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Joe Lennerz: Introducing the Tumor-Immune Partitioning and Clustering algorithm

Joe Lennerz/pathologyoutlines.com

Mar 1, 2025, 20:18

Joe Lennerz: Introducing the Tumor-Immune Partitioning and Clustering algorithm

Joe Lennerz, Chief Scientific Officer of BostonGene, shared a post on LinkedIn about a paper he co-authored with colleagues published in PLOS:

“In this study, we introduce a new computational tool called the Tumor-Immune Partitioning and Clustering (TIPC) algorithm.

Unlike traditional methods that simply count immune cells or look at their immediate neighbors, TIPC examines how immune cells are distributed between the tumor and the surrounding supportive tissue (stroma) and whether they form clusters or remain dispersed.

Some key messages

Application in Colorectal Cancer:

TIPC was used on 931 colorectal cancer cases, revealing six distinct tumor subtypes based on the spatial distribution of T lymphocytes. These subtypes included two ‘cold’ types (with fewer or less actively organized immune cells) and four ‘hot’ types.

Importantly, three of the ‘hot’ subtypes were linked to better cancer-specific survival, indicating that ‘how’ immune cells are organized – not just their overall number – can affect patient outcomes.

Insights into Tumor Heterogeneity:

Even when tumors had similar numbers of T cells, the differences in their spatial arrangement led to different prognoses. For example, TIPC could distinguish subtypes within microsatellite instability-high tumors, suggesting that this approach might refine how we classify tumors and predict their behavior.

Broader Applicability:

The algorithm was also applied to other immune cells like eosinophils and neutrophils, and even in a small cohort of hepatocellular carcinomas. In these analyses, TIPC identified specific interactions between different cell types, such as those between CXCL9+ and CXCR3+ or CD8+ cells, which are important for the immune response against tumors.

Validation:

The findings were confirmed using additional datasets, including data from The Cancer Genome Atlas, strengthening the case that spatial patterns in the tumor microenvironment are key to understanding cancer progression and guiding precision immunotherapy.

TIPC provides an approach to capture the tumor immune microenvironment by analyzing not just the quantity but the arrangement of immune cells. This deeper understanding can support tumor classification and hopefully soon improve strategies for personalized cancer treatment.

PMC.”

“Tumor-immune partitioning and clustering algorithm for identifying tumor-immune cell spatial interaction signatures within the tumor microenvironment”

Authors: Mai Chan Lau, Jennifer Borowsky, Juha Väyrynen, Jochen Lennerz, Shuji Ogino, Jonathan Nowak et al.

Joe Lennerz: Introducing the Tumor-Immune Partitioning and Clustering algorithm

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Joe Lennerz: Introducing the Tumor-Immune Partitioning and Clustering algorithm