Biology subjects

Greenwald, A. C.

Publications and source records attributed to Greenwald, A. C..

4 recordsLinked to original sources

bioRxiv2026

Spatial analysis reveals the evolving organization of low-grade and high-grade IDH-mutant glioma

Adult diffuse gliomas are comprised of malignant cell states interwoven with the non-malignant brain microenvironment. Here we combine spatial transcriptomics and spatial proteomics of IDH-mutant gliomas to define organizational principles across histological grades. In low-grade tumors, spatial organization arises from underlying nonmalignant brain structures. For example, we classify low-grade tumor regions as embedded into white matter and identify a sharp white-grey matter junction that restricts cortical invasion and is associated with marked changes in tumor composition and cellular phenotypes. This junction is preferentially traversed by oligodendrocyte progenitor (OPC)-like malignant cells, which may drive tumor expansion. In contrast, intermediate-grade tumors are largely disorganized, with few recurring pairwise interactions between cancer cell states and TME cell types. In high-grade tumors, hypoxia/necrosis-associated global structure begins to emerge, reminiscent of IDH-wildtype glioblastoma. Together, these findings reveal two independent axes of glioma spatial organization--from brain anatomy-driven organization in low-grade tumors to hypoxia-associated structure in high-grade tumors--and establishes a framework that links tumor grade to recurrent spatial associations between cell states and cell types.

cancer biology↗

bioRxiv2023

snPATHO-seq: unlocking the pathology archives

Formalin-fixed paraffin-embedded (FFPE) samples are valuable but underutilized in single-cell omics research due to their low DNA and RNA quality. In this study, leveraging recent single-cell genomic technology advances, we introduce a versatile method to derive high-quality single-nucleus transcriptomic data from FFPE samples.

molecular biology↗

bioRxiv2023

Integrative spatial analysis reveals a multi-layered organization of glioblastoma

Glioma contains malignant cells in diverse states. Hypoxic regions are associated with a unique histology of pseudopalisading cells, while other regions appear to have limited histological organization, reflecting the diffuse nature of glioma cells. Here, we combine spatial transcriptomics with spatial proteomics and novel computational approaches to define glioma cellular states at high granularity and uncover their organization. We find three prominent modes of cellular organization. First, cells in any given state tend to be spatially clustered, such that tumors are composed of small local environments that are each typically enriched with one major cellular state. Second, specific pairs of states preferentially reside in proximity across multiple scales. Despite the unique composition of each tumor, this pairing of states remains largely consistent across tumors. Third, the pairwise interactions that we detect collectively define a global architecture composed of five layers. Hypoxia appears to drive this 5-layered organization, as it is both associated with unique states of surrounding cells and with a long-range organization that extends from the hypoxic core to the infiltrative edge of the tumor. Accordingly, tumor regions distant from any hypoxic foci and tumors that lack hypoxia such as IDH-mutant glioma are less organized. In summary, we provide a conceptual framework for the organization of gliomas at the resolution of cellular states and highlight the role of hypoxia as a long-range tissue organizer.

cancer biology↗

bioRxiv2019

Pan-cancer single cell RNA-seq uncovers recurring programs of cellular heterogeneity

Cultured cell lines are the workhorse of cancer research, but it is unclear to what extent they recapitulate the cellular heterogeneity observed among malignant cells in tumors, given the absence of a native tumor microenvironment. Here, we used multiplexed single cell RNA-seq to profile ~200 cancer cell lines. We uncovered expression programs that are recurrently heterogeneous within many cancer cell lines and are largely independent of observed genetic diversity. These programs of heterogeneity are associated with diverse biological processes, including cell cycle, senescence, stress and interferon responses, epithelial-to-mesenchymal transition, and protein maturation and degradation. Notably, some of these recurrent programs recapitulate those seen in human tumors, suggesting a prominent role of intrinsic plasticity in generating intra-tumoral heterogeneity. Moreover, the data allowed us to prioritize specific cell lines as model systems of cellular plasticity. We used two such models to demonstrate the dynamics, regulation and drug sensitivities associated with a cancer senescence program also observed in human tumors. Our work describes the landscape of cellular heterogeneity in diverse cancer cell lines, and identifies recurrent patterns of expression heterogeneity that are shared between tumors and specific cell lines and can thus be further explored in follow up studies.

cancer biology↗