Understanding the diverse cell states and molecular composition within the tumor
microenvironment (TME) is crucial for improving risk stratification and predicting therapy
responses. Given the variable response rates to current immuno-oncology treatments, there is
a growing need to deeply profile TME cells, focusing not only on immune cells but also on
stromal components like cancer-associated fibroblasts.
While single-cell RNA sequencing has revolutionized our understanding of the cellular and
molecular landscape of cancers, its limited spatial context and the small number of tumor
samples analyzed often constrain the conclusions about clinical relevance. In contrast,
multiplex immunofluorescence (mIF) imaging offers high-throughput, single-cell analysis
within the spatial context of tissues, enabling the correlation of cellular phenotypes with
clinical outcomes in large patient cohorts with long-term treatment and follow-up data.
This presentation will cover the principles of antibody-based multiplex imaging for detecting
cell types and phenotypes in formalin-fixed, paraffin-embedded (FFPE) sections (Pellinen et
al., 2025) . I will explore both the opportunities and challenges of applying
immunofluorescence and digital image analysis in translational cancer research.
I will discuss various approaches to digital image analysis, from straightforward cell
classification using dichotomized marker thresholds to more advanced data-driven methods
(Atarsaikhan et al., 2025, Pellinen et al., 2024) . Preliminary findings from our ongoing large-
scale pan-cancer multiplex profiling study, which includes 50,000 patient samples stained
with 33 antibodies, will be highlighted (Osterlund et al., 2025, Pellinen et al., 2024) .
References
ATARSAIKHAN, G., MOGOLLON, I., VÄLIMÄKI, K., ICAN, MIRTTI, T., PELLINEN, T. &
PAAVOLAINEN, L. 2025. Self-supervised learning enables unbiased patient characterization from
multiplexed cancer tissue microscopy images. bioRxiv, 2025.03. 05.640729.
OSTERLUND, P., BERNABE, A. M., MÄKINEN, M., SUNDSTRÖM, J., NIEMINEN, L., VÄYRYNEN, J.,
KÄRJÄ, V., BÖHM, J., AHTIAINEN, M.,…, & PELLINEN T. 2025. 30P T cell cancer cell interaction
in prediction of response to EGFR-, VEGF-inhibitors or no biologics in first-line treatment of
metastatic colorectal cancer (mCRC) patients. Annals of Oncology, 36, S17-S18.
PELLINEN, T., LINNAVIRTA, N., SCHOONENBERG, A. & VÄLIMÄKI, K. 2025. FIMM Digital
Microscopy and Molecular Pathology Core Unit.
https://dx.doi.org/10.17504/protocols.io.rm7vz6775gx1/v1
PELLINEN, T., LUOMALA, L., MATTILA, K. E., HEMMES, A., VÄLIMÄKI, K., BRÜCK, O.,
PAAVOLAINEN, L., KANKKUNEN, E., NISÉN, H.,…, & MIRTTI, T. 2024. Fibroblast activation
protein defines an aggressive, immunosuppressive EMT-associated tumor subtype in highly inflamed
localized clear cell renal cell carcinoma. bioRxiv, 2024.10. 27.620479.
21/11/2025 Aula Tecce (CU026) 12:00, Dr. Teijo Pellinen, Institute for Molecular Medicine FIMM, University of Helsinki (Finland)