Presentación de PowerPointcontentednet.clientes.factoriadeinnovacion.com... · 2. Inmunoterapia • PDL1 – Harmonización: BP2B, LC-SCRUM-IBIS – PDL1 en citología: MA13 (WCLC18)

Biomarcadores pronósticosRamón PalmeroInstitut Català d’Oncologia, Hospital Duran i ReynalsL’Hospitalet de Llobregat (Barcelona)

Agenda

1. Diagnóstico precoz– Circulating cancer genome atlas (CCGA)

2. Inmunoterapia– PDL1– TMB– bTMB– Otros biomarcadores

3. Terapias dirigidas– EGFR– ALK

1. Diagnóstico precoz

• TC de baja dosis:– NLST y NELSON han demostrado una reducción de la

mortalidad por cáncer de pulmón. – No todas las personas de riesgo cumplen los criterios de

screening actuales.– Tasa de falsos positivos genera un problema diagnóstico.– Implementación difícil.

• Blood-based screening assays:– Los tests con uno o pocos marcadores tienen una alta

especificidad pero una baja sensibilidad.– Plasma cfDNA permitiría desarrollar una firma genética

relacionada con cáncer más amplia.

ASCO18 #LBA8501: Genome-wide sequencing for early stage lung cancer detection from plasma cell-free DNA (cfDNA): The Circulating Cancer Genome Atlas (CCGA) study – Oxnard GR, et al

Study objective: To investigate the suitability of a non-invasive plasma cfDNA analysis to detect early lung cancer

ASCO18 #LBA8501: Genome-wide sequencing for early stage lung cancer detection from plasma cell-free DNA (cfDNA): The Circulating Cancer Genome Atlas (CCGA) study – Oxnard GR, et al

The assays consistently detected lung cancer across stages, histological subtypes and populations, which was replicated in the training and test sets.

Subgroup Targeted WGS MethylationCases

0% 20% 40% 60% 80% 100%Sensitivity at 98% specificity

Stage I

Stage II

Stage III

Stage IV

22

13

38

45

• cfDNA-based assays showed promise in the development of an early cancer detection test with high specificity but confirmatory analyses are needed (ongoing).

The majority of cfDNA SNVs were WBC-matched (98% in non-cancer and 54% in cancer group)High specificity was achieved by correcting for WBC-matched variants; false positives occurred in only 5 of 580 (<1%) of non-cancer samples.

Test

Single locNo WBC filtering

NGSNo WBC filtering

CCGA targetedwith WBC filtering

• cfDNA-based assays (NGS genotyping, bTMB…) require controlling for clonal hematopoiesis.

2. Inmunoterapia

• PDL1– Harmonización: BP2B, LC-SCRUM-IBIS– PDL1 en citología: MA13 (WCLC18)

• TMB– Harmonización: ESMO: chang, stenzinger, fabrizio.– FxPx: pantumor Ding, BioLACE– FxPd: 2L Higgs ESMO18, Rizvi WCLC18

• bTMB– Harmonización: TSO500, GHOmni500– Gandara Nat Med– BF1RST (trial confirmación BFAST)

Harmonización PDL1 IHC

Summary of approved and investigational PD-L1 IHC diagnostic assays

Nivolumab Pembrolizumab Atezolizumab Durvalumab Avelumab

Antibody clone 28-8 SP263 22C3 SP263 SP142 SP263 73-10

Assay developer Dako Ventana Dako Ventana Ventana Ventana Dako

PD-L1 scoring TC TC TC TC TC and IC TC TC

Cutoff value forclinical trials

≧1%≧5%≧10%

≧1% ≧5% ≧10%

≧1%≧50%

≧1%≧50%

TC≧50% (TC3)+ IC≧10% (IC3) TC≧25% TC≧1%

Cutoff value for1st line /2nd line

NA/ None

NA/ None

≧50%/≧1%

≧50%/≧1% NA/ None NA/NA NA/NA

PD-L1 staining PD-L1 interpretationTumor sampling

Correlation toclinical outcome and

clinical decision

Tumor heterogeneitySample type and size

Preanalytical parametersAnalytical performance: PD-L1 assays, LDT

Interobserver agreementTraining

Sources of variability in PD-L1 IHC


Comparing PD-L1 tumor cell expression in paired specimens

FNACNB

ResectionPrimary NSCLC

Endoscopy

Resection vs. biopsy81 to 92% concordanceKappa 0.40-0.70

Resection vs. TMA cores79 to 93% concordance

Cell blocks Good concordance (~80%)with paired tissue specimens

Biopsy

Li et al., J Thor Oncol 2017Gniadek et al., Mod Pathol 2017Casadevall et al., Clin Lung Cancer 2017Nakamura et al., PLoS One 2017Munari et al., J Thor Oncol 2018

Ilié et al., Ann Oncol 2016Gradecki et al., Am J Surg Pathol 2018 Skov et al., AIMM 2017

Heymann et al., Cancer Cytopathol 2017Wang et al. Ann Oncol 2018Jain et al., Cancer Cytopathol 2018Noll et al., Cancer Cytopathol 2018Ilié et al., Cancer Cytopathol 2018Russel-Glodman et al., Cancer Cytopathol 2018

Paired primary vs metastases76 to 90% concordanceKappa 0.61-0.75

Mansfield et al., Ann Oncol 2016Mansfield et al., Clin Cancer Res 2016Midha et al., abstract in J Clin Oncol 2016Kim et al., Oncotarget 2017Liu et al., Clin Lung Cancer 2017Takamori et al., Anticancer Res 2017Keller et al., Mod Pathol 2018Munari et al., Oncotarget 2018 Metastases:

Lymph nodes, lung, brain,…


• PD-L1 assay comparability• Team of international experts• Industrial-academic

collaborative partnership

• Prospective nationwide study• PD-L1 assay comparison in

real world• Analytical and clinical

performance


Concordance between PD-L1 assays in the Blueprint study



clinical decision




Blueprint 2B Blueprint 1/2A Blueprint 2AComparability of PD-L1 scores in matched specimens preparedfrom the same resected tumors


Interobserver agreement for PD-L1 staining assessment (TC)


clinical decision

Blueprint 2B Blueprint 1/2A Blueprint 2AComparability of PD-L1 scores in matched specimens preparedfrom the same resected tumors






Concordance between PD-L1 assays in the Blueprint study


clinical decision

LC-SCRUM-IBIS Analytical comparison in a large multicenter prospective cohort

Interobserver comparison:3 pathologists

Correlation to TMB and clinical outcome





22C3 28-8 SP263 SP142_TC SP142_TC+IC

Negative405 418 480 756 64143% 45% 51% 81% 69%

Low268 266 199 109 17829% 29% 21% 12% 19%

High260 249 254 68 11428% 27% 27% 7% 12%

Distribution of PD-L1 IHC expression Cohen's kappa value

28-8 SP263 SP142_TC

22C33-tier 0.894 0.765 0.187

10-tier 0.722 0.517 0.136

22C3 28-8 SP263 SP142_TC

SP142_TC+IC 0.271 0.293 0.324 0.597

No agreement Almost perfect≦0 0.01-0.20 0.21-0.40 0.41-0.60 0.61-0.80 0.81-1.00

pathologistconsensus score

22C3 28-8 SP263 SP142_tc SP142_ic

A 0.657 0.659 0.700 0.732 0.595

B 0.772 0.775 0.762 0.702 0.804

C 0.880 0.869 0.869 0.856 0.884

Tumor Mutational Burden (TMB)

• TMB es una medida del nº de mutaciones somáticas de un genoma tumoral.

• TMB varia entre tipos tumorales y entre pacientes dentro de cada tipo de tumor.

• TMB se puede medir con diferentes técnicas de next-generation sequencing (NGS), incluyendo whole exome sequencing (WES) y targeted gene panel assays (>300 genes)

• TMB puede variar dependiendo de la región genómica secuenciada y del tipo de mutaciones incluidas.

• Una TMB alta y una carga de neoantigenos alta estan asociadas con una tasa mayor de respuesta inmune antitumoral y un mayor beneficio clínico a immune checkpoint inhibitors.

• Necesitamos estandarizar los parámetros de los diferentes métodos de medición de TMB para poder interpretar los resultados.

• El valor clínico de la medida de la TMB depende de disponer de tests precisos y reproducibles en diferentes plataformas y centros.

TMB assays









TMB como factor predictor de respuesta a IO

Rizvi, Science 2015

Months

100

75

50

25

0

6 1893

PFS

(%)

0 12 15 2421

High TMB, PD-L1 ≥50%

Low/medium TMB, PD-L1 ≥50%

Nivolumab Arm

CheckMate 026

Carbone, NEJM 2017

CheckMate 032

Low

Medium

Hellmann, Cancer Cell 2018

Ove

rall

surv

ival

PFS

Borghaei, ASCO 2018; abstract 9001

Hellmann, NEJM 2018

PFS

PFS

CheckMate 227









Harmonización TMB

• Bioinformatic pipelines:– Germline filtering– Variant calling

• WES vs targeted panel (>300 genes)• Total # exonic muts vs muts/Mb• Threshold # mutations• Type of mutations?

– Only transcriptome?– Only neoantigens?– Only clonality?

• Different thresholds for different tumor types?• Tumor vs cfDNA

ESMO Fabrizio 56PDESMO Chaudhary 173PESMO Ikeda 1410P

ESMO Chang 69PESMO Stenzinger 141P

ESMO TSO500ESMO GHOmni

ESMO18 #69P: Toward the Standardization of Bioinformatics Methods for the Accurate Assessment of Tumor Mutational Burden. H Chang

ESMO18 #69P: Toward the Standardization of Bioinformatics Methods for the Accurate Assessment of Tumor Mutational Burden. H Chang

ESMO18 #141P: Tumor Mutational Burden (TMB) Standardization Initiative: Establishing a Consistent Methodology for TMB Measurement in Clinical Samples. Stenzinger

ESMO18 #141P: Tumor Mutational Burden (TMB) Standardization Initiative: Establishing a Consistent Methodology for TMB Measurement in Clinical Samples. Stenzinger

ESMO18 #56PD: Analytic Validation of Tumor Mutational Burden as a Companion Diagnostic for Combination Immunotherapy in Non-Small Cell Lung Cancer. Fabrizio

27



Harmonización TMB

• Too many cut offs

• Tumor requirements variable, with high rejection rate (¡¡42%¡¡ CM227)

• Related factors: Aneuploidy, clonality (heterogeneity)

• Low precision (high overlap btw response groups)

• Inmature, mainly PFS, subgroups or retrospective

• Predictive or prognostic?

▪ TMB: total non-silent somatic mutation counts in coding region, including nonsense, missense, insertion, deletion and splice mutation

ESMO18 #: TMB and prognosis across pan-cancers. H. Ding

TMB prognostic in NSCLC

• High nonsynonymous TMB was associated with a better prognosis in patients with resected NSCLC.

• The benefit of adjuvant chemotherapy on LCSS was more pronounced in patients with low nonsynonymous TMBs

Devarakonda JCO18

ESMO #65PD: High TMB and PD-L1 have similar predictive utility in 2L+ NSCLC patients treated with anti-PD-L1 and anti-CTLA-4. Higgs BW

• Non-Sq NSCLC 2L• Durvalumab + tremelimumab • PD-L1 pos ≥25% (SP263)• TMB FM in 106/200 (53%).• TMB high (11 mut/Mb)

ESMO #65PD: High TMB and PD-L1 have similar predictive utility in 2L+ NSCLC patients treated with anti-PD-L1 and anti-CTLA-4. Higgs BW

WCLC18 #P2.04-14: TMB assessed by a targeted NGS assay predicts benefit from immune checkpoint inhibitors in NSCLC. Rothschild S

Benefit No Benefit

%

Local validation of Oncomine TML Assay(University Hospital Basel, Thermo Fisher)

n=62

P<0.01

High Intermed. Low

ASCO #9022: Clinical and molecular features predicting long-term response (LTR) to anti-PD-(L)1 based therapy in patients with NSCLC – Rizvi H

• Study objective– To investigate the clinical and molecular features that may help to

identify those patients with NSCLC who will derive long-term benefit from anti-PD-(L)1-based therapies

• Methods– Data were collected for patients (n=766) from one centre with

advanced NSCLC who received anti-PD-(L)1-based therapies between April 2011 and November 2016

– A long-term response (LTR) was defined as PFS >18 months– Tumour mutation burden (TMB) was assessed using MSK-IMPACT – PD-L1 expression was determined by immunohistochemistry

• Key results– 62 (8%) patients had LTR; TMB was higher (12.24 vs. 6.34 mut/Mb) and the

proportion of high PD-L1 expression was greater (43% vs. 23%) in those with vs. those without LTR

– TMB was also higher in patients with LTR compared with those who showed initial response (PR with PFS <18 months), whereas PD-L1 expression is similar

• Conclusion– Characteristics that identify patients with LTR may be distinct from the features

predicting initial response to anti-PD-(L)1 therapy, with high TMB significantly predicting for LTR

TMB,

Mb

100

80

60

40

20

0Long-term response

Short-termresponse

Tumour mutation burden (TMB) PD-L1 expressionp=0.002 p=0.87

Patie

nts,

%

100

80

60

40

20

0Long-term response

Short-termresponse

39%

35%

26%

35%

42%

23%

ASCO #9022: Clinical and molecular features predicting long-term response (LTR) to anti-PD-(L)1 based therapy in patients with NSCLC – Rizvi H

Harmonización TMB

• Bioinformatic pipelines:– Germline filtering– Variant calling

• WES vs targeted panel (>300 genes)• Total # exonic muts vs muts/Mb• Threshold # mutations• Type of mutations?

– Only transcriptome?– Only neoantigens?– Only clonality?

• Different thresholds for different tumor types?• Tumor vs cfDNA

ESMO Fabrizio 56PDESMO Chaudhary 173PESMO Ikeda 1410P

ESMO Chang 69PESMO Stenzinger 141P

ESMO TSO500ESMO GHOmni

For each plasma sample, matched FFPE tissue was tested to calculate the TMB and tumor fraction in plasma. In addition, tumor fraction is also estimated by plasma only by leveraging clonal mutation frequency.

ESMO18 #163P: Accurate measurement of TMB in liquid biopsy (bTMB) using a 500 gene panel. Jiang

• Most plasma only mutations are clustered in TP53, DNMT3A, TET2…, which are known to be associated with clonal hematopoiesis (CH).

• Therefore, mutations in CH associated genes are removed from bTMBcalculation.

ESMO18 #163P: Accurate measurement of TMB in liquid biopsy (bTMB) using a 500 gene panel. Jiang

44

ESMO18 #131P: Development and analytical validation of a plasma-based TMB score from nex generation sequencing panels. Quinn.

45

ESMO18 #131P: Development and analytical validation of a plasma-based TMB score from nex generation sequencing panels. Quinn.

46

• Plasma yields an accurate readout of TMB

• Clonal hematopoiesis should be taken into account

• Validación en series pequeñas

• Comparación con WES (¿gold standard in tissue?)

Estandarización bTMB

WCLC18 #12001: Prospective clinical evaluation of blood-based tumor mutational burden (bTMB) as a predictive biomarker for atezolizumab (atezo) in 1L non-small cell lung cancer (NSCLC): Interim B-F1RST results – Velcheti V, et al

ESMO18 #LBA55: Primary efficacy results from B-F1RST, a prospective phase II trial evaluating blood-based tumour mutational burden (bTMB) as a predictive biomarker for atezolizumab (atezo) in 1L nonsmall cell lung cancer (NSCLC) – Kim ES, et al





• Strenghts: Prospective validation of bTMB based on preliminary bTMB data

from OAK/POPLAR Pts with high bTMB achieved higher ORR and longer PFS (HR

0.66, 95%CI 0.42-1.02) PFS curves together during the first 3 months

• Limitations: Non-randomized study (potential biases) – B-FAST study is

ongoing where pts with moderate/high bTMB (cohort C) are randomized to 1L CT or atezo

No data on PD-L1 was shown



Otros biomx IO

• Comutaciones• irAEs• Corticoides• Antibiotico• Microbiota.

3. Terapias dirigidas

• EGFR– Mecanismos de resistencia a osimertinib:

1ª línea: cf DNA en FLAURA (Ramalingam SS) 2ª línea: cf DNA en AURA3 (Papadimitrakopoulou VA)

• ALK – Valor predictivo de las variantes de fusión

(WCLC18, Qiao) ALEX study (ESMO, Dziadziuszko R)

• ROS1– IHC interobservador (WCLC18, Hanlon)

ESMO18 #LBA50: Mechanisms of acquired resistance to first-line osimertinib: preliminary data from the phase III FLAURA study –Ramalingam SS

• Analysis set of valid paired NGS data were available for 272 patients– Osimertinib: 113/279 (41%)– Gefitinib + erlotinib: 159/277 (57%)

ESMO18 #LBA50: Mechanisms of acquired resistance to first-line osimertinib: preliminary data from the phase III FLAURA study –Ramalingam SS

• The most common acquired resistance mechanisms in the osimertinib arm (n=91) were:

– MET amplification (15%) and EGFR C797S mutation (7%)– There was no evidence of acquired T790M

• New mechanisms that may lead to aggressive disease biology were not identified

ESMO #LBA51: Analysis of resistance mechanisms to osimertinib in patients with EGFR T790M advanced NSCLC from the AURA3 study. Papadimitrakopoulou VA

• Analysis set of valid paired NGS data were available for 113 patients– Osimertinib: 83/279 (30%)– Platinum-pemetrexed: 30/140 (21%)

Papadimitrakopoulou VA, et al. Ann Oncol 2018;29(suppl 5):Abstr LBA51

• Acquired EGFR mutations: 21%• METamp*: 19%• Cell cycle gene alterations: 12%• HER2amp*: 5%• PIK3CAamp* / mutation: 5%• Oncogenic fusion: 4%• BRAF V600E: 3%

ESMO #LBA51: Analysis of resistance mechanisms to osimertinib in patients with EGFR T790M advanced NSCLC from the AURA3 study. Papadimitrakopoulou VA

Resistencia a osimertinib

ALK inhibitors

ALK inhibitors

• Diferente sensibilidad in vitro según mutaciones y variantes de fusión.

Gainor Cancer Discover 2016

ALK mutations ALK Fusion variants

Childress, Mol Cancer Res 2018

ALK inhibitors

Lin JCO 18

Dziadziuszko, ESMO 2018

V1 > non V1 (35p)

V1/2 > V3a/b (54p)

V2 > non V2 (60p)

Yoshida JCO 16Woo Ann Oncol 17

Qiao, WCLC 18

no difference

no difference

ASCO #9032: Lorlatinib in Patients With Previously Treated ALK+ Advanced Non-Small Cell Lung Cancer (NSCLC): Updated Efficacy and Safety. Besse

cfDNA analysis:- 45/190 patients (24%) with 1 or more

ALK kinase domain mutations- 75 mutations detected (used for the

frequency denominator)

Shaw AT ASCO 2018Lovly C ASCO 2018

Conclusiones

• Biomarcadores de diagnóstico precoz– Low dose CT screening (NELSON)– Blood-based assays (CCGA)

• Biomarcadores de respuesta a IO– Más estandarización/harmonización– Más validación prospectiva

• Biomarcadores de terapias dirigidas– Validación en plasma (cfDNA)– Integración en plataformas multiplexing.– Validación prospectiva de valor predictivo (fusion variants,

comutaciones…)

Documents

Presentación de PowerPointcontentednet.clientes.factoriadeinnovacion.com... · 2. Inmunoterapia • PDL1 – Harmonización: BP2B, LC-SCRUM-IBIS – PDL1 en citología: MA13 (WCLC18)