Osteosarcoma (OS) is the most prevalent malignant tumor among adolescents, characterized by high recurrence rates and poor prognosis. Identifying novel prognostic biomarkers and therapeutic targets has become an urgent clinical need. We analyzed the GSE99671 dataset and identified TMED2, STC2, and GAL as high-risk genes for OS through LASSO regression and multivariate Cox proportional hazards modeling. Further examination of the expression levels of these genes in paired tumor and adjacent non-tumor tissue samples from OS patients ultimately pinpointed TMED2 as a key candidate gene. Preliminary analysis based on TCGA data suggested that TMED2 might influence osteosarcoma progression by regulating immune cell infiltration. Functional experiments demonstrated that shRNA-mediated knockdown of TMED2 significantly suppressed the proliferation, migration, and invasive capacity of osteosarcoma cells, while promoting the polarization of M0 macrophages toward the M1 phenotype. KEGG enrichment analysis indicated that TMED2's function is closely associated with the MAPK signaling pathway, and Western blot experiments further validated TMED2's role in activating this pathway. Mechanistic studies revealed that CKAP4 may serve as a downstream effector molecule of TMED2, with CKAP4 knockdown significantly affecting macrophage polarization and the activation status of the MAPK pathway. To further validate these findings, we established a xenograft mouse model, and the in vivo experimental results were consistent with those of the in vitro cell experiments, confirming that the TMED2/CKAP4 axis may promote osteosarcoma progression by regulating the MEK/ERK signaling pathway and macrophage polarization.
Glioma is the most common and aggressive type of primary malignant brain tumor. The N6-methyladenosine (m6A) modification widely exists in eukaryotic cells and plays an important role in the occurrence and development of human tumors. However, the function and mechanism of heterogeneous nuclear ribonucleoprotein C (HNRNPC), an RNA-binding protein and m6A reader in gliomas remains to be comprehensively and extensively explored. Herein, we found that HNRNPC mRNA and protein overexpression were associated with a poor prognosis for patients with gliomas, based on the data from TCGA, the CGGA, and the TMAs. Biologically, HNRNPC knockdown markedly repressed malignant phenotypes of glioma in vitro and in vivo, whereas ectopic HNRNPC expression had the opposite effect. Integrative RNA sequencing and MeRIP sequencing analyses identified interleukin-1 receptor-associated kinase 1 (IRAK1) as a downstream target of HNRNPC. The glioma public datasets and tissue microarrays (TMAs) data indicated that IRAK1 overexpression was associated with poor prognosis, and IRAK1 knockdown significantly repressed malignant biological behavior in vitro. Mechanistically, HNRNPC maintains the mRNA stability of IRAK1 in an m6A-dependent manner, resulting in activation of the mitogen-activated protein kinase (MAPK) signaling pathway, which was necessary for the malignant behavior of glioma. Our findings demonstrate the HNRNPC-IRAK1-MAPK axis as a crucial carcinogenic factor for glioma and the novel underlying mechanism of IRAK1 upregulation, which provides a rationale for therapeutically targeting epitranscriptomic modulators in glioma.
PURPOSE:This study aimed to explore the postoperative sleep experience of colorectal cancer patients with temporary stomas. METHODS:This was a descriptive qualitative study. Seventeen eligible patients with temporary stomas were purposively sampled and participated in face-to-face, semi-structured interviews. Data were analyzed using thematic analysis. RESULTS:Four main themes and 12 subthemes emerged: (1) Treatment-related physical symptoms disrupting sleep (postoperative pain and discomfort; nighttime stoma care burden; Drug-related adverse reactions). (2) Bidirectional reinforcement between psychosocial distress and sleep disturbances (nocturnal rumination in the context of self-perceived burden; nighttime exacerbation of negative emotions; Mutual aggravation of distress and sleep dysfunction). (3) Adaptive challenges to sleep environments and routines (hospital-environmental barriers to sleep; home sleep-environment reorganization; changes in sleep habits). (4) Patient-initiated sleep optimization strategies (self-management techniques for relaxation; dietary modifications; seeking professional support). CONCLUSIONS:The postoperative sleep experiences of patients with temporary stomas are complex, influenced by multiple factors including physical, psychological, and care-related aspects, and have relatively inadequate supportive measures.
Although poly(adenosine diphosphate-ribose) polymerase inhibitors (PARPis) and bevacizumab were approved as first-line maintenance for advanced ovarian cancer (OC), evidence comparing this combination with PARPi monotherapy, especially in BRCA-mutated/homologous recombination-deficient (HRD) patients, is lacking. This study compared combined fuzuloparib (a PARPi) plus apatinib (a vascular endothelial growth factor receptor-2 inhibitor) with either fuzuloparib or placebo as first-line maintenance in patients with advanced OC. Patients who had newly diagnosed, advanced OC and responded to first-line, platinum-based chemotherapy were randomized 2:2:1 to receive combined fuzuloparib (100 mg twice daily) plus apatinib (375 mg daily), fuzuloparib (150 mg twice daily) plus placebo, or double-placebo treatment. The primary end point was blinded independent review committee (BIRC)-assessed progression-free survival (PFS). Six hundred seventy-four patients were randomized to receive fuzuloparib plus apatinib (n = 269), fuzuloparib (n = 269), or placebo (n = 136). At the final analysis (November 1, 2024; 385 BIRC-assessed PFS events; median follow-up, 40 months), the median BIRC-assessed PFS was 26.9 months with the combination versus placebo (hazard ratio [HR], 0.57; 95% confidence interval [CI], 0.44-0.75; one-sided p < .0001) and 29.9 months with fuzuloparib monotherapy versus placebo (HR, 0.58; 95% CI, 0.44-0.75; one-sided p < .0001) compared with 11.1 months with placebo. A PFS benefit was observed regardless of germline BRCA1/2 mutation status. In homologous recombination-deficient patients (including those with BRCA1/2 mutations), combined fuzuloparib and apatinib produced a PFS similar to that of fuzuloparib (34.1 vs. 35.8 months, respectively); in homologous recombination-proficient patients, PFS had a trend favoring the combination (16.6 vs. 11.0 months; HR, 0.73; 95% CI, 0.45-1.19). Both treatments were well tolerated. Overall survival was immature. Both fuzuloparib and combination therapy improved PFS compared with placebo as maintenance therapy for patients who had newly diagnosed, advanced OC. Adding apatinib to fuzuloparib did not prolong PFS among homologous recombination-deficient patients. There was a PFS benefit trend among homologous recombination-proficient patients who received combination therapy compared with those who received monotherapy.
Objectives Intratumoral tertiary lymphoid structures (iTLSs) are prognostic biomarkers for hepatocellular carcinoma (HCC). This study aimed to develop a machine learning approach based on topologically distinct intratumoral heterogeneity (ITH) scores derived from CT images to predict iTLS status and patient outcomes. Methods In this multicenter study, patients from Centers 1 and 2 were divided into training (n = 475) and internal validation (n = 204) cohorts, with an independent cohort (n = 208) used for external validation from Center 3. Two complementary ITH scores were developed: a 2D score integrating local radiomics with global pixel patterns on the largest cross-sectional slice, and a 3D score extending this quantification to the entire tumor volume. A stacking ensemble classifier (2D3D-TD-ITH-Ensemble) incorporating clinicoradiological features and ITH scores was constructed to predict iTLS status. Model performance was compared with clinical and traditional radiomics models. SHapley Additive exPlanations (SHAP) analysis was used for interpretability. Disease-free survival (DFS) was assessed using Kaplan-Meier analysis. Results The 2D3D-TD-ITH-Ensemble demonstrated superior diagnostic performance compared to reference models. In the internal validation cohort, the ensemble model achieved an AUC of 0.904, outperforming the radiomics (AUC 0.887) and clinical models (AUC 0.811). Consistent results were observed in the external validation cohort, where the ensemble model yielded an AUC of 0.890, versus 0.864 for the radiomics model and 0.817 for the clinical model. SHAP analysis identified the 3D ITH score as the most influential contributor to model output. Furthermore, HCC patients with the presence of iTLS and lower 3D ITH scores exhibited significantly better DFS (p < 0.05). Conclusions The preoperative CT-based 3D ITH score serves as a robust non-invasive biomarker for predicting iTLS status and prognosis in HCC, potentially guiding stratified immunotherapy strategies.
