Ludwig Center at Harvard

Baker, A.R., et al. Transcriptome profiling of ADAR1 targets in triple-negative breast cancer cells reveals mechanisms for regulating growth and invasion. Mol Cancer Res (2022).Abstract

ADARs catalyze Adenosine-to-Inosine (A-to-I) editing of double-stranded RNA and regulate global gene expression output through interactions with RNA and other proteins. ADARs play important roles in development and disease, and previous work has shown that ADAR1 is oncogenic in a growing list of cancer types. Here we show that ADAR1 is a critical gene for triple-negative breast cancer cells, as ADAR1 loss results in reduced growth (viability and cell cycle progression), invasion, and mammosphere formation. Whole transcriptome sequencing analyses demonstrate that ADAR1 regulates both coding and non-coding targets by altering gene expression level, A-to-I editing, and splicing. We determine that a recoding edit in filamin B (FLNB chr3:58156064) reduces the tumor suppressive activities of the protein to promote growth and invasion. We also show that several tumor suppressor microRNAs are upregulated upon ADAR1 loss and suppress cell cycle progression and invasion. Implications: This work describes several novel mechanisms of ADAR1-mediated oncogenesis in triple-negative breast cancer, providing support to strategies targeting ADAR1 in this aggressive cancer type that has few treatment options.

Schapiro, D., et al. MITI minimum information guidelines for highly multiplexed tissue images. Nat Methods 19, 3, 262-267 (2022).

Gaglia, G., et al. Temporal and spatial topography of cell proliferation in cancer. Nat Cell Biol 24, 3, 316-326 (2022).Abstract

Proliferation is a fundamental trait of cancer cells, but its properties and spatial organization in tumours are poorly characterized. Here we use highly multiplexed tissue imaging to perform single-cell quantification of cell cycle regulators and then develop robust, multivariate, proliferation metrics. Across diverse cancers, proliferative architecture is organized at two spatial scales: large domains, and smaller niches enriched for specific immune lineages. Some tumour cells express cell cycle regulators in the (canonical) patterns expected of freely growing cells, a phenomenon we refer to as 'cell cycle coherence'. By contrast, the cell cycles of other tumour cell populations are skewed towards specific phases or exhibit non-canonical (incoherent) marker combinations. Coherence varies across space, with changes in oncogene activity and therapeutic intervention, and is associated with aggressive tumour behaviour. Thus, multivariate measures from high-plex tissue images capture clinically significant features of cancer proliferation, a fundamental step in enabling more precise use of anti-cancer therapies.

Plana, D., Fell, G., Alexander, B.M., Palmer, A.C. & Sorger, P.K. Cancer patient survival can be parametrized to improve trial precision and reveal time-dependent therapeutic effects. Nat Commun 13, 1, 873 (2022).Abstract

Individual participant data (IPD) from oncology clinical trials is invaluable for identifying factors that influence trial success and failure, improving trial design and interpretation, and comparing pre-clinical studies to clinical outcomes. However, the IPD used to generate published survival curves are not generally publicly available. We impute survival IPD from ~500 arms of Phase 3 oncology trials (representing ~220,000 events) and find that they are well fit by a two-parameter Weibull distribution. Use of Weibull functions with overall survival significantly increases the precision of small arms typical of early phase trials: analysis of a 50-patient trial arm using parametric forms is as precise as traditional, non-parametric analysis of a 90-patient arm. We also show that frequent deviations from the Cox proportional hazards assumption, particularly in trials of immune checkpoint inhibitors, arise from time-dependent therapeutic effects. Trial duration therefore has an underappreciated impact on the likelihood of success.

Tsvetkov, P., et al. Copper induces cell death by targeting lipoylated TCA cycle proteins. Science 375, 6586, 1254-1261 (2022).Abstract

Copper is an essential cofactor for all organisms, and yet it becomes toxic if concentrations exceed a threshold maintained by evolutionarily conserved homeostatic mechanisms. How excess copper induces cell death, however, is unknown. Here, we show in human cells that copper-dependent, regulated cell death is distinct from known death mechanisms and is dependent on mitochondrial respiration. We show that copper-dependent death occurs by means of direct binding of copper to lipoylated components of the tricarboxylic acid (TCA) cycle. This results in lipoylated protein aggregation and subsequent iron-sulfur cluster protein loss, which leads to proteotoxic stress and ultimately cell death. These findings may explain the need for ancient copper homeostatic mechanisms.

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