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Poster Display session

350P - Spatial and single-cell transcriptomics to characterize T/B cell immune structures and neighborhood stromal components associated to immunotherapy response in Non-Small Cell Lung Cancer

Date

28 Mar 2025

Session

Poster Display session

Presenters

Nicla Porciello

Citation

Journal of Thoracic Oncology (2025) 20 (3): S208-S232. 10.1016/S1556-0864(25)00632-X

Authors

N. Porciello1, G. Frisullo1, V. Balzano1, G. Campo1, F. Di Modugno1, B. Palermo1, E. Gallo2, F. Goeman1, F. De Nicola2, F.T. Gallina3, L. Landi4, F. Cappuzzo4, P. Visca5, M.M. Rosado1, P. Nisticò1

Author affiliations

  • 1 IRCCS Regina Elena National Cancer Institute, Roma/IT
  • 2 IRCCS Istiuto Nazionale Tumori Regina Elena (IRE), Rome/IT
  • 3 IRCCS Regina Elena National Cancer Institute (IRE), Rome/IT
  • 4 IRCCS Regina Elena National Cancer Institute, Rome/IT
  • 5 Pathology Unit, IRCCS Regina Elena National Cancer Institute, Roma/IT

Resources

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Abstract 350P

Background

The composition and organization of the Tumor Immune Microenvironment (TIME) play a critical role in patient clinical outcomes. The presence of tertiary lymphoid structures (TLS)—ectopic formations where T and B cells interact to generate specific memory and high-affinity effector responses—has emerged as a prognostic and predictive biomarker for response to immune checkpoint therapies (ICT). Concurrently, growing evidence underscores the role of cancer-associated fibroblast (CAF) subtypes in modulating the TIME and shaping anti-tumor immune responses. Our recent findings reveal that the actin regulatory protein hMENA in CAFs influences the expression of the lymphotoxin β receptor (LTβR), promotes the secretion of CXCL13, a chemokine essential for TLS formation and identified a predictive signature associated with ICT response.

Methods

We employed spatial transcriptomics, by both 10X-Visium and GeoMx, along with scRNA-seq to identify the composition of TLS and hMENA-expressing CAFs localization. We collected tumor, adjacent nontumor tissue, and peripheral blood samples from treatment-naive NSCLC patients who received curative surgery at our institution and were ICT-treated at recurrence.

Results

Mapping of public single-cell T and B atlases onto our spatial transcriptomics data allowed us to define TIME characteristics in ICT responder and non-responder patients. We found different composition of TLS between good and poor responder patients. Furthermore, integration of single-cell atlas of lung CAFs with our spatial transcriptomics data highlighted increased immunosuppressive hMENA-over-expressing CAFs inside and outside TLS in poor compared to good ICTresponder patients. We are currently exploring scRNA-seq analysis of circulating lymphocytes from good and poor ICT responder patients to identify peripheral immune-related signatures that parallel TIME subtypes.

Conclusions

We envisage that this pilot study will pave the way for a comprehensive view of the TIME and peripheral immune profiling of NSCLC patients and will contribute to understanding the mechanisms of immune evasion and broaden the ICT response in NSCLC.

Legal entity responsible for the study

The authors.

Funding

AIRC; Ministry of Health.

Disclosure

All authors have declared no conflicts of interest.

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