Translational cancer research最新文献

Background: Hepatocellular carcinoma (HCC) ranks as a leading global cause of cancer-related mortality. Our study investigates the functional role between CD8⁺CD101⁺TIM3⁺ T cells (CCT) and CD8⁺CD101^-TIM3⁺ T cells in HCC, with a focus on their implications for immunotherapy.

Methods: We utilized single-cell RNA sequencing (scRNA-seq) to delineate the transcriptional landscapes and intercellular crosstalk of CCT and CD8⁺CD101^-TIM3⁺ T cells in HCC tissues. Clinical characteristics and scRNA-seq data were curated from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. For the differentially expressed genes (DEGs), Gene Ontology (GO) functional analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway-enrichment were performed. Prognostic model was constructed using univariate Cox and least absolute shrinkage and selection operator (LASSO) Cox regression model, validated through Kaplan-Meier survival curves and receiver operating characteristic (ROC) curves. A corresponding nomogram was also established to predict the prognosis of HCC patients.

Results: Our results indicated that T cell re-clustering revealed four functionally distinct subsets: CD8⁺ T cells, CD8⁺CD101^-TIM3⁺ T cells, CCT, and CD4⁺ T cells. Pseudotime trajectory analysis demonstrated that CD8⁺CD101^-TIM3⁺ T cells progressively differentiated into CCT, a process mediated by MIF-CD74/CXCR4 and SPP1-CD44 signaling axes. Enrichment analysis identified 1,281 CCT-specific genes enriched in mitochondrial electron transport and oxidative phosphorylation pathways. The prognostic model showed strong discriminatory power for overall survival (OS), achieving areas under the curve of 0.825, 0.873, and 0.865 at 1, 3, and 5 years in the training cohort, compared to 0.654, 0.636, and 0.644 in the validation cohort. The developed nomogram effectively predicts OS for HCC patients.

Conclusions: Our findings elucidate the functional alterations of CCT and precursor cells within the context of HCC. The novel prognostic framework provides actionable insights for stratifying patients likely to benefit from combinatorial immunotherapy and chemotherapy.

Background and objective: Most sarcomas have complex karyotypes, making them particularly challenging to study and treat due to their genetic diversity and aggressive nature. Animal models are essential in sarcoma research as they provide a comprehensive approach to studying tumour biology, progression and therapeutic responses that cannot be fully replicated in vitro. However, choosing the right model requires consideration of many practical aspects that have not been adequately addressed, particularly in sarcomas. Therefore, we aim to fill this gap by focusing on several animal models used in sarcoma research.

Methods: We performed a literature search in Scopus, MEDLINE and Web of Science using specific search terms to identify published original in vivo studies regarding different sarcoma subtypes, as well as selection tools.

Key content and findings: The most commonly used models are: syngeneic, genetically engineered mouse (GEM), chemically induced, cell-derived xenografts (CDX), patient-derived xenografts (PDX), humanised PDX (huPDX), and zebrafish. Each model has its own advantages, for example: CDXs enable high-throughput drug screening, PDXs preserve tumour heterogeneity in patients, while huPDXs most closely resemble the human immune response, However, there are various limitations to each model, including a lack of genetic diversity in syngeneic models, the complexity and time requirements of GEMs, and the short life span of cost-effective zebrafish. We also described various tools that can be used to help select the right animal model, including the International Mouse Strain Resource (ISMR) and the Mouse Tumour Biology Database (MTB), and inoculation methods (e.g., subcutaneus, orthopic).

Conclusions: With the right model, researchers can accurately study tumour behaviour, therapeutic responses and the basic mechanisms that underlie sarcoma development. We provide a practical guide for animal model selection though detailed discussion of model classes, inoculation routes, and endpoint to sarcoma-specific use cases as well as a list of active repositories/databases.

Background: Phosphoglycerate dehydrogenase (PHGDH), the key rate-limiting enzyme responsible for controlling the serine biosynthetic pathway, has been implicated in metabolic reprogramming in numerous cancers. Despite this, its significance and regulatory mechanistic relevance in gastric cancer (GC) have yet to be fully elucidated. Here, we sought to elucidate the influence of PHGDH on autophagy and malignant phenotypes in GC and to elucidate its mechanistic relevance in GC progression.

Methods: GC tissues and adjacent noncancerous tissues (n=7 pairs) were assessed for PHGDH expression by Western blotting, quantitative real-time polymerase chain reaction (qRT-PCR), and immunohistochemistry. GC cell lines with differential PHGDH expression were screened, and stable knockdown and overexpression models were established. Functional assays, including MTS assays, colony formation, wound healing, and Transwell migration assays, were performed to evaluate proliferation and motility, respectively. Western blotting and autophagic flux assays, as well as analyses of live-cells expressing mRFP-GFP-LC3, were used to evaluate ROS production and autophagy.

Results: PHGDH was upregulated in GC tissues (n=7 pairs) with a stage-dependent trend, though larger cohorts are needed to confirm this pattern. Downregulation of PHGDH curtailed MGC803 cell growth, migratory and invasive abilities, and triggered apoptosis, while overexpression enhanced cell motility. Mechanistically, PHGDH silencing increased ROS and HIF-1α levels, reduced mTOR phosphorylation, and facilitated autophagic flux, as demonstrated by elevated LC3-II and reduced P62 expression. These changes were further confirmed by 3-MA/CQ treatment and mRFP-GFP-LC3 imaging. Notably, PHGDH downregulation may indirectly promote the assembly of the ULK1 complex through the concomitant upregulation of FIP200 and ATG101, thereby initiating autophagy.

Conclusions: These data suggest that PHGDH plays a role in the progression of GC and may be considered a potential therapeutic target upon further confirmation in larger clinical studies.

Background: Patients with triple-negative breast cancer (TNBC) who failed to achieve pathological complete response after neoadjuvant chemotherapy (NAC) may have a poorer prognosis. This study aimed to explore the factors associated with the adverse outcomes of these patients, and to develop a nomogram model for predicting disease-free survival (DFS).

Methods: Patients diagnosed with TNBC at our institution between 2013 and 2022 were retrospectively evaluated. Clinicopathological and sonographic features associated with DFS were identified through multivariate Cox regression analysis to establish a nomogram model. The predictive performance of the nomogram model was assessed using receiver operating characteristic (ROC) curves and calibration curves.

Results: A total of 103 TNBC patients with residual lesions following NAC were included in this study, with 15 cases (14.6%) experiencing DFS events. Multivariate analysis revealed that the pathological type of non-invasive ductal carcinoma [hazard ratio (HR) =7.741, 95% confidence interval (CI): 1.928-31.081, P=0.004], lymph node involvement (HR =3.455, 95% CI: 1.152-10.359, P=0.027), and the presence of a hyperechoic halo on ultrasound images (HR =4.43, 95% CI: 1.164-16.852, P=0.029) were independent prognostic factors associated with poor DFS. Patients with multiple risk factors exhibited worse survival outcomes. The areas under the ROC curve for predicting 2-, 3-, 4-, and 5-year DFS rates in the nomogram model were 0.767, 0.786, 0.785, and 0.739, respectively. The calibration curves demonstrated excellent consistency between the nomogram-predicted and actual survival probabilities.

Conclusions: Our study developed a nomogram model to predict poor survival outcomes in TNBC patients with residual lesions after NAC, which may provide guidance for treatment strategies in high-risk populations.

Background: Triple-negative breast cancer (TNBC), defined by the lack of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) expression, is an aggressive subtype of breast cancer (BC) with limited therapeutic options. Signal transducer and activator of transcription 3 (STAT3) plays a critical oncogenic role in TNBC by promoting tumor progression and conferring resistance to apoptosis. (-)-epigallocatechin-3-gallate (EGCG), a bioactive green tea polyphenol, has been reported to inhibit STAT3 signaling and exert anti-cancer effects. However, its mechanistic effect on STAT3-mediated pathways in TNBC has yet to be fully elucidated. This study aims to investigate the effects of EGCG on TNBC cell proliferation, migration, and apoptosis, and to elucidate the underlying mechanisms involving STAT3-associated signaling and hydrogen sulfide-related pathways.

Methods: BT-549 TNBC cells were treated with EGCG to assess its effects on cell viability, migration, and apoptosis. STAT3 expression was assessed at both the transcript and protein levels. Apoptotic regulatory proteins, including Bax, Bcl-2, caspase-3, and caspase-8, were quantified to examine pathway involvement. Molecular docking and molecular dynamics simulations were conducted to evaluate the interaction between EGCG and STAT3, and to explore the potential inhibition of the JAK/STAT3/ERK signaling cascade.

Results: EGCG significantly reduced the viability, impaired the migratory capacity, and significantly enhanced the apoptosis of BT-549 cells. The treatment significantly downregulated STAT3 at both the messenger RNA (mRNA) and protein levels. EGCG further modulated apoptotic regulators by increasing the Bax/Bcl-2 ratio and promoting the activation of caspase-3 and caspase-8. Computational analyses revealed a stable binding interaction between EGCG and STAT3, which supporting the inhibitory effect on the JAK/STAT3/ERK signaling axis.

Conclusions: EGCG effectively suppresses STAT3-driven oncogenic signaling in TNBC by inhibiting cell proliferation, reducing migration, and inducing apoptosis through the modulation of key apoptotic pathways. Thus, EGCG could be a promising therapeutic candidate for targeting STAT3-mediated mechanisms in TNBC. Further research should be conducted to examine the clinical application of EGCG.

Background: Gastric cancer (GC) is an important malignancy of the digestive system with a high lethal rate. Emerging evidence implicates necrosis-related genes (NRGs) as key regulators of GC progression; however, their specific mechanisms of action within the tumor microenvironment (TME), particularly regarding immune and stromal cell interactions, require further characterization. This study investigates the functional roles and clinical relevance of NRGs in shaping the GC TME.

Methods: Utilizing clinical and transcriptomic profiles from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, we systematically evaluated 159 necrosis-associated genes in GC. Through differential expression analysis and functional validation, 24 genes demonstrating significant necrosis-related dysregulation were identified. Applying consensus clustering to transcriptomic profiles, we delineated three molecularly distinct necrosis subtypes in GC. These subtypes dynamically regulate distinct pathobiological cascades, functionally link to disease aggressiveness metrics, sculpt tumor immune ecosystems, and stratify patients into differential survival probability groups. Subsequently, we formulated a scoring system termed necrosis score, which was calculated to quantify the different NRG clusters of the individual GC.

Results: Integrative analysis revealed a significant negative correlation between necrosis scores and immunogenic biomarkers [programmed death-ligand 1 (PD-L1) expression, tumor mutational burden (TMB), microsatellite instability-high (MSI-H) status], identifying a patient subset with enhanced immunotherapy response rates and superior survival outcomes. The opposite was observed in the high-necrosis score group.

Conclusions: Collectively, necrosis subtypes are involved in TME, clinicopathological characteristics, and prognosis. Necrosis score could serve as a potential biomarker for GC and provide a new perspective on developing personalized immune therapeutic strategies for GC patients.

Background: Endoscopic submucosal dissection (ESD) is preferred for rectal neuroendocrine tumors (NETs), yet technical refinements are needed. This study aims to analyze the therapeutic efficacy of the injection mucosa knife (IMK) in ESD for rectal NETs.

Methods: This retrospective study analyzed data from patients with rectal NETs undergoing ESD at three tertiary hospitals from January 2021 to December 2024, with 86 cases in the IMK group and 74 cases in the traditional Dual knife (DK) group. Primary endpoints comprised operative time, R0 resection rate, and complication incidence. Logistic regression was used to identify risk factors for positive vertical margins.

Results: The preoperative demographic and clinical features of both groups were comparable (P>0.05). Notably, 72.5% of patients had tumors <5.0 mm, and 88.8% exhibited submucosal invasion. The IMK group showed shorter operative time (7.25 vs. 12.0 min, P<0.001) and lower muscular layer injury rate (7.0% vs. 21.6%, P=0.007) than the DK group, while R0 resection and postoperative complication rates were similar (P>0.05). Univariate analysis identified muscularis propria invasion as a risk factor for positive vertical margins.

Conclusions: In the ESD treatment of rectal NETs, the IMK can shorten operative time and reduce muscular layer injury compared to the traditional DK. Moreover, it achieves a low incidence of postoperative complications, making it worthy of clinical promotion and application.

Background: Osteoglycin (OGN), an extracellular matrix protein, has emerging but poorly characterized roles in cancer. This study presents the first pan-cancer investigation of OGN's expression patterns, clinical significance, immune interactions, and functional mechanisms.

Methods: Multi-omics data from Genotype Tissue Expression (GTEx), Cancer Cell Line Encyclopedia (CCLE), The Cancer Genome Atlas (TCGA), and Human Protein Atlas (HPA) databases were integrated. Differential expression was analyzed in normal tissues and tumor samples. Diagnostic utility was evaluated using area under the curve (AUC) of receiver operating characteristic (ROC) curve. Prognostic value was assessed via Kaplan-Meier [overall survival (OS); disease-specific survival (DSS); disease free interval (DFI); progression-free interval (PFI)] and Cox regression analyses. Immune microenvironment correlations were quantified using ESTIMATE, CIBERSORT, and gene set enrichment. Functional pathways were explored through gene set enrichment analysis (GSEA) and correlation with hallmark cancer signatures.

Results: OGN was broadly expressed in normal tissues (brain, liver, kidney) but significantly downregulated in most tumor types (P<0.05, TCGA; validated at protein level, HPA). OGN demonstrated high diagnostic accuracy in pan-cancer (AUC: 0.703-0.990), achieving near-perfect performance in colon adenocarcinoma (COAD) (AUC: 0.966) and thyroid cancer (THCA) (AUC: 0.920). High OGN expression correlated with improved survival outcomes in thymoma (THYM) (OS/DSS) and cholangiocarcinoma (CHOL) (PFI/DFI), but worse prognosis in lung adenocarcinoma​/liver hepatocellular carcinoma​ (LUAD/LIHC), indicating cancer-type specificity. OGN expression strongly associated with immune cell infiltration (macrophages, natural killer cells, T cells), chemokine signaling, programmed death-ligand 1 (PD-L1) levels, microsatellite instability (MSI), and tumor mutation burden (TMB). GSEA revealed enrichment of OGN-linked genes in epithelial-mesenchymal transition (EMT), angiogenesis, JAK-STAT, and PI3K pathways across cancers.

Conclusions: Our pan-cancer analysis highlights OGN as a context-dependent regulator linking extracellular matrix (ECM) remodeling with immune and angiogenic signaling. Its pan-cancer dysregulation, diagnostic/prognostic value, and crosstalk with immune evasion mechanisms nominate OGN as a promising multi-functional biomarker and therapeutic target.

Background: Accumulating evidence highlights the critical role of palmitoylation in tumorigenesis, including the regulation of oncogenic signaling pathways, metabolic reprogramming, and immune evasion mechanisms. This study was designed to systematically investigate the prognostic significance of palmitoylation-related genes in glioblastoma multiforme (GBM).

Methods: Through comparative transcriptome analysis of GBM and normal brain tissues based on The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx), we identified 343 palmitoylation-related differentially expressed genes (DEGs). Subsequently, 80 candidate genes were extracted from the constructed protein-protein interaction (PPI) network. By applying the machine learning algorithm-least absolute shrinkage and selection operator (LASSO) regression combined with Kaplan-Meier (K-M) survival analysis, we identified core genes significantly associated with patients' overall survival (OS). Furthermore, single-cell RNA sequencing (scRNA-seq) analysis demonstrated that GABRB2, NCF2, and GRIN2A were enriched in critical oncogenic pathways, including MYC targets and KRAS signaling. Meanwhile, they exhibited a significantly heterogeneous expression pattern in GBM.

Results: Palmitoylation-related gene expression was higher in GBM tissues than in normal brain tissue. GABRB2 and GRIN2A inhibited the proliferation and migration of GBM cell lines. NCF2 promoted the proliferation and migration of GBM cell lines.

Conclusions: This study was designed to systematically investigate the prognostic significance of palmitoylation-related genes in GBM. GABRB2, NCF2, and GRIN2A are expected to become new biomarkers for GBM.