Assessment of Immunological Features in Muscle-Invasive Bladder Cancer Prognosis Using Ensemble Learning.

The clinical staging and prognosis of muscle-invasive bladder cancer (MIBC) routinely includes the assessment of patient tissue samples by a pathologist. Recent studies corroborate the importance of image analysis in identifying and quantifying immunological markers from tissue samples that can provide further insight into patient prognosis. In this paper, we apply multiplex immunofluorescence to MIBC tissue sections to capture whole-slide images and quantify potential prognostic markers related to lymphocytes, macrophages, tumour buds, and PD-L1.

Spatial immune profiling of the colorectal tumor microenvironment predicts good outcome in stage II patients.

Cellular subpopulations within the colorectal tumor microenvironment (TME) include CD3 and CD8 lymphocytes, CD68 and CD163 macrophages, and tumor buds (TBs), all of which have known prognostic significance in stage II colorectal cancer. However, the prognostic relevance of their spatial interactions remains unknown. Here, by applying automated image analysis and machine learning approaches, we evaluate the prognostic significance of these cellular subpopulations and their spatial interactions.

Automated tumour budding quantification by machine learning augments TNM staging in muscle-invasive bladder cancer prognosis.

Tumour budding has been described as an independent prognostic feature in several tumour types. We report for the first time the relationship between tumour budding and survival evaluated in patients with muscle invasive bladder cancer. A machine learning-based methodology was applied to accurately quantify tumour buds across immunofluorescence labelled whole slide images from 100 muscle invasive bladder cancer patients.

Automated Analysis of Lymphocytic Infiltration, Tumor Budding, and Their Spatial Relationship Improves Prognostic Accuracy in Colorectal Cancer.

Both immune profiling and tumor budding significantly correlate with colorectal cancer patient outcome but are traditionally reported independently. This study evaluated the association and interaction between lymphocytic infiltration and tumor budding, coregistered on a single slide, in order to determine a more precise prognostic algorithm for patients with stage II colorectal cancer. Multiplexed immunofluorescence and automated image analysis were used for the quantification of CD3CD8 T cells, and tumor buds (TBs), across whole slide images of three independent cohorts (training cohort: = 114, validation cohort 1: = 56, validation cohort 2: = 62).