FMS-like tyrosine kinase 3 (FLT3), a class III receptor tyrosine kinase, exhibits a mutation frequency of approximately 30% in acute myeloid leukemia (AML) patients and constitutes a critical therapeutic target. As representative type I and type II FLT3 inhibitors, respectively, gilteritinib and Quizartinib (AC220) are clinically employed in FLT3-mutant AML management. Gilteritinib inhibits both activated and inactivated FLT3 proteins, with additional inhibition of AXL targets to help overcome resistance. AC220 inhibits activated FLT3. The comet assay was systematically employed to quantify and compare DNA damage patterns induced by type I versus type II FLT3 inhibitors in mutant cells. The experimental results revealed that the DNA damage caused by AC220 was significantly higher than that caused by Gilteritinib. For strong DNA damage, FLT3 inhibitors can be combined with DNA damage repair inhibitors to target DNA repair defects. The results provide experimental support for the rational combination strategy of DNA damage-targeting drugs.

As the foremost endocrine system cancer, thyroid carcinoma exhibits an accelerating epidemiological trend across populations. Despite advances in treatment modalities, recurrence and metastasis remain challenges. The long non-coding RNA PVT1 (lncPVT1) has emerged as a conserved oncogenic regulator in multiple cancer types, yet its specific function in TC requires further exploration. Our research focused on examining how lncPVT1 affects glycolysis under both normoxic and hypoxic conditions using TC cell lines TPC-1 and K1. Overexpression of lncPVT1 significantly enhanced glucose consumption and lactate production under hypoxia, corroborating its ability to augment glycolysis. Further, lncPVT1 upregulated key glycolytic genes such as GLUT1, HK1, HK2, and PGK1, and facilitated TC cell proliferation. Mechanistically, lncPVT1 stabilized hypoxia-inducible factor 1α (HIF-1α) by impeding its degradation and leading to its accumulation. This accumulated HIF-1α then bound to specific regulatory sequences that control the expression of genes involved in glycolysis, ultimately activating these genes and boosting glycolytic activity. Our findings demonstrate that lncPVT1 regulates HIF-1α stability and glycolytic gene expression, advancing our understanding of TC metabolism and potentially revealing novel therapeutic targets.

The development of spatial transcriptomics (ST) technologies has enabled researchers to better understand cells' spatial organization and functional heterogeneity within their native tissue context. Spatial domain identification plays a crucial role in ST data analysis. However, most existing spatial domain identification methods do not fully exploit spatial information, and often fail to adequately integrate both local and global features, resulting in suboptimal spatial domain identification. We propose SLGCA, a novel method based on cross-level graph contrastive learning to address these challenges. SLGCA adopts a dual-channel learning mechanism, combining local-level contrastive learning based on spatial neighborhood information and global information contrastive learning across views, thereby significantly enhancing the accuracy of spatial domain identification. SLGCA can integrate multiple tissue sections without needing pre-alignment or external tools, eliminating batch effects and accurately identifying spatial domains across multiple slices. Experimental results show that SLGCA significantly outperforms the benchmark methods in spatial domain identification accuracy on ST data generated by multiple techniques. Moreover, SLGCA enables accurate dissection of tumor heterogeneity in human breast cancer datasets and effectively uncovers the heterogeneous tumor microenvironment in liver cancer, revealing two distinct fibroblast subtypes.

The high recurrence rate of tumor limits the growth of precision medicine, whereas the exploration of correlations in multimodal data enables mining of features linked to tumor recurrence, ultimately identifying prospective biomarkers. Nevertheless, existing multimodal approaches centered on genetic molecular data inadequately leveraged data structure and ignored the involvement of genes in the pathway or biological processes, thereby hampering interpretability of association models. In this study, a novel joint similarity nonnegative matrix factorization (JSNMF) model based on data-driven idea was proposed by adding pathway scoring data based on utilizing pathological images of tumor, gene expression data. The similarity network fusion model was applied to calculate the fusion matrices of the three-modality data with tumor recurrence as the label. Additionally, the prior information was calculated using the principal component analysis method, which was then applied to the joint nonnegative matrix factorization model with network regularization constraints. The solving efficiency of JSNMF model was enhanced by incorporating sparse orthogonality constraints on objective function. Experimental results demonstrate that incorporating prior knowledge enhances the search efficiency for joint patterns across multimodal data. The model identified recurrence-related common modules, including cellular features, genes, and pathways. Bioinformatics analysis indicated that the model can identify potential biomarkers associated with immune cell infiltration levels for recurrence diagnosis. Furthermore, the proposed method provides a new perspective for mining task-specific associations in multimodal data. This study also improves understanding of association patterns among genetic molecular features linked to tumor recurrence.

Alkylating agent-based chemotherapy is one of the main treatment options for patients with metastatic pancreatic neuroendocrine tumors (PanNETs).However, it favors the acquisition of a hypermutator phenotype, suggesting a potential benefit of immunotherapy.We aimed to describe the efficacy of immunotherapy in an international retrospective cohort of patients with metastatic well-differentiated PanNETs pretreated with alkylating therapy. The primary endpoint was progression-free survival (PFS) and the main secondary endpoint was the radiological objective response rate (ORR). We explored the impact of tumor mutation burden (TMB) and mismatch repair deficiency (MMRd), and evaluated variables associated with PFS.We included 64 patients with heavily pretreated PanNETs (median Ki-67 28%). Among 51 PanNETs with mutational profiling, 37 (73%) were TMBhigh (median 35 mut/Mb). Among 46 PanNETs with available MMR status, 18 (39%) were MMRd, representing 49% of all TMBhigh PanNETs. Immunotherapy consisted of a single (31%) or a dual (69%) immune checkpoint inhibitor. Median PFS was 3.2 months (95% CI, 1.3-5.0.3.0) and the ORR was 17%. Patients with TMBhigh PanNETs had longer PFS (median 3.8 vs. 2.3 months, p = 0.015) and higher ORR (30% vs. 0%, p = 0.002) compared with TMBlow/unk cases. Patients with MMRd PanNETs had longer PFS (median 8.9 vs. 2.7 months, p = 0.003) and higher ORR (44% vs. 7%, p < 0.001) compared with MMRp/unk. On multivariable analyses, MMRd predicted longer PFS (HR 0.42, 95% CI [0.20-0.82], p = 0.015).Overall, immunotherapy may be effective against alkylating-pretreated metastatic PanNETs exhibiting TMBhigh and MMRd. MMR immunohistochemistry and TMB assessment could be implemented in the routine assessment of alkylating-pretreated metastatic PanNETs.

CD40 is a T-cell co-stimulatory receptor targeted by next-generation immunotherapies. We conducted a pan-cancer transcriptome analysis of CD40, its ligand, and related immune markers to evaluate co-expression patterns and clinical outcomes.

Thyroid cancer is the most common endocrine malignancy, with an increasing incidence, particularly driven by differentiated thyroid cancers (DTC), including papillary thyroid carcinoma (PTC) and follicular thyroid carcinoma (FTC). Although DTC generally have excellent prognosis, dedifferentiated forms such as poorly differentiated thyroid cancer (PDTC) and anaplastic thyroid cancer (ATC) exhibit aggressive progression and poor outcomes. Understanding the tumor microenvironment (TME) is crucial for developing novel therapeutic strategies.

Lung adenocarcinoma (LUAD) treatment remains a substantial clinical challenge, warranting a thorough investigation of the molecular mechanisms underlying tumor progression. In our study, the expression patterns and clinical implications of the macrophage M1 related gene, membrane spanning 4-domains A1 (MS4A1) were assessed using quantitative real-time PCR (RT-qPCR), western blotting, and immunohistochemistry in LUAD. A co-culture system involving LUAD cells and macrophages assessed macrophage polarization and recruitment using RT-qPCR, flow cytometry, immunofluorescence, and macrophage chemotaxis assay. Additionally, transcriptome sequencing, tube formation, and co-immunoprecipitation assays demonstrated the roles and mechanisms underlying MS4A1 in HIPPO pathway and angiogenesis in cancer progression and M1 polarization. Furthermore, the efficacy of antagonists against angiogenesis and HIPPO pathway including ivonescimab and verteporfin was assessed in MS4A1 low tumor-bearing mouse receiving immunotherapy. Results showed that the significant prognostic association of MS4A1 expression was specific to LUAD. Furthermore, MS4A1 facilitated the malignant progression of LUAD by modulating macrophage M1 polarization, migration, and angiogenesis. Mechanistically, MS4A1 interacted with Yes-associated protein to regulate macrophage polarization and cancer progression through the HIPPO pathway. In vivo experiments also demonstrated that verteporfin inhibited the in-situ tumor progression and ivonescimab enhanced the efficacy of immunotherapy in MS4A1 low tumor-bearing mouse. The MS4A1/M1 macrophage axis was identified as a crucial regulator of malignancy in LUAD, indicating MS4A1 as a promising novel therapeutic target for advanced LUAD treatment.

While mismatch repair-deficient (dMMR) colorectal cancers (CRCs) exhibit strong immunogenicity and better response to immune checkpoint inhibitors, the more prevalent mismatch repair-proficient (pMMR) CRCs typically show poor T- cell infiltration and inferior outcomes. Profiling the limited tumor-infiltrating CD8+ T cells helps identify responders and guides new strategies to enhance their infiltration and function in pMMR CRC tumors. Our study reveals that the proportion and number of CD103-CD8+ T (CD103N) cells are significantly increased in pMMR CRC tissue compared to adjacent non-tumor tissue. Distinguish from CD103+CD8+ T (CD103P) cells with elevated TEX markers, these CD103N cells display a precursor exhausted T cells (TPEX) phenotype with elevated stemness properties, reduced exhaustion markers, and retained functional capacity to secrete anti-tumor mediators. Moreover, CD103N cells in pMMR CRC shared a substantial number of identical TCR clonotypes with both CD103P cells in tumor and CD103N cell in peripheral blood. In dMMR CRC patients, enrichment of TPEX-like CD103N cells is associated with a favorable prognosis following anti-PD-1 therapy, suggesting their association with clinical outcome. Our findings identify an expanded population of CD103N cells exhibiting a TPEX phenotype with anti-tumor potential in pMMR CRC, highlighting their promise as therapeutic targets for recruitment into the tumor microenvironment to enhance the efficacy of immunotherapy.

Diffuse large B-cell lymphoma (DLBCL) patients with co-expression of MYC (≥ 40%) and BCL2 (≥ 50%), classified as double-expressor DLBCL (DE-DLBCL), consistently exhibit poor prognosis with traditional first-line therapies. In order to address the unmet therapeutic needs in this high-risk population, this real-world study retrospectively reviewd 46 newly diagnosed DE-DLBCL patients from two centers to evaluate the efficacy and safety of zanubrutinib-based regimens. Key outcomes included complete response rate (CRR), objective response rates (ORR), progression-free survival (PFS), overall survival (OS) and adverse events. Univariate analysis was conducted to evaluate the impact of various prognostic factors on complete response. The median age was 57.8 years (range:20-81), with 45.65% of patients over 60 years old and 17.39% over 75 years old. Advanced-stage (III/IV) disease was present in 60.87% of patients at diagnosis, 78.26% had a non-germinal center B-cell (non-GCB) subtype, and 41.3% exhibited an International Prognostic Index score ≥ 3. The best CRR was 73.90% (95% CI, 58.90%-85.70%), and the best ORR was 95.70% (95% CI, 85.20%-99.50%). At a median follow-up of 15.7 months, the 3-year PFS and OS was 86.27% (95% CI, 75.37%-98.75%) and 89.79% (95% CI, 78.40%-100%) respectively. Multivariate analysis revealed that zanubrutinib-based chemotherapy regimen significantly improved CRR. Significant differences in PFS were observed across age, bulky disease, IPI score, and extranodal involvement stratification. Adverse events were mainly hematologic toxicities and fatigue. These findings suggest that zanubrutinib may serve as an effective component of first-line therapy for this population, with favorable tolerability.

Gastric cancer (GC), a malignant and highly proliferative disease, has profoundly impacts a substantial global population and is associated with several variables, including genetic, epigenetic, and environmental impacts. Global variance is associated with Helicobacter pylori infection and dietary factors.

Bladder cancer is a significant malignancy, for which prognostic prediction and understanding of the tumor immune microenvironment are crucial. B cells play a key regulatory role in this environment, making their study essential for advancing bladder cancer research.

Bisphenol A (BPA) is an endocrine-disrupting chemical that may contribute to cancer development. However, its role in lung adenocarcinoma (LUAD) remains poorly understood. This study aimed to investigate how BPA affects LUAD development by examining key genes involved in tumor progression and the immune microenvironment.

Epithelial ovarian cancer (EOC) remains a lethal epithelial malignancy. Immune-checkpoint inhibitors have entered management for recurrent/metastatic disease; yet durable benefit is confined to a subset, reflecting TGF-β-conditioned stromal barriers and organised T-cell exclusion. In this review we summarise advances from single-cell RNA and ATAC profiling and spatial transcriptomics that resolve fibroblast, tumour and immune programmes linked to TGF-β signalling, and appraise translational opportunities spanning selective pathway modulation, checkpoint combinations and spatial biomarkers. We also discuss enduring challenges-including site-specific heterogeneity across adnexal, omental and peritoneal niches, limited assay standardisation and a scarcity of predictive metrics-that temper implementation. By integrating TGF-β-informed readouts (e.g., INHBA+ cancer-associated fibroblast burden, periostin/fibronectin indices, MHC-I status and CD8-tumour distances) with PD-1-based regimens and TGF-β-axis agents (ALK5 inhibitors, Activin A neutralisation, NOX4-directed reprogramming), emerging strategies aim to restore antigen presentation, improve lymphocyte access and remodel tumour-stroma interfaces. Our synthesis provides an appraisal of the evolving landscape of TGF-β-informed precision immuno-oncology in ovarian cancer and outlines pragmatic standards and avenues for clinical translation. We hope these insights will assist researchers and clinicians as they endeavour to implement more effective, individualised regimens.

Advanced endometrial cancer (EC) poses significant therapeutic challenges due to molecular heterogeneity and immune evasion. Immune checkpoint inhibitors (ICIs) show promise, particularly in mismatch repair-deficient (MMRd) and POLE-mutated subtypes, but resistance remains a barrier. This review synthesizes recent advances in biomarker-driven immunotherapy for EC, focusing on predictive biomarkers (e.g., LRP2, FANCE, MSH2, miRNA signatures), combination strategies (ICIs with anti-angiogenics or PARP inhibitors), and challenges in clinical translation. We highlight the impact of tumor microenvironment components, emerging technologies like machine learning, and future directions for personalized immunotherapy. Standardizing biomarker testing and optimizing trial designs will be critical to overcome resistance and improve outcomes.

Metastasis is the most common cause of cancer patient deaths. It is a complex process strongly influenced by the extracellular matrix (ECM). A mass spectrometry analysis comparing ECM proteins from healthy mouse lungs versus metastatic lungs has previously been performed, and the basement membrane (BM) component nidogen-1 has been identified to be one of the most downregulated ECM proteins in metastatic lungs. Here, we investigated the role of stromal cell-derived nidogen-1 in metastasis. We found that nidogen-1 is expressed by fibroblasts but not cancer cells, and nidogen-1 is downregulated in breast tumors compared to healthy mammary gland. Using the HCmel12 melanoma model, we found that loss of stromal nidogen-1 causes increased lung metastasis. Using electron microscopy, we found that nidogen-1 knockout mice have defects in the lung alveoli, such as fragmented endothelium, poorly defined BM, and enlarged interstitium. This suggests that loss of nidogen-1 may cause BM defects, which compromise its barrier function, thereby increasing the ability of cancer cells to extravasate and colonize the lungs. Our findings provide novel insight into cancer-stromal interplay and the role of nidogen-1 at the metastatic niche.

Histone deacetylase 10 (HDAC10) is emerging as a critical modulator of tumor immunity, chemoresistance, and transcriptional plasticity in colorectal cancer. Its suppression has been linked to altered CD8+ T cell activity, increased p53 expression, and reduced programmed death ligand 1 levels, suggesting a potential role in immune evasion. However, mechanistic understanding of HDAC10's selective function, especially in shaping the tumor microenvironment, remains limited. We advocate for targeted investigations using isoform-selective inhibitors, functional in vivo studies, and immune subset profiling to clarify HDAC10's therapeutic relevance in colorectal cancer.

Lung squamous cell carcinoma (LUSC) is a common and aggressive malignancy. Necroptosis, a regulated mode of cell death, has been implicated in tumor immunity and oncogenic processes, yet the mechanistic involvement of necroptosis-related genes (NRGs) in LUSC pathogenesis remains unclear, necessitating systematic evaluation of their biological and clinical relevance.

Oral squamous cell carcinoma (OSCC) is one of the most frequent types of head and neck tumor. Keratinocytes play a crucial part in tumor cell growth but their role in OSCC remains unknown.

cBioPortal has established itself as a widely used platform for exploring and visualizing multidimensional cancer data. Additionally, users have the option to upload their own cancer study for a comprehensive experience. However, the uploading step can be challenging due to the numerous files required by the platform, as well as the meticulous review of genomic alterations that need to be included in the study. Therefore, there is an increasing need for efficient data management solutions to facilitate the creation of studies in cBioPortal and optimize user experience by streamlining research workflows. In this application note, we present Varan, an innovative data management tool developed to help users at the initial stage of cancer genomic studies' upload, enhancing the data preparation process. Varan addresses challenges related to data formatting, filtering variants based on annotation, metadata file creation, quality checks, and study versioning, thereby enabling researchers to shorten the preparation process time and have control over the type of data to be uploaded to cBioPortal. In conclusion, Varan significantly improves the efficiency and accuracy of preparing cancer genomic studies for cBioPortal, ultimately enhancing the user experience and advancing cancer research through streamlined data management.