Predictive correlates of response to the anti-PD-L1 antibody MPDL3280A in cancer patients (original) (raw)

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Acknowledgements

We thank the patients and their families. We also thank all of the investigators and their staff, including A. Balmanoukian and P. Boasberg from The Angeles Clinic and Research Institute; T. Powles from Barts Cancer Institute, QMUL, Barts Health NHS Trust; D. Cho from NYU Langone Medical Center; P. Cassier from Centre Léon-Bérard; F. Braiteh from USON Research Network, Comprehensive Cancer Centers of Nevada; N. Vogelzang from USON Research Network, Comprehensive Cancer Centers of Nevada and University of Nevada; T. Choueiri, L. Gandhi, N. Ibrahim and P. Ott from Dana-Farber Cancer Institute; J.-P. Delord and C. Gomez-Rocca from Institut Claudius Regaud; A. Hollebecque and R. Bahleda from Gustave Roussy; L. Emens from Johns Hopkins Medicine, The Sidney Kimmel Comprehensive Cancer Center; K. Flaherty and R. Sullivan from Massachusetts General Hospital; S. Antonia from Moffitt Cancer Center; H. Burris, J. Infante and D. Spigel from Sarah Cannon Research Institute; G. Fisher from Stanford Medicine, Cancer Institute; P. Conkling and L. Garbo from US Oncology Research, Inc.; C. Cruz and J. Tabenero from Vall d’Hebron Institute of Oncology and Vall d’Hebron University Hospital; W. Pao and I. Puzanov from Vanderbilt-Ingram Cancer Center; P. Eder, H. Kluger and M. Sznol from Yale Cancer Center. From Genentech, we thank M. Anderson, M. Boe, Z. Boyd, C. Chappey, M. Denker, R. Desai, L. Fu, B. Irving, D. Jin, W. Kadel, R. Nakamura, I. Rhee, X. Shen, M. Stroh, T. Sumiyoshi, J. Wu, Y. Xin and J. Yi. Support for third-party writing assistance for this manuscript was provided by F. Hoffmann-La Roche Ltd. NCI grants 1R01CA155196 (Battle-2) and P30 CA 016359 (CCSG) to R.S.H. helped support the infrastructure for this trial and program.

Author information

Authors and Affiliations

  1. Yale Comprehensive Cancer Center, Yale School of Medicine, 333 Cedar Street, WWW221, New Haven, Connecticut 06520, USA,
    Roy S. Herbst & Scott N. Gettinger
  2. Gustave Roussy South-Paris University, 114 Rue Edouard Vaillant, 94805 Villefuij, Cedex, France,
    Jean-Charles Soria
  3. Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, USA,
    Marcin Kowanetz, Gregg D. Fine, Sandra Rost, Maya Leabman, Yuanyuan Xiao, Ahmad Mokatrin, Hartmut Koeppen, Priti S. Hegde, Ira Mellman & Daniel S. Chen
  4. The Angeles Clinic and Research Institute, 11818 Wilshire Blvd, Los Angeles, 90025, California, USA
    Omid Hamid
  5. Pinnacle Oncology Hematology, 9055 E Del Camino Dr 100, Scottsdale, 85258, Arizona, USA
    Michael S. Gordon
  6. Vanderbilt-Ingram Cancer Center, 2220 Pierce Avenue, Nashville, 37212, Tennessee, USA
    Jeffery A. Sosman
  7. Beth Israel Deaconess Medical Center, 330 Brookline Avenue, Shapiro 9, Boston, Massachusetts 02215, USA,
    David F. McDermott
  8. Carolina BioOncology Institute, 9801 W. Kincey Ave, Suite 145, Huntersville, North Carolina 28078, USA,
    John D. Powderly
  9. Stanford University, CCSR Bldg Room 1110, Stanford, 94305, California, USA
    Holbrook E. K. Kohrt
  10. Vanderbilt-Ingram Cancer Center, 1301 Medical Center Dr, Suite 1710, Nashville, Tennessee 37212, USA,
    Leora Horn
  11. Massachusetts General Hospital, 55 Fruit Street, YAW 9E, Boston, Massachusetts 02114, USA,
    Donald P. Lawrence
  12. Dana-Farber/Brigham and Women’s Cancer Center, 450 Brookline Avenue, Boston, 02215, Massachusetts, USA
    F. Stephen Hodi

Authors

  1. Roy S. Herbst
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  2. Jean-Charles Soria
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  3. Marcin Kowanetz
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  4. Gregg D. Fine
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  5. Omid Hamid
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  6. Michael S. Gordon
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  7. Jeffery A. Sosman
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  8. David F. McDermott
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  9. John D. Powderly
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  10. Scott N. Gettinger
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  11. Holbrook E. K. Kohrt
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  12. Leora Horn
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  13. Donald P. Lawrence
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  14. Sandra Rost
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  15. Maya Leabman
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  16. Yuanyuan Xiao
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  17. Ahmad Mokatrin
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  18. Hartmut Koeppen
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  19. Priti S. Hegde
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  20. Ira Mellman
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  21. Daniel S. Chen
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  22. F. Stephen Hodi
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Contributions

R.S.H., J.-C.S., D.S.C., F.S.H. and J.A.S. contributed to the overall study design. M.K., S.R., Y.X., H.K. and P.S.H. provided the biomarker studies. M.L. performed the pharmacokinetic analysis. I.M. provided the pre-clinical analysis. A.M. performed the statistical analysis. All authors analysed the data. All authors contributed to writing the paper.

Corresponding author

Correspondence toRoy S. Herbst.

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Competing interests

R.S.H. is a consultant for and receives research funding from Genentech, Inc. O.H. is a speaker and consultant for, and receives research funding from, Genentech, Inc. F.S.H. works as a non-paid advisor to Genentech, Inc., Bristol-Myers Squibb and Merck; is a member of the Amgen advisory board; is a compensated advisor to Novartis; and received clinical trials support from Genentech, Inc., Bristol-Myers Squibb, Merck and Novartis. L.H. received research funding from Astellas; is a member of advisory boards for Bristol-Myers Squibb, Clovis and Helix BioPharma; provides uncompensated advice for PUMA and Xcovery; is an uncompensated member of Bayer’s steering committee; and received an honoraria from Boehringer Ingelheim. D.F.M. is a participant on advisory boards for Genentech, Inc. Bristol-Myers Squibb and Merck. J.D.P. is the Founder and CEO of Biologics Human Application Lab; worked as a consultant and/or advisor to Bristol-Myers Squibb, Genentech, Inc., Amplimmune and Merck; received honoraria from Bristol-Myers Squibb; received research funding from Bristol-Myers Squibb, Genentech, Inc., Amplimmune, Merck, AstraZeneca and ImClone Systems; and has participated in Bristol-Myers Squibb Speaker’s Bureau and advisory boards. J.-C.S. is a compensated advisory board participant for Genentech, Inc. M.K., G.D.F., S.R., M.L., Y.X., A.M., H.K., P.S.H., I.M. and D.S.C. are employees of Genentech, Inc. M.S.G., J.A.S., S.N.G., H.E.K.K. and D.P.L. have nothing to declare.

Extended data figures and tables

Extended Data Figure 1 Study design and pharmacokinetics.

a, Summary of PCD4989g design, including screening, treatment period and follow-up. b, Summary of the dose-escalation (patient numbers are given in the lower right corners) and dose-expansion cohorts. c, Pharmacokinetics for MPDL3280A. Error bars indicate standard deviation. C, cycle; CR, complete response; CT, computed tomography; DLT, dose-limiting toxicity; IV, intravenous; NSCLC, non-small cell lung cancer; PD, progressive disease; PR, partial response; RCC, renal cell carcinoma; RECIST, Response Evaluation Criteria in Solid Tumours; SD, stable disease.

Extended Data Figure 2 Pyrexia and biomarkers over time.

a, The graph on the left shows patients who developed pyrexia during the first cycle of MPDL3280A treatment by day. The graph on the right shows patients who developed pyrexia during all cycles of treatment with MPDL3280A. The percentage of patients with pyrexia and the number of patients available for analysis at each time point is indicated below the graph. b, Changes in CD8+HLA-DR+Ki-67+ cells over the first 5 cycles of treatment with MPDL3280A. The y axis represents the log2 fold-change versus C1D1 pre-dose level. Error bars are standard error of the mean. Samples from 164 patients were examined at cycle (C) 1 day (D) 1 (C1D1) and 145 patients at C2D1. The P value for the difference in fold change between C2D1 versus C1D1 was <0.00001. c, Changes in IFN-γ, ITAC, IL-18 and IL-6 levels shown over the first seven 21-day cycles of treatment with MPDL3280A. To measure fold changes in IFN-γ and IL-6 levels, 112 and 109 patient samples were examined for C1D1 and C2D1, respectively. To measure fold changes in IL-18, 260 and 253 patient samples were examined for C1D1 and C2D1, respectively; to measure ITAC, 262 and 256 patient samples were examined for C1D1 and C2D1, respectively. The adjusted P values comparing C2D1 versus C1D1 were 0.94 for IFN-γ, 1 for IL-6, <0.00001 for IL-18 and <0.00001 for ITAC. Error bars are standard error of the mean.

Extended Data Figure 3 Antitumour activity of MPDL3280A in patients with all tumour types.

a, Time to response and the duration of study treatment by tumour type and IHC (tumour-infiltrating immune cell) status. b, Representative images (10× magnification) of PD-L1 and CD8 immunohistochemistry (IHC) staining from a pre-treatment tumour biopsy sample from a patient with NSCLC. The patient’s best response to MPDL3280A was a partial response. CRC, colorectal cancer; IC, tumour-infiltrating immune cells; ND, not determined; NSCLC, non-small cell lung cancer; PD, progressive disease; RCC, renal cell carcinoma; TC, tumour cells.

Extended Data Figure 4 Antitumour activity of MPDL3280A by PD-L1 immunohistochemistry (IHC) status.

a, The overall objective response rate (ORR; best response of complete response (CR) and partial response (PR)), stable disease (SD) as the best response rate and progressive disease (PD) as the best response rate for patients with non-small cell lung cancer (NSCLC) who received MPDL3280A by PD-L1 IHC (tumour-infiltrating immune cell (IC)) status. Overall, 53 patients with NSCLC were evaluated: 6 patients had an IHC (IC) score of 3; 7 patients had a score of 2; 13 patients had a score of 1; and 20 patients had a score of 0. Seven patients had an unknown IHC status (data not shown). Patients with no post-first dose assessment were not estimable and not plotted (1 in IHC 1 and 1 in IHC 2), but were included in the denominator for purposes of calculating ORR. Using a logistic regression model, PD-L1 by IHC (IC) was significantly associated with response to MPDL3280A (P = 0.015). b, The ORR, SD as best response rate, and PD as best response rate for patients with all tumour types who received MPDL3280A by PD-L1 IHC (IC) status. Patients with no post-first dose assessment were not estimable (NE) and not plotted (1 in IHC 0, 2 in IHC 1, 1 in IHC 2 and 1 in IHC 3), but were included in the denominator for purposes of calculating ORR. Using a logistic regression model, PD-L1 by IHC (IC) was significantly associated with response to MPDL3280A (P = 0.007). c, The ORR, SD as best response rate, and PD as best response rate for patients with NSCLC who received MPDL3280A by PD-L1 IHC (TC) status. Overall, 53 patients with NSCLC were evaluated: 8 patients had an IHC score of 3; 1 patient had a score of 2; 3 patients had a score of 1; and 34 patients had a score of 0. Seven patients had an unknown IHC status (data not shown). Patients with no post-first dose assessment were not estimable and not plotted (2 in IHC 0), but were included in the denominator for purposes of calculating ORR. All responses were confirmed except for in 1 patient. Using a logistic regression model, PD-L1 by IHC (TC) did not meet statistical significance for association with response (P = 0.920). d, The ORR and SD and PD best response rates for patients with all tumour types who received MPDL3280A by PD-L1 IHC (TC) status. Overall, 175 patients with all tumour types were evaluated: 15 patients had an IHC score of 3; 3 patients had a score of 2; 11 patients had a score of 1; and 121 patients had a score of 0; 25 patients had an unknown IHC status (data not shown). Patients with no post-first dose assessment were not estimable and not plotted (3 in IHC 0, 1 in IHC 1 and 1 in IHC 3), but were included in the denominator for purposes of calculating ORR. All responses were confirmed except for in 1 patient with NSCLC, 1 patient with RCC and 2 patients with melanoma. Using a logistic regression model, PD-L1 by IHC (TC) did not meet statistical significance for the association with response (P = 0.079).

Extended Data Figure 5 Biomarkers and antitumour activity of MPDL3280A.

a, Objective response rates (ORRs) were plotted by the biomarker status of tumour samples from patients who had tumour available for both immunohistochemistry (IHC) staining and immunochip (n = 37). Left: ORRs for patient sub-populations defined by positivity in a single biomarker as indicated. Right: ORRs for patients positive for PD-L1 and one other marker as indicated. PD-L1 positivity was defined as ≥5% of tumour-infiltrating immune cells (ICs) staining for PD-L1 by IHC. For PD-L2, IDO1, LAG3, TIM3, CTLA4, B7-H3 and B7-H4 positivity was determined by gene expression ≥ the median. b, Baseline CX3CL1 and CTLA4 gene expression levels are binned according to patient response to treatment with MPDL3280A. Includes patients with all tumour types. P values were determined by _t_-test. c, Changes in PD-L1 (IHC) versus interferon (IFN)-γ (qPCR) expression after treatment with MPDL3280A in patients with paired serial biopsies. Pearson correlation coefficient = 0.70. CR, complete response; PD, progressive disease; PR, partial response; RECIST, Response Evaluation Criteria in Solid Tumours.

Extended Data Figure 6 Gene expression levels according to patient response and tumour type.

Baseline _IFN_γ, IDO1 and CXCL9 gene expression levels are binned according to patient response to treatment with MPDL3280A. Patients are grouped according to tumour type. P values were determined by _t_-test. CR, complete response; NSCLC, non-small cell lung cancer; PD, progressive disease; PR, partial response; RCC, renal cell carcinoma.

Extended Data Figure 7 Biomarker analyses for a responding patient receiving MPDL3280A.

A patient with PD-L1-positive (IHC (IC) 3) renal cell carcinoma who responded to treatment with MPDL3280A. a, Representative computed tomography scans taken at pre-treatment and at post-cycle. Red arrows indicate the location of tumours or where tumours used to be. b, Top panel: representative image of CD8 IHC staining from a pre-treatment tumour biopsy (40× magnification). Bottom panel: representative image of CD8 IHC staining from a tumour biopsy of a shrinking lesion during week 4 of treatment with MPDL3280A that demonstrates an increase in CD8+ T-cell infiltration (20× magnification). c, Gene-expression analysis of T-cell markers pre-treatment (set to 1) and on treatment at week 4. Data were normalized to the baseline. Twofold was the cutoff for a gene to be considered induced (indicated by the dashed line).

Extended Data Figure 8 Biomarker analyses of patients with immunological ignorance and a non-functional immune response.

a, A patient with PD-L1-negative (IHC (IC) 0) breast cancer whose best response to MPDL3280A was progressive disease with immunological ignorance. Top: representative image of PD-L1 IHC staining from a pre-treatment tumour biopsy. Bottom: representative image of PD-L1 IHC staining from a tumour biopsy during week 9 of treatment with MPDL3280A. Both images are at 10× magnification. b, A patient with PD-L1 IHC 1 melanoma whose best response to MPDL3280A was progressive disease with a non-functional immune response. Gene-expression analysis of T-cell markers at pre-treatment (set to 1) and on treatment at week 6. Data were normalized to baseline. Twofold was the cutoff for a gene to be considered induced (indicated by the dashed line).

Extended Data Figure 9 Biomarker analyses of a patient with an excluded infiltrate.

A patient with PD-L1-negative (IHC (IC) 1) melanoma whose best response to MPDL3280A was progressive disease with an ‘excluded infiltrate’. Gene expression analysis of T-cell markers at pre-treatment (set to 1) and on treatment at week 6. Data were normalized to baseline. Twofold was the cutoff for a gene to be considered induced (indicated by the dashed line).

Extended Data Figure 10 Characterization of MPDL3280A.

a, Affinity measurements conducted by surface plasmon resonance and binding to PD-L1-expressing human cells using MPDL3280A and trastuzumab. Data from a representative experiment (1 of 4) is shown here. b, In vitro assays for antibody-dependent cellular cytotoxicity. The wild-type antibody is unmodified and the Fc modified MPDL3280A antibody has an engineered Fc domain. GPE, glycophorin E; MFI, mean of fluorescence intensity.

Extended Data Table 1 Patient demographics and disease characteristics (safety population)

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Herbst, R., Soria, JC., Kowanetz, M. et al. Predictive correlates of response to the anti-PD-L1 antibody MPDL3280A in cancer patients.Nature 515, 563–567 (2014). https://doi.org/10.1038/nature14011

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