In:
Cancer Research, American Association for Cancer Research (AACR), Vol. 75, No. 15_Supplement ( 2015-08-01), p. 1708-1708
Abstract:
Background TNBC comprises 10-20% of breast cancers. Lehmann et al. identified 6 TNBC subtypes by gene expression profiling: BL1, BL2, IM, M, MSL & LAR. Despite the diversity of TNBC, standard of care is combination chemotherapy as in non TNBCs. Identification of chemosensitive TNBC subtypes is necessary. Chemoresistant TNBCs need alternative targets to improve treatment strategies. Aims 1. To validate an IHC biomarker panel to define molecular subtypes of TNBC 2. To correlate molecular subtypes with prognosis to identify appropriate therapy 3. To improve diagnostic tools to individualize therapy based on TNBC subtypes Methods A TMA was constructed of 197 TNBCs diagnosed from 1999 - 2014. An 8-protein IHC panel was developed to identify TNBC subtypes on FFPE tissue. The panel includes markers for key pathways to discriminate between 6 subtypes: AR, Bcl2, c-myc, TIE1, PDGFC, MMP2, Il2R, MSH2. To date, AR & Bcl2 have been stained and assessed, together with p53 & Ki67. 10% was used as the cut off for positivity. Clinical data were obtained from hospital records and incorporated in the database. Results On initial observation, AR+ tumors had an older age at diagnosis than AR- (60 v 56), lower rates of family history (36 v 87%) and longer DFS (31 v 21 months). Bcl2+ tumors had a younger age at diagnosis than Bcl2- (55 v 59), lower recurrence rates (25 v 31%) and longer DFS (33 v 15 months). High Ki67 tumors had a younger age at diagnosis than low Ki67 (56 v 65), higher rates of family history (30 v 14%), lower recurrence rates (16 v 25%) and longer DFS (30 v 2 months). By the time of presentation, the entire panel of 8 proteins will be analyzed. The clinicopathological association of specific TNBC subtypes and the impact of TNBC subtype on chemotherapy response will be statistically assessed. Analysis will include response, duration, DFS and OS. This study will ultimately correlate TNBC molecular subtypes with prognosis to aid clinical decision making, individualize therapies and improve patient outcomes. n = 197AR +AR -Bcl2 +Bcl2 -Ki67 & gt;10%Ki67 & lt;10%P53 +P53 -n141429963160149164%7%72%50%32%30%7%46%32%Median Age6056555956655755Range37-7729-9029-8431-9229-8235-9029-9030-88Family Historyn51232916182313%36%87%29%25%30%14%3%20%BRCA Mutation06331134BRCA 1-3121122BRCA 2-321--12NACT010544364PR-8324144SD-111-11-POD-111-11-Recurrencen3 (of 12)38 (of 138)25 (of 98)18 (of 58)9 (of 58)3 (of 12)22 (of 88)18 (of 62)%25%28%25%31%16%25%25%29%Median DFS312133153022731Range30-342-549-542-384-542-22-549-52Median OS3537373628363438Range5-890-1342-1341-1331-1379-1261-1340-137 Citation Format: Elaine M. Walsh, Aliaa Shalaby, Laura Murillo, Mark Webber, Michael Kerin, Sharon Glynn, Grace Callaghy, Helen Ingoldsby, Maccon Keane. Identification of triple negative breast cancer (TNBC) subtypes by an immunohistochemistry (IHC) panel with impact on clinical outcomes. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1708. doi:10.1158/1538-7445.AM2015-1708
Type of Medium:
Online Resource
ISSN:
0008-5472
,
1538-7445
DOI:
10.1158/1538-7445.AM2015-1708
Language:
English
Publisher:
American Association for Cancer Research (AACR)
Publication Date:
2015
detail.hit.zdb_id:
2036785-5
detail.hit.zdb_id:
1432-1
detail.hit.zdb_id:
410466-3
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