Impact of stromal tumor-infiltrating lymphocytes (sTILs) on response to neoadjuvant chemotherapy in triple-negative early breast cancer in the WSG-ADAPT TN trial.
Antineoplastic Combined Chemotherapy Protocols
/ therapeutic use
Biomarkers, Tumor
/ analysis
Breast Neoplasms
/ pathology
Female
Humans
Intracellular Signaling Peptides and Proteins
Lymphocytes, Tumor-Infiltrating
Neoadjuvant Therapy
/ methods
Reproducibility of Results
Triple Negative Breast Neoplasms
/ drug therapy
3-Week biopsy
Neoadjuvant chemotherapy
Pathologic complete response
Triple-negative breast cancer
sTils
Journal
Breast cancer research : BCR
ISSN: 1465-542X
Titre abrégé: Breast Cancer Res
Pays: England
ID NLM: 100927353
Informations de publication
Date de publication:
02 09 2022
02 09 2022
Historique:
received:
22
12
2021
accepted:
25
07
2022
entrez:
2
9
2022
pubmed:
3
9
2022
medline:
9
9
2022
Statut:
epublish
Résumé
Higher density of stromal tumor-infiltrating lymphocytes (sTILs) at baseline has been associated with increased rates of pathological complete response (pCR) after neoadjuvant chemotherapy (NACT) in triple-negative breast cancer (TNBC). While evidence supports favorable association of pCR with survival in TNBC, an independent impact of sTILs (after adjustment for pCR) on survival is not yet established. Moreover, the impact of sTIL dynamics during NACT on pCR and survival in TNBC is unknown. The randomized WSG-ADAPT TN phase II trial compared efficacy of 12-week nab-paclitaxel with gemcitabine versus carboplatin. This preplanned translational analysis assessed impacts of sTIL measurements at baseline (sTIL-0) and after 3 weeks of chemotherapy (sTIL-3) on pCR and invasive disease-free survival (iDFS). Predictive performance of sTIL-0 and sTIL-3 for pCR was quantified by ROC analysis and logistic regression; Kaplan-Meier estimation and Cox regression (with mediation analysis) were used to determine their impact on iDFS. For prediction of pCR, the AUC statistics for sTIL-0 and sTIL-3 were 0.60 and 0.63, respectively, in all patients; AUC for sTIL-3 was higher in NP/G. The positive predictive value (PPV) of "lymphocyte-predominant" status (sTIL-0 ≥ 60%) at baseline was 59.3%, though only 13.0% of patients had this status. To predict non-pCR, the cut point sTIL-0 ≤ 10% yielded PPV = 69.5% while addressing 33.8% of patients. Higher sTIL levels (particularly at 3 weeks) were independently and favorably associated with better iDFS, even after adjusting for pCR. For example, the adjusted hazard ratio for 3-week sTILs ≥ 60% (vs. < 60%) was 0.48 [0.23-0.99]. Low cellularity in 3-week biopsies was the strongest individual predictor for pCR (in both therapy arms), but not for iDFS. The independent impact of sTILs on iDFS suggests that favorable immune response can influence key tumor biological processes for long-term survival. The results suggest that the reliability of pCR following neoadjuvant therapy as a surrogate for survival could vary among subgroups in TNBC defined by immune response or other factors. Dynamic measurements of sTILs under NACT could support immune response-guided patient selection for individualized therapy approaches for both very low levels (more effective therapies) and very high levels (de-escalation concepts). Clinical trials No: NCT01815242, retrospectively registered January 25, 2013.
Sections du résumé
BACKGROUND
Higher density of stromal tumor-infiltrating lymphocytes (sTILs) at baseline has been associated with increased rates of pathological complete response (pCR) after neoadjuvant chemotherapy (NACT) in triple-negative breast cancer (TNBC). While evidence supports favorable association of pCR with survival in TNBC, an independent impact of sTILs (after adjustment for pCR) on survival is not yet established. Moreover, the impact of sTIL dynamics during NACT on pCR and survival in TNBC is unknown.
METHODS
The randomized WSG-ADAPT TN phase II trial compared efficacy of 12-week nab-paclitaxel with gemcitabine versus carboplatin. This preplanned translational analysis assessed impacts of sTIL measurements at baseline (sTIL-0) and after 3 weeks of chemotherapy (sTIL-3) on pCR and invasive disease-free survival (iDFS). Predictive performance of sTIL-0 and sTIL-3 for pCR was quantified by ROC analysis and logistic regression; Kaplan-Meier estimation and Cox regression (with mediation analysis) were used to determine their impact on iDFS.
RESULTS
For prediction of pCR, the AUC statistics for sTIL-0 and sTIL-3 were 0.60 and 0.63, respectively, in all patients; AUC for sTIL-3 was higher in NP/G. The positive predictive value (PPV) of "lymphocyte-predominant" status (sTIL-0 ≥ 60%) at baseline was 59.3%, though only 13.0% of patients had this status. To predict non-pCR, the cut point sTIL-0 ≤ 10% yielded PPV = 69.5% while addressing 33.8% of patients. Higher sTIL levels (particularly at 3 weeks) were independently and favorably associated with better iDFS, even after adjusting for pCR. For example, the adjusted hazard ratio for 3-week sTILs ≥ 60% (vs. < 60%) was 0.48 [0.23-0.99]. Low cellularity in 3-week biopsies was the strongest individual predictor for pCR (in both therapy arms), but not for iDFS.
CONCLUSION
The independent impact of sTILs on iDFS suggests that favorable immune response can influence key tumor biological processes for long-term survival. The results suggest that the reliability of pCR following neoadjuvant therapy as a surrogate for survival could vary among subgroups in TNBC defined by immune response or other factors. Dynamic measurements of sTILs under NACT could support immune response-guided patient selection for individualized therapy approaches for both very low levels (more effective therapies) and very high levels (de-escalation concepts).
TRIAL REGISTRATION
Clinical trials No: NCT01815242, retrospectively registered January 25, 2013.
Identifiants
pubmed: 36056374
doi: 10.1186/s13058-022-01552-w
pii: 10.1186/s13058-022-01552-w
pmc: PMC9438265
doi:
Substances chimiques
Biomarkers, Tumor
0
Intracellular Signaling Peptides and Proteins
0
STIL protein, human
0
Banques de données
ClinicalTrials.gov
['NCT01815242']
Types de publication
Clinical Trial, Phase II
Journal Article
Randomized Controlled Trial
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
58Informations de copyright
© 2022. The Author(s).
Références
Int J Cancer. 2020 Jan 1;146(1):262-271
pubmed: 31162838
Ann Oncol. 2018 Jan 1;29(1):170-177
pubmed: 29045543
J Pers Soc Psychol. 1986 Dec;51(6):1173-82
pubmed: 3806354
NPJ Breast Cancer. 2020 May 12;6:17
pubmed: 32411819
J Clin Oncol. 2019 Mar 1;37(7):559-569
pubmed: 30650045
Ann Oncol. 2009 Dec;20(12):1913-27
pubmed: 19901010
N Engl J Med. 2010 Nov 11;363(20):1938-48
pubmed: 21067385
Lancet Oncol. 2018 Jan;19(1):40-50
pubmed: 29233559
Breast Cancer Res. 2020 May 14;22(1):46
pubmed: 32410705
Clin Cancer Res. 2020 Jun 1;26(11):2704-2710
pubmed: 31796517
J Clin Oncol. 2007 Jul 1;25(19):2650-5
pubmed: 17602071
J Clin Oncol. 2022 Jul 20;40(21):2361-2374
pubmed: 35353548
Semin Cancer Biol. 2018 Oct;52(Pt 2):16-25
pubmed: 29024776
NPJ Breast Cancer. 2020 May 12;6:16
pubmed: 32411818
Clin Cancer Res. 2007 Apr 15;13(8):2329-34
pubmed: 17438091
J Clin Oncol. 2010 Jan 1;28(1):105-13
pubmed: 19917869
J Clin Oncol. 2013 Mar 1;31(7):860-7
pubmed: 23341518
Front Oncol. 2017 Aug 03;7:156
pubmed: 28824872
Mod Pathol. 2016 Oct;29(10):1155-64
pubmed: 27363491
Breast Cancer Res Treat. 2013 Apr;138(2):591-9
pubmed: 23460246
Anticancer Res. 2020 Apr;40(4):1883-1890
pubmed: 32234876
J Natl Cancer Inst. 2018 Jun 1;110(6):628-637
pubmed: 29228315
Lancet. 2014 Jul 12;384(9938):164-72
pubmed: 24529560
Clin Cancer Res. 2016 May 15;22(10):2323-8
pubmed: 26842238
Nat Rev Clin Oncol. 2016 Apr;13(4):228-41
pubmed: 26667975
Ann Oncol. 2019 Feb 1;30(2):236-242
pubmed: 30590484
Breast Cancer Res. 2020 May 14;22(1):47
pubmed: 32408905
Curr Opin Oncol. 2019 Nov;31(6):486-492
pubmed: 31464762
J Clin Oncol. 2008 Mar 10;26(8):1275-81
pubmed: 18250347
J Clin Oncol. 2016 Apr 10;34(11):1223-30
pubmed: 26834066
Chin Med J (Engl). 2020 Mar 5;133(5):552-560
pubmed: 32044815