Serie, DJ

Abstract BACKGROUND Clinical trials NRG/NSABP B-31 and Alliance/NCCTG N9831 demonstrated that trastuzumab added to chemotherapy extended disease-free survival (DFS) in breast cancer patients (pts) in the adjuvant setting (Romond et al). However, the degree of trastuzumab benefit varies among pts. We previously described an 8-gene model that was predictive for trastuzumab benefit, which was validated in an independent cohort of B-31 patients (Pogue-Geile 2013). The 8-gene signature subtyped B-31 pts in an independent validation cohort into three trastuzumab benefit groups: one with large benefit HR=0.27, one with medium benefit HR=0.56, and one with little to no benefit HR=1.56. The purpose of this study was to validate the 8-gene model in pts enrolled into N9831, which tested the efficacy of adding trastuzumab to doxorubicin plus cyclophosphamide → paclitaxel by randomizing pts into one of three arms: chemotherapy only (Arm A), trastuzumab given after chemotherapy (Arm B), or trastuzumab given concurrently with chemotherapy (Arm C). METHODS NCounter data, consisting of 8 predictive genes and 4 house-keeping genes, for 1,379 patients enrolled into N9831 were used to assign each patient to one of the three benefit groups. Assignments to one of the three trastuzumab benefit groups based on the 8-gene model were made by the NSABP/NRG Pathology Laboratory Biostatistician, who was blinded to outcome data. Predictions were sent to N9831 investigators and accuracy of predictions were tested in pts enrolled into arms A and C (N=892) using Cox models adjusted for age, nodes, ER/PR status, tumor size, and grade. Recurrence-free survival (RFS) and DFS were used as endpoints. RESULTS Tumors from N9831were placed into one of the three trastuzumab benefit groups based on the 8-gene signature. The N9831 pts in the predicted-large benefit group had a hazard ratio (HR) of 0.47, P=0.0006, pts in the predicted-medium benefit group had an HR of 0.6, P=0.02, and the predicted-low benefit group had an HR of 1.54, P=0.375. The interaction P value was significant at 0.019 in adjusted Cox models. The RFS at 10 years for trastuzumab-treated pts was 72%, 83%, and 83% in the low, medium, and large benefit groups, respectively. CONCLUSIONS The 8-gene signature developed in a discovery cohort and validated in an independent cohort of B-31 pts has now been validated in N9831. Many anti-HER2 therapies such as lapatinib, afatinib, neratinib, pertuzumab, and TDM-1 have been approved for treatment in metastatic breast cancer pts and although these agents have shown responses, the actual improvements in outcomes in pts is variable and it is not known which pts actually receive benefit. Thus this signature may be clinically useful in identifying pts who may benefit from additional treatment beyond trastuzumab or for stratification of pts enrolled into clinical trials testing new anti-HER2 therapies. SUPPORT U10CA180868, -180822, UG1CA189867, U24CA196067, the PA DOH, which disclaims certain responsibilities, Genentech, Inc., and the Breast Cancer Research Foundation. Citation Format: Pogue-Geile KL, Song N, Serie DJ, Thompson EA. The NSABP/NRG 8-gene signature accurately predicts degree of benefit from trastuzumab in Alliance/NCCTG N9831: Validation of the 8-gene signature in an independent clinical trial [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 PD3-18.

Abstract Background: While previous study showed that the enrichment of immune-related gene expression was associated with outcome in HER2+ patients receiving sequential or concurrent trastuzumab (H), stromal tumor infiltrating lymphocytes (sTIL) have not been consistently shown to associate with outcome in this group of patients. Given that TIL scoring may be subjective, we analyzed molecular signatures of different subsets of tumor infiltrating immune cell populations, using NanoStringTM gene expression data to assess molecular TIL (mTIL) signature enrichment and intrinsic subtype as a function of relapse-free survival (RFS). Methods: NanoStringTM technology was used to quantify mRNA in samples from 1,280 patients in N9831, 168 patients in FinHer, and 170 patients in FinXX. In N9831, patients in arm A were treated with chemotherapy alone (AC-T), arm B received chemotherapy followed by sequential H (AC-T-H), and arm C received H concurrently with chemotherapy (AC-TH). In the FinHer trial, H was given concurrently for 9 weeks and either 1 year or 9 weeks in FinXX trial. Cox proportional hazard ratio (HR) was used to determine the association of each gene signature with RFS. Different immune subset signatures, including CD45, B-cells, CD8 T-cells, cytotoxic-cells, and T-cells were analyzed using algorithms developed by NanoString. Results: In N9831, CD45, cytotoxic-cell, and T-cell signatures were significantly associated with improved RFS in patients receiving chemotherapy alone and AC-T-H. However, none of the mTIL signatures were significantly associated with outcome in patients receiving AC-TH. Patients lacking CD45 enrichment had better outcome when H was given concurrently with chemotherapy. The 10-year Kaplan-Meier estimates for RFS in arm B patients with CD45 enrichment or no enrichment were 81.3% and 72.6%, respectively (HR 0.63 [95% CI, 0.42-0.93]; p = 0.02), and in arm C were 83.6% and 79.8%, respectively (HR 0.79, 95%CI 0.49-1.28; p = 0.34). Among patients with HER2-enriched subtype, all of the mTIL signatures were associated with improved RFS in arm A (AC-T) and B (AC-T-H) but remained non-significant in arm C (AC-TH). In patients with luminal subtypes, mTIL signatures were not significantly associated with outcome in patients treated with chemotherapy alone. Similar findings were observed in the FinHer and FinXX trials, in which, none of mTIL signatures were significantly associated with outcome among patients who received H. Conclusion: This analysis sheds light on previous discrepancy between immune-related gene signature and sTIL findings. Our data also suggests that the poor prognosis associated with lack of infiltrating immune cells can be partly overcome by the concomitant administration of H with chemotherapy. mTIL signatures, specifically CD45, cytoxic, and T cells, were prognostically associated with improved outcome in patients receiving chemotherapy without concurrent trastuzumab. Understanding the role of the immune system in response to H will require a higher degree of granularity than can be achieved by histological quantification of TILs. Further studies are needed to validate the significance of mTIL signatures as predictive or prognostic biomarker in HER+ patients. Citation Format: Chumsri S, Serie DJ, Mashadi-Hossein A, Tenner KS, Lauttia SL, Moreno-Aspitia A, McLaughlin SA, Nassar A, Warren S, Danaher P, Colon-Otero G, Lindman H, Joensuu H, Perez EA, Thompson EA. Prognostic value of molecular tumor infiltrating lymphocyte (mTIL) signatures in HER2-positive breast cancer patients in N9831 and FinHer/FinXX trials [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 PD5-06.

Abstract Fusion transcript 24analysis by five groups, each using "in house" analytical workflow to analyze RNA-seq data from 813 breast tumors from The Cancer Genome Atlas project detected 2514 high confidence RNA fusions (2 or more junction spanning reads detected by 2 or more groups). A subset of tumors with fusions were evaluated for chromosomal rearrangement using whole genome sequence data (WGS), and about half of the high confidence fusions could be validated, with the remainder likely subclonal and therefore below the limits of detection by WGS at the relatively low depth of coverage (30X) available. The majority of tumors contained one or more fusion transcript (range 0-24 fusions/tumor), but recurrence of specific chimaeric transcripts was low. Only ESR1->CCDC170, C20orf3->ACSS1, and USP22->MYH10 fusions were detected in 10 or more tumors. Additional ESR1 fusions were detected with AKAP12, BNC2, C6orf211, GNAS, POLH, USP25, and UTRN, within 19 tumors, primarily of the Luminal B subtype. RARA was the second most common 5' fusion partner with 17 tumors, predominately of the HER2-enriched subtype, expressing out of frame RARA fusions to 19 different 3' fusion partners. Other common 5' fusion partners included FBXL20, USP22, USP32, BCAS3, MED1, BPTF, ERBB2, MED24, and PPF1A1 (expressed in 10 or more tumors each). The most common 3' fusion partners were ERBB2, CCDC170, PITPNC1, ACSS1, MYH10, IKZF3, and RAB6A (10 or more tumors each). HER2-enriched tumors expressed significantly more fusions than other subtypes (4.9 fusions/tumor vs 3.3 for Basal-like, 1.3 for LumA, and 3.2 for LumB). Almost all HER2-enriched tumors expressed fusions (97%), whereas 85% of Basal-like tumors and 79% of Luminal B tumors expressed one or more fusions. Among Luminal A tumors, only 48% expressed one or more fusion transcript. Those Luminal A tumors with multiple fusion transcripts contained significantly more copy number aberrations and were enriched for expression of mitotic cell cycle genes (p=3.07E-18), characteristic of the recently described high risk CNH subclass of Luminal A tumors. We conclude that, consistent with other observations, breast tumors generally exhibit a high level of genomic instability, associated with multiple copy number alterations and multiple fusion transcripts. However, recurrence of specific fusion transcripts is low. About half of Luminal A tumors express fusion transcripts; and these tumors exhibit multiple copy number events, consistent with high level genomic instability, as well as enriched expression of mitotic cell cycle genes. These tumors appear to be related to the relatively high risk Luminal A CNH subclass, and express high levels of aurora kinases and polo-like kinases, which might be considered as therapeutic targets. Given the increasing emphasis on transcript profiling of clinical samples and the clinical significance of high risk Luminal A tumors, it may be timely to consider inclusion of fusion transcripts in such analyses as surrogate markers of genomic instability and potential therapeutic and/or prognostic indicators. Citation Format: Thompson EA, Asmann YW, Su X, Ellis MJ, Shao J, Hu Y, White KP, Cherniack AD, Hoadley KA, Serie DJ, Perez EA, Perou CM. A comprehensive analysis of fusion transcripts in breast cancer reveals associations between number of fusion transcripts, copy number events, gene expression profiles, and potentially clinical outcome. [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 S4-02.

Abstract Background: Mammographic density, the variation in fat, epithelial and stromal tissues seen on screening mammography, is a strong risk factor for breast cancer and can be modified by hormonal agents. Changes in density from tamoxifen or postmenopausal hormone (PMH) use are associated with risk, suggesting that density may be a surrogate marker of therapeutic efficacy. Aromatase inhibitors (AIs) are given as adjuvant therapy in hormone receptor positive postmenopausal breast cancer and are known to decrease levels of estrone and estradiol in both serum and breast tissue. Our goal here was to examine the influence of AIs on mammographic density in women with early breast cancer. Methods: We conducted a case-control study of postmenopausal breast cancer patients initiating adjuvant AI therapy (anastrozole or exemestane) on protocols NCIC CTG MA27, NCCTG N063I and MC (Mayo Clinic) 0532. Eligibility included; an intact contralateral breast with no prior surgery; a screening mammogram within twelve months before AI initiation and at 9-15 months on therapy; no prior endocrine therapy and informed consent. Controls were sampled from the Mayo Mammography Health Study, a cohort of 19,924 receiving screening mammography at the Mayo Clinic, and matched to cases on age, prior PMH use, baseline body mass index (BMI) and interval between mammograms. Pre-treatment and on-study mammograms for cases (corresponding mammograms for controls) were digitized. Change in percent density was estimated on the craniocaudal view of the non-cancerous breast using two methods: a subjective assessment of change by an expert radiologist (within 5%; 5-10% increase, 10-25% increase, 25%+ increase, 5-10% decrease, 10-25% decrease and 25%+ decrease) and a quantitative assessment of absolute change using a computer-assisted thresholding program (Cumulus). Analyses compared magnitude of change in density by both the subjective and quantitative methods between cases and matched controls. Results: 574 pairs were eligible for analyses (MA27-505 cases; N063I-12 cases; MC0532-57 cases). Characteristics of the two groups are shown in the table below. Using either density estimation method, there was a greater decrease in density among women on AI therapy vs. matched controls. In 33% (95% CI: 29-37%) of pairs, there was at least a one greater category decrease for the case relative to her control by subjective estimation. In 14% (95% CI: 11-18%) of the pairs, there was at least a 5% greater decrease for the case relative to her control by quantitative estimation. Data will be available according to AI class (non-steroidal versus steroidal) in November. Conclusions: In the largest report to date to examine the influence of AI therapy on mammographic density, we provide evidence that AI is associated with decreases in density in a small subgroup of women. We are currently examining factors that influence these AI-associated decreases in density and whether these differences are unique to one class of AI. (Supported in part by NIH grants P50CA116201, U01GM61388, U10CA77202, U10CA25224) Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr P2-09-03.