Decoding how tissue properties emerge across multiple spatial and temporal scales from the integration of local signals is a grand challenge in quantitative biology. For example, the collective behavior of epithelial cells is critical for shaping developing embryos. Understanding how epithelial cells interpret a diverse range of local signals to coordinate tissue-level processes requires a systems-level understanding of development. Integration of multiple signaling pathways that specify cell signaling information requires second messengers such as calcium ions. Increasingly, specific roles have been uncovered for calcium signaling throughout development. Calcium signaling regulates many processes including division, migration, death, and differentiation. However, the pleiotropic and ubiquitous nature of calcium signaling implies that many additional functions remain to be discovered. Here we review a selection of recent studies to highlight important insights into how multiple signals are transduced by calcium transients in developing epithelial tissues. Quantitative imaging and computational modeling have provided important insights into how calcium signaling integration occurs. Reverse-engineering the conserved features of signal integration mediated by calcium signaling will enable novel approaches in regenerative medicine and synthetic control of morphogenesis.

Embryogenesis is an extraordinarily robust process, exhibiting the ability to control tissue size and repair patterning defects in the face of environmental and genetic perturbations. The size and shape of a developing tissue is a function of the number and size of its constituent cells as well as their geometric packing. How these cellular properties are coordinated at the tissue level to ensure developmental robustness remains a mystery; understanding this process requires studying multiple concurrent processes that make up morphogenesis, including the spatial patterning of cell fates and apoptosis, as well as cell intercalations. In this work, we develop a computational model that aims to understand aspects of the robust pattern repair mechanisms of the Drosophila embryonic epidermal tissues. Size control in this system has previously been shown to rely on the regulation of apoptosis rather than proliferation; however, to date little work has been done to understand the role of cellular mechanics in this process. We employ a vertex model of an embryonic segment to test hypotheses about the emergence of this size control. Comparing the model to previously published data across wild type and genetic perturbations, we show that passive mechanical forces suffice to explain the observed size control in the posterior (P) compartment of a segment. However, observed asymmetries in cell death frequencies across the segment are demonstrated to require patterning of cellular properties in the model. Finally, we show that distinct forms of mechanical regulation in the model may be distinguished by differences in cell shapes in the P compartment, as quantified through experimentally accessible summary statistics, as well as by the tissue recoil after laser ablation experiments. Developing embryos are able to grow organs of the correct size even in the face of significant external perturbations. Such robust size control is achieved via tissue-level coordination of cell growth, proliferation, death and rearrangement, through mechanisms that are not well understood. Here, we employ computational modelling to test hypotheses of size control in the developing fruit fly. Segments in the surface tissues of the fruit fly embryo have been shown to achieve the same size even if the number of cells in each segment is perturbed genetically. We show that simple mechanical interactions between the cells of this tissue can recapitulate previously gathered data on tissue sizes and cell numbers. However, this simple model does not capture the experimentally observed spatial variation in cell death rates in this tissue, which may be explained through several adaptations to the model. These distinct adaptations may be distinguished through summary statistics of the tissue behaviour, such as statistics of cell shapes or tissue recoil after cutting. This work demonstrates how computational modelling can help investigate the complex mechanical interactions underlying tissue size and shape, which are important for understanding the underlying causes of birth defects and diseases driven by uncontrolled growth.

Recurrent/metastatic (R/M) head and neck squamous cell carcinoma (HNSCC) patients overall have a poor prognosis. However, human papillomavirus (HPV)-associated R/M oropharyngeal squamous cell carcinoma (OPSCC) is associated with a better prognosis compared to HPV−negative disease. Immune checkpoint blockade (ICB) is the standard of care for R/M HNSCC. However, whether HPV and its surrogate marker, p16, portend an improved response to ICB remains controversial. We queried the Caris Life Sciences CODEai database for p16+ and p16− HNSCC patients using p16 as a surrogate for HPV. A total of 2905 HNSCC (OPSCC, n = 948) cases were identified. Of those tested for both HPV directly and p16, 32% (251/791) were p16+ and 28% (91/326) were HPV+. The most common mutation in the OPSCC cohort was TP53 (33%), followed by PIK3CA (17%) and KMT2D (10.6%). TP53 mutations were more common in p16− (49%) versus the p16+ group (10%, p < 0.0005). Real-world overall survival (rwOS) was longer in p16+ compared to p16− OPSCC patients, 33.3 vs. 19.1 months (HR = 0.597, p = 0.001), as well as non-oropharyngeal (non-OP) HNSCC patients (34 vs. 17 months, HR 0.551, p = 0.0001). There was no difference in the time on treatment (TOT) (4.2 vs. 2.8 months, HR 0.796, p = 0.221) in ICB-treated p16+ vs. p16− OPSCC groups. However, p16+ non-OP HNSCC patients treated with ICB had higher TOT compared to the p16− group (4.3 vs. 3.3 months, HR 0.632, p = 0.016), suggesting that p16 may be used as a prognostic biomarker in non-OP HNSCC, and further investigation through prospective clinical trials is warranted.

Wing disc pouches of fruit flies are a powerful genetic model for studying physiological intercellular calcium (Ca ²⁺ ) signals for dynamic analysis of cell signaling in organ development and disease studies. A key to analyzing spatial-temporal patterns of Ca ²⁺ signal waves is to accurately align the pouches across image sequences. However, pouches in different image frames may exhibit extensive intensity oscillations due to Ca ²⁺ signaling dynamics, and commonly used multimodal non-rigid registration methods may fail to achieve satisfactory results. In this paper, we develop a new two-phase non-rigid registration approach to register pouches in image sequences. First, we conduct segmentation of the region of interest. (i.e., pouches) using a deep neural network model. Second, we use a B-spline based registration to obtain an optimal transformation and align pouches across the image sequences. Evaluated using both synthetic data and real pouch data, our method considerably outperforms the state-of-the-art non-rigid registration methods.