Characterization of tumor budding and the tumor microenvironment in colorectal cancer using hyperplex immunofluorescence

Aim

Current colon cancer classification, prognostication, and therapy decisions are based mainly on cancer staging. However, additional biomarkers are needed to improve patient stratification and complement treatment decision-making strategies. Tumor budding is recognized as an independent prognostic factor in a variety of solid cancers. Tumor buds intratumorally (TBs) are isolated single tumor cells or groups of up to four tumor cells, located both peri- and intratumorally. A higher tumor bud count correlates with poor prognosis in colorectal cancer (CRC), and it is hypothesized that a subset of TBs represents an Epithelial-Mesenchymal Transition (EMT) state. To explore this hypothesis further, we developed a sequential immunofluorescence (seqIF) marker panel to characterize TBs and the tumor microenvironment spatially. The tumor microenvironment (TME) is a complex network that is composed of immune cells, fibroblasts, blood vessels, and an extracellular matrix. The interaction of tumor buds with other components of TME is yet to be explored.

Adapted from Lugli, A. et al. Nat Rev Clin Oncol, 2021.

Methods

Human CRC sections from different cohorts underwent initial pre-processing on PT Module™ (Thermo Fisher) followed by automated cycles of seqIF™ and imaging performed on COMET™ (Lunaphore Technologies). Hyperplex panels consisting of 26 protein biomarkers were generated using off-the-shelf antibodies and served to characterize the tumor-stroma interactions in a preliminary cohort of samples.

Findings

We built an optimized panel consisting of 26 biomarkers for the characterization of the tumor and the surrounding stroma. In line with the previously described EMT phenotype of TBs, our observations showed loss of EpCAM and E-Cadherin in a group of TBs verifying decreased epithelial phenotype.  The 26-plex panel generated on COMET™ allowed (i) to discriminate TB signatures within the depth of tumor-stroma interactions and (ii) to extract valuable TB features in terms of marker expression. Next, crucial info about TBs phenotypes and their cellular neighborhood will be obtained through an unsupervised analysis approach. This will finally serve to better identify novel immunograms of these cellular entities, thus defining their therapeutic potential for personalized medicine.

Members

Mauro Gwerder

Inti Zlobec

Cristina Graham Martínez