# 3MO - Comprehensive biomarkers (BMs) analysis to predict efficacy of PD1/L1 immune checkpoint inhibitors (ICIs) in combination with chemotherapy: a subgroup analysis of the Precision Immuno-Oncology for advanced Non-Small Cell Lung CancER (PIONeeR) trial

Fabrice Barlesi, Laurent Greillier, Florence Monville, C Audigier-Valette, S. Martinez, N. Cloarec, Sylvie van Hulst, L. Odier, Frédéric Vely, L. Juquel, et al.

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Fabrice Barlesi, Laurent Greillier, Florence Monville, C Audigier-Valette, S. Martinez, et al. 3MO - Comprehensive biomarkers (BMs) analysis to predict efficacy of PD1/L1 immune checkpoint inhibitors (ICIs) in combination with chemotherapy: a subgroup analysis of the Precision Immuno-Oncology for advanced Non-Small Cell Lung CancER (PIONeeR) trial. 2022 ESMO Immuno-Oncology Congress, Dec 2022, Geneva, Switzerland. **hal-03928784**

HAL Id: hal-03928784

https://hal.science/hal-03928784

Submitted on 12 Jan 2023

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# ESMO IMMUNO-ONCOLOGY

## Annual Congress

## COMPREHENSIVE BIOMARKERS ANALYSIS TO PREDICT EFFICACY OF PD1/L1 ICI IN COMBINATION WITH CHEMOTHERAPY

### A subgroup analysis of the Precision Immuno-Oncology for advanced Non-Small Cell Lung Cancer (PIONeeR) trial

F. Barlesi¹,², L. Greillier⁴,⁵, F. Monville⁶, C. Audigier Valette⁷, S. Martinez⁸, N. Cloarec⁹, S. Van Hulst¹⁰, L. Odier¹¹, F. Vely³,⁵, L. Juquel³,⁵, L. Arnaud⁵, S. Bokobza¹², M. Hamimed⁴, M. Karlsen¹³, P.Dufosse¹³, A. Pouchin⁵, L. Ghezali⁶, M. Le Ray⁵, J. Fieschi-Meric⁶, S. Benzekry¹³

1- Gustave Roussy, Villejuif, France 2- Université Paris Saclay, Faculté de Médecine, Kremlin Bicêtre, France 3- Aix Marseille Université, Marseille, France 4- CRCM - Inserm U1068, CNRS UMR7258, Aix Marseille Université, Institut Paoli-Calmettes, Marseille, France 5- Assistance Publique-Hôpitaux de Marseille (APHM), Marseille, France 6- Veracyte SAS, Marseille, France 7- Centre Hospitalier Sainte-Musse, Toulon, France 8- Centre Hospitalier d'Aix-en-Provence, Aix-en-Provence, France 9- Centre Hospitalier Henri Duffaut, Avignon, France 10- Centre Hospitalier de Nîmes, Nîmes, France 11- Hôpital Nord-Ouest, Villefranche-sur-Saône, France 12- Innate Pharma, Marseille, France 13- Inria, Nice - Sophia Antipolis, France

<figure><img src="image_1.png" /></figure>
# DECLARATION OF INTERESTS

Fabrice Barlesi, MD, PhD

**Personal financial interests:**

- None (since August 2021)

**Institutional financial interests:**

- Abbvie, ACEA, Amgen, Astra-Zeneca, Bayer, Bristol-Myers Squibb, Boehringer-Ingelheim, Eisai, Eli Lilly Oncology, F. Hoffmann-La Roche Ltd, Genentech, Ipsen, Ignyta, Innate Pharma, Loxo, Novartis, Medimmune, Merck, MSD, Pierre Fabre, Pfizer, Sanofi-Aventis and Takeda

**Non-financial interests:**

- Principal Investigator for Astra-Zeneca, BMS, Innate Pharma, Merck, Pierre Fabre and F. Hoffmann-La Roche, Ltd, sponsored trials (or ISR)

**No other conflicts of interest**
# THE PIONEER STUDY DESIGN

## Assess, Understand & Overcome ICI resistances in advanced NSCLC

### Baseline, On-treatment & Progression biopsies
Both 2nd and 1st line settings

### A comprehensive biomarkers assessment, thanks to the public/private PIONeeR consortium

<figure><img src="image_2.png" /></figure>

<figure><img src="image_3.png" /></figure>

\*R : RECIST 1.1 evaluation every 6 weeks
# GENERATE A MULTIMODAL PREDICTIVE SIGNATURE

## Aim: predict patients deriving the largest long-lasting PFS benefit

<figure><img src="image_4.png" /></figure>
# PATIENTS CHARACTERISTICS & OUTCOMES

Overall, 350 pts included to date - Focus on the 1st line setting*

To date, 155 pts treated with Chemo/Pembrolizumab

<table><tbody><tr><td rowspan="2">SEX</td><td>M</td><td>101 (65%)</td></tr><tr><td>F</td><td>54 (35%)</td></tr><tr><td rowspan="2">AGE</td><td>&lt;70</td><td>127 (82%)</td></tr><tr><td>≥70</td><td>28 (18%)</td></tr><tr><td rowspan="3">ECOG</td><td>0</td><td>68 (44%)</td></tr><tr><td>1</td><td>86 (56%)</td></tr><tr><td>Unknown</td><td>1</td></tr><tr><td rowspan="4">TOBACCO HISTORY</td><td>Current</td><td>55 (37%)</td></tr><tr><td>Never</td><td>7 (4.7%)</td></tr><tr><td>Previous</td><td>88 (59%)</td></tr><tr><td>Unknown</td><td>5</td></tr></tbody></table>

<table><tbody><tr><td rowspan="3">PD-L1 EXPRESSION</td><td>≥1%</td><td>43 (35%)</td></tr><tr><td>&lt;1%</td><td>81 (65%)</td></tr><tr><td>Not interpretable</td><td>31</td></tr><tr><td rowspan="3">BIOPSY SITE</td><td>Metastasis</td><td>51 (38%)</td></tr><tr><td>Primitive tumor</td><td>85 (62%)</td></tr><tr><td>Unknown</td><td>19</td></tr><tr><td rowspan="4">HISTOLOGY</td><td>ADK</td><td>98 (84%)</td></tr><tr><td>Others</td><td>4 (3.4%)</td></tr><tr><td>Squamous</td><td>15 (13%)</td></tr><tr><td>Unknown</td><td>38</td></tr><tr><td rowspan="3">TREATMENT</td><td>anti-PD1</td><td>6 (3.9%)</td></tr><tr><td>anti-PDL1</td><td>0 (0%)</td></tr><tr><td>PEMBRO+CHEMO</td><td>149 (96%)</td></tr><tr><td rowspan="5">RECIST</td><td>CR</td><td>8 (7.1%)</td></tr><tr><td>PD</td><td>4 (3.5%)</td></tr><tr><td>PR</td><td>60 (53%)</td></tr><tr><td>SD</td><td>41 (36%)</td></tr><tr><td>Unknown</td><td>42</td></tr></tbody></table>

PFS outcomes in line with reported results

<figure><img src="image_5.png" /></figure>
# RESULTS: STANDARD ANALYSIS

## Biomarkers associated with PFS (1st line setting only)

<table><caption>Global Table (Univariate/Multivariate Analyses)</caption><thead><tr><th rowspan="2">Variable</th><th colspan="2">UV</th><th colspan="2">MV</th></tr><tr><th>HR</th><th>p</th><th>HR</th><th>p</th></tr></thead><tbody><tr><td>Albumin</td><td>0.71 (0.55 - 0.92)</td><td>**</td><td>0.47 (0.31 - 0.7)</td><td>***</td></tr><tr><td>Alkaline phosphatase</td><td>1.5 (1.3 - 1.8)</td><td>****</td><td>1.4 (1.2 - 1.7)</td><td>***</td></tr><tr><td>C reactive protein</td><td>1.6 (1.3 - 2.1)</td><td>***</td><td>1.9 (1.3 - 2.7)</td><td>***</td></tr><tr><td>Chlorine</td><td>0.66 (0.51 - 0.85)</td><td>**</td><td>0.6 (0.43 - 0.82)</td><td>**</td></tr><tr><td>Circulating Monocytes</td><td>1.4 (1.1 - 1.7)</td><td>*</td><td>1.6 (1.2 - 2.2)</td><td>**</td></tr><tr><td>VEGFR1</td><td>1.4 (1 - 2.1)</td><td>*</td><td>1.9 (1.2 - 2.8)</td><td>**</td></tr><tr><td>Platelets</td><td>1.3 (1 - 1.6)</td><td>*</td><td>1.5 (1.2 - 2)</td><td>**</td></tr><tr><td>ASAT</td><td>1.3 (1 - 1.6)</td><td>*</td><td>1.7 (1.2 - 2.5)</td><td>**</td></tr><tr><td>PD-L1 ≥ 1%</td><td>2.2 (1.2 - 3.8)</td><td>**</td><td>2.7 (1.3 - 5.7)</td><td>**</td></tr><tr><td>Prothrombin rate</td><td>0.65 (0.49 - 0.87)</td><td>**</td><td>0.55 (0.35 - 0.87)</td><td>*</td></tr><tr><td>Total bilirubin</td><td>1.5 (1.2 - 1.9)</td><td>***</td><td>1.6 (1.1 - 2.3)</td><td>*</td></tr><tr><td>Circulating Neutrophils</td><td>1.3 (1 - 1.6)</td><td>*</td><td>1.4 (1.1 - 2)</td><td>*</td></tr><tr><td>Vascular Micro-particles</td><td>1.6 (1.1 - 2.2)</td><td>**</td><td>1.7 (1.1 - 2.7)</td><td>*</td></tr><tr><td>Circulating Leukocytes</td><td>1.4 (1.1 - 1.7)</td><td>**</td><td>1.5 (1 - 2.1)</td><td>*</td></tr><tr><td>Stromal Monocytic MDSC</td><td>0.55 (0.31 - 0.98)</td><td>*</td><td>0.27 (0.081 - 0.92)</td><td>*</td></tr></tbody></table>

UV= univariable, MV = multivariable, **** = p<0.0001, *** = p<0.001, ** = p<0.01, * = p<0.05

<figure><img src="image_6.png" /><figcaption>Alkaline phosphatase</figcaption></figure>

<figure><img src="image_7.png" /><figcaption>Vascular Micro-particles</figcaption></figure>

<figure><img src="image_8.png" /><figcaption>Circulating Monocytes</figcaption></figure>

<figure><img src="image_9.png" /></figure>

Vascular activation

Patients sampling

Routine Blood Tests

Blood soluble factors

Tumor multiplex IHC

<figure><img src="image_10.png" /></figure>

Tumor NGS
# RESULTS: MACHINE LEARNING

## Biomarkers associated with PFS (1st line setting only)

### A 15-biomarkers signature

<figure><img src="image_11.png" /></figure>

### Training set (n=116, 75%), Testing set (n=39, 25%)

<figure><img src="image_12.png" /></figure>

### Prediction of the 1-year PFS with 83% sensitivity

<figure><img src="image_13.png" /></figure>

Blood
soluble
factors

Tumor
multiplex
IHC

<figure><img src="image_14.png" /></figure>

Vascular
activation

Patients
sampling

Tumor
NGS

Circulating
Blood
cells

Routine
Blood
Tests
# CONCLUSIONS

A multimodal signature predicts the 1st line chemo/ICI benefit in advanced NSCLC pts

* Our 15-biomarkers signature includes clinical, biological, tissue and circulating biomarkers

* Our predictive algorithm achieves good c-index and AUC in both cross-validation and testing set cohorts

* Variability of the cross-validation results is due to multiple samples still remaining to be processed; the completion of the study is expected in 2023

* The predictive model will be dissected at the pathophysiological level and an external validation will be performed on other cohorts
# ACKNOWLEDGEMENTS

## Patients & Families

## Investigators and Study teams

### Marseille (& area)

* APHM Mult. Oncology & Therap Innov. Dep. : Pr L. Greillier, Dr P Tomasini

* St Joseph Private Hospital : Dr. C. Foa

* Europ. Hospital : Dr. J. Le Treut

* Ste Musse CHI, Toulon : Dr. C. Audigier-Valette

* Maymard Private Hospital, Bastia, Corsica : Dr. A. Frikha

* Bastia Hospital : Dr. P. Bory

* Aix-Pertuis Hospital : Dr S. Martinez

* OncoGard : Dr. A. Serre

* Nîmes Hospital : Dr. S. Van Hulst

* Avignon Hospital : Dr. N. Cloarec

### Lyon (& area)

* Léon Bérard Center Medical Oncology Department : Dr. M. Pérol

* Villefranche Hospital : Drs. L. Falchero, L. Odier

* Annecy Hospital : Dr. S. Hominal

### Toulouse (& area)

* Toulouse CHU Thoracic Oncology Department : Pr. J. Mazières

* Cahors Hospital : Dr. P. Barre

* Montauban Hospital : Dr. S. Zahi

* CHIVA center : Drs. F. Romagné, L. Lebas

## Aix-Marseille Université

* M. Roumieux, Pr. J. Ciccolini, M. Hamimed

## Assistance Publique Hôpitaux de Marseille (trials sponsor)

* Health & Research Dep. : A. Giuliani

* Oncology Phase I Unit CLIP² labeled (CEPCM) : M. Le Ray, Dr. A. Pelletier

* Pathology Dep. : Drs. JP. Dales, L. Juquel & team

* ImmunoProfiling Platform : Dr. F. Vély, A. Pouchin

* VasculoMonitoring Platform : Pr. F. Sabatier, L. Arnaud

* Data Management : R. Malkoun

## Veracyte

* J. Fieschi, F. Monville, L. Ghezali & team

## Innate Pharma

* E. Vivier, S. Bokobza, C. Laporte

## Inserm - Inria (COMPO Team)

* Biostatistics - Machine Learning : S. Benzekry, M. Karlsen, P. Dufosse & team

## Institut Paoli Calmettes - CRCM & ImCheck Therapeutics

* D. Olive & teams

## Léon Bérard Center

* Methodologists: Dr. D. Pérol, S. Chabaud, C. Cropet
# ESMO IMMUNO-ONCOLOGY

## Annual Congress

European Society for Medical Oncology (ESMO)

Via Ginevra 4, CH-6900 Lugano

T. +41 (0)91 973 19 00

esmo@esmo.org

esmo.org

<figure><img src="image_15.png" /></figure>