Multimodal Biomarkers That Predict the Presence of Gleason Pattern 4: Potential Impact for Active Surveillance

PURPOSE

Latent grade group ≥2 prostate cancer can impact the performance of active surveillance protocols. To date, molecular biomarkers for active surveillance have relied solely on RNA or protein. We trained and independently validated multimodal (mRNA abundance, DNA methylation, and/or DNA copy number) biomarkers that more accurately separate grade group 1 from grade group ≥2 cancers.

MATERIALS AND METHODS

Low- and intermediate-risk prostate cancer patients were assigned to training (n=333) and validation (n=202) cohorts. We profiled the abundance of 342 mRNAs, 100 DNA copy number alteration loci, and 14 hypermethylation sites at 2 locations per tumor. Using the training cohort with cross-validation, we evaluated methods for training classifiers of pathological grade group ≥2 in centrally reviewed radical prostatectomies. We trained 2 distinct classifiers, PRONTO-e and PRONTO-m, and validated them in an independent radical prostatectomy cohort.

RESULTS

PRONTO-e comprises 353 mRNA and copy number alteration features. PRONTO-m includes 94 clinical, mRNAs, copy number alterations, and methylation features at 14 and 12 loci, respectively. In independent validation, PRONTO-e and PRONTO-m predicted grade group ≥2 with respective true-positive rates of 0.81 and 0.76, and false-positive rates of 0.43 and 0.26. Both classifiers were resistant to sampling error and identified more upgrading cases than a well-validated presurgical risk calculator, CAPRA (Cancer of the Prostate Risk Assessment; P < .001).

CONCLUSIONS

Two grade group classifiers with superior accuracy were developed by incorporating RNA and DNA features and validated in an independent cohort. Upon further validation in biopsy samples, classifiers with these performance characteristics could refine selection of men for active surveillance, extending their treatment-free survival and intervals between surveillance.

A DNA copy number alteration classifier as a prognostic tool for prostate cancer patients

BACKGROUND

Distinguishing between true indolent and potentially life-threatening prostate cancer is challenging in tumours displaying clinicopathologic features associated with low or intermediate risk of relapse. Several somatic DNA copy number alterations (CNAs) have been identified as potential prognostic biomarkers, but the standard cytogenetic method to assess them has a limited multiplexing capability.

METHODS

Multiplex ligation-dependent probe amplification (MLPA) targeting 14 genes was optimised to survey 448 tumours of patients with low or intermediate risk (Grade Group 1-3, Gleason score ≤7) who underwent radical prostatectomy. A 6-gene CNA classifier was developed using random survival forest and Cox proportional hazard modelling to predict biochemical recurrence.

RESULTS

The classifier score was significantly associated with biochemical recurrence after adjusting for standard clinicopathologic variables and the known prognostic index CAPRA-S score with a hazard ratio of 2.17 and 1.80, respectively (n = 406, P < 0.01). The prognostic value of this classifier was externally validated in published CNA data from three radical prostatectomy cohorts and one radiation therapy pre-treatment biopsy cohort.

CONCLUSION

The 6-gene CNA classifier generated by a single MLPA assay compatible with the small quantities of DNA extracted from formalin-fixed paraffin-embedded (FFPE) tissue specimens has the potential to improve the clinical management of patients with low or intermediate risk disease.

Correlative studies of the Breast Cancer Index (HOXB13/IL17BR) and ER, PR, AR, AR/ER ratio and Ki67 for prediction of extended endocrine therapy benefit: a Trans-aTTom study

BACKGROUND

Multiple clinical trials demonstrate consistent but modest benefit of adjuvant extended endocrine therapy (EET) in HR + breast cancer patients. Predictive biomarkers to identify patients that benefit from EET are critical to balance modest reductions in risk against potential side effects of EET. This study compares the performance of the Breast Cancer Index, BCI (HOXB13/IL17BR, H/I), with expression of estrogen (ER), progesterone (PR), and androgen receptors (AR), and Ki67, for prediction of EET benefit.

METHODS

Node-positive (N+) patients from the Trans-aTTom study with available tissue specimen and BCI results (N = 789) were included. Expression of ER, PR, AR, and Ki67 was assessed by quantitative immunohistochemistry. BCI (H/I) gene expression analysis was conducted by quantitative RT-PCR. Statistical significance of the treatment by biomarker interaction was evaluated by likelihood ratio tests based on multivariate Cox proportional models, adjusting for age, tumor size, grade, and HER2 status. Pearson's correlation coefficients were calculated to evaluate correlations between BCI (H/I) versus ER, PR, AR, Ki67 and AR/ER ratio.

RESULTS

EET benefit, measured by the difference in risk of recurrence between patients treated with tamoxifen for 10 versus 5 years, is significantly associated with increasing values of BCI (H/I) (interaction P = 0.01). In contrast, expression of ER (P = 0.83), PR (P = 0.66), AR (P = 0.78), Ki67 (P = 0.87) and AR/ER ratio (P = 0.84) exhibited no significant relationship with EET benefit. BCI (H/I) showed a very weak negative correlation with ER (r = - 0.18), PR (r = - 0.25), and AR (r = - 0.14) expression, but no correlation with either Ki67 (r = 0.04) or AR/ER ratio (r = 0.02).

CONCLUSION

These findings are consistent with the growing body of evidence that BCI (H/I) is significantly predictive of response to EET and outcome. Results from this direct comparison demonstrate that expression of ER, PR, AR, Ki67 or AR/ER ratio are not predictive of benefit from EET. BCI (H/I) is the only clinically validated biomarker that predicts EET benefit.

Systematically higher Ki67 scores on core biopsy samples compared to corresponding resection specimen in breast cancer: a multi-operator and multi-institutional study

Ki67 has potential clinical importance in breast cancer but has yet to see broad acceptance due to inter-laboratory variability. Here we tested an open source and calibrated automated digital image analysis (DIA) platform to: (i) investigate the comparability of Ki67 measurement across corresponding core biopsy and resection specimen cases, and (ii) assess section to section differences in Ki67 scoring. Two sets of 60 previously stained slides containing 30 core-cut biopsy and 30 corresponding resection specimens from 30 estrogen receptor-positive breast cancer patients were sent to 17 participating labs for automated assessment of average Ki67 expression. The blocks were centrally cut and immunohistochemically (IHC) stained for Ki67 (MIB-1 antibody). The QuPath platform was used to evaluate tumoral Ki67 expression. Calibration of the DIA method was performed as in published studies. A guideline for building an automated Ki67 scoring algorithm was sent to participating labs. Very high correlation and no systematic error (p = 0.08) was found between consecutive Ki67 IHC sections. Ki67 scores were higher for core biopsy slides compared to paired whole sections from resections (p ≤ 0.001; median difference: 5.31%). The systematic discrepancy between core biopsy and corresponding whole sections was likely due to pre-analytical factors (tissue handling, fixation). Therefore, Ki67 IHC should be tested on core biopsy samples to best reflect the biological status of the tumor.

Selecting patients with HER2-low breast cancer: Getting out of the tangle

The promising effect of antibody-drug conjugates on breast cancer with low expression of HER2 (HER2-low) raises many questions regarding the optimal selection of patients for this treatment. A key question is whether HER2 immunohistochemistry, an assay optimised to detect HER2 amplification, is reliable enough to assess HER2 protein levels to select patients with HER2-low breast cancer in daily pathology practices worldwide. Moreover, whether this assessment can be performed with sufficient reproducibility between pathologists in daily practices is debatable. Herein, we address the historical track record of the CAP-ASCO HER2 Guidelines, the reported limited reproducibility by pathologists of HER2 immunohistochemistry in the non-amplified cases, and the performance variation of different antibodies. Based on this summary, we propose solutions to improve the robustness to enable reliable identification of patients with HER2-low breast cancer.

Discordance between Immunohistochemistry and Erb-B2 Receptor Tyrosine Kinase 2 mRNA to Determine Human Epidermal Growth Factor Receptor 2 Low Status for Breast Cancer

Novel human epidermal growth factor receptor 2 (HER2)-directed antibody-drug conjugates have demonstrated efficacy in HER2-low expressing breast cancers, which are currently defined as those with immunohistochemistry (IHC) scores of 1+ or 2+ with a negative in situ hybridization assay. However, current HER2 testing methods are designed to identify HER2-amplified tumors with high expression levels. The true definition of HER2-low expressing breast cancers remains controversial. Using quantitative molecular analysis of breast cancers based on RNA expression, the dynamic range of HER2 expression exceeds that detected by in situ IHC approaches. Erb-B2 receptor tyrosine kinase 2 (ERBB2) mRNA expression levels across IHC groups using patient samples derived from the Tamoxifen Exemestane Adjuvant Multicenter Trial were investigated. The standardized mean differences in ERBB2 mRNA scores in log base 2 are 0.47 (95% CI, 0.36-0.57), 0.58 (95% CI, 0.26-0.70), and 0.32 (95% CI, -0.12 to 0.75) when comparing IHC 0+ without staining versus IHC 0+ with some staining, IHC 0+ with some staining versus IHC 1+, and IHC 1+ versus IHC 2+/fluorescence in situ hybridization-negative, respectively. The results showed immunohistochemical methods have a comparatively limited dynamic range for measuring HER2 protein expression. The range of expression based on RNA abundance suggests a molecular method defining HER2-low cancers may better serve the treatment decision needs of this group. Indeed, the validity of RNA abundance to identify HER2-low cancers and predict treatment response needs to be further evaluated by prospective clinical trials.

Multi-omic machine learning predictor of breast cancer therapy response

Breast cancers are complex ecosystems of malignant cells and the tumour microenvironment1. The composition of these tumour ecosystems and interactions within them contribute to responses to cytotoxic therapy2. Efforts to build response predictors have not incorporated this knowledge. We collected clinical, digital pathology, genomic and transcriptomic profiles of pre-treatment biopsies of breast tumours from 168 patients treated with chemotherapy with or without HER2 (encoded by ERBB2)-targeted therapy before surgery. Pathology end points (complete response or residual disease) at surgery3 were then correlated with multi-omic features in these diagnostic biopsies. Here we show that response to treatment is modulated by the pre-treated tumour ecosystem, and its multi-omics landscape can be integrated in predictive models using machine learning. The degree of residual disease following therapy is monotonically associated with pre-therapy features, including tumour mutational and copy number landscapes, tumour proliferation, immune infiltration and T cell dysfunction and exclusion. Combining these features into a multi-omic machine learning model predicted a pathological complete response in an external validation cohort (75 patients) with an area under the curve of 0.87. In conclusion, response to therapy is determined by the baseline characteristics of the totality of the tumour ecosystem captured through data integration and machine learning. This approach could be used to develop predictors for other cancers.

Residual cancer burden after neoadjuvant chemotherapy and long-term survival outcomes in breast cancer: a multicentre pooled analysis of 5161 patients

BACKGROUND

Previous studies have independently validated the prognostic relevance of residual cancer burden (RCB) after neoadjuvant chemotherapy. We used results from several independent cohorts in a pooled patient-level analysis to evaluate the relationship of RCB with long-term prognosis across different phenotypic subtypes of breast cancer, to assess generalisability in a broad range of practice settings.

METHODS

In this pooled analysis, 12 institutes and trials in Europe and the USA were identified by personal communications with site investigators. We obtained participant-level RCB results, and data on clinical and pathological stage, tumour subtype and grade, and treatment and follow-up in November, 2019, from patients (aged ≥18 years) with primary stage I-III breast cancer treated with neoadjuvant chemotherapy followed by surgery. We assessed the association between the continuous RCB score and the primary study outcome, event-free survival, using mixed-effects Cox models with the incorporation of random RCB and cohort effects to account for between-study heterogeneity, and stratification to account for differences in baseline hazard across cancer subtypes defined by hormone receptor status and HER2 status. The association was further evaluated within each breast cancer subtype in multivariable analyses incorporating random RCB and cohort effects and adjustments for age and pretreatment clinical T category, nodal status, and tumour grade. Kaplan-Meier estimates of event-free survival at 3, 5, and 10 years were computed for each RCB class within each subtype.

FINDINGS

We analysed participant-level data from 5161 patients treated with neoadjuvant chemotherapy between Sept 12, 1994, and Feb 11, 2019. Median age was 49 years (IQR 20-80). 1164 event-free survival events occurred during follow-up (median follow-up 56 months [IQR 0-186]). RCB score was prognostic within each breast cancer subtype, with higher RCB score significantly associated with worse event-free survival. The univariable hazard ratio (HR) associated with one unit increase in RCB ranged from 1·55 (95% CI 1·41-1·71) for hormone receptor-positive, HER2-negative patients to 2·16 (1·79-2·61) for the hormone receptor-negative, HER2-positive group (with or without HER2-targeted therapy; p<0·0001 for all subtypes). RCB score remained prognostic for event-free survival in multivariable models adjusted for age, grade, T category, and nodal status at baseline: the adjusted HR ranged from 1·52 (1·36-1·69) in the hormone receptor-positive, HER2-negative group to 2·09 (1·73-2·53) in the hormone receptor-negative, HER2-positive group (p<0·0001 for all subtypes).

INTERPRETATION

RCB score and class were independently prognostic in all subtypes of breast cancer, and generalisable to multiple practice settings. Although variability in hormone receptor subtype definitions and treatment across patients are likely to affect prognostic performance, the association we observed between RCB and a patient's residual risk suggests that prospective evaluation of RCB could be considered to become part of standard pathology reporting after neoadjuvant therapy.

FUNDING

National Cancer Institute at the US National Institutes of Health.

The tale of TILs in breast cancer: A report from The International Immuno-Oncology Biomarker Working Group

The advent of immune-checkpoint inhibitors (ICI) in modern oncology has significantly improved survival in several cancer settings. A subgroup of women with breast cancer (BC) has immunogenic infiltration of lymphocytes with expression of programmed death-ligand 1 (PD-L1). These patients may potentially benefit from ICI targeting the programmed death 1 (PD-1)/PD-L1 signaling axis. The use of tumor-infiltrating lymphocytes (TILs) as predictive and prognostic biomarkers has been under intense examination. Emerging data suggest that TILs are associated with response to both cytotoxic treatments and immunotherapy, particularly for patients with triple-negative BC. In this review from The International Immuno-Oncology Biomarker Working Group, we discuss (a) the biological understanding of TILs, (b) their analytical and clinical validity and efforts toward the clinical utility in BC, and (c) the current status of PD-L1 and TIL testing across different continents, including experiences from low-to-middle-income countries, incorporating also the view of a patient advocate. This information will help set the stage for future approaches to optimize the understanding and clinical utilization of TIL analysis in patients with BC.

Circulating tumor DNA is readily detectable among Ghanaian breast cancer patients supporting non-invasive cancer genomic studies in Africa

Circulating tumor DNA (ctDNA) sequencing studies could provide novel insights into the molecular pathology of cancer in sub-Saharan Africa. In 15 patient plasma samples collected at the time of diagnosis as part of the Ghana Breast Health Study and unselected for tumor grade and subtype, ctDNA was detected in a majority of patients based on whole- genome sequencing at high (30×) and low (0.1×) depths. Breast cancer driver copy number alterations were observed in the majority of patients.

Evaluation of multiple transcriptomic gene risk signatures in male breast cancer

Male breast cancer (BCa) is a rare disease accounting for less than 1% of all breast cancers and 1% of all cancers in males. The clinical management is largely extrapolated from female BCa. Several multigene assays are increasingly used to guide clinical treatment decisions in female BCa, however, there are limited data on the utility of these tests in male BCa. Here we present the gene expression results of 381 M0, ER+ve, HER2-ve male BCa patients enrolled in the Part 1 (retrospective analysis) of the International Male Breast Cancer Program. Using a custom NanoString™ panel comprised of the genes from the commercial risk tests Prosigna®, OncotypeDX®, and MammaPrint®, risk scores and intrinsic subtyping data were generated to recapitulate the commercial tests as described by us previously. We also examined the prognostic value of other risk scores such as the Genomic Grade Index (GGI), IHC4-mRNA and our prognostic 95-gene signature. In this sample set of male BCa, we demonstrated prognostic utility on univariate analysis. Across all signatures, patients whose samples were identified as low-risk experienced better outcomes than intermediate-risk, with those classed as high risk experiencing the poorest outcomes. As seen with female BCa, the concordance between tests was poor, with C-index values ranging from 40.3% to 78.2% and Kappa values ranging from 0.17 to 0.58. To our knowledge, this is the largest study of male breast cancers assayed to generate risk scores of the current commercial and academic risk tests demonstrating comparable clinical utility to female BCa.

Comparative survival analysis of multiparametric tests-when molecular tests disagree-A TEAM Pathology study

Multiparametric assays for risk stratification are widely used in the management of both node negative and node positive hormone receptor positive invasive breast cancer. Recent data from multiple sources suggests that different tests may provide different risk estimates at the individual patient level. The TEAM pathology study consists of 3284 postmenopausal ER+ve breast cancers treated with endocrine therapy Using genes comprising the following multi-parametric tests OncotypeDx®, Prosigna™ and MammaPrint® signatures were trained to recapitulate true assay results. Patients were then classified into risk groups and survival assessed. Whilst likelihood χ2 ratios suggested limited value for combining tests, Kaplan-Meier and LogRank tests within risk groups suggested combinations of tests provided statistically significant stratification of potential clinical value. Paradoxically whilst Prosigna-trained results stratified Oncotype-trained subgroups across low and intermediate risk categories, only intermediate risk Prosigna-trained cases were further stratified by Oncotype-trained results. Both Oncotype-trained and Prosigna-trained results further stratified MammaPrint-trained low risk cases, and MammaPrint-trained results also stratified Oncotype-trained low and intermediate risk groups but not Prosigna-trained results. Comparisons between existing multiparametric tests are challenging, and evidence on discordance between tests in risk stratification presents further dilemmas. Detailed analysis of the TEAM pathology study suggests a complex inter-relationship between test results in the same patient cohorts which requires careful evaluation regarding test utility. Further prognostic improvement appears both desirable and achievable.

Assessment of Ki67 in Breast Cancer: Updated Recommendations From the International Ki67 in Breast Cancer Working Group

Ki67 immunohistochemistry (IHC), commonly used as a proliferation marker in breast cancer, has limited value for treatment decisions due to questionable analytical validity. The International Ki67 in Breast Cancer Working Group (IKWG) consensus meeting, held in October 2019, assessed the current evidence for Ki67 IHC analytical validity and clinical utility in breast cancer, including the series of scoring studies the IKWG conducted on centrally stained tissues. Consensus observations and recommendations are: 1) as for estrogen receptor and HER2 testing, preanalytical handling considerations are critical; 2) a standardized visual scoring method has been established and is recommended for adoption; 3) participation in and evaluation of quality assurance and quality control programs is recommended to maintain analytical validity; and 4) the IKWG accepted that Ki67 IHC as a prognostic marker in breast cancer has clinical validity but concluded that clinical utility is evident only for prognosis estimation in anatomically favorable estrogen receptor–positive and HER2-negative patients to identify those who do not need adjuvant chemotherapy. In this T1-2, N0-1 patient group, the IKWG consensus is that Ki67 5% or less, or 30% or more, can be used to estimate prognosis. In conclusion, analytical validity of Ki67 IHC can be reached with careful attention to preanalytical issues and calibrated standardized visual scoring. Currently, clinical utility of Ki67 IHC in breast cancer care remains limited to prognosis assessment in stage I or II breast cancer. Further development of automated scoring might help to overcome some current limitations.

Computational approaches to support comparative analysis of multiparametric tests: Modelling versus Training

Multiparametric assays for risk stratification are widely used in the management of breast cancer, with applications being developed for a number of other cancer settings. Recent data from multiple sources suggests that different tests may provide different risk estimates at the individual patient level. There is an increasing need for robust methods to support cost effective comparisons of test performance in multiple settings. The derivation of similar risk classifications using genes comprising the following multi-parametric tests Oncotype DX^® (Genomic Health.), Prosigna^™ (NanoString Technologies, Inc.), MammaPrint^® (Agendia Inc.) was performed using different computational approaches. Results were compared to the actual test results. Two widely used approaches were applied, firstly computational “modelling” of test results using published algorithms and secondly a “training” approach which used reference results from the commercially supplied tests. We demonstrate the potential for errors to arise when using a “modelling” approach without reference to real world test results. Simultaneously we show that a “training” approach can provide a highly cost-effective solution to the development of real-world comparisons between different multigene signatures. Comparisons between existing multiparametric tests is challenging, and evidence on discordance between tests in risk stratification presents further dilemmas. We present an approach, modelled in breast cancer, which can provide health care providers and researchers with the potential to perform robust and meaningful comparisons between multigene tests in a cost-effective manner. We demonstrate that whilst viable estimates of gene signatures can be derived from modelling approaches, in our study using a training approach allowed a close approximation to true signature results.

Design and Development of a Fully Synthetic Multiplex Ligation-Dependent Probe Amplification-Based Probe Mix for Detection of Copy Number Alterations in Prostate Cancer Formalin-Fixed, Paraffin-Embedded Tissue Samples

DNA copy number alterations (CNAs) are promising biomarkers to predict prostate cancer (PCa) outcome. However, fluorescence in situ hybridization (FISH) cannot assess complex CNA signatures because of low multiplexing capabilities. Multiplex ligation-dependent probe amplification (MLPA) can detect multiple CNAs in a single PCR assay, but PCa-specific probe mixes available commercially are lacking. Synthetic MLPA probes were designed to target 10 CNAs relevant to PCa: 5q15-21.1 (CHD1), 6q15 (MAP3K7), 8p21.2 (NKX3-1), 8q24.21 (MYC), 10q23.31 (PTEN), 12p13.1 (CDKN1B), 13q14.2 (RB1), 16p13.3 (PDPK1), 16q23.1 (GABARAPL2), and 17p13.1 (TP53), with 9 control probes. In cell lines, CNAs were detected when the cancer genome was as low as 30%. Compared with FISH in radical prostatectomy formalin-fixed, paraffin-embedded samples (n = 18: 15 cancers and 3 matched benign), the MLPA assay showed median sensitivity and specificity of 80% and 93%, respectively, across all CNAs assessed. In the validation set (n = 40: 20 tumors sampled in two areas), the respective sensitivity and specificity of MLPA compared advantageously with FISH and TaqMan droplet digital PCR (ddPCR) when assessing PTEN deletion (FISH: 85% and 100%; ddPCR: 100% and 83%) and PDPK1 gain (FISH: 100% and 92%; ddPCR: 93% and 100%). This new PCa probe mix accurately identifies CNAs by MLPA across multiple genes using low quality and quantities (50 ng) of DNA extracted from clinical formalin-fixed, paraffin-embedded samples.

Overestimation of Late Distant Recurrences in High-Risk Patients With ER-Positive Breast Cancer: Validity and Accuracy of the CTS5 Risk Score in the TEAM and IDEAL Trials

PURPOSE

Most distant recurrences (DRs) in women with hormone receptor-positive breast cancer occur after 5 years from diagnosis. The Clinical Treatment Score post-5 years (CTS5) estimates DRs after 5 years of adjuvant endocrine therapy (AET). The aim of this study was to externally validate the CTS5 as a prognostic/predictive tool.

METHODS

The CTS5 categorizes patients who have been disease free for 5 years into low, intermediate, and high risk and calculates an absolute risk for developing DRs between 5 and 10 years. Discrimination and calibration were assessed using data from the TEAM and IDEAL trials. The predictive value of the CTS5 was tested with data from the IDEAL trial.

RESULTS

A total of 5,895 patients from the TEAM trial and 1,591 patients from the IDEAL trial were included. When assessing the CTS5 discrimination, significantly more DRs were found at 10 years after diagnosis in the CTS5 high- and intermediate-risk groups than in the low-risk group (hazard ratio, 5.7 [95% CI, 3.6 to 8.8] and 2.8 [95% CI, 1.7 to 4.4], respectively). In low- and intermediate-risk patients, the CTS5-predicted DR rates were higher, although not statistically significantly so, than observed rates. However, in high-risk patients, the CTS5-predicted DR rates were significantly higher than observed rates (29% v 19%, respectively; P < .001). The CTS5 was not predictive for extended AET duration.

CONCLUSION

The CTS5 score as applied to patients treated in the TEAM and IDEAL cohorts discriminates between risk categories but overestimates the risk of late DRs in high-risk patients. Therefore, the numerical risk assessment from the CTS5 calculator in its current form should be interpreted with caution when used in daily clinical practice, particularly in high-risk patients.

Abstract B02: Genomic and transcriptomic profiling of urine in prostate cancer

Prostate cancer (CaP) affects one in 8 men in the US and Canada, but many of these men could be spared aggressive treatment, often associated with significant morbidity, if diagnostic tools could more accurately assess the risk that the cancer will metastasize. Low pathologic/Gleason grade (Gleason Grade 3+3=6, equivalent to WHO Grade Group 1) is the main defining feature of nonlethal low-risk CaP, and active surveillance (AS) is the standard of care for such men. However, current diagnostic methods cannot accurately separate low and higher risk CaP based on core biopsies, presenting a major dilemma as repeated biopsies during AS carry significant risks. At present no diagnostic tools, either imaging-based or biomarker-based, can safely supplant repeated invasive biopsies. Genomic profiling of liquid biospecimens (“liquid biopsies”) is quickly becoming translated as part of contemporary clinical trials and is being translated for use in the diagnostic setting. Less invasive than traditional solid tissue biopsy approaches, liquid biopsy specimens have the potential to be used not only for early detection but also to monitor therapeutic response and progression. Leveraging the advantage of the anatomic relationship between the prostate and urinary tract, we obtained 11 post-digital rectal exam (DRE) urine samples from patients who presented at the Kingston Health Sciences Centre (Kingston, Ontario) to be evaluated for prostate cancer. Through a pan-Canadian research consortium called PRONTO, we developed a tissue-based classifier (PRONTO-T) differentiating between low- and high-risk cancer with an independently validated AUC of 0.85. This proof-of-concept study tests post-digital rectal examination (DRE) urine samples for genomic features associated with aggressive CaP, including features included in the PRONTO-T risk classifier. DNA and RNA were extracted from 11 post-DRE urine samples. Profiling with a customized NGS-based targeted-methylation panel by Thermo Fisher demonstrated robust signals from urine-derived DNA. Similarly, urine samples profiled with the pan-cancer Oncomine Comprehensive Assay (v3) detected potentially actionable mutations in MET and PIK3CA. RNA obtained from post-DRE urines met quality control standards for transcriptional profiling using the NanoString nCounter System and revealed patterns of gene expression changes consistent with prostate cancer biology. These encouraging preliminary results demonstrate that the profiling of urine can provide sufficient diagnostic and potentially prognostic information to significantly impact the clinical management of prostate cancer.

Citation Format: Jane Bayani, Palak G. Patel, Dan Dion, Vanessa Bratti, Ania Ahmadian-Namin, Tamara Jamaspishvili, Jason Izard, D. Robert Siemens, David M. Berman, John M. S. Bartlett. Genomic and transcriptomic profiling of urine in prostate cancer [abstract]. In: Proceedings of the AACR Special Conference on Advances in Liquid Biopsies; Jan 13-16, 2020; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(11_Suppl):Abstract nr B02.

Abstract A03: Evaluation of the Oncomine Pan-Cancer Cell-Free Assay for liquid biopsy profiling

Genomic profiling of liquid biopsies is no longer an emerging area of clinical research, but quickly becoming translated as part of contemporary clinical trials for use in the diagnostic setting. Comparatively less invasive than traditional solid tissue biopsy approaches, liquid biopsy specimens such as blood or urine can be used not only for early detection, but also for the monitoring of therapeutic response and progression. While custom circulating tumor DNA (ctDNA) assays are being academically developed for the profiling of specific biomarkers in a specific disease or therapeutic context, there are commercially available pan-cancer circulating nucleic acid (cNA) panels available. These commercially available panels can be used to reveal the spectrum of genomic changes within liquid biopsies and determine the level of sensitivity that can be obtained. In this study, we profiled 39 patients (n= 78 samples) with matched plasma and solid tumor to evaluate the Oncomine Pan-Cancer Cell-Free Assay, a 52-gene total nucleic acid panel for the detection of hotspot mutation and copy-number changes in key cancer driving genes. The evaluation cohort comprises 30 invasive breast cancers, 5 lung cancers, and 4 cancers of indeterminate origin, ranging from early and localized cancers to those that were characterized as late or metastatic. The Oncomine Pan-Cancer Cell-Free Assay utilizes molecular tagging technology to enable variant detection as low as 0.1%, given an optimal input of 20 ng of ctDNA. To determine whether variants detected using the Oncomine Pan-Cancer Cell-Free Assay were represented in the solid tumor, the solid tumor tissues were assayed using the Oncomine Pan-Cancer Cell-Free Assay in addition to the Oncomine Comprehensive Assay v3 (OCAv3). The OCAv3 profiles 161 pan-cancer genes for both full exon coverage as well as hotspot mutation and copy-number detection. Using these commercially available panels, for which OCAv3 is currently being utilized in the NCI-MATCH Trial (NCT02465060), we were able to validate the detection of genomic changes in the ctDNAs to the matching solid tissues; among them, MET mutations detected in the plasma of invasive breast cancers were identified in the matching solid tumor, as were PIK3CA and TP53 mutations, in addition to amplification of ERBB2. Similarly, KRAS mutations detected in the plasma of lung cancer patients were identified in the matched solid tumor. This presentation will summarize those findings with respect to the limit of detection obtained and the implications of monitoring progression and therapeutic response. These data suggest that existing commercial panels such as the Oncomine Pan-Cancer Cell-Free Assay, the Ion Torrent Platform, and Ion Reporter have the potential to be used in a routine clinical setting.

Citation Format: Jane Bayani, Megan Hopkins, Melanie Spears, John M. S. Bartlett. Evaluation of the Oncomine Pan-Cancer Cell-Free Assay for liquid biopsy profiling [abstract]. In: Proceedings of the AACR Special Conference on Advances in Liquid Biopsies; Jan 13-16, 2020; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(11_Suppl):Abstract nr A03.

Pitfalls in assessing stromal tumor infiltrating lymphocytes (sTILs) in breast cancer

Stromal tumor-infiltrating lymphocytes (sTILs) are important prognostic and predictive biomarkers in triple-negative (TNBC) and HER2-positive breast cancer. Incorporating sTILs into clinical practice necessitates reproducible assessment. Previously developed standardized scoring guidelines have been widely embraced by the clinical and research communities. We evaluated sources of variability in sTIL assessment by pathologists in three previous sTIL ring studies. We identify common challenges and evaluate impact of discrepancies on outcome estimates in early TNBC using a newly-developed prognostic tool. Discordant sTIL assessment is driven by heterogeneity in lymphocyte distribution. Additional factors include: technical slide-related issues; scoring outside the tumor boundary; tumors with minimal assessable stroma; including lymphocytes associated with other structures; and including other inflammatory cells. Small variations in sTIL assessment modestly alter risk estimation in early TNBC but have the potential to affect treatment selection if cutpoints are employed. Scoring and averaging multiple areas, as well as use of reference images, improve consistency of sTIL evaluation. Moreover, to assist in avoiding the pitfalls identified in this analysis, we developed an educational resource available at www.tilsinbreastcancer.org/pitfalls.

Application of a risk-management framework for integration of stromal tumor-infiltrating lymphocytes in clinical trials

Stromal tumor-infiltrating lymphocytes (sTILs) are a potential predictive biomarker for immunotherapy response in metastatic triple-negative breast cancer (TNBC). To incorporate sTILs into clinical trials and diagnostics, reliable assessment is essential. In this review, we propose a new concept, namely the implementation of a risk-management framework that enables the use of sTILs as a stratification factor in clinical trials. We present the design of a biomarker risk-mitigation workflow that can be applied to any biomarker incorporation in clinical trials. We demonstrate the implementation of this concept using sTILs as an integral biomarker in a single-center phase II immunotherapy trial for metastatic TNBC (TONIC trial, NCT02499367), using this workflow to mitigate risks of suboptimal inclusion of sTILs in this specific trial. In this review, we demonstrate that a web-based scoring platform can mitigate potential risk factors when including sTILs in clinical trials, and we argue that this framework can be applied for any future biomarker-driven clinical trial setting.

Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group

Assessment of tumor-infiltrating lymphocytes (TILs) is increasingly recognized as an integral part of the prognostic workflow in triple-negative (TNBC) and HER2-positive breast cancer, as well as many other solid tumors. This recognition has come about thanks to standardized visual reporting guidelines, which helped to reduce inter-reader variability. Now, there are ripe opportunities to employ computational methods that extract spatio-morphologic predictive features, enabling computer-aided diagnostics. We detail the benefits of computational TILs assessment, the readiness of TILs scoring for computational assessment, and outline considerations for overcoming key barriers to clinical translation in this arena. Specifically, we discuss: 1. ensuring computational workflows closely capture visual guidelines and standards; 2. challenges and thoughts standards for assessment of algorithms including training, preanalytical, analytical, and clinical validation; 3. perspectives on how to realize the potential of machine learning models and to overcome the perceptual and practical limits of visual scoring.

Author Correction: Transcription phenotypes of pancreatic cancer are driven by genomic events during tumor evolution

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

A Four-Chemokine Signature Is Associated with a T-cell-Inflamed Phenotype in Primary and Metastatic Pancreatic Cancer

PURPOSE

The molecular drivers of antitumor immunity in pancreatic ductal adenocarcinoma (PDAC) are poorly understood, posing a major obstacle for the identification of patients potentially amenable for immune-checkpoint blockade or other novel strategies. Here, we explore the association of chemokine expression with effector T-cell infiltration in PDAC.

EXPERIMENTAL DESIGN

Discovery cohorts comprised 113 primary resected PDAC and 107 PDAC liver metastases. Validation cohorts comprised 182 PDAC from The Cancer Genome Atlas and 92 PDACs from the Australian International Cancer Genome Consortium. We explored associations between immune cell counts by immunohistochemistry, chemokine expression, and transcriptional hallmarks of antitumor immunity by RNA sequencing (RNA-seq), and mutational burden by whole-genome sequencing.

RESULTS

Among all known human chemokines, a coregulated set of four (CCL4, CCL5, CXCL9, and CXCL10) was strongly associated with CD8⁺ T-cell infiltration (P < 0.001). Expression of this "4-chemokine signature" positively correlated with transcriptional metrics of T-cell activation (ZAP70, ITK, and IL2RB), cytolytic activity (GZMA and PRF1), and immunosuppression (PDL1, PD1, CTLA4, TIM3, TIGIT, LAG3, FASLG, and IDO1). Furthermore, the 4-chemokine signature marked tumors with increased T-cell activation scores (MHC I presentation, T-cell/APC costimulation) and elevated expression of innate immune sensing pathways involved in T-cell priming (STING and NLRP3 inflammasome pathways, BATF3-driven dendritic cells). Importantly, expression of this 4-chemokine signature was consistently indicative of a T-cell-inflamed phenotype across primary PDAC and PDAC liver metastases.

CONCLUSIONS

A conserved 4-chemokine signature marks resectable and metastatic PDAC tumors with an active antitumor phenotype. This could have implications for the appropriate selection of PDAC patients in immunotherapy trials.

Transcription phenotypes of pancreatic cancer are driven by genomic events during tumor evolution

Pancreatic adenocarcinoma presents as a spectrum of a highly aggressive disease in patients. The basis of this disease heterogeneity has proved difficult to resolve due to poor tumor cellularity and extensive genomic instability. To address this, a dataset of whole genomes and transcriptomes was generated from purified epithelium of primary and metastatic tumors. Transcriptome analysis demonstrated that molecular subtypes are a product of a gene expression continuum driven by a mixture of intratumoral subpopulations, which was confirmed by single-cell analysis. Integrated whole-genome analysis uncovered that molecular subtypes are linked to specific copy number aberrations in genes such as mutant KRAS and GATA6. By mapping tumor genetic histories, tetraploidization emerged as a key mutational process behind these events. Taken together, these data support the premise that the constellation of genomic aberrations in the tumor gives rise to the molecular subtype, and that disease heterogeneity is due to ongoing genomic instability during progression.

Breast Cancer Index and prediction of benefit from extended endocrine therapy in breast cancer patients treated in the Adjuvant Tamoxifen-To Offer More? (aTTom) trial

BACKGROUND

Extending the duration of adjuvant endocrine therapy reduces the risk of recurrence in a subset of women with early-stage hormone receptor-positive (HR+) breast cancer. Validated predictive biomarkers of endocrine response could significantly improve patient selection for extended therapy. Breast cancer index (BCI) [HOXB13/IL17BR ratio (H/I)] was evaluated for its ability to predict benefit from extended endocrine therapy in patients previously randomized in the Adjuvant Tamoxifen-To Offer More? (aTTom) trial.

PATIENTS AND METHODS

Trans-aTTom is a multi-institutional, prospective-retrospective study in patients with available formalin-fixed paraffin-embedded primary tumor blocks. BCI testing and central determination of estrogen receptor (ER) and progesterone receptor (PR) status by immunohistochemistry were carried out blinded to clinical outcome. Survival endpoints were evaluated using Kaplan-Meier analysis and Cox regression with recurrence-free interval (RFI) as the primary endpoint. Interaction between extended endocrine therapy and BCI (H/I) was assessed using the likelihood ratio test.

RESULTS

Of 583 HR+, N+ patients analyzed, 49% classified as BCI (H/I)-High derived a significant benefit from 10 versus 5 years of tamoxifen treatment [hazard ratio (HR): 0.35; 95% confidence interval (CI) 0.15-0.86; 10.2% absolute risk reduction based on RFI, P = 0.027]. BCI (H/I)-low patients showed no significant benefit from extended endocrine therapy (HR: 1.07; 95% CI 0.69-1.65; -0.2% absolute risk reduction; P = 0.768). Continuous BCI (H/I) levels predicted the magnitude of benefit from extended tamoxifen, whereas centralized ER and PR did not. Interaction between extended tamoxifen treatment and BCI (H/I) was statistically significant (P = 0.012), adjusting for clinicopathological factors.

CONCLUSION

BCI by high H/I expression was predictive of endocrine response and identified a subset of HR+, N+ patients with significant benefit from 10 versus 5 years of tamoxifen therapy. These data provide further validation, consistent with previous MA.17 data, establishing level 1B evidence for BCI as a predictive biomarker of benefit from extended endocrine therapy.

TRIAL REGISTRATION

ISRCTN17222211; NCT00003678.

A three-gene DNA methylation biomarker accurately classifies early stage prostate cancer

BACKGROUND

We identify and validate accurate diagnostic biomarkers for prostate cancer through a systematic evaluation of DNA methylation alterations.

MATERIALS AND METHODS

We assembled three early prostate cancer cohorts (total patients = 699) from which we collected and processed over 1300 prostatectomy tissue samples for DNA extraction. Using real-time methylation-specific PCR, we measured normalized methylation levels at 15 frequently methylated loci. After partitioning sample sets into independent training and validation cohorts, classifiers were developed using logistic regression, analyzed, and validated.

RESULTS

In the training dataset, DNA methylation levels at 7 of 15 genomic loci (glutathione S-transferase Pi 1 [GSTP1], CCDC181, hyaluronan, and proteoglycan link protein 3 [HAPLN3], GSTM2, growth arrest-specific 6 [GAS6], RASSF1, and APC) showed large differences between cancer and benign samples. The best binary classifier was the GAS6/GSTP1/HAPLN3 logistic regression model, with an area under these curves of 0.97, which showed a sensitivity of 94%, and a specificity of 93% after external validation.

CONCLUSION

We created and validated a multigene model for the classification of benign and malignant prostate tissue. With false positive and negative rates below 7%, this three-gene biomarker represents a promising basis for more accurate prostate cancer diagnosis.

Benchmarking to the Gold Standard: Hyaluronan-Oxime Hydrogels Recapitulate Xenograft Models with In Vitro Breast Cancer Spheroid Culture

Many 3D in vitro models induce breast cancer spheroid formation; however, this alone does not recapitulate the complex in vivo phenotype. To effectively screen therapeutics, it is urgently needed to validate in vitro cancer spheroid models against the gold standard of xenografts. A new oxime-crosslinked hyaluronan (HA) hydrogel is designed, manipulating gelation rate and mechanical properties to grow breast cancer spheroids in 3D. This HA-oxime breast cancer model maintains the gene expression profile most similar to that of tumor xenografts based on a pan-cancer gene expression profile (comprising 730 genes) of three different human breast cancer subtypes compared to Matrigel or conventional 2D culture. Differences in gene expression between breast cancer cultures in HA-oxime versus Matrigel or 2D are confirmed for 12 canonical pathways by gene set variation analysis. Importantly, drug response is dependent on the culture method. Breast cancer cells respond better to the Rac inhibitor (EHT-1864) and the PI3K inhibitor (AZD6482) when cultured in HA-oxime versus Matrigel. This study demonstrates the superiority of an HA-based hydrogel as a platform for in vitro breast cancer culture of both primary, patient-derived cells and cell lines, and provides a hydrogel culture model that closely matches that in vivo.

Analytical validation of a standardised scoring protocol for Ki67 immunohistochemistry on breast cancer excision whole sections: an international multicentre collaboration

AIMS

The nuclear proliferation marker Ki67 assayed by immunohistochemistry has multiple potential uses in breast cancer, but an unacceptable level of interlaboratory variability has hampered its clinical utility. The International Ki67 in Breast Cancer Working Group has undertaken a systematic programme to determine whether Ki67 measurement can be analytically validated and standardised among laboratories. This study addresses whether acceptable scoring reproducibility can be achieved on excision whole sections.

METHODS AND RESULTS

Adjacent sections from 30 primary ER⁺ breast cancers were centrally stained for Ki67 and sections were circulated among 23 pathologists in 12 countries. All pathologists scored Ki67 by two methods: (i) global: four fields of 100 tumour cells each were selected to reflect observed heterogeneity in nuclear staining; (ii) hot-spot: the field with highest apparent Ki67 index was selected and up to 500 cells scored. The intraclass correlation coefficient (ICC) for the global method [confidence interval (CI) = 0.87; 95% CI = 0.799-0.93] marginally met the prespecified success criterion (lower 95% CI ≥ 0.8), while the ICC for the hot-spot method (0.83; 95% CI = 0.74-0.90) did not. Visually, interobserver concordance in location of selected hot-spots varies between cases. The median times for scoring were 9 and 6 min for global and hot-spot methods, respectively.

CONCLUSIONS

The global scoring method demonstrates adequate reproducibility to warrant next steps towards evaluation for technical and clinical validity in appropriate cohorts of cases. The time taken for scoring by either method is practical using counting software we are making publicly available. Establishment of external quality assessment schemes is likely to improve the reproducibility between laboratories further.

Characterization of male breast cancer: results of the EORTC 10085/TBCRC/BIG/NABCG International Male Breast Cancer Program

Background

Male breast cancer (BC) is rare, managed by extrapolation from female BC. The International Male BC Program aims to better characterize and manage this disease. We report the results of part I, a retrospective joint analysis of cases diagnosed during a 20-year period.

Methods

Patients with follow-up and tumor samples, treated between 1990 and 2010, in 93 centers/9 countries. Samples were centrally analyzed in three laboratories (the United Kingdom, the Netherlands and the United States).

Results

Of 1822 patients enrolled, 1483 were analyzed; 63.5% were diagnosed between 2001 and 2010, 57 (5.1%) had metastatic disease (M1). Median age at diagnosis: 68.4 years. Of 1054 M0 cases, 56.2% were node-negative (N0) and 48.5% had T1 tumors; 4% had breast conserving surgery (BCS), 18% sentinel lymph-node biopsy; half received adjuvant radiotherapy; 29.8% (neo)adjuvant chemotherapy and 76.8% adjuvant endocrine therapy (ET), mostly tamoxifen (88.4%). Per central pathology, for M0 tumors: 84.8% ductal invasive carcinomas, 51.5% grade 2; 99.3% estrogen receptor (ER)-positive; 81.9% progesterone receptor (PR)-positive; 96.9% androgen receptor (AR)-positive [ER, PR or AR Allred score ≥3]; 61.1% Ki67 expression low (<14% positive cells); using immunohistochemistry (IHC) surrogates, 41.9% were Luminal-A-like, 48.6% Luminal-B-like/HER-2-negative, 8.7% HER-2-positive, 0.3% triple negative. Median follow-up: 8.2 years (0.0-23.8) for all, 7.2 years (0.0-23.2), for M0, 2.6 years (0.0-12.7) for M1 patients. A significant improvement over time was observed in age-corrected BC mortality. BC-specific-mortality was higher for men younger than 50 years. Better overall (OS) and recurrence-free survival (RFS) were observed for highly ER+ (P = 0.001), highly PR+ (P = 0.002), highly AR+ disease (P = 0.019). There was no association between OS/RFS and HER-2 status, Ki67, IHC subtypes nor grade.

Conclusions

Male BC is usually ER, PR and AR-positive, Luminal B-like/HER2-negative. Of note, 56% patients had T1 tumors but only 4% had BCS. ER was highly positive in >90% of cases but only 77% received adjuvant ET. ER, PR and AR were associated with OS and RFS, whereas grade, Ki67 and IHC surrogates were not. Significant improvement in survival over time was observed.

RNA and DNA Integrity Remain Stable in Frozen Tissue After Long-Term Storage at Cryogenic Temperatures: A Report from the Ontario Tumour Bank

Background: It is widely assumed that the integrity of tissue specimens remains stable indefinitely if preserved at cryogenic temperatures. With biobanking reaching a level of maturity where samples are increasingly stored for 10 years and beyond, this assumption of prolonged stability should be tested. Data from such an assessment are critical to verify if samples stored for extended durations remain "fit for purpose" or if there is need to reconsider the utility of samples stored beyond a certain timeframe. The Ontario Tumour Bank has been collecting samples since 2004, and assesses a random selection of frozen samples each year for RNA and DNA integrity as a part of ongoing quality control (QC) practices. This historical quality assessment data provide a unique opportunity to assess the impact of extended storage on nucleic acid integrity using replicate samples that remain in the bank in the present day as comparators. Methods: To examine the stability of fresh-frozen tumor tissue stored at cryogenic temperatures, RNA was extracted and analyzed from 87 cases over 14 disease sites stored long term in vapor-phase liquid nitrogen (LN2) (approximately -180°C). Historical QC data were compared against new data after re-extraction of replicate samples to determine the effect of extended storage on RNA quality. In addition, DNA was extracted from a subselection of samples (n = 20) to determine the effect of prolonged storage on DNA integrity. Results: No time-dependent decrease in tissue RNA or DNA quality, as measured by RNA integrity number (RIN) and DNA integrity number, was observed over an 11-year period. As a secondary observation, RNA integrity was not predictive of DNA integrity: DNA quality may still be very good, and as such RIN scores should not be used as a substitute indicator for evaluating DNA. Conclusions: Extended cryogenic storage beyond 2-11 years remains a viable option for maintaining the high quality of specimens in biobanks.

Integration of Genomic and Transcriptional Features in Pancreatic Cancer Reveals Increased Cell Cycle Progression in Metastases

We integrated clinical, genomic, and transcriptomic data from 224 primaries and 95 metastases from 289 patients to characterize progression of pancreatic ductal adenocarcinoma (PDAC). Driver gene alterations and mutational and expression-based signatures were preserved, with truncations, inversions, and translocations most conserved. Cell cycle progression (CCP) increased with sequential inactivation of tumor suppressors, yet remained higher in metastases, perhaps driven by cell cycle regulatory gene variants. Half of the cases were hypoxic by expression markers, overlapping with molecular subtypes. Paired tumor heterogeneity showed cancer cell migration by Halstedian progression. Multiple PDACs arising synchronously and metachronously in the same pancreas were actually intra-parenchymal metastases, not independent primary tumors. Established clinical co-variates dominated survival analyses, although CCP and hypoxia may inform clinical practice.

Whole genomes define concordance of matched primary, xenograft, and organoid models of pancreas cancer

Pancreatic ductal adenocarcinoma (PDAC) has the worst prognosis among solid malignancies and improved therapeutic strategies are needed to improve outcomes. Patient-derived xenografts (PDX) and patient-derived organoids (PDO) serve as promising tools to identify new drugs with therapeutic potential in PDAC. For these preclinical disease models to be effective, they should both recapitulate the molecular heterogeneity of PDAC and validate patient-specific therapeutic sensitivities. To date however, deep characterization of the molecular heterogeneity of PDAC PDX and PDO models and comparison with matched human tumour remains largely unaddressed at the whole genome level. We conducted a comprehensive assessment of the genetic landscape of 16 whole-genome pairs of tumours and matched PDX, from primary PDAC and liver metastasis, including a unique cohort of 5 'trios' of matched primary tumour, PDX, and PDO. We developed a pipeline to score concordance between PDAC models and their paired human tumours for genomic events, including mutations, structural variations, and copy number variations. Tumour-model comparisons of mutations displayed single-gene concordance across major PDAC driver genes, but relatively poor agreement across the greater mutational load. Genome-wide and chromosome-centric analysis of structural variation (SV) events highlights previously unrecognized concordance across chromosomes that demonstrate clustered SV events. We found that polyploidy presented a major challenge when assessing copy number changes; however, ploidy-corrected copy number states suggest good agreement between donor-model pairs. Collectively, our investigations highlight that while PDXs and PDOs may serve as tractable and transplantable systems for probing the molecular properties of PDAC, these models may best serve selective analyses across different levels of genomic complexity.

An international multicenter study to evaluate reproducibility of automated scoring for assessment of Ki67 in breast cancer

The nuclear proliferation biomarker Ki67 has potential prognostic, predictive, and monitoring roles in breast cancer. Unacceptable between-laboratory variability has limited its clinical value. The International Ki67 in Breast Cancer Working Group investigated whether Ki67 immunohistochemistry can be analytically validated and standardized across laboratories using automated machine-based scoring. Sets of pre-stained core-cut biopsy sections of 30 breast tumors were circulated to 14 laboratories for scanning and automated assessment of the average and maximum percentage of tumor cells positive for Ki67. Seven unique scanners and 10 software platforms were involved in this study. Pre-specified analyses included evaluation of reproducibility between all laboratories (primary) as well as among those using scanners from a single vendor (secondary). The primary reproducibility metric was intraclass correlation coefficient between laboratories, with success considered to be intraclass correlation coefficient >0.80. Intraclass correlation coefficient for automated average scores across 16 operators was 0.83 (95% credible interval: 0.73-0.91) and intraclass correlation coefficient for maximum scores across 10 operators was 0.63 (95% credible interval: 0.44-0.80). For the laboratories using scanners from a single vendor (8 score sets), intraclass correlation coefficient for average automated scores was 0.89 (95% credible interval: 0.81-0.96), which was similar to the intraclass correlation coefficient of 0.87 (95% credible interval: 0.81-0.93) achieved using these same slides in a prior visual-reading reproducibility study. Automated machine assessment of average Ki67 has the potential to achieve between-laboratory reproducibility similar to that for a rigorously standardized pathologist-based visual assessment of Ki67. The observed intraclass correlation coefficient was worse for maximum compared to average scoring methods, suggesting that maximum score methods may be suboptimal for consistent measurement of proliferation. Automated average scoring methods show promise for assessment of Ki67 scoring, but requires further standardization and subsequent clinical validation.

Incorporating Biology Into Breast Cancer Staging: American Joint Committee on Cancer, Eighth Edition, Revisions and Beyond

Higher-quality imaging, refined surgical procedures, enhanced pathologic evaluation, and improved understanding of the impact of tumor biology on treatment and prognosis have necessitated revisions of the AJCC breast cancer staging system. The eighth edition includes clinical and pathologic prognostic stages that incorporate biologic variables-grade, estrogen and progesterone receptor status, HER2 status, and multigene panels-with the anatomic extent of disease defined by tumor, node, and metastasis categories. The prognostic staging systems facilitate more refined stratification with respect to survival than anatomic stage alone. Because the prognostic staging systems are dependent on biologic factors, accuracy is dependent on rigorous pathologic evaluation of tumors and on administration of treatment dictated by tumor biology. It is anticipated that technological advances will facilitate even more refined determination of underlying biology within tumors and in the peripheral blood, which increasingly is being evaluated as a compartment that reflects the primary tumor and sites of distant metastases. Diseases should be staged according to the eighth edition staging system to accurately reflect prognosis and to allow standardized data collection. Such standardization will facilitate assessment of the impact of advances in diagnosis and treatment of patients with breast cancer.

Pathway-based subnetworks enable cross-disease biomarker discovery

Biomarkers lie at the heart of precision medicine. Surprisingly, while rapid genomic profiling is becoming ubiquitous, the development of biomarkers usually involves the application of bespoke techniques that cannot be directly applied to other datasets. There is an urgent need for a systematic methodology to create biologically-interpretable molecular models that robustly predict key phenotypes. Here we present SIMMS (Subnetwork Integration for Multi-Modal Signatures): an algorithm that fragments pathways into functional modules and uses these to predict phenotypes. We apply SIMMS to multiple data types across five diseases, and in each it reproducibly identifies known and novel subtypes, and makes superior predictions to the best bespoke approaches. To demonstrate its ability on a new dataset, we profile 33 genes/nodes of the PI3K pathway in 1734 FFPE breast tumors and create a four-subnetwork prediction model. This model out-performs a clinically-validated molecular test in an independent cohort of 1742 patients. SIMMS is generic and enables systematic data integration for robust biomarker discovery.

Human Epidermal Growth Factor Receptor 2 Testing in Breast Cancer: American Society of Clinical Oncology/College of American Pathologists Clinical Practice Guideline Focused Update

PURPOSE.—

To update key recommendations of the American Society of Clinical Oncology (ASCO)/College of American Pathologists (CAP) human epidermal growth factor receptor 2 (HER2) testing in breast cancer guideline.

METHODS.—

Based on the signals approach, an Expert Panel reviewed published literature and research survey results on the observed frequency of less common in situ hybridization (ISH) patterns to update the recommendations.

RECOMMENDATIONS.—

Two recommendations addressed via correspondence in 2015 are included. First, immunohistochemistry (IHC) 2+ is defined as invasive breast cancer with weak to moderate complete membrane staining observed in >10% of tumor cells. Second, if the initial HER2 test result in a core needle biopsy specimen of a primary breast cancer is negative, a new HER2 test may (not "must") be ordered on the excision specimen based on specific clinical criteria. The HER2 testing algorithm for breast cancer is updated to address the recommended workup for less common clinical scenarios (approximately 5% of cases) observed when using a dual-probe ISH assay. These scenarios are described as ISH group 2 ( HER2/chromosome enumeration probe 17 [CEP17] ratio ≥2.0; average HER2 copy number <4.0 signals per cell), ISH group 3 ( HER2/CEP17 ratio <2.0; average HER2 copy number ≥6.0 signals per cell), and ISH group 4 ( HER2/CEP17 ratio <2.0; average HER2 copy number ≥4.0 and <6.0 signals per cell). The diagnostic approach includes more rigorous interpretation criteria for ISH and requires concomitant IHC review for dual-probe ISH groups 2 to 4 to arrive at the most accurate HER2 status designation (positive or negative) based on combined interpretation of the ISH and IHC assays. The Expert Panel recommends that laboratories using single-probe ISH assays include concomitant IHC review as part of the interpretation of all single-probe ISH assay results.

Exploration of tumour-infiltrating lymphocytes as a predictive biomarker for adjuvant endocrine therapy in early breast cancer

PURPOSE

Tumour-infiltrating lymphocytes (TILs) have been shown to be prognostic for disease-free survival and predictive for the benefit of chemotherapy in patients with early breast cancer, but have not been studied for endocrine therapy.

EXPERIMENTAL DESIGN

The number of CD8-positive TILs was assessed in a subcohort of 236 patients in the Intergroup Exemestane Study. AQ After 2-3 years of adjuvant tamoxifen, AQpatients were randomized between the schemes of continuation for 5 years on tamoxifen and switching to exemestane. The numbers of CD8-positive TILs were analysed for correlations with disease-free survival (DFS) and overall survival (OS). A similar analysis was performed on 2596 patients in the TEAM trial who were randomized between the sequential scheme and the exemestane monotherapy.

RESULTS

In the first cohort, patients with low (below median) numbers of CD8-positive TILs had a univariate hazard ratio (HR) for DFS of 0.27 (95% CI 0.13-0.55) in favour of treatment with exemestane, whereas this benefit was not observed in patients with high numbers of CD8-positive TILs (HR 1.34, 95% CI 0.71-2.50, HR for interaction 5.02, p = 0.001). In the second cohort, patients with low numbers of CD8-positive TILs showed a benefit of exemestane treatment on recurrence-free survival (RFS HR 0.67, 95% CI 0.45-0.99), and not with above-median numbers of CD8-positive TILs (HR 0.86, 95% CI 0.59-1.26, HR for interaction 1.29, p = 0.36).

CONCLUSIONS

This study is the first to propose the number of CD8-positive TILs as potential predictive markers for endocrine therapy, with the low presence of CD8-positive TILs associated to benefit for exemestane-inclusive therapy. However, treatment-by-marker interactions were only significant in one cohort, indicating the need for further validation.

Tumoral BRD4 expression in lymph node-negative breast cancer: association with T-bet+ tumor-infiltrating lymphocytes and disease-free survival

Background

We previously observed that T-bet+ tumor-infiltrating T lymphocytes (T-bet+ TILs) in primary breast tumors were associated with adverse clinicopathological features, yet favorable clinical outcome. We identified BRD4 (Bromodomain-Containing Protein 4), a member of the  Bromodomain and Extra Terminal domain (BET) family, as a gene that distinguished T-bet+/high and T-bet−/low tumors. In clinical studies, BET inhibitors have been shown to suppress inflammation in various cancers, suggesting a potential link between BRD4 and immune infiltration in cancer. Hence, we examined the BRD4 expression and clinicopathological features of breast cancer.

Methods

The cohort consisted of a prospectively ascertained consecutive series of women with axillary node-negative breast cancer with long follow-up. Gene expression microarray data were used to detect mRNAs differentially expressed between T-bet+/high (n = 6) and T-bet−/low (n = 41) tumors. Tissue microarrays (TMAs) constructed from tumors of 612 women were used to quantify expression of BRD4 by immunohistochemistry, which was analyzed for its association with T-bet+ TILs, Jagged1, clinicopathological features, and disease-free survival.

Results

Microarray analysis indicated that BRD4 mRNA expression was up to 44-fold higher in T-bet+/high tumors compared to T-bet−/low tumors (p = 5.38E-05). Immunohistochemical expression of BRD4 in cancer cells was also shown to be associated with T-bet+ TILs (p = 0.0415) as well as with Jagged1 mRNA and protein expression (p = 0.0171, 0.0010 respectively). BRD4 expression correlated with larger tumor size (p = 0.0049), pre-menopausal status (p = 0.0018), and high Ki-67 proliferative index (p = 0.0009). Women with high tumoral BRD4 expression in the absence of T-bet+ TILs exhibited a significantly poorer outcome (log rank test p = 0.0165) relative to other subgroups.

Conclusions

The association of BRD4 expression with T-bet+ TILs, and T-bet+ TIL-dependent disease-free survival suggests a potential link between BRD4-mediated tumor development and tumor immune surveillance, possibly through BRD4’s regulation of Jagged1 signaling pathways. Further understanding BRD4’s role in different immune contexts may help to identify an appropriate subset of breast cancer patients who may benefit from BET inhibitors without the risk of diminishing the anti-tumoral immune activity.

Human Epidermal Growth Factor Receptor 2 Testing in Breast Cancer: American Society of Clinical Oncology/College of American Pathologists Clinical Practice Guideline Focused Update

Purpose To update key recommendations of the American Society of Clinical Oncology/College of American Pathologists human epidermal growth factor receptor 2 (HER2) testing in breast cancer guideline. Methods Based on the signals approach, an Expert Panel reviewed published literature and research survey results on the observed frequency of less common in situ hybridization (ISH) patterns to update the recommendations. Recommendations Two recommendations addressed via correspondence in 2015 are included. First, immunohistochemistry (IHC) 2+ is defined as invasive breast cancer with weak to moderate complete membrane staining observed in > 10% of tumor cells. Second, if the initial HER2 test result in a core needle biopsy specimen of a primary breast cancer is negative, a new HER2 test may (not "must") be ordered on the excision specimen based on specific clinical criteria. The HER2 testing algorithm for breast cancer is updated to address the recommended work-up for less common clinical scenarios (approximately 5% of cases) observed when using a dual-probe ISH assay. These scenarios are described as ISH group 2 ( HER2/chromosome enumeration probe 17 [CEP17] ratio ≥ 2.0; average HER2 copy number < 4.0 signals per cell), ISH group 3 ( HER2/CEP17 ratio < 2.0; average HER2 copy number ≥ 6.0 signals per cell), and ISH group 4 ( HER2/CEP17 ratio < 2.0; average HER2 copy number ≥ 4.0 and < 6.0 signals per cell). The diagnostic approach includes more rigorous interpretation criteria for ISH and requires concomitant IHC review for dual-probe ISH groups 2 to 4 to arrive at the most accurate HER2 status designation (positive or negative) based on combined interpretation of the ISH and IHC assays. The Expert Panel recommends that laboratories using single-probe ISH assays include concomitant IHC review as part of the interpretation of all single-probe ISH assay results. Find additional information at www.asco.org/breast-cancer-guidelines .

Disease-free and overall survival at 3.5 years for neoadjuvant bevacizumab added to docetaxel followed by fluorouracil, epirubicin and cyclophosphamide, for women with HER2 negative early breast cancer: ARTemis Trial

Background

The ARTemis trial previously reported that addition of neoadjuvant bevacizumab (Bev) to docetaxel (D) followed by fluorouracil, epirubicin and cyclophosphamide (D-FEC) in HER2 negative breast cancer improved the pathological complete response (pCR) rate. We present disease-free survival (DFS) and overall survival (OS) with central pathology review.

Patients and methods

Patients were randomized to 3 cycles of D followed by 3 cycles of FEC (D-FEC), ±4 cycles of Bev (Bev + D-FEC). DFS and OS were analyzed by treatment and by central pathology reviewed pCR and Residual Cancer Burden (RCB) class.

Results

A total of 800 patients were randomized [median follow-up 3.5 years (IQR 3.2–4.4)]. DFS and OS were similar across treatment arms [DFS hazard ratio (HR)=1.18 (95% CI 0.89–1.57), P = 0.25; OS HR = 1.26 (95% CI 0.90–1.76), P = 0.19). Both local pathology report review and central histopathology review confirmed a significant improvement in DFS and OS for patients who achieved a pCR [DFS HR = 0.38 (95% CI 0.23–0.63), P < 0.001; OS HR = 0.43 (95% CI 0.24–0.75), P = 0.003]. However, significant heterogeneity was observed (P = 0.02); larger improvements in DFS were obtained with a pCR achieved with D-FEC than a pCR achieved with Bev + D-FEC. As RCB class increased, significantly worse DFS and OS was observed (P for trend <0.0001), which effect was most marked in the ER negative group.

Conclusions

The addition of short course neoadjuvant Bev to standard chemotherapy did not demonstrate a DFS or OS benefit. Achieving a pCR with D-FEC is associated with improved DFS and OS but not when pCR is achieved with Bev + D-FEC. At the present time therefore, Bev is not recommended in early breast cancer.

ClinicalTrials.gov number

NCT01093235.

Pancreatic cancer ascites xenograft-an expeditious model mirroring advanced therapeutic resistant disease

Pancreatic ductal adenocarcinoma has limited treatment options. There is an urgent need for developing appropriate pre-clinical models recapitulating metastatic disease, the most common clinical scenario at presentation. Ascites accumulation occurs in up to 20–30% of patients with pancreatic cancer; this milieu represents a highly cellular research resource of metastatic peritoneal spread. In this study, we utilized pancreatic ascites/pleural effusion cancer cells to establish patient derived xenografts.

Ascites/pleural effusion-patient derived xenografts were established from twelve independent cases. Xenografts were serially passed in nude mice and tissue bio-specimen banking has been established. Histopathology of emergent tumors demonstrates poorly to moderately differentiated, glandular and mucin producing tumors, mirroring morphology of primary pancreatic cancer tumors. Whole genome sequencing of six patient derived xenografts samples demonstrates common mutations and structural variations similar to those reported in primary pancreatic cancer. Xenograft tumors were dissociated to single-cells and in-vitro drug sensitivity screen assays demonstrated chemo-resistance, correlating with patient clinical scenarios, thus serving as a platform for clinically relevant translational research.

Therefore, establishment of this novel ascites/pleural effusion patient derived xenograft model, with extensive histopathology and genomic characterization, opens an opportunity for the study of advanced aggressive pancreatic cancer. Characterization of metastatic disease and mechanisms of resistance to therapeutics may lead to the development of novel drug combinations.

Tumor PIK3CA Genotype and Prognosis in Early-Stage Breast Cancer: A Pooled Analysis of Individual Patient Data

Purpose Phosphatidylinositol-4, 5-bisphosphate 3-kinase catalytic subunit alpha ( PIK3CA) mutations are frequently observed in primary breast cancer. We evaluated their prognostic relevance by performing a pooled analysis of individual patient data. Patients and Methods Associations between PIK3CA status and clinicopathologic characteristics were tested by applying Cox regression models adjusted for age, tumor size, nodes, grade, estrogen receptor (ER) status, human epidermal growth factor receptor 2 (HER2) status, treatment, and study. Invasive disease-free survival (IDFS) was the primary end point; distant disease-free survival (DDFS) and overall survival (OS) were also assessed, overall and by breast cancer subtypes. Results Data from 10,319 patients from 19 studies were included (median OS follow-up, 6.9 years); 1,787 patients (17%) received chemotherapy, 4,036 (39%) received endocrine monotherapy, 3,583 (35%) received both, and 913 (9%) received none or their treatment was unknown. PIK3CA mutations occurred in 32% of patients, with significant associations with ER positivity, increasing age, lower grade, and smaller size (all P < .001). Prevalence of PIK3CA mutations was 18%, 22%, and 37% in the ER-negative/HER2-negative, HER2-positive, and ER-positive/HER2-negative subtypes, respectively. In univariable analysis, PIK3CA mutations were associated with better IDFS (HR, 0.77; 95% CI, 0.71 to 0.84; P < .001), with evidence for a stronger effect in the first years of follow-up (0 to 5 years: HR, 0.73; 95% CI, 0.66 to 0.81; P < .001; 5 to 10 years: HR, 0.82; 95% CI, 0.68 to 0.99; P = .037); > 10 years: (HR, 1.15; 95% CI, 0.84 to 1.58; P = .38; P heterogeneity = .02). In multivariable analysis, PIK3CA genotype remained significant for improved IDFS ( P = .043), but not for the DDFS and OS end points. Conclusion In this large pooled analysis, PIK3CA mutations were significantly associated with a better IDFS, DDFS, and OS, but had a lesser prognostic effect after adjustment for other prognostic factors.

Characteristics and outcome of the COEUR Canadian validation cohort for ovarian cancer biomarkers

BACKGROUND

Ovarian carcinoma is the most lethal gynecological malignancy due to early dissemination and acquired resistance to platinum-based chemotherapy. Reliable markers that are independent and complementary to clinical parameters are needed to improve the management of patients with this disease. The Canadian Ovarian Experimental Unified Resource (COEUR) provides researchers with biological material and associated clinical data to conduct biomarker validation studies. Using standards defined by the Canadian Tissue Repository Network (CTRNet), we have previously demonstrated the quality of the biological material from this resource. Here we describe the clinical characteristics of the COEUR cohort.

METHODS

With support from 12 Canadian ovarian cancer biobanks in Canada, we created a central retrospective cohort comprised of more than 2000 patient tissue samples with associated clinical data, including 1246 high-grade serous, 102 low-grade serous, 295 endometrioid, 259 clear cell and 89 mucinous carcinoma histotypes. A two-step reclassification process was applied to assure contemporary histological classification (histotyping). For each histotypes individually, we evaluated the association between the known clinico-pathological parameters (stage, cytoreduction, chemotherapy treatment, BRCA1 and BRCA2 mutation) and patient outcome by using Kaplan-Meier and Cox proportional hazard regression analyses.

RESULTS

The median follow-up time of the cohort was 45 months and the 5-year survival rate for patients with high-grade serous carcinomas was 34%, in contrast to endometrioid carcinomas with 80% at 5 years. Survival profiles differed by histotype when stratified by stage or cytoreduction. Women with mucinous or clear cell carcinomas at advanced stage or with non-optimally debulked disease had the worst outcomes. In high-grade serous carcinoma, we observed significant association with longer survival in women harboring BRCA1 or BRCA2 mutation as compared to patients without detectable mutation.

CONCLUSIONS

Our results show the expected survival rates, as compared with current literature, in each histotype suggesting that the cohort is an unbiased representation of the five major histotypes. COEUR, a one stop comprehensive biorepository, has collected mature outcome data and relevant clinical data in a comprehensive manner allowing stratified analysis.

Characteristics and outcome of the COEUR Canadian validation cohort for ovarian cancer biomarkers

BACKGROUND

Ovarian carcinoma is the most lethal gynecological malignancy due to early dissemination and acquired resistance to platinum-based chemotherapy. Reliable markers that are independent and complementary to clinical parameters are needed to improve the management of patients with this disease. The Canadian Ovarian Experimental Unified Resource (COEUR) provides researchers with biological material and associated clinical data to conduct biomarker validation studies. Using standards defined by the Canadian Tissue Repository Network (CTRNet), we have previously demonstrated the quality of the biological material from this resource. Here we describe the clinical characteristics of the COEUR cohort.

METHODS

With support from 12 Canadian ovarian cancer biobanks in Canada, we created a central retrospective cohort comprised of more than 2000 patient tissue samples with associated clinical data, including 1246 high-grade serous, 102 low-grade serous, 295 endometrioid, 259 clear cell and 89 mucinous carcinoma histotypes. A two-step reclassification process was applied to assure contemporary histological classification (histotyping). For each histotypes individually, we evaluated the association between the known clinico-pathological parameters (stage, cytoreduction, chemotherapy treatment, BRCA1 and BRCA2 mutation) and patient outcome by using Kaplan-Meier and Cox proportional hazard regression analyses.

RESULTS

The median follow-up time of the cohort was 45 months and the 5-year survival rate for patients with high-grade serous carcinomas was 34%, in contrast to endometrioid carcinomas with 80% at 5 years. Survival profiles differed by histotype when stratified by stage or cytoreduction. Women with mucinous or clear cell carcinomas at advanced stage or with non-optimally debulked disease had the worst outcomes. In high-grade serous carcinoma, we observed significant association with longer survival in women harboring BRCA1 or BRCA2 mutation as compared to patients without detectable mutation.

CONCLUSIONS

Our results show the expected survival rates, as compared with current literature, in each histotype suggesting that the cohort is an unbiased representation of the five major histotypes. COEUR, a one stop comprehensive biorepository, has collected mature outcome data and relevant clinical data in a comprehensive manner allowing stratified analysis.

Recapitulating the clinical scenario of BRCA-associated pancreatic cancer in pre-clinical models

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies. BRCA-associated PDAC comprises a clinically relevant subtype. A portion of these patients are highly susceptible to DNA damaging therapeutics, however, responses are heterogeneous and clinical resistance evolves. We have developed unique patient-derived xenograft (PDX) models from metastatic lesions of germline BRCA-mutated patients obtained at distinct time points; before treatment and at progression. Thus, closely mimicking clinical scenarios, to further investigate treatment naïve and resistant patients. DNA was isolated from six BRCA-mutated PDXs and classified by whole-genome sequencing to stable-genome or homologous recombination deficient (HRD)-genome. The sensitivity to DNA-damaging agents was evaluated in vivo in three BRCA-associated PDAC PDXs models: (1) HRD-genome naïve to treatments; (2) stable-genome naïve to treatment; (3) HRD-genome resistant to treatment. Correlation between disease course at tissue acquisition and response to PARP inhibitor (PARPi)/platinum was demonstrated in PDXs in vivo. Only the HRD-genome PDX, naïve to treatment, was sensitive to PARP inhibitor/cisplatin treatments. Our results demonstrate heterogeneous responses to DNA damaging agents/PARPi in BRCA-associated PDX thus reflecting the wide clinical spectrum. An HRD-genome PDX generated from a naïve to treatment biopsy was sensitive to platinum/PARPi whereas no benefit was observed in treating a HRD-genome PDXs generated from a patient that had acquired resistance nor stable-genome PDXs.

Abstract OT1-06-01: OPTIMA: A prospective randomized trial to validate the predictive utility and cost-effectiveness of gene expression test-directed chemotherapy decisions in early breast cancer

Background: Multi-parameter gene expression assays (MPAs) are widely used to estimate individual patient residual risk in hormone-sensitive HER2-negative node-negative early breast cancer, allowing patients with low risk to safely avoid chemotherapy. Evidence for MPA use in node-positive breast cancer is limited. OPTIMA (Optimal Personalised Treatment of early breast cancer usIng Multi-parameter Analysis) aims to validate MPA's as predictors of chemotherapy sensitivity in a largely node-positive breast cancer population.

Methods: OPTIMA is a partially blinded multi-center, phase 3 randomized controlled trial with an adaptive two-stage design. The main eligibility criteria are women or men aged 40 or older with resected ER-positive, HER2-negative breast cancer and up to 9 involved axillary lymph nodes. Randomization is to standard management (chemotherapy and endocrine therapy) or to MPA-directed treatment. Those with a “high risk” tumor MPA score receive standard management whilst those at “low risk” are treated with endocrine therapy alone. The preliminary phase (OPTIMA prelim) evaluated the performance of several MPAs to select a test to be used in the main efficacy trial based on economic analysis, and assessed the feasibility and acceptability of a large UK trial. OPTIMA prelim used Oncotype DX as the primary discriminator; the main trial will use Prosigna (PAM50) with Prosigna Score ≤60 defined as “low-risk”. The co-primary outcomes are (1) Invasive Disease Free Survival (IDFS) and (2) cost-effectiveness of test-directed therapy. Secondary outcomes include IDFS in “low-risk” patients, quality of life and additional survival measures. An integrated qualitative recruitment study will identify and address challenges to recruitment and informed consent. Tumor blocks from all consenting participants will be banked allowing the performance of alternative MPA technologies to be evaluated. Recruitment of 4500 patients will permit demonstration of 3% non-inferiority of test-directed treatment, with 5% significance and 85% power, assuming 3 years follow-up and a control arm 5-year IDFS of at least 85%. The addition of patients from OPTIMA prelim will allow non-inferiority to be assessed with 2.5% significance.

Results: OPTIMA-prelim recruited 412 patients in 23 months from 35 sites with a 47% acceptance rate. The main study opened in January 2017. Early progress indicates that the recruitment target is achievable in the intended 46-month timescale through the participation of &gt;100 sites

Conclusion: OPTIMA, as one of two large scale prospective trials validating the use of test-guided chemotherapy decisions in node-positive early breast cancer, is expected to have a global impact on breast cancer treatment. Experience from OPTIMA prelim showed that patient advocate support and close engagement with sites will aid trial success.

Funding: The project is funded in the UK by the NIHR HTA Programme (10/34/501). Views expressed are those of the authors and not those of the HTA Programme, NIHR, NHS or the DoH.

Citation Format: Stein RC, Makris A, Hughes-Davies L, Macpherson IR, Hall PS, Cameron DA, Earl HM, Pinder SE, Poole CJ, Rea DW, McIntosh S, Harmer V, Morgan A, Rooshenas L, Conefrey C, Donovan JL, Hulme C, McCabe C, Stallard N, Campbell A, Higgins H, Bartlett JMS, Marshall A, Dunn JA. OPTIMA: A prospective randomized trial to validate the predictive utility and cost-effectiveness of gene expression test-directed chemotherapy decisions in early breast cancer [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr OT1-06-01.

Abstract P1-06-02: Comparative survival analysis of multiparametric tests in the TEAM pathology study: What to do when molecular tests disagree?

Multiparametric assays for risk are increasingly used in the management of node-negative and node-positive hormone receptor-positive invasive breast cancer. Data from multiple sources suggests different tests may provide different risk estimates at the individual patient level1. Analysis from the TEAM pathology study (Bayani and Yao et al npjBreast Cancer, 2017) allows direct comparison of prognostic information from gene signatures in a clinical trial cohort of postmenopausal patients. Risk classifications using genes comprising the following multi-parametric tests: OncotypeDx® (Genomic Health Inc.)2,3, Prosigna™(NanoString Technologies, Inc.)4-6, Mammaprint® (Agendia Inc.)7,8 were performed. For the OncotypeDX-Like Recurrence Score (RS), RNA abundance was processed to fit the measurement range as described2,3, with classification into high, intermediate or low risk groups based the derived RS and modeled for DRFS. For the Prosigna-Like Risk of Recurrence Score (ROR), samples were processed as previously outlined9, then modelled against DRFS. For the MammaPrint-Like Risk Score, samples were processed by published methods8 and modelled for DRFS. Comparing OncotypeDx-Like with Prosigna-Like showed that 45% of cases were classified identically by both (3.3% low risk, 20.9% intermediate, 20.7% high). Of 3370 cases, 353 (10.5%) had scores differing by more than 1 classification (i.e. hi/low or low/high). Almost all (343) of these were cases classified high risk by OncotypeDX-Like RS/low risk by Prosigna-Like ROR (Table 1). Univariate Cox regression analysis, using low/low cases as a reference (relative risk of distant metastasis =1.0), suggested that cases called low risk by Prosigna-Like ROR/High risk by OncotypeDx-Like RS did not perform differently from cases called low risk by both tests (Table 2). However, all cases called intermediate by one test and high risk by another appeared to be high risk (Table 2). Comparisons between Prosigna-Like ROR and MammaPrint-Like scores showed similar concordance between low/low and high/high (52.5% of cases with concordant results). In Prosigna-Like ROR intermediate risk cases, MammaPrint-Like results divided cases between low and high risk, as predicted. Comparisons between these tests is challenging, and evidence on their discordance in risk stratification presents further dilemmas. Preliminary analysis of TEAM suggests a complex inter-relationship between test results in the same patient cohorts requiring careful evaluation.

Table 1OncotypeDX-Like RSLowInt.HighTotalLow1126163431071Prosigna-Like RORInt.1677046151486High10106697813Total289142616553370

Table 2OncotypeDX-Like RSLowInt.HighLowRef1.26 (0.57-2.79)1.13 (0.49-2.62)Prosigna-Like RORInt.1.2 (0.47-3.05)2.22 (1.03-4.78)4.27 (2.01-9.08)High6.10 (1.58-23.6)4.15 (1.79-9.59)4.92 (2.32-10.42)

Citation Format: Bartlett JMS, Bayani J, Kornaga E, Piper T, Mallon E, Yao CQ, Boutros PC, Hasenburg A, Kieback DG, Markopoulos C, Dirix L, Seynaeve C, Can de Velde CJH, Rea DW. Comparative survival analysis of multiparametric tests in the TEAM pathology study: What to do when molecular tests disagree? [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P1-06-02.

Abstract P2-10-01: Validation that a histone gene signature predicts anthracycline response in early breast cancer

Background: The use of anthracycline-based chemotherapies has improved overall and disease free survival in breast cancer. However, anthracyclines can have significant toxicities including cardiotoxicity and leukemia. It is, therefore, imperative to identify those patients who will benefit from adjuvant anthracycline treatment and patients who could be spared unnecessary toxicities and be considered for alternative adjuvant therapy. Previous work performed by our laboratory identified a histone gene expression signature as a predictive marker of anthracycline benefit in the BR9601 clinical trial. In this study we validate the 18 histone gene signature in the MA.5 clinical trial and examine the role of the signature in individual intrinsic subtypes of breast cancer.

Methods We analysed the CCTG MA.5 clinical trial in a prospectively planned retrospective biomarker approach to validate this signature and tested the role of intrinsic subtyping as predictive markers of anthracycline benefit. RNA was extracted from patients in the MA.5 adjuvant trial evaluating the addition of epirubicin (E) to CMF and analysed using NanoString technology. Log-rank analyses validated the predictive values of the signature on distant relapse-free survival (DRFS). Cox-regression models tested independent predictive value on DRFS in the presence of treatment, age, tumour size, nodal status, HER2, ER status and grade, and treatment by marker interactions.

Results Analysis of the MA.5 clinical cohort revealed that patients whose tumour had low histone gene signature expression experienced increased DRFS (HR: 0.54, 95% CI 0.38-0.76, p=0.001) when treated with CEF compared with patients treated with CMF alone. Conversely, there was no apparent benefit of CEF vs CMF in patients with high histone gene expression signature (HR: 1.01, 95%CI 0.66-1.55, p=0.963). After multivariate analysis and adjustment for HER2, nodal status, age, grade and ER, the treatment by marker interaction for the gene signature was 0.54 (95%CI 0.31-0.94, p=0.030) for DRFS.

The predictive impact of the histone signature was independent of intrinsic subtype.

Conclusion The histone gene expression signature is an independent predictor of anthracycline benefit and could be a potential candidate diagnostic assay for patients with early breast cancer.

Citation Format: Spears M, Kornaga E, Lyttle N, Liao L, Bayani J, Quintayo M-A, Yao CQ, D'Costa A, Boutros PC, Twelves CJ, Pritchard KI, Levine MN, Nielsen TO, Shepherd L, Bartlett JMS. Validation that a histone gene signature predicts anthracycline response in early breast cancer [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P2-10-01.