Cells within a tumor microenvironment (TME) dynamically communicate and influence each other's cellular states through an intercellular communication network (ICN). In cancers, intercellular communications underlie immune evasion mechanisms of individual tumors. We developed an individualized causal analysis framework for discovering tumor specific ICNs. Using head and neck squamous cell carcinoma (HNSCC) tumors as a testbed, we first mined single-cell RNA-sequencing data to discover gene expression modules (GEMs) that reflect the states of transcriptomic processes within tumor and stromal single cells. By deconvoluting bulk transcriptomes of HNSCC tumors profiled by The Cancer Genome Atlas (TCGA), we estimated the activation states of these transcriptomic processes in individual tumors. Finally, we applied individualized causal network learning to discover an ICN within each tumor. Our results show that cellular states of cells in TMEs are coordinated through ICNs that enable multi-way communications among epithelial, fibroblast, endothelial, and immune cells. Further analyses of individual ICNs revealed structural patterns that were shared across subsets of tumors, leading to the discovery of 4 different subtypes of networks that underlie disparate TMEs of HNSCC. Patients with distinct TMEs exhibited significantly different clinical outcomes. Our results show that the capability of estimating individual ICNs reveals heterogeneity of ICNs and sheds light on the importance of intercellular communication in impacting disease development and progression.

In this paper, we describe the process of making a robot useful as a guide robot for people who are blind or visually impaired. For this group, the interactive audio feature of a robot assumes a very high level of importance. We have introduced some features that will help to make the robot sound natural and be more comfortable. We first addressed the question of the speaker placement to help the user determine the size and distance of the robot. After the initial meeting, user data will be retained by the robot so that their communication evolves with every interaction. The robot will also ask the users if they need to take a rest after a specified interval depending upon the user's age and the distance they need to cover. The next time they visit, all this information will be used to make the interaction more natural and customized for each individual user.