Spatiotemporal lineage tracing reveals the dynamic spatial architecture of tumor growth and metastasis.

Tumor progression is driven by dynamic interactions between cancer cells and their surrounding microenvironment. Investigating the spatiotemporal evolution of tumors can provide crucial insights into how intrinsic changes within cancer cells and extrinsic alterations in the microenvironment cooperate to drive different stages of tumor progression. Here, we integrate high-resolution spatial transcriptomics and evolving lineage tracing technologies to elucidate how tumor expansion, plasticity, and metastasis co-evolve with microenvironmental remodeling in a -driven mouse model of lung adenocarcinoma.

Phosphate dysregulation via the XPR1-KIDINS220 protein complex is a therapeutic vulnerability in ovarian cancer.

Despite advances in precision medicine, the clinical prospects for patients with ovarian and uterine cancers have not substantially improved. Here, we analyzed genome-scale CRISPR-Cas9 loss-of-function screens across 851 human cancer cell lines and found that frequent overexpression of SLC34A2-encoding a phosphate importer-is correlated with sensitivity to loss of the phosphate exporter XPR1, both in vitro and in vivo. In patient-derived tumor samples, we observed frequent PAX8-dependent overexpression of SLC34A2, XPR1 copy number amplifications and XPR1 messenger RNA overexpression.

Multiplexed single-cell transcriptional response profiling to define cancer vulnerabilities and therapeutic mechanism of action.

Assays to study cancer cell responses to pharmacologic or genetic perturbations are typically restricted to using simple phenotypic readouts such as proliferation rate. Information-rich assays, such as gene-expression profiling, have generally not permitted efficient profiling of a given perturbation across multiple cellular contexts. Here, we develop MIX-Seq, a method for multiplexed transcriptional profiling of post-perturbation responses across a mixture of samples with single-cell resolution, using SNP-based computational demultiplexing of single-cell RNA-sequencing data.

Inferring Tunicate Relationships and the Evolution of the Tunicate Hox Cluster with the Genome of Corella inflata.

Tunicates, the closest living relatives of vertebrates, have served as a foundational model of early embryonic development for decades. Comparative studies of tunicate phylogeny and genome evolution provide a critical framework for analyzing chordate diversification and the emergence of vertebrates. Toward this goal, we sequenced the genome of Corella inflata (Ascidiacea, Phlebobranchia), so named for the capacity to brood self-fertilized embryos in a modified, "inflated" atrial chamber.