New molecular targets in lung cancer therapy
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1 New molecular targets in lung cancer therapy Giuseppe Pelosi Pathology Division, Science & Technology Park, IRCCS Multimedica, Milan Milan - Italy
2 Advanced lung cancer (IIIB IV) Subtyping Oncogene addiction (EGFR, ALK, ROS1) Clinics (age, PS, comorbidities) Subtyping PD-L1 expression (TPS) Clinics (age, PS, comorbidities) No oncogene addiction
3 Advanced lung cancer: subtyping NON-SQUAMOUS no p40, Parwise no squamous comparison of p40 and TTF1 IHC between biopsy/ cellblock (BCS) samples and paired surgical specimens (SS) SQUAMOUS resulted in close correlation coefficients (by far > 0.9), revealing that BCS were as reliable as SS for rendering the definitive diagnoses
4 Molecular diagnostics Highly selective testing Stepwise, single-gene testing algorithms tailored to specific cancers Multiplex testing Simultaneous multigene and multiplexed approach Unbiased testing Global and unbiased whole-genome approach EGFR mutation DNA RNA DNA RNA KRAS mutation Multiplexed mutation testing Multiplexed RNA profiling and fusion transcript detection Whole-exome (or genome) sequencing Whole-transcriptome sequencing (including paired ends) ALK fusion Genomic copy number profiling Present Taylor BS & Ladanyi M J Pathol 2011 Future
5 Multiplex testing by targeted NGS
6 Advanced lung cancer (IIIB IV) Testing Subtyping should extend beyond those molecular alterations Oncogene addiction for which (EGFR, targeted ALK, therapies ROS1 are stand-alone approved by gene; regulatory HER2, MET, agencies to BRAF, KRAS, include RET molecular NGS panel) alterations Immunohistochemistry for which there for ALK/ROS1 is compelling evidence of effective 5% sensitivity investigational assay for EGFR targeted T790M therapies (and, more recently, immunotherapies) from published cfdna for targetable mutations, when the tissue is an issue clinical trials Immunotherapy markers (PD-L1) Lindeman et al, JTO 2017
7 Advanced lung cancer (IIIB IV) Must-test biomarkers: EGFR, ALK, ROS1, PD- L1 by all laboratories Should-test biomarkers: an expanded panel (BRAF, MET, RET, HER2, KRAS) Investigational biomarkers: all the other genes Must-test biomarkers as single-gene assay: standard of care for all patients Should-test biomarkers: to direct patients to clinical trials (in larger gene panel) Investigational biomarkers: not yet applicable to clinical use
8 Advanced lung cancer (IIIB IV) H&E SPA TTF1 EGFR: ex 19, pk745_750a del
9 Advanced lung cancer: ALK IHC 2+/3+ using mab 5A4 and/or D5F3
10 Advanced lung cancer: ROS-1 IHC 2+/3+ using mab D4D6
11 Should-test biomarkers Lindeman et al, JTO 2017
12 Investigational biomarkers Lindeman et al, JTO 2017 Lindeman et al, JTO 2017
13 Molecular biomarkers 1. Targeted therapy: new targets muts, fusions, CNVs driver variations actionable variations immune checkpoint 2. Tumor heterogeneity cancer biology drug resistance 3. Classification WHO & beyond 4. Prognosis
14 PD-L1 assessing for immunotherapy Baseline On-treatment CD8 T cells PD-L1 CD8 T cells PD-L1 MPDL3280A (PD-L1 inhibitor)
15 PD-L1 assessing for immunotherapy Blueprint Phase 2 Team Members 15 countries 5 continents M. S. Tsao (Toronto) M.-B. Beasley (New York) A. Borczuk (New York) A. Moreira (New York) J. Sauter (New York) W. D. Travis (New York) L. Chirieac (Boston) M. Mino-Kenudson (Boston) S. Dacic (Pittsburgh) I. Wistuba (Houston) F. R. Hirsch (Denver) H. Yu (Denver) M. Wynes (Denver) C. Poleri (Buenos Aires) STATISTICS: M. Pintilie (Toronto) Y. Yatabe (Nagoya) M. Noguchi (Tokyo) K. M. Kerr (Aberdeen) A. G. Nicholson (London) S. Lantuejoul (Lyon) G. Pelosi (Milan) L. Bubendorf (Basel) J. Botling (Uppsula) E. Thunnissen (Amsterdam) M. Kockx (Antwerp) J.-H. Chung (Seoul) G. Chen (Shanghai) T.-Y. Chou (Taipei) P. Russell (Melbourne)
16 PD-L1 assessing for immunotherapy Comparability among five assays on tumor cell staining Each circle represents the mean of all scores (glass slide & digital combined)
17 PD-L1 assessing for immunotherapy Moderate to strong reliability among all pathologists on tumor cell scoring Fleiss Kappa Statistics 1 >0.90: Near perfect : Strong : Moderate : Weak 1 McHugh ML. Biochemia Medica 2012;22:276-82
18 PD-L1 assessing for immunotherapy Poor reliability for immune cell scoring Fleiss Kappa Statistics : Moderate : Weak : Minimal
19 Tumor burden for immunotherapy Rhabdoid tumor Ewing sarcoma Thyroid AML Medulloblastoma Carcinoid Neuroblastoma Prostate CLL Low-grade glioma Breast Pancreas Multiple myeloma Kidney clear cell Kidney papillary cell Ovarian Glioblastoma multifome Cervical DLBCL Head and neck Colorectal Oesophageal adenocarcinoma Stomach Bladder Lung adenocarcinoma Lung squamous cell carcinoma Melanoma Mutation burden (WES, WGS, TNGS, mismatch repair deficiency) RCC RR 5 15% 2 Head and neck RR 19.6% 3 NSCLC RR 19% 4 Somatic mutation frequency (/Mb) 1 n = , Ovarian RR ~10 25% 5 Bladder RR 26% 6 Melanoma RR 25 40% 7 10 BMS
20 Tumor molecular heterogeneity
21 Tumor heterogeneity spontaneous deamination APOBEC activity smoke-related DNA damage unknown microsatellite instability APOBEC activity unknown
22 Tumor heterogeneity: cancer biology spatial-termporal hierarchy of mutations Pelosi et al, Virchows Arch 2016 KDR LKB1 HER2 PTEN BRAF passenger SMAD4 ALK passenger passenger TP53 SMARCB1 ABL1 EZH2 branching PIK3CA SRC EGFR KRAS dominant/trunk
23 Tumor heterogeneity: cancer biology Hierarchizing mutations EGFR was dominant in EGFRmutated tumors, but branching in a few KRAS- and ALKaltered tumors The same gene could diversely act in diverse ADC, indicating different mechanisms operating in the lung cancer development TP53 was either branching or passenger in a few KRASmutated tumors EGFR tumor group BRAF EZH2 MET SMARCB1 SRC KRAS tumor group BRAF EGFR LKB1 MET SMARCB1 TP53 ALK tumor group ABL1 ALK EGFR HER2 KDR PIK3CA PTEN SMAD4 TP53 Pelosi et al, Virchows Arch 2016
24 Tumor heterogeneity: resistance EMT Vim E-cad MET/EGFR/ALK amplification
25 Tumor heterogeneity: classification 40% 50% LCNEC is not one tumor only 10%
26 Tumor heterogeneity: therapy 77 LCNEC TNGS: TP53 (87%), RB1 (46%), STK11 (13%), KEAP1 (18%) Co-mutation: TP53-RB1 (94%), STK11-KEAP1 (never RB1-STK11) OS PFS NSCLC-t: plat + gem/taxanes/pem SCLC-t: plat + etoposide RB1 wt NSCLC-t vs. SCLC-t 8.5 mo. vs 5.8 mo., p=0.05 without pemetrexed 9.6 mo. vs 5.8 mo. p=0.026 RB1 mut NSCLC-t vs. SCLC-t no differences Molecular matters for therapy LCNEC not one tumor only!
27 Tumor heterogeneity: prognosis OS DFS
28 Tumor heterogeneity: pathogenesis
29 Tumor heterogeneity: pathogenesis 100/148 tumors = 68%
30 Liquid biopsy to reassess over time
31 cfdna testing in liquid biopsy R: EGFR mutations when the tissue is an issue (also unwilling or unable patients) but if negative try on tissue biopsy (also to exclude other resistance mechanisms) Sensitivity 60-80%; specificity 80-95% ECO: Identifying EGFR T790M mutation in lung ADC patients with progression or secondary clinical resistance to EGFR-TKI No R: cfdna & CTC cannot be used for diagnosis of primary lung cancer; CTC cannot be used for the identification of EGFR or other mutations or EGFR T790M R: recommendation; ECO: expert consensus opinion Lindeman, JTO 2018
32 Summing up.. Subtyping, essential Multiplexed testing, by far preferable to stand-alone genes Molecular classification for clinical handling, classification and prognosis cfdna, a potential standard in EGFR TKI-treated lung cancer patients
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