Abstract P2-05-19: Impact of TP53 functional mutation type on clinical outcomes of advanced breast cancer patients
Bibliographic record
Abstract
Abstract Background: Next-generation sequencing (NGS) has improved our understanding of breast cancer (BC) biology. Somatic TP53 mutations (TP53m) are present in 30% of BC, and are particularly common in triple negative (TN) tumors. Although multiple studies have indicated poor prognosis in BC patients (pts) with TP53m, there is still uncertainty regarding its correlation with clinical outcomes, which may be influenced by other molecular, histological and clinical factors. Our aim was to investigate the functional effect of TP53m in advanced BC pts and evaluate associations with clinical outcomes in different BC subtypes. Methods: Advanced BC pts enrolled in an institutional molecular screening program (NCT01505400) were evaluated. TP53m were assessed on archived FFPE tumor samples using NGS Illumina MiSeq TruSeq Amplicon Cancer Panel (500x depth of coverage; 10-15% variant detection threshold). Functional effect of TP53m was classified as gain of function (GOF), loss of function (LOF) and variants of unknown significance (VUS), as adapted from IARC TP53 database. Patients' medical records were reviewed for clinical data. TP53m functional effect class was correlated with BC subtypes using Fisher's exact test. TP53m were correlated with time from surgery with curative intent to distant relapse (TTR) and overall survival from diagnosis to death (OS) using Log-rank test. Impact of TP53m functional type on TTR and OS was determined by Cox proportional hazard model. Results: The study enrolled 220 pts from Oct 2012 - Nov 2015. Median age at diagnosis was 46 years (range 21-80). The cohort included 141 ER+/HER2- (64%), 25 HER2+ (11%) and 54 triple negative (TN) (25%) BC pts. Stage at diagnosis was: I (14%), II (33%), III (24%), IV (21%) and not documented in 8%. Median follow-up was 15 months (m) (range 1-41). Somatic TP53 variants were identified in 80 patients [36%; 23 ER+/HER2- (16%), 18 HER2+ (72%), 39 TN (72%)]. By TP53 functional class, there were 19 GOF (24%), 35 LOF (44%) and 26 VUS (32%). Histologic subtypes were not correlated with TP53m function (p = 0.09). TTR for 174 pts, who underwent surgery with curative intent at diagnosis, and OS (94 death events, 43%) are reported in Table 1. TTR and OS were shorter in TP53m compared to TP53 wild type (wt) in the overall cohort and the ER+/HER2- subgroup, but not the HER2+ and TN subgroups. TABLE 1: Log rank test resultsTP53mTP53wtP valueTotal cohortTTR (m)2054<0.001 OS (m)58195<0.001ER+/HER2-TTR (m)2958<0.001 OS (m)52208<0.001HER2+TTR (m)32940.1 OS (m)1132750.42TNTTR (m)17180.54 OS (m)46490.89 In the ER+ subgroup TP53m was significant prognostic factor associated with poor outcome in univariate analysis and remained significant after adjusting for age, stage and grade at diagnosis, neoadjuvant chemotherapy and germline BRCA1/2 status, with HR for TTR 3.4 (95%CI: 1.9-6.0, p<0.001) and OS 10.2 (95% CI: 4.5-23.4, p<0.001). Within the TP53m group, the functional class of TP53m (GOF, LOF, VUS) was not associated with TTR (23 m, 28 m, 17m, p =0.94) or OS (75 m, 58 m, 49 m, p =0.47). Conclusions: In advanced breast cancer, somatic TP53m status is prognostic for outcome in ER+/HER2- but not TNBC or HER2+ subtypes. TP53m functional class was not associated with any difference in survival outcomes. Citation Format: Stjepanovic N, Garg S, Berman H, Warr D, Amir E, Cescon D, Elser C, Wang L, Kamel-Reid S, Siu L, Bedard PL, Stockley T. Impact of TP53 functional mutation type on clinical outcomes of advanced breast cancer patients [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 P2-05-19.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".