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.

Abstract 2698: Spatial gene expression profiling in breast cancer

Over the last decade breast cancer survival has improved, largely due to the therapies offered to patients with the disease. However, despite the advances in diagnosis and treatment of breast cancer, it is still remains the second leading cause of death from cancer in women. Breast cancer is a heterogeneous disease, this in part, explains why the majority of current therapeutic approaches for cancer work best when multiple agents are combined. The interaction between immune and tumor cells is critical in the development and progression of breast cancer. Here we present in situ transcriptomic profiling, using the NanoString Digital Spatial Profiler (DSP) cancer transcriptomic atlas (CTA) assay, of a cohort of breast cancer lumpectomies to reveal the extent of heterogeneity in pathologically defined unifocal and multifocal cancers. In this study, lumpectomies were processed as whole mounts with serial blocks reviewed. Tissue cores were taken from at least three different regions through the lumpectomy for tissue microarray (TMA) construction, focusing on morphologic/histological differences in addition to the spatial orientation of the sampled region within the lumpectomy. In situ quantification of 1800 tumor and immune genes across 60 patients revealed heterogeneity of tumor and immune genes in most patients. Expression of genes such as HER2, ER and AKT were enriched in the tumor compartment. Whereas, genes such as COLA1, CD68 and CD3 were enriched in the immune compartment. Using a SpatialDecon algorithm for mixed cell deconvolution on the immune areas heterogeneity of the tumor infiltrate at a cell type levels was observed. Fibroblasts and macrophages were prevalent in all samples while immune dense areas also contained B-cells and T-cells. While there are a number of clinically validated transcriptional assays available for breast cancer, we have demonstrated that the immune microenvironment needs to be considered to develop rational stratification of patients to currently available targeted therapies.

Citation Format: Melanie Spears, Vida Talebian, Linda Liao, Megan Hopkins, Drashti Jain, Mary Anne Quintayo, Jane Bayani, Alison Cheung, Martin Yaffe, John M. Bartlett. Spatial gene expression profiling in breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2698.

Abstract 3131: Tumour spatial heterogeneity in breast cancer and the impact on clinical management

We recognize that many cancers are highly complex mixtures of sub-populations of cells, which are also influenced by their microenvironment. This heterogeneity explains in part, why the majority of current therapeutic approaches for cancer work best when multiple agents are combined. Therefore, in an era of targeted therapeutics it becomes critical to understand the complexity of tumors both at diagnosis and over the course of therapy, including measures of heterogeneity. Here we present genomic, transcriptomic and in situ proteomic profiling of a cohort of breast cancer (BCa) lumpectomies to reveal the extent of heterogeneity in pathologically defined unifocal and multifocal cancers. Integration of molecular profiling, phylogenetic analyses and radiomics has the potential to significantly improve BCa clinical management and stratification to targeted therapies that are already available in the clinic. In this study, lumpectomies with imaging data were processed as whole mounts with serial blocks reviewed. Tissue cores were taken from at least three different regions through the lumpectomy for nucleic acid extraction and tissue microarray (TMA) construction, focusing on morphologic/histological differences in addition to the spatial orientation of the sampled region within the lumpectomy. Targeted sequencing using the Oncomine Comprehensive Assay v3 (OCAv3); transcriptional profiling using the NanoString Breast Cancer 360 Panel; in situ profiling by multiplex fluorescence immunohistochemistry (MxIF) and Digital Spatial Profiling (see abstract Spears et al) were performed. From this cohort of 60 patients, we present a subset of patients demonstrating integration of the molecular profiling to reveal the phylogenetic relationship between the multiple samplings and the impact on clinical decision making in BCa. Briefly, we identified differences in the molecular subtypes between the different sample regions from the same unifocal cancer as well as differences in the predicted responses to anti-PDL1 therapy by transcriptional profiling; while targeted sequencing of driver mutations suggested the likelihood of an ancestral tumor cell giving rise to the lesions in pathologically defined multifocal cancers. However it was evident that genes and pathways found to be aberrant in these different lesions from the same cancer could impact the response to standard BCa treatment, or the selection of targeted therapies. In situ proteomics demonstrated differences in the expression of standard BCa markers ER, PgR, HER2 and Ki67 in addition to immune markers in the tumor and tumor microenvironment. While there are clinically validated transcriptional risk test available for BCa, we have demonstrated that transcriptomics or genomics alone is insufficient for a rational stratification of patients to currently available targeted therapies; therefore supporting the need for an integrative approach.

Citation Format: Jane Bayani, Quang M. Trinh, Mary Anne Quintayo, Cheryl Crozier, Megan Hopkins, Jingping Qiao, Alison Cheung, James Mainprize, Quaid Morris, Melanie Spears, Martin Yaffe, Lincoln Stein, John M. Bartlett. Tumour spatial heterogeneity in breast cancer and the impact on clinical management [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 3131.

Abstract PO-002: Revealing tumour spatial heterogeneity in breast cancer and the impact on clinical management

Many cancers are highly complex mixtures of many sub-populations of cells, also influenced by their microenvironment. This heterogeneity explains, in part, why the majority of current therapeutic approaches for cancer work best when multiple agents are combined. Therefore, in an era of targeted therapeutics it becomes critical to understand the complexity of tumours both at diagnosis and over the course of therapy, including measures of heterogeneity. Here we present genomic, transcriptomic and in situ proteomic profiling of a cohort of breast cancer (BCa) lumpectomies with associated imaging data to reveal the extent of heterogeneity in pathologically defined unifocal and multifocal cancers. Integration of molecular profiling, phylogenetic analyses and radiomics has the potential to significantly improve BCa clinical management and stratification to targeted therapies that are already available in the clinic. In this study, lumpectomies were processed as whole mounts with serial blocks reviewed. Tissue cores were taken from at least three different regions throughout the lumpectomy for nucleic acid extraction and tissue microarray (TMA) construction, focusing on morphologic/histological differences in addition to the spatial orientation of the sampled region within the lumpectomy. Targeted sequencing using the Oncomine Comprehensive Assay v3 (OCAv3); transcriptional profiling using the NanoString Breast Cancer 360 Panel; and in situ profiling by multiplex fluorescence immunohistochemistry (MxIF) performed (see abstract Cheung et al). From this cohort of 60 patients, we present a subset of patients demonstrating integration of the molecular profiling to reveal the phylogenetic relationship between the multiple samplings and the potential impact on clinical decision making in BCa. We identified differences in the molecular subtypes between the different sample regions from the same unifocal cancer as well as differences in the predicted responses to anti-PDL1 therapy by transcriptional profiling. Targeted sequencing of driver mutations suggested the likelihood of an ancestral tumour cell giving rise to the lesions in pathologically defined multifocal cancers; however it was evident that genes and pathways found to be aberrant in these different lesions from the same cancer could impact the response to standard BCa treatment, or the selection of targeted therapies. In situ proteomics demonstrated differences in the expression of standard BCa markers ER, PgR, HER2 and Ki67, in addition to immune markers in the tumour and its microenvironment. While there are clinically validated transcriptional risk tests available for BCa, we have demonstrated that transcriptomics or genomics alone is insufficient for a rational stratification of patients to currently available targeted therapies, therefore, supporting the need for an integrative approach.

Citation Format: Jane Bayani, Quang M. Trinh, Mary Anne Quintayo, Cheryl Crozier, Megan Hopkins, Jingping Qiao, Alison Cheung, James G Mainprize, Quaid Morris, Melanie Spears, Martin J. Yaffe, Lincoln D. Stein, John M.S. Bartlett. Revealing tumour spatial heterogeneity in breast cancer and the impact on clinical management [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PO-002.

Abstract P3-08-22: The mutational landscape of cancer driver genes in matched primary ductal carcinoma in situ and recurrent ductal carcinoma in situ or recurrent invasive cancers

Due to breast screening, ductal carcinoma in situ (DCIS) accounts for approximately 25% of all newly diagnosed breast neoplasms. Believed to be a precursor to invasive carcinoma, a significant number of patients diagnosed with DCIS are effectively managed by surgery alone or in conjunction with radiotherapy and endocrine therapy. In general, there is an 8-11% relative risk for a subsequent invasive carcinoma over a period of 10 year, with 98% breast cancer-specific survival after 10 years of follow up. Although mastectomy, breast conserving surgery, and radiotherapy can reduce the risk of recurrence, there are ongoing lifetime consequences of treatment. Thus, there is a clinical need to identify those patients who are at risk of an invasive recurrence from those who might not recur or experience a subsequent DCIS recurrence. In this study, 60 patients with pure primary DCIS, treated with only with breast conserving therapy, across three different clinical outcome groups were examined: patients who did not experience a recurrence within 5 years (n=20); patients who experienced a recurrent DCIS within 5 years (n=20); and patients that recurred with an invasive cancer within 5 years (n=20). Pure primary DCIS lesions, as well as the matched DCIS recurrence or invasive recurrence, were macrodissected from formalin fixed paraffin embedded tissues and subjected to nucleic acid extraction. All samples were profiled using Thermo Fisher Scientific’s validated targeted sequencing panel, the Oncomine Comprehensive Assay v3.0 (OCAv3.0). This assay is comprised of common cancer driver genes shown to be prognostic and predictive to targeted therapies in use or in late-phase clinical trials, and is currently being used in the NCI-MATCH trial (NCT02465060). While the OCA panel and accompanying Oncomine Knowledgebase Reporter provides information regarding the targeted treatments linked to known actionable mutations, this study utilized all somatic mutations and copy number changes to reveal the genomic landscape of DCIS and their matched recurrences across these pan-cancer driver genes Amongst all primary DCIS samples across the three different clinical outcome groups, PIK3CA, was frequently found to be affected by SNV and Indels (32.8%) in addition to TP53 (26.2%), NF1 (21.3%), CREBBP (16.4%), ATM (14.8%), PALB2 (14.8%). DNA repair genes, including CHEK1, RAD50, RAD51B, MRE11A, BRCA1 and BRCA2, were found to be frequently subject to mutation in these primary DCIS samples ranging from 5%-15%. Similarly, copy number gains were frequently detected in HER2 (26.2%), CDK12 (18%), FGFR1 (4.9%), GNAS (4.9%), MYC, CCNE1, AR, RAD51C and RNF43 (1.6% each), and loses at H3F3A and KNSTRN (each 1.6%). Matched primary DCIS and their recurrent DCIS or invasive lesions exhibited similar changes with invasive cancers suggesting that in some cases, the primary DCIS gives rise to the invasive cancer. We will present the preliminary findings mapping the mutational and copy-number landscape of primary DCIS and matched recurrences to identify putative genomic changes defining these clinical outcome groups and to investigate the genomic progression of DCIS to invasive carcinoma.

Citation Format: Jane Bayani, Quang M Trinh, Mary Anne Quintayo, Cheryl Crozier, Ilinca Lungu, Dan Dion, Joema Felipe-Lima, Giancarlo Pruneri, Jonas Bergh, Fredrik Warnberg, Giuseppe Viale, Lincoln D Stein, John MS Bartlett. The mutational landscape of cancer driver genes in matched primary ductal carcinoma in situ and recurrent ductal carcinoma in situ or recurrent invasive cancers [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P3-08-22.

Abstract P5-02-01: Analytical validation and prognostic potential of an automated digital scoring protocol for Ki67: An International Ki67 Working Group study

Background: The nuclear proliferation biomarker Ki67 has multiple potential roles in breast cancer, including aiding decisions based on prognosis, but has unacceptable between-laboratory variability. Here we tested an open source and calibrated automated digital image analysis (DIA) platform to: (i) Assess inter-laboratory reproducibility of automated Ki67 measurement among 17 participating labs and compare those with standardized pathologist-based visual scoring. (ii) Investigate the comparability of Ki67 measurement across corresponding core biopsy and whole section cases. (iii) Test prognostic potential of the built Ki67 scoring algorithms on an independent cohort.

Methods: Two sets of 60 previously stained slides containing 30 core-cut biopsy and 30 corresponding whole tumor sections from 30 ER+ breast cancer cases were sent to 17 participating labs for automated assessment of average Ki67 expression. The blocks were centrally cut and stained for Ki67 using the Mib-1 antibody. The QuPath (open-source software) DIA platform was used to evaluate tumoral Ki67 expression. Calibration of the DIA method was performed in our previous study (Acs et al, Lab Invest 2019). A detailed guideline for building an automated Ki67 scoring algorithm was sent to the participating labs. Visual scoring of average Ki67 expression was performed by pathologists according to published standardized methods (Leung et al, NPJ Br Cancer 2016; Leung et al, Histopath 2019). Locked down DIA Ki67 scoring algorithms were applied to a validation cohort: 222 breast cancer cases from the Karolinska University Hospital in whole section format. Sufficient reproducibility to declare analytical validity was defined as an Intra Class Correlation (ICC) with lower limit of 95% credible interval (CI) >0.80. Markov Chain Monte Carlo routines for generalized linear mixed models were used to estimate ICCs and calculate corresponding CIs.

Results: The same-section ICC was 0.902 (CI: 0.852-0.949) across 17 labs using calibrated DIA platform on core biopsy slides and 0.845 (CI: 0.778-0.912) on whole sections. The different-section ICC across the 17 labs was 0.873 (CI: 0.806-0.932) scoring on core biopsy slides and 0.777 (CI: 0.670-0.874) on whole sections. The pathologist-based visual Ki67 scoring showed ICC of 0.860 for all comparisons, respectively (CI: 0.795-0.927). Similar to what was observed for visual Ki67 scoring, the DIA scores are higher for core biopsy slides compared to paired whole sections (p≤0.001; median difference: 5.31%; IQR: 11.50%). Ki67 scores of all locked down DIA algorithms correlates significantly (p≤0.023) with outcome on the validation cohort (observed hazard ratios range: 2.518-2.922).

Conclusions: Automated Ki67 evaluation using a calibrated, open-source DIA platform (QuPath) met the pre-specified criterion of success on core biopsies but not on whole sections in the multi-institutional setting. The systematic discrepancy between core biopsy and corresponding whole sections was likely due to pre-analytical factors (tissue handling, fixation) and intratumor heterogeneity. We found that different algorithms built according to calibrated DIA methods had similar prognostic potential. Assessment of clinical utility is planned.

Citation Format: Balazs Acs, Samuel C.Y. Leung, Kelley M. Kidwell, Indu Arun, Renaldas Augulis, Sunil S. Badve, Yalai Bai, Anita L. Bane, John M.S. Bartlett, Jane Bayani, Gilbert Bigras, Annika Blank, Signe Borgquist, Henk Buikema, Martin C. Chang, Robin L. Dietz, Andrew Dodson, Anna Ehinger, Susan Fineberg, Cornelia M. Focke, Dongxia Gao, Allen M. Gown, Carolina Gutierrez, Johan Hartman, Judith C. Hugh, Zuzana Kos, Anne-Vibeke Lænkholm, Arvydas Laurinavicius, Richard M. Levenson, Rustin Mahboubi-Ardakani, Mauro G. Mastropasqua, Takuya Moriya, Sharon Nofech-Mozes, C. Kent Osborne, Liron Pantanowitz, Frédérique M. Penault-Llorca, Tammy Piper, Mary Anne Quintayo, Tilman T. Rau, Stefan Reinhard, Stephanie Robertson, Takashi Sakatani, Roberto Salgado, Melanie Spears, Jane Starczynski, Tomoharu Sugie, Bert van der Vegt, Giuseppe Viale, Shakeel Virk, Lila A. Zabaglo, Daniel F. Hayes, Mitch Dowsett, Torsten O. Nielsen, David L. Rimm, International Ki67 in Breast Cancer Working Group, BIG-NABCG. Analytical validation and prognostic potential of an automated digital scoring protocol for Ki67: An International Ki67 Working Group study [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P5-02-01.

Abstract P1-10-08: Assessing immune biomarkers of response to anthracyclines in breast cancer

Background: Pathologists have long recognized that the interaction between immune and tumour cells is critical in the development and progression of breast cancer. Studies have demonstrated the presence of tumour-infiltrating lymphocytes (TILs) correlates with improved clinical outcome in breast cancer especially in the triple negative and HER-2 positive subtypes. TILs predict for improved response to certain therapies including chemotherapy and trastuzumab. The predictive value of TILs in ER positive tumours is less clear. It has been demonstrated the higher presence of the immune microenvironment is associated with a better prognosis and as a result a higher likelihood of benefit from chemotherapy and possibly from immunotherapy, whereas cold immune microenvironment carries greater risk of relapse and lower benefit from chemotherapy and possibly immuno-therapies. In this study, we evaluated whether TILs could be used to predict chemotherapy response and characterize the pre-existing tumour microenvironment (TME) using NanoString’s GeoMx Digital Spatial Profiling (DSP) platform.

Methods: We assessed haematoxylin and eosin stained slides from the phase III BR9601 adjuvant breast cancer trial using software used in the international ring study 2 for standardized evaluation of TILs integrated in VMscope slide explorer. Evaluation of stromal TILs was based on international guidelines. NanoString’s DSP platform was used to analysis 256 patient samples from the BR9601 clinical trial. For analysis, region of interest were selected and compared for the TME (CD45+ve) and tumour rich (pan cytokeratin) in tissue microarrays. A panel of 56-antibodies were analysed in each ROI.

Results: The mean TIL score in this cohort of patients was 15.58% (ranging from 0 to 66.67%). The presence of higher levels of TILs was significantly associated with ER negativity (p<0.001), high grade (p=0.01) and increased lymph nodal involvement (p=0.002). In multivariate analysis, patients whose tumours had medium/high levels of TILS expression had better DRFS (HR: 0.49, 95%CI 0.24-1.02, p=0.057) when treated with E-CMF than those treated with CMF alone. Highest levels of TILs were found in Basal and HER2-like tumours. A T-cell score was generated using the average expression of CD3, CD4 and CD8. The T-cell score was examined in both the tumour and TME. Using the T cell score it was apparent that the cohort had a range of immune “hot” and immune “cold” tumours. It was demonstrated that immune “hot” TME doesn’t not always correlate with immune “hot” tumour expression. Proteins that were most associated with T-cell exclusion (p<0.01) in the TME were Fibronectin, B7-H3, PTEN, ER-α, TGFB1, FAPα and CD34. This would indicate that these proteins are causal inhibitors of T-cell invasion.

Conclusion: In conclusion, this study highlights the significance of assessing the entire tumour since TILs, tumour and stromal cells collectively engage in a complex interplay that contributes to disease development and progression. NanoString’s GeoMx DSP is a promising technology for multiplexed analysis. TILs, whether measured using automated software, or estimation by protein profiling, are predictive of chemotherapy benefit.

Citation Format: Melanie Spears, Carsten Denkert, Sonia L Villagas, Nicola Lyttle, Linda Liao, Mary Anne Quintayo, Christopher J Twelves. Assessing immune biomarkers of response to anthracyclines in breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P1-10-08.

Abstract P2-09-17: Evaluation of the oncomine comprehensive assay for the identification of actionable mutations for therapeutic stratification from the TEAM pathology cohort

Large-scale sequencing initiatives have revealed a wealth of common and novel variants as well as copy-number aberrations, across different malignancies. This growing list of variants/aberrations can sometimes be matched to specific therapeutics. Such “actionable mutations/changes” hold promise for personalized treatment in the future, with treatments tailored to molecular abnormalities. Presently, women with hormone positive early breast cancer continue to experience improved survival on adjuvant anti-hormone therapy, but a significant number of women continue to progress. Therefore, there is a need to identify those women for whom current therapies are insufficient and to identify alternative therapeutic interventions. We explored the used of genetic profiling using a comprehensive solid tumor next generation sequencing (NGS) assay (the Oncomine Comprehensive Assay, OCA) to characterize early invasive breast cancer. The OCA is based on the Ion Torrent™ NGS platform and Ion AmpliSeq™ library preparation technology, coupled to the Oncomine™ Knowledgebase, for target selection, variant calling, and data annotations. The OCA includes 87 genes for hotspot mutation detection, 48 genes for full length sequencing and 43 genes for focal copy number assessment. The OCA provides a standardized informatics workflow and quality control (QC) parameters to process samples in a translational clinical research setting. To explore the application of the OCA to early invasive breast cancers, we performed a retrospective pilot study in a subset of cases from the TEAM trial. From the TEAM pathology samples, 420 were chosen in a case-control fashion, 413 samples were analyzed, 388 samples passed standard QC metrics, and 254 samples (65%) were found to contain 368 variants with Oncomine Knowledgebase annotations. Briefly, variants of PIK3CA were most frequent at 42.7% (157/368), followed by TP53 at 27.2% (100/368), PTEN at 5.7% (21/368), BRCA2 at 3.8% (14/368), SF3B1 (12/368), AKT1 (11/368) and PTCH1 (11/368) at 3.3%, 3.0%, 3.0%; respectively. Other variants were detected in ATM, ERBB2, RB1, FGFR2, NF1, CDKN2A, PIK3R1 and others. Amongst the 43 genes assessed for copy-number, 23 showed copy-number changes across 132 samples totalling 167 CNVs. 256 samples showed no copy-number alterations in any of the genes on the panel. ERBB2 was most frequently altered at 28.1% (47/167), followed by FGFR1 at 23.4% (39/167), CCND1 at 15.0% (25/167) and MDM2 at 10.2% (17/167). Copy-number losses were identified in TP53, RB1, PTEN, BRCA2 at 0.6% each; as well as CDKN2A at 1.8% (3/167). Analytical validation of a subset of gene variants and copy-number changes will be presented in addition to the evidence of potential future application of the Oncomine Comprehensive Assay to precision oncology goals.

Citation Format: Bayani J, Crozier C, Quintayo MA, Amemiya Y, Zhang X, Larivière M, Sadis S, Smith JM, Hasenburg A, Kieback D, Markopoulos C, Dirix L, Yaffe M, Seth A, Feilotter H, Rea D, Bartlett JMS. Evaluation of the oncomine comprehensive assay for the identification of actionable mutations for therapeutic stratification from the TEAM pathology cohort [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 P2-09-17.

Abstract P1-05-27: Evaluation of the Oncomine focus and comprehensive assays for therapeutic stratification in early hormone receptor positive breast cancers

Large-scale sequencing initiatives have revealed a wealth of common and novel variants as well as copy-number aberrations, across different solid tumours and hematological malignancies. The growing list of variants/aberrations can sometimes be matched to specific therapeutics. Such “actionable mutations/changes” hold promise for personalized treatment, as treatments could be tailored to molecular abnormalities, rather than disease site. In breast cancer, women with hormone positive early breast cancer continue to experience improved survival on adjuvant anti-hormone therapy, but even today, a significant number of women continue to progress. Therefore there is not only a need to identify those women for whom current therapies are insufficient, but to identify alternative therapeutic interventions. The ThermoFisher Scientific Oncomine™ Focus and Oncomine™ Comprehensive Assays (OFA and OCA) are based on the Ion Torrent™ next-generation sequencing platform and Ion AmpliSeq™ library preparation technology, coupled to the Oncomine™ Knowledgebase, for target selection, variant calling, and data annotations. Both panels interrogate the most referenced oncology biomarker variants that are matched to curated published evidence from clinical trials supporting the matching of driver genetic variants with relevant potential clinical therapeutic options. The ability to identify SNVs, CNVs and fusion events in a single assay provides an unprecedented approach to maximizing the molecular information to be derived from a single tumour sample. To explore the value of the Oncomine™ assays in early invasive breast cancers, we have performed a pilot study to assess the reproducibility and accuracy of the OFA and OCA from nucleic acids extracted from formalin-fixed paraffin embedded tissues. In addition to the sequencing and copy-number data generated by these assays, we will compare these results to copy-number information generated using the Oncoscan® (Affymetrix)copy-number assay as well as information derived by Multiplex Ligation-dependent Probe Amplification-based panels (MRC-Holland) and Fluorescent in situ Hybridization (FISH). Our preliminary analyses of 35 invasive breast cancers by Oncoscan® identified the frequent whole chromosomal gains of 2, 3, 5, 7, 18, 19 and 20; gains of 1q, 7p, 8q, 11p, 16p, 17q; losses at 1p, 8p, 11q, 13, 16q, 17p and chromosome 18. High level amplifications were also identified for breast cancer related genes such as ERBB2, CCND1, MYC, FGFR1; in addition to the frequent losses of TP53, RB1, CDKN2A. Copy-number changes were confirmed by locus-specific FISH and MLPA. Data generated from the OFA and OCA from these same samples will be compared to the other platform findings and provide a snapshot of the mutational landscape of early breast cancers across these pan-cancer panels. Having established the robustness and accuracy of the assays, the applicability of the OCA in the context of improved stratification for breast cancers for prognostic and predictive tests will be discussed.

Citation Format: Bayani J, Crozier C, Zhang NX, Amemiya Y, Quintayo MA, Yan FJ, Dion D, Mccormack S, Yaffe M, Seth A, Feilotter H, Bartlett JMS. Evaluation of the Oncomine focus and comprehensive assays for therapeutic stratification in early hormone receptor positive breast cancers [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P1-05-27.

Molecular stratification of early breast cancer identifies drug targets to drive stratified medicine

Many women with hormone receptor-positive early breast cancer can be managed effectively with endocrine therapies alone. However, additional systemic chemotherapy treatment is necessary for others. The clinical challenges in managing high-risk women are to identify existing and novel druggable targets, and to identify those who would benefit from these therapies. Therefore, we performed mRNA abundance analysis using the Tamoxifen and Exemestane Adjuvant Multinational (TEAM) trial pathology cohort to identify a signature of residual risk following endocrine therapy and pathways that are potentially druggable. A panel of genes compiled from academic and commercial multiparametric tests as well as genes of importance to breast cancer pathogenesis was used to profile 3825 patients. A signature of 95 genes, including nodal status, was validated to stratify endocrine-treated patients into high-risk and low-risk groups based on distant relapse-free survival (DRFS; Hazard Ratio = 5.05, 95% CI 3.53-7.22, p = 7.51 × 10-19). This risk signature was also found to perform better than current multiparametric tests. When the 95-gene prognostic signature was applied to all patients in the validation cohort, including patients who received adjuvant chemotherapy, the signature remained prognostic (HR = 4.76, 95% CI 3.61-6.28, p = 2.53× 10-28). Functional gene interaction analyses identified six significant modules representing pathways involved in cell cycle control, mitosis and receptor tyrosine signaling; containing a number of genes with existing targeted therapies for use in breast or other malignancies. Thus the identification of high-risk patients using this prognostic signature has the potential to also prioritize patients for treatment with these targeted therapies.

Abstract P1-05-01: The epithelial to mesenchymal transition: Identifying a signature of recurrence in ductal carcinoma in situ

Background: The epithelial to mesenchymal transition (EMT) plays a critical role in the progression from non-invasive to invasive breast carcinomas (IBC). It is characterized by alterations in gene expression, changes in cellular polarity, the disruption of tight junctions; production of metalloproteinases, transforming growth factor-β (TGFβ) induction, expression of cancer stem cell markers, hypoxia, decrease in e-cadherin expression, along with other molecular biological events. Several transcription factors including ZEB1/2, TWIST1, SNAIL1/2, FOX family, GATA4/6 are involved in the process. There is a need to identify the molecular events driving the progression of ductal carcinoma in situ (DCIS); and to derive a signature that differentiates DCIS lesions that have the potential to recur as a subsequent DCIS, an IBC, or to not recur. To catalog the changes associated with EMT that may reveal a clinically relevant signature of progression from DCIS to DCIS or IBC recurrences using a panel of 200 genes related to EMT.

Methodology: RNA was extracted from formalin-fixed paraffin embedded (FFPE) sections of pure primary DCIS lesions representing three categories of outcome: those that did not recur; those that recurred with a subsequent DCIS; and those that recurred with invasive cancer. RNA abundance profiling was performed using Nanostring platform and data processing using an R statistical environment. Levels of mRNA abundance were modelled as a function of recurrence status. Coefficients were fit to terms representing the effect and the standard errors of the coefficient were adjusted with an empirical Bayes moderation. Model-based t-tests were then used to test if the coefficients were significantly different from zero.

Results: Using a technical control sample, pairwise comparisons across three replicates showed high correlation (ρ=0.99, Pρ<2.2x10-16 for all 3 comparisons), suggesting the robustness of the assay. In our preliminary survey of 45 patients across the three groups, we have identified a number of genes that showed differential mRNA abundance levels between patients who recurred (either DCIS or invasive recurrence) vs. those who did not recur. Using Random Forest analysis in a leave-one-out cross-validation approach, we were able to obtain a classifier with a sensitivity of 82% and specificity of 58%. Based on these initial findings, an additional 200 samples have been processed to support these initial findings.

Conclusion: The current literature provided increasing evidence that transcriptomic patterns reflecting the EMT may reveal novel biomarkers and elucidate molecular mechanisms leading to improved prognosis. Among breast carcinomas, differential expression of the EMT genes has been associated with a worse outcome, among estrogen receptor-negative and basal-like carcinomas. However, the understanding of the role of EMT genes in DCIS is limited; therefore, to elucidate whether the EMT plays a role in the progression of DCIS, we have designed an EMT gene panel that also includes genes that are significant prognosticators for IBC, including ER, PgR, Ki67 and HER2. In an exploratory analysis of cases trained based on clinical outcome, the sensitivity for predicting recurrence (whether DCIS or invasive) was 82%.

Citation Format: Felipe Lima J, Yao CQ, Yan F, Dion D, Quintayo MA, Lungu I, Nofech-Mozes S, Pruneri G, Viale G, Boutros PC, Bartlett JMS, Bayani J. The epithelial to mesenchymal transition: Identifying a signature of recurrence in ductal carcinoma in situ. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P1-05-01.

Abstract P2-08-29: Defining a signature of residual risk following endocrine treatment in the tamoxifen and exemestane adjuvant multinational (TEAM) trial

Introduction: There are a number of commercially-available tests to stratify risk for women diagnosed with early breast cancer. While such "Generation I" tests are increasingly being used, a consensus is growing that these tests are moderately accurate in assessing risk. Moreover, Generation I tests fail to direct more personalized treatment. Therefore, there is a clear need for more informative "Generation II" tests that better assess risk, also on the long term, and provide theranostic targets. To this end, we have performed an mRNA abundance-based analysis trained in the 790 patients of the UK TEAM cohort to identify a signature of residual risk , to be validated in the remaining 3000 patients from the TEAM pathology study.

Methods: RNA extracted from the tumors of respective TEAM pathology study patients were profiled using a 165-gene NanoString code set. The gene list was compiled from targets that comprise many of the existing risk assessment tests, in addition to genes known to be of importance for breast cancer pathogenesis. Signal intensities were normalized using the R statistical environment; 336 different combinations of preprocessing methods were assessed and the most optimal method selected using unbiased criteria. A10-fold cross-validation approach, in combination with a network-based patient risk score calculation formula, was used to derive a 95-gene signature. Briefly, genes were first filtered based on a Cox regression p-value threshold of 0.25; the sum of the weighted mRNA abundance levels of the result genes was calculated for each patient as the risk score. Patient-wise risk scores were then used in a multivariate Cox proportional hazards model along with clinical covariates such as age, grade, HER2 status and nodal status, using DRFS truncated to 10 years as an end-point.

Results: Univariate survival analysis revealed a number of significantly prognostic candidates. The resulting 95-gene signature identified in the training set, stratified patients into high and low risk with an HRhigh of 2.74 (p<2.06 x10-4) when adjusted for age, grade, HER2 status and nodal status; resulting in an AUC of 0.73. Modular analyses of the genes comprising the 95-gene signature identified pathways associated with receptor tyrosine kinase signalling, regulation of cell cycle, and the spindle assembly checkpoint. Additionally, the composition of the gene-list made it possible to characterize the patients into their intrinsic subtypes and to determine their relative risk for recurrence relative to assessment tools available today . The validation of the 95-gene signature will be conducted in the remaining samples in the TEAM pathology study using the bioinformatics strategy described above.

Conclusions: The impact of test-guided therapy using multi-parametric tests is increasingly being felt in the clinic, and is reshaping modern health-care economics. A successful Generation II multi-parametric test will better discriminate those that are truly at high risk for recurrence following endocrine therapy and indicate potential therapeutic options for intervention for those who would not benefit from current modalities.

Citation Format: Bayani J, Yao CQ, Quintayo MA, Haider S, Brookes CL, Yan F, van de Velde CJH, Hasenburg A, Kieback DG, Markopoulos C, Dirix L, Seynaeve C, Boutros PC, Rea DW, Bartlett JMS. Defining a signature of residual risk following endocrine treatment in the tamoxifen and exemestane adjuvant multinational (TEAM) trial. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P2-08-29.

Abstract P4-11-05: Does androgen receptor (AR) expression impact on residual risk? A TEAM pathology study

Introduction: Several studies have suggested that AR expression, particularly in luminal cancers following endocrine therapy, may be associated with improved outcome in early breast cancer. We performed an analysis of AR expression in the TEAM pathology cohort to test the hypothesis that AR would represent an independent predictor of residual risk following adjuvant endocrine therapy.

Methods:

Triplicate 0.6mm2 TMA cores from the TEAM pathology cohort (N=4,598) were stained using AR clone ER179(2) on a Ventana automated staining platform and analysed by image analysis using the Ariol Image analysis platform. Continuous histoscores were generated as previously described (Bartlett et al, JCO 2011).

Results: AR histoscores were generated from 3866/4598 (84%) of available cases. Median AR histoscores were 227 (interquartile range 195-262). In a univariate Cox proportional hazard model with AR histoscore as a continuous variable, increased AR histoscores were significantly associated with a reduced hazard of distant disease relapse or death from breast cancer. The hazard ratio (HR) associated with a 50 unit increase in the histoscore was 0.88, 95% confidence interval (95%CI) 0.83-0.93, P<0.0001. There was evidence that a log transformation of the histoscore resulted in a better fitting model (P<0.0001) resulting in the following model estimates HR= 0.93, 95% CI 0.89-0.98, P=0.006. However, a multivariate model of AR histoscore including other known prognostic factors such as age, grade, tumour size, number of positive nodes, HER2 status, ER and PgR histoscores found AR histoscore was not independently prognostic for distant relapse or death (HR=1.00, 95% CI 0.94-1.06, P=0.96). There was no significant interaction between AR expression and type of endocrine treatment (Tamoxifen →exemestane versus exemestane alone) in either univariate (HR 1.003 95%CI 0.91-1.11, p=0.96) or multivariate (HR 0.92, 95%CI 0.81-1.04, p=0.18) analysis.

Logistic regression analysis was performed to investigate the association between AR histoscore (2 groups above and below the median) and the known prognostic factors mentioned above. Increased AR histoscore is associated with good risk factors; young age, low grade, small tumours, decreasing ki67 and increasing ER and PgR histoscores.

Conclusion: AR expression is common in luminal breast cancers. However, in this study AR histoscore does not add residual risk information beyond what can already be assessed using conventional prognostic factors. High AR expression is associated with good prognostic factors, including young age, low tumour grade, small tumour size, lower Ki67 and higher ER/PgR expression.

Citation Format: John MS Bartlett, Cassandra L Brookes, Fu J Yan, Mary Anne Quintayo, Jane Bayani, Jane Starczynski, Cornelis JH van de Velde, Annette Hasenburg, Dirk G Kieback, Christos Markopoulos, Luc Dirix, Caroline Seynaeve, Daniel W Rea. Does androgen receptor (AR) expression impact on residual risk? A TEAM pathology study [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P4-11-05.

Abstract P2-05-12: Signatures of endocrine resistance in the tamoxifen and exemestane adjuvant multinational trial (TEAM)-UK cohort

Introduction: There are a number of commercially-available tests to stratify risk for women diagnosed with early breast cancer. While such "Generation I" tests are increasingly being used, a consensus is growing that these tests are moderately accurate in assessing risk. Moreover, Generation I tests fail to direct more personalized treatment. There exists, therefore, a clear need for more informative "Generation II" tests that have theranostic targets. To this end, we have performed an mRNA abundance-based analysis using the UK cohort of the TEAM trial to identify signatures of endocrine resistance, from which pathways for putative therapeutic intervention may be identified.

Methods: RNA extracted from 790 patients in the UK-TEAM cohort were profiled using a 165-gene NanoString codeset. The gene list was compiled from targets that comprise many of the existing risk assessment tests, in addition to genes known to be of importance for breast cancer pathogenesis. Signal intensities were normalized using the R statistical environment; 336 different combinations of preprocessing methods were assessed and the most optimal method selected using unbiased criteria.

Results: Univariate survival analysis revealed a number of significantly prognostic candidates. Using inter-gene correlation and consensus clustering, we identified five gene clusters. Not surprisingly, these clusters included a strong proliferation, hormone signalling and cell migration component. Derivation of risk scores using Cox proportional hazards model, with the inclusion of age and nodal status, generated a signature identifying patients with differences in distant relapse-free survival (DRFS). Moreover, the composition of the gene-list made it possible to characterize the patients into their intrinsic subtypes and to determine their relative risk for recurrence relative to assessment tools available today. The added value of subtyping and the gene clusters identified in this discovery cohort will be discussed.

Conclusions: The impact of test-guided therapy using multi-parametric tests is increasingly being felt in the clinic, and is reshaping modern health-care economics. A successful Generation II multi-parametric test will better discriminate those that are truly at high risk for recurrence following endocrine therapy and offer potential therapeutic options for intervention for those who would not benefit from current modalities.

Citation Format: Jane Bayani, Mary Anne Quintayo, Cindy Q Yao, Syed Haider, Cassandra Brookes, Paul C Boutros, John MS Bartlett, Daniel W Rea. Signatures of endocrine resistance in the tamoxifen and exemestane adjuvant multinational trial (TEAM)-UK cohort [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P2-05-12.

Abstract P4-11-06: TLE3 is not a predictive biomarker for taxane sensitivity in the NCIC CTG MA.21 clinical trial

Background: TLE3, a nuclear transcriptional repressor downstream of the WNT signaling pathway, has been identified as a candidate predictive biomarker of taxane benefit in early breast cancer. However, robust clinical evidence is required before implementing novel diagnostic biomarkers. We tested the hypothesis that TLE3 predicts for benefit from taxane containing polychemotherapy in the NCIC CTG MA.21 clinical trial.

Methods: MA.21 accrued 2104 patients [701 each to cyclophosphamide, epirubicin, and 5 fluorouracil (CEF) and epirubicin and cyclophosphamide with filgrastim and epoetin alfa followed by paclitaxel (EC/T), 702 to doxorubicin and cyclophosphamide followed by paclitaxel (AC/T)] who were followed median 8 years by the final analysis. EC/T and CEF were not significantly different (p= 0.69) while AC/T was inferior to both EC/T and CEF (respectively, p=0.001 and p=0004). Tissue microarrays were constructed from 1097 of the 2104 patients. Patient characteristics were well balanced between those included in the TLE3 analysis and the full trial population. Up to four 0.6 mm tumor cores were stained for TLE3 expression by immunohistochemistry using a previously validated methodology. Continuous visual TLE3 score was the average % positive stain across all cores, while continuous automated score was sum of cells with positive stain/ total cells assessed in all cores. The primary objective used the EC/T (taxane-containing) and CEF (non-taxane; similar dose-density) arms for a test of predictive effect of TLE3 on relapse free survival. TLE3 was positive if >30% of cells stained, the established cut-point, with data available from at least 1 core/tumor. We also examined quartile cut-points, multivariate effects of TLE3, and compared AC/T and CEF.

Results: MA.21 patients had 83.2% TLE3+ tumors by visual score and 80.6% TLE3+ by automated image analysis greater than the predicted rate of TLE3 positivity (58.6%) based on prior series and adjusting for clinicopathological features. TLE3 expression was significantly positively associated with ER expression (91.2% of ER+ were TLE3+; p<0.0001). There was no evidence of a predictive effect of TLE3 expression with respect to taxane benefit using the established 30% cut-point, nor quartile cut-points. The treatment and TLE3 interaction term for the EC/T by CEF comparison was not significant (stratified p=0.68, for manual TLE3; p=0.44, for automated TLE3).

Conclusions: MA.21 patients had a much higher proportion of TLE3+ tumors than anticipated. Multiple assessments of TLE3 cut-points yielded no evidence that it was predictive of taxane benefit.

In our trial TLE3 expression was not a biomarker for taxane benefit (EC/T vs CEF) when using either previously established or common quartile cut-offs for expression in breast cancer.

Citation Format: John MS Bartlett, Torsten O Nielsen, Dongxia Gao, Karen A Gelmon, Mary Anne Quintayo, Jane Starczynski, Lei Han, Margot J Burnell, Mark N Levine, Lois E Shepherd, Judy-Anne W Chapman. TLE3 is not a predictive biomarker for taxane sensitivity in the NCIC CTG MA.21 clinical trial [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P4-11-06.

Abstract P2-03-17: Assessing reproducibility of copy number arrays to assist breast cancer biomarker discovery

Introduction:

Large-scale interrogation of the genome has emerged as an attractive method for identifying useful characteristics of cancer biology; in particular, the study of copy number aberrations (CNA) has recently received tremendous attention. A number of different technologies have been developed to assess the copy-number landscape, allowing us to better understand the role of CNA in cancer cells. The OncoScan CNA platform (Affymetrix Inc.) has been particularly appealing for oncology due of its ability to work well with formalin-fixed, paraffin-embedded (FFPE) materials, which is the primary form for storage of clinical samples. In addition, its high resolution, rapid analysis time and ability to interrogate different genomic characteristics (CNA, loss of heterozygosity or mutation) make the OncoScan platform highly popular: it has been widely cited in the literature for use in biomarker discovery, clonal evolution and sub-clonal detection, as well as population-based analyses. While CNAs identified by the OncoScan platform have shown good concordance with fluorescence in-situ hybridization (FISH) results, to date, no studies have been conducted to thoroughly assess the reproducibility of the assay. In this study, we have assessed the reproducibility of the OncoScan platform using identical samples performed in replicates across multiple chip batches. Moreover, we have assessed the effect on reproducibility of DNA treatment, including elution in water or TE buffer, as well as in the use of varying amounts of DNA.

Methods:

Affymetrix OncoScan FFPE Express 3.0 SNP Arrays were performed using the optimal input DNA as recommended by the manufacturer as well as fewer input amounts for comparison. CNAs were called using BioDiscovery Nexus Copy Number™ software (http://www.biodiscovery.com/software/nexus-copy-number/) using the SNP-FASST2 algorithm with modified parameters (significance threshold of 1 x 10-9 and minimum number of probes per segment of 10).

Results:

Initial reproducibility analysis involving 12 samples repeated either 2, 4 or 6 times both within a single batch and across different batches has revealed that CNA calls were concordant between replicates for the majority of the genome (ranges between 81% to 100%), suggesting high precision of the assay. In addition, we are in the process of assessing and comparing mutation calls across replicates to gain a more in-depth understanding of the platform.

Conclusion:

This is the first study examining the reproducibility of OncoScan FFPE assays; initial results have suggested that the assay is precise and has the potential for robust biomarker discovery. Additional characterizations would be interesting for evaluating its use as a clinical tool in the long term.

Citation Format: Cindy Q Yao, Cheryl Crozier, Mary Anne Quintayo, Jane Bayani, Melanie Spears, Julie Livingstone, Esther Jung, Clement Fung, Victoria Sabine, Paul C Boutros, John MS Bartlett. Assessing reproducibility of copy number arrays to assist breast cancer biomarker discovery [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P2-03-17.

Virtual tissue microarrays: a novel and viable approach to optimizing tissue microarrays for biomarker research applied to ductal carcinoma in situ

AIMS

Tissue microarrays (TMAs) are effective tools for performing high-throughput standardization analyses of biomarkers, but evidence indicating the core number required to be representative of the whole tumour is lacking. Ductal carcinoma in situ (DCIS) is a non-obligate precursor of invasive breast cancer. The number and size of cores that can best represent a DCIS lesion are unknown. Rather than performing extensive experiments using several variants of physical TMAs, the aim of this study was to develop a 'virtual TMA' approach that is effective at optimizing biomarker discovery and validation.

METHODS AND RESULTS

Whole DCIS sections from 95 patients were evaluated by immunohistochemistry for oestrogen receptor (ER), progesterone receptor (PgR), HER2, and Ki67. Histoscores were generated manually for ER, PgR, and HER2, as well as percentage positivity for Ki67. Slides were scanned using the FDA-approved Ariol SL50 Image Analysis system, and the virtual array (V-Array) module was used. Virtual cores created virtual TMAs, and our validated scoring classifiers were applied. Automated histoscores and percentage positivity were determined, and compared against increasing numbers of cores. The optimal number of cores was based on concordant results between virtual TMAs and corresponding whole sections.

CONCLUSIONS

We have shown that virtual arrays constitute an important tool in digital pathology in both research and clinical settings.

Do type 1 receptor tyrosine kinases inform treatment choice? A prospectively planned analysis of the TEAM trial

BACKGROUND

Epidermal growth factor receptors contribute to breast cancer relapse during endocrine therapy. Substitution of aromatase inhibitors (AIs) may improve outcomes in HER-positive cancers.

METHODS

Tissue microarrays were constructed. Quantitative analysis of HER1, HER2, and HER3 was performed. Data were analysed relative to disease-free survival and treatment using outcomes at 2.75 and 6.5 years.

RESULTS

Among 4541 eligible samples, 4225 (93%) had complete HER1-3 data. Overall, 5% were HER1-positive, 13% HER2-positive, and 21% HER3-positive; 32% (n=1351) overexpressed at least one HER receptor. In the HER1-3-negative subgroup, the hazard ratio (HR) for upfront exemestane vs tamoxifen at 2.75 years was 0.67 (95% confidence interval (CI), 0.52-0.87), in the HER1-3-positive subgroup, the HR was 1.15 (95% CI, 0.85-1.56). A prospectively planned treatment-by-marker analysis demonstrated a significant interaction between HER1-3 and treatment at 2.75 years (HR=0.58; 95% CI, 0.39-0.87; P=0.008), as confirmed by multivariate regression analysis adjusting for prognostic factors (HR=0.55; 95% CI, 0.36-0.85; P=0.005). This effect was time dependent.

CONCLUSION

In the 2.75 years prior to switching patients initially treated with tamoxifen to exemestane, a significant treatment-by-marker effect exists between AI/tamoxifen treatment and HER1-3 expression, suggesting HER expression could be used to select appropriate endocrine treatment at diagnosis to prevent or delay early relapses.

Abstract P1-07-17: V Array: A novel tool for constructing virtual tissue microarrays (TMAs), an evaluation of its use in optimizing TMA construction for Ductal Carcinoma in Situ (DCIS)

Introduction: The use of TMAs has become invaluable in the assessment of large patient cohorts in clinical practice. TMAs facilitate high throughput analysis and increase biomarker standardization. However, there is little evidence in the literature validating the number of cores required to be representative of the whole tumor. With increasing evidence indicating the heterogeneous nature of many tumors such evidence is critical.

DCIS is becoming an increasingly common diagnosis with 5000 new cases p.a. in Canada; with women at risk of recurrence and invasion. It is challenging to create TMAs for DCIS in view of the scattered distribution of the involved ducts. Furthermore, ducts affected with DCIS often vary in architecture, nuclear grade and presence of comedo necrosis even within individual patients. This study aims to determine the number of cores required to construct representative TMAs for different biomarkers in the setting of DCIS.

Materials and Methods: Tumor blocks from 102 patients presenting with DCIS alone were retrieved from the archives of Sunnybrook Hospital. Sequential tissue sections were stained with H&E, ER, PgR, HER2 and Ki67. All slides were manually evaluated and Histo-scores determined for ER, and PR, % positive cells for Ki67. and HER2 was classified in accordance with the 2007 ASCO/CAP guidelines. Slides were then scanned at x1.25 magnification on the Ariol SL50 Image Analysis system (Leica Microsystems). A map representing a 5 × 2 TMA, with 0.6mm2 cores was placed on the scanned image of the H&E stained slides and 10 regions of interest (ROI) identified (where possible). The H&E and IHC were then slide linked to then allow identification of the same ROI. The slides were then rescanned on x20, this time only the mapped areas were scanned creating virtual “TMA cores”. Using the V Array (virtual array) function within the Ariol software the virtual cores were placed in a V Array. Previously validated algorithms for ER, PR, HER2 and Ki67 were used to directly analyze each core and the results exported to Excel for analysis. The continuous mean was assessed for increasing numbers of cores and used to determine the optimal number of cores required to be representative of the whole tumor.

Results: Virtual TMAs were successfully constructed on all cases. The Histo score of increasing numbers of cores was determined and compared to the overall Histo score for the tumor. The mean numbers of cores required to be representative of the whole tumor was three.

Discussion: V array proved an excellent tool for the creation of virtual TMAs and helped to identify the minimum number of cores required to be representative. This technology also has wider applications and may prove very useful in the evaluation of samples with insufficient tumor to allow physical cores to be taken, or where tumors are rare. With the increase in digital pathology and access to scanned images V array will be a valuable addition as a research tool.

Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr P1-07-17.

GSK3β and cyclin D1 expression predicts outcome in early breast cancer patients

Glycogen synthase kinase 3β (GSK3β) is phosphorylated and inactivated by the phosphoinositide 3 kinase PI3K/Akt pathway. Activation of Akt phosphorylates GSK3β preventing phosphorylation of cyclin D1 which leads to accumulation and nuclear localisation of cyclin D1, activation of CDK4/6 and cell cycle progression. The CCND1 gene found at chromosome 11q13 has been shown to be amplified in approximately 15 % of breast cancers. Cyclin D1, the product of the CCND1 gene, is one of the most commonly overexpressed proteins in breast cancer. Protein expression for GSK3β, phosphorylated-GSK3β (p-GSK3β), cyclin D1 and gene expression of CCND1 were examined in tissue microarrays of 1,686 patients from the Edinburgh Breast Conservation Series. High GSK3β expression was associated with reduced distant relapse-free survival (DRFS), while no association between p-GSK3β and breast cancer-specific survival was seen. CCND1 amplification is also associated with poor DRFS. On the contrary, cyclin D1 overexpression is associated with an increase in DRFS. Multivariate analysis was performed. We suggest that analysis of both GSK3β and cyclin D1 expressions can be considered as a marker of good prognosis in early breast cancer.

Expression of activated type I receptor tyrosine kinases in early breast cancer

Overexpression of EGFR, HER2 and HER3 are known to be associated with poor outcome in breast cancer. Few studies have examined the clinical impact of activation of these proteins. In the present study, we evaluated EGFR, HER2 and HER3 and the activated (phosphorylated) forms of these proteins in patients with early breast cancer. EGFR, HER2, HER3, pEGFR, pHER2 and pHER3 expression was determined by immunohistochemical analysis of tissue microarrays constructed from tumours within the Edinburgh Breast Conservation Series (BCS). The BCS represents a fully-documented consecutive cohort of 1,812 patients treated by breast conservation surgery in a single institution. Our results demonstrate overexpression of HER2 and pHER2 to be associated with a significant reduction in overall survival (OS) (HR: 1.66, 95 % CI 1.22-2.26, p = 0.001 and HR: 1.57, 95 % CI 1.22-2.03, p = 0.001, respectively) and distant relapse-free survival (DRFS) (HR: 1.63, 95 % CI 1.23-2.18, p = 0.001 and HR: 1.55, 95 % CI 1.23-1.97, p = 0.0002, respectively). Paradoxically, expression of pEGFR was associated with a significantly improved OS (HR: 0.67 95 % CI 0.50-0.91, p = 0.01) and DRFS (HR: 0.73, 95 % CI 0.56-0.96, p = 0.025). Expression of activated EGFR/HER2 provides additional information on ER positive breast cancer patients and suggests alternative treatment for those in this subgroup.

The p160 ER co-regulators predict outcome in ER negative breast cancer

The SRC family of ER co-regulators are frequently overexpressed in breast cancer. Overexpression of AIB1 appears to be linked to hormone resistance in HER2 positive breast cancer. However, the role of these co-regulators in ER negative disease is poorly understood. SRC1, SRC2 and AIB1 expression was determined by immunohistochemical analysis of tissue microarrays constructed from tumours within the Edinburgh Breast Conservation Series (BCS). The BCS represents a fully documented consecutive cohort of 1,812 patients treated by breast conservation surgery in a single institution. Our results demonstrate tumours that overexpress both HER2 and AIB1 were associated with markedly reduced relapse free, distant relapse free and overall survival compared to HER2 and AIB1 only overexpressing tumours irrespective of ER status. In ER negative disease both SRC1 and AIB1 were linked to early relapse and death. The SRC family of ER co-regulators is involved in early relapse and resistance in both ER negative and ER positive breast cancer challenging the conventional concept that this effect is mediated solely via the ER.