Phenomics. 2026 May 20;6(3):213-229. doi: 10.1007/s43657-026-00322-4. eCollection 2026 Jun.

ABSTRACT

Early cancer detection remains challenging due to the lack of reliable pan-cancer screening methods, particularly blood-based biomarkers. Using a novel three-tiered validation framework combining artificial intelligence (AI)-powered literature mining of 180,000 PubMed articles (1950-2024), multiomics integration across major databases, and extensive clinical validation, we identified macrophage migration inhibitory factor (MIF) as a promising blood-based biomarker for pan-cancer detection. Multiomics analysis revealed consistent MIF upregulation across 21 cancer types at the transcriptional level and across 12 cancer types at the protein level. Clinical validation in independent cohorts (n = 4,269) showed that serum MIF protein levels discriminated effectively between cancer patients and healthy controls (median AUC = 0.994) and between cancer and benign conditions (median AUC = 0.881). Notably, comparative analyses showed that MIF demonstrated superior or comparable performance to established cancer-specific markers, including AFP for hepatocellular carcinoma (MIF AUC = 0.885 vs. AFP AUC: 0.744-0.887) and CA125 for ovarian cancer (MIF AUC = 0.831 vs. CA125 AUC: 0.58-0.71). Meta-analysis of 28 cohorts (n = 5,347) confirmed the diagnostic efficacy of MIF (pooled AUC: 0.782). This cost-effective, blood-based ELISA approach establishes MIF as a valuable tool for broad applications in cancer screening.

SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at https://doi.org/10.1007/s43657-026-00322-4.

PMID:42750739 | PMC:PMC13578188 | DOI:10.1007/s43657-026-00322-4

J Thorac Oncol. 2026 Sep 16:104204. doi: 10.1016/j.jtho.2026.104204. Online ahead of print.

ABSTRACT

BACKGROUND: Early-stage EGFR-mutant lung adenocarcinoma (LUAD) demonstrates heterogeneous outcomes after curative surgery, yet adjuvant treatment decisions are guided by pathological stage alone. Following the ADAURA trial, adjuvant osimertinib is the standard of care for resected stage IB-IIIA EGFR-mutant LUAD; however, real-world data demonstrate that up to 40% of patients remain disease-free at five years without adjuvant osimertinib, underscoring the need for improved risk stratification.

PATIENTS AND METHODS: We performed integrated clinical, genomic and transcriptomic profiling of 400 patients with resected stage IA-IIIA EGFR-mutant LUAD. EGFR-mutant recurrence risk models integrating clinical, genomic and transcriptomic data were developed and validated across one internal and three external cohorts.

RESULTS: Genomic instability, including TP53 co-mutations, copy number alterations and APOBEC-associated mutational signatures, increased with pathological stage. RBM10 co-mutations were enriched in tumours with L858R mutations and correlated with upregulation of WNT signalling and epithelial-mesenchymal transition. Transcriptomic features outperformed clinical or genomic variables alone in predicting recurrence risk, and a multi-omic model demonstrated superior and reproducible performance, achieving a median concordance index of 75.4% across four independent validation cohorts. The multi-omic model stratified recurrence risk within individual pathological stages, including stage I disease, and identified patients most likely to benefit from adjuvant EGFR TKI.

CONCLUSIONS: These findings define the molecular heterogeneity of early-stage EGFR-mutant LUAD and support multi-omic risk stratification to inform adjuvant EGFR TKI decisions beyond pathological stage. Prospective validation in larger cohorts will be required to confirm these findings.

PMID:42749051 | DOI:10.1016/j.jtho.2026.104204

Biochim Biophys Acta Rev Cancer. 2026 Sep 15:189717. doi: 10.1016/j.bbcan.2026.189717. Online ahead of print.

ABSTRACT

Breast cancer deaths are mainly caused by metastasis to distant organs, not by the primary tumor. Bone, lung, liver, and brain are the most common metastatic sites, each showing different clinical behaviors and treatment responses-a pattern often called metastatic organotropism. Bulk omics can provide tissue-level information, but they fall short in identifying rare metastasis-initiating clones or capturing how tumor cells adapt to distinct organ microenvironments. With recent progress in single-cell sequencing, multi-omics integration, and spatial profiling, it is now possible to study metastasis at much finer cellular and spatial resolution. In this review, we synthesize current evidence from two complementary perspectives. First, we summarize pan-organ programs associated with metastatic competence, including partial epithelial-mesenchymal transition, lineage plasticity, stem-like states, stress tolerance, metabolic flexibility, immune evasion, and stromal-vascular remodeling. Second, we discuss how these programs are reshaped by organ-specific microenvironments: osteolytic and mixed bone remodeling and marrow dormancy in bone, inflammatory vascular niches in lung, tolerogenic antigen presentation and hepatic metabolism in liver, and blood-brain/blood-tumor barrier constraints, glial crosstalk, neuronal interactions, and lipid-metabolic adaptation in brain. We also highlight how CTC/CTM profiling, spatial mapping, and longitudinal integration refine the understanding of dissemination, dormancy, colonization, outgrowth, and treatment resistance. Although these approaches hold translational promise, most remain at the discovery or early validation stage and require assay simplification, prospective testing, and cross-center standardization. Overall, single-cell and spatial multi-omics are reframing breast cancer metastasis as a dynamic, multi-stage, and tissue-shaped process, providing a foundation for future biomarker development and mechanism-guided therapeutic strategies.

PMID:42744123 | DOI:10.1016/j.bbcan.2026.189717

Biology (Basel). 2026 Sep 4;15(17):1549. doi: 10.3390/biology15171549.

ABSTRACT

OBJECTIVE: This study established a rat model of lipopolysaccharide (LPS)-induced acute lung injury (ALI) to evaluate pathological damage, collagen deposition, inflammatory cytokine levels, and key gene/protein expression following Hedyotis diffusa water extract (HDWE) intervention. Combined with ultra-high-performance liquid chromatography-quadrupole Orbitrap high-resolution mass spectrometry (UHPLC-Q-Orbitrap HRMS), transcriptomic analysis, and molecular simulation, this study identified the bioactive components of HDWE, evaluated their potential interactions with ALI-related targets, and explored the multi-omics-based protective mechanisms of HDWE.

METHODS: Thirty-six Sprague-Dawley (SD) rats were randomly divided into six groups: Control group, ALI group, DXMS group, HDWE-L group (100 mg/kg), HDWE-M group (200 mg/kg), and HDWE-H group (300 mg/kg). Hematoxylin and eosin (H&E) and Masson's trichrome staining were used to evaluate lung pathological changes and collagen deposition. Enzyme-linked immunosorbent assay (ELISA) was used to measure serum tumor necrosis factor-α TNF-α interleukin-1β IL-1β, erleukin-6 (IL-6), and interleukin-10 (IL-10) levels. Transcriptomic analysis identified differentially expressed genes (DEGs), followed by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), receiver operating characteristic (ROC), and immune infiltration analyses. Quantitative real-time polymerase chain reaction (qRT-PCR) detected the mRNA expression levels of SPHK1, RELA, and NFKBIA. Immunohistochemistry evaluated the expression of eight hub targets, including endothelin-1 (EDN1), sphingosine kinase 1 (SPHK1), intercellular adhesion molecule 1 (ICAM1), interleukin-17 (IL-17), prostaglandin-endoperoxide synthase 2 (PTGS2/COX-2), NF-κB p65 (encoded by RELA), WT1-associated protein (WTAP), and myeloperoxidase (MPO). UHPLC-Q-Orbitrap HRMS characterized HDWE constituents. Molecular docking analysis was performed between 22 compounds and eight hub targets, followed by 100 ns molecular dynamics simulations and molecular mechanics-Poisson-Boltzmann surface area (MM/PBSA) binding free energy calculations for five core targets. Compared with the control group, the ALI group showed increased levels of TNF-α (86%), IL-1β (107%), and IL-6 (66%), accompanied by a 43% reduction in IL-10 and a 300% increase in lung collagen deposition. All HDWE doses alleviated inflammatory responses, with medium-dose HDWE showing the most pronounced effects. Specifically, medium-dose HDWE increased IL-10 levels by 52% and reduced IL-6, TNF-α, and IL-1β levels by 18%, 22%, and 11%, respectively. Transcriptomic analysis identified 2512 DEGs between the control group and ALI groups, 832 exclusive DEGs between the ALI group and HDWE-M groups, and 876 overlapping DEGs enriched in TNF, IL-17, and NF-κB signaling pathways. The eight-hub-gene diagnostic model achieved an area under the curve (AUC) of 0.969. RELA, SPHK1, and four other hub genes showed positive correlations with Th1, Th17, and neutrophil infiltration. In the ALI group, SPHK1, RELA, and NFKBIA mRNA expression levels were 1.30-, 0.96-, and 0.71-fold of those in the control group, respectively. Compared with the ALI group, high-dose HDWE treatment and low-dose HDWE treatment reduced SPHK1 expression to 0.62- and 0.57-fold, respectively, and increased NFKBIA expression to 1.68- and 1.58-fold, respectively. High-dose HDWE treatment reduced RELA expression to 0.43-fold. The expression levels of inflammation-related proteins were increased in the ALI group and were reduced after HDWE treatment. Twenty-two HDWE components were identified, 16 of which met the docking criteria. Asperulosidic acid exhibited favorable predicted binding affinities with all eight targets, with calculated binding free energies of -14.74, -14.92, -17.58, -23.04, and -16.10 kcal/mol for MPO, IL-17, NF-κB p65, PTGS2/COX-2, and SPHK1, respectively.

CONCLUSIONS: This study provides systematic in vivo pharmacodynamic and in silico component-target evidence regarding the protective effects of HDWE against LPS-induced ALI. HDWE treatment increased NFKBIA expression and reduced SPHK1, RELA, and multiple inflammatory protein levels, suggesting that HDWE may regulate the IL-17/NF-κB-associated inflammatory network, although direct causal relationships require further validation. Asperulosidic acid may represent a key bioactive component with broad target-binding potential. This study was limited by the use of an LPS-induced rat ALI model without gene knockout or target inhibitor validation; therefore, further functional experiments are required to confirm the proposed regulatory mechanisms.

PMID:42737981 | PMC:PMC13564518 | DOI:10.3390/biology15171549