Chinese Journal of Cancer Research最新文献

Objective: Neoadjuvant therapy (NAT) has become the standard treatment option for patients with locally advanced breast cancer. How to non-invasively screen out patients with pathological complete response (pCR) after NAT has become an urgent world-wide clinical problem. Our work aims to the assessment of neoadjuvant treatment response in breast cancer patients for higher accuracy prediction using innovative artificial intelligence system.

Methods: In this study, we retrospectively collected longitudinal (pre-NAT and post-NAT) multi-parametric magnetic resonance imaging (MRI) and clinicopathologic data of a total of 1,315 breast cancer patients (clinical stage I-III) who had undergone NAT followed by standard surgery and treated across 5 independent medical centers from January 2010 to January 2023. We used radiomics, 3D convolutional neural network technology and clinical data statistical analysis methods to extract and screen multimodal features, and then developed and validated a Clinical-Radiomics-Deep-Learning (CRDL) model to predict patients' pCR outcomes based on multimodal fusion features.

Results: We use the area under the receiver operating characteristic curve (AUC) in the primary cohort (PC) and 3 external validation cohorts (VC_1-3) to evaluate the model performance. The results showed that the AUC in the PC composed of 2 medical centers was 0.947 [95% confidence interval (95% CI): 0.931-0.960], and the AUC values in VC_1-3 were 0.857 (95% CI: 0.810-0.901), 0.883 (95% CI: 0.841-0.918) and 0.904 (95% CI: 0.860-0.941), respectively.

Conclusions: The CRDL model demonstrated high accuracy and robustness in predicting pCR to NAT using multimodal fusion data. This study provides a strong foundation for non-invasive assessment of pCR status in breast cancer patients following NAT and offers critical insights to guide clinical decision-making in post-NAT treatment planning.

Esophageal cancer (EC) is one of the most common malignancies in China, accounting for over half of the world's new cases and deaths, and posing a severe threat to national health. Currently, the prevention and control of EC primarily rely on secondary prevention through screening, early diagnosis and early treatment to reduce EC-specific mortality. Upper gastrointestinal endoscopy with Lugol's iodine or optical staining followed by histopathological diagnosis of biopsy samples, serves as the gold standard for EC screening and has been widely implemented in numerous national public health programs for early cancer detection and treatment. Nevertheless, traditional pathology-centered diagnostic and surveillance strategies face significant challenges in current screening practices. Relying on large-scale population-based screening cohorts, including the Efficacy of Endoscopic Screening for Esophageal Cancer in China (ESECC) trial (ClinicalTrials.gov, identifier NCT01688908), a series of investigations into the diagnosis and surveillance of EC screening provided critical new insights and evidence for optimizing endoscopic screening strategies for EC in China. Summarizing relevant research findings from the above investigations, this article provides a systematic review of the epidemiology, current screening diagnostic and surveillance strategies, existing challenges, and key innovations related to EC. These insights offer valuable guidance for public health practice and clinical decision-making in the prevention and screening of EC and other cancers.

Cancer is a leading cause of death in China, and its epidemiological profile has shifted markedly in recent years. This review summarizes contemporary trends in cancer incidence and mortality, delineates the major modifiable risk factors, and highlights recent national efforts to ease the burden of cancer. In 2022, China recorded 4.8 million new cancer cases (crude rate: 341.7 per 100,000) and 2.5 million cancer deaths (182.3 per 100,000). Lung, colorectal, thyroid, liver, stomach, and female breast cancers accounted for 65% of all diagnoses, while lung, liver, stomach, colorectal, and esophageal cancers constituted 67.5% of cancer deaths. Notable shifts in sex-specific rankings underscored the rising mortality burden of prostate, female breast, and cervical cancers. China has made measurable progress in cancer control. Between 2000 and 2018, the age-standardized mortality rate for all cancers declined by approximately 1.3% annually, and the age-standardized 5-year relative survival improved from 30.9% in 2003-2005 to 43.7% in 2019-2021. According to Global Burden of Disease (GBD) 2023, nearly half of cancer deaths and disability-adjusted life years (DALYs) were attributable to modifiable risk factors such as tobacco, air pollution, high alcohol use, dietary risks, and unsafe sex. In response, the government has implemented a suite of prevention-oriented policies, including expansion of human papillomavirus (HPV) vaccination, strengthened tobacco control, sustained air pollution reduction, enhanced health education, and broadened cancer screening coverage. Collectively, these initiatives demonstrate a sustained national commitment to reducing the cancer burden.

Objective: Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer. Despite significant advances in immunotherapy, treatment responses vary substantially among individuals. Metabolic reprogramming, as a hallmark of cancer, plays a crucial role in tumor progression and immune evasion. However, the interplay between metabolic features and tumor immune microenvironment in LUAD remains to be systematically elucidated.

Methods: We analyzed data from 1,231 LUAD patients across seven global cohorts and developed an integrated Metabolism-Related Signature (iMRS) using machine learning approaches based on 114 metabolic features. The signature's ability to predict immunotherapy response was validated using 9 immunotherapy cohorts (n=712, including LUAD, melanoma, and glioma). An in-house LUAD tissue cohort (n=146) confirmed the prognostic significance of SLC25A1, a key gene within the signature, and its spatial relationship with immune cells. In vivo and in vitro experiments investigated SLC25A1's role in cancer promotion, immune exclusion, and its impact on programmed cell death protein 1 (PD-1) therapy efficacy.

Results: iMRS demonstrated superior prognostic performance in LUAD patients, outperforming 129 published LUAD signatures. In immunotherapy cohorts, responders showed significantly lower iMRS scores. High iMRS was associated with reduced immune activity and "cold" tumor characteristics. SLC25A1 (correlation coefficient=0.54, P<0.05), a key gene in the signature, showed the highest expression in CD8 desert phenotype and correlated with poor prognosis. Multiplexed immunofluorescence revealed exclusion patterns between SLC25A1 and immune cells (CD4+ T cells and CD20+ B cells). SLC25A1 knockdown reduced lung metastasis and enhanced anti-PD-1 efficacy by increasing CD8+ T cell abundance and cytotoxicity [increased interferon-γ (IFN-γ)+/GZMB+ CD8+ T cells].

Conclusions: iMRS provides personalized immunotherapy prediction for LUAD patients. SLC25A1, identified as a novel immune-exclusion related oncogene, represents a promising therapeutic target for LUAD treatment.

Objective: A highly aggressive and lethal malignancy, characterized by its heterogeneity, lung adenocarcinoma (LUAD) presents significant challenges in prognosis and treatment. Disulfidptosis, a newly identified form of regulated cell death, offers novel insights into cancer progression, yet its role in LUAD remains poorly understood.

Methods: We identified disulfidptosis-related genes (DRGs) from prior studies and analyzed their interactions and functional enrichment. Molecular subtypes were identified through consensus clustering based on DRG expression, and a prognostic DRG signature was developed using multivariate Cox regression analysis. A nomogram integrating clinical variables was developed to predict survival. Comprehensive analyses, including single-cell RNA sequencing, immune infiltration, and drug sensitivity, were validated using clinical specimens, LUAD cell lines, Western blotting (WB) and immunohistochemistry (IHC).

Results: A total of 16 DRGs were identified, classifying LUAD patients into three distinct subtypes with differential survival and immune profiles. A 4-gene signature (GYS1, NDUFA11, NDUFB10, SLC7A11) was used to build a risk score model, demonstrating robust prognostic accuracy. A nomogram combining this signature with clinical features reliably predicted 1-, 3-, and 5-year survival. The signature correlated with immune cell infiltration, with single-cell analysis revealing DRG enrichment in myeloid cells. Notably, SLC7A11 and GYS1 were positively associated with chemotherapeutic drug sensitivity. Validation through reverse transcription quantitative polymerase chain reaction (RT-qPCR), WB and IHC confirmed upregulated DRG expression in LUAD tissues and cell lines.

Conclusions: This research highlights the essential role of DRGs in modulating the tumor microenvironment, influencing therapeutic response, and determining the prognosis of LUAD. The risk model and nomogram, derived from DRG expression, offer robust tools for survival prediction and personalized treatment stratification, facilitating the development of disulfidptosis-targeted therapeutic strategies.

Objective: Robotic gastrectomy (RG) is increasingly used in the treatment of gastric cancer. However, studies on patients with clinical serosa-invasive (cT4a) gastric cancer remain scarce. This study aimed to compare the short- and long-term outcomes of RG and laparoscopic gastrectomy (LG) in the treatment of stage cT4a gastric cancer.

Methods: A retrospective analysis was conducted on the clinical data of patients with stage cT4a gastric cancer diagnosed and treated at eight high-volume tertiary teaching hospitals in China from 2016 to 2019. Propensity score matching (PSM) analysis and inverse probability of treatment weighting (IPTW) analysis was used to adjust for the imbalance in baseline characteristics. The primary research endpoint was the 3-year overall survival (OS) and disease-free survival (DFS). The secondary research endpoint was intraoperative outcomes and postoperative complications.

Results: After IPTW and PSM adjustments, baseline characteristics between the RG and LG groups were comparable [standardized mean difference (SMD) <0.10]. Post-PSM analysis revealed that the RG group exhibited longer operative time (P<0.001), lower postoperative complication rates (P<0.001), shorter postoperative hospital stays (P=0.037), and earlier initiation of adjuvant chemotherapy (P=0.041) compared with the LG group. Survival analysis demonstrated comparable 3-year OS (P=0.110) and DFS (P=0.088) in the PSM cohort, whereas the IPTW cohort showed superior OS (P=0.030) and DFS (P=0.046) for RG. No significant differences were observed in overall recurrence rates or recurrence sites between groups.

Conclusions: For patients with stage cT4a gastric cancer, compared with the LG group, the RG group had shorter postoperative hospital stay, lower incidence of postoperative complications, earlier postoperative adjuvant chemotherapy, and no worse long-term efficacy.

Adverse-risk acute myeloid leukemia (AML) is a therapeutic challenge despite advances in risk stratification. Unmet needs persist in high-risk molecular subgroups, such as AML with myelodysplasia-related changes, TP53 mutations, or rearrangements involving NUP98, NUP214, or FUS::ERG. These subtypes are associated with poor responses to conventional induction therapies and high relapse rates. Allogeneic hematopoietic stem cell transplantation (allo-HSCT) remains the cornerstone of consolidation for eligible patients; however, due to high relapse rates, regimen-related toxicity, and variable responses across genetic subtypes, optimal transplant timing, conditioning regimens (e.g., busulfan- or melphalan-based protocols), and bridging strategies require further refinement. Meanwhile, post-transplant maintenance therapies, such as hypomethylating agents or targeted drugs, are one emerging area under investigation for relapse prevention. In this perspective, we review the latest advances in allo-HSCT strategies for adverse-risk AML and highlight the importance of molecularly-guided approaches to improve outcomes in these aggressive subtypes.

Measurable residual disease (MRD) has become a critical biomarker in the management of acute lymphoblastic leukemia (ALL), particularly for patients undergoing allogeneic hematopoietic stem cell transplantation (allo-HSCT). The incorporation of MRD-directed strategies into clinical practice can enable personalized therapy and improve outcomes in ALL patients. Growing evidence has demonstrated that MRD status not only reflects the treatment response and relapse risk but also informs clinical decisions across the transplant continuum, including transplant indications, donor selection, conditioning regimens, and post-transplant interventions. With the advent of highly sensitive technologies such as real-time polymerase chain reaction and next-generation sequencing, MRD assessment has reached unprecedented accuracy, enabling precision medicine for ALL. This review systematically addresses six key clinical questions related to the application of MRD in ALL patients undergoing transplantation. We discuss optimal MRD detection methods, timing and sampling strategies, the prognostic implications of MRD positivity or clearance, and MRD-directed approaches before and after allo-HSCT. We further highlight emerging immunotherapeutic options and research gaps that must be addressed to refine MRD-guided strategies. In summary, incorporating MRD evaluation into routine clinical practice has the potential to optimize transplant outcomes and reduce relapse in ALL patients.