What is it about?
Invasive lobular carcinoma (ILC) is the second most common type of breast cancer, but it behaves differently from other breast cancers. Current classification systems mainly focus on cancer cells themselves and often miss how tumors are organized within the tissue and how they interact with surrounding cells — the tumor microenvironment. In this study, we analyzed tumors from 43 patients using a technology that shows where genes are active directly inside the tissue. This allowed us to see not only the cancer cells, but also the nearby immune cells, connective tissue, and other components around the tumor. We found that ILC tumors vary greatly from patient to patient and even within the same tumor. By combining gene activity, tissue structure, and spatial organization, we identified four main subtypes of ILC. Each subtype reflects a different tumor “ecosystem”: one rich in normal and stromal cells, one fast-growing, one driven by hormone-related signals, and one linked to metabolism and immune activity. We then tested these subtypes in other large patient datasets and found the same patterns. The subtypes were also linked to patient survival. In particular, the fast-growing subtype had poorer outcomes, while the normal/stroma-rich subtype had better prognosis. Overall, this study shows that looking at how tumors are organized — not just what genes they express — reveals new, clinically relevant subtypes of invasive lobular breast cancer that could help improve risk prediction and treatment decisions.
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Why is it important?
The environment surrounding tumor cells — called the tumor microenvironment — plays an important role in cancer behavior, but it has been little studied in invasive lobular breast cancer (ILC). Using spatial transcriptomics, a method that maps gene activity within tissue, we examined how cancer cells interact with nearby immune cells, connective tissue, and other components. We discovered four distinct microenvironment-based subtypes of ILC, each defined by different biological features, such as hormone signaling, metabolism, and immune cell infiltration. These subtypes were linked to patient prognosis and may point to new treatment opportunities. To ensure the findings were robust, we confirmed them in large independent datasets. By combining tissue imaging, spatial gene data, and computational cell analysis, this work provides a more complete picture of ILC biology and lays the groundwork for more personalized treatment strategies based on the tumor microenvironment.
Perspectives
Working on this publication was especially meaningful because it brought together the areas I am most passionate about. Integrating spatial transcriptomics, image analysis, and clinical data was challenging, but also the most rewarding part of my work, as it allowed us to study this disease in a more comprehensive way. I had the privilege of collaborating with a broad range of professionals — from computational researchers to clinical oncologists — all sharing the same goal of improving patient stratification and identifying new therapeutic opportunities in an understudied breast cancer subtype. The support of patient advocacy organizations further reinforced the purpose of this effort. This experience strengthened my belief that advancing our understanding of complex cancers like ILC requires close collaboration across disciplines.
Matteo Serra
Memorial Sloan-Kettering Cancer Center
Read the Original
This page is a summary of: Spatial transcriptomics reveals tumor microenvironment–driven subtypes of invasive lobular carcinoma, Proceedings of the National Academy of Sciences, February 2026, Proceedings of the National Academy of Sciences,
DOI: 10.1073/pnas.2517567123.
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