DNA methylation profiling to predict recurrence risk in meningioma: development and validation of a nomogram to optimize clinical management

F Nassiri; Y Mamatjan; S Suppiah; Jetan H. Badhiwala; Sheila Mansouri; Shirin Karimi; Olli Saarela; L Poisson; Irina Gepfner-Tuma; Jens Schittenhelm; Ho Keung Ng; H Noushmehr; Patrick Harter; Peter Baumgarten; Michael Weller; Matthias Preusser; C Herold-Mende; M Tatagiba; G Tabatabai; F Sahm; Deimling A von; Kenneth D. Aldape; Karolyn Au; Jill Barnhartz-Sloan; Wenya Linda Bi; Priscilla K. Brastianos; Nicholas Butowski; Carlos Carlotti; Michael D. Cusimano; Francesco Dimeco; Katharine Drummond; Ian F. Dunn; Evanthia Galanis; Caterina Giannini; Roland Goldbrunner; Brent Griffith; Rintaro Hashizume; C. Oliver Hanemann; C Herold-Mende; Craig Horbinski; Raymond Y. Huang; David James; Michael D. Jenkinson; Christine Jungk; Timothy J. Kaufman; Boris Krischek; Daniel Lachance; Christian Lafougère; Ian Lee; Jeff C. Liu; Y Mamatjan; Tathiane M. Malta; Christian Mawrin; Michael McDermott; David Munoz; F Nassiri; H Noushmehr; Ho Keung Ng; Arie Perry; Farhad Pirouzmand; LM Poisson; Bianca Pollo; David Raleigh; F Sahm; Andrea Saladino; Thomas Santarius; Christian Schichor; David Schultz; Nils O. Schmidt; Warren Selman; Andrew Sloan; Julian Spears; James Snyder; S Suppiah; G Tabatabai; M Tatagiba; Daniela Tirapelli; Joerg C. Tonn; Derek Tsang; Michael A. Vogelbaum; Deimling A von; Patrick Y. Wen; Tobias Walbert; Manfred Westphal; Adriana M. Workewych; Gelareh Zadeh; Gelareh Zadeh

doi:10.1093/neuonc/noz061

DNA methylation profiling to predict recurrence risk in meningioma: development and validation of a nomogram to optimize clinical management

F Nassiri, Y Mamatjan, S Suppiah, Jetan H. Badhiwala, Sheila Mansouri, Shirin Karimi, Olli Saarela, L Poisson, Irina Gepfner-Tuma, Jens Schittenhelm, Ho Keung Ng, H Noushmehr, Patrick Harter, Peter Baumgarten, Michael Weller, Matthias Preusser, C Herold-Mende, M Tatagiba, G Tabatabai, F SahmDeimling A von, Kenneth D. Aldape^*, Karolyn Au, Jill Barnhartz-Sloan, Wenya Linda Bi, Priscilla K. Brastianos, Nicholas Butowski, Carlos Carlotti, Michael D. Cusimano, Francesco Dimeco, Katharine Drummond, Ian F. Dunn, Evanthia Galanis, Caterina Giannini, Roland Goldbrunner, Brent Griffith, Rintaro Hashizume, C. Oliver Hanemann, C Herold-Mende, Craig Horbinski, Raymond Y. Huang, David James, Michael D. Jenkinson, Christine Jungk, Timothy J. Kaufman, Boris Krischek, Daniel Lachance, Christian Lafougère, Ian Lee, Jeff C. Liu, Y Mamatjan, Tathiane M. Malta, Christian Mawrin, Michael McDermott, David Munoz, F Nassiri, H Noushmehr, Ho Keung Ng, Arie Perry, Farhad Pirouzmand, LM Poisson, Bianca Pollo, David Raleigh, F Sahm, Andrea Saladino, Thomas Santarius, Christian Schichor, David Schultz, Nils O. Schmidt, Warren Selman, Andrew Sloan, Julian Spears, James Snyder, S Suppiah, G Tabatabai, M Tatagiba, Daniela Tirapelli, Joerg C. Tonn, Derek Tsang, Michael A. Vogelbaum, Deimling A von, Patrick Y. Wen, Tobias Walbert, Manfred Westphal, Adriana M. Workewych, Gelareh Zadeh, Gelareh Zadeh

^*Corresponding author for this work

Peninsula Medical School

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Abstract

Abstract Background Variability in standard-of-care classifications precludes accurate predictions of early tumor recurrence for individual patients with meningioma, limiting the appropriate selection of patients who would benefit from adjuvant radiotherapy to delay recurrence. We aimed to develop an individualized prediction model of early recurrence risk combining clinical and molecular factors in meningioma. Methods DNA methylation profiles of clinically annotated tumor samples across multiple institutions were used to develop a methylome model of 5-year recurrence-free survival (RFS). Subsequently, a 5-year meningioma recurrence score was generated using a nomogram that integrated the methylome model with established prognostic clinical factors. Performance of both models was evaluated and compared with standard-of-care models using multiple independent cohorts. Results The methylome-based predictor of 5-year RFS performed favorably compared with a grade-based predictor when tested using the 3 validation cohorts (ΔAUC = 0.10, 95% CI: 0.03–0.018) and was independently associated with RFS after adjusting for histopathologic grade, extent of resection, and burden of copy number alterations (hazard ratio 3.6, 95% CI: 1.8–7.2, P < 0.001). A nomogram combining the methylome predictor with clinical factors demonstrated greater discrimination than a nomogram using clinical factors alone in 2 independent validation cohorts (ΔAUC = 0.25, 95% CI: 0.22–0.27) and resulted in 2 groups with distinct recurrence patterns (hazard ratio 7.7, 95% CI: 5.3–11.1, P < 0.001) with clinical implications. Conclusions The models developed and validated in this study provide important prognostic information not captured by previously established clinical and molecular factors which could be used to individualize decisions regarding postoperative therapeutic interventions, in particular whether to treat patients with adjuvant radiotherapy versus observation alone.

Original language	English
Pages (from-to)	901-910
Number of pages	0
Journal	Neuro-Oncology
Volume	21
Issue number	7
Early online date	3 Jun 2019
DOIs	https://doi.org/10.1093/neuonc/noz061
Publication status	Published - Jul 2019

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Nassiri, F., Mamatjan, Y., Suppiah, S., Badhiwala, J. H., Mansouri, S., Karimi, S., Saarela, O., Poisson, L., Gepfner-Tuma, I., Schittenhelm, J., Ng, H. K., Noushmehr, H., Harter, P., Baumgarten, P., Weller, M., Preusser, M., Herold-Mende, C., Tatagiba, M., Tabatabai, G., ... Zadeh, G. (2019). DNA methylation profiling to predict recurrence risk in meningioma: development and validation of a nomogram to optimize clinical management. Neuro-Oncology, 21(7), 901-910. https://doi.org/10.1093/neuonc/noz061

@article{fcedb956c7d843b2b93eb6ddbf84a0e9,

title = "DNA methylation profiling to predict recurrence risk in meningioma: development and validation of a nomogram to optimize clinical management",

abstract = "Abstract Background Variability in standard-of-care classifications precludes accurate predictions of early tumor recurrence for individual patients with meningioma, limiting the appropriate selection of patients who would benefit from adjuvant radiotherapy to delay recurrence. We aimed to develop an individualized prediction model of early recurrence risk combining clinical and molecular factors in meningioma. Methods DNA methylation profiles of clinically annotated tumor samples across multiple institutions were used to develop a methylome model of 5-year recurrence-free survival (RFS). Subsequently, a 5-year meningioma recurrence score was generated using a nomogram that integrated the methylome model with established prognostic clinical factors. Performance of both models was evaluated and compared with standard-of-care models using multiple independent cohorts. Results The methylome-based predictor of 5-year RFS performed favorably compared with a grade-based predictor when tested using the 3 validation cohorts (ΔAUC = 0.10, 95% CI: 0.03–0.018) and was independently associated with RFS after adjusting for histopathologic grade, extent of resection, and burden of copy number alterations (hazard ratio 3.6, 95% CI: 1.8–7.2, P < 0.001). A nomogram combining the methylome predictor with clinical factors demonstrated greater discrimination than a nomogram using clinical factors alone in 2 independent validation cohorts (ΔAUC = 0.25, 95% CI: 0.22–0.27) and resulted in 2 groups with distinct recurrence patterns (hazard ratio 7.7, 95% CI: 5.3–11.1, P < 0.001) with clinical implications. Conclusions The models developed and validated in this study provide important prognostic information not captured by previously established clinical and molecular factors which could be used to individualize decisions regarding postoperative therapeutic interventions, in particular whether to treat patients with adjuvant radiotherapy versus observation alone. ",

author = "F Nassiri and Y Mamatjan and S Suppiah and Badhiwala, {Jetan H.} and Sheila Mansouri and Shirin Karimi and Olli Saarela and L Poisson and Irina Gepfner-Tuma and Jens Schittenhelm and Ng, {Ho Keung} and H Noushmehr and Patrick Harter and Peter Baumgarten and Michael Weller and Matthias Preusser and C Herold-Mende and M Tatagiba and G Tabatabai and F Sahm and von, {Deimling A} and Aldape, {Kenneth D.} and Karolyn Au and Jill Barnhartz-Sloan and Bi, {Wenya Linda} and Brastianos, {Priscilla K.} and Nicholas Butowski and Carlos Carlotti and Cusimano, {Michael D.} and Francesco Dimeco and Katharine Drummond and Dunn, {Ian F.} and Evanthia Galanis and Caterina Giannini and Roland Goldbrunner and Brent Griffith and Rintaro Hashizume and Hanemann, {C. Oliver} and C Herold-Mende and Craig Horbinski and Huang, {Raymond Y.} and David James and Jenkinson, {Michael D.} and Christine Jungk and Kaufman, {Timothy J.} and Boris Krischek and Daniel Lachance and Christian Lafoug{\`e}re and Ian Lee and Liu, {Jeff C.} and Y Mamatjan and Malta, {Tathiane M.} and Christian Mawrin and Michael McDermott and David Munoz and F Nassiri and H Noushmehr and Ng, {Ho Keung} and Arie Perry and Farhad Pirouzmand and LM Poisson and Bianca Pollo and David Raleigh and F Sahm and Andrea Saladino and Thomas Santarius and Christian Schichor and David Schultz and Schmidt, {Nils O.} and Warren Selman and Andrew Sloan and Julian Spears and James Snyder and S Suppiah and G Tabatabai and M Tatagiba and Daniela Tirapelli and Tonn, {Joerg C.} and Derek Tsang and Vogelbaum, {Michael A.} and von, {Deimling A} and Wen, {Patrick Y.} and Tobias Walbert and Manfred Westphal and Workewych, {Adriana M.} and Gelareh Zadeh and Gelareh Zadeh",

year = "2019",

month = jul,

doi = "10.1093/neuonc/noz061",

language = "English",

volume = "21",

pages = "901--910",

journal = "Neuro-Oncology",

issn = "1522-8517",

publisher = "Oxford University Press",

number = "7",

}

Nassiri, F, Mamatjan, Y, Suppiah, S, Badhiwala, JH, Mansouri, S, Karimi, S, Saarela, O, Poisson, L, Gepfner-Tuma, I, Schittenhelm, J, Ng, HK, Noushmehr, H, Harter, P, Baumgarten, P, Weller, M, Preusser, M, Herold-Mende, C, Tatagiba, M, Tabatabai, G, Sahm, F, von, DA, Aldape, KD, Au, K, Barnhartz-Sloan, J, Bi, WL, Brastianos, PK, Butowski, N, Carlotti, C, Cusimano, MD, Dimeco, F, Drummond, K, Dunn, IF, Galanis, E, Giannini, C, Goldbrunner, R, Griffith, B, Hashizume, R, Hanemann, CO, Herold-Mende, C, Horbinski, C, Huang, RY, James, D, Jenkinson, MD, Jungk, C, Kaufman, TJ, Krischek, B, Lachance, D, Lafougère, C, Lee, I, Liu, JC, Mamatjan, Y, Malta, TM, Mawrin, C, McDermott, M, Munoz, D, Nassiri, F, Noushmehr, H, Ng, HK, Perry, A, Pirouzmand, F, Poisson, LM, Pollo, B, Raleigh, D, Sahm, F, Saladino, A, Santarius, T, Schichor, C, Schultz, D, Schmidt, NO, Selman, W, Sloan, A, Spears, J, Snyder, J, Suppiah, S, Tabatabai, G, Tatagiba, M, Tirapelli, D, Tonn, JC, Tsang, D, Vogelbaum, MA, von, DA, Wen, PY, Walbert, T, Westphal, M, Workewych, AM, Zadeh, G & Zadeh, G 2019, 'DNA methylation profiling to predict recurrence risk in meningioma: development and validation of a nomogram to optimize clinical management', Neuro-Oncology, vol. 21, no. 7, pp. 901-910. https://doi.org/10.1093/neuonc/noz061

TY - JOUR

T1 - DNA methylation profiling to predict recurrence risk in meningioma: development and validation of a nomogram to optimize clinical management

AU - Nassiri, F

AU - Mamatjan, Y

AU - Suppiah, S

AU - Badhiwala, Jetan H.

AU - Mansouri, Sheila

AU - Karimi, Shirin

AU - Saarela, Olli

AU - Poisson, L

AU - Gepfner-Tuma, Irina

AU - Schittenhelm, Jens

AU - Ng, Ho Keung

AU - Noushmehr, H

AU - Harter, Patrick

AU - Baumgarten, Peter

AU - Weller, Michael

AU - Preusser, Matthias

AU - Herold-Mende, C

AU - Tatagiba, M

AU - Tabatabai, G

AU - Sahm, F

AU - von, Deimling A

AU - Aldape, Kenneth D.

AU - Au, Karolyn

AU - Barnhartz-Sloan, Jill

AU - Bi, Wenya Linda

AU - Brastianos, Priscilla K.

AU - Butowski, Nicholas

AU - Carlotti, Carlos

AU - Cusimano, Michael D.

AU - Dimeco, Francesco

AU - Drummond, Katharine

AU - Dunn, Ian F.

AU - Galanis, Evanthia

AU - Giannini, Caterina

AU - Goldbrunner, Roland

AU - Griffith, Brent

AU - Hashizume, Rintaro

AU - Hanemann, C. Oliver

AU - Herold-Mende, C

AU - Horbinski, Craig

AU - Huang, Raymond Y.

AU - James, David

AU - Jenkinson, Michael D.

AU - Jungk, Christine

AU - Kaufman, Timothy J.

AU - Krischek, Boris

AU - Lachance, Daniel

AU - Lafougère, Christian

AU - Lee, Ian

AU - Liu, Jeff C.

AU - Mamatjan, Y

AU - Malta, Tathiane M.

AU - Mawrin, Christian

AU - McDermott, Michael

AU - Munoz, David

AU - Nassiri, F

AU - Noushmehr, H

AU - Ng, Ho Keung

AU - Perry, Arie

AU - Pirouzmand, Farhad

AU - Poisson, LM

AU - Pollo, Bianca

AU - Raleigh, David

AU - Sahm, F

AU - Saladino, Andrea

AU - Santarius, Thomas

AU - Schichor, Christian

AU - Schultz, David

AU - Schmidt, Nils O.

AU - Selman, Warren

AU - Sloan, Andrew

AU - Spears, Julian

AU - Snyder, James

AU - Suppiah, S

AU - Tabatabai, G

AU - Tatagiba, M

AU - Tirapelli, Daniela

AU - Tonn, Joerg C.

AU - Tsang, Derek

AU - Vogelbaum, Michael A.

AU - von, Deimling A

AU - Wen, Patrick Y.

AU - Walbert, Tobias

AU - Westphal, Manfred

AU - Workewych, Adriana M.

AU - Zadeh, Gelareh

PY - 2019/7

Y1 - 2019/7

N2 - Abstract Background Variability in standard-of-care classifications precludes accurate predictions of early tumor recurrence for individual patients with meningioma, limiting the appropriate selection of patients who would benefit from adjuvant radiotherapy to delay recurrence. We aimed to develop an individualized prediction model of early recurrence risk combining clinical and molecular factors in meningioma. Methods DNA methylation profiles of clinically annotated tumor samples across multiple institutions were used to develop a methylome model of 5-year recurrence-free survival (RFS). Subsequently, a 5-year meningioma recurrence score was generated using a nomogram that integrated the methylome model with established prognostic clinical factors. Performance of both models was evaluated and compared with standard-of-care models using multiple independent cohorts. Results The methylome-based predictor of 5-year RFS performed favorably compared with a grade-based predictor when tested using the 3 validation cohorts (ΔAUC = 0.10, 95% CI: 0.03–0.018) and was independently associated with RFS after adjusting for histopathologic grade, extent of resection, and burden of copy number alterations (hazard ratio 3.6, 95% CI: 1.8–7.2, P < 0.001). A nomogram combining the methylome predictor with clinical factors demonstrated greater discrimination than a nomogram using clinical factors alone in 2 independent validation cohorts (ΔAUC = 0.25, 95% CI: 0.22–0.27) and resulted in 2 groups with distinct recurrence patterns (hazard ratio 7.7, 95% CI: 5.3–11.1, P < 0.001) with clinical implications. Conclusions The models developed and validated in this study provide important prognostic information not captured by previously established clinical and molecular factors which could be used to individualize decisions regarding postoperative therapeutic interventions, in particular whether to treat patients with adjuvant radiotherapy versus observation alone.

AB - Abstract Background Variability in standard-of-care classifications precludes accurate predictions of early tumor recurrence for individual patients with meningioma, limiting the appropriate selection of patients who would benefit from adjuvant radiotherapy to delay recurrence. We aimed to develop an individualized prediction model of early recurrence risk combining clinical and molecular factors in meningioma. Methods DNA methylation profiles of clinically annotated tumor samples across multiple institutions were used to develop a methylome model of 5-year recurrence-free survival (RFS). Subsequently, a 5-year meningioma recurrence score was generated using a nomogram that integrated the methylome model with established prognostic clinical factors. Performance of both models was evaluated and compared with standard-of-care models using multiple independent cohorts. Results The methylome-based predictor of 5-year RFS performed favorably compared with a grade-based predictor when tested using the 3 validation cohorts (ΔAUC = 0.10, 95% CI: 0.03–0.018) and was independently associated with RFS after adjusting for histopathologic grade, extent of resection, and burden of copy number alterations (hazard ratio 3.6, 95% CI: 1.8–7.2, P < 0.001). A nomogram combining the methylome predictor with clinical factors demonstrated greater discrimination than a nomogram using clinical factors alone in 2 independent validation cohorts (ΔAUC = 0.25, 95% CI: 0.22–0.27) and resulted in 2 groups with distinct recurrence patterns (hazard ratio 7.7, 95% CI: 5.3–11.1, P < 0.001) with clinical implications. Conclusions The models developed and validated in this study provide important prognostic information not captured by previously established clinical and molecular factors which could be used to individualize decisions regarding postoperative therapeutic interventions, in particular whether to treat patients with adjuvant radiotherapy versus observation alone.

U2 - 10.1093/neuonc/noz061

DO - 10.1093/neuonc/noz061

M3 - Article

SN - 1522-8517

VL - 21

SP - 901

EP - 910

JO - Neuro-Oncology

JF - Neuro-Oncology

IS - 7

ER -

DNA methylation profiling to predict recurrence risk in meningioma: development and validation of a nomogram to optimize clinical management

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