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CKLF instigates a “cold” microenvironment to promote MYCN-mediated tumor aggressiveness

https://doi.org/10.1126/sciadv.adh9547

Qin, Xiaodan; Lam, Andrew; Zhang, Xu; Sengupta, Satyaki; Iorgulescu, J Bryan; Ni, Hongru; Das, Sanjukta; Rager, Madison; Zhou, Zhenwei; Zuo, Tao; et al (March 2024, Science Advances)

Solid tumors, especially those with aberrant MYCN activation, often harbor an immunosuppressive microenvironment to fuel malignant growth and trigger treatment resistance. Despite this knowledge, there are no effective strategies to tackle this problem. We found that chemokine-like factor (CKLF) is highly expressed by various solid tumor cells and transcriptionally up-regulated by MYCN. Using the MYCN-driven high-risk neuroblastoma as a model system, we demonstrated that as early as the premalignant stage, tumor cells secrete CKLF to attract CCR4-expressing CD4⁺cells, inducing immunosuppression and tumor aggression. Genetic depletion of CD4⁺T regulatory cells abolishes the immunorestrictive and protumorigenic effects of CKLF. Our work supports that disrupting CKLF-mediated cross-talk between tumor and CD4⁺suppressor cells represents a promising immunotherapeutic approach to battling MYCN-driven tumors.
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Massively parallel single-cell mitochondrial DNA genotyping and chromatin profiling

https://doi.org/10.1038/s41587-020-0645-6

Lareau, Caleb A.; Ludwig, Leif S.; Muus, Christoph; Gohil, Satyen H.; Zhao, Tongtong; Chiang, Zachary; Pelka, Karin; Verboon, Jeffrey M.; Luo, Wendy; Christian, Elena; et al (April 2021, Nature Biotechnology)

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Measuring the predictability of life outcomes with a scientific mass collaboration

https://doi.org/10.1073/pnas.1915006117

Salganik, Matthew J.; Lundberg, Ian; Kindel, Alexander T.; Ahearn, Caitlin E.; Al-Ghoneim, Khaled; Almaatouq, Abdullah; Altschul, Drew M.; Brand, Jennie E.; Carnegie, Nicole Bohme; Compton, Ryan James; et al (April 2020, Proceedings of the National Academy of Sciences)

How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the common task method; 160 teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. Despite using a rich dataset and applying machine-learning methods optimized for prediction, the best predictions were not very accurate and were only slightly better than those from a simple benchmark model. Within each outcome, prediction error was strongly associated with the family being predicted and weakly associated with the technique used to generate the prediction. Overall, these results suggest practical limits to the predictability of life outcomes in some settings and illustrate the value of mass collaborations in the social sciences.
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