptional data sets and technologies using compositional statistics yields new mislabelled ovarian cell line

Here, we describe gene expression compositional assignment (GECA), a powerful, yet simple method based on compositional statistics that can validate the transfer of prior knowledge, such as gene lists, into independent data sets, platforms and technologies. Transcriptional profiling has been used to derive gene lists that stratify patients into prognostic molecular subgroups and assess biomarker performance in the pre-clinical setting. Archived public data sets are an invaluable resource for subsequent in silico validation, though their use can lead to data integration issues. We show that GECA can be used without the need for normalising expression levels between data sets and can outperform rank-based correlation methods. To validate GECA, we demonstrate its success in the cross-platform transfer of gene lists in different domains including: bladder cancer staging, tumour site of origin and mislabelled cell lines. We also show its effectiveness in transferring an epithelial ovarian cancer prognostic gene signature across technologies, from a microarray to a next-generation sequencing setting. In a final case study, we predict the tumour site of origin and histopathology of epithelial ovarian cancer cell lines. In particular, we identify and validate the commonly-used cell line OVCAR-5 as non-ovarian, being gastrointestinal in origin. GECA is available as an open-source R package.

Model selection for prognostic time-to-event gene signature discovery with applications in early breast cancer data

Abstract Model selection between competing models is a key consideration in the discovery of prognostic multigene signatures. The use of appropriate statistical performance measures as well as verification of biological significance of the signatures is imperative to maximise the chance of external validation of the generated signatures. Current approaches in time-to-event studies often use only a single measure of performance in model selection, such as logrank test p-values, or dichotomise the follow-up times at some phase of the study to facilitate signature discovery. In this study we improve the prognostic signature discovery process through the application of the multivariate partial Cox model combined with the concordance index, hazard ratio of predictions, independence from available clinical covariates and biological enrichment as measures of signature performance. The proposed framework was applied to discover prognostic multigene signatures from early breast cancer data. The partial Cox model combined with the multiple performance measures were used in both guiding the selection of the optimal panel of prognostic genes and prediction of risk within cross validation without dichotomising the follow-up times at any stage. The signatures were successfully externally cross validated in independent breast cancer datasets, yielding a hazard ratio of 2.55 [1.44, 4.51] for the top ranking signature.

Analytical Performance of a 15-Gene Prognostic Assay for Early-Stage Non–Small-Cell Lung Carcinoma Using RNA-Stabilized Tissue

A 15-gene prognostic signature for early-stage, completely resected, non-small-cell lung carcinoma, (which distinguishes between patients with good and poor prognoses) was clinically validated in prior studies. To achieve operational efficiencies, this study was designed to evaluate the assays performance in RNA-stabilized tissue as an alternative to the fresh-frozen tissue format originally used to develop the assay. The percent concordance between matched tissue formats was 84% (95% Wilson CI, 70%-92%), a level of agreement comparable to the inherent reproducibility of the assay observed within biological replicates of fresh-frozen tissue. Furthermore, the analytical performance of the assay using the RNA-stabilized tissue format was evaluated. When compared to an accredited reference laboratory, the clinical laboratory achieved a concordance of 94% (95% Wilson CI, 81%-98%), and there was no evidence of bias between the laboratories. The lower limit of quantitation for the target RNA concentration was confirmed to be, at most, 12.5 ng/μL. The assay reportable range defined in terms of risk score units was determined to be -4.295 to 4.210. In a large-scale precision study, the assay showed high reproducibility and repeatability. When subjected to a maximal amount of genomic DNA, a potential contaminant, the assay still produced the expected results. The 15-gene signature was confirmed to produce reliable results and, thus, is suitable for its intended use.

Reply to L. Casadaban et al

We presented univariable results according to the REMARK guidelines for associations between ColDx score and prognostic factors for recurrence-free interval (RFI; Appendix Table A1 [online only] in our article). As Casadaban et al point out, ColDx is associated with T-stage and lymphovascular invasion but not the number of nodes examined, perineural invasion, or tumor grade. It is not clear why such a relationship would be expected. The assay was designed to be independent from other known prognostic clinical factors and to add new prognostic information. As Casadaban et al suggest, we considered the subgroup of high-risk patients who we defined as exhibiting any one of the following clinical characteristics: obstruction or perforation (six patients), lymphovascular invasion (42 patients), fewer than 12 nodes sampled (176 patients), or microsatellite instability low or stable (283 patients; n 5 317; 80 RFI events). RFI was then compared between highrisk patients and low-risk patients as determined by ColDx score. Results were significant at P5 .05, with a hazard ratio of 1.62 (95%CI, 0.99 to 2.68). Thus, ColDx provides further discrimination in this higher-risk subgroup. The number of events was too small to make this comparison in the low-risk subgroup. In the parent trial, Alliance C9581, investigators sought to determine whether the use of edrecolomab—a relatively nontoxic adjuvant therapy—would demonstrate an overall survival benefit in a cohort of patients with resected, stage II colon cancer that excluded patients with high-risk factors. Patients were considered disease-free postsurgery. Thus, tumor response was not a study end point. Patient samples were obtained before treatment with edrecolomab. Overall survival and disease-free survival between treated and untreated patients were essentially equivalent (Fig 2A in our article). Nonetheless, under the case-cohort design in our validation study, we randomly selected patients stratified by assigned treatment and accounted for stratification in the analysis. Overall, toxicity was low. A maximum of grade 3 toxicity was reported for 242 (29.4%) of 823 participants who reported adverse events with edrecolomab treatment, and 48 patients (5.8%) experienced a maximum grade 4 toxicity. No individual adverse event was reported in . 5% of patients, the most prevalent of which was diarrhea. One death occurred within 30 days of completing edrecolomab therapy and was not attributed to treatment. This validation study used the same primary end point on which the gene signature was developed. Among patients who were studied in the Alliance C9581 trial, we found that it is important to distinguish between disease-related death and other causes of death in this low-risk, older patient population with stage II disease. We found large differences in outcome by sex and age for all-cause mortality that were primarily caused by association of these factors with death as a result of other causes. Including deaths as a result of other causes as an event may unduly bias results. Regarding sample insufficiency, in clinical testing, the quality control fail rate that was observed for the study is not unusual considering the average age of the formalin-fixed, paraffinembedded tissue used in the validation study (average age, 13.2 years). This limitation is acknowledged in the manuscript. In addition, average quality control fail rate within fresh formalinfixed, paraffin-embedded tissue is 5%. We stated the reason for the different prognostic score cut points in our article, which was “migration of the ColDx assay from the Affymetrix GeneChip System 3000 7G scanner to the Affymetrix microarray platform GeneChip System 3000Dx v.2.” With respect to the association with lymphocyte proliferation and activation of biologic functions with recurrence-free survival in colorectal liver metastases, the validation study was performed within primary tissuematerial. Biologic signaling within metastatic tissue is inherently different from that found within primary tissue material. That said, the most significant molecular pathways measured by the ColDx assay are detailed by Kennedy et al, among which are TGF-b and chemokine signaling, and both are associated with lymphocyte proliferation and recruitment. It is not unusual that two assays, such as the 12-gene recurrence score and ColDx, have good discrimination and calibration but do not agree with one another in individual probability predictions. It is more relevant to determine which assay is better calibrated and has better discrimination—that is, which assay is better at generating estimates that are closer to observed values. We agree with Casadaban et al that further studies are needed to demonstrate the ability of the gene expression signature to predict treatment benefit. Despite its limitations, our study was prospectively planned and used specimens and clinical data from a cohesive, well-conducted clinical trial. The results demonstrate the additive prognostic value of the measure.

Abstract MIP-055: IDENTIFICATION OF A MOLECULAR SUBTYPE OF HIGH GRADE SEROUS OVARIAN CANCER REPRESENTING MAPK PATHWAY ACTIVATION AND PLATINUM RESISTANCE

BACKGROUND: We previously defined 3 molecular subgroups of High Grade Serous Ovarian Cancer (HGSOC), using gene expression data from 265 FFPE samples obtained from treatment naive patients, who received platinum based treatment following surgical resection. The 3 molecular subgroups were Angio: characterised by upregulation of angiogenesis genes; Immune: characterised by upregulation of immune genes and AngioImmune: characterised by upregulation of angiogenesis and immune genes. Patients within these 3 subgroups respond differently to standard of care treatment The Immune subgroup have the best prognosis and the Angio and AngioImmune subgroups have similar worse prognosis. A weighted gene signature to identify each of the molecular subgroups was developed. This dataset was used as a reference to investigate the effect of chemotherapy on molecular subgroup designation. METHODS: To investigate the effect of chemotherapy on predefined molecular subgroups, we analysed 35 matched pre- and post- chemotherapy samples by gene expression. The molecular subgroup assignment for each of the paired samples was determined using the gene expression signatures for each subgroup. Novel cisplatin resistant HGSOC cell lines were generated to study the mechanisms of acquired cisplatin resistance. RESULTS: 40% of the treatment naive samples that were aligned with the AngioImmune subgroup and this increased to 67.5% post-chemotherapy. 10/15 (67%) treatment naive tumours that were initially assigned to the good prognostic Immune molecular subgroup shifted to the bad prognostic AngioImmune molecular subgroup post chemotherapy. Hence platinum chemotherapy selects for the AngioImmune subgroup, suggesting that this subgroup represents tumours which are innately platinum resistant but also provides a mechanism of acquired resistance. Additionally we demonstrate that the AngioImmune subgroup is driven by activation of the MAPK pathway and shows that cisplatin resistant HGSOC cell lines are specifically sensitive to MEK inhibitors. CONCLUSIONS: The MAPK pathway is a mechanism of innate and acquired platinum resistance in HGSOC. Furthermore the data suggests that original pre-treatment surgical/biopsy samples may fall within a different molecular subgroup to samples taken post-platinum therapy. Citation Format: Aya El-Helali, Nuala McCabe, Charlie Gourley, Andrena McCavigan, Caroline O. Michie, Bethanie Price, Niamh McGivern, Michael Churchman, Aya El-Helai, Eamonn J. O9Brien, Laura Hill, Timothy S Davison, Alistair Williams, W Glenn McCluggage, Katherine E Keating, Denis P Harkin, and Richard Kennedy. IDENTIFICATION OF A MOLECULAR SUBTYPE OF HIGH GRADE SEROUS OVARIAN CANCER REPRESENTING MAPK PATHWAY ACTIVATION AND PLATINUM RESISTANCE [abstract]. In: Proceedings of the 11th Biennial Ovarian Cancer Research Symposium; Sep 12-13, 2016; Seattle, WA. Philadelphia (PA): AACR; Clin Cancer Res 2017;23(11 Suppl):Abstract nr MIP-055.