Tumor mutational burden and immune infiltration as independent predictors of response to neoadjuvant immune checkpoint inhibition in early TNBC in GeparNuevo

T Karn; C Denkert; K E Weber; U Holtrich; C Hanusch; B V Sinn; B W Higgs; P Jank; H P Sinn; J Huober; C Becker; J-U Blohmer; F Marmé; W D Schmitt; S Wu; M van Mackelenbergh; V Müller; C Schem; E Stickeler; P A Fasching; C Jackisch; M Untch; A Schneeweiss; S Loibl

doi:10.1016/j.annonc.2020.05.015

Tumor mutational burden and immune infiltration as independent predictors of response to neoadjuvant immune checkpoint inhibition in early TNBC in GeparNuevo

Standard

Tumor mutational burden and immune infiltration as independent predictors of response to neoadjuvant immune checkpoint inhibition in early TNBC in GeparNuevo. / Karn, T; Denkert, C; Weber, K E; Holtrich, U; Hanusch, C; Sinn, B V; Higgs, B W; Jank, P; Sinn, H P; Huober, J; Becker, C; Blohmer, J-U; Marmé, F; Schmitt, W D; Wu, S; van Mackelenbergh, M; Müller, V; Schem, C; Stickeler, E; Fasching, P A; Jackisch, C; Untch, M; Schneeweiss, A; Loibl, S.

In: ANN ONCOL, Vol. 31, No. 9, 09.2020, p. 1216-1222.

Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review

Harvard

Karn, T, Denkert, C, Weber, KE, Holtrich, U, Hanusch, C, Sinn, BV, Higgs, BW, Jank, P, Sinn, HP, Huober, J, Becker, C, Blohmer, J-U, Marmé, F, Schmitt, WD, Wu, S, van Mackelenbergh, M, Müller, V, Schem, C, Stickeler, E, Fasching, PA, Jackisch, C, Untch, M, Schneeweiss, A & Loibl, S 2020, 'Tumor mutational burden and immune infiltration as independent predictors of response to neoadjuvant immune checkpoint inhibition in early TNBC in GeparNuevo', ANN ONCOL, vol. 31, no. 9, pp. 1216-1222. https://doi.org/10.1016/j.annonc.2020.05.015

APA

Karn, T., Denkert, C., Weber, K. E., Holtrich, U., Hanusch, C., Sinn, B. V., Higgs, B. W., Jank, P., Sinn, H. P., Huober, J., Becker, C., Blohmer, J-U., Marmé, F., Schmitt, W. D., Wu, S., van Mackelenbergh, M., Müller, V., Schem, C., Stickeler, E., ... Loibl, S. (2020). Tumor mutational burden and immune infiltration as independent predictors of response to neoadjuvant immune checkpoint inhibition in early TNBC in GeparNuevo. ANN ONCOL, 31(9), 1216-1222. https://doi.org/10.1016/j.annonc.2020.05.015

Vancouver

Karn T, Denkert C, Weber KE, Holtrich U, Hanusch C, Sinn BV et al. Tumor mutational burden and immune infiltration as independent predictors of response to neoadjuvant immune checkpoint inhibition in early TNBC in GeparNuevo. ANN ONCOL. 2020 Sep;31(9):1216-1222. https://doi.org/10.1016/j.annonc.2020.05.015

Bibtex

@article{fea27a3963b54470b21e42b874043aec,

title = "Tumor mutational burden and immune infiltration as independent predictors of response to neoadjuvant immune checkpoint inhibition in early TNBC in GeparNuevo",

abstract = "BACKGROUND: The predictive value of tumor mutational burden (TMB), alone or in combination with an immune gene expression profile (GEP), for response to neoadjuvant therapy in early triple negative breast cancer (TNBC) is currently not known, either for immune checkpoint blockade (ICB) or conventional chemotherapy.PATIENTS AND METHODS: We obtained both whole exome sequencing and RNA-Seq data from pretreatment samples of 149 TNBC of the recent neoadjuvant ICB trial, GeparNuevo. In a predefined analysis, we assessed the predictive value of TMB and a previously developed immune GEP for pathological complete remission (pCR).RESULTS: Median TMB was 1.52 mut/Mb (range 0.02-7.65) and was significantly higher in patients with pCR (median 1.87 versus 1.39; P = 0.005). In multivariate analysis, odds ratios for pCR per mut/Mb were 2.06 [95% confidence intervals (CI) 1.33-3.20, P = 0.001] among all patients, 1.77 (95% CI 1.00-3.13, P = 0.049) in the durvalumab treatment arm, and 2.82 (95% CI 1.21-6.54, P = 0.016) in the placebo treatment arm, respectively. We also found that both continuous TMB and immune GEP (or tumor infiltrating lymphocytes) independently predicted pCR. When we stratified patients in groups based on the upper tertile of TMB and median GEP, we observed a pCR rate of 82% (95% CI 60% to 95%) in the group with both high TMB and GEP in contrast to only 28% (95% CI 16% to 43%) in the group with both low TMB and GEP.CONCLUSIONS: TMB and immune GEP add independent value for pCR prediction. Our results recommend further analysis of TMB in combination with immune parameters to individually tailor therapies in breast cancer.",

keywords = "Biomarkers, Tumor, Humans, Immune Checkpoint Inhibitors, Mutation, Neoadjuvant Therapy, Triple Negative Breast Neoplasms/drug therapy",

author = "T Karn and C Denkert and Weber, {K E} and U Holtrich and C Hanusch and Sinn, {B V} and Higgs, {B W} and P Jank and Sinn, {H P} and J Huober and C Becker and J-U Blohmer and F Marm{\'e} and Schmitt, {W D} and S Wu and {van Mackelenbergh}, M and V M{\"u}ller and C Schem and E Stickeler and Fasching, {P A} and C Jackisch and M Untch and A Schneeweiss and S Loibl",

year = "2020",

month = sep,

doi = "10.1016/j.annonc.2020.05.015",

language = "English",

volume = "31",

pages = "1216--1222",

journal = "ANN ONCOL",

issn = "0923-7534",

publisher = "Oxford University Press",

number = "9",

}

RIS

TY - JOUR

T1 - Tumor mutational burden and immune infiltration as independent predictors of response to neoadjuvant immune checkpoint inhibition in early TNBC in GeparNuevo

AU - Karn, T

AU - Denkert, C

AU - Weber, K E

AU - Holtrich, U

AU - Hanusch, C

AU - Sinn, B V

AU - Higgs, B W

AU - Jank, P

AU - Sinn, H P

AU - Huober, J

AU - Becker, C

AU - Blohmer, J-U

AU - Marmé, F

AU - Schmitt, W D

AU - Wu, S

AU - van Mackelenbergh, M

AU - Müller, V

AU - Schem, C

AU - Stickeler, E

AU - Fasching, P A

AU - Jackisch, C

AU - Untch, M

AU - Schneeweiss, A

AU - Loibl, S

PY - 2020/9

Y1 - 2020/9

N2 - BACKGROUND: The predictive value of tumor mutational burden (TMB), alone or in combination with an immune gene expression profile (GEP), for response to neoadjuvant therapy in early triple negative breast cancer (TNBC) is currently not known, either for immune checkpoint blockade (ICB) or conventional chemotherapy.PATIENTS AND METHODS: We obtained both whole exome sequencing and RNA-Seq data from pretreatment samples of 149 TNBC of the recent neoadjuvant ICB trial, GeparNuevo. In a predefined analysis, we assessed the predictive value of TMB and a previously developed immune GEP for pathological complete remission (pCR).RESULTS: Median TMB was 1.52 mut/Mb (range 0.02-7.65) and was significantly higher in patients with pCR (median 1.87 versus 1.39; P = 0.005). In multivariate analysis, odds ratios for pCR per mut/Mb were 2.06 [95% confidence intervals (CI) 1.33-3.20, P = 0.001] among all patients, 1.77 (95% CI 1.00-3.13, P = 0.049) in the durvalumab treatment arm, and 2.82 (95% CI 1.21-6.54, P = 0.016) in the placebo treatment arm, respectively. We also found that both continuous TMB and immune GEP (or tumor infiltrating lymphocytes) independently predicted pCR. When we stratified patients in groups based on the upper tertile of TMB and median GEP, we observed a pCR rate of 82% (95% CI 60% to 95%) in the group with both high TMB and GEP in contrast to only 28% (95% CI 16% to 43%) in the group with both low TMB and GEP.CONCLUSIONS: TMB and immune GEP add independent value for pCR prediction. Our results recommend further analysis of TMB in combination with immune parameters to individually tailor therapies in breast cancer.

AB - BACKGROUND: The predictive value of tumor mutational burden (TMB), alone or in combination with an immune gene expression profile (GEP), for response to neoadjuvant therapy in early triple negative breast cancer (TNBC) is currently not known, either for immune checkpoint blockade (ICB) or conventional chemotherapy.PATIENTS AND METHODS: We obtained both whole exome sequencing and RNA-Seq data from pretreatment samples of 149 TNBC of the recent neoadjuvant ICB trial, GeparNuevo. In a predefined analysis, we assessed the predictive value of TMB and a previously developed immune GEP for pathological complete remission (pCR).RESULTS: Median TMB was 1.52 mut/Mb (range 0.02-7.65) and was significantly higher in patients with pCR (median 1.87 versus 1.39; P = 0.005). In multivariate analysis, odds ratios for pCR per mut/Mb were 2.06 [95% confidence intervals (CI) 1.33-3.20, P = 0.001] among all patients, 1.77 (95% CI 1.00-3.13, P = 0.049) in the durvalumab treatment arm, and 2.82 (95% CI 1.21-6.54, P = 0.016) in the placebo treatment arm, respectively. We also found that both continuous TMB and immune GEP (or tumor infiltrating lymphocytes) independently predicted pCR. When we stratified patients in groups based on the upper tertile of TMB and median GEP, we observed a pCR rate of 82% (95% CI 60% to 95%) in the group with both high TMB and GEP in contrast to only 28% (95% CI 16% to 43%) in the group with both low TMB and GEP.CONCLUSIONS: TMB and immune GEP add independent value for pCR prediction. Our results recommend further analysis of TMB in combination with immune parameters to individually tailor therapies in breast cancer.

KW - Biomarkers, Tumor

KW - Humans

KW - Immune Checkpoint Inhibitors

KW - Mutation

KW - Neoadjuvant Therapy

KW - Triple Negative Breast Neoplasms/drug therapy

U2 - 10.1016/j.annonc.2020.05.015

DO - 10.1016/j.annonc.2020.05.015

M3 - SCORING: Journal article

C2 - 32461104

VL - 31

SP - 1216

EP - 1222

JO - ANN ONCOL

JF - ANN ONCOL

SN - 0923-7534

IS - 9

ER -