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Biology subjects

Troncone, G.

Publications and source records attributed to Troncone, G..

3 recordsLinked to original sources

KRAS-Mediated CCDC6 Degradation Drives xCT Upregulation and Ferroptosis Evasion

Oncogenic KRAS mutations drive tumorigenesis by promoting pro-survival signaling and metabolic reprogramming, including the maintenance of redox balance to evade oxidative stress. A key mechanism involves the upregulation of the xCT cystine/glutamate antiporter, which sustains glutathione (GSH) synthesis and protects cells from oxidative damage and ferroptosis. While it is known that the ETS1-ATF4 complex mediates transcriptional upregulation of xCT, the upstream regulators linking KRAS signaling to this axis remain to be fully defined. Here, we demonstrate that oncogenic KRAS signaling induces the GSK3{beta}-mediated proteasomal degradation of the tumor suppressor CCDC6. We show that CCDC6 acts as a negative regulator of the xCT-promoting transcription factor ATF4 by directly interacting with it and preventing its recruitment to the xCT promoter. Consequently, KRAS-driven CCDC6 degradation disinhibits ATF4, leading to increased xCT expression, elevated intracellular GSH, and enhanced resistance to ferroptosis. Crucially, pharmacological inhibition of CCDC6 turnover using proteasome, GSK3{beta}, or specific KRAS mutant inhibitors (Sotorasib, Adagrasib, HRS4642) restored CCDC6 protein levels and robustly sensitized KRAS-mutated cells to ferroptosis-inducing agents like Sulfasalazine. Furthermore, validation in preclinical models and human colorectal cancer samples revealed that CCDC6 protein levels are predominantly downregulated in KRAS-mutant cases This work uncovers a novel KRAS/CCDC6/xCT signaling axis that mediates ferroptosis resistance in KRAS-mutated cancers. Moreover, it identifies CCDC6 turnover as a critical vulnerability and a promising therapeutic target to enhance the efficacy of ferroptosis-inducing agents.

cancer biology↗

Type 2 Deiodinase in Cancer-Associated Fibroblasts is required to sustain growth of poorly and undifferentiated thyroid cancer

Poorly differentiated (PDTC) and anaplastic thyroid carcinomas (ATC) are characterized by rapid progression and poor patient survival. While the tumor microenvironment (TME) - particularly cancer-associated bibroblasts (CAFs)- plays a crucial role in supporting tumor growth, its metabolic contribution remains poorly understood. Here, we identify a critical role for type 2 deiodinase (D2), the enzyme that activates the thyroid hormone (TH) thyroxine (T4) into the biologically active triiodothyronine (T3), in sustaining a pro-tumorigenic TME in PDTC and ATC. We show that D2 is expressed not only in thyroid epithelial cancer cells, but at even higher levels in CAFs, especially inblammatory CAFs (iCAFs). In in vivo mouse models, pharmacological inhibition of D2 reduces tumor growth and alters composition of CAFs. In 3D co-culture spheroids, D2 activity proves essential for supporting tumor cell proliferation by establishing a paracrine loop between stromal and epithelial cancer cells that amplibies local TH signaling. Notably, human PDTC organoids expressing D2 respond to modulation of TH levels, conbirming the functional relevance of this metabolic axis in human tumors. In conclusion, these bindings identify D2 as a key mediator of stromal-epithelial crosstalk in PDTC and ATC, and highlight local TH metabolism as a potential therapeutic target in these lethal cancers.

cancer biology↗

Nanoscale prognosis of colorectal cancer metastasis from AFM image processing of histological sections

Early ascertainment of metastatic tumour phases is crucial to improve cancer survival, formulate an accurate prognostic report of disease advancement and, most important, quantify the metastatic progression and malignancy state of primary cancer cells with a universal numerical indexing system. This work proposes an early improvement of cancer detection with 97 nm spatial resolution by indexing the metastatic cancer phases from the analysis of atomic force microscopy images of human colorectal cancer histological sections. The procedure applies variograms of residuals of Gaussian filtering and theta statistics of colorectal cancer tissue image settings. The methodology elucidates the early metastatic progression at the nanoscale level by setting metastatic indexes and critical thresholds from relatively large histological sections and categorising the malignancy state of a few suspicious cells not identified with optical image analysis. In addition, we sought to detect early tiny morphological differentiations indicating potential cell transition from epithelial cell phenotypes of low to high metastatic potential. The metastatic differentiation, also identified by higher moments of variograms, sets different hierarchical levels for the metastatic progression dynamic, potentially impacting therapeutic cancer protocols.

cancer biology↗