Search Results (87)

Tumor-agnostic therapies represent an evolving approach in oncology, shifting from conventional histology-based treatment models to strategies guided by molecular alterations. Regulatory approvals of therapies targeting tumors harboring genomic alterations such as NTRK and RET fusions, BRAF V600E mutation, and those with deficient mismatch repair (dMMR) and a high tumor mutational burden (TMB-H) have demonstrated clinical activity across multiple cancer types. However, responses to these therapies are not uniform across all tumors. This review examines the variability of clinical outcomes across different cancer histologies and the challenges associated with this tumor-agnostic treatment paradigm. Despite sharing the same molecular alterations, some malignancies, including pancreatic and colorectal cancers, demonstrate lower response rates due to tissue-specific resistance mechanisms such as bypass signaling pathways and co-occurring genomic alterations. We discuss how these biological differences influence treatment response and their implications for future drug development and clinical trial design. Addressing these biological and clinical complexities will be essential to optimize the use of tumor-agnostic therapies across diverse cancer types. Full article

Background/Objectives: Duchenne muscular dystrophy (DMD) is a fatal, progressive neuromuscular disorder caused by mutations in the dystrophin gene, leading to the absence of functional dystrophin protein. As the largest gene in the human genome, the DMD locus is highly susceptible to mutations, contributing to a prevalence of approximately 1 in 3800–6300 live male births worldwide. This review aims to provide a comprehensive and critical synthesis of current and emerging therapeutic strategies for DMD. Methods: We conducted a narrative review of the literature, integrating findings from clinical trials, regulatory approvals, and preclinical studies. We categorized therapeutic approaches into mutation-agnostic and mutation-specific strategies, with emphasis on the mechanism of action, clinical progress, and translational limitations. Results: Current standards of care, including corticosteroids and supportive interventions, remain foundational in disease management. Mutation-specific approaches such as exon skipping and adeno-associated virus (AAV)-mediated gene replacement can restore dystrophin expression, although clinical benefit remains variable and is influenced by factors such as mutation type, delivery efficiency, and durability. Emerging genome editing strategies offer the potential for permanent correction but face significant challenges related to delivery, safety, and scalability. Emerging mutation-agnostic therapies targeting inflammation, fibrosis, and membrane instability provide broader applicability but do not directly address the underlying genetic defect. Across modalities, key limitations include modest functional outcomes, safety concerns, and variability in clinical trial endpoints. Conclusions: The DMD therapeutic landscape is rapidly evolving, and future progress will likely depend on optimizing delivery platforms, improving durability, and integrating combination strategies to address the multifaceted nature of disease progression. Full article

Snakebite envenoming causes an estimated 138,000 deaths annually worldwide, with approximately 75% of fatalities occurring prior to arrival at definitive medical care. Even in regions where antivenom is available in hospitals, the absence of treatment options before a victim can reach definitive care results in delays of many hours before therapy is initiated. Manufacturing complexity, region-specific products, and the risk of anaphylaxis further limit the availability and use of antivenom in many regions. Reducing the persistently high mortality of snakebite envenoming requires both novel scientific approaches and partnerships that extend beyond traditional disciplinary and funding silos. This article describes the collaboration between Ophirex, a Public Benefit Corporation developing the oral secretory phospholipase A2 (sPLA2) inhibitor varespladib, and the United States military, which has identified a capability gap in snakebite treatment for forward-deployed personnel. The partnership was driven by a shared requirement for a shelf-stable, easy-to-administer, snake-species-agnostic therapy suitable for use prior to definitive medical care. A central insight of the program was that military operational requirements and global public health needs converged around the same product characteristics, enabling a strategically aligned development effort. From early proof-of-concept studies through regulatory pathway definition and advanced development, the Military–Ophirex partnership integrated operational requirements, regulatory planning, and iterative risk mitigation to advance manufacturing, nonclinical, and clinical development. This work provides both practical insights into complex drug development and a case study in how structured partnerships can carry innovation through translation in underfunded and operationally challenging conditions. Full article

Background/Objectives: Inherited retinal diseases (IRDs) represent a genetically heterogeneous group of disorders caused by mutations in over 280 genes with more than 3100 identified variants. While gene-specific replacement therapies have achieved landmark success with voretigene neparvovec (Luxturna) for biallelic RPE65-associated retinal dystrophy, developing individual therapies for each genetic subtype remains impractical. This review examines gene-agnostic therapeutic approaches utilizing neuroprotection and immunomodulation that target common pathophysiological mechanisms shared across multiple IRD genotypes. Methods: We reviewed the literature on neuroprotective and immunomodulatory gene therapy strategies for IRDs, focusing on neurotrophic factors and complement system modulation. Results: Neuroprotective approaches delivering neurotrophic factors—including pigment epithelium-derived factor (PEDF), ciliary neurotrophic factor (CNTF), rod-derived cone viability factor (RdCVF), brain-derived neurotrophic factor (BDNF), fibroblast growth factors (FGFs), glial cell line-derived neurotrophic factor (GDNF), and proinsulin—have demonstrated photoreceptor preservation across multiple preclinical IRD models regardless of the underlying genetic mutation. The recent FDA approval of CNTF cell-based gene therapy (Encelto) for macular telangiectasia type 2 validates this therapeutic paradigm. Complement system inhibition represents another gene-agnostic strategy, with intravitreal complement inhibitors approved for geographic atrophy secondary to age-related macular degeneration and gene therapy approaches targeting C3, C5, or delivering soluble complement regulators under investigation for IRDs. Combination strategies simultaneously addressing multiple pathogenic pathways may offer synergistic benefits. Conclusions: Gene-agnostic approaches targeting neuroprotection and immunomodulation offer a therapeutic paradigm capable of benefiting patients across the spectrum of IRD genotypes, potentially transforming treatment for conditions where mutation-specific therapies remain unavailable. Full article

Next-generation sequencing (NGS) has impacted the treatment landscape for mCRC, leading to improved outcomes through the use of molecularly targeted and immune checkpoint inhibitor therapies. The National Comprehensive Cancer Network (NCCN) and the American Society of Clinical Oncology (ASCO) recommend, at a minimum, initial testing to assess RAS, BRAF, HER2, and microsatellite instability (MSI)/mismatch repair (MMR) status, as these results determine therapeutic eligibility. Broader testing to identify the eligibility for tumor-agnostic therapy for a tumor mutation burden (TMB), NTRK gene fusions, and RET fusions is encouraged for all patients with advanced solid tumors. Patients with metastatic disease may develop progressive disease, often as a result of adaptive resistance mechanisms and selective therapeutic pressure on disease heterogeneity. Repeat biomarker testing at progression has the potential to define these resistance mechanisms and to guide the next therapy or clinical trial enrollment. While these practices have become more commonplace, unified guidelines have yet to be established. In this review of the literature, we evaluate the advantages and pitfalls of sequential biomarker testing during disease progression in patients with mCRC. Full article

Background and Objectives: Diabetes mellitus represents one of the most prevalent chronic metabolic disorders worldwide, necessitating precise insulin dose management to prevent both acute and long-term complications. The optimization of insulin dosing remains a significant clinical challenge, as inappropriate dosing can lead to hypoglycemia or hyperglycemia, each carrying substantial morbidity risks. Machine learning approaches have emerged as promising tools for developing clinical decision support systems; however, their practical implementation requires both high predictive accuracy and model interpretability. This study aimed to develop and evaluate an explainable machine learning framework for predicting insulin dose adjustments in diabetic patients. We sought to compare multiple ensemble learning approaches and identify the optimal model configuration that balances predictive performance with clinical interpretability through comprehensive SHAP and LIME analyses. Materials and Methods: A comprehensive dataset comprising 10,000 patient records with 12 clinical and demographic features was utilized. We implemented and compared nine machine learning models, including gradient boosting variants (XGBoost, LightGBM, CatBoost, GradientBoosting), AdaBoost, and four ensemble strategies (Voting, Stacking, Blending, and Meta-Learning). Model interpretability was achieved through SHapley Additive exPlanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME) analyses. Performance was evaluated using accuracy, weighted F1-score, area under the receiver operating characteristic curve (AUC-ROC), precision-recall AUC (PR-AUC), sensitivity, specificity, and cross-entropy loss. Results: The Meta-Learning Ensemble achieved superior performance across all evaluation metrics, attaining an accuracy of 81.35%, weighted F1-score of 0.8121, macro-averaged AUC-ROC of 0.9637, and PR-AUC of 0.9317. The model demonstrated exceptional sensitivity (86.61%) and specificity (91.79%), with particularly high performance in detecting dose reduction requirements (100% sensitivity for the ‘down’ class). SHAP analysis revealed insulin sensitivity, previous medications, sleep hours, weight, and body mass index as the most influential predictors across different insulin adjustment categories. The meta-model feature importance analysis indicated that LightGBM probability estimates contributed most significantly to the ensemble predictions. Conclusions: The proposed explainable Meta-Learning Ensemble framework demonstrates robust predictive capability for insulin dose adjustment recommendations while maintaining clinical interpretability. The integration of SHAP-based explanations facilitates clinician understanding of model predictions, supporting transparent and informed decision-making in diabetes management. This approach represents a significant advancement toward the clinical implementation of artificial intelligence in personalized insulin therapy. Full article

Background/Objectives: Tissue-agnostic therapy has transformed oncology by enabling treatment selection based on molecular alterations rather than tumor origin. Since 2017, nine U.S. Food and Drug Administration approvals across six biomarker classes have defined this paradigm. Thoracic and head and neck (H&N) cancers have been underrepresented in the registrational evidence supporting these approvals. This review systematically evaluated biomarker representation, histologic distribution, and clinical applicability of tissue-agnostic therapies in thoracic and H&N malignancies. Methods: A narrative systematic review was conducted using PubMed, ClinicalTrials.gov, and regulatory documents for all tissue-agnostic approvals between January 2017 and October 2025. Data were extracted from pivotal trials, including total enrollment, objective response rate (ORR), histologic distribution, and thoracic/H&N representation. Emerging biomarkers and resistance mechanisms were assessed from phase I–III studies and basket trials. Results: Nine tissue-agnostic approvals encompassing six biomarkers were identified: MSI-H/dMMR, TMB-High, NTRK, RET, BRAF V600E, and HER2 (IHC 3+). Across pivotal datasets (3800 patients), thoracic and H&N cancers accounted for fewer than 8% (n = 290) of enrolled patients. Thoracic representation was dominated by non-small-cell lung cancer (NSCLC) in RET, NTRK, and HER2 programs (150 patients, 4%), while small-cell lung, mesothelioma, and thymic carcinomas contributed <1% combined. H&N cancers comprised 140 patients (3–4%), primarily secretory salivary carcinoma in NTRK trials (n = 12–20), thyroid carcinoma in BRAF (n = 36) and RET (n = 45) programs, and rare HER2-positive salivary duct carcinomas. Conventional HNSCC and sinonasal cancers were limited to 1–2 cases per trial. Only two of nine trials (22%) reported prespecified CNS endpoints, and RNA-based fusion testing was employed in <40%, underscoring diagnostic variability and limited applicability. Conclusions: Although tissue-agnostic therapy has expanded the reach of precision oncology, thoracic and H&N cancers remain underrepresented in registrational evidence. Most approvals rely on single-arm basket studies with small, heterogeneous subsets that preclude histology-specific conclusions. Future research should prioritize histology-enriched trial designs, standardized molecular diagnostics, and real-world validation to establish reliable, equitable standards of care for these underrepresented malignancies. Full article

Background: Therapeutic resistance to CDK4/6 inhibitors (CDK4/6i) remains a critical barrier in HR⁺ breast cancer. While network-based approaches offer a route to identify salvage therapies, existing methods often rely on inconsistent centrality metrics or retrospective public transcriptomes, lacking a unified framework to translate topology into pharmacological actionability. Methods: We developed the Topology-Integrated Hubness Score (TIHS), a quantitative framework that integrates five orthogonal network metrics into a unified hubness vector. To rigorously validate this framework and overcome the limitations of public bulk datasets, we combined cross-cohort statistical benchmarking with original RNA-sequencing data generated from a laboratory-derived palbociclib-resistant model (MCF7-PR). TIHS was applied to prioritize repurposing candidates by overlaying network hubness with drug–target affinity profiles. Results: Methodologically, TIHS demonstrated robust cross-dataset stability (cosine similarity ≥ 0.98) and statistically outperformed single-metric approaches in predicting drug sensitivity. In application, the framework identified sorafenib as a top-ranked candidate for reversing CDK4/6i resistance. Experimental validation confirmed these predictions: sorafenib significantly resensitized resistant cells (IC₅₀ reduction from 6.57 μM to 1.15 μM), and molecular dynamics simulations supported stable binding to the TIHS-prioritized hub, FGFR3. Furthermore, functional assays involving siRNA-mediated knockdown validated that FGFR3 is mechanistically required for the sorafenib resensitization phenotype. Conclusions: This study presents TIHS as a mechanism-agnostic, experimentally validated bridge between resistance-state transcriptomes and clinical decision-making. By coupling computational prioritization with in vitro functional verification, we demonstrate that targeting topology-defined hubs is a viable strategy for overcoming therapy resistance. Full article

Background: In triple-negative breast cancer (TNBC), the addition of immunotherapy has significantly improved outcomes. Immune-related adverse events (irAEs) can be accelerated in patients with pre-existing autoimmune (AI) conditions. The treatment-response standardized protocol used in clinical care raises concerns about the need for right-sizing strategies. As the use of immunotherapy expands, recognizing toxicity from recurrence and optimizing response-adapted approaches are essential to balance cure with quality of survival. Case Presentation: A 38-year-old pregnant woman with a distant history of uveitis and psoriasis was discovered to have pregnancy-associated TNBC. Postnatally, she was treated with neoadjuvant chemotherapy and pembrolizumab, followed by wire-guided left breast wide local excision and sentinel lymph node biopsy of the left axilla. After surgery, residual cancer was noted. She continued adjuvant pembrolizumab and adjuvant radiotherapy 40.05 Gy/15 fr to the breast and nodes, followed by a 13.35 Gy/5 fr boost to the tumour bed (breast). Despite a persistent residual tumour, pembrolizumab was continued as per protocol in a response-agnostic manner. At the end of one year of adjuvant pembrolizumab, she developed progressive numbness and weakness in the ipsilateral arm, initially raising suspicion for local recurrence. Comprehensive MRI and PET-CT imaging did not identify recurrent tumour or new metastatic disease. Electromyography confirmed a lower-trunk brachial plexopathy without a structural cause. An immune-mediated process was diagnosed by a process of elimination. Despite treatment with 1st-line high-dose corticosteroids and 2nd-line intravenous immunoglobulin (IVIG), improvement was limited. Therapeutic plasmapheresis led to marked functional recovery and symptom resolution 20 months later. Discussion: Four main challenges are identified: (1) the diagnostic difficulty in identifying local recurrence or radiation injury from immune-related neuropathy; (2) the emerging therapeutic role of plasmapheresis in steroid-refractory irAEs; (3) the possible inconsistencies between rare toxicities observed in clinical trials vs. clinical practice; and (4) the limitations in response in adjuvant therapy, particularly in patients with coexisting AI conditions. Conclusions: Early recognition and accurate distinction from tumour recurrence, as well as support for plasmapheresis as a potential option in steroid-refractory presentations, have been shown to improve patient survival and symptom reduction. With increasing use of immunotherapy, real-world toxicity data, predictive biomarkers, and personalized treatment strategies are urgently needed to balance cure with long-term functional outcomes. Full article

ALS is a multistep disease, in which (epi)genetic, environmental, and age-related processes, including senescence, converge over decades to reduce resilience resulting in self-sustaining symptomatic disease. The multistep model visualizes five to six impactful events in sporadic ALS, but fewer in those carrying high-penetrance mutations, such as SOD1, FUS, or C9orf72 expansions. The timing, duration, and cumulative effects of specific steps are presumed to have individual variability but, the steps themselves are inferred since they have not been observed and remain agnostic as to biological identity. Nevertheless, the model gives an opportunity to integrate genetics, aging, environmental exposures, and systems-level vulnerability into a single framework. Acting as step modifiers, environmental exposures including trauma lower the threshold for step acquisition, accelerate the accumulation of steps, influence the anatomical site of disease onset, and unmask preclinical disease. Because ALS emerges from the gradual collapse of multiple layers of biological robustness, tackling a single pathway will be insufficient and the multistep model forces a reconsideration of therapeutic timing and strategies. Protection against early-life insults, anti-aging, and anti-senescent therapies may curtail step accumulation preventing ALS from exceeding threshold and disease manifestation. Full article

Ampullary carcinoma (AC) is a rare gastrointestinal malignancy with dual intestinal and pancreatobiliary differentiation, complicating diagnosis, staging, and treatment. This review synthesizes current epidemiology, pathology, and multi-omic data to outline a pragmatic care pathway: lineage-first at presentation, mutation-fast at progression. Histology remains the primary classifier: the intestinal subtype generally aligns with colorectal regimens, whereas pancreatobiliary and mixed subtypes favor pancreaticobiliary therapy. In selected fit patients, modified FOLFIRINOX may address mixed phenotypes. Next-generation sequencing adds precision by identifying therapeutically relevant alterations, including ERBB2/HER2 amplifications, MSI-high/dMMR, BRAF V600E, and rare NTRK or RET fusions, while KRAS mutations are enriched in pancreatobiliary tumors. We recommend early application of a rapid-core panel (KRAS/BRAF, MSI/dMMR, ERBB2/HER2, RNA-based fusions) to capture high-impact targets, followed by comprehensive profiling at first progression. Liquid biopsy, plasma circulating tumor DNA (ctDNA), or bile-derived DNA may complement tissue and help identify the dominant lineage. Research priorities include ampulla-enriched umbrella trials, explicit AC subcohorts in tissue-agnostic studies, and ctDNA-informed endpoints. This lineage-first, mutation-fast paradigm supports precision care and evidence generation in AC. Full article

Cancer of unknown primary (CUP) is evolving from a diagnosis of exclusion treated with empirical chemotherapy to a molecularly defined entity amenable to precision-based interventions. This heterogeneous entity, comprising 2–3% of all metastatic malignancies, encompasses diverse cancers with clinically occult primary sites at diagnosis after a thorough workup. Recent landmark trials including CUPISCO and Fudan CUP-001 have demonstrated significant survival improvements with molecularly guided therapies compared to empirical chemotherapy, fundamentally enhancing and complementing traditional organ-centric treatment paradigms. This review synthesizes the current evidence supporting molecular diagnostics, tumor-agnostic therapies, and precision-based approaches in CUP management. We examine the clinical utility of comprehensive genomic profiling, gene expression profiling, and liquid biopsy technologies, while addressing implementation challenges and future directions. The integration of molecular tumor boards and the emergence of tissue/tissue-of-origin agnostic therapies herald a new era where CUP transitions from therapeutic nihilism to personalized oncology. As molecular technologies advance and targeted therapies proliferate, CUP may no longer represent a diagnosis of exclusion but rather an opportunity for molecularly informed precision care. Full article

Background: H3K27-altered diffuse midline glioma (DMG) is a highly aggressive central nervous system malignancy with limited therapeutic options and poor prognosis. Precision medicine strategies that integrate molecular profiling with individualized treatment selection represent a critical avenue for improving outcomes. Case presentation: We describe a 31-year-old woman with H3K27-altered DMG who, after standard chemoradiotherapy, was treated with a personalized, mechanism-guided combination regimen based on her tumor’s molecular profile. Next-generation sequencing identified pathogenic alterations in ATRX, H3F3A, and NF1, with a high NF1 mutation allelic fraction indicating RAS/MAPK pathway activation. Immunohistochemistry demonstrated elevated phosphorylated mTOR consistent with PI3K/AKT/mTOR pathway upregulation. The individualized regimen comprised trametinib and everolimus for dual pathway inhibition, the tissue-agnostic agent dordaviprone (ONC201), metabolic modulation with 2-deoxy-D-glucose, and electric field-based therapy. At seven months, MRI showed approximately a 60% volumetric reduction in the enhancing tumor component, accompanied by marked T2-weighted signal regression. Clinically, the patient remained neurologically intact with a Karnofsky Performance Score of 100%. Conclusions: This case illustrates the potential clinical value of a genomics-guided, multimodal treatment strategy in H3K27-altered DMG. The systematic integration of comprehensive molecular profiling with mechanistically rational treatment selection may contribute to meaningful radiological and clinical benefit in this otherwise uniformly fatal disease. These observations support further investigation of individualized, pathway-targeted approaches in prospective studies and N-of-1 trial frameworks. Full article

Background: Adoptive cell therapy using genetically engineered recombinant T cell receptors (rTCRs) expressed in T cells (TCR-T cell therapy) provides precision targeting of cancer cells expressing tumor-associated or tumor-specific antigens recognized by the rTCRs. Standardized analytical tools are lacking to easily quantify receptor expression. Methods: To overcome this hindrance, a universal tagging system (UniTope & TraCR) was designed consisting of a minimal peptide epitope (UniTope) inserted into the constant region of the rTCR α or β chain and a high-affinity monoclonal antibody (TraCR) specific to this tag. Detailed biophysical, biochemical, and functional assays were performed to evaluate rTCR expression, folding, pairing, and antigen recognition, as well as antibody performance, using the UniTope & TraCR System. Results: Tagged rTCRs were stably expressed in human T cells with surface densities comparable to untagged rTCRs. The TraCR antibody bound UniTope with nanomolar affinity and no detectable cross-reactivity was observed for endogenous proteins expressed by human cells of diverse origin, importantly, including T cells of the natural T cell repertoires of multiple human donors. Functional assays confirmed that UniTope-tagged rTCRs preserved their antigen-specific cytokine secretion and cytolytic activity upon antigen-specific stimulation. The UniTope & TraCR System enabled robust detection of rTCR-expressing T cells by flow cytometry, and rTCR protein expression by Western blot or immunoprecipitation, supporting the quantitative assessment of receptor copy number and structural integrity. Conclusions: The UniTope & TraCR System provides a modular, construct-agnostic platform for monitoring engineered rTCRs, integrated into TCR-T cell therapies currently in development. Full article

Next-generation sequencing (NGS) is instrumental for clinical decisions on molecularly targeted therapy (TT). In pediatric oncology, TT is a relatively rare choice administered chiefly on a tumor-agnostic basis. The investigation enrolled 304 pediatric patients with extracranial solid tumors that were diagnosed and treated in 2018–2023. Tumor DNA was sequenced using a customized QiaSeq panel (Qiagen, Hilden, Germany) of genes known to be relevant for pediatric solid tumors, including ALK, BRAF, BRCA1/2, EGFR, FGFR1, KIT, MAP2K1/2, NF1, PDGFRA/B, PIK3CA, PTEN, PTPN11, RAS family genes, etc. The assay allowed detection of nucleotide substitutions and small insertions/deletions, as well as gene copy number alterations. TT sensitivity predictors were identified in 120/304 cases (39.5%): Tier II in 83 patients, Tier IB in 32 patients (almost always ALK in neuroblastoma, n = 31) and Tier IA in 5 patients: BRAF p.V600E (n = 3) and NF1 aberrations (n = 2). TT commenced in 21/304 cases (6.9%), often first-line or as a first relapse therapy (14/21 cases), combined with chemotherapy (TT-CT) in 13 cases. The median of TT duration was 10.9 (range 0.8–43.5) months for single-mode and 12.3 (0.3–61.5) months for TT-CT. Clinical benefit rate was achieved in 14/21 patients (66.7%). At the time of writing, nine patients (42.8%) have no progression and are still on treatment for 30.4 months (range 10.3–40.5) after the start of TT. The median time to the best response to TT was 6 (range 0.8–12.3) months. The tolerance was generally good: the therapy was discontinued for toxicity in only one case. The study provides a TT-focused prospective analysis still rare in pediatric oncology. The outcomes indicate satisfactory tolerance and promising efficacy of TT, prompting an update of current treatment standards for several pediatric cancers. Full article