Coordinación científica:

Dr. Rafael López López

Complejo Hospitalario Universitario de Santiago de Compostela

Organizado por: Sede:

San Francisco Hotel Monumento

Campillo de San Francisco, 3 - Santiago de Compostela

LUNG CANCER

Searching “early” biomarkers in blood

Eloisa Jantus Lewintre

Laboratorio Oncología Molecular- FIHGUV

Servicio Oncología Médica, CHGUV

Dpto Biotecnología- Universitat Politècnica de València

CIBERONC, Respiratory tract tumour programme

Screening & Diagnosis

Early detection of molecular alterations

Early detection of relapse

Early detection of resistance

Early diagnosis…

Is cancer present?

Is any “druggable”

alteration present?

Monitoring: Is it

possible to early

detect resistance

mechanism?

“Early” biomarkers … in different

scenarios

After tumor resection…

Early detection of relapse *Dr. Paz-Ares

Screening & Diagnosis Is lung cancer

present?

1º SCENARIO

• Enormous complexity and variability of cancer

• The lower frequency and volume of aberrations

• Potentially confounding phenomena such as clonal expansions of non-tumorous

tissues

• The accumulation of cancer-associated mutations with age

• The incomplete insight into driver alterations.

• Hence, pre-knowledge about endangered organs significantly extends options

for analysis which significantly facilitate early detection efforts.

CHALLENGES

Heitzer E. et al, Precision Oncology, 2017

1º SCENARIO

General

population

No knowledge of organ at risk

Systemic & Proximal samples (i.e. sputum, saliva, BAL)

Population at risk

Known organ at risk

Surveillance

Chronic exposure to toxic agents

1º SCENARIO

Screening

TRACER-X Data based on 100 NSCLC patients -> profiling preoperative plasma samples and compared to tissue samples

1º SCENARIO

GENOME

Abbosh, Nature 2017

Exome seq in Tumor samples

Blood: multiplex PCR for patient’s specific SNVs

Circulating Cell- Free Genome Atlas (CCGA) clinicaltrials.gov: NCT02889978 GRAIL company (investment $900 millions) & Memorial Sloane Kettering N=7.000 (cancer ) + 3.000 (no-cancer)

1º SCENARIO

To address two main challenges

1. sensitivity for early stage disease

2. the need for exquisite specificity

Aravanis A., Cell 2017

GENOME

508 genes analyzed Preliminary data : N= 161 (Breast, lung and prostate pts

• In 89 % of pts at least one mutation detected (tissue and blood) -> 85 % in those with lung cancer

• A total of 76% of actionable mutations detected in tumor tissue were also detected in cfDNA

Razavi et al, ASCO 2017

TRANSCRIPTOMICS: mRNA, miRNA, lncRNA

1º SCENARIO

Cui et al, Lung Cancer 2018

RNA isolation

TRANSCRIPTOMICS: miRNA

1º SCENARIO

• 24 miRNAs signature -> MILD trial -> N= 1000 controls ; N= 85 LC (Sozzi G, et al ; J Clin Oncol 2014)

Sensitiviy: 87% Specificity: 81%

• miR- Test -> High-risk individuals (n = 1115) enrolled in the Continuous

Observation of Smoking Subjects (COSMOS) lung cancer screening program. (Montani et al; J Natl Cancer Inst 2015)

Sensitivity of 79.2% (95% CI = 67.7% to 90.7%) Specificty of 75.9% (95% CI = 73.3% to 78.5%) • Tumor derived exosomal miRNAs for early detection of lung cancer (let 7b,

miR24, miR486 and let 7e) (N=48 training set and N=50 validation set) (Jin et al, Clin Cancer Res 2017)

PROTEOMIC , EPIGENOMIC

Ajona D, J Natl Cancer Inst 2013 Diaz-Lagares A, Clin Cancer Res 2016.

Sample: BAL

Sample: BAL

1º SCENARIO

C4d

Four genes signature

Puchades et al, Oncotarget 2016

METABOLOMICS

Training cohort

Validation cohort

NSCLC= 40 Healthy controls= 13 BPD=27

NSCLC= 142 Healthy controls= 74

1º SCENARIO

Fundación Mutua Madrileña APM-10/15 (Generalitat Valenciana)

METABOLOMICS

Louis E,. J Thorac Oncol 2016

Training set

Validation set

NSCLC= 98 Healthy controls= 89

NSCLC= 233 Healthy controls= 226

NSCLC correctly classified: 75% Healthy Controls correctly classified: 82%

1º SCENARIO

Plasma

GENOME & PROTEINS

CancerSEEK: circulating proteins and mutations in cell-free DNA

Cohen et al., Science 2018

Patients = 1,005 (non-metastatic cancers of the ovary, liver, stomach, pancreas, esophagus, colorectum, lung, or breast)

Controls = 802

• Capacity to identify the presence of relatively early cancers • Able to localize the organ of origin of these cancers.

16 genes 61-amplicon panel 33 bp/ amplicon

Gene

AKT1

APC

BRAF

CDKN2A

CTNNB1

EGFR

FBXW7

FGFR2

GNAS

HRAS

KRAS

NRAS

PIK3CA

PPP2R1A

PTEN

TP53

PCR-based assay

PROTEIN CA-125 CA19-9

CEA

HGF

Myeloperoxidase

OPN

Prolactin

TIMP-1

AFP

Angiopoietin-2

AXL

CA 15-3 CD44

CYFRA 21-1

DKK1

Endoglin

FGF2

Follistatin

Galectin-3

G-CSF

GDF15

HE4

IL-6 IL-8

Kallikrein-6

Leptin

Mesothelin

Midkine

NSE

OPG

PAR

sEGFR

sFas

SHBG

sHER2/sEGFR2/sErbB2

sPECAM-1

TGFa

Thrombospondin-2

TIMP-2

39 proteins (for organ

assessment)

8 proteins (including in

Cancer SEEK)

Multiplex assay (Luminex)

1º SCENARIO

Sensitivity: 70% Specificity: 99%

Cohen et al., Science 2018

• Presence of a mutation in one assayed gene OR, • Elevation in the level of one of the analyzed proteins.

Positive case

GENOME & PROTEINS

CancerSEEK

1º SCENARIO

Cohen et al., Science 2018

Estimated cost/ sample: < 500 USD

58%

42%

GENOME & PROTEINS

CancerSEEK

1º SCENARIO

Lung cancer = 38%

“Early” detection of molecular alterations

Is any “druggable” alteration

present?

2º SCENARIO

* Dr. Costa

Blood based approaches for de novo discovery of actionable targets in patients with cancer.

GENOME

Siravegna, G. et al. (2017) Nat. Rev. Clin. Oncol.

2º SCENARIO

To analyze the clinical utility of plasma-based targeted NGS using cell-free circulating tumor DNA (ctDNA) for advanced-stage lung ADC patients, as a complement or alternative to tissue-based molecular profiling

12 Hospitals

3 cohorts (advanced lung ADC)

COHORT 1 N=69 Insufficient tissue (for EGFR, ALK or ROS1 analysis)

NGS

• SNVs= in 73 genes • Gene Copy Nr: 18 genes

Fusions/rearrangements: 6 genes

• Indels: 23 genes

Gene variant actionability was stratified into four levels according to the OncoKB

criteria (Jordan et al. Cancer Discov

2017)

•Patients with > 2 level 1-4 oncogenic drivers were grouped with the highest-level actionable driver.

This panel was designed to report on gene alterations with current clinical utility

Garrido P et al, WCLC 2017

2º SCENARIO

• Patients included : N= 156

Characteristics Global Cohort 1

Total 118 69 (58.5%)

Gender - Female - Male

66 (56%)

52 (44%)

36 33

Smoking history - Never smoker - Former smoker - Current smoker

50 (42%)

46 (39%)

22 (19%)

17 33 19

Performance status - 0 - 1 - 2 - 3

47 (40%)

58 (49%)

12 (10%)

1 (1%)

25 37 6 1

Stage - IIIB - IV M1a - IV M1b

1 (1%)

42 (36%)

75 (63%)

1 (1.5%)

27 (39,5%)

41 (59%)

Nº metastatic organs - 3 - > 3

101(86%)

18 (14%)

59 10

Nº of prior lines of therapy - 0 - 1 - 2 - 3

39 (33%)

47 (40%)

20 (17%)

12 (17%)

38 (55.5%)

21 (30%)

9 (13%)

1 (1.5%) Garrido et al, WCLC 2017

Level alteration Global Cohort 1

Level 1 17 (14 %) 6 (9 %)

Level 2 -2A -2B

5 (4 %)

1 (< 1 %)

1 (1 %)

0

Level 3 10 (8 %) 9 (13 %)

Level 4 24 (20 %) 21 (30 %)

N of patients with potentially actionable alterations

57 (48 %)

37 (53 %)

Total of patients 118 69

2º SCENARIO

Early detection of resistance

mechanisms

Monitoring: Is it possible to early detect resistance mechanism ?

3º SCENARIO

Blood based approaches for dynamic monitoring of targets -> requieres a priori knowledge of resistance mechanisms.

GENOME

Siravegna, G. et al. (2017) Nat. Rev. Clin. Oncol.

3º SCENARIO

GENOME

EGFR mut (+)

Modified from Mok, IASLC 2017

3º SCENARIO

Thress, ASCO 2017

6 weeks

3º SCENARIO

EGFR mut (+): monitoring treatment

Oxnard et al, J Clin Oncol 2016

NEW PARADIGM: Data support that plasma genotyping as a screening test for T790M prior to performing an EGFR resistance biopsy

AURA 1

3º SCENARIO

EGFR mut (+): early detection of resistance

Beaming Del.747_750A

qPCR Del.747_750A

0

2

4

6

8

10

1-4

-15

1-6

-15

1-8

-15

1-1

0-15

1-1

2-1

5

1-2

-16

1-4

-16

1-6

-16

1-8

-16

1-1

0-1

6

1-1

2-1

6

1-2

-17

1-4

-17

1-6

-17

1-8

-17

Beaming Del.747_750A Beaming T790M qPCR Del.747_750A qPCR T790M

Mu

tan

t Fr

acti

on

%

mu

tan

t al

lele

CASE 1: EGFR mut +

3rd generation EGFR-TKI 1st generation EGFR-TKI

20 wk

3º SCENARIO

EGFR mut (+): “early” detection of resistance … but using sensitive methods

Initial biopsy insufficient, unavailable, or undergenotyped

Diagnosis

Molecular alteration detected

Follow up

If…

Molecular alteration detected

Progression

Targeted therapy 1 Targeted therapy 2

1st option 2nd option

If negative

Jantus-Lewintre, 2018 quantification

quantification

Advanced stages

Early stages Screening (high risk polulation)

Complementary to other biomarkers. Better results in combined approaches

NGS: Improving results and lower costs -> in a near future a complementary and/or alternative ¿? to tissue biopsies

1st scenario 2nd scenario

3rd scenario

Finally ….