Epidemiological data show that approximately 80% of cancer patients experience pain of varying degrees throughout the course of their disease, with nearly one-third experiencing severe pain, significantly impacting their quality of life and the effectiveness of antitumor treatment. Triple-negative (TN) breast cancer tissues typically exhibit increased stromal stiffness and abnormally elevated mechanical stress; these biomechanical alterations may amplify pain signals by activating mechanosensitive channels. Utilizing single-cell RNA sequencing analysis, this study aims to elucidate the potential biological links between fibroblast mechanotransduction and cancer-associated pain, thereby providing a theoretical basis for clinical diagnosis and treatment.

Dimensionality reduction and unsupervised clustering were used to identify cell types in TN breast cancer single-cell RNA sequencing data. To assess the association between pain and mechanical stimulation, we constructed a set of gene signatures associated with mechanical stimulation and pain and calculated scores using the Area Under the Curve Cell (AUCell). CellChat and SCENIC were used to reveal the communication networks and transcription factor regulatory mechanisms of fibroblast subtypes.

COL3A1⁺ fibroblasts derived from TN breast cancer are highly involved in biological processes such as extracellular matrix remodeling, collagen fiber formation, and mechanotransduction. To assess the association between pain and mechanical stimulation, we constructed a gene signature set related to mechanical stimuli and pain and calculated corresponding scores using the AUCell tool. Cell communication studies showed that COL3A1⁺ fibroblasts interact extensively with epithelial cells and other cells through laminin and collagen signaling pathways, potentially leading to mechanotransduction remodeling of the TN breast cancer microenvironment.

COL3A1⁺ fibroblasts demonstrate enhanced transcriptional profiles pertinent to collagen deposition and cytoskeletal reorganization, which are correlated with mechanotransduction signaling and may be connected with mechanical sensitivity in cancer-related pain. This study systematically characterizes the potential relationship between fibroblast-associated mechanotransduction characteristics and pain-related gene signatures at the single-cell level in TN breast cancer. These findings offer hypothesis-generating insights into the molecular landscape of tumor-associated pain, although additional experimental and clinical validation is necessary.

Automatic segmentation of ultrasound-based thyroid nodules can assist physicians in more efficiently and accurately assessing thyroid diseases. However, thyroid ultrasound imaging presents certain unique challenges, such as blurred boundaries of nodules, strong heterogeneity in tissue echoes, and limited contrast between the lesions and adjacent normal thyroid tissue, which hinder the precise identification of nodules in clinical assessment.

To overcome these obstacles, we propose a deep hybrid convolutional network, named UTNseg, for precisely automatic segmentation of ultrasound-based thyroid nodules.

UTNseg contains four newly designed modules upon TransUNet: (1) the spatial-channel feature strong capture (STransformer) module is designed to reinforce the ability of encoder on capturing spatial and channel features, (2) the redundant feature map utilization (RMU) module is devised to mitigate redundant information in the skip connections, (3) the composite convolution (CConv) module is newly designed to further preserve the key multi-scale features of the target thyroid nodules, (4) the lightweight edge refinement (LER) module is newly proposed to refine the initial segmentation outputs. UTNseg was evaluated on two publicly available ultrasound datasets of thyroid nodules (TN3K with 3493 images and DDTI with 637 images). Datasets were divided at the patient level, with 4000 training images (2000 images from TN3K and 2000 images from DDTI, augmented by random rotation, scaling, and horizontal flipping on 445 images), 761 validation images (698 images from TN3K and 63 images from DDTI), and 924 test images (795 images from TN3K and 129 images from DDTI). Additionally, separate experiments were performed on these two datasets in comparative experiments. And the performance was compared with six state-of-the-art segmentation methods (U-Net, TransUNet, TRFENet, UNeXt, TRFE+ and BPAT-UNet). Evaluation metrics mainly included Dice similarity coefficient (DSC) and 95th percentile Hausdorff distance (HD95). Statistical significance level was analyzed through the Wilcoxon signed-rank test, and the effect size was quantified by Cohen's d . Holm-Bonferroni correction was employed to correct for multiple comparisons.

On the TN3K dataset, UTNseg achieved 79.52% DSC and 16.32 HD95. On the DDTI dataset, UTNseg achieved 86.21% DSC and 12.76 HD95. On the hybrid dataset, UTNseg achieved 80.77% DSC and 14.56 HD95. These results showed that UTNseg achieved superior performance. Compared with state-of-the-art approaches, UTNseg was statistically significant ( p < 0.05 ), and the corresponding effect sizes were mostly medium or large, further quantifying the practical importance of the improvements.

UTNseg demonstrated excellent segmentation performance on the public dataset. Statistical significance and effect size analysis both indicate that the improvements are reliable and have practical significance.

To assess the pathogenicity of a novel duplication in the RP17 locus identified in a cone dystrophy proband with biallelic CEP290 variants. Structural variants (SVs) in this locus have previously been associated with dominant retinitis pigmentosa.

Inheritance of the duplication was assessed by breakpoint polymerase chain reaction (PCR). Ophthalmic evaluation included fundus examination, multimodal retinal imaging, and full-field electroretinogram (ERG). A proband-derived pluripotent stem cell line was differentiated into photoreceptor precursor cells (PPCs) and retinal organoids (ROs). Variant-induced mis-splicing of CEP290 was assessed by reverse-transcription PCR (RT-PCR) and long-read cDNA sequencing, and immunohistochemistry was used to assess photoreceptor morphology. Expression of GDPD1 was quantified by quantitative RT-PCR.

The proband and father carried the 324-kb duplication in the RP17 locus. The father was clinically unaffected, but the proband showed features of cone dystrophy, including reduced visual acuity, foveal abnormalities, diminished cone density, and preserved dark-adapted but absent light-adapted ERG responses. The compound heterozygous variants in CEP290 resulted in pseudoexon inclusion and exon 36 skipping in patient-derived retinal cells. Immunohistochemistry revealed altered ciliation and reduced trafficking of L/M opsin and rhodopsin in ROs. In silico modeling predicted that the novel RP17 duplication does not disrupt chromatin looping, and GDPD1 expression was not upregulated in patient ROs, in contrast to pathogenic RP17-SVs.

The cone dystrophy phenotype of the proband can be attributed to the CEP290 variants, whereas the novel RP17 duplication can be classified as likely benign based on the integrated evidence. These findings emphasize the importance of modeling and functional studies for accurately classifying RP17-SVs and preventing misinterpretation in clinical diagnostics.

Blinatumomab is the first globally approved bispecific T cell engager targeting the B-cell surface antigen CD19, and numerous clinical trials have demonstrated its significant efficacy in B-acute lymphoblastic leukemia (B-ALL) patients. However, with its widespread application, the problem of drug resistance is gradually becoming apparent. The specific mechanisms of drug resistance mainly include antigen escape, lineage switch, immune checkpoint pathway dysregulation and T cell exhaustion. In this review, the mechanisms of resistance to blinatumomab in B-ALL are systematically described, and relevant therapeutic strategies targeting these resistance factors are summarized to provide a reference for clinical diagnosis and treatment.

Chimeric antigen receptor T cell (CAR-T) therapy is a revolutionary progress in the current field of tumor treatment, especially showing remarkable potential in relapsed/refractory hematological malignancies. However, there are significant differences in efficacy among different patients, and such differences are affected by multiple clinical and biomedical factors. This review will discuss the current application status of CAR-T therapy in hematological malignancies, analyze the key factors influencing the efficacy, and summarize the latest research trends and development directions in this field, so as to provide references for clinical decision - making and scientific research innovation.

The development and progression of leukemia are driven not only by intrinsic genetic and epigenetic alterations in leukemia cells, but also by the dynamic remodeling of immune niches within the bone marrow microenvironment (BMM). Accumulating evidence has indicated that leukemic cells can reshape the immune microenvironment through cytokine secretion, metabolic reprogramming, and other mechanisms, inducing T-cell dysfunction/exhaustion, impaired NK-cell effector functions, and immunosuppressive polarization of myeloid cells, thereby establishing a protective niche that facilitates disease progression, drug resistance, and relapse. In parallel, epigenetic mechanisms such as DNA methylation, histone modification, and RNA modifications bridge the phenotypic plasticity of leukemic cells and immune evasion processes by regulating antigen presentation, interferon signaling pathways, chemokine profiles, and immune checkpoint expression, thereby influencing the response to immunotherapy. This review centers on the core conceptual framework of "immune microenvironment remodeling - epigenetic regulation - drug resistance and relapse - combination therapy strategies". It systematically outlines the key immunosuppressive networks and their epigenetic foundations across different leukemia subtypes. Emphasis is placed on the advances and challenges in combining epigenetic drugs, such as demethylating agents and histone deacetylase inhibitors, with immune checkpoint inhibitors, BCL-2 inhibitors, and microenvironment-targeted therapies. Furthermore, it outlines future directions in microenvironment subtyping and precision interventions driven by single-cell and spatial multi-omics technologies, aiming to provide a theoretical basis for optimizing combination treatment strategies in leukemia.

Acute myeloid leukemia (AML) is a highly heterogeneous disease. This heterogeneity often leads to treatment failure or unsustainable efficacy, and high relapse rates as well as short progression-free survival (PFS) are closely associated with poor prognosis. Cyclin-dependent kinases (CDKs) play a central role in cell cycle regulation, transcription regulation, and metabolic processes, and their aberrant expression or dysfunction is considered as one of the key drivers of AML progression. Recent studies have increasingly focused on CDK inhibitors, aiming to address drug resistance and improve prognosis. Although some CDK inhibitors have shown promising anti-AML potential, challenges such as off-target effects and systemic toxicity remain daunting. This review systematically summarized the research progress of CDK inhibitors in the treatment of AML, with a particular focus on the results of preclinical studies and clinical trials targeting CDKs in AML, such as CDK2, CDK4/6, CDK7, and CDK9. In addition, the limitations of current therapeutic applications of CDK inhibitors were discussed, and potential strategies to overcome these challenges were explored, aiming to provide a reference for optimizing AML treatment regimens.

To analyze the expression level of heterogeneous nuclear ribonucleoprotein U (hnRNP U) and its correlation with prognosis in patients with multiple myeloma (MM), and explore the functional role as well as molecular mechanism of hnRNP U, thereby providing a theoretical basis for development of hnRNP U as a novel therapeutic target for MM.

Based on Gene Expression Omnibus (GEO) database, the expression of hnRNP U in plasma cell diseases and healthy controls was compared. Based on the GSE9782 dataset (n =264), patients were divided into high expression group (n =114) and low expression group (n =150) according to the median expression level of hnRNP U . Overall survival (OS) between the two groups was compared. RPMI 8226, NCI-H929 and MM.1S cell lines were selected as tool cell lines. Following knockdown of hnRNP U by shRNA, the cell proliferation was detected by CCK-8. The apoptosis of MM cells was analyzed by Annexin V/7-AAD staining, and cell cycle was detected by BrdU/DAPI staining followed by flow cytometric analysis. The effect of hnRNP U on the biological characteristics of human MM cells was explored. The effect of knockdown of hnRNP U on DNA damage response pathways was analyzed by Western blot.

Analysis of GSE5900 and GSE2113 datasets showed that the mRNA level of hnRNP U rose with the increased degree of malignancy of plasma cell diseases. Survival curve analysis of GSE9782 dataset showed that the high expression group of hnRNP U had a shorter OS than that of the low expression group. Down-regulation of hnRNP U in MM cell lines RPMI 8226, NCI-H929 and MM.1S could inhibit the cell proliferation, promote cell apoptosis and arrest the cell cycle. After knocking down hnRNP U, the expression levels of cleaved PARP and p-H2A.X, as the important markers of activated DNA damage pathway, were significantly increased in MM cells.

hnRNP U is highly expressed in several plasma cell diseases including MM, and the high expression of hnRNP U in MM patients predicts poor prognosis. Knocking down hnRNP U can inhibit the malignant progression of MM cells, which is possibly associated with aggravated DNA damage.

To explore the clinical features, treatment strategies, and prognostic factors of patients with new diagnosed Lymphoplasmacytic lymphoma/Waldenström macroglobulinemia (LPL/WM), thereby enhancing the diagnostic and therapeutic understanding of this disease.

Comprehensive clinical data were collected from 35 newly diagnosed LPL/WM patients at our hospital between December 2015 and June 2024. A systematic analysis was conducted on baseline characteristics, laboratory parameters, treatment regimens, and follow-up information. Survival analysis was performed using the Kaplan-Meier method, and a Cox regression model was applied to assess prognostic factors.

A total of 35 LPL/WM patients were enrolled, with a male predominance (91.4%) and a median age at diagnosis of 69 years (range: 32-83). The most common clinical manifestations were fatigue (45.7%), lower limb edema (28.5%), and lymphadenopathy (62.9%). Laboratory findings revealed anemia in 88.6% of patients. The vast majority (94.3%) secreted monoclonal IgM, one patient secreted monoclonal IgG, and one patient had both monoclonal IgM and IgG. The light chain type was predominantly kappa (77.1%). Molecular genetic testing showed a MYD88 L265P mutation rate of 82.4% (28/34), while the CXCR4 mutation rate was lower (17.6%, 3/17). The overall response rate was 82.4% in the treatment group containing Bruton's tyrosine kinase inhibitors (BTKi) and 66.7% in the non-BTKi treatment group. With a median follow-up of 70 months, one patient was lost to follow-up and 14 patients died. The median overall survival (OS) for the entire cohort was 71 months. Univariate analysis identified β₂-microglobulin ≥4 mg/L at diagnosis was associated with OS (P =0.036) and PFS (P =0.021). Multivariate analysis confirmed β₂-microglobulin ≥4 mg/L at diagnosis as an independent adverse prognostic factor for OS (HR =3.854, P =0.025) and PFS (HR=3.201, P =0.030), while receiving BTKi-containing therapy was identified as a protective factor for OS (HR=0.312, P =0.047).

This study confirms that elevated β₂-microglobulin levels are an independent adverse prognostic factor in patients with LPL/WM. In our center's cohort, patients receiving BTKi therapy achieve higher response rates and longer OS.