Transl Oncol. 2026 Jan 6;64:102660. doi: 10.1016/j.tranon.2025.102660. Online ahead of print.

ABSTRACT

Lung cancer remains the leading cause of cancer incidence and mortality worldwide, with non-small cell lung cancer (NSCLC) accounting for about 85% of cases. The low rate of early diagnosis and the high rate of occult metastases limit the survival benefits of conventional treatments. The current TNM staging system fails to fully reflect tumor heterogeneity or the dynamic molecular evolution of the disease, thus affecting the prediction of recurrence and the prognostic stratification. Some recent advances in minimal residual disease (MRD) detection, such as ultra-sensitive liquid biopsy technologies, have largely overcome the limitations of traditional imaging and offered a transformative approach for continuous, precision-based management of lung cancer. This review systematically summarized the technological evolution of MRD detection and highlighted its clinical significance in guiding adaptive therapy for NSCLC, including treatment escalation, de-escalation, and the emerging concept of precision-guided drug holidays. Moreover, the authors comprehensively discussed the "Four-Dimensional TNMB Staging System," which incorporates continuous molecular monitoring to address the static limitations of conventional staging and enhance the accuracy of prognostic stratification. Although ongoing challenges, such as the lack of standardized interpretation criteria and limited detection sensitivity, the combinations with the third-generation liquid biopsy platforms, multi-omics analyses, and multi-center prospective validation studies are expected to advance the clinical implementation of MRD-guided strategies. The paradigm change will enable the transition of NSCLC management from conventional standardized models to a precision-guided, closed-loop system of "monitoring-intervention-remonitoring," establishing a solid theoretical and practical foundation for comprehensive, molecularly driven management strategies.

PMID:41496417 | DOI:10.1016/j.tranon.2025.102660

J Transl Med. 2026 Jan 6. doi: 10.1186/s12967-025-07596-8. Online ahead of print.

ABSTRACT

INTRODUCTION: Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies with a 5-year survival rate of < 13%. Standard treatments such as FOLFIRINOX or gemcitabine/nab-paclitaxel yield modest response rates, underscoring the urgent need for precision oncology approaches. Patient-derived organoids (PDOs) preserve the genomic, phenotypic, and histopathological features of the source tumor and offer a promising platform for drug screening, biomarker development, and personalized therapy. However, a systematic evaluation of their translational capacities is lacking.

METHODS: A systematic review was conducted according to the PRISMA 2020 guidelines (PROSPERO registration pending) using PubMed, EMBASE, and Cochrane CENTRAL (December 10, 2024) to identify English-language PDAC PDO studies that incorporated therapeutic testing. Ninety-five studies met the inclusion criteria. Data extraction captured >75 variables per study, including spanning culture methodology, therapeutic profiling, biomarker integration, and clinical correlation. A 13-domain weighted Translatability Scoring Framework adapted from Wehling et al. assessed predictive validity, biomarker strength, pharmacogenetics, and clinical trial alignment. Scores ranged from 0 to 5 and were categorized as good (>4.0), moderate (3.0-4.0), or low (<3.0) translational potential.

RESULTS: Of the 95 studies, 70.5% have been published since 2021, reflecting the rapid growth in this field. The mean PDO generation success rate was 89.7%, with the primary tumor tissue being the predominant source (48.4%). Only 24.8% were directly linked to clinical trials and 5.3% incorporated multi-omic profiling. The median translatability score was 3.13 (range, 1.72-4.59): 45.3% of the studies had low translatability, 50.5% moderate, and only 4.2% had good translational potential. High-scoring studies consistently combine multi-omic biomarker platforms, in vivo validation, clinical outcome correlation, and prospective trial integration. Conversely, the weakest domains were pharmacogenetics, endpoint strategies, and biomarker validation, limiting their overall clinical relevance.

CONCLUSIONS: PDOs have demonstrated strong feasibility and in vitro clinical correlation in PDAC; however, their clinical translation remains constrained by limited multi-omic integration, absence of pharmacogenomic modeling, and sparse clinical trial embedding. Standardization of protocols, adoption of harmonized and clinically relevant endpoints, and systematic incorporation of biomarker-driven co-clinical trial frameworks are urgently needed to transition PDOs from promising experimental surrogates to validating precision oncology tools capable of informing therapeutic decision-making in PDAC.

PMID:41495743 | DOI:10.1186/s12967-025-07596-8