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Discovery of NAT-6-321056 as a novel modulator of VEGFR2 signaling to suppress tumor angiogenesis.

Vascular endothelial growth factor receptor 2 (VEGFR2) is a master regulator of angiogenesis and cancer progression. However, current VEGFR2 modulators face significant challenges, including off-target toxicity and acquired resistance, underscoring the urgent need for novel therapeutic agents with improved efficacy and safety profiles. Here, we reported that virtual screening of 39,442 natural products from the ZINC natural products-derived library, coupled with molecular docking and molecular dynamics (MD) simulations to evaluate the binding stability of candidate compounds, identified NAT-6-321056 as a highly promising modulator of VEGFR2 signaling. Biological evaluations demonstrated that NAT-6-321056 exerted potent inhibition on the growth of a broad spectrum of cancer cells, including both solid tumors and hematological malignancies. In EA.hy 926 endothelial cells and SK-N-DZ neuroblast cells, the compound significantly suppressed proliferation, migration, and invasion. Microscale thermophoresis (MST) confirmed direct binding of NAT-6-321056 to VEGFR2 with favorable affinity. Kinase profiling against a panel of 33 kinases indicated that NAT-6-321056 exhibited a multi-kinase modulation profile. Mechanistic studies revealed that NAT-6-321056 suppressed the expression of hypoxia-inducible factor 1-alpha (HIF-1α) and was associated with reduced VEGFR2 phosphorylation and attenuation of the downstream ERK/JNK/AKT signaling pathways. Moreover, NAT-6-321056 exhibited robust in vivo anti-angiogenic effects in both the chick chorioallantoic membrane (CAM) assay and transgenic zebrafish vascular fluorescence imaging models. Computational absorption, distribution, metabolism, excretion, and toxicity (ADMET) prediction suggested acceptable drug-like properties. Collectively, these findings demonstrated that NAT-6-321056 is a promising modulator of VEGFR2 signaling with potent anti-angiogenic activity and represents a viable candidate for cancer therapy.

Vascular Endothelial Growth Factor Receptor-2

Cost-Effectiveness of Electronic Patient-Reported Outcome Measure Interventions in Cancer: Systematic Review and Parameter Extraction for Economic Modeling.

BACKGROUND: Complex digital interventions that integrate electronic patient-reported outcome measures (ePROM) into clinical practice in cancer have the potential to improve quality of life, increase survival, and reduce health resource use and costs. Such systems can help patients with cancer self-manage chemotherapy symptoms, reduce clinicians' workloads through automated decision support, and resolve problems earlier. However, more research on the cost-effectiveness of ePROM monitoring is needed. OBJECTIVE: This paper comprises two complementary components: (1) a systematic literature review summarizing and evaluating the quantitative and qualitative evidence related to the cost-effectiveness of ePROM monitoring and (2) a health economic model parameter extraction. We also conducted supplementary targeted searches and scoping to provide context to our findings. METHODS: We searched Ovid (including MEDLINE and Embase), Scopus, and the International Health Technology Assessment Database for original English-language papers published on or before March 2025 using search strings that combined terms related to ePROMs, health economics, and cancer/oncology. We included papers reporting health economic-related outcomes for ePROM interventions designed for adult cancer populations and excluded screening tools and conference abstracts. RESULTS: We included 34 publications from 27 unique studies and identified and analyzed 26 ePROM-integrated interventions within these. Most (23/26) of the included interventions explicitly described some form of alert handling and automated decision support based on remote ePROM monitoring. Of the 34 publications, 5 presented full cost-effectiveness analysis results, of which 3 were highly uncertain and lacked clear differences in costs and health outcomes between ePROMs and standard care; conversely, 2 presented strong evidence of cost-effectiveness due to quality-of-life improvements, reduced hospitalizations, and potentially more autonomy in health-related travel (eg, ePROM-monitored patients can drive or walk to the hospital instead of using taxis or ambulances). A further 5 publications reported partial health economic results (eg, cost-consequence and budget impact), of which 1 detected no difference in strategies; in contrast, 4 reported lower health resource use and costs of ePROMs, mainly due to hospitalization reductions. Overall, 12 of the 27 studies included a qualitative component but mostly focused on user experience and design-related themes; only 2 of these addressed economic-specific themes (eg, changes in workflow and resource use due to ePROM implementation and integration), indicating some potential for time saving due to ePROM monitoring. CONCLUSIONS: Some ePROM-integrated interventions demonstrated cost-effectiveness in cancer care, but the evidence base remains limited. Where evidence does exist, cost-effectiveness appears driven by reduced hospitalization and improved quality of life. Qualitative research within the included studies rarely addressed economic questions. We provide a detailed parameter extraction for use in future economic modeling and recommend research priorities, including quantitative mapping of ePROM symptom data onto health resource use patterns, and qualitative work exploring how ePROM implementation affects clinical workloads and patient-perspective costs.

Humans

Prevalence of Claudin 18.2 Expression in Gastric and Gastroesophageal Junction Adenocarcinoma: A Systematic Review and Meta-Analysis.

BACKGROUND: Claudin 18 isoform 2 (CLDN18.2) has emerged as a clinically validated therapeutic target in gastric and gastroesophageal junction (GEJ) adenocarcinoma following the regulatory approval of zolbetuximab in combination with first-line chemotherapy. Accurate prevalence data at the clinically validated immunohistochemical threshold are essential for patient selection, healthcare resource planning, and treatment strategy. Reported prevalence estimates vary widely across studies due to differences in populations, methodologies, and immunohistochemical protocols. This systematic review and meta-analysis aimed to generate a robust pooled prevalence estimate of CLDN18.2 expression at the threshold used in pivotal phase III trials. METHODS: PubMed, Embase, and the Cochrane Library were searched from database inception through March 12th, 2026. Studies reporting CLDN18.2 expression in gastric or gastroesophageal junction adenocarcinoma using the ≥ 75% moderate-to-strong membranous staining threshold were included. Prevalence proportions were pooled using a random-effects model with logit transformation and restricted maximum-likelihood estimation of between-study variance. Heterogeneity was assessed using the I² statistic and Cochran's Q test, and a 95% prediction interval was calculated. Pre-specified subgroup analyses assessed antibody clone and geographic region, with additional exploratory analyses according to disease setting and specimen type. Sensitivity analyses were performed to assess the robustness of the pooled estimate. RESULTS: Twenty-two predominantly retrospective cohort studies comprising 12,173 patients were included. The pooled prevalence of CLDN18.2 positivity using a random-effects model was 33.99% (95% CI: 30.13%-38.07%; 95% prediction interval: approximately 18%-55%), with high between-study heterogeneity (I² = 92.4%). Subgroup analysis by antibody clone showed no statistically significant difference between studies using the 43-14 A clone (32.79%, 95% CI: 28.86%-36.97%) and those using other reported antibody clones (41.74%, 95% CI: 26.76%-58.42%; p = 0.281). One study with an unreported antibody clone was excluded from this subgroup analysis. Geographic subgroup analysis excluding the multinational Shitara et al. cohort demonstrated a non-significant trend toward higher prevalence in non-Asian populations (37.85%, 95% CI: 31.59%-44.54%) compared with Asian populations (32.10%, 95% CI: 27.28%-37.34%; p = 0.169). All three sensitivity analyses confirmed robustness of the pooled estimate. No significant evidence of publication bias was detected (Egger's test p = 0.56). CONCLUSIONS: Approximately one-third of patients with gastric and GEJ adenocarcinoma express CLDN18.2 at the clinically validated ≥ 75% threshold. However, because the included studies encompassed heterogeneous disease settings and were predominantly HER2-unselected, the pooled estimate should not be interpreted directly as the proportion of patients eligible for zolbetuximab. The estimate was robust across sensitivity analyses and provides an evidence base for understanding CLDN18.2 prevalence and biomarker-testing requirements. Standardisation of immunohistochemical assessment methods is warranted to reduce between-study heterogeneity in future research.

Humans

METTL14-mediated m6A modification of CCNE1 accelerates progression of myelodysplastic syndromes via MAPK-ERK and PI3K-AKT signaling pathways.

BACKGROUND: N6-methyladenosine (m6A) is the most common RNA modification and plays a key role in the initiation, progression, and relapse of multiple cancers, including hematologic malignancies. However, the role of m6A and m6A regulatory genes in myelodysplastic syndromes (MDS) remains unclear. This study aims to elucidate the function and molecular mechanism of methyltransferase METTL14 in MDS. METHODS: RT-qPCR was used to assess the expression of multiple m6A regulators, focusing on METTL14 in MDS patients and cell lines. METTL14 overexpressing and knockdown cell lines were established, and CCK-8, EdU, and flow cytometry assays were performed to explore the biological functions of METTL14.Dot blot, MeRIP-Seq, MeRIP-qPCR, RT-qPCR, and Western blot were employed to investigate the underlying molecular mechanism. RESULTS: Dysregulation of multiple m6A regulators was observed in MDS, among which METTL14 was upregulated. Elevated METTL14 expression increases MDS risk and adverse prognosis, emerging as a biomarker for poor prognosis. METTL14 promoted proliferation and cell-cycle progression of MDS cells while inhibiting apoptosis; corresponding changes were observed in cell cycle and apoptosis markers. METTL14 regulated cellular m6A levels. Downstream targets of METTL14 were enriched in cell cycle-related pathways, with CCNE1 identified as a critical target. Knockdown of METTL14, actinomycin D, or S-adenosylhomocysteine treatment reduced CCNE1 mRNA and protein levels. Furthermore, METTL14 activated MAPK-ERK and PI3K-AKT signaling via CCNE1 in an m6A-dependent manner, thereby promoting proliferative MDS cells' capacity. CONCLUSIONS: This study delineates a METTL14/m6A/CCNE1 signaling axis in MDS progression and suggests that METTL14-mediated m6A modification may be a potential therapeutic target for MDS.

Humans

Whole-Genome Deep Learning Predicts Chemotherapy Response in Colorectal Cancer.

Chemotherapy response in colorectal cancer (CRC) exhibits significant heterogeneity, with current clinical predictors failing to capture complex genomic determinants of resistance. We developed a hybrid deep learning framework integrating convolutional neural networks (CNNs) and bidirectional long short-term memory (BiLSTM) networks to analyze whole-genome somatic mutations, evolutionary conservation, chromatin accessibility, and 3D genome architecture in 2,546 TCGA patients. An attention mechanism identified predictive genomic regions. The model achieved an AUC of 0.92 (95% CI: 0.89-0.94) in cross-validation and 0.88 (95% CI: 0.85-0.91) in independent validation, outperforming clinical models (&#x394;AUC = +0.18, p < 0.001). Key predictors included non-coding variants in TP53, KRAS, and PIK3CA regulatory regions. Triple-positive patients (mutations in all 3 regions) had significantly worse progression-free survival (HR = 4.7, p < 0.001). Our framework enables accurate chemotherapy response prediction and reveals novel non-coding resistance mechanisms, advancing precision oncology in CRC.

Humans

Beyond risk factors: A capacity framework for cancer survivorship research.

Cancer survivorship research has identified numerous biological, behavioral, psychosocial, health care, and structural factors that influence recovery. However, these factors are typically studied as separate determinants rather than interacting influences. This commentary proposes available survivorship capacity as a unifying framework that explains how these diverse determinants collectively shape recovery and survivorship outcomes. Concepts from geroscience, health care delivery, rehabilitation, occupational therapy, and human factors science were synthesized to develop a conceptual framework of available survivorship capacity. The framework conceptualizes recovery as a function of the capacity remaining after competing health care and life demands draw upon survivors' finite physical, cognitive, emotional, social, financial, temporal, and health care resources. It generates testable propositions for measurement, intervention research, health care delivery, and implementation science while positioning available survivorship capacity as a common mechanism linking diverse determinants of recovery and identifying actionable targets for intervention. Available capacity offers a unifying conceptual framework for understanding heterogeneity in survivorship outcomes and intervention effectiveness while generating a research agenda for future survivorship science. Measuring and strengthening survivors' available capacity, while reducing unnecessary demands, may improve engagement in care, health behaviors, and long-term recovery.

Humans

ORBIT: Oncogenic Representation Learning via Bi-Prototype Contrastive Learning in Hyperbolic Space for cancer driver gene identification.

Accurate identification of cancer driver genes is crucial for precision oncology but remains challenging due to the complexity of integrating heterogeneous data and modeling dynamic biological systems. To address these limitations, we propose ORBIT (Oncogenic Representation Learning via Bi-Prototype Contrastive Learning in Hyperbolic Space). Our framework synergistically fuses multi-omics profiles with functional network data using a context-adaptive graph reweighting mechanism to capture cancer-specific dynamics. The model employs a bi-prototype contrastive learning strategy within hyperbolic space, which aligns gene representations around distinct driver and non-driver semantic anchors while preserving the intrinsic hierarchy of biological networks. Comprehensive evaluations demonstrate that ORBIT achieves highly competitive stability in pan-cancer analysis while consistently outperforming state-of-the-art methods in cancer-specific predictions. Furthermore, functional enrichment analysis confirms that the model effectively segregates core cancer pathways, and drug sensitivity profiling validates the clinical relevance of the identified drivers. By integrating hyperbolic geometry with context-adaptive learning, ORBIT offers a robust and interpretable paradigm for precision medicine. The source codes and datasets are publicly accessible at https://github.com/spcho-dev/ORBIT.

Humans

Insights into the regulation of the HOTAIR proximal promoter.

HOTAIR (HOX transcript antisense RNA) is a HOXC-cluster long intervening non-coding RNA (lincRNA) whose cancer relevance is tightly coupled to how its transcription is wired into hormone, hypoxia, inflammatory, and developmental signaling. HOTAIR is known to associate with cancer cell proliferation, motility, tumor invasion, and metastasis. The present mini-review focuses on the regulatory architecture and mechanistic complexity of HOTAIR transcriptional regulation, with emphasis on three organizing principles. First, we consider the impact of promoter choice between a canonical proximal promoter (P1), which supports the 2.2-2.4 kb transcript, and an alternative upstream promoter/TSS (P2), which contributes to context-dependent transcription initiation. Second, we examine the long-distance enhancer-promoter communication between HOTAIR distal enhancer and P1/P2. Third, we summarize the recent epigenetic and epi-transcriptomic mechanisms involved in HOTAIR transcript initiation and elongation. A combination of these events determines isoform-specific transcription to govern cell-type-, context-, and cancer specific modulation of HOTAIR expression that promotes tumor formation and cancer progression. Finally, the review proposes how large-scale RNA datasets, long-read sequencing, and isoform-specific studies can refine our understanding of this versatile lincRNA's regulation.

Humans

Proteomic profiling reveals that DPP4 overexpression increases cell adhesion, inhibits cell migration, and restores androgen sensitivity in prostate cancer.

Dipeptidyl peptidase-4 (DPP4), a serine protease with both enzymatic and non-enzymatic roles, has emerged as a context-dependent modulator of tumor progression. In the present study, we investigated the expression and function of DPP4 in androgen-sensitive and castration-resistant prostate cancer (CRPC) models. Proteomic analysis of androgen-resistant prostate cells overexpressing DPP4 identified the involvement of the cellular adhesion molecules pathway. In prostate cells, lentiviral-mediated DPP4 overexpression restored androgen receptor signaling, inhibited epithelial-to-mesenchymal transition, and reduced cell migration, whereas DPP4 silencing produced the opposite effects. We demonstrate that DPP4 expression is down-regulated in CRPC cells and that treatment with capsaicin (CAP), a bioactive compound derived from red peppers, restores DPP4 expression. Moreover, DPP4 restoration by CAP suppresses prostate tumorigenesis in the TRAMP mice in vivo model of prostate cancer. Our results suggest that DPP4 could be a new target for CRPC.

Male

In vivo genome-wide CRISPR screens identify FOXR1 as a suppressor of CD8+ T cell antitumor immunity.

T cell dysfunction critically limits the efficacy of T cell-based immunotherapies in solid tumors, yet the intrinsic regulators of T cell dysfunction remain incompletely understood. Through an in vivo genome-wide CRISPR screen in tumor-infiltrating CD8+ T cells, we identified Forkhead Box R1 (FOXR1) as a potent transcriptional suppressor of CD8+ T cell effector functions. Genetic ablation of FOXR1 significantly enhanced cytokine production and cytotoxic capacity in both murine and human CD8+ T cells, whereas its overexpression impaired T cell activation and effector molecule expression. Mechanistically, multiomics integration of RNA-seq, CUT&Tag-seq, and ATAC-seq revealed that FOXR1 binds directly to promoter regions of key effector genes, including IL2, GZMB, and PRF1, and represses their expression. Importantly, FOXR1 deletion in human anti-CD19 CAR T cells improved their efficacy against solid tumors, demonstrating that FOXR1 is a checkpoint of T cell effector function and targeting FOXR1 is a promising strategy to enhance CAR T cell efficacy against solid tumors.

Animals

Deciphering CD8+ T cell exhaustion in human cancers through single-cell and spatial transcriptomics.

Exhausted CD8+ T cells (Tex) within the tumor microenvironment (TME) represents a critical barrier limiting anti-tumor immune responses. Tex cells are characterized by upregulated inhibitory immune checkpoint receptors, reduced cytotoxicity, and functional heterogeneity. Their genomic features and regulatory networks remain poorly defined, and only a minority of patients respond to immune checkpoint blockade (ICB) therapy. Single-cell RNA sequencing (scRNA-seq), through high-resolution transcriptomic profiling, has revealed diverse Tex subpopulations, identified subpopulation-specific marker genes and regulatory pathways. Spatial transcriptomics has further mapped the spatial distribution of Tex and their interaction networks with immune cells, tumor cells, and stromal cells, elucidating the impact of spatial heterogeneity on Tex functionality. Current studies indicate that the exhausted state of Tex is dynamic and modifiable, with functional differences among subpopulations closely associated with tumor progression and therapeutic response. However, the genomic characteristics, epigenetic regulation, and spatial interaction mechanisms of Tex require further exploration. This review summarizes recent advances in high-resolution omics technologies for precisely dissecting Tex heterogeneity, functional features, and interactions with other cells. It emphasizes the central value of optimizing Tex-targeted tumor immunotherapy strategies, providing theoretical foundations and directional guidance for developing more effective anti-tumor immunotherapies.

Humans

Liver Cancer Risk and Incidence Attributable to Human Immunodeficiency Virus: A Meta-Analysis and Population-Attributable Modeling Study of Over 1.2 Million Individuals.

HIV-induced immune suppression and chronic inflammation elevate the risk of cancer progression. We conducted a systematic review and meta-analysis of studies published between January 1, 1984 and October 13, 2023 to assess the association between HIV infection and liver cancer. People living with HIV (PLHIV) had a higher risk (pooled relative risk&#x2009;=&#x2009;3.36, 95% CI: 2.72-4.15). The global PAF for HIV-attributed liver cancer was 1.43% in 2019, with a three-fold increase over the past 30&#x2009;years. The Asia-Pacific region recorded the second highest new cases of HIV-attributed liver cancer in 2019, and the highest age-standardized incidence rate (ASIR) in Eastern and Southern Africa. Particularly, the ASIR of HIV-attributed liver cancer increased rapidly in Eastern Europe and Central Asia, with the highest estimated annual percentage change reaching 22.98%. PLHIV have an increased risk and incidence of liver cancer. In regions with high burden of HIV-attributed liver cancer, it is essential to integrate prevention and effective treatment for HIV, viral hepatitis, alcoholic liver disease, nonalcoholic steatohepatitis, and liver cancer.

Humans

Mining Stored-Specimen Studies for Information about Cancer Natural History.

The advent of new multicancer early detection tests and publication of early diagnostic results have generated expectations of clinical benefit from multicancer screening. The clinical benefit of a cancer screening test depends critically on disease natural history, which is typically learned from prospective screening studies. Retrospective studies of stored blood specimens are important in learning about a test's preclinical diagnostic performance but have rarely been used to infer natural history. The extent to which these studies might be harnessed to also learn natural history is discussed in the context of an article in this issue that infers the combined natural history of a range of cancers targeted by a multicancer early detection test using a case-control subsample of specimens from a large cohort study. The critical question concerns the identifiability of key transition rates in multistate models of natural history alongside state-specific sensitivities. The article suggests that these parameters are estimable within a Bayesian framework that leverages prior information about test sensitivity from diagnostic studies. We offer a heuristic discussion of identifiability in this setting and encourage formal study to determine the extent to which models with varying degrees of complexity may be learned from stored-specimen studies. See related article by Dai et al., p. 1535.

Humans

Matching-adjusted indirect comparison of fruquintinib versus ramucirumab in advanced gastric or gastroesophageal junction adenocarcinoma.

Aim: Fruquintinib (Fruq), a selective VEGFR 1/2/3 inhibitor, showed a significant progression-free survival (PFS) benefit in the Phase III FRUTIGA trial for advanced gastric/gastroesophageal junction (G/GEJ) adenocarcinoma. Ramucirumab (RAM), an anti-VEGFR2 antibody, demonstrated efficacy in the RAINBOW-Asia trial. This anchored matching-adjusted indirect comparison (MAIC) evaluated Fruq plus paclitaxel versus RAM plus paclitaxel as second-line therapy for G/GEJ adenocarcinoma in the absence of head-to-head trials. Materials & methods: Data from individual patients in the FRUTIGA study (N&#xa0;=&#xa0;703) and aggregated data from the RAINBOW-Asia study (N&#xa0;=&#xa0;440) were analyzed. Baseline characteristics were balanced using entropy balancing. The placebo plus paclitaxel (PBO&#xa0;+&#xa0;PTX) groups served as the common comparators. The primary outcome was PFS; secondary outcomes included overall survival, objective response rate (ORR) and disease control rate (DCR). Rates of treatment-emergent adverse events (TEAEs) were also compared as an exploratory outcome using an adjusted indirect risk difference. Sensitivity analyses included restricted mean survival time and simulated treatment comparison. Results: After weighting (effective sample size&#xa0;=&#xa0;564), baseline covariates were balanced. The anchored MAIC demonstrated that Fruq&#xa0;+&#xa0;PTX significantly improved PFS compared with RAM&#xa0;+&#xa0;PTX (HR: 0.70; 95% CI: 0.51-0.96; p&#xa0;=&#xa0;0.0280), corresponding to a 30% reduction in progression risk, with a significant restricted mean survival time benefit of 1.18&#xa0;months at 20&#xa0;months (95% CI: 0.08-2.27; p&#xa0;=&#xa0;0.024). Fruq achieved significantly higher ORR (OR: 1.76, 95% CI: 1.16-2.68; p&#xa0;=&#xa0;0.008) and DCR (OR: 1.94, 95% CI: 1.33-2.83; p&#xa0;<&#xa0;0.001). Overall survival was similar (0.97; 95% CI: 0.73-1.30; p = 0.8640). Subgroup analyses showed PFS benefits with Fruq in patients with ECOG PS 1, peritoneal metastases and two or fewer metastatic sites. In sensitivity analysis, the simulated treatment comparison also suggested a PFS benefit for Fruq&#xa0;+&#xa0;PTX (HR: 0.40, 95% CI: 0.32-0.50; p&#xa0;<&#xa0;0.0001). For any-grade TEAEs, the indirect comparison showed higher adjusted relative incidences of increased bilirubin with Fruq&#xa0;+&#xa0;PTX than with RAM&#xa0;+&#xa0;PTX (RD: 12.3%; 95% CI: 2.3-22.4%, p&#xa0;<&#xa0;0.05) and of hypokalemia (RD: 9.0%; 95% CI: 1.5-16.4%, p&#xa0;<&#xa0;0.05). For grade &#x2265;3 TEAEs, the adjusted relative incidence of decreased body weight was higher with Fruq&#xa0;+&#xa0;PTX than with RAM&#xa0;+&#xa0;PTX (RD: 2.9%; 95% CI: 0.6-5.2%, p&#xa0;<&#xa0;0.05). The adjusted relative incidences of increased AST, ALT and hypocalcemia were numerically lower in the fruquintinib group than in the RAM group. Conclusion: This MAIC indicates that Fruq&#xa0;+&#xa0;PTX may be more effective than RAM&#xa0;+&#xa0;PTX in second-line advanced G/GEJ adenocarcinoma, with potentially improved PFS, ORR and DCR, and similar overall survival. Safety analyses suggested generally comparable safety profiles across the two regimens. Fruq&#xa0;+&#xa0;PTX remains a valuable treatment option, offering important comparative evidence for clinical and health technology assessment decisions. Trial Registration: Clinicaltrials.gov identifiers: NCT07144995.

Adult

A multicenter randomized phase II/III trial of salvage treatment for refractory primary central nervous system lymphoma using tirabrutinib: JCOG2314 (ReSTART).

Primary central nervous system lymphoma (PCNSL) is an aggressive malignancy. Patients refractory to high-dose methotrexate-based induction therapy have an extremely poor prognosis. Although whole-brain radiotherapy (WBRT) is the standard salvage treatment and provides potent tumor control, early functional deterioration and late neurocognitive toxicity remain major concerns. A phase I/II trial on relapsed or refractory PCNSL demonstrated favorable efficacy and tolerability of tirabrutinib, a second-generation selective Bruton's tyrosine kinase inhibitor. Tirabrutinib's oral administration has enabled outpatient management. However, its clinical value for induction-refractory PCNSL remains uncertain. We designed a multicenter, randomized phase II/III trial (JCOG2314) to assess the non-inferiority of tirabrutinib to WBRT in overall survival and its potential to reduce functional deterioration and cognitive impairment. A total of 94 patients from 49 institutions will be enrolled over 4 years. The trial has been registered in the Japan Registry of Clinical Trials (study number: jRCT1031250645).

Humans

Prophylactic folinic acid prevents pemetrexed myelosuppression: A randomized trial toward safer treatment with chemotherapy in non-small cell lung cancer.

Background Pemetrexed is a cornerstone in advanced non-small cell lung cancer treatment. Although generally well tolerated, severe myelosuppression occurs in 26% of patients. Preventing chemotherapy-associated toxicity has become increasingly important with the introduction of osimertinib combined with pemetrexed-based chemotherapy. Due to substantial toxicity, this regimen is often not administered to frail patients. Folinic acid prophylaxis can mitigate pemetrexed-induced toxicity, however its preventive use has not been routinely studied. We aimed to investigate the efficacy of folinic acid prophylaxis to reduce myelosuppression. Methods Fifty patients treated with pemetrexed were randomized (1:1) to receive pemetrexed with or without oral folinic acid prophylaxis on days 2-4 after each chemotherapy cycle. The primary endpoint was absolute neutrophil count (ANC) after the first chemotherapy cycle. Secondary endpoints included ANC after the second cycle, grade neutropenia, treatment efficacy, renal function and incidence of dose modifications. Results Twenty-four patients received folinic acid and twenty-six served as controls. Higher ANC were observed in the folinic acid group after the first cycle (median 3.79; IQR 2.22-4.93 vs. 1.85; IQR 1.43-3.78; p.

Humans

Pharmacogenomic and drug interactions risk in cardio-oncology: A precision medicine perspective for India.

Cardio-oncology patients may face complex treatment regimens due to the concurrent existence of cancer and cardiovascular disease, leading to a considerable polypharmacy burden. This significantly increases the prospect of drug-drug interactions (DDIs) and gene-drug interactions. The majority of these interactions arise from comparable pharmacokinetic and pharmacological pathways associated with drug transporters and cytochrome P450 enzymes. The significance of pharmacogenomics in tailored treatment strategies are emphasised by the fact that genetic variability enhances individual differences in drug response, safety, and efficacy. This narrative review focus on the effects of key genetic polymorphisms (e.g., DPYD, CYP2C19, and CYP2C9) on the metabolism and efficacy of commonly prescribed anticancer and cardiovascular medications such as fluoropyrimidines, clopidogrel, and warfarin. In addition it explore the role of pharmacogenomic variants on drug-drug interactions within the field of cardio-oncology. The study ultimately emphasizes the necessity of precision medicine in India to address the genetic diversity and underrepresentation in global genomic databases. The absence of pharmacogenomic testing, infrastructural deficiencies, financial constraints, and insufficient clinical integration hinder the widespread use of this technology in India. The Genome India Project and other national initiatives establish the foundation for pharmacogenomic-guided therapy. Utilizing genetic data, together with artificial intelligence-based predictive tools, for clinical decision-making may enhance medication safety and yield optimal outcomes in Indian cardio-oncology patients.

Humans

Targeted variant analysis of feline mediastinal lymphoma using MassARRAY and clinical associations.

Lymphoma is the most commonly diagnosed cancer in cats. This study used the Agena MassARRAY to genotype 40 variants across 17 genes in feline mediastinal lymphoma. These variants have previously been identified in tumors, including T- and B-cell lymphomas, acute and chronic lymphocytic leukemias, and mast cell tumors, in humans, dogs, and cats, using various methods. They were selected based on high prevalence reported in prior oncology studies, potential relevance to targeted therapy, and suitability for multiplex PCR amplification. Pleural fluid samples were collected from 76 cats with mediastinal lymphoma, including 69 domestic shorthairs, two Persians, two Siamese, two Wichienmaat, and one Scottish Fold. The most prevalent variants were found in the BCL2, KIT, STAT3, and ZEB1 genes. Specifically, BCL2 c.83275986G&#xa0;>&#xa0;A and c.83275992G&#xa0;>&#xa0;T were present in 71.1% and 57.9%, respectively. In cats with variant-positive in KIT c.163965724C&#xa0;>&#xa0;CT significantly reduced (11&#xa0;days) compared to wild-type cats (94&#xa0;days) (p&#xa0;<&#xa0;0.001). In cats with variant-positive in STAT3 c.42942437C&#xa0;>&#xa0;CA, resulted in shorter median survival compared to wild-type cats (18&#xa0;days vs. 77&#xa0;days, p&#xa0;=&#xa0;0.006). The findings suggest that the variant panel could be useful for the genomic landscape of feline mediastinal lymphoma and warrant further validation.

Animals