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Patient centered treatment options in lung cancer J. Vansteenkiste

Patient centered treatment options in lung cancer J. Vansteenkiste. Respiratory Oncology Unit Dept. Pulmonology Univ . Hospital Leuven Leuven Lung Cancer Group. The principle of (therapeutic) biomarkers Why could biomarkers improve treatment ? Challenges with biomarkers

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Patient centered treatment options in lung cancer J. Vansteenkiste

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  1. Patientcentered treatment options in lung cancer J. Vansteenkiste Respiratory Oncology Unit Dept. Pulmonology Univ. Hospital Leuven Leuven Lung Cancer Group

  2. The principle of (therapeutic) biomarkers Why could biomarkers improve treatment ? Challenges with biomarkers Biomarkers in adv. NSCLC 1st line therapy Biomarkers in relapsed NSCLC therapy Summary: current impact of biomarkers ?

  3. NSCLC individualised treatment • prognostic markers • who is at increased risk of relapse / death ? • (who might benefit from treatment ?) • clinical markers • patient-related factors • tumour-related factors • predictive markers • who will benefit from treatment ? • who will benefit from the new treatment ? • molecular markers • tumour related factors • tumour environment factors

  4. NSCLC individualised treatment> markers predictive for response Wild type: EGFR activated by EGF • EGFR activating mut (exon 19/21) • no need for activation by ligand • TK works on its own • tumour ‘addicted’ to this pathway • -> very sensitive to TKIs High response rate Lynch et al, N Engl J Med 350:2129-2139, 2004 Paez et al, Science 304:1497-1500, 2004

  5. ? NSCLC individualised treatment> markers predictive for response Wild type: EGFR activated by EGF • EGFR activating mut (exon 19/21) • no need for activation by ligand • TK works on its own • tumour ‘addicted’ to this pathway • -> very sensitive to TKIs High response rate OS (PFS) benefit Lynch et al, N Engl J Med 350:2129-2139, 2004 Paez et al, Science 304:1497-1500, 2004

  6. 100 80 60 40 20 0 Active treatment: biomarker-negative Active treatment: biomarker-positive Survival (%) 0 6 12 18 24 Time (months) NSCLC individualised treatment> prognostic vs. predictive markers Single arm (uncontrolled) study: impossible to know if marker is prognostic or predictive for survival

  7. PROG Biomarker-negative (control) 100 80 60 40 20 0 Biomarker-positive (control) Biomarker-negative (active treatment) Biomarker-positive (active treatment) Survival (%) 0 6 12 18 24 Time (months) NSCLC individualised treatment> prognostic marker RCT: prognostic biomarker

  8. NSCLC individualised treatment> predictive marker PRED Biomarker-positive (control) 100 80 60 40 20 0 Biomarker-negative (control) Biomarker-negative (active treatment) Biomarker-positive (active treatment) Survival (%) 0 6 12 18 24 Time (months) RCT: biomarker predictive for survival [“quantitative”]: biomarker + => survival benefit with active treatment

  9. NSCLC individualised treatment> predictive marker PRED+ 100 80 60 40 20 0 Biomarker-positive (control) Biomarker-negative (control) Biomarker-negative (active treatment) Biomarker-positive (active treatment) Survival (%) 0 6 12 18 24 Time (months) RCT: biomarker stongly pred. for survival [“qualitative”]: biomarker + => survival benefit with active treatment biomarker - => survival harm with active treatment

  10. Biomarker-positive (control) 100 80 60 40 20 0 Biomarker-negative (control) Biomarker-negative (active treatment) Biomarker-positive (active treatment) Survival (%) 0 6 12 18 24 Time (months) NSCLC individualised treatment> predictive marker Two types of statistical analysis: - is there a significant effect of treatment in a stratum?- P P

  11. 100 80 60 40 20 0 Survival (%) 0 6 12 18 24 Time (months) NSCLC individualised treatment> predictive marker Two types of statistical analysis: - is there a significant effect of treatment in a stratum? - does the biomarker significantly discriminates treatment effects over strata? P-value of interaction

  12. The principle of (therapeutic) biomarkers Why could biomarkers improve treatment ? Challenges with biomarkers Biomarkers in adv. NSCLC 1st line therapy Biomarkers in relapsed NSCLC therapy Summary: current impact of biomarkers ?

  13. NSCLC individualised treatment> Erlotinib for low PS patients • Phase II randomised study • 1st line carbo-paclitaxel • vs. • 1st line erlotinib “Unselected patients with advanced NSCLC and PS 2 are best treated with combination chemotherapy as first-line therapy” Lilenbaum et al, J Clin Oncol 26:863-869, 2008

  14. NSCLC individualised treatment> Gefitinib for very low PS, EGFR mut+ pts • 30 poor PS NSCLC patients • 22 with PS 3 to 4 • response rate 66% • disease control rate 90% • PS improvement rate 79% • median PFS 6.5 mo • median OS 17.8 mo • 1-year survival 63% Inoue et al, J Clin Oncol 27:1394-1400, 2009

  15. The principle of (therapeutic) biomarkers • Why could biomarkers improve treatment ? • Challenges with biomarkers • Biomarkers in 1st line studies • Biomarkers in maintenance studies • Biomarkers in relapse treatment studies • Summary: what could be the current impact of biomarkers ?

  16. NSCLC individualised treatment

  17. Ideal situation: prospective use of molecular markers in large randomised controlled trials with well defined patient populations standardised/validated marker analysis methods NSCLC individualised treatment > the labyrinth of predictive biomarkers Reality: • retrospective analysis of molecular markers • on a small subset of RCT patients – or from non-randomised studies • in often heterogeneous populations • with variable analysis methods

  18. NSCLC individualised treatment Literature on lung cancer biomarkers

  19. The principle of (therapeutic) biomarkers Why could biomarkers improve treatment ? Challenges with biomarkers Biomarkers in adv. NSCLC 1st line therapy Biomarkers in relapsed NSCLC therapy Summary: current impact of biomarkers ? Histology PGX EGFR / Kras Missing

  20. R Advanced NSCLC 1st line> Cis-Pem vs. Cis-Gem: OS results • Stage IIIB/IV NSLC • Chemonaive • PS 0-1 Cis 75 mg/m2 day 1+ Pemetrexed 500 mg/m2 day 1 N=850 Cis 75 mg/m2 day 1 + Gemcitabine 1250 mg/m2 day 1,8 N=850 Stratified: stage, PS, gender, histo v. cyto diagnosis, brain mets Primary endpoint: non-inferior OS Prespecified analyses (in addition to randomisation factors): age, ethnicity, smoking status, and histology Scagliotti et al, WCLC12 and J Clin Oncol 26:3543-3551, 2008

  21. NSCLC individualised treatment> Cis-Pem vs Cis-Gem: histology predictive Scagliotti et al, WCLC12 2007

  22. NSCLC individualised treatment> Cis-Pem vs Cis-Gem: histology predictive P for interaction = 0.0011 Scagliotti et al, WCLC12 2007

  23. 6 Thymidilate Synthase (TS) P<0.0001 5 4 3 2 1 Adeno Squamous NSCLC individualised treatment > expression of TS in NSCLC Ceppi et al, Cancer 107:1589-1596, 2006

  24. The principle of (therapeutic) biomarkers Why could biomarkers improve treatment ? Challenges with biomarkers Biomarkers in adv. NSCLC 1st line therapy Biomarkers in relapsed NSCLC therapy Summary: current impact of biomarkers ? Histology PGX EGFR / Kras Missing

  25. NSCLC individualised treatment> pharmacogenomics phase II (MADeIT) RRM1 expression High Low R/ without Gemcitabine R/ with Gemcitabine ERCC1 expression ERCC1 expression High Low High Low R/ without platinum R/ with platinum R/ without platinum R/ with platinum = Docetaxel Vinorelbine = Carboplatin Docetaxel = Docetaxel Gemcitbine = Carboplatin Gemcitabine Simon et al, J Clin Oncol 25:2741-2746, 2007

  26. NSCLC individualised treatment> pharmacogenomics phase II (MADeIT) Simon et al, J Clin Oncol 25:2741-2746, 2007

  27. R NSCLC individualised treatment > pharmacogenomics phase III trial • Advanced NSCLC • Chemonaive • Paraffin-embedded • tumour tissue • PS 0-1 • ERCC1 genotyped • low: Cis-Docetaxel • high: Gem-Docetaxel N=225 • Control • Cis-Docetaxel N=141 Primary endpoint: overall response rate Cobo et al, J Clin Oncol 25:2747-2754, 2007

  28. NSCLC individualised treatment > pharmacogenomics phase III trial

  29. The principle of (therapeutic) biomarkers Why could biomarkers improve treatment ? Challenges with biomarkers Biomarkers in adv. NSCLC 1st line therapy Biomarkers in relapsed NSCLC therapy Summary: current impact of biomarkers ? Histology PGX EGFR / Kras Missing

  30. R NSCLC individualised treatment > IPASS [IRESSA Pan Asia Study] • First-line NSCLC (N=1217) • Asian Adenocarcinoma • Never/light ex-smokers* • PS 0-2 Gefitinib 250 mg/d until PD N=609 Carboplatin-Paclitaxel max. 6 cycles N=608 * Never smokers, <100 cigarettes in lifetime Light ex-smokers, stopped 15 years ago and smoked 10 pack years * Stratified: PS, gender, smoking history, centre Primary endpoint: non-inferior PFS Mok et al, ESMO 2008 and N Engl J Med 316: Aug 19, 2009

  31. 1.0 PFS HR 0.74 [0.65-0.85] P<0.0001 0.8 0.6 0.4 Gefitinib (N=609) 0.2 Carbo-Pacli (N=608) 0.0 0 4 8 12 16 20 24 Months NSCLC individualised treatment> IPASS: PFS Mok et al, ESMO 2008 and N Engl J Med 316: Aug 19, 2009

  32. NSCLC individulised treatment > IPASS: PFS by EGFR mutation status EGFR mut + EGFR mut - 1.0 1.0 HR 0.48 [0.36, 0.64] P<0.0001 HR 2.85 [2.05, 3.98] P<0.0001 0.8 0.8 0.6 0.6 Gefitinib (n=132) Carbo-pacli (n=85) Progression-free survival Progression-free survival 0.4 0.4 0.2 0.2 Carbo-pacli (n=129) Gefitinib (n=91) 0.0 0.0 0 4 8 12 16 20 24 0 4 8 12 16 20 24 Months Months Mok et al, ESMO 2008 and N Engl J Med 316: Aug 19, 2009

  33. NSCLC individulised treatment > IPASS: PFS by EGFR mutation status EGFR mut + EGFR mut - 1.0 1.0 HR 0.48 [0.36, 0.64] P<0.0001 HR 2.85 [2.05, 3.98] P<0.0001 0.8 0.8 0.6 0.6 Gefitinib (n=132) Carbo-pacli (n=85) Progression-free survival Progression-free survival 0.4 0.4 0.2 0.2 Carbo-pacli (n=129) Gefitinib (n=91) 0.0 0.0 0 4 8 12 16 20 24 0 4 8 12 16 20 24 Months Months Treatment by subgroup interaction test, P<0.0001 Mok et al, ESMO 2008 and N Engl J Med 316: Aug 19, 2009

  34. NSCLC individualised treatment>EGFR mutation in relation to clinical factors Mitsudomi et al, Cancer Sci 98:1817-1824, 2007

  35. The principle of (therapeutic) biomarkers Why could biomarkers improve treatment ? Challenges with biomarkers Biomarkers in 1st line studies Biomarkers in maintenance studies Biomarkers in relapse treatment studies Summary: what could be the current impact of biomarkers ? Histology PGX EGFR / Kras Missing

  36. R Advanced NSCLC 1st line > Bevacizumab phase III (AVAiL) • Advanced NSCLC • Chemonaive • PS 0-1 • Non-squamous • “Beva-eligible” N=345 N=351 Cis-Gemcitabine up to 6 cy + Bevacizumab 7.5 mg/kg until PD Cis-Gemcitabine up to 6 cy + Bevacizumab 15 mg/kg until PD N=347 Cis-Gemcitabine up to 6 cy + Placebo until PD • Beva-eligible: • no gr 2 haemoptysis • no invasion of major vessels • no brain/spinal cord metastases • no uncontrolled hypertension • no history of thrombosis • no hemorrhagic disorders • no recent anticoagulation Primary endpoint: PFS (modified from OS) Reck et al, J Clin Oncol 27:1227-1234, 2009

  37. NSCLC individualised treatment>predictors of benefit from VEGF directed therapy

  38. The principle of (therapeutic) biomarkers Why could biomarkers improve treatment ? Challenges with biomarkers Biomarkers in adv. NSCLC 1st line therapy Biomarkers in relapsed NSCLC therapy Summary: current impact of biomarkers ?

  39. R Relapsing NSCLC > Erlotinib phase III (BR.21) • Relapsed NSCLC • 3rd line • 2nd line unfit for chemo • PS 0-3 • no EGFR testing • required BSC + Erlotinib 150 mg/d N=488 BSC + Placebo N=243 • Stratified PS (0-1, 2-3), stage (IIIB, IV) • prior chemo, centre HR 0.70 [0.58-0.85] P<0.001 Primary endpoint: superior OS Shepherd et al, N Engl J Med 353:123-132, 2005

  40. Relapsing NSCLC> EGFR factors and survival P-value of interaction 0.25 Tsao et al, N Engl J Med 353:133-44, 2005

  41. Relapsing NSCLC> BR.21 updated EGFR / Kras data ? ? Shepherd et al, ASCO 2007

  42. Relapsing NSCLC>EGFR biomarkers and differential survival effect

  43. Relapsing NSCLC>EGFR factors (EGFR-TKI vs. placebo) Predictive for diff. survival benefit • Clinical • never-smoking history • SE Asian • skin rash (post-hoc) • Biological • EGFR FISH • (EGFR IHC)

  44. Erlotinib active in relapsed NSCLC: better than BSC But is this the relevant overall comparison in 2nd line? do we treat a fit patient with relapsed NSCLC with BSC only? The real comparison is between chemo and EGFR-TKI INTEREST Coming: TITAN (E vs. P or D), US (E vs. P) Relapsing NSCLC>tailoring the treatment to the patient

  45. R HR 1.02 [0.91-1.15] Relapsing NSCLC > phase III INTEREST • Relapsed NSCLC • 1 previous line (85%) • 2 previous lines (15%) • PS 0-2 Gefitinib 250 mg/d N=733 Docetaxel 75 mg/m2 q3w N=733 . Primary endpoint: non-inferior OS [upper limit of 95%CI of HR <1.154] Douillard et al, WCLC12, 2007 and Kim et al, Lancet 372:1809-1818, 2008

  46. Overall EGFR FISH + EGFR FISH - EGFR expression + EGFR expression - EGFR mutation + EGFR mutation - K-RAS mutation + K-RAS mutation - 0 0.5 1.0 1.5 2.0 HR (gefitinib vs docetaxel) and 95% CI Favors gefitinib Favors docetaxel Relapsing NSCLC > INTEREST: Forest plot Douillard et al, WCLC12, 2007 ad Kim et al, Lancet 372:1809-1818, 2008

  47. Relapsing NSCLC>EGFR biomarkers and differential survival effect

  48. Predictive for diff. survival benefit Clinical N prior regimens Biological None Relapsing NSCLC >EGFR factors (EGFR-TKI vs. docetaxel)

  49. The principle of (therapeutic) biomarkers Why could biomarkers improve treatment ? Challenges with biomarkers Biomarkers in adv. NSCLC 1st line therapy Biomarkers in relapsed NSCLC therapy Summary: current impact of biomarkers ?

  50. NSCLC individualised treatment

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