Editors’ Selections from Relevant Scientific Publications

Killer T cells surround a cancer cell (by Alex Ritter et al from National Institutes of Health via Flickr)A recent study demonstrates how T cells mediate immunoediting and suppress tumor development. Using a murine sarcoma model expressing fluorescent neoantigens, Cheung and colleagues found that sarcomas developed in only ∼53% of T cell-sufficient mice compared with 100% of T cell-deficient mice. Tumor cells from T cell-sufficient mice were all neoantigen-negative, whereas those from T cell-deficient mice were antigenically heterogenous, suggesting that neoantigen silencing was necessary to evade T cells recognition but insufficient for tumor outgrowth. Genetic removal of neoantigens on day 5 after tumor initiation restored tumor formation, but not when performed on day 10. This was attributed to infiltration of CD4+ and CD8+ T cells that eliminated most neoantigen-positive and -negative cells by day 8. Single-cell analyses of day-7 tumors revealed T cell-dependent enrichment of interferon-γ (IFNγ) responses, including upregulation of Cd274 (PD-L1), and IFNγ produced against neoantigen-positive cells also eliminated neighboring neoantigen-negative cells through a bystander effect. While T cell depletion rescued all tumor cells, IFNγ blockade selectively rescued neoantigen-negative cells, indicating distinct IFNγ-dependent and -independent mechanisms of T cell-mediated elimination of tumor cells. These findings uncover how T cells edit and intercept early tumors before their establishment, providing insights into immune surveillance and potential preventative strategies.Cheung JF, … Joshi NS. Cancer Cell. 2025 Oct 2:S1535-6108(25)00397-6.Aspirin (by Intropin via Wikimedia Commons)A secondary analysis of the Aspirin in Reducing Events in the Elderly (ASPREE) randomized clinical trial suggests that the effectiveness of low-dose aspirin (LDA) for cancer prevention in older adults varies significantly with individual characteristics. Using data from 9,350 participants aged 70 and older, Thao and colleagues developed and validated an effect score model to estimate individualized treatment effects (ITEs) of LDA (100 mg/day) over a median follow-up of 4.5 years. Factors associated with LDA benefit included nonsmoking status, older age, lower body mass index, family history of cancer, and, notably, clonal hematopoiesis of indeterminate potential (CHIP) with a variant allele frequency ≥10%, which emerged as the strongest predictor of benefit. Based on the model, personalized treatment improved 5-year cancer risk reduction by a median of 2.3% compared with a treat-all approach. LDA use was linked to lower cancer risk in treatment-favorable subgroup but higher cancer risk in treatment-unfavorable individuals. These findings reveal heterogeneity in preventive effects of LDA and support the development of personalized chemoprevention strategies in older adults.Thao LTP, … Wolfe R. JAMA Oncol. 2025 Sep 25:e253593.The genomic classification and prognostic model of multiple myeloma precursors (by Maura et al via J Clin Oncol.)A new study indicates that genomic profiling can identify malignant transformation in multiple myeloma (MM) precursor conditions: monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM). By analyzing whole-genome and exome sequencing data from 374 patients, Maura and colleagues reclassified these precursor conditions into “genomic MM” and “genomic MGUS”, separating biological malignant cases from truly premalignant ones unlikely to progress. Most SMM cases exhibited genomic characteristics indistinguishable from active MM, indicating a high risk of progression. In contrast, 60% of MGUS and 10% of SMM showed no genomic evidence of malignancy and remained stable over 5 years of follow-up. Moreover, integration of genomic data with the 2/20/20 International Myeloma Working Group model significantly improved predictive accuracy. These findings establish a genomics-based framework for risk stratification, offering a refined classification system that may guide early intervention and improve management of myeloma precursor states.Maura F, … Rajkumar SV. J Clin Oncol. 2025 Oct 8:JCO2501733.DNA Helix representing genetic variants (by Bango Renders via Stocksnap)A recent study examines the combined impact of pathogenic variants (PVs), family history, and other factors on breast cancer risk in the general U.S. population. Using pooled data from 67,692 women (33,841 cases and 33,851 controls) across 13 case-control studies in the Cancer Risk Estimates Related to Susceptibility (CARRIERS) consortium, O’Brien and colleagues found that women with a PV and a first-degree family history of breast cancer had significantly elevated risks—22.5% by age 50 and 51.2% between ages 50 and 80—compared with 9.4% and 29.7%, respectively, in PV carriers without family history. PVs in ATM, BRCA1, BRCA2, CHEK2, and PALB2, were strongly associated with increased risk, with BRCA1 and PALB2 showing pronounced modification by family history. Using the Individualized Coherent Absolute Risk Estimation (iCARE) model, the study generated population-based cumulative risk estimates stratified by genetic status, family history, race/ethnicity, and modifiable risk factors. These findings provide actionable insights for personalized screening and prevention, supporting more precise and individualized risk assessment in clinical practice.O'Brien KM, … Sandler DP. JAMA Oncol. 2025 Oct 9.