Abstract PO2-14-04: Circulating tumor DNA after neoadjuvant chemotherapy is a better prognostic test than Residual Cancer Burden in patients with triple negative breast cancer and residual tumor
Bibliographic record
Abstract
Abstract Background The presence of residual tumor at surgery (non-pathological complete response or non-pCR) occurs in about half of TNBCs treated with neoadjuvant chemotherapy (NAC) signals chemoresistance. Although the addition of further adjuvant chemotherapy (Capecitabine/Xeloda) significantly improves RFS in these patients, the majority of patients nevertheless have a good prognosis, and thus may not require adjuvant Capecitabine. One of the best prognostic biomarkers in these patients is Residual Cancer Burden (RCB), which relies on the pathological examination of the residual tumor bed and lymph nodes obtained at surgery. Circulating tumor DNA (ctDNA) is a plasma-based biomarker, which has been shown to accurately detect minimal residual disease in breast cancer. We have previously shown that detection of ctDNA after NAC but before surgery in patients with non-pCR signals very poor prognosis, while non-detectable ctDNA is associated with an excellent prognosis. We now compare ctDNA to RCB score in TNBC patients with non-pCR. Methods In the multicenter TRICIA study, 44 TNBC patients with non-pCR after NAC in 5 hospital centers had consented to serial plasma collection prior to and after surgery. RCB score was calculated from pathology records. Whole exome sequencing (WES) was performed on DNA extracted from primary tumor biopsies or residual tumors at surgery to identify tumor-specific mutations (5 variants/patient). Digital droplet PCR (ddPCR) assays were developed for these mutations and tests were run in an academic hospital setting. Patients with at least one detectable mutation were considered ctDNA positive for a given time point. The detection of ctDNA was correlated with relapse-free survival (RFS). Results: The median follow up was 40 months. 19 of the 44 patients relapsed within 2 years after surgery. Detection of ctDNA at the end of NAC but before surgery (T1) was correlated with very poor RFS (H.R. = 0.15, p< 0.0001 (95% CI = 0.067-0.35)). 14/15 patients (93%) without detectable ctDNA did not recur, while 76% of patients with detectable ctDNA relapsed. The RCB score distribution was as follows: 7 RCB1, 21 RCB2 and 16 RCB3. According to RCB score, 1/7 RCB1, 11/21 RCB2 and 11/16 RCB3 patients relapsed. All but one of the relapsed patients had detectable ctDNA in at least one timepoint. All 11 RCB3 patients that relapsed had detectable ctDNA while none of the 5 RCB3 patients without relapse had detectable ctDNA. The one RCB1 patient with detectable ctDNA also relapsed. In cox regression analysis, the lack of ctDNA detection was significantly associated with excellent RFS in RCB2 (HR=0.16, p=0.003, (95% CI=0.05-.53)) and RCB3 groups (HR=0.10, p=0.0005, 95% CI= 0.03-.36). Conclusion ctDNA testing using ddPCR in an academic hospital-based setting at the post-NAC time point identifies an excellent prognostic group in TNBC patients with non-pCR and can discriminate very good from very poor prognosis in both RCB2 and RCB3 score subgroups. The detection of ctDNA may be superior to RCB scores in assessing prognosis in patients with non-pCR. Citation Format: Mark Basik, Talia Roseshter, Anna Klemantovich, Luca Cavallone, Adriana Aguilar-Mahecha, Josiane Lafleur, Cathy Lan, Oluwadara Elebute, Sarah Jenna, Jean-Francois Boileau, Manuela Pelmus. Circulating tumor DNA after neoadjuvant chemotherapy is a better prognostic test than Residual Cancer Burden in patients with triple negative breast cancer and residual tumor [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO2-14-04.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".