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Whole-genome doubling (WGD) is common in human cancers, occurring early in tumorigenesis and generating genetically unstable tetraploid cells that fuel tumour development 1 , 2 . Cells that undergo WGD (WGD + cells) must adapt to accommodate their abnormal tetraploid state; however, the nature of these adaptations, and whether they confer vulnerabilities that can be exploited therapeutically, is unclear. Here, using sequencing data from roughly 10,000 primary human cancer samples and essentiality data from approximately 600 cancer cell lines, we show that WGD gives rise to common genetic traits that are accompanied by unique vulnerabilities. We reveal that WGD + cells are more dependent than WGD − cells on signalling from the spindle-assembly checkpoint, DNA-replication factors and proteasome function. We also identify KIF18A , which encodes a mitotic kinesin protein, as being specifically required for the viability of WGD + cells. Although KIF18A is largely dispensable for accurate chromosome segregation during mitosis in WGD – cells, its loss induces notable mitotic errors in WGD + cells, ultimately impairing cell viability. Collectively, our results suggest new strategies for specifically targeting WGD + cancer cells while sparing the normal, non-transformed WGD − cells that comprise human tissue. Cancer cells that have undergone whole-genome doubling are more reliant than their near-diploid counterparts on DNA-replication factors, the spindle-assembly checkpoint and a mitotic kinesin protein, KIF18A.

The Hippo and mammalian target of rapamycin complex 1 (mTORC1) pathways are the two predominant growth-control pathways that dictate proper organ development. We therefore explored potential crosstalk between these two functionally relevant pathways to coordinate their growth-control functions. We found that the LATS1 and LATS2 kinases, the core components of the Hippo pathway, phosphorylate S606 of Raptor, an essential component of mTORC1, to attenuate mTORC1 activation by impairing the interaction of Raptor with Rheb. The phosphomimetic Raptor-S606D knock-in mutant led to a reduction in cell size and proliferation. Compared with Raptor+/+ mice, RaptorD/D knock-in mice exhibited smaller livers and hearts, and a significant inhibition of elevation in mTORC1 signalling induced by Nf2 or Lats1 and Lats2 loss. Thus, our study reveals a direct link between the Hippo and mTORC1 pathways to fine-tune organ growth.The Hippo and mTORC1 pathways regulate growth control for proper organ development. Here, Gan et al. find that the Hippo pathway kinases LATS1 and LATS2 phosphorylate the mTORC1 component Raptor to attenuate mTORC1 activation.

The Hippo pathway maintains tissue homeostasis by negatively regulating the oncogenic transcriptional co-activators YAP and TAZ. Though functional inactivation of the Hippo pathway is common in tumors, mutations in core pathway components are rare. Thus, understanding how tumor cells inactivate Hippo signaling remains a key unresolved question. Here, we identify the kinase STK25 as an activator of Hippo signaling. We demonstrate that loss of STK25 promotes YAP/TAZ activation and enhanced cellular proliferation, even under normally growth-suppressive conditions both in vitro and in vivo. Notably, STK25 activates LATS by promoting LATS activation loop phosphorylation independent of a preceding phosphorylation event at the hydrophobic motif, which represents a form of Hippo activation distinct from other kinase activators of LATS. STK25 is significantly focally deleted across a wide spectrum of human cancers, suggesting STK25 loss may represent a common mechanism by which tumor cells functionally impair the Hippo tumor suppressor pathway. Hippo pathway inactivation plays a role in many cancers, although how tumor cells depress signaling is unclear. Here, Lim et al. identify STK25, which activates LATS in a manner distinct from other upstream kinases and is focally deleted from a range of human cancers.

Hyperactive sphingosine 1-phosphate (S1P) signaling is associated with a poor prognosis of triple-negative breast cancer (TNBC). Despite recent evidence that links the S1P receptor 1 (S1P1) to TNBC cell survival, its role in TNBC invasion and the underlying mechanisms remain elusive. Combining analyses of human TNBC cells with zebrafish xenografts, we found that phosphorylation of S1P receptor 1 (S1P1) at threonine 236 (T236) is critical for TNBC dissemination. Compared to luminal breast cancer cells, TNBC cells exhibit a significant increase of phospho-S1P1 T236 but not the total S1P1 levels. Misexpression of phosphorylation-defective S1P1 T236A (alanine) decreases TNBC cell migration in vitro and disease invasion in zebrafish xenografts. Pharmacologic disruption of S1P1 T236 phosphorylation, using either a pan-AKT inhibitor (MK2206) or an S1P1 functional antagonist (FTY720, an FDA-approved drug for treating multiple sclerosis), suppresses TNBC cell migration in vitro and tumor invasion in vivo. Finally, we show that human TNBC cells with AKT activation and elevated phospho-S1P1 T236 are sensitive to FTY720-induced cytotoxic effects. These findings indicate that the AKT-enhanced phosphorylation of S1P1 T236 mediates much of the TNBC invasiveness, providing a potential biomarker to select TNBC patients for the clinical application of FTY720.

Whole genome doubling (WGD) occurs early in tumorigenesis and generates genetically unstable tetraploid cells that fuel tumor development. Cells that undergo WGD (WGD+) must adapt to accommodate their abnormal tetraploid state; however, the nature of these adaptations, and whether they confer vulnerabilities that can subsequently be exploited therapeutically, is unclear. Using sequencing data from ~10,000 primary human cancer samples and essentiality data from ~600 cancer cell lines, we show that WGD gives rise to common genetic traits that are accompanied by unique vulnerabilities. We reveal that WGD+ cells are more dependent on spindle assembly checkpoint signaling, DNA replication factors, and proteasome function than WGD– cells. We also identify KIF18A, which encodes for a mitotic kinesin, as being specifically required for the viability of WGD+ cells. While loss of KIF18A is largely dispensable for accurate chromosome segregation during mitosis in WGD– cells, its loss induces dramatic mitotic errors in WGD+ cells, ultimately impairing cell viability. Collectively, our results reveal new strategies to specifically target WGD+ cancer cells while sparing the normal, non-transformed WGD– cells that comprise human tissue.

Whole genome doubling (WGD) occurs early in tumorigenesis and generates genetically unstable tetraploid cells that fuel tumor development. Cells that undergo WGD (WGD+) must adapt to accommodate their abnormal tetraploid state; however, the nature of these adaptations, and whether they confer vulnerabilities that can subsequently be exploited therapeutically, is unclear. Using sequencing data from ~10,000 primary human cancer samples and essentiality data from ~600 cancer cell lines, we show that WGD gives rise to common genetic traits that are accompanied by unique vulnerabilities. We reveal that WGD+ cells are more dependent on spindle assembly checkpoint signaling, DNA replication factors, and proteasome function than WGD- cells. We also identify KIF18A, which encodes for a mitotic kinesin, as being specifically required for the viability of WGD+ cells. While loss of KIF18A is largely dispensable for accurate chromosome segregation during mitosis in WGD- cells, its loss induces dramatic mitotic errors in WGD+ cells, ultimately impairing cell viability. Collectively, our results reveal new strategies to specifically target WGD+ cancer cells while sparing the normal, non-transformed WGD- cells that comprise human tissue. Competing Interest Statement The authors have declared no competing interest.

Tetraploid cells, which are most commonly generated by errors in cell division, are genomically unstable and have been shown to promote tumorigenesis. Recent genomic studies have estimated that ~40% of all solid tumors have undergone a genome-doubling event during their evolution, suggesting a significant role for tetraploidy in driving the development of human cancers. To safeguard against the deleterious effects of tetraploidy, non-transformed cells that fail mitosis and become tetraploid activate both the Hippo and p53 tumor suppressor pathways to restrain further proliferation. Tetraploid cells must therefore overcome these anti-proliferative barriers to ultimately drive tumor development. However, the genetic routes through which spontaneously arising tetraploid cells adapt to regain proliferative capacity remain poorly characterized. Here, we conducted a comprehensive, gain-of-function genome-wide screen to identify miRNAs that are sufficient to promote the proliferation of tetraploid cells. Our screen identified 23 miRNAs whose overexpression significantly promotes tetraploid proliferation. The vast majority of these miRNAs facilitate tetraploid growth by enhancing mitogenic signaling pathways (e.g. miR-191-3p); however, we also identified several miRNAs that impair the p53/p21 pathway (e.g. miR-523-3p), and a single miRNA (miR-24-3p) that significantly inactivates the Hippo pathway via downregulation of the tumor suppressor gene NF2. Collectively, our data reveal several avenues through which tetraploid cells may regain the proliferative capacity necessary to drive tumorigenesis.

Histopathology is essential for disease diagnosis and treatment decision-making. Recent advances in artificial intelligence (AI) have enabled the development of pathology foundation models that learn rich visual representations from large-scale whole-slide images (WSIs). However, existing models are often trained on disparate datasets using varying strategies, leading to inconsistent performance and limited generalizability. Here, we introduce ELF (Ensemble Learning of Foundation models), a novel framework that integrates five state-of-the-art pathology foundation models to generate unified slide-level representations. Trained on 53,699 WSIs spanning 20 anatomical sites, ELF leverages ensemble learning to capture complementary information from diverse models while maintaining high data efficiency. Unlike traditional tile-level models, ELF's slide-level architecture is particularly advantageous in clinical contexts where data are limited, such as therapeutic response prediction. We evaluated ELF across a wide range of clinical applications, including disease classification, biomarker detection, and response prediction to major anticancer therapies, cytotoxic chemotherapy, targeted therapy, and immunotherapy, across multiple cancer types. ELF consistently outperformed all constituent foundation models and existing slide-level models, demonstrating superior accuracy and robustness. Our results highlight the power of ensemble learning for pathology foundation models and suggest ELF as a scalable and generalizable solution for advancing AI-assisted precision oncology.