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Unlocking the potential of bacteriophage-based therapeutic gene delivery in hepatocellular carcinoma.

Liver cancer, mainly hepatocellular carcinoma (HCC), remains a global health burden marked by poor prognosis with limited therapeutic efficacy, and high recurrence rates. HCC remains one of the most lethal malignancies worldwide, with limited therapeutic options and high resistance to conventional treatments. Despite low therapeutic efficacy, molecular heterogeneity, treatment resistance and high recurrence rate, hepatocellular carcinoma (HCC) is still a significant health problem worldwide. These restrictions have stimulated the research of focused methods for delivering therapeutic genetic payload into cancer cells. Bacteriophages have been gaining growing attention as an emerging delivery platform due to their genetic versatility, ease of engineering, ability to be surface modified and payload targeted. In this narrative review, the therapeutic potential of engineered bacteriophages in the context of HCC therapy is critically analyzed focusing on phage display-mediated tumor targeting, phage-mediated intracellular gene delivery, TRAIL gene delivery, and CRISPR/Cas-based therapeutic strategies. It has been previously noted in the literature that phage display can be used to attach tumor-targeting ligands to the surface of a phage, which may aid in the recognition of receptors at the tumor site and promote targeted delivery to the receptor. Therapeutic application is stunted by inefficient trafficking to the cytosol, endosomal degradation, immune recognition and clearance, vector stability, manufacturing scalability and regulatory issues. In conclusion, engineered bacteriophages are a promising and versatile tool for targeted gene delivery in HCC but more mechanistic, preclinical and translational research is needed to prove their therapeutic effectiveness and clinical usefulness for this purpose.

Humans

Machine learning prognostic model and drug survival analysis for lung adenocarcinoma in the context of radiotherapy.

BACKGROUND: Patients with lung adenocarcinoma (LUAD) receiving radiotherapy represent an important but underexplored clinical subgroup. These patients often undergo concomitant pharmacologic treatments, yet the prognostic impact and underlying determinants of such combined regimens remain poorly understood. OBJECTIVE: This retrospective observational study aimed to develop and validate a radiotherapy-specific machine learning prognostic model for LUAD and to compare survival across concomitant pharmacologic regimens. METHODS: In this retrospective observational study, using genomic and clinical data from TCGA, a radiotherapy-specific prognostic model for LUAD was developed and validated through ten machine learning algorithms. Survival analyses were conducted across distinct concomitant pharmacologic strategies, followed by functional enrichment to elucidate molecular mechanisms underlying differential outcomes. RESULTS: Demonstrating robust prognostic abilities, the model efficiently sorted patients into high- and low-risk categories. Both treatment type and risk score independently predicted overall survival, with significant interaction effects. Low-risk patients receiving targeted or combination therapy-mainly erlotinib, gefitinib, or bevacizumab-exhibited substantially improved survival compared with those receiving conventional chemotherapy. Enrichment of "Exogenous peptide presentation," "MHC class II assembly," "Peptide-MHC II assembly," and "Symbiotic interaction" pathways indicated immune modulation and host-tumor crosstalk as key mediators of treatment efficacy. CONCLUSION: This study establishes a radiotherapy-specific prognostic model for lung adenocarcinoma, demonstrating distinct molecular and therapeutic heterogeneity and highlighting the superior survival benefit of targeted combination therapy in low-risk patients.

Humans

APOL1 kidney disease: a critical narrative review of molecular mechanisms, clinical heterogeneity, and the emerging therapeutic landscape.

BACKGROUND: The G1 and G2 variants of the APOL1 gene represent significant genetic risk factors for APOL1 kidney disease and contribute substantially to the excess burden of renal disease observed in individuals of African ancestry. Importantly, both variants exhibit incomplete penetrance, with only approximately 15-20% of high-risk genotype carriers ultimately developing overt nephropathy. OBJECTIVE: To provide a critically appraised, clinically oriented narrative synthesis of APOL1 kidney disease that (i) assigns an explicit certainty rating to each major mechanistic and clinical claim, (ii) identifies where published estimates diverge, where associations remain contested, and where conclusions have been overstated in the secondary literature, and (iii) aligns terminology, testing guidance and therapeutic expectations with the conclusions of the 2025 KDIGO Controversies Conference and with clinical trial data available to August 2026. METHODS: This literature narrative review was performed using a literature search of PubMed and Scopus focusing on APOL1-related nephropathy. Mainly studies published from 2010 to 2026 were considered; however, some selected historical papers from 2005 to 2010 were used for better understanding of the underlying mechanisms and history. Used search terms were "APOL1," "APOL1 risk variants," "chronic kidney disease," AMPLITUDE trial, MZE829, HORIZON trial, "focal segmental glomerulosclerosis," "HIV-associated nephropathy," "podocyte injury," "inaxaplin," "VX-147," KDIGO 2025, and "antisense oligonucleotides." Trial status and topline results for agents in development were additionally verified against ClinicalTrials.gov registrations and sponsor disclosures. The literature search was last updated on 10 August 2026. The inclusion criteria of the study were peer-reviewed original articles, genome-wide association studies, randomised controlled trials, translational studies, mechanistic investigations, and high-quality review articles published in the English language. Exclusion criteria included conference abstracts without peer review, duplicate papers, non-English publications with unreliable translation, and case reports with no relevance to the underlying mechanisms. More attention was paid to studies focusing on molecular pathogenesis of APOL1 nephropathy, second-hit pathophysiology, genotypes/phenotypes, and new therapies (e.g. inhibitors such as Inaxaplin). The review method and design have been prepared according to SANRA (Scale for the Assessment of Narrative Review Articles) criteria. Among eligible articles, priority was given to studies with larger sample sizes, more recent publication dates, higher-impact peer-reviewed journals, and direct clinical or mechanistic relevance to APOL1-associated nephropathy; where multiple studies addressed the same question, the most methodologically rigorous and most recent source was preferentially cited. To move beyond description, each principal claim carried forward into this review was assigned a qualitative certainty rating (high, moderate, low or very low) on the basis of study design, consistency across independent cohorts, directness of the evidence to human disease, and precision of the estimate. These ratings, together with the study design that would be required to resolve each remaining uncertainty, are presented in Table 5. This grading represents a structured judgement by the authors and is not a formal GRADE assessment. RESULTS: Pathogenic actions of APOL1 risk alleles depend on toxic gain-of-function activities that result from the disruption of ion channels. Mitochondrial dysfunction, endoplasmic reticulum stress, and inflammasome activation play roles as secondary downstream modulators of podocyte damage. The existence of incomplete penetrance and lack of symptoms in people with high-risk alleles highlights the need for secondary triggers, including environmental, infectious, and inflammatory factors, for disease onset and progression. High-risk APOL1 genotypes increase the likelihood of rapidly progressing kidney diseases like FSGS, which amplify susceptibility in HIVAN when accompanied by secondary causes like HIV infection. Management is mainly through renin-angiotensin antagonists, but recent treatments include antisense oligonucleotides, immunomodulators, and small molecule inhibitors like inaxaplin. Although promising, inaxaplin (VX-147) showed a ~47% reduction in urine protein/creatinine ratio (UPCR) in Phase 2a trial; however, these findings are based on a relatively small sample size, an open-label study design, and short-term follow-up, and therefore require confirmation in ongoing Phase 3 studies. As this is a narrative review rather than a primary study, no new patient-level data are reported. Across the studies synthesised, high-risk APOL1 genotypes were consistently associated with podocyte injury and with a faster decline in kidney function than low-risk genotypes; however, the magnitude of this association varied substantially with how cohorts were ascertained. The association is robust and reproducible for focal segmental glomerulosclerosis, HIV-associated nephropathy, and hypertension-attributed kidney failure, and remains inconsistent for diabetic kidney disease. Therapeutic development has accelerated, but the supporting clinical evidence remains early phase. Inaxaplin (VX-147) reduced the urine protein-to-creatinine ratio by approximately 47.6% at week 13 in a 16-participant, single-group, open-label Phase 2a study, and is now being evaluated in the randomised, double-blind, placebo-controlled Phase 2/3 AMPLITUDE trial (NCT05312879), whose pre-specified week 48 interim analysis is anticipated in early 2027. MZE829, an orally administered APOL1 inhibitor, produced a mean 35.6% reduction in the urine albumin-to-creatinine ratio at 12 weeks in the Phase 2 HORIZON study; because HORIZON was a small, open-label, single-arm basket study (15 participants enrolled, 12 evaluable) whose primary endpoints were safety and tolerability, this reduction is neither placebo adjusted nor the result of a formal test of efficacy. To date, no APOL1-targeted agent has demonstrated benefit on a hard kidney endpoint. CONCLUSION: APOL1 is the clearest current example of a genetically defined, mechanism-targetable kidney disease, but its evidence base is uneven. The genetic association is firmly established; whereas much of the mechanistic literature derives from overexpression systems, several downstream pathways remain contested, and every APOL1-targeted therapy is so far supported only by short-term, surrogate-endpoint data. The principal unresolved issues are the determinants of incomplete penetrance, the absence of a validated progression biomarker and of any model reproducing the common slowly progressive phenotype, and the long-term efficacy and safety of APOL1-directed therapy. Genotype-guided risk stratification is therefore best regarded as clinically reasonable but not yet proven, and routine population-level screening is not currently supported.

AMPLITUDE trial

Multi-omics approaches in idiopathic pulmonary fibrosis: from molecular mechanisms to therapeutic targets and precision medicine.

Idiopathic pulmonary fibrosis (IPF) is a progressive interstitial lung disease with limited therapeutic options and marked molecular heterogeneity. Despite available antifibrotic therapies, disease progression remains poorly predictable, highlighting the need for improved mechanistic understanding and therapeutic targeting. This review summarizes recent advances in multi-omics research to elucidate the molecular mechanisms underlying IPF and to identify potential biomarkers and pharmacological targets. Multi-omics studies, including genomics, epigenomics, transcriptomics, proteomics, metabolomics, microbiome profiling, and single-cell sequencing, have revealed key pathogenic mechanisms in IPF. Genetic susceptibility factors such as MUC5B promoter variants and telomere-related genes contribute to disease risk. Epigenetic regulation, including DNA methylation, histone modifications, and non-coding RNAs, plays a central role in fibrotic remodeling. Transcriptomic and proteomic analyses have identified dysregulated signaling pathways, including TGF-β, mTOR, cellular senescence, and extracellular matrix remodeling. Metabolomic alterations indicate disrupted lipid and amino acid metabolism. Importantly, integration of multi-omics datasets enables the identification of molecular endotypes, candidate biomarkers, and potential therapeutic targets. However, challenges including data integration, tissue heterogeneity, limited cohort size, and the need for functional validation remain important barriers to clinical translation. Continued development of multi-omics approaches may facilitate more accurate disease classification and support the development of personalized therapeutic strategies for IPF.

biomarkers

Integrating explainable artificial intelligence with multiomics systems biology and electronic health record data mining for personalized drug repurposing in Alzheimer's disease.

Alzheimer's disease (AD) is characterized by region- and patient-specific molecular heterogeneity, which hinders therapeutic design. In this study, we introduce PRISM-ML (PRecision-medicine using Interpretable Systems and Multiomics with Machine Learning), an open-source integrated analysis pipeline that combines interpretable machine learning with systems biology and electronic health records data mining to elucidate the molecular diversity of AD and predict promising drug repurposing opportunities. First, we integrated and harmonized transcriptomic (bulk RNA-seq) and genomic (genome-wide association study) data from 2105 brain samples, each with matched data from the same individual (1363 AD patients, 742 controls; 9 tissues), sourced from three independent studies. Random forest classifiers with SHapley Additive exPlanations identified patient-specific biomarkers; unsupervised clustering resolved 36 molecularly distinct subtissues (defined as clusters of samples within a brain tissue that share a specific expression pattern); and gene-gene coexpression networks prioritized 262 high-centrality bottleneck genes as putative regulators of dysregulated pathways. Next, knowledge graph-based drug repurposing predicted six Food and Drug Administration (FDA)-approved drugs that simultaneously target multiple bottleneck genes and multiple AD-relevant pathways. Notably, in a large US de-identified insurance-claims database (n&#x2009;=&#x2009;364&#xa0;733), exposure to promethazine, one of the candidate drugs, was associated with a 57%-62% lower incidence of AD versus an active antihistamine comparator (adjusted hazard ratio 0.38; inverse-probability weighted 0.43; both P&#x2009;<&#x2009;.001), providing real-world support for its repurposing potential. In summary, PRISM-ML, as an explainable multiomics analysis pipeline, is readily transferable to other complex diseases, advancing precision medicine.

Alzheimer Disease

Integrating explainable AI with multiomics systems biology and EHR data mining for personalized drug repurposing in Alzheimer's disease.

Alzheimer's disease (AD) is characterized by region- and patient-specific molecular heterogeneity, which hinders therapeutic design. In this study, we introduce PRISM-ML (PRecision-medicine using Interpretable Systems and Multiomics with Machine Learning), an open-source integrated analysis pipeline that combines interpretable machine learning with systems biology and electronic health record (EHR) data mining to elucidate the molecular diversity of AD and predict promising drug repurposing opportunities. First, we integrated and harmonized transcriptomic (bulk RNA-seq) and genomic (genome-wide association study) data from 2105 brain samples, each with matched data from the same individual (1363 AD patients, 742 controls; nine tissues), sourced from three independent studies. Random forest classifiers with SHapley Additive exPlanations (SHAP) identified patient-specific biomarkers; unsupervised clustering resolved 36 molecularly distinct "subtissues" (clusters of samples); and gene-gene co-expression networks prioritized 262 high-centrality bottleneck genes as putative regulators of dysregulated pathways. Next, knowledge graph-based drug repurposing predicted six FDA-approved drugs that simultaneously target multiple bottleneck genes and multiple AD-relevant pathways. Notably, in a large U.S. de-identified insurance-claims database (n = 364733), exposure to promethazine, one of the candidate drugs, was associated with a 57-62 % lower incidence of AD versus an active antihistamine comparator (adjusted hazard ratio 0.38; inverse-probability weighted 0.43; both p < 0.001), providing real-world support for its repurposing potential. In summary, PRISM-ML, as an explainable multi-omics analysis pipeline, is readily transferable to other complex diseases, advancing precision medicine.

Computational Biology

Comprehensive genomic profiling and tumor mutational burden in parathyroid carcinoma: a nationwide real-world study from Japan.

PURPOSE: Parathyroid carcinoma (PC) is an extremely rare endocrine malignancy with limited treatment options for unresectable or recurrent cases. With the increasing use of comprehensive genomic profiling (CGP), treatment based on genomic findings is becoming more common. However, the frequency and clinical significance of elevated tumor mutational burden (TMB) in PC remain unclear because previous studies have been limited by small sample sizes. METHODS: We retrospectively analyzed genomic and clinical data of patients with PC registered in the Center for Cancer Genomics and Advanced Therapeutics database in Japan between June 2019 and March 2025. TMB values were obtained as reported by each CGP assay. TMB-H was defined as TMB&#x2009;&#x2265;&#x2009;10 mut/Mb for descriptive analyses. We also assessed genomic alterations, microsatellite instability (MSI) status, and clinicogenomic characteristics. RESULTS: Twenty-five patients with PC were included. The median assay-reported TMB was 4.0 mut/Mb (range, 0-35). Seven tumors (28.0%) had assay-reported TMB values of &#x2265;&#x2009;10 mut/Mb, including three (12.0%) with TMB&#x2009;&#x2265;&#x2009;20 mut/Mb. The most frequently altered genes were CDC73 (40%), TP53 (32%), and MEN1 (24%). No co-alterations were observed between CDC73 and MEN1 or between CDC73 and TP53. One tumor was MSI-high and was included in the TMB-H group. POLE alterations were detected in three cases, including two tumors in the TMB-H group. CONCLUSION: This nationwide, real-world study demonstrated that a subset of PCs showed elevated assay-reported TMB values and genomic features potentially related to abnormalities in DNA replication or repair pathways. These findings support the clinical relevance of comprehensive genomic profiling in identifying the molecular heterogeneity and potential therapeutic opportunities for this rare malignancy.

Humans

MicroRNAs and predicted targets in the switch from monolayered to spheroids of cholangiocarcinoma cells.

BACKGROUND: Extrahepatic cholangiocarcinoma (eCCA) is characterized by marked molecular heterogeneity and limited therapeutic options. MicroRNAs (miRNAs) are key post-transcriptional regulators of cancer-related pathways, but their contribution to tumor adaptation in physiologically relevant models remains poorly understood. Three-dimensional (3D) tumor spheroids better mimic in vivo conditions than conventional two-dimensional (2D) cultures. METHODS: We compared miRNA expression profiles in two eCCA cell lines (Sk-ChA-1 and Mz-ChA-1) grown as monolayers (2D) or multicellular tumor spheroids (3D). MiRNA profiling was performed using NanoString technology. Predicted targets were analyzed by over-representation analysis, and selected miRNAs and genes were validated by RT-qPCR and ELISA-based assays. RESULTS: 3D growth induced extensive miRNA remodeling, with distinct (54 deregulated in Sk-ChA-1 and 29 in Mz-ChA-1 cells) and partially overlapping signatures (miR-1283, miR-577, and miR-2113). Among the shared miRNAs, predicted targets included DUSP10 and RBFOX1, while in spheroids, cell-specific multiple miRNAs converged on shared targets (TNRC6B, SMARCAD1, ATG14, HMGA2, and CLOCK) displaying inverse expression patterns. The transcriptional program impacted MAPK signaling, enhanced EMT, and activated stress-adaptive networks but attenuated proliferation in 3D Sk-ChA-1 cells, while Mz-ChA-1 cells retained a more epithelial and proliferative profile. In this context, we point out the involvement of miR-19b-3p using anti-miR transfection experiments. CONCLUSION: Our findings reveal a miRNA-driven regulatory landscape associated with 3D growth in eCCA, linking tumor architecture to signaling rewiring and cellular plasticity, and highlight potentially druggable candidate targets and pathways to investigate as candidates using inhibitors or gene therapy-based interventions.

Humans

Multi-sampling allows intra-tumoral heterogeneity querying and vulnerability profiling in glioblastoma.

BACKGROUND: Glioblastoma (GBM) remains a devastating cancer with limited treatment options, largely due to its heterogeneity. While supramaximal resection has recently provided survival benefits, therapeutic profiling of different tumor compartments, particularly its infiltrative edge remains largely unexplored. METHODS: Here, we leveraged magnetic resonance imaging (MRI)-guided multi-sampling, collecting 2 cores and 2 margins per case, to query GBM heterogeneity. Whole-exome and RNA-seq with drug testing in two patient-derived 3D models were used to reveal similarities and differences in genomic and transcriptomic makeups, cellular compositions, and drug responses across cores and margins. Bioinformatics interrogations further identified response biomarkers. RESULTS: Mutation analysis showed that oncogenes exhibited a higher degree of spatial heterogeneity than tumor suppressor genes, regardless of MRI status. While the mesenchymal transcriptional subtype with extracellular matrix remodeling, stress response, and immune programs were preferentially enriched in enhancing cores, proneural tumors with neurological processes favored non-enhancing margins. Using a 15-drug GBM-targeted panel, ERK (ulixertinib) and PI3K pathway (paxalisib, CC-115) inhibitors showed preferential efficacy in enhancing cores and non-enhancing margins, respectively. The anti-apoptosis, pan-Bcl2 agent navitoclax and the epigenetic drug trotabresib represented the most effective, tumor-wide monotherapies. Importantly, drug combinations generally outperformed single agents across all regions. CONCLUSIONS: This work demonstrates the regional heterogeneity of therapeutic vulnerabilities in GBM ex vivo, showing various drugs with tumor-wide or MRI-enhancement informed activity. These findings offer preclinical bases of numerous monotherapies and drug combinations for future clinical trial design.

Humans

Omics in optic neuropathies: From molecular landscapes to personalized therapeutics.

Optic neuropathies comprise a heterogeneous group of disorders involving transient or permanent injury to retinal ganglion cells (RGCs) and their axons. Clinically, these neurodegenerative conditions manifest as dyschromatopsia, decreased visual acuity, and visual field defects, and in severe cases may ultimately lead to blindness and disability. The marked heterogeneity across disease subtypes, incompletely understood etiologies, and complex pathogenic mechanisms pose substantial challenges to precise diagnosis and effective treatment. Recent advances in omics technologies - including genomics, transcriptomics, proteomics, metabolomics, lipidomics, single-cell and spatial sequencing, and integrative multi-omics approaches - have ushered optic nerve degenerative disease research into an era of high-resolution comprehensive investigation. In this review, we summarize representative applications of omics approaches to elucidate genetic alterations, signaling dysregulation, metabolic reprogramming, and immune responses in optic neuropathies. We further discuss the emerging potential of multi-omics in identifying early diagnostic biomarkers and informing individualized therapeutic strategies. Finally, we provide a forward-looking perspective on the future trajectory of omics technologies and their prospects in both fundamental research and clinical translation, with the overarching aim of accelerating the bench-to-bedside transition in this critical eye disease field.

biomarkers

Genetic insight into lung neuroendocrine tumors: Notch and Wnt signaling pathways as potential targets.

BACKGROUND: The molecular landscape of lung neuroendocrine neoplasms is still poorly characterized, making it difficult to develop a molecular classification and personalized therapeutic approaches. Significant clinical heterogeneity of these malignancies has been highlighted among poorly differentiated histotypes and within the subgroup of well-differentiated neuroendocrine tumors (NET). Currently, the main prognostic factors of lung NET include stage, histotype, grade, peripheral location, and demographic parameters. To gain deeper insights into the genomic underpinnings of lung NETs, we conducted a pilot investigation to uncover potential genetic mutations and copy number variations (CNVs) implicated in their pathogenesis. METHODS: Formalin-fixed, paraffin-embedded intraoperative tumor biopsies and matched peripheral blood mononuclear cell samples were collected from six consecutive patients with lung NETs. The whole exome sequencing (WES) was performed to profile germline and somatic mutations, identify novel genetic alterations, and detect CNVs. Clinical and pathological data were systematically documented at diagnosis and during follow-up. RESULTS: The WES analysis identified a subset of mutations shared between germline and somatic; some were of particular clinical interest as they were associated with tumor proliferation and potential therapeutic targets such as the genes KDM5C, ATR, COL7A1, NOTCH4, PTPRS, SMO, SPEN, SPTA1, TAF1. These mutations were predominantly linked to chromatin remodeling and were involved in critical oncogenic pathways such as Notch and Wnt signaling. CONCLUSIONS: This pilot study highlights the potential role of NGS analysis on solid biopsy in the assessment of the mutational profile of lung NET. A comparison of germline and somatic mutations is critical to identifying putative tumor driver mutations. In perspective, the enrichment of a subpopulation of cancer cells in the blood, with one or more specific mutations, is information of enormous clinical relevance, either for prognosis or therapeutic decisions. Translational studies on large prospective series are required to establish the role of liquid biopsy in lung NET.

Humans

Digestive cancers: mechanisms, therapeutics and management.

Cancers of the digestive system are major contributors to global cancer-associated morbidity and mortality, accounting for 35% of annual cases of cancer deaths. The etiologies, molecular features, and therapeutic management of these cancer entities are highly heterogeneous and complex. Over the last decade, genomic and functional studies have provided unprecedented insights into the biology of digestive cancers, identifying genetic drivers of tumor progression and key interaction points of tumor cells with the immune system. This knowledge is continuously translated into novel treatment concepts and targets, which are dynamically reshaping the therapeutic landscape of these tumors. In this review, we provide a concise overview of the etiology and molecular pathology of the six most common cancers of the digestive system, including esophageal, gastric, biliary tract, pancreatic, hepatocellular, and colorectal cancers. We comprehensively describe the current stage-dependent pharmacological management of these malignancies, including chemo-, targeted, and immunotherapy. For each cancer entity, we provide an overview of recent therapeutic advancements and research progress. Finally, we describe how novel insights into tumor heterogeneity and immune evasion deepen our understanding of therapy resistance and provide an outlook on innovative therapeutic strategies that will shape the future management of digestive cancers, including CAR-T cell therapy, novel antibody-drug conjugates and targeted therapies.

Humans

A Patient-Derived Xenograft Repository Capturing Clinical and Molecular Heterogeneity of Large B-cell Lymphoma.

UNLABELLED: Large B-cell lymphomas (LBCL) are a clinically and molecularly diverse group of malignancies with a rapidly evolving therapeutic landscape that has introduced new areas of clinical need, such as post-CD19 chimeric antigen receptor T (CART19) progression. Patient-derived xenograft (PDX) models are an important tool for mechanistic studies and preclinical evaluation of new therapies and can be generated from a variety of clinical contexts that capture tumor-intrinsic resistance mechanisms. We therefore undertook a comprehensive effort to generate PDX models that encompass the molecular landscape of LBCLs and include important clinical scenarios for new drug development. Here, we describe the first 48 models within this publicly available repository, capturing the transcriptional and genetic subsets of LBCL. These models also include 23 generated from post-CART19 progression patient biopsies, which reproduce patterns of progression driven by CD19 mutation or expression loss, as well as tumor cell-intrinsic CART19 resistance that we validated in vivo. SIGNIFICANCE: Here, we describe X-LYMPH (Xenografts of Lymphoma), a publicly available and molecularly annotated PDX repository that captures the heterogeneity of LBCL. X-LYMPH includes models of CAR T-cell resistance, providing a shared foundation for mechanistic research and therapeutic development for lymphomas. See related commentary by Evgin and Steidl, p. 655.

Humans

Molecular profiling of exhaled breath condensate in respiratory diseases.

BACKGROUND: Respiratory disorders, , continue to pose a major global health burden. Their complexity and heterogeneity challenge accurate diagnosis, effective monitoring, and therapeutic decision-making. Exhaled breath condensate (EBC) provides a reliable, non-invasive means of sampling the molecular environment of the airways. AIM: This review presents the state-of-the-art in EBC-based omics approaches-particularly metabolomics and proteomics-to characterize molecular signatures associated with chronic respiratory (e.g. asthma, chronic obstructive pulmonary disease, and rhinitis) and infectious diseases (e.g. COVID-19). RESULTS: We critically examine findings from studies applying nuclear magnetic resonance (NMR), mass spectrometry (MS), and sensor-based technologies to analyze EBC across various respiratory conditions. NMR, valued for its reproducibility and minimal sample preparation, consistently discriminates among disease phenotypes, identifies distinct metabotypes, and monitors treatment response over time. MS-based approaches afford enhanced sensitivity and specificity, enabling detailed profiling of inflammatory mediators, such as lipid-derived eicosanoids and amino acid derivatives. Proteomic studies reveal protein-level alterations associated with inflammation and tissue remodeling. In COVID-19 and long COVID, metabolomic and volatile compound profiling distinguishes affected individuals from healthy controls suggesting clinical potential. However, inconsistent sample processing and lack of analytical standardization remain limiting factors. CONCLUSIONS: EBC profiling shows clear promise for improving diagnosis, monitoring, and stratification in respiratory medicine. Yet, translation into clinical practice is hindered by limited standardization and validation. Broader, longitudinal studies will be essential to establish robust molecular signatures across disease states. This review underscores the timely need to implement breathomics investigations to gain mechanistic insight into the underlying biology of respiratory diseases.

Humans

Molecular Landscape and Advanced Diagnostic Technologies for BRAF Mutations in Cancer: From Quantitative PCR and ddPCR to CRISPR-Based Platforms.

BRAF mutations are key oncogenic alterations across multiple malignancies, including melanoma, thyroid carcinoma, colorectal cancer, non-small cell lung cancer, glioma, and hairy cell leukemia. The most prevalent variant, BRAF-V600E, induces constitutive activation of the MAPK signaling pathway, promoting tumor progression and influencing therapeutic responsiveness. Accurate detection of BRAF alterations is therefore essential for molecular classification, prognostic assessment, treatment selection, and resistance surveillance. This review summarizes the molecular heterogeneity of BRAF mutations and critically evaluates current diagnostic methodologies. Conventional approaches such as allele-specific PCR and Sanger sequencing are compared with advanced quantitative platforms, including high-resolution melting analysis, droplet digital PCR, and next-generation sequencing, with emphasis on analytical sensitivity, mutation coverage, and clinical applicability. Emerging technologies such as CRISPR-based assays, rolling circle amplification systems, and nanoparticle-based biosensors and point-of-care diagnostic platforms are also discussed for their potential to enhance ultra-sensitive detection, particularly in liquid biopsy settings. These emerging tools are highlighted for their potential to enable ultra-sensitive, rapid, and decentralized mutation detection, particularly in liquid biopsy settings. Key challenges, including intratumoral heterogeneity, low allele-frequency variants, FFPE-associated artifacts, and clonal evolution under therapeutic pressure, are examined within a translational framework. In addition, we examine critical barriers to clinical implementation, including standardization, cost, and global accessibility of molecular diagnostics, and outline potential solutions through scalable technologies and decentralized testing strategies. We propose that optimal BRAF testing requires a mutation subclass-informed and clinically integrated strategy combining comprehensive baseline profiling with longitudinal molecular monitoring. Future diagnostic paradigms will likely integrate multi-omics data and artificial intelligence (AI)-assisted interpretation to refine precision oncology implementation. Looking forward, we propose that optimal BRAF testing will require integration of multi-omics profiling with AI-assisted interpretation, enabling automated variant classification, real-time clinical decision support, and improved prediction of therapeutic response and resistance.

Humans

Epigenetic modulators in triple-negative breast cancer: epigenetic modifications and future treatment perspectives.

Triple Negative Breast Cancer (TNBC), an aggressive type of Breast Cancer (BC) characterized by the loss of expression of Estrogen Receptor (ER), Progesterone Receptor (PR), and Human Epidermal growth factor Receptor 2 (HER2) protein. TNBC is quite heterogenous in nature with limited available therapeutic options due to the lack of defined molecular targets. Epigenetic abnormalities have been implicated in the onset, progression, immune escape, and resistance to treatment in TNBC. Important epigenetic modulations, include DNA methylation, histone lactylation, histone modifications, and chromatin remodeling. Global hypomethylation contributes to genomic instability, while promoter hypermethylation inhibits tumor suppressor genes, by dysregulating their expression, thereby promoting uncontrolled proliferation, EMT, metastasis, and immune evasion in TNBC. Targeting epigenetic modulators, have the potential to develop novel therapeutic interventions have been developed and being explored. These epidrugs have proven to be effective in preclinical and clinical trials when used in combination with chemotherapy, immunotherapy, or targeted therapy, reducing drug resistance and aberrant proliferation. Despite of the advancements, challenges like target specificity, precise biomarkers and treatment related toxicity are the major hurdles. The review comprehensively summarized the important epigenetic alterations as well as novel treatment strategies with potential clinical applications in TNBC.

Humans

Single cell mutational analysis of PIK3CA in circulating tumor cells and metastases in breast cancer reveals heterogeneity, discordance, and mutation persistence in cultured disseminated tumor cells from bone marrow.

BACKGROUND: Therapeutic decisions in cancer are generally guided by molecular biomarkers or, for some newer therapeutics, primary tumor genotype. However, because biomarkers or genotypes may change as new metastases emerge, circulating tumor cells (CTCs) from blood are being investigated for a role in guiding real-time drug selection during disease progression, expecting that CTCs will comprehensively represent the full spectrum of genomic changes in metastases. However, information is limited regarding mutational heterogeneity among CTCs and metastases in breast cancer as discerned by single cell analysis. The presence of disseminated tumor cells (DTCs) in bone marrow also carry prognostic significance in breast cancer, but with variability between CTC and DTC detection. Here we analyze a series of single tumor cells, CTCs, and DTCs for PIK3CA mutations and report CTC and corresponding metastatic genotypes. METHODS: We used the MagSweeper, an immunomagnetic separation device, to capture live single tumor cells from breast cancer patients' primary and metastatic tissues, blood, and bone marrow. Single cells were screened for mutations in exons 9 and 20 of the PIK3CA gene. Captured DTCs grown in cell culture were also sequenced for PIK3CA mutations. RESULTS: Among 242 individual tumor cells isolated from 17 patients and tested for mutations, 48 mutated tumor cells were identified in three patients. Single cell analyses revealed mutational heterogeneity among CTCs and tumor cells in tissues. In a patient followed serially, there was mutational discordance between CTCs, DTCs, and metastases, and among CTCs isolated at different time points. DTCs from this patient propagated in vitro contained a PIK3CA mutation, which was maintained despite morphological changes during 21 days of cell culture. CONCLUSIONS: Single cell analysis of CTCs can demonstrate genotypic heterogeneity, changes over time, and discordance from DTCs and distant metastases. We present a cautionary case showing that CTCs from any single blood draw do not always reflect metastatic genotype, and that CTC and DTC analyses may provide independent clinical information. Isolated DTCs remain viable and can be propagated in culture while maintaining their original mutational status, potentially serving as a future resource for investigating new drug therapies.

Bone Marrow

Molecular differences between poorly and well/moderately differentiated lung adenocarcinoma and their clinical implications.

BACKGROUND: Diagnostic and therapeutic techniques for lung adenocarcinoma (LUAD) have advanced rapidly. However, the morphology-based assessment of tumor differentiation commonly used in clinical practice has several limitations, including strong subjectivity, inability to reflect tumor heterogeneity, and limited prognostic predictive value. This study aimed to identify key genetic mutations associated with tumor differentiation features and explored their potential clinical impact of these molecular features on tumor prognosis and therapeutic response. METHODS: In this study, 196 LUAD tissue samples collected from Fujian Cancer Hospital between 2021 and 2023 were analyzed using integrated high-throughput sequencing and comprehensive bioinformatics approaches. Molecular differences between poorly differentiated tumors and moderately/well-differentiated tumors were characterized. The effects of these molecular alterations on tumor behavior and therapeutic response were examined, with the aim of exploring biomarkers associated with poor prognosis and treatment in LUAD. RESULTS: Our findings showed a significant quantitative difference in tumor mutation burden, EGFR co-mutations, patterns of co-occurrence resulting in distinct clinical outcomes. Among these alterations, mutations in LRP1B and TP53, as well as EGFR amplification, MET amplification, JAK2 deletion and CDKN2B deletion were significantly enriched in the poorly differentiated group, whereas EGFR mutations were significantly enriched in the moderately/well-differentiated group. We also identified MET amplification and LRP1B mutation as independent poor prognostic factors in LUAD. Moreover, a subset of poorly differentiated group exhibited DNA double-strand breaks possibly due to homologous recombination deficiency (HRD), along with frequent alterations of immune evasion-related genes. CONCLUSIONS: These findings provide novel insights into the molecular basis of LUAD and the development of novel targeted differentiation-related therapies and precision genome-guided treatments.

Lung adenocarcinoma (LUAD)