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PubMed2025

Aberrant TERT expression: linking chronic inflammation to hepatocellular carcinoma†.

Telomerase reverse transcriptase (TERT), the catalytic enzyme component of telomerase, plays multiple roles in cellular biology. Its canonical function is primarily associated with telomere maintenance and genomic stability. In addition, several studies revealed critical non-canonical extra-telomeric functions of TERT in various cellular processes, including cell proliferation and survival, DNA damage response, transcription, signal transduction, and metabolic regulation, both in normal and in cancer cells. Notably, TERT is aberrantly upregulated in more than 80% of hepatocellular carcinoma (HCC) cases, making it an important target in liver cancer research. However, due to the diversity and complexity of TERT's functions in vivo, the precise mechanisms by which TERT contributes to the initiation and progression of HCC remain unclear. A recent study published in The Journal of Pathology using the Alb-Cre;TertTg mouse model and clinical HCC samples addresses the role of TERT in hepatocarcinogenesis. The study demonstrates that TERT promotes cell cycle progression and hepatocarcinogenesis by enhancing NF-κB promoter activity and facilitating the ubiquitination of p21. Notably, absence of functional p53 accelerates liver tumor development in TERT transgenic mice. These findings further underscore the critical role of TERT in inflammation-driven hepatocarcinogenesis and provide new insights into its underlying mechanisms. © 2025 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Telomerase↗
PubMed2026

Targeting USP22 reprograms the tumor microenvironment and sensitizes KRAS/p53-driven lung cancer to anti-PD-1 immunotherapy.

RATIONALE: Ubiquitin-specific peptidase 22 (USP22), a deubiquitinase and component of the "Death-from-Cancer" 11-gene signature, is overexpressed in multiple malignancies and linked to recurrence, therapy resistance, and poor prognosis. Its role in KRAS/p53-driven lung cancer and the response to immune checkpoint inhibitors (ICIs) remains poorly defined. Here, we investigated USP22 as a potential therapeutic target in KRAS/p53-driven lung cancer. METHODS: A conditional Usp22 knockout (Usp22-KO) was generated in the KRASG12D; p53-/- (KP) mouse model. Cancer progression was monitored by micro-computed tomography (micro-CT). Multiplex immunofluorescence (mIF), RNA sequencing, and spatial transcriptomics profiled cancer and tumor microenvironment (TME) changes. Responses to anti-PD-1/PD-L1 therapies were compared between KP and Usp22-KO KP (KPU-) lung cancers. RESULTS: USP22 was highly expressed in early-stage KRAS/p53-driven mouse lung cancers and strongly correlated with proliferation marker Ki67. Usp22 deletion suppressed cancer growth, prolonged survival, and promoted cancer differentiation. Spatial transcriptomics and mIF revealed reduced CD206+ M2 macrophages, myeloid-derived suppressor cells (MDSCs), TGF-β1, and angiogenesis, along with increased functional CD8+ T cells. Mechanistically, USP22 regulated gene expression and protein stability, reducing c-Myc, PD-L1, TGF-β1, and SPARC upon Usp22 loss. Compared with KP cancer, KPU- and SPARC-knockdown KP cancers showed reduced macrophage chemotaxis and impaired basal- and TGF-β1-induced M2 polarization of RAW264.7 cells, suggesting that TGF-β1 and SPARC downregulation partially contributes to decreased M2 macrophage infiltration in KPU- cancers. Notably, Usp22 loss enhanced the efficacy of anti-PD-L1 and anti-PD-1 therapies in orthotopic and subcutaneous KP lung cancer models, respectively. USP22 and SPARC expression were also strongly correlated in human lung cancers. CONCLUSIONS: USP22 promotes progression and immune evasion in KRAS/p53-driven lung cancer. Targeting USP22 reprograms the TME, suppresses oncogenic signaling, and sensitizes tumors to ICI, establishing USP22 as a promising therapeutic target.

Animals↗
PubMed2026

AI-Driven Multi-Omics Integration of Synthetic Colon Adenocarcinoma for Cluster-Guided PROTAC Candidate Design Targeting KRASG12D.

Colorectal cancer is a leading cause of cancer death, yet its molecular heterogeneity remains poorly translated into individualized treatment. We present a reproducible artificial intelligence (AI) framework that integrates multi-omics benchmarking, sample-level drug prioritization, E3 ubiquitin ligase selection, and shape-anchored Proteolysis Targeting Chimera (PROTAC) design for KRASG12D in colon adenocarcinoma (COAD). A controlled synthetic benchmark comprising 425 tumor and 41 simulated normal profiles, parameterized to match The Cancer Genome Atlas (TCGA) distributions, was used for pipeline verification. Among sixteen methods, the Balanced Latent Integration with Stability Selection (BLISS) model achieved the highest silhouette width (0.86) and competitive agreement (Adjusted Rand Index, ARI, 0.90). The pipeline was validated on real data: a TCGA COAD cohort (186 tumors) with independent Consensus Molecular Subtype (CMS) labels and a CPTAC cohort (104 tumors). Integration modestly recovered CMS (ARI 0.28), and stage, not molecular cluster, drove survival (log-rank p = 0.005 versus 0.81). Sample-level prioritization differed from cluster-level ranking in 82.6% of profiles, below chance (p < 0.0001), without indicating efficacy. Candidate NOVEL00489 showed a good MM-GBSA estimate, matching the reference ASP3082. Compounds are computational candidates requiring experimental validation. This establishes a transparent benchmark for in silico degrader generation in precision oncology.

Humans↗