Nature cancer最新文献

Treatments for leptomeningeal metastasis (LM) are limited and prognosis is poor. In this phase 2, nonrandomized, single-arm, multicenter study, we evaluated a tucatinib-trastuzumab-capecitabine regimen in patients with newly diagnosed LM and human epidermal growth factor receptor 2-positive (HER2⁺) breast cancer. The primary endpoint was overall survival; secondary endpoints included central nervous system progression-free survival, LM objective response, neurological symptom improvement, pharmacokinetics and safety. The trial met its prespecified interim efficacy threshold and exceeded the historical control of 4.4 months. Among 17 enrolled women, all had magnetic resonance imaging-confirmed LM, 15 (88%) were symptomatic and 8 (47%) had abnormal cerebrospinal fluid cytology. For a median follow-up of 18 months (range 9.0-26.7 months), 6 of 17 (41%) remained alive. Tucatinib reached therapeutic levels in the cerebrospinal fluid. The median overall survival was 10 months (95% confidence interval 4.1 months, not reached). The median time to central nervous system progression was 6.9 months (95% confidence interval 2.8, 13.8 months). Of 13 response-evaluable patients, 5 (38%) achieved composite LM objective response. Of 12 evaluable patients, 7 (58%) had improved neurological deficits. This prospective study suggests clinical benefit with a systemic regimen for HER2⁺ LM including objective responses, improved symptoms and extended survival. These data support systemic therapy as an approach in HER2⁺ breast cancer LM. ClinicalTrials.gov registration: NCT03501979 .

Artificial intelligence (AI) tools can improve breast screening performance but different screening sites have varying needs. Here the GEMINI prospective evaluation of 10,889 women, within one UK region, used both live AI integration and simulations to model 17 different ways AI could be used in breast screening. All women received routine care. One AI tool was assessed. When the AI tool recommended recall but routine double reading did not, cases underwent additional human review, detecting 11 additional cancers. The primary AI workflow could improve cancer detection by 10.4% (1 per 1,000), maintain the recall rate (0.8% reduction) and reduce workload by up to 31%. Other workflow variations significantly improved all measured metrics (superiority in cancer detection rate, recall rate, positive predictive value (PPV), sensitivity and specificity) with up to 36% workload savings. Different AI integrations in breast screening could offer various clinical and operational gains, allowing for adaptation to local healthcare needs.

The impact of incorporating artificial intelligence (AI) into a double-read breast-screening workflow, including arbitration, is unclear. This retrospective study included 50,000 representative women from two NHS breast-screening centers. All the women had long-term follow-up, allowing us to determine whether use of AI leads to earlier cancer detection. Cases requiring arbitration (8,732 cases) were read by 22 readers in a reader study, following their normal arbitration workflow. Overall, after arbitration, replacing the second reader with AI was noninferior (5% margin) to two human readers in terms of sensitivity and specificity (P < 0.001) while offering a workload benefit. Arbitration improved the specificity of the AI arm by overruling cases incorrectly recalled by the AI tool; however, it also overruled the AI tool recall decision for some interval and next-round cancers. Further development of the AI tool alongside improvement in its explainability could lead to the earlier detection of cancers.

Artificial intelligence (AI) promises to enhance breast cancer screening. Here we evaluated Google's mammography AI system (version 1.2) across two phases: a retrospective study using 115,973 mammograms from five National Health Service screening services with 39-month follow-up and prospective noninterventional feasibility deployment at 12 sites (9,266 cases). The primary endpoint was AI sensitivity and specificity versus first reader using a 5% noninferiority margin. The secondary endpoints were performance versus second or consensus readers and breast-level analyses. Retrospectively, AI achieved superior sensitivity (0.541 versus 0.437 for first reader, P < 0.001) and noninferior specificity (0.943 versus 0.952, P < 0.001). Cancer detection rate increased from 7.54 to 9.33 per 1,000 women, with AI detecting 25.0% of interval cancers. Performance was particularly strong for first screens (39.3% fewer recalls, 8.8% higher detection) and invasive cancers. No systematic demographic disparities were observed. Simulated second-reader replacement reduced reading time by 32% while increasing detection by 17.7%. Prospective deployment confirmed technical feasibility but revealed a distribution shift requiring threshold recalibration. Implementation requires adaptive calibration and continuous monitoring to ensure safety and equity.

The benefit from immune checkpoint blockade (ICB) can be mitigated by the onset of immune-related adverse events (irAEs). The identification of checkpoints specific to irAEs could mitigate toxicity without antitumor efficacy trade-off. Here we integrated transcriptome and pharmacovigilance data to decipher the efficacy-toxicity equilibrium of ICB-regulated molecules and identified cytotoxic and regulatory T cell molecule (CRTAM) as an irAE checkpoint. Crtam knockout or T cell lineage-specific Crtam ablation impaired irAE induction in preclinical models. CRTAM⁺ T cells preferentially infiltrated normal tissues over tumors through the CRTAM-cell adhesion molecule 1 interaction and promoted interleukin 23-centered type 3 immunity. CRTAM inhibition preserved the 'hot' tumor microenvironment required for efficacy while mitigating toxicity in tumor-bearing irAE models. Quantification of the CRTAM-type 3 immune axis in blood samples enabled monitoring of irAEs in cohorts treated with ICB. Our study identifies CRTAM as a T cell checkpoint of irAEs, providing a potential target to uncouple efficacy from toxicity during immunotherapy.