Multiplexed immunofluorescence bioimaging of single-cells and their spatial organization in tissue holds great promise to the development of future precision diagnostics and therapeutics. Current multiplexing pipelines typically involve multiple rounds of immunofluorescence staining across multiple tissue slides. This introduces experimental batch effects that can hide underlying biological signal. It is important to have robust algorithms that can correct for the batch effects while not introducing biases into the data. Performance of data normalization methods can vary among different assay pipelines. To evaluate differences, it is critical to have a ground truth dataset that is representative of the assay. A new immunoFLuorescence Image NOrmalization method is presented and evaluated against alternative methods and workflows. Multiround immunofluorescence staining of the same tissue with the nuclear dye DAPI was used to represent virtual slides and a ground truth. DAPI was restained on a given tissue slide producing multiple images of the same underlying structure but undergoing multiple representative tissue handling steps. This ground truth dataset was used to evaluate and compare multiple normalization methods including median, quantile, smooth quantile, median ratio normalization and trimmed mean of the M-values. These methods were applied in both an unbiased grid object and segmented cell object workflow to 24 multiplexed biomarkers. An upper quartile normalization of grid objects in log space was found to obtain almost equivalent performance to directly normalizing segmented cell objects by the middle quantile. The developed grid-based technique was then applied with on-slide controls for evaluation. Using five or fewer controls per slide can introduce biases into the data. Ten or more on-slide controls were able to robustly correct for batch effects. The data underlying this article along with the FLINO R-scripts used to perform the evaluation of image normalizations methods and workflows can be downloaded from https://github.com/GE-Bio/FLINO. Supplementary data are available at Bioinformatics online.
Entosis is a form of nonphagocytic cell-in-cell (CIC) interaction where a living cell enters into another. Tumors show evidence of entosis; however, factors controlling entosis remain to be elucidated. Here, we find that besides inducing apoptosis, TRAIL signaling is a potent activator of entosis in colon cancer cells. Initiation of both apoptosis and entosis requires TRAIL receptors DR4 and DR5; however, induction of apoptosis and entosis diverges at caspase-8 as its structural presence is sufficient for induction of entosis but not apoptosis. Although apoptosis and entosis are morphologically and biochemically distinct, knockout of Bax and Bak, or inhibition of caspases, also inhibits entotic cell death and promotes survival and release of inner cells. Analysis of colorectal cancer tumors reveals a significant association between TRAIL signaling and CIC structures. Finally, the presence of CIC structures in the invasive front regions of colorectal tumors shows a strong correlation with adverse patient prognosis.