Chinese Journal of Cancer Research最新文献

Objective: This study aims to quantify the potential impact of controlling major risk factors on liver cancer deaths in China from 2021 to 2050 under various intervention scenarios.

Methods: We developed a macro-level simulation model based on comparative risk assessment to estimate population attributable fractions and avoidable liver cancer deaths. Risk factor prevalence data were obtained from national surveys and epidemiological estimates. Three intervention scenarios for each risk factor were projected: elimination (Scenario 1), ambitious reduction (Scenario 2), and manageable targets aligned with national/global goals (Scenario 3). The impact of secondary prevention through liver cancer screening at different coverage was evaluated.

Results: Between 2021 and 2050, liver cancer deaths in China are projected to reach 9.44 million in males and 4.29 million in females. Eliminating hepatitis B virus and hepatitis C virus could prevent 65.62% (57.47%-73.77%) and 28.47% (24.93%-32.00%) of liver cancer deaths, respectively. Achieving manageable targets in reducing the prevalence of smoking and alcohol drinking could prevent 6.57% (5.75%-7.38%) and 0.85% (0.75%-0.96%) of liver cancer deaths, with a more pronounced effect observed in males. Eliminating high body mass index (BMI) could avert 45,000 male and 25,000 female deaths annually by 2050, while diabetes elimination could prevent 60,000 male and 21,000 female deaths. Secondary prevention through liver cancer screening with 80% coverage could reduce liver cancer deaths by 3.59% (3.14%-4.04%) for the total population. Combining all interventions under Scenario 1 could prevent up to 88.39% (76.65%-99.81%) of male and 77.80% (67.42%-87.88%) of female liver cancer deaths by 2050.

Conclusions: Comprehensive risk factor control could prevent over 80% of liver cancer deaths in China by 2050. Secondary prevention through screening may offer modest additional benefits. These findings provide strong quantitative support for targeted, evidence-based interventions and underscore the need for policy action to address key risk factors.

Objective: Triple-negative breast cancer (TNBC) is a highly aggressive subtype that lacks targeted therapies, leading to a poorer prognosis. However, some patients achieve long-term recurrence-free survival (RFS), offering valuable insights into tumor biology and potential treatment strategies.

Methods: We conducted a comprehensive multi-omics analysis of 132 patients with American Joint Committee on Cancer (AJCC) stage III TNBC, comprising 36 long-term survivors (RFS≥8 years), 62 moderate-term survivors (RFS: 3-8 years), and 34 short-term survivors (RFS<3 years). Analyses investigated clinicopathological factors, whole-exome sequencing, germline mutations, copy number alterations (CNAs), RNA sequences, and metabolomic profiles.

Results: Long-term survivors exhibited fewer metastatic regional lymph nodes, along with tumors showing reduced stromal fibrosis and lower Ki67 index. Molecularly, these tumors exhibited multiple alterations in genes related to homologous recombination repair, with higher frequencies of germline mutations and somatic CNAs. Additionally, tumors from long-term survivors demonstrated significant downregulation of the RTK-RAS signaling pathway. Metabolomic profiling revealed decreased levels of lipids and carbohydrate, particularly those involved in glycerophospholipid, fructose, and mannose metabolism, in long-term survival group. Multivariate Cox analysis identified fibrosis [hazard ratio (HR): 12.70, 95% confidence interval (95% CI): 2.19-73.54, P=0.005] and RAC1 copy number loss/deletion (HR: 0.22, 95% CI: 0.06-0.83, P=0.026) as independent predictors of RFS. Higher fructose/mannose metabolism was associated with worse overall survival (HR: 1.30, 95% CI: 1.01-1.68, P=0.045). Our findings emphasize the association between biological determinants and prolonged survival in patients with TNBC.

Conclusions: Our study systematically identified the key molecular and metabolic features associated with prolonged survival in AJCC stage III TNBC, suggesting potential therapeutic targets to improve patient outcomes.

Objective: Patients with homologous recombination deficiency (HRD) demonstrate distinct clinicopathological and prognostic features. However, standardised and clinically validated HRD detection methodologies specifically tailored for non-small cell lung cancer (NSCLC) have yet to be established. Further research is needed to clarify the precise role and clinical implications of HRD in NSCLC.

Methods: A cohort of 580 treatment-naïve NSCLC patients was retrospectively enrolled. Comprehensive genomic profiling (CGP) was performed for all patients, and HRD status was evaluated using two genomic scar score (GSS)-based algorithms: a machine learning-based GSS (ML-GSS) and a continuous linear regression-based GSS (CLR-GSS). To assess the diagnostic performance (sensitivity and specificity) of the ML-GSS and CLR-GSS algorithms for HRD detection, immunohistochemical (IHC) staining was conducted for two HRD-related biomarkers: Schlafen 11 (SLFN11) and RAD51. Survival analysis, including progression-free survival (PFS), along with multivariable Cox proportional hazards models, was performed to compare the prognostic value of the two HRD algorithms.

Results: Among all patients, 146 (25.2%) and 46 (7.9%) were classified as HRD-positive (HRD+) by ML-GSS and CLR-GSS, respectively. Using SLFN11 IHC expression as the reference standard, comparative analysis demonstrated that ML-GSS exhibited significantly higher sensitivity but lower specificity than CLR-GSS. This trend was consistently observed in RAD51 staining analysis. Compared to HRD-negative (HRD-) patients, ML-GSS-defined HRD+ cases displayed distinct clinicopathological and genomic features, including a higher prevalence of homologous recombination (HR)-related genes mutations, BRCA1/2 mutations, TP53 mutations, elevated tumor mutation burden (TMB), and increased copy number variations (CNVs). In contrast, CLR-GSS-defined HRD+ patients were only enriched for BRCA1/2 mutations, TP53 mutations, and elevated TMB. Furthermore, ML-GSS-defined HRD+ status was associated with significantly worse prognosis following first-line therapy compared to HRD- patients. Univariate and multivariable Cox analyses identified ML-GSS-defined HRD+ and TP53 mutations as significant predictors and independent risk factors, respectively. No such associations were observed in the CLR-GSS-defined HRD+ cohort.

Conclusions: ML-GSS demonstrated superior performance to CLR-GSS in assessing chromosomal instability (CIN) and showed greater clinical utility. We recommend the ML-GSS algorithm as a robust and clinically validated tool for HRD/CIN evaluation in NSCLC. Furthermore, ML-GSS-defined HRD+ status was identified as both a significant predictor and an independent risk factor.

Drug resistance continues to be the principal limiting factor in achieving a cure for patients with cancer, significantly hindering the long-term efficacy of novel cancer drugs. Accumulating evidence has shown that metabolites derived from tumor cells regulate immune cell metabolism via tumor microenvironment crosstalk. However, as immunometabolic research has deepened, the leading role played by the intrinsic metabolic regulation of immune cells in the drug resistance of tumor cells has been discovered. Immune metabolites have been shown to cause immune resistance, target therapy resistance, and chemotherapy resistance, and drugs that target immune metabolism have great potential. To date, researchers have not fully explored the impact of immune-derived metabolites on tumor cells and their influence on the responsiveness to cancer drugs. In this review, we focus on the lactate, fatty acid, glucose, and nucleotide metabolic alterations that take place in T cells and macrophages and how these changes can impair anti-tumor immunity, ultimately promoting tumor cell survival and decreasing responsiveness to the corresponding therapeutic approaches. We present the current developments in drugs targeting immunometabolic pathways and propose constructive suggestions, such as precise delivery to immune cell targets to enhance efficacy and safety, offering novel perspectives for cancer drug development.

Pancreatic cancer, particularly pancreatic ductal adenocarcinoma (PDAC), is one of the most lethal malignancies, which is characterized by a complex tumor microenvironment (TME) that fosters immune evasion and treatment resistance. Recent genomic advancements have unveiled diverse molecular subtypes of PDAC, providing insights into targeted therapies and precision medicine. This review synthesizes the current understanding of PDAC's molecular characterization and immunosuppressive TME, as well as emerging therapeutic strategies, including innovative approaches targeting key molecular pathways such as kirsten rat sarcoma viral oncogene homolog (KRAS), epidermal growth factor receptor (EGFR), and immune checkpoints. Despite advances, challenges remain in overcoming treatment resistance and inherent heterogeneity of pancreatic cancer subtypes. We highlight the need for multidisciplinary collaboration to enhance early diagnosis and develop individualized therapeutic protocols, paving the way for improving the outcomes of this aggressive cancer. This integrated perspective underscores the urgency of transforming the innovative research into pancreatic cancer management.

In the past decade, immunotherapies targeting cytotoxic T-lymphocyte antigen-4 (CTLA-4), programmed cell death 1 (PD-1), and PD-1 ligand (PD-L1) have been approved for solid tumors. However, some patients demonstrate suboptimal clinical outcomes due to resistance. The tumor microenvironment (TME) significantly affects the efficiency of immunotherapy by mediating interactions between tumor and non-tumor cells, including dendritic cells, T cells, B cells, macrophages, neutrophils, NK cells, and myeloid-derived suppressor cells (MDSCs). These non-tumor cells often exhibit two phenotypes with altered functions, and tumor cells drives their transition towards tumor promotion through tumor-education. Tumor-educated cells (TECs) are cells influenced by tumor cells, which acquire immune-suppressive phenotypes and promote tumor progression through resistance to anti-cancer therapies. These cells undergo modifications in response to signals from the tumor, which can influence their roles in tumor progression. Their dynamic interactions with tumor cells contribute to the reshaping of the TME, facilitating cancer growth and immune modulation. This review summarizes research on TECs in TME, explores mechanisms related to tumor education, and discusses their role in tumor progression and immunotherapy resistance. Additionally, potential therapeutic approaches targeting these cells are also reviewed, which may complement current treatment strategies.

Objective: This study aimed to describe the updated disease burden and temporal trends of stomach cancer (SC) and colorectal cancer (CRC), and to explore potential influence factors of the two cancers in the Western Pacific region (WPR).

Methods: Estimates of incidence, deaths, and disability-adjusted life years (DALYs) for SC and CRC were obtained from the Global Burden of Disease Study 2021. Trends in age-standardized incidence rates (ASIR), age-standardized mortality rates (ASMR), and age-standardized DALY rates (ASDR) were assessed. A decomposition analysis was conducted to quantify the role of three factors (i.e., population aging, population growth, and epidemiological change) driving DALY changes between 2000 and 2021. Pearson correlation analysis was used to examine the association between cancer burden and Socio-demographic Index (SDI) at the national level in 2021.

Results: In 2021, the WPR accounted for 61.77% of global incident SC cases and 43.07% of global incident CRC cases. From 2000 to 2021, the ASIR, ASMR, and ASDR of SC and the ASMR and ASDR of CRC decreased, whereas the ASIR of CRC increased by an average of 1.32% per year. Among the 31 WPR countries and territories, China had the highest number of incident cases, deaths, and DALYs for both cancers in 2021. Epidemiology change was the primary driver to the reduction of DALYs for SC, while population aging and population growth contributed to the increase of DALYs for CRC. Additionally, ASMR (r=-0.37, P=0.041) and ASDR (r=-0.43, P=0.016) of SC were negatively correlated with SDI in 2021, whereas positive correlations were observed between SDI and ASIR (r=0.74, P<0.001), ASMR (r=0.47, P=0.008), and ASDR (r=0.36, P=0.044) for CRC.

Conclusions: SC and CRC continue to pose considerable public health threats in the WPR. Targeted prevention and control strategies should be prioritized, particularly in high-burden and resource-limited countries.

Objective: The Safety of robotic gastrectomy (RG) compared to laparoscopic gastrectomy (LG) for gastric cancer remains uncertain on a national scale, with limited comparative studies across institutions. This study aims to compare the morbidity rates between RG and LG using data from a nationwide survey.

Methods: We utilized data from the Korean Gastric Cancer Association's 2019 nationwide survey. The proportion of robotic surgeries in minimally invasive surgery at each institution was classified using a cut-off value of 10%, and defined as high robotic proportion cohort and low robotic proportion cohort. We analyzed surgical outcomes between robotic and laparoscopic gastrectomy in each cohort using propensity score matching (PSM). To account for potential clustering effects within hospitals, we employed Generalized Estimating Equations with hospital as the clustering variable.

Results: This study included 776 patients who underwent RG and 7,804 patients who underwent LG for gastric cancer. In low robotic proportion cohort, RG had a longer operation time (P<0.001) but similar blood loss (P=0.792) compared to LG. In the high robotic proportion cohort, RG showed longer operation time (P<0.001), less blood loss (P<0.001), and shorter hospital stays (P<0.001) compared to LG. Additionally, RG in the high robotic proportion cohort had shorter operative time (P<0.001) and less blood loss (P=0.024) compared with that in the low robotic proportion cohort.

Conclusions: RG demonstrated comparable perioperative outcomes to LG in a nationwide PSM analysis. However, RG offers limited benefits over LG at institutions with lower frequencies of RG use.