Fig. 1. Immune cell infiltration of lung carcinoma-in-situ lesions. (a-b) Immunohistochemistry images of (a) progressive CIS lesion and (b) regressive CIS lesion with CD4+ cells stained in brown, CD8+ cells in red and FOXP3+ in blue. Immune cells are separately quantified within the CIS lesion and in the surrounding stroma. c) Combined quantitative immunohistochemistry data of CD4, CD8 and FOXP3 staining (n=44; 28 progressive, 16 regressive) with total lymphocyte quantification from H&E images (n=116; 69 progressive, 47 regressive) shown. We observe increased lymphocytes (p=0.023) and CD8+ cells (p=0.037) per unit area of epithelium within regressive CIS lesions compared to progressive. Stromal regions adjacent to CIS lesions showed no significant differences in immune cells between progressive and regressive lesions. p-values are calculated using linear mixed effects models to account for samples from the same patient; *p<0.05. 2 | bioRχiv Pennycuick et al. | Immune surveillance in clinical regression of pre-invasive squamous cell lung cancer .

Spatial molecular technologies have revolutionised the study of disease microenvironments by providing spatial context to tissue heterogeneity. Recent spatial technologies are increasing the throughput and spatial resolution of measurements, resulting in larger datasets. The added spatial dimension and volume of measurements poses an analytics challenge that has, in the short-term, been addressed by adopting methods designed for the analysis of single-cell RNA-seq data. Though these methods work well in some cases, not all necessarily translate appropriately to spatial technologies. A common assumption is that total sequencing depth, also known as library size, represents technical variation in single-cell RNA-seq technologies, and this is often normalised out during analysis. Through analysis of several different spatial datasets, we noted that this assumption does not necessarily hold in spatial molecular data. To formally assess this, we explore the relationship between library size and independently annotated spatial regions, across 23 samples from 4 different spatial technologies with varying throughput and spatial resolution. We found that library size confounded biology across all technologies, regardless of the tissue being investigated. Statistical modelling of binned total transcripts shows that tissue region is strongly associated with library size across all technologies, even after accounting for cell density of the bins. Through a benchmarking experiment, we show that normalising out library size leads to sub-optimal spatial domain identification using common graph-based clustering algorithms. On average, better clustering was achieved when library size effects were not normalised out explicitly, especially with data from the newer sub-cellular localised technologies. Taking these results into consideration, we recommend that spatial data should not be specifically corrected for library size prior to analysis unless strongly motivated. We also emphasise that spatial data are different to single-cell RNA-seq and care should be taken when adopting algorithms designed for single cell data.

ARHGAP19 is a hematopoietic-specific Rho GTPase-activating protein (RhoGAP) that acts through the RhoA/ROCK pathway to critically regulate cell elongation and cytokinesis during lymphocyte mitosis. We report here that, during mitosis progression, ARHGAP19 is sequentially phosphorylated by the RhoA-activated kinases ROCK1 and ROCK2 (hereafter ROCK) on serine residue 422, and by CDK1 on threonine residues 404 and 476. The phosphorylation of ARHGAP19 by ROCK occurs before mitosis onset and generates a binding site for 14-3-3 family proteins. ARHGAP19 is then phosphorylated by CDK1 in prometaphase. The docking of 14-3-3 proteins to phosphorylated S422 protects ARHGAP19 from dephosphorylation of the threonine sites and prevents ARHGAP19 from relocating to the plasma membrane during prophase and metaphase, thus allowing RhoA to become activated. Disruption of these phosphorylation sites results in premature localization of ARHGAP19 at the cell membrane and in its enrichment to the equatorial cortex in anaphase leading to cytokinesis failure and cell multinucleation.