Breast Cancer Assay Research Articles

Impact of oncotype Dx score on treatment and long-term outcomes.

e12518 Background: Oncotype dx is a 21 gene breast cancer assay that helps predict benefit of chemotherapy in early-stage hormone receptor positive (HR+), HER2 negative, 0 to 3 node positive breast cancer as reported by TAILORx and RxPonder trials. Both trials found no benefit of adjuvant therapy in mid-range scores of 11-25 with the exception of some benefit in age under 50 or premenopausal status, no benefit if score was 0-10, and benefit of chemotherapy if >25. Methods: All breast cancer patients between 2019-2020 were chart checked to evaluate oncotype dx scores. Patient characteristics were analyzed between oncotype dx scores of 0-10, 11-25, and >25 using X square tests. 2000-2020 institutional cancer registry data was analyzed to understand recurrence and mortality in patients with oncotype dx testing. Results: 173 patients had oncotype dx testing between 2019-2020, and most were HR+, HER2-, and had 0-3 lymph nodes. There was no difference in race or ethnicity between the groups of oncotype dx scores (Table), and average age at diagnosis for all three groups was 58 years. More patients with lower oncotype dx score had hormone therapy, but this was not significant (0-10 at 93.6%, 11-25 at 90.8%, and >25 at 82.1%, p=0.26). Patients with a higher oncotype score were significantly more likely to have chemotherapy (0-10 at 0%, 11-25 at 17.3%, and >25 at 82.1%, p<0.01). When looking at long term outcomes, the mortality rate was highest in the 11-25 score group at 9.5%, but was not significantly higher than 0-10 at 4.7% and >25 at 2.1% (p=0.15). The recurrence was highest in the 0-10 group at 5.4%, but not significant compared to the 11-25 group at 4.1% and >25 group at 4.2% (p=0.09). Conclusions: Race, ethnicity, and age does not impact predisposition to high oncotype dx score, which is interesting since literature shows minority women have higher mortality rates. This could be because oncotype dx looks at early-stage breast cancers and many minority women have later stages at diagnosis. There was no difference in which group received hormone therapy and there was significantly higher rate of chemotherapy administration in patients with scores >25, which is consistent with prospective trial recommendations. When evaluating long term outcomes between oncotype dx groups over 20 years, there was no significant difference in recurrence of disease or mortality indicating that oncotype dx scoring accurately predicted overall benefit of chemotherapy.[Table: see text]

P057. The implementation of oncotype DX score on MDT decision making - A service evaluation

Introduction: The Oncotype Dx recurrence score (RS) predicts chemotherapy benefit based on the 21-gene breast cancer assay. We set out to evaluate the implementation of the Oncotype Dx score on MDT decision making and to investigate its' impact on our service.

Comparison of breast cancer surrogate subtyping using a closed-system RT-qPCR breast cancer assay and immunohistochemistry on 100 core needle biopsies with matching surgical specimens

BackgroundRoutine clinical management of breast cancer (BC) currently depends on surrogate subtypes according to estrogen- (ER) and progesterone (PR) receptor, Ki-67, and HER2-status. However, there has been growing demand for reduced immunohistochemistry (IHC) turnaround times. The Xpert® Breast Cancer STRAT4* Assay (STRAT4)*, a standardized test for ESR1/PGR/MKi67/ERBB2 mRNA biomarker assessment, takes less than 2 hours. Here, we compared the concordance between the STRAT4 and IHC/SISH, thereby evaluating the effect of method choice on surrogate subtype assessment and adjuvant treatment decisions.MethodsIn total, 100 formalin-fixed paraffin-embedded core needle biopsy (CNB) samples and matching surgical specimens for 98 patients with primary invasive BC were evaluated using the STRAT4 assay. The concordance between STRAT4 and IHC was calculated for individual markers for the CNB and surgical specimens. In addition, we investigated whether changes in surrogate BC subtyping based on the STRAT4 results would change adjuvant treatment recommendations.ResultsThe overall percent agreement (OPA) between STRAT4 and IHC/SISH ranged between 76 and 99% for the different biomarkers. Concordance for all four biomarkers in the surgical specimens and CNBs was only 66 and 57%, respectively. In total, 74% of surgical specimens were concordant for subtype, regardless of the method used. IHC- and STRAT4-based subtyping for the surgical specimen were shown to be discordant for 25/98 patients and 18/25 patients would theoretically have been recommended a different adjuvant treatment, primarily receiving more chemotherapy and trastuzumab.ConclusionsA comparison of data from IHC/in situ hybridization and STRAT4 demonstrated that subsequent changes in surrogate subtyping for the surgical specimen may theoretically result in more adjuvant treatment given, primarily with chemotherapy and trastuzumab.

Immunomodulatory, Antioxidant Activity and Cytotoxic Effect of Sulfated Polysaccharides from Porphyridium cruentum. (S.F.Gray) Nägeli.

Porphyridium cruentum is a unicellular microalga that can synthesize and secrete to the culture medium-high amounts of polysaccharides. In this study, the immunomodulatory, cytotoxic effect and antioxidant activity of the sulfated polysaccharides (PcSPs) were determinate. The PcSPs were precipitated with 2% Cetylpyridinium bromide hydrate and ethanol and purified by dialysis. The extract was lyophilized for its characterization by Fourier transform-Infrared (FT-IR) spectroscopy and gas chromatography–mass spectrometry (GC-MS). The antioxidant activity of PcSPs were examined with assay 2,2′-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) and compared with that of the biomass, observing significant differences between the results obtained from the PcSPs and biomass. To determine their ability to induce cytokine production Tumor Necrosis Factor alpha (TNF-α) and interleukina-6 (IL-6), the immunomodulatory activity of the PcSPs has been evaluated. In the mouse macrophage cell line (RAW 264.7), PcSPs are potent inducers of IL-6 cytokines but mainly of TNF-α. The cytotoxic capacity of PcSPs was measured by the MTT colorimetric assay in colorectal carcinoma (HTC-116), human leukemia (U-937 and HL-60), breast cancer (MCF-7), lung cancer (NCI-H460) and human gingival fibroblasts (HGF-1) cell lines. The IC50 value of 2311.20 µg mL−1, 1676.74 µg mL−1, 1089.63 µg mL−1, 5498.14 µg mL−1 and 2861.49 µg mL−1 respectively in the tumor lines and 5022.55 µg mL−1 in gingival fibroblasts were obtained. Our study suggested that PcSPs from P. cruentum have a moderate immunomodulatory and cytotoxic effect. The results obtained indicate that the polysaccharides from P. cruentum are potent inducers of IL-6 cytokines and, most importantly, of TNF-α. PcSPs showed no evidence of antigenic activity or hypersensitivity when administered intraperitoneally in mice. Furthermore, the in vivo study revealed an improvement of local inflammatory response against stress in the peritoneum. These findings suggest that the PcSPs from P. cruentum might have potential as a valuable ingredient in nutraceutical products.

Abstract PS5-46: Introduction and clinical validation of metrology standards for immunohistochemistry (IHC); New tool for standardization of estrogen receptor (ER) IHC assay in breast cancer

Abstract Traceability of measurement to a higher order reference standard is a foundation of laboratory testing. There is as yet no method for creating reference standards for cellular proteins in situ in an analogous fashion as for soluble analytes. At present, IHC laboratories produce results for breast cancer hormone receptors without connection to a reference standard. Not surprisingly, high rates of testing variation as well as discrepancies among IHC laboratories have been reported. To address this need, we developed a system of measurement traceability using a linked fluorescein tag for creating reference standards for any cellular analyte and, as a first test, validate it for estrogen receptor (ER) testing. In this study, the newly developed ER standard defines and compares the thresholds separating “high positive”, “low positive”, and “negative” tests according to updated ASCO/CAP guidelines as detected by clinical IHC laboratories in a national external quality assessment survey. This reference standard utilizes NIST Standard Reference Material (SRM) 1934 as a universal IHC standard. We calculated ER concentration based on a linked fluorescence measurement traceable to NIST SRM 1934 as each ER is linked to a single fluorescein, and fluorescein concentration equals ER concentration. Each laboratory’s lowest detected ER concentration (i.e. “limit of detection”, LOD) was compared to their results with 80 tumor samples enriched for triple negative breast cases. For the Canadian Immunohistochemistry Quality Control (CIQC) ER proficiency testing run, calibrator sets with peptides for the SP1, EP1, and 6F11 epitopes were created. The various concentrations were pipetted onto histology slides used by CIQC to place its 80-case breast cancer tissue microarray. These slides were stained by participating laboratories using their routine ER IHC protocols and returned to the CIQC. For the purpose of this study, Histology Score and ASCO/CAP categorical scoring recommendation was used for the readout. Results with SP1 clone are reported here because it was employed by overwhelming majority of laboratories. A total of 3,038 readouts were included in the analysis. Most IHC laboratories had a LOD between 10,000 – 25,000 molecules ER per microbead. Highly sensitive ER assays (low LODs) detected more positive cases while those with poorly sensitive assay detected fewer. The LOD correlated with the percent positive cases (R2= -.767, p < 0.0001, Spearman Correlation) as well as with cumulative individual laboratory Histology Score (R2= -.612, p < 0.0001, Spearman Correlation). The tumor samples accounting for this difference were principally “low positive” (ASCO/CAP classification) while ER-high positive tumors were less affected. Although the concept of a non-quantitative IHC LOD has been introduced with critical assay performance controls (iCAPCs, e.g. germinal center cells in the tonsil for ER), there were no tools until now to actually measure LOD for ER IHC testing. With the calibrators introduced here, it is now possible to measure the LOD for ER IHC assays. Furthermore, our data show that ER low positive and some cases of ER high positive breast cancers are highly affected by the variability of analytic sensitivity between clinical IHC laboratories. These data argue for the urgent need to standardize testing to a defined analytic sensitivity range, which is now possible for the first time. Beyond inter-laboratory standardization, known measured LOD also enables: i) methodology transfer from clinical trials to clinical laboratories; ii) determination of optimal analytical sensitivity to produce assays with highest clinical and analytical validity, and iii) daily monitoring of analytical sensitivity for each tested IHC slide. Citation Format: Emina Emilia Torlakovic, Seshi R. Sompuram, Kodela Vani, Lili Wang, Anika K Schaedle, Paul C. DeRose, Steven A. Bogen. Introduction and clinical validation of metrology standards for immunohistochemistry (IHC); New tool for standardization of estrogen receptor (ER) IHC assay in breast cancer [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS5-46.

Abstract PD6-02: Digital MammaPrint and BluePrint using machine learning and whole slide imaging

Abstract Background: The rise of whole slide imaging systems has enabled pathologists to remotely view cases in high resolution to diagnose cancer, and efficiently archive images . The advent of machine learning techniques and their application in digital pathology have facilitated the identification of histological patterns for effective diagnosis of disease. Deep learning-based solutions have been developed to detect and recognize cancer types, and automatically grade and stage tumors through evaluation of pathological features and patterns. However, no image-based solutions have been able to replicate a multivariate test, such as a risk -of recurrence assay for early stage breast cancer. Traditionally, subtle differences in gene expression have been measured by microarray or NGS, however these changes may also be recognized phenotypically from hematoxylin and eosin stained (H&E) slides by digital biomarkers developed using novel machine learning techniques. The large repository of images with MammaPrint and BluePrint results may enable us to develop digital MammaPrint and digital BluePrint biomarkers that predict the risk of distant recurrences and the molecular subtypes of a tumor sample using only H&E stained digitized tumor slides. Methods: Using over70,000 H&E images of early stage breast cancer patients in combination with machine learning techniques, digital versions of MammaPrint and BluePrint were developed. In total 20,000 images were used for feasibility and algorithm optimization, another 50,000 images were used for further finetuning. MammaPrint indices and BluePrint scores and categorical results were used to train the system. After the algorithms were optimized, they were locked and validated in an independent set of 5000 H&E stained images. The MammaPrint and BluePrint predictions were compared to the original MammaPrint and BluePrint results obtained from the microarray assay. The finalized and locked algorithms were further validated for precision and reproducibility in a large data set of xx Images and processed multiple times. Multicenter clinical validation was performed in H&E stained images of multiple series with long term follow up (tbd), totaling ##k images. In this ##K cohort of patients, #% were HR+/HER2-, #% were clinically HER2+ and x% were triple negative. Results: Using an independent dataset of 5000 samples, we compared the MammaPrint and BluePrint predictions obtained from the H&E slides to the traditional versions of MammaPrint and BluePrint based on a microarray. The binary performance of the digital MammaPrint had a concordance of xx% (with an AUC of xx%),%NPA and %PPA when compared to the traditional MammaPrint high-low classification. For digital BluePrint, the system had a concordance of xx% and a classification accuracy of xx%. The analytical performance showed a precision and reproducibility of xx% In a multicenter clinical validation the DRFI was xx% in dMP low risk and yy% in dMP high risk groups. The xxx dataset the performance was similar to the microarray and better than compared to clinical parameters. Analyses will be available by the Placeholder Abstract deadline. Conclusions: The combination of machine learning and digital pathology has enabled development of rapid and highly accurate in silico versions of MammaPrint and BluePrint. Implementation of digital H&E based risk of recurrence and molecular subtyping could enable preservation of valuable diagnostic tissue, faster turnaround time for test results, and a more cost effective approach to treatment planning tools, especially in countries that do not allow send out of human tissue and this adoption of risk scoring is low. Final conclusions tbd Citation Format: Annuska M Glas, Jorge S Reis-Filho, Diederik Wehkamp, Belma Dodgas, Leonie Delahaye, Ran Godrich, Jeroen Mollink, Adam Casson, Anke Witteveen, Julian Viret, Donghun Lee, Matthew Lee, Hugo Horlings, Leo Grady, Thomas Fuchs, William Audeh, Christopher Kanan, Laura J van't Veer. Digital MammaPrint and BluePrint using machine learning and whole slide imaging [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PD6-02.

Abstract PS14-11: Differential gene expression analysis and clinical utility of MammaPrint and BluePrint in male breast cancer patients

Abstract Background: Male breast cancer (MaBC) is rare, comprising <1% of all breast cancers in the United States. The low incidence of MaBC limits the ability to conduct clinical trials specifically for this population. Due to the paucity of research on MaBC, current understanding regarding MaBC biology, pathology, and treatment strategies has been primarily based on evidence extrapolated from research on female breast cancer (FBC) patients. Traditional diagnostic biomarkers such as ER, PR, and HER2, as well as newer multi-gene prognostic signatures, are employed when making treatment decisions for both MaBC and FBC. However, limited empirical data is available to support the use of identical laboratory biomarkers and molecular signatures in both MaBC and FBC. The 70-gene risk of distant recurrence signature, MammaPrint (MP), and the 80-gene molecular subtyping signature, BluePrint (BP), are commonly used to help make treatment decisions for both MaBC and FBC patients. To support the clinical utility of MP and BP in MaBC, this study aims to elucidate whether significant molecular biological differences exist between MaBC and FBC. To address this knowledge gap, we evaluated and compared 1) MP index results within Low Risk (LR) and High Risk (HR) groups, 2) MP and BP gene expression, and 3) differentially expressed genes within the full genome and their associated biological pathways between tumors from MaBC and FBC. Methods: This analysis included a total of 817 breast tumor samples sent to Agendia, Inc. (Irvine, CA) for MP and BP testing. Full-transcriptome microarray data were available for 1) a subset of 400 post-menopausal FBC patients enrolled in the FLEX Registry (NCT03053193) and 2) 80 MaBC pateints, 32 of whom enrolled in the FLEX registry and 48 non-study patients for whom data were limited to metadata and quality metrics routinely captured for diagnostic testing. Data from all patients were de-indentified. Differences in mean MP indices between FBC (N=400) and MaBC (N=417) according to MP Risk classification (LR or HR) were analyzed using a Z-test. Differential gene expression analysis was performed using the R-limma package in which gene expression data were quantile normalized. Pathway analyses were performed using GOseq. Differentially expressed genes (DEGs) were identified between FBC (N=400) and MaBC (N=80) for whom full transcriptome microarray data were available. DEGs were defined as those with a fold change of > 2 and an adjusted P value of < 0.05. Results: All patients in this study had hormone positive, HER2 negative early-stage breast cancer. There was no statistical difference in the average MP index between MaBC and FBC classified as MP LR (P=0.273) or those classified as MP HR (P=0.692). Gene expression comparison revealed 166 DEGs between MaBC (N=80) and FBC (N=400), 99 DEGs between MP HR MaBC (N=42) and MP HR FBC (N=200), and 290 DEGs between MP LR MaBC (N=38) and MP LR FBC (N=200). Pathway analyses revealed that downregulated genes in MaBC compared to FBC enriched to immune-related functions, including B-cell mediated immunity, whereas upregulated genes were associated with hormone metabolic processes. In all comparisons, expression of MP or BP genes was not significantly different. Conclusions: We found similar MP index distributions between MaBC and FBC. Importantly, differential gene expression between MaBC and FBC provides novel insight into the mechanisms underlying MaBC. Although these data reveal biological distinctions between male and female breast cancer, MP and BP assay performance is preserved across both groups. Further studies are needed to assess clinical outcomes; however, these findings support the use of MP risk of recurrence assay and BP molecular subtyping assay for prognosis and informing treatment decisions in MaBC. Citation Format: Jennifer Crozier, Julie Barone, Kalyan Banda, Beth Lesnikoski, Robert Maganini, Sami Diab, Ian Grady, Thomas Lomis, Charles Cox, Amy Truitt, Benjamin Nota, Andrea Menicucci, Erin Yoder, William Audeh, FLEX Investigators Group. Differential gene expression analysis and clinical utility of MammaPrint and BluePrint in male breast cancer patients [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS14-11.

A novel immune prognostic index for stratification of high-risk patients with early breast cancer

The prognostic value of current multigene assays for breast cancer is limited to hormone receptor-positive, human epidermal growth factor receptor 2-negative early breast cancer. Despite the prognostic significance of immune response-related genes in breast cancer, immune gene signatures have not been incorporated into most multigene assays. Here, using public gene expression microarray datasets, we classified breast cancer patients into three risk groups according to clinical risk and proliferation risk. We then developed the immune prognostic index based on expression of five immune response-related genes (TRAT1, IL2RB, CTLA4, IGHM and IL21R) and lymph node status to predict the risk of recurrence in the clinical and proliferation high-risk (CPH) group. The 10-year probability of disease-free survival (DFS) or distant metastasis-free survival (DMFS) of patients classified as high risk according to the immune prognostic index was significantly lower than those of patients classified as intermediate or low risk. Multivariate analysis revealed that the index is an independent prognostic factor for DFS or DMFS. Moreover, the C-index revealed that it is superior to clinicopathological variables for predicting prognosis. Its prognostic significance was also validated in independent datasets. The immune prognostic index identified low-risk patients among patients classified as CPH, regardless of the molecular subtype of breast cancer, and may overcome the limitations of current multigene assays.

Prosigna® breast cancer assay: histopathologic correlation, development, and assessment of size, nodal status, Ki-67 (SiNK™) index for breast cancer prognosis

The Prosigna® assay is a United States Food and Drug Administration (US-FDA) cleared molecular test for prognostic use in hormone receptor-positive stage I/II breast cancer in postmenopausal women. We analyzed histopathologic features of 79 cases with Prosigna® assay results and found a significant correlation between tumor size, grade, and Ki-67 labeling index with Prosigna® score (0–40, 41–60, and 61–100) and Prosigna® risk categories. Since the Prosigna® risk stratification is influenced by lymph node status, we designed an index that included lymph node status and the two most correlated variables (size and Ki-67 labeling index). This was termed the size, nodal, and Ki-67 (SiNK™) index and is calculated as follows: (size in mm) + (pN × 10) + (Ki-67 labeling index). The SiNK™ index was divided into ≤40 and >40 to test its prognostic significance in a well-characterized dataset of 106 ER+/HER2-negative stage I–II invasive breast cancers treated with standard multi-modality therapy with long term follow-up (average 101 months follow-up). Patients with SiNK™ ≤40 showed significantly improved distant recurrence-free survival (96% distant recurrence-free survival in SiNK™ ≤40 compared to 81% in SiNK™ >40; log-rank test p value: 0.0027). SiNK™ provides strong prognostic information in ERo+/HER2-negative breast cancers. SiNK™ index is simple to calculate using data from routine pathology reports. This should be further evaluated in larger datasets.

Comparison of three FDA-approved diagnostic immunohistochemistry assays of PD-L1 in triple-negative breast carcinoma

The Dako 28-8, Dako 22C3, and Ventana SP142 assays are among the approved programmed death ligand 1 (PD-L1) immunohistochemical companion/complementary diagnostics associated with cancer treatment. To address the concordance of these assays in triple-negative breast cancer (TNBC), we examined PD-L1 expression in 98 TNBC tumors and compared the positive rates using the three assays and three scoring methods: immune cell (IC), tumor cell (TC), and combined tumor cell and immune cell (TCIC) (an equivalent to combined positive score, or CPS). The positive rate for PD-L1 expression with a 1% cutoff was highest with 28-8, followed by the 22C3. These two assays demonstrated almost perfect or substantial agreement in all three scores. There was less agreement between SP142 and the other assays. Using the IC score or the TCIC score at a 1% cutoff (CPS 1), 4% of tumors were positive for PD-L1 with SP142 but negative with the other assays. Using SP142 with a 1% cutoff as a reference, the optimal cutoff for best agreement was at 1% for IC, 30% for TC, and 2% for TCIC (CPS 2) with the other two assays. A 2% cutoff for the 22C3 TCIC (CPS 2) yielded the best agreement with SP142 1% IC cutoff (kappa 0.65). Our study showed the lowest positive rate with SP142 among the three assays. However, the other two assays were not able to identify all tumors that would test positive with SP142 using IC or TCIC/CPS. It is unlikely to achieve high agreement between SP142 and the other two assays by changing the analytical cutoffs.

Abstract PO-068: Intratumoral heterogeneity of prognostic multigene signatures for breast cancer

Abstract Background Multigene assays for breast cancer are becoming more commonly used for research, diagnostic, and treatment-selection purposes. These assays are commonly based on a single tumor sample, so this study assesses whether clinically-relevant multigene scores are subject to misclassification due to technical variation or intratumoral heterogeneity. Methods Using FFPE blocks, tumors from 37 patients were sampled at different pathologist-selected spatial locations, targeting regions with distinct histological appearance. A second pathologist assessed mitotic activity and presence of immune infiltration for each specimen. Gene expression was quantified using the PAM50 assay. Samples were classified with respect to intrinsic subtype (Luminal A, Luminal B, HER2-enriched, or Basal-like) and risk of recurrence with proliferation score (ROR-P, high vs. med/low). Euclidean distances between samples were calculated across the 50 genes, and the distribution of Euclidean distances were compared for samples that were concordant vs. discordant for each multigene classifier for PAM50 or ROR-P. Results Of the 37 tumors, 11 had samples with discordant PAM50 subtype and 7 had samples with discordant ROR-P group (75% and 83% agreement, respectively). The Euclidean distance between paired samples with discordant PAM50 intrinsic subtype or ROR-P score was significantly greater than that among concordant tumors. Samples discordant for ROR-P had more heterogeneity in histological characteristics, while discordance of PAM50 subtype call was generally not predicted by heterogeneity of these histological characteristics. Conclusion The concordance of PAM50 subtype calls and ROR-P, despite oversampling of heterogenous-appearing tumor regions, demonstrates reproducibility of the PAM50 classifier for breast cancer tumor intrinsic subtyping. However, assay sampling strategies for histologically heterogeneous tumors merit further consideration. Citation Format: Amber N. Hurson, Alina Hamilton, Linnea T. Olsson, Erin L. Kirk, Benjamin C. Calhoun, Joseph Geradts, Mark E. Sherman, Melissa A. Troester. Intratumoral heterogeneity of prognostic multigene signatures for breast cancer [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-068.

Racial and ethnic disparities in 21-gene recurrence scores, chemotherapy, and survival among women with hormone receptor-positive, node-negative breast cancer.

Cutoffs of the 21-gene recurrence score (RS), a commonly used genomic assay for hormone receptor-positive breast cancer, have been updated. Little is known about racial/ethnic differences in RS results, RS-guided chemotherapy use, and outcomes on updated cutoff (RS ≥ 31 defined as high-risk) in the real-world setting. A total of 81,937 women [75.0% whites, 7.7% blacks, 8.3% Asian American/Pacific Islanders (AAPIs), and 9.0% Hispanics] diagnosed with hormone receptor-positive breast cancer between 2004 and 2015, who received the 21-gene assay, were identified from the Surveillance, Epidemiology, and End Results. Logistic regressions estimated the race-associated odds ratios (ORs) of RS and chemotherapy use. Cox regressions estimated the race-associated hazard ratios (HRs) of breast cancer-specific and all-cause mortality. Compared with white women, black women were more likely to have RS-defined high-risk tumors (adjusted OR [aOR] 1.29; 95% CI 1.16-1.42). In high RS, blacks had lower odds of chemotherapy use (aOR 0.76; 95% CI 0.62-0.94) than whites, particularly among women ≥ 65years (aOR 0.51; 95% CI 0.35-0.76), while AAPI and Hispanic women had no variation in chemotherapy use compared with whites in high RS. Black women had a higher risk of breast cancer-specific mortality (HR 1.37; 95% CI 1.12-1.67) and all-cause mortality compared with white women after adjusting for demographic and pathological factors, county-level socioeconomic deprivation, treatments and RS; AAPIs had lower mortality and Hispanics had similar mortality. Black women were more likely to have a high-risk RS tumor and less likely to receive chemotherapy in the group of high RS, especially those ≥ 65years. Further studies are needed to identify barriers to chemotherapy in black patients with high RS scores.

Abstract 2481: Concordance of PAM50 molecular subtyping between oligonucleotide microarray and nanoString nCounter assay for Taiwanese breast cancer

Abstract Concordance of PAM50 molecular subtyping between oligonucleotide microarray and nanoString nCounter assay for Taiwanese breast cancer Introduction Breast cancer is molecularly heterogeneous and at least five molecular subtypes have been defined according to intrinsic genes transcription. Currently microarrays, RT-PCR, and next generation RNA sequencing have been adopted for subtyping in addition to the original nanoString nCounter assay. This study aimed to evaluate the consistency in subtyping Taiwanese breast cancers. Methods A total of 109 Taiwanese breast cancers (24 with adjacent normal breast) were assayed with Affymetrix Human Genome U133 plus 2.0 arrays and 96 were assayed with the customized 145-gene nanoString Codeset BCeCSig, of which the academic PAM50 was investigated. Of note, 64 patients were assayed for both platforms. Subtyping with the nearest centroid (single sample prediction) was called for each patient; Spearman's rank correlation coefficients were used, and samples were unclassified if correlation coefficients to all 5 centroids were less than 0.1. Results Table 1 showed the distributions of molecular subtypes with clinical IHC results. For 24 matched normal breast tissues, 21 were classified as normal breast-like. For 64 breast cancers (one unclassified) tested for both platforms, 41 (65%) were classified with identical subtype, resulting in a fair Kappa statistic of 0.55. Taking nCounter as gold standard, classification accuracy was 50% (3/6), 72% (13/18), 53% (10/19), 87% (13/15), and 40% (2/5) for basal-like, HER2-enriched, luminal-A, luminal-B, and normal breast-like subtype using Affymetrix microarray. ER-/HER2- phenotype and basal-like subtype experienced worse relapse free survival at 8-year follow-up (55.6% and 63.6% censored). Table 1.Molecular subtypes and IHC phenotypes (two unclassified and one missing IHC result).Subtype IHCBasal-likeHER2-enrichedLuminal-ALuminal-BNormal breast-likeHR+/HER2+276174HR+/HER2-6442429HR-/HER2+625209HR-/HER2-144003 Conclusions: Using public domain microarrays as a handy shortcut for breast cancer molecular subtyping is luring in scientific communities. Our experiments showed that fundamental discrepancy existed between distinct approaches, and more cation should be taken without too much extrapolation. On the other hand, adjacent normal breast tissue did display normal breast-like character, and this subtype should be viewed as a continuum of surrounding stroma. Citation Format: Chi-Cheng Huang, Chao-Chiang Tu, Mong-Hsun Tsai, Liang-chuan Lai, Ching-Shui Huang. Concordance of PAM50 molecular subtyping between oligonucleotide microarray and nanoString nCounter assay for Taiwanese breast cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2481.

Abstract 4309: A novel immune prognostic index for the stratification of high-risk patients with early breast cancer

Abstract The prognostic or predictive value of current commercial multigene assays for breast cancer are limited to hormone receptor-positive, human epidermal growth factor receptor 2-negative (HR+/HER2-) early breast cancer. Despite the prognostic or predictive significance of immune response-related genes in breast cancer, immune gene signatures have not been incorporated into most current assays. Here, we developed a novel immune gene based-prognostic model to predict the risk of recurrence in high-risk women with early breast cancer. Using public gene expression microarray datasets for breast cancer, we classified breast cancer patients into three risk groups according to clinical risk and proliferation risk, and identified the most significant five immune response-related genes (TRAT1, IL2RB, CTLA4, IGHM and IL21R) associated with clinical outcome in the clinical and proliferation high-risk (CPH) subgroup. Immune prognostic index based on the combination of the expression of five immune response-related genes and lymph node status was developed to predict the risk of recurrence in high-risk breast cancer patients and its prognostic significance was validated in independent validation datasets. Disease-free survival (DFS) or distant metastasis-free survival (DMFS) of patients classified as high risk according to the immune prognostic index was significantly lower than those of patients classified as intermediate and low risk in the CPH group. Multivariate analysis demonstrated that the immune prognostic index is an independent prognostic factor for DFS or DMFS. Moreover, c-index showed that the immune prognostic index is superior to clinicopathological variables in predicting the prognosis. Our immune index was also prognostic in independent validation datasets. Our immune prognostic index identified low-risk patients among patients classified as CPH group in all molecular subtypes of breast cancer and may be used to overcome the limitations of the current multigene assay. Citation Format: Hannah Lee, Mi Jeong Kwon, Beom-Mo Koo, Jinil Han, Young Kee Shin. A novel immune prognostic index for the stratification of high-risk patients with early breast cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4309.

The Long Non-coding RNA LINC01705 Regulates the Development of Breast Cancer by Sponging miR-186-5p to Mediate TPR Expression as a Competitive Endogenous RNA.

Long non-coding RNAs (lncRNAs) may be a regulatory factor of tumorigenesis. However, it is unclear what its biomechanisms are in breast cancer. In this study, different lncRNAs were detected in breast cancer through microarray analysis (GSE119233) and LINC01705 was selected for further study. qRT-PCR was then utilized for the detection of LINC01705 expression in breast cancer cells. A transwell assay, flow cytometry, 5-ethynyl-2′-deoxyuridine (EdU), a cell counting Kit-8 (CCK-8), and a wound-healing assay were performed to determine cell migration, invasion, apoptosis, and proliferation in breast cancer, respectively. For the identification of potential targets of LINC01705, dual-luciferase reporter gene and bioinformatics assays were conducted. Moreover, for the clarification of their interaction and roles in the regulation of the occurrence of breast cancer, Western blotting and RIP assays were conducted. Our findings revealed high LINC01705 expression in breast cancer tissues relative to adjacent non-cancerous tissues (n = 40, P < 0.001). Overexpression of LINC01705 notably enhanced cell migration and proliferation in breast cancer. In addition, LINC01705 positively regulated the translocated promoter region, nuclear basket protein (TPR) through competition with miR-186-5p. In conclusion, our results suggest that LINC01705 is implicated in the progression of breast cancer via competitively binding to miR-186-5p as a competing endogenous RNA (ceRNA), thereby regulating TPR expression.

21-gene recurrence score testing utilization among older women from different races: A population-based study

ObjectivesThe influence of older age at diagnosis in combination with race/ethnicity on utilization and results of the 21-gene recurrence score (RS) assay for breast cancer (BC) patients is not fully understood. Our objectives were to evaluate the utilization of RS among older women with BC, the likelihood of a high-risk RS, and factors associated with breast cancer-specific mortality (BCSM) among older patients across different races. Materials and methodsWe utilized the Surveillance, Epidemiology, and Results (SEER) database with linked RS results to evaluate women with estrogen receptor-positive BC diagnosed 2004–2015. Multivariable logistic regression was used to describe the differences in utilization of RS testing and the association of high-risk RS according to patient characteristics. The Cox proportional hazards model was used to analyze factors associated with BCSM. ResultsWe found that 20.4% (109,244/536,555) of all women ≥18 and 14.3% (33,584/235,171) of women ≥65 underwent RS testing. Non-whites had lower odds of RS testing at younger ages whereas among women ≥65 there was no significant difference. After taking into account stage and grade, being ≥65 reduced the odds of high-risk RS in all races except American Indian/Alaskan Native. Age ≥ 65 was independently associated with increased hazard BCSM. Among women ≥65 with high-risk RS, chemotherapy was associated with lower hazard of BCSM in all races. ConclusionsOlder women are less likely to be tested for RS, but also less likely to have high-risk RS. Older women with high-risk RS, when given chemotherapy have reduced BCSM across all races.

Propensity score analysis of the prognostic value of genomic assays for breast cancer in diverse populations using the National Cancer Data Base.

Genomic assays such as Oncotype Dx (ODX) and MammaPrint are used for risk-adapted treatment decisions among patients with early breast cancer. However, to the authors' knowledge, concordance between genomic assays is modest. Using real-world data, the authors performed a comparative analysis of ODX and MammaPrint. A cohort of women diagnosed with early-stage, hormone receptor-positive breast cancer who received ODX or MammaPrint was established using the National Cancer Data Base (NCDB) for 2010 through 2016. Using the propensity score matching method, 2 groups of patients with similar clinical and demographic characteristics were defined: one group received ODX and the other received MammaPrint. The authors examined the association between use of the ODX or MammaPrint assays and overall survival using Cox models. Of the 451,693 eligible patients, approximately 45.3% received ODX and 1.8% received MammaPrint testing. The use of ODX increased from 36.1% in 2010 to 49.9% in 2016, whereas use of MammaPrint increased from 0.5% in 2010 to 3.3% in 2016. The authors matched 5042 patients who received ODX with 5042 patients who received MammaPrint. The 5-year risks of death for the MammaPrint low-risk group and the ODX low-risk group were 3.4% and 4.7%, respectively. The prognostic value of MammaPrint was similar to that of ODX; the C-index was 0.614 (95% confidence interval, 0.572-0.657) for MammaPrint and 0.581 (95% confidence interval, 0.530-0.631) for ODX. There was a difference in the performance of the ODX assay observed across racial and/or ethnic groups (P<.001), with a slightly better performance noted among white compared with African American and Hispanic individuals. Both the ODX and MammaPrint tests are good at identifying low-risk individuals who could be spared chemotherapy. The suboptimal performance of ODX in ethnic minority individuals deserves further investigation.

Concordance of multispectral immunofluorescence (mIF) with programmed death ligand 1 (PD-L1) and stromal tumor infiltrating lymphocyte (sTILs) clinical assays in early-stage breast cancer (BC).

e12589 Background: There is growing need for surrogate immune-based biomarkers in BC to enhance prediction accuracy and to facilitate comparisons of therapeutic activity in the context of clinical trials. We report mIF as a high-dimensional biomarker that is highly concordant with both PD-L1 (SP142) and sTIL clinical assays (H&amp;E), but with greater precision to quantify on-treatment pharmacodynamic effects. We also demonstrate how statistical modeling can be employed to improve precision of PD-L1/sTIL estimates, and reduce sample size requirements for biomarkers-driven comparative clinical trials. Methods: Samples were obtained from a recently-reported pre-surgical cytokine-based phase Ib immunotherapy (IRX-2) clinical trial (NCT02950259). Pre-treatment and resection tissues (n = 30) were analyzed for sTIL score, PD-L1 status, and mIF (PerkinElmer Vectra) using antibodies to quantify BC cells (cytokeratin), immune cells (CD3, CD8, CD163, FOXP3), and per-cell PD-L1 expression. Mixed effects regression models were employed to correct for intratumoral heterogeneity and enhance statistical precision. Monte Carlo simulations were employed to evaluate whether regression modeling could reduce sample size required to detect treatment-related increases in sTIL/PD-L1 in pre-surgical clinical trials. Results: Results: mIF sTIL estimates were highly correlated with H&amp;E sTIL score (pre-treatment samples: r = 0.59, p &gt; 0.001; excisional samples: r = 0.63, p &gt; 0. 001). mIF PD-L1 estimates were highly correlated with the PDL1 SP142 assay, with average densities increasing concordantly according to SP142 IC category (IC0 v. IC1, p = 0.04; IC0 v. IC2/3, p = 0.003). Our regression modeling approach dramatically improved power to demonstrate treatment-related changes in sTIL and PD-L1. The estimated sample size requirement to show the observed effect on sTIL score (1.80 fold change, CV 0.83) was n = 25 with conventional t-testing of means, versus n = 13 with regression modeling. Conclusions: mIF is concordant with SP142 and sTIL prognostic assays, but with increased precision to quantify treatment related changes. Regression modeling can dramatically improve the utility of mIF as a surrogate immune-based biomarker. Our approach is being utilized in ongoing phase II studies to compare the activity of pembrolizumab +/- locoregional cytokines (IRX-2) in triple negative BC, and paclitaxel/trastuzumab +/- pembrolizumab +/- pertuzumab in HER2-positive BC.

New Advances in Molecular Breast Cancer Pathology.

Breast cancer (BC) comprises a diverse spectrum of diseases featuring distinct presentation, morphological, biological, and clinical phenotypes. BC behaviour and response to therapy also vary widely. Current evidence indicates that traditional prognostic and predictive classification systems are insufficient to reflect the biological and clinical heterogeneity of BC. Advancements in high-throughput molecular techniques and bioinformatics have contributed to the improved understanding of BC biology, refinement of molecular taxonomies and the development of novel prognostic and predictive molecular assays. Molecular testing has also become increasingly important in the diagnosis and treatment of BC in the era of precision medicine. Despite the enormous amount of research work to develop and refine BC molecular prognostic and predictive assays, it is still in evolution and proper incorporation of these molecular tests into clinical practice to guide patient's management remains a challenge. With the increasing use of more sophisticated high throughput molecular techniques, large amounts of data will continue to emerge, which could potentially lead to identification of novel therapeutic targets and allow more precise classification systems that can accurately predict outcome and response to therapy. In this review, we provide an update on the molecular classification of BC and molecular prognostic assays. Companion diagnostics, contribution of massive parallel sequencing and the use of liquid biopsy are also highlighted.

The impact of Oncotype DX breast cancer assay results on clinical practice: a UK experience

BackgroundGenomic tests are increasingly being used by clinicians when considering adjuvant chemotherapy for patients with oestrogen receptor-positive (ER+), human epidermal growth factor 2-negative (HER2−) breast cancer. The Oncotype DX breast recurrence score assay was the first test available in the UK National Health Service. This study looked at how UK clinicians were interpreting Recurrence Scores (RS) in everyday practice.MethodsRS, patient and tumour characteristics and adjuvant therapy details were retrospectively collected for 713 patients from 14 UK cancer centres. Risk by RS-pathology-clinical (RSPC) was calculated and compared to the low/intermediate/risk categories, both as originally defined (RS < 18, 18–30 and > 30) and also using redefined boundaries (RS < 11, 11–25 and > 25).Results49.8%, 36.2% and 14% of patients were at low (RS < 18), intermediate (RS 18–30) and high (RS > 30) risk of recurrence, respectively. Overall 26.7% received adjuvant chemotherapy. 49.2% of those were RS > 30; 93.3% of patients were RS > 25. Concordance between RS and RSPC improved when intermediate risk was defined as RS 11–25.ConclusionsThis real-world data demonstrate the value of genomic tests in reducing the use of adjuvant chemotherapy in breast cancer. Incorporating clinical characteristics or RSPC scores gives additional prognostic information which may also aid clinicians’ decision making.