Abstract P2-10-02: Basal biomarkers nestin and INPP4b predict gemcitabine benefit in metastatic breast cancer: Results from the phase III SBG0102 clinical trial
Bibliographic record
Abstract
Abstract Background: A growing body of evidence is suggesting that basal-like and triple negative breast cancers may be particularly sensitive to nucleoside analogues (gemcitabine, capecitabine). In a prospective-retrospective analysis of the phase III SBG0102 clinical trial randomizing metastatic breast cancer patients to gemcitabine plus docetaxel (GD) or to higher-dose single agent docetaxel (D), patients with basal-like breast cancer by PAM50 gene expression had significantly better overall survival (OS) in the gemcitabine arm. By immunohistochemistry (IHC), triple negative status was not predictive, but is a poor surrogate for the basal-like intrinsic subtype. More accurate IHC biomarkers have since become available defining basal-like breast cancers by nestin positivity or by loss of inositol polyphosphate-4-phosphate (INPP4b). Methods: Formalin-fixed paraffin embedded blocks of primary tumor tissue corresponding to 270 of the 337 patients participated in the SBG0102 trial were used to build tissue microarrays. IHC staining and interpretation for nestin and INPP4b by pathologists (who had no access to clinical data) followed published methods. A prespecified statistical plan was executed independently by Danish Breast Cancer Group statisticians, testing the primary hypothesis that patients with basal breast cancer – defined as positive for nestin or negative for INPP4b, regardless of ER/PR/HER2 status – would have superior OS on the GD treatment arm when compared to the D treatment arm by interaction test. Secondary outcomes included time to tumor progression (TTP) and response rate. Kaplan-Meier method with log-rank test of nestin and INPP4b status was used to measure OS and TTP. Forest plots were used to visualize predictive capacities relative to IHC markers and treatment effects. Results: Two hundred fifty two cases were evaluable for this study, among which 38 (15%) had been classified as basal-like, 45 (18%) as HER2-Enriched, 74 (29%) as luminal A and 91 (36%) as luminal B by PAM50. Among 241 cases being evaluable for both IHC nestin and INPP4b markers, positive staining of nestin or loss of INPP4b was observed in 43 (17%) of the total cases and was significantly associated with PAM50 basal-like subtype (p<0.0001). Within a median follow up of 13 years, patients assigned as IHC-basal by virtue of being “nestin+ or INPP4b-” demonstrated a significantly lower OS when compared to non-basal cases defined as “nestin- and INPP4b+” (HR=2.45, 95% CI: 1.47-4.07) (p=0.0006). The IHC-basal patients did much better on the GD vs. the D arm (HR=0.36, 95% CI: 0.19-0.68) whereas there was no such difference in outcomes for other patients (HR=0.99). The interaction test was significant (p-interaction<0.005). Conclusions: The nestin/INPP4b IHC panel offers a practical and inexpensive technology to identify basal-like patients. In the metastatic setting, women with IHC-basal breast cancers defined using these markers have superior overall survival when randomized to gemcitabine-containing chemotherapy compared to docetaxel alone. Citation Format: Asleh-Aburaya K, Lyck Carstensen S, Burugu S, Gao D, Tykjær Jørgensen CL, Won JR, Jensen M-B, Balslev E, Lænkholm A-V, Nielsen DL, Ejlertsen B, Nielsen TO. Basal biomarkers nestin and INPP4b predict gemcitabine benefit in metastatic breast cancer: Results from the phase III SBG0102 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 P2-10-02.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".