Chinese Journal of Cancer Research最新文献

Objective: Lymphovascular invasion (LVI) is a crucial step in metastasis and is closely associated with poor prognosis in patients with breast cancer. However, its clinical and molecular characteristics remain insufficiently defined. We aimed to identify molecular targets for LVI-positive (LVI+) breast cancer and predict patient prognosis via the analysis of genomic variations using targeted sequencing.

Methods: We established a large-scale targeted sequencing cohort of 4,079 breast cancer samples, which included 3,159 early-stage and locally advanced patients with available LVI statuses. Comparisons of somatic mutation frequencies and germline pathogenic/likely pathogenic (P/LP) mutation frequencies, mutational signature analyses, and mutual exclusivity and co-occurrence analyses were performed to identify key genomic features involved in LVI+ patients. Additionally, Kaplan-Meier survival analysis was conducted to further explore the prognostic value of co-mutations in LVI+ cases.

Results: We observed that LVI+ patients with the hormone receptor-positive/human epidermal growth factor receptor 2-negative (HR+/HER2-) and triple-negative breast cancer (TNBC) subtypes exhibited worse disease-free survival. Notably, HR+/HER2- and HER2+ breast cancer patients with LVI displayed distinct genomic features compared with LVI- tumors. Specifically, LVI+ HR+/HER2- tumors exhibited greater frequencies of somatic mutations in TP53 and ESR1, germline BRCA2 P/LP variations, and an enrichment of clock-like single-base substitution (SBS)1 mutational signatures. In contrast, LVI+ HER2+ tumors demonstrated a higher incidence of somatic PIK3CA mutations and increased activity of the apolipoprotein B mRNA editing enzyme catalytic polypeptide (APOBEC)-associated SBS2 signature. Furthermore, we revealed that the co-mutation of TP53 and NF1 could serve as a potential prognostic marker for LVI+ HR+/HER2- patients.

Conclusions: Our findings provide a comprehensive overview of the genomic characteristics of LVI in breast cancer, thereby offering insights that may help in refining precision treatment strategies for LVI+ breast cancer patients.

Objective: Radiotherapy (RT) is the definitive treatment for stage II nasopharyngeal carcinoma (NPC), which is classified as stages IA and IB in the latest ninth edition of American Joint Committee on Cancer (AJCC)/Union for International Cancer Control (UICC). A crucial question is whether concurrent chemo-radiotherapy (CCRT) could derive additional benefits to this recent "down-staging" subgroup of NPC patients. This study aimed to interrogate clinical and radiomic features for predicting 5-year progression-free survival (PFS) of stage II NPC treated with RT alone or CCRT.

Methods: Imaging and clinical data of 166 stage II NPC (eighth edition AJCC/UICC) patients were collected. Data were allocated into training, internal testing, and external testing sets. For each case, 851 radiomic features were extracted and 10 clinical features were collected. Radiomic and clinical features most associated with the 5-year PFS were selected separately. A combined model was developed using multivariate logistic regression by integrating selected features and treatment option to predict 5-year PFS. Model performances were evaluated by area under the receiver operating curve (AUC), prediction accuracy, and decision curve analysis. Survival analyses including Kaplan-Meier analysis and Cox regression model were performed for further analysis.

Results: Thirteen radiomic features, three clinical features, and treatment option were considered for model development. The combined model showed higher prognostic performance than using either. For the merged testing set (internal and external testing sets), AUC is 0.76 (combined) vs. 0.56-0.80 (clinical or radiomic alone) and accuracy is 0.75 (combined) vs. 0.62-0.73 (clinical or radiomic alone). Kaplan-Meier analysis using the combined model showed significant discrimination in PFS of the predicted low-risk and high-risk groups in the training and internal testing cohorts (P<0.05).

Conclusions: Integrating with clinical and radiomic features could provide prognostic information on 5-year PFS under either treatment regimen, guiding individualized decisions of chemotherapy based on the predicted treatment outcome.

Objective: Lynch syndrome (LS) increases the risk of various cancers, including colorectal cancer, endometrial cancer and gastric cancer (GC). The incidence of LS among microsatellite instability-high (MSI-H) GC and their association in South Korea remains underexplored. This study investigates LS-associated pathogenic germline variants in MSI-H GC patients using whole-exome sequencing (WES) on normal tissues.

Methods: This retrospective study included patients who underwent gastrectomy for GC at Soonchunhyang University Bucheon and Cheonan Hospitals from January 2011 to October 2023. Among 1,537 patients screened for MSI status, 127 (8.3%) were identified as MSI-H. WES was performed on normal tissues from 123 patients. Pathogenic/likely pathogenic (P/LP) variants in mismatch repair (MMR) genes were identified using in silico models and protein loss assessments in corresponding tumor tissues.

Results: Of the 127 MSI-H GC cases, characteristics aligned with typical MSI-H GC. The average age was 70.02 years, with 98 (77.2%) located in the lower body and 81 (63.8%) of the intestinal type. All five MSI markers were positive in 46.5% of cases, whereas four markers were positive in 27.6%. Of the MSI-H GCs, 10 LS candidates were identified. Three patients had known P/LP variants [MLH1 (c.1758dup), MSH6 (c.3261dup), MSH2 (c.1241T>C)]. Seven patients had variants of unknown significance (VUS) in MMR genes. Six (4.9%) patients were identified as having LS or possible LS, including one patient with the MLH1 (c.1153C>T) variant previously classified as VUS but now considered LS-associated.

Conclusions: This large-scale screening for LS in MSI-H GC patients using retrospective samples confirmed the lower incidence of LS than those of colorectal or endometrial cancer and GC patients in Western countries, emphasizing the need for clinical consideration in managing MSI-H GC patients.

Objective: Cytotoxic T lymphocytes (CTLs) play a crucial role in the therapeutic approach to hepatocellular carcinoma (HCC). Recent research has indicated that junctional adhesion molecule-like protein (JAML) enhances the antitumor activity of CD8+ T cells. Our study investigates the role of JAML+ CD8+ T cells in HCC.

Methods: We utilized time-of-flight mass cytometry and an orthotopic mouse model of HCC to examine histone modifications in tumor-infiltrating immune cells undergoing immunotherapy. Flow cytometry was used to assess CD4+ T cells differentiation and JAML expression in CD8+ T cells infiltrating HCC. Correlation analysis revealed a strong positive correlation between lactate dehydrogenase A+ (LDHA+) CD4+ T cells and JAML+ CD8+ T cells. Subsequently, we evaluated the therapeutic effects of an agonistic anti-JAML antibody, both alone and combined with immunotherapy. Finally, RNA sequencing was conducted to identify potential regulatory mechanisms.

Results: Immunotherapy significantly increased the percentage of CD8+ T cells infiltrating HCC and induced histone modifications, such as H3K18 lactylation (H3K18la) in CD4+ T cells. Flow cytometry analysis revealed that lactate promotes the differentiation of CD4+ T cells into Th1 cells. LDHA, an enzyme that converts pyruvate to lactate, plays a key role in this process. Correlation analysis revealed a strong positive relationship between LDHA+ CD4+ T cells and JAML+ CD8+ T cells in patients who responded to immunotherapy. Moreover, high JAML expression in CD8+ T cells was associated with a more favorable prognosis. In vivo experiments demonstrated that agonistic anti-JAML antibody therapy reduced tumor volume and significantly prolonged the survival of tumor-bearing mice, independent of the effects of anti-programmed cell death protein ligand-1 antibody (αPD-L1)-mediated immunotherapy. Pathway enrichment analysis further revealed that JAML enhances CTL responses through the oxidative phosphorylation pathway.

Conclusions: Activation of JAML enhances CTL responses in HCC treatment, independent of αPD-L1-mediated immunotherapy, providing a promising strategy for advanced HCC.

[This corrects the article DOI: 10.21147/j.issn.1000-9604.2024.02.02.].

Serotonin (5-hydroxytryptamine, 5-HT), a neurotransmitter known for its roles in the central nervous system, showing dual effects in various pathological conditions, including tumor progression and wound healing. This review explores the complex and context-dependent actions of 5-HT, highlighting its contrasting roles in promoting tumor growth and facilitating wound repair. 5-HT can enhance tumor growth, survival, and metastasis via its receptors, but it also accelerates wound healing by stimulating cell proliferation, migration, and angiogenesis. This duality emphasizes the intricate balance of 5-HT and its receptors in the body. We discuss the synthesis, storage, secretion, and metabolism of 5-HT, as well as the classification and mechanisms of its receptors (5-HTRs) in different cell types under pathological conditions. We further examine the potential roles of 5-HT in both tumor progress and wound healing, proposing targeted strategies for each disease state. For tumors, "blocking therapy" involving receptor antagonists or gene silencing may inhibit tumor progression, while "activation therapy" can stimulate wound healing by enhancing receptor activation on skin cells. Challenges in clinical application, including issues related to targeting, specificity, and dosage, are addressed, alongside the promise of nanotechnology for improving targeted drug delivery. The review also explores emerging research on 5-HT's interaction with the immune system, offering insights into potential immunotherapeutic strategies for both cancer and wound healing. By balancing 5-HT's diverse effects, personalized treatments can be developed to optimize therapeutic outcomes in both contexts.

Thyroid cancer (TC) is one of the most common endocrine system tumors, and its incidence continues to increase worldwide. Although most TC patients have a good prognosis, especially with continuous advancements in surgery, radioactive iodine therapy, chemotherapy, endocrine therapy and targeted therapy, the effectiveness of disease treatment has significantly improved. However, there are still some cases with a higher risk of death and greater aggressiveness. In these more challenging advanced or highly aggressive cases, tyrosine kinase inhibitors appear to be an effective treatment option. Unfortunately, these drugs are less than ideal in terms of efficacy because of their toxicity and potential for intrinsic or acquired resistance. Therefore, exploring new strategies targeting the metabolic characteristics of TC cells and overcoming drug resistance barriers in existing treatments have become key topics in the current field of TC research. In recent years, lipid metabolic reprogramming has gained attention as an important aspect of cancer development. Lipid metabolic reprogramming not only participates in the formation of the cell membrane structure, but also plays an important role in signal transduction and promoting cell proliferation. In particular, fatty acid (FA) metabolic reprogramming has attracted widespread attention and plays an important role in multiple aspects such as tumor growth, metastasis, enhanced invasive ability, immune escape, and drug resistance. Although TC is considered a disease that is highly dependent on specific types of metabolic activities, a comprehensive understanding of the specific mechanism of action of FA metabolic reprogramming in this process is lacking. This article aims to review how FA metabolic reprogramming participates in the occurrence and development of TC, focusing on the impact of abnormal FA metabolic pathways and changes in the expression and regulation of related genes over the course of this disease. By examining the complex interactions between FA metabolic disorders and carcinogenic signaling pathways in depth, we aim to identify new therapeutic targets and develop more precise and effective treatments for TC.

Objective: Early predicting response before neoadjuvant chemotherapy (NAC) is crucial for personalized treatment plans for locally advanced breast cancer patients. We aim to develop a multi-task model using multiscale whole slide images (WSIs) features to predict the response to breast cancer NAC more finely.

Methods: This work collected 1,670 whole slide images for training and validation sets, internal testing sets, external testing sets, and prospective testing sets of the weakly-supervised deep learning-based multi-task model (DLMM) in predicting treatment response and pCR to NAC. Our approach models two-by-two feature interactions across scales by employing concatenate fusion of single-scale feature representations, and controls the expressiveness of each representation via a gating-based attention mechanism.

Results: In the retrospective analysis, DLMM exhibited excellent predictive performance for the prediction of treatment response, with area under the receiver operating characteristic curves (AUCs) of 0.869 [95% confidence interval (95% CI): 0.806-0.933] in the internal testing set and 0.841 (95% CI: 0.814-0.867) in the external testing sets. For the pCR prediction task, DLMM reached AUCs of 0.865 (95% CI: 0.763-0.964) in the internal testing and 0.821 (95% CI: 0.763-0.878) in the pooled external testing set. In the prospective testing study, DLMM also demonstrated favorable predictive performance, with AUCs of 0.829 (95% CI: 0.754-0.903) and 0.821 (95% CI: 0.692-0.949) in treatment response and pCR prediction, respectively. DLMM significantly outperformed the baseline models in all testing sets (P<0.05). Heatmaps were employed to interpret the decision-making basis of the model. Furthermore, it was discovered that high DLMM scores were associated with immune-related pathways and cells in the microenvironment during biological basis exploration.

Conclusions: The DLMM represents a valuable tool that aids clinicians in selecting personalized treatment strategies for breast cancer patients.

Objective: Prostate cancer (PCa) is a complex disease characterized by diverse cellular ecosystems within the tumor microenvironment (TME) and high tumor heterogeneity, which challenges clinically stratified management and reinforces the need for novel strategies to fight against castration-resistant PCa (CRPC).

Methods: We performed single-cell RNA sequencing (scRNA-seq) on 10 untreated primary PCa tissues and integrated public scRNA-seq resources from three normal prostate tissues, two untreated primary PCa tissues, and six CRPC tumors to portray a comprehensive cellular and molecular interaction atlas of PCa. We further integrated the single-cell and bulk transcriptomes of PCa to establish a molecular classification system.

Results: scRNA-seq profiles revealed substantial inter- and intra-tumoral heterogeneity across different cell subpopulations in untreated PCa and CRPC tumors. In the malignant epithelial reservoir, cells evolved along decoupled paths in treatment-naive PCa and CRPC tumors, and distinct transcriptional reprogramming processes were activated, highlighting anti-androgen therapy-induced lineage plasticity. Based on the specifically expressed markers of the epithelial subpopulations, we conducted unsupervised clustering analysis in The Cancer Genome Atlas prostate adenocarcinoma (TCGA-PRAD) cohort and identified three molecularly and clinically distinct subtypes. The C1 subtype, characterized by high enrichment of CRPC-enriched epithelial cells, had a high risk of rapid development of anti-androgen resistance and might require active surveillance and additional promising intervention treatments, such as integrin A3 (ITGA3) + integrin B1 (ITGB1) inhibition. The C2 subtype resembled the immune-modulated subtype that was most likely to benefit from anti-LAG3 immunotherapy. The C3 subtype had a favorable prognosis.

Conclusions: Our study provides a comprehensive and high-resolution landscape of the intricate architecture of the PCa TME, and our trichotomic molecular taxonomy could help facilitate precision oncology.