Cellular senescence contributes to aging and disease, and senolytic drugs that selectively eliminate senescent cells hold therapeutic promise. Although over 20 candidates have been reported, their relative efficacies remain unclear. Here we systematically compared 21 senolytic agents using a senolytic specificity index, identifying the Bcl-2 inhibitor ABT263 and the BET inhibitor ARV825 as most effective senolytics across fibroblast and epithelial senescence models. However, even upon extended treatment with these most potent senolytics, a proportion of senescent cells remained viable. We found that senolytic resistance was driven by maintenance of mitochondrial integrity through V-ATPase-mediated clearance of damaged mitochondria. Imposing mitochondrial stress via metabolic workload enhanced the senolytic efficacies of ABT263 and ARV825 in vitro, and in mouse models, ketogenic diet adoption or SGLT2 inhibition similarly potentiated ABT263-induced and ARV825-induced senolysis, reducing metastasis and tumor growth. These findings suggest that mitochondrial quality control is a key determinant of resistance to ABT263-induced and ARV825-induced senolysis, providing a possible framework for rational combination senotherapies.
Regulation of RNA polymerase II (Pol II) transcription is closely associated with cell proliferation. However, it remains unclear how the Pol II transcription program is rewired in cancer to promote uncontrolled growth. Here, we find that expression of NELFCD, a known negative transcription elongation factor, is upregulated in colorectal tumors. Auxin-dependent protein degradation of NELF-C in combination with nascent transcript sequencing demonstrates a direct role of NELF-C on Pol II transcription in this cancer. Strikingly, we demonstrate that the acute loss of NELF-C protein globally redistributes termination factors and perturbs Pol II transcription termination. These changes drive pervasive Pol II transcription into DNA replication zones, leading to transcription-replication conflict that may block the cell cycle in G1 or early S phase. Our findings reveal a previously unrecognized role of NELF in transcription termination and highlight NELF as a potential therapeutic target in colorectal cancer.
Prognostication for pancreatic ductal adenocarcinoma (PDAC) using histologic images is difficult due to tumor heterogeneity. We developed an artificial intelligence (AI) model to predict postoperative recurrence using histologic image patches. We included 591 patients with resected PDAC to train an AI model for recurrence prediction at 12 or 24 months and validated it using external cohorts (n = 302 in total). Image patches from hematoxylin and eosin-stained slides were clustered via uniform manifold approximation and projection (UMAP) and used to train a random forest model. Predictive performance was evaluated using area under the receiver operating characteristic curve (AUC). Gene expression analysis was conducted to characterise survival-related clusters. Seventeen patch clusters were identified. Two were linked to high recurrence risk, and one to low risk. In external validation, the model achieved an AUC of up to 0.792. The random forest score independently predicted recurrence. Greater heterogeneity in patch composition correlated with shorter time to recurrence (P < 0.01). High-risk clusters showed elevated CSF3R expression; the low-risk cluster showed increased IGFBP3 expression. Our AI model, using only archival histologic slides, accurately predicted postoperative recurrence in PDAC and revealed image features linked to outcomes and gene expression.
Pancreaticoduodenectomy (PD) remains the standard procedure for tumors of the pancreatic head region but is one of the most technically demanding abdominal procedures. Robot-assisted PD (Robot-PD) is a promising minimally invasive alternative, with retrospective and early randomized studies suggesting its potential benefits; however, concerns remain regarding its surgical quality and safety. The Japan Society of Hepato-Biliary-Pancreatic Surgery has implemented a strict certification system for surgeons and institutions to ensure high-quality hepatopancreatobiliary surgeries. To date, no randomized trial has evaluated the safety and efficacy of Robot-PD under these rigorous standards. This study aims to evaluate the safety and efficacy of Robot-PD. This multicenter, prospective, open-label, randomized phase 2 trial will be conducted at four certified high-volume centers in Japan. Eligible patients will be aged 20–85 years with resectable tumors of the pancreatic head region without radiological evidence of major vascular invasion. The participants will be randomized in a 2:1 ratio to Robot-PD or open PD using a centralized web-based system with stratification based on institution, main pancreatic duct diameter ≥ 3 mm, and a history of pancreatitis or cholangitis. The primary endpoint will be the incidence of postoperative complications of Clavien–Dindo grade ≥ 3a in the Robot-PD group. The secondary endpoints will include intraoperative outcomes, postoperative complications and recovery (with comparisons between Robot-PD and open PD), pathological findings, oncological outcomes, quality of life, and cost. The target sample size will be 100 patients, allowing for a 10
IntroductionPersonalized neoantigen vaccines can induce antitumor T cell responses, but only 10-20% of selected peptides have induced immune responses in patients, underscoring the limitations of current prediction strategies.MethodsWe analyzed a clinically annotated dataset from 352 cancer patients who received personalized neoantigen peptide-pulsed dendritic cell vaccines. We focused on 2,317 short peptides derived from single nucleotide variants for which post-vaccination T cell responses were evaluated by IFN-γ ELISPOT assay. Immunogenic neoantigen peptides were defined as those inducing a ≥2.0-fold increase in IFN-γ ELISPOT responses after vaccination. We systematically examined peptide intrinsic characteristics and physicochemical properties, as well as predicted scores related to antigen-processing machinery.Results and discussionImmunogenicity was not associated with specific mutation positions or sequence patterns but was significantly correlated with higher hydrophobicity (P = 5.2 × 10-4). Among several predictive scores, peptides with higher binding affinity to HLA molecules (P = 0.0014 for NetMHC3, P = 0.028 for MHCflurry-affinity), higher binding stability (P = 0.043 for NetMHCstab) or better peptide presentation scores (P = 0.012 for mixmhcPred3, P = 0.0085 for MHCflurry-presentation) were significantly enriched among immunogenic neoantigen peptides. Composite models integrating peptide physicochemical features, particularly hydrophobicity, with prediction scores improved the area under the receiver operating characteristic curve and balanced accuracy compared with individual tools alone. Together, these findings highlight the multifactorial determinants of neoantigen immunogenicity and support the integration of complementary peptide features to refine neoantigen prioritization for personalized vaccines and T cell-based immunotherapies.
