2024年 · 第137卷第17期

Background: The incidence and mortality of colorectal cancer (CRC) in China are increasing in recent years. The clarified pathogenesis and detectable precancerous lesions of CRC make it possible to prevent, screen, and diagnose CRC at an early stage. With the development of endoscopic and surgical techniques, the choice of treatment for early CRC is also worth further discussion, and accordingly, a standard follow-up program after treatment needs to be established. Methods: This clinical practice guideline (CPG) was developed following the recommended process of the World Health Organization, adopting Grading of Recommendations Assessment, Development and Evaluation (GRADE) in assessing evidence quality, and using the Evidence to Decision framework to formulate clinical recommendations, thereby minimizing bias and increasing transparency of the CPG development process. We used the Reporting Items for practice Guidelines in HealThcare (RIGHT) statement and Appraisal of Guidelines for Research and Evaluation II (AGREE II) as reporting and conduct guides to ensure the guideline’s completeness and transparency. Results: This CPG comprises 46 recommendations concerning prevention, screening, diagnosis, treatment, and surveillance of CRC. In these recommendations, we have indicated protective and risk factors for CRC and made recommendations for chemoprevention. We proposed a suitable screening program for CRC based on the Chinese context. We also provided normative statements for the diagnosis, treatment, and surveillance of CRC based on existing clinical evidence and guidelines. Conclusions: The 46 recommendations in this CPG are formed with consideration for stakeholders’ values and preferences, feasibility, and acceptability. Recommendations are generalizable to resource-limited settings with similar CRC epidemiology pattern as China.

Anti-angiogenic drugs (AADs), which mainly target the vascular endothelial growth factor-A signaling pathway, have become a therapeutic option for cancer patients for two decades. During this period, tremendous clinical experience of anti-angiogenic therapy has been acquired, new AADs have been developed, and the clinical indications for AAD treatment of various cancers have been expanded using monotherapy and combination therapy. However, improvements in the therapeutic outcomes of clinically available AADs and the development of more effective next-generation AADs are still urgently required. This review aims to provide historical and perspective views on tumor angiogenesis to allow readers to gain mechanistic insights and learn new therapeutic development. We revisit the history of concept initiation and AAD discovery, and summarize the up-to-date clinical translation of anti-angiogenic cancer therapy in this field.

Tumor bioinformatics plays an important role in cancer research and precision medicine. The primary focus of traditional cancer research has been molecular and clinical studies of a number of fundamental pathways and genes. In recent years, driven by breakthroughs in high-throughput technologies, large-scale cancer omics data have accumulated rapidly. How to effectively utilize and share these data is particularly important. To address this crucial task, many computational tools and databases have been developed over the past few years. To help researchers quickly learn and understand the functions of these tools, in this review, we summarize publicly available bioinformatics tools and resources for pan-cancer multi-omics analysis, regulatory analysis of tumorigenesis, tumor treatment and prognosis, immune infiltration analysis, immune repertoire analysis, cancer driver gene and driver mutation analysis, and cancer single-cell analysis, which may further help researchers find more suitable tools for their research.

Bacille Calmette-Guérin (BCG) vaccine is designed to provide protection against tuberculosis (TB). However, numerous epidemiological, clinical, and immunological studies have shown that BCG vaccination affects neonatal and infant mortality, which may be related to the reduction of TB-unrelated infections and diseases by BCG vaccine. We aimed to discuss the off-target effects of BCG vaccine on un-TB infections and diseases, as well as the potential mechanism and influencing factors. Literature was retrieved mainly from PubMed using medical subject headings "BCG, variations, and non-specific, heterologous or off-target". Studies have showed that BCG vaccination can prevent various heterologous infections, including respiratory tract infections, leprosy, and malaria, treat viral infections including human papillomavirus and herpes simplex virus infection as immunotherapy, and improve the immune responses as vaccine adjuvant. Besides, BCG vaccine can reduce the recurrence rate of non-muscle-invasive bladder cancer, and may provide protection against autoimmune diseases. These off-target effects of BCG vaccine are thought to be achieved by modulating heterologous lymphocyte responses or inducing trained immunity, which were found to be sex-differentiated and affected by the BCG vaccine strains, sequence or time of vaccination.

Background: The association and its population heterogeneities between low-density lipoprotein cholesterol (LDL-C) and all-cause and cardiovascular mortality remain unknown. We aimed to examine the dose-dependent associations of LDL-C levels with specific types of cardiovascular disease (CVD) mortality and heterogeneities in the associations among different population subgroups. Methods: A total of 2,968,462 participants aged 35-75 years from China Health Evaluation And risk Reduction through nationwide Teamwork (ChinaHEART) (2014-2019) were included. Cox proportional hazard models and Fine-Gray subdistribution hazard models were used to estimate associations between LDL-C categories (<70.0, 70.0-99.9, 100.0-129.9 [reference group], 130.0-159.9, 160.0-189.9, and ≥190.0 mg/dL) and all-cause and cause-specific mortality. Results: During a median follow-up of 3.7 years, 57,391 and 23,241 deaths from all-cause and overall CVD were documented. We observed J-shaped associations between LDL-C and death from all-cause, overall CVD, coronary heart disease (CHD), and ischemic stroke, and an L-shaped association between LDL-C and hemorrhagic stroke (HS) mortality (P for non-linearity <0.001). Compared with the reference group (100.0-129.9 mg/dL), very low LDL-C levels (<70.0 mg/dL) were significantly associated with increased risk of overall CVD (hazard ratio [HR]: 1.10, 95% confidence interval [CI]: 1.06-1.14) and HS mortality (HR: 1.37, 95% CI: 1.29-1.45). Very high LDL-C levels (≥190.0 mg/dL) were associated with increased risk of overall CVD (HR: 1.51, 95% CI: 1.40-1.62) and CHD mortality (HR: 2.08, 95% CI: 1.92-2.24). The stronger associations of very low LDL-C with risk of CVD mortality were observed in individuals with older age, low or normal body mass index, low or moderate 10-year atherosclerotic CVD risk, and those without diagnosed CVD or taking statins. Stronger associations between very high LDL-C levels and all-cause and CVD mortality were observed in younger people. Conclusions: People with very low LDL-C had a higher risk of all-cause, CVD, and HS mortality; those with very high LDL-C had a higher risk of all-cause, CVD, and CHD mortality. On the basis of our findings, comprehensive health assessment is needed to evaluate cardiovascular risk and implement appropriate lipid-lowering therapy for people with very low LDL-C.

Background: Breast cancer (BC) risk-stratification tools for Asian women that are highly accurate and can provide improved interpretation ability are lacking. We aimed to develop risk-stratification models to predict long- and short-term BC risk among Chinese women and to simultaneously rank potential non-experimental risk factors. Methods: The Breast Cancer Cohort Study in Chinese Women, a large ongoing prospective dynamic cohort study, includes 122,058 women aged 25-70 years old from the eastern part of China. We developed multiple machine-learning risk prediction models using parametric models (penalized logistic regression, bootstrap, and ensemble learning), which were the short-term ensemble penalized logistic regression (EPLR) risk prediction model and the ensemble penalized long-term (EPLT) risk prediction model to estimate BC risk. The models were assessed based on calibration and discrimination, and following this assessment, they were externally validated in new study participants from 2017 to 2020. Results: The AUC values of the short-term EPLR risk prediction model were 0.800 for the internal validation and 0.751 for the external validation set. For the long-term EPLT risk prediction model, the area under the receiver operating characteristic curve was 0.692 and 0.760 in internal and external validations, respectively. The net reclassification improvement index of the EPLT relative to the Gail and the Han Chinese Breast Cancer Prediction Model (HCBCP) models for external validation was 0.193 and 0.233, respectively, indicating that the EPLT model has higher classification accuracy. Conclusions: We developed the EPLR and EPLT models to screen populations with a high risk of developing BC. These can serve as useful tools to aid in risk-stratified screening and BC prevention.

Background: Accurately and efficiently extracting microbial genomic sequences from complex metagenomic data is crucial for advancing our understanding in fields such as clinical diagnostics, environmental microbiology, and biodiversity. As sequencing technologies evolve, this task becomes increasingly challenging due to the intricate nature of microbial communities and the vast amount of data generated. Especially in intensive care units (ICUs), infections caused by antibiotic-resistant bacteria are increasingly prevalent among critically ill patients, significantly impacting the effectiveness of treatments and patient prognoses. Therefore, obtaining timely and accurate information about infectious pathogens is of paramount importance for the treatment of patients with severe infections, which enables precisely targeted anti-infection therapies, and a tool that can extract microbial genomic sequences from metagenomic dataset would be of help. Methods: We developed MetaGeneMiner to help with retrieving specific microbial genomic sequences from metagenomes using a k-mer-based approach. It facilitates the rapid and accurate identification and analysis of pathogens. The tool is designed to be user-friendly and efficient on standard personal computers, allowing its use across a wide variety of settings. We validated MetaGeneMiner using eight metagenomic samples from ICU patients, which demonstrated its efficiency and accuracy. Results: The software extensively retrieved coding sequences of pathogens Acinetobacter baumannii and herpes simplex virus type 1 and detected a variety of resistance genes. All documentation and source codes for MetaGeneMiner are freely available at https://gitee.com/sculab/MetaGeneMiner. Conclusions: It is foreseeable that MetaGeneMiner possesses the potential for applications across multiple domains, including clinical diagnostics, environmental microbiology, gut microbiome research, as well as biodiversity and conservation biology. Particularly in ICU settings, MetaGeneMiner introduces a novel, rapid, and precise method for diagnosing and treating infections in critically ill patients. This tool is capable of efficiently identifying infectious pathogens, guiding personalized and precise treatment strategies, and monitoring the development of antibiotic resistance, significantly impacting the diagnosis and treatment of severe infections.

Background: To date, there is still a lack of standardized management strategies for gastric low-grade dysplasia (LGD), which is a direct neoplastic precancerous lesion and requires specifically superficial destruction. Radiofrequency ablation (RFA) is expected to be an effective method for gastric LGD, but post-RFA pain may affect patients’ satisfaction and compliance. The current study aimed to evaluate the value of a submucosal injection prior to RFA (SI-RFA) for postoperative pain and treatment outcomes. Methods: Between October 2014 and July 2021, gastric LGDs without risk factors (size >2 cm, unclear boundary, and abnormal microsurface and microvascularity) undergoing regular RFA and SI-RFA were retrospectively analyzed. Postoperative pain scores, wound healing, and clinical efficacy were compared. Propensity score matching, stratified analysis, and multivariable logistic regression were performed to control the confounding variables. Results: One hundred and ninety-seven gastric LGDs in 151 patients received regular RFA. Forty-nine gastric LGDs in 36 patients received SI-RFA. Thirty-six pairs of patients were selected for the assessment of postoperative pain by propensity score matching. Compared to regular RFA, SI-RFA significantly decreased the degree and duration of postoperative pain (OR, 0.32; 95% CI, 0.13-0.84; P = 0.020), improved wound healing rate (80.0% [36/45] vs. 58.9% [89/151], P = 0.012), increased the complete ablation rate (91.8% [45/49] vs. 86.3% [170/197], χ2 = 1.094, P = 0.295), but correlated with higher rates of local recurrence and progression (25.6% [10/39] vs. 13.2% [18/136], χ2 = 3.471, P = 0.062; 8.3% [3/36] vs. 0.9% [1/116], P = 0.042). The multivariable logistic regression model confirmed that submucosal injection was associated with local recurrence (OR, 2.93; 95% CI, 1.13-7.58; P = 0.027). Conclusions: Submucosal injections prior to RFA may reduce postoperative pain and scar formation while ensuring complete ablation of gastric LGD. However, local recurrence and progression should be considered seriously.

Background: Endoscopic papillectomy (EP) is recommended as the first-line therapy for ampullary tumors, despite a relatively high incidence of complications. Pancreatic and/or biliary stents are placed at the endoscopist’s discretion to prevent post-EP complications. The present study aimed to evaluate the efficacy of different stents. Methods: A total of 117 patients who underwent EP and met the criteria between June 2006 and October 2022 were enrolled in the study. These patients were divided into a pancreatic stent group (PS group, n = 47), a biliary stent group (BS group, n = 38), and a two-stent group (PBS [PS and BS] group, n = 32). Relevant clinical data were collected and compared among the three groups. Multivariate logistic analyses were performed to explore risk factors for post-EP complications. Results: The incidence of all complications was 37.6% (44/117). Pancreatitis and hemorrhage were the two most common complications with incidence rates of 14.5% (17/117) and 17.9% (21/117). The incidence rates of post-EP pancreatitis were 10.6% (5/47), 23.7% (9/38), and 9.4% (3/32) in the PS group, BS group, and PBS group, respectively, with no significant differences. There were also no significant differences in other complications among the three groups. Age (odds ratio [OR]: 0.95; 95% confidence interval [CI]: 0.91-0.99; P = 0.022) was independently associated with post-EP pancreatitis while tumor size (OR: 1.66; 95% CI: 1.06-2.60; P = 0.028) was independently associated with post-EP hemorrhage. Conclusions: While pancreatic stenting is the first choice to prevent post-EP pancreatitis, biliary stenting could also be considered as a substitute for patients with difficulties in pancreatic cannulation. Two-stent (biliary and pancreatic stent) placement is unnecessary unless it is required due to other concerns.