1P - Integrated Data Analysis within IMMUcan Identifies Prognostic Features of Early NSCLC

Background

The advent of personalized medicine and ever-increasing numbers of available cancer drugs necessitate better prognostic and predictive biomarkers. In turn, this requires a deeper profiling and understanding of tumors and the tumor microenvironment (TME). To address this challenge the Integrated iMMUnoprofiling of large adaptive CANcer patient cohorts (IMMUcan) consortium collects samples and longitudinal clinical data from up to 3000 patients. All samples undergo bulk RNA-seq and whole exome sequencing (WES) for molecular profiling, whole slide multiplexed immunofluorescence (mIF) for broad and imaging mass cytometry (IMC) for detailed cellular profiling.

Methods

We analyzed a retrospective sub-cohort of non-small cell lung cancer (NSCLC) consisting of stage I-IIIA resected tumor samples from 192 patients collected between 2012 and 2018 under the EORTC-SPECTA protocol (NCT 02214134). Median follow up was 2.8 years and 42 patients died of the disease. Bulk RNA-seq and WES data were processed using standard tools. An image analysis workflow for mIF and IMC data paired with a tiling approached from ecology and spatial data analysis were used for feature extraction and subsequent multivariate cox proportional hazard modeling.

Results

The TME did not differ across clinical stage, smoking status or driver mutations. The TME of squamous cell carcinoma (LUSC) subtypes was enriched for immune suppressed cell types compared to adenocarcinoma (LUAD) subtypes in mIF and IMC data. Most samples (78%) contained B cell aggregates or tertiary lymphoid structures but their amount, size and location were not prognostic for overall survival (OS). In this cohort, not the density of CD8⁺ T cells but the variability of CD8+ T cell density across tissue sections, next to factors such as CD8⁺ T cell exclusion and broad T cell activation/exhaustion were strong prognostic factors for OS. Finally, we highlight results obtained from multi-modal data integration for the identification of the strongest prognostic features.

Conclusions

Our analyses reveal the potential of multi-modal data analysis and integration, and form the basis for analyses of all molecular and cellular profiling data from IMMUcan patients for biomarker discovery.

Clinical trial identification

NCT 02214134.

Legal entity responsible for the study

EORTC.

Funding

IMI2 JU grant agreement 821558, supported by EU’s Horizon 2020 and EFPIA.

Disclosure

M. Morfouace: Other, Personal, Member, employee: Merck Healthcare. T. Trefzer: Other, Personal, Member, employee: Bayer AG. H.S. Hong: Other, Personal, Member, employee: Merck Healthcare. T. Cufer: Financial Interests, Personal, Invited Speaker: MSD, Pfizer, Roche; Financial Interests, Personal, Advisory Board: Boehringer Ingelheim, Takeda; Financial Interests, Institutional, Local PI: MSD. A.C. Dingemans: Financial Interests, Institutional, Advisory Board: Roche, Sanofi, Amgen, Bayer, Boehringer Ingelheim; Financial Interests, Institutional, Invited Speaker: Takeda, Lilly, Jansen, Pfizer, AstraZeneca; Financial Interests, Institutional, Research Grant: Amgen; Financial Interests, Institutional, Local PI: Lilly, Amgen, Daiichi, JNJ, Mirati; Financial Interests, Institutional, Coordinating PI: Roche; Financial Interests, Institutional, Steering Committee Member: Roche; Non-Financial Interests, Personal, Other, Chair EORTC lung cancer group: EORTC; Non-Financial Interests, Personal, Member: IASCL, ASCO, AACR. B. Besse: Financial Interests, Institutional, Funding: 4D Pharma, AbbVie, Amgen, Aptitude Health, AstraZeneca, BeiGene, Blueprint Medicines, Boehringer Ingelheim, Celgene, Cergentis, Cristal Therapeutics, Daiichi Sankyo, Eli Lilly, GSK, Pfizer, Janssen, Onxeo, OSE Immunotherapeutics, Roche-Genentech, Sanofi, Takeda, Tolero Pharmaceuticals; Financial Interests, Institutional, Research Grant: Genzyme Corporation, Chugai pharmaceutical, Eisai, Inivata, Ipsen, Turning Point Therapeutics. All other authors have declared no conflicts of interest.