2025年 · 第138卷第17期

Neoantigens exhibit high immunogenic potential and confer a uniqueness to tumor cells, making them ideal targets for personalized cancer immunotherapy. Neoantigens originate from tumor-specific genetic alterations, abnormal viral infections, or other biological mechanisms, including atypical RNA splicing events and post-translational modifications (PTMs). These neoantigens are recognized as foreign by the immune system, eliciting an immune response that largely bypasses conventional mechanisms of central and peripheral tolerance. Advances in next-generation sequencing (NGS), mass spectrometry (MS), and artificial intelligence (AI) have greatly expedited the rapid detection and forecasting of neoantigens, markedly propelling the development of diverse immunotherapeutic strategies, including cancer vaccines, adoptive cell therapy, and antibody treatment. In this review, we comprehensively explore the discovery and characterization of neoantigens and their clinical use within promising immunotherapeutic frameworks. Additionally, we address the current landscape of neoantigen research, the intrinsic challenges of the field, and potential pathways for clinical application in cancer treatment.

Colon cancer is a leading cause of cancer-related mortality worldwide, with surgical resection followed by adjuvant chemotherapy being the traditional standard for localized disease. However, the emergence of neoadjuvant therapies has introduced new possibilities for improving outcomes in locally advanced colon cancer (LACC). Neoadjuvant chemotherapy has demonstrated promising results in tumor downstaging, improved resectability, and reduced recurrence rates, as highlighted in trials like FOxTROT (Fluoropyrimidine oxaliplatin and targeted receptor pre-operative therapy), OPTICAL (A phase III study to evaluate the 3-year disease-free survival in patients with locally advanced colon cancer receiving either perioperative or postoperative chemotherapy with FOLFOX or CAPOX regimens), and NeoCol (Neoadjuvant chemotherapy versus standard treatment in patients with locally advanced colon cancer). For deficient mismatch repair (dMMR) tumors, neoadjuvant immunotherapy, exemplified by the NICHE (Neoadjuvant immune checkpoint inhibition and novel IO combinations in early-stage colon cancer) trial, has shown good pathologic response rates. Despite these advancements, challenges such as disease progression during treatment, staging inaccuracies, and chemotherapy-related toxicities underscore the need for precise patient selection and monitoring. Immunotherapy offers significant potential for dMMR tumors, potentially leading to non-surgical management strategies, while neoadjuvant chemotherapy presents a viable option for MMR-proficient (pMMR) patients, improving long-term outcomes in select populations. As the landscape of LACC management evolves, this review emphasizes the importance of personalized treatment strategies informed by biomarkers such as MMR status to maximize therapeutic efficacy and minimize risks. Future directions include refining the role of neoadjuvant therapies in clinical practice, expanding the use of immunotherapy, and exploring innovative combinations of systemic and targeted approaches to enhance survival and quality of life in patients with LACC. This review examines the current evidence supporting neoadjuvant approaches in pMMR and dMMR colon cancer, emphasizing their potential benefits and challenges.

Antibiotic-resistant (AR) bacterial wound infections (WIs) impose major burdens on healthcare systems, exacerbated by ineffective therapies and stalled antibiotic development. Phage therapy and phage-derived enzymes have gained traction as potent alternatives, leveraging targeted bactericidal mechanisms to combat AR pathogens. In this review, we summarised the antimicrobial mechanisms of both phage therapy and phage-derived enzymes as antimicrobial therapy, and outlined recent advances in their use for in vitro, in vivo and clinical applications for WI management. In addition, we also highlights recent advancements in their development, driven by genetic engineering, chemical modifications, and artificial intelligence. Finally, we identified the potential barriers and challenges they may encounter in clinical practice and the corresponding strategies to address these issues. The entire review gives us a comprehensive understanding of the latest advances in phages and their derivative enzyme therapies for treating WIs, in the hope that research in this field will continue to improve and innovate, accelerating the transition from the laboratory to application at the bedside and ultimately improving the efficacy of treatment for AR bacterial WIs.

Alzheimer’s disease (AD) is the most common cause of dementia and is a growing public health challenge. Neuroinflammation has been proposed as a prominent pathological feature of AD and has traditionally been attributed to the innate immune system. However, emerging evidence highlights the involvement of adaptive immunity, particularly T and B lymphocytes, in the neuroinflammatory processes of AD. It remains unclear how adaptive immune responses, originally intended to protect the body, contribute to chronic inflammation and neuronal dysfunction in AD. Here, we review the roles of adaptive immunity, cellular composition, and niches and their contribution to AD development and progression. Notably, we synthesize the crosstalk between adaptive immunity and the innate immune system of the central nervous system (CNS), which is mainly mediated by glial cells and myeloid cells, and their interrelationships with amyloid-β (Aβ)/Tau pathology. We hypothesized that the alterations observed in innate immunity in AD mirror age-related immune alterations, whereas the dysregulation of adaptive immunity contributes more accurately to disease-specific immune responses. Targeting adaptive immunity in the context of neuroinflammation may provide new insights into potential therapeutic strategies designed to modulate immune responses, thereby facilitating the diagnosis, intervention, and treatment of AD.

Background: The purpose of this study was to evaluate the safety and efficacy of subsequent radiotherapy (RT) following first-line treatment with durvalumab plus chemotherapy in patients with extensive-stage small cell lung cancer (ES-SCLC). Methods: A total of 122 patients with ES-SCLC from three hospitals during July 2019 to December 2021 were retrospectively analyzed. Inverse probability of treatment weighting (IPTW) analysis was performed to address potential confounding factors. The primary focus of our evaluation was to assess the impact of RT on progression-free survival (PFS) and overall survival (OS). Results: After IPTW analysis, 49 patients received durvalumab plus platinum-etoposide (EP) chemotherapy followed by RT (Durva + EP + RT) and 72 patients received immunochemotherapy (Durva + EP). The median OS was 17.2 months vs. 12.3 months (hazard ratio [HR]: 0.38, 95% confidence interval [CI]: 0.17-0.85, P = 0.020), and the median PFS was 8.9 months vs. 5.9 months (HR: 0.56, 95% CI: 0.32-0.97, P = 0.030) in Durva + EP + RT and Durva + EP groups, respectively. Thoracic radiation therapy (TRT) resulted in longer OS (17.2 months vs. 14.7 months) and PFS (9.1 months vs. 7.2 months) compared to RT directed to other metastatic sites. Among patients with oligo-metastasis, RT also showed significant benefits, with a median OS of 17.4 months vs. 13.7 months and median PFS of 9.8 months vs. 5.9 months compared to no RT. Continuous durvalumab treatment beyond progression (TBP) prolonged OS compared to patients without TBP, in both the Durva + EP + RT (NA vs. 15.8 months, HR: 0.48, 95% CI: 0.14-1.63, P = 0.238) and Durva + EP groups (12.3 months vs. 4.3 months, HR: 0.29, 95% CI: 0.10-0.81, P = 0.018). Grade 3 or 4 adverse events occurred in 13 (26.5%) and 13 (18.1%) patients, respectively, in the two groups; pneumonitis was mostly low-grade. Conclusion: Addition of RT after first-line immunochemotherapy significantly improved survival outcomes with manageable toxicity in ES-SCLC.

Background: The American Heart Association (AHA) introduced the concept of cardiovascular-kidney-metabolic (CKM) health and stage, reflecting the interaction among metabolism, chronic kidney disease (CKD), and the cardiovascular system. However, the association between CKM stage and the long-term risk of cardiovascular disease (CVD) has not been validated. This study aimed to evaluate the long-term CVD risk associated with CKM health metrics and CKM stage using data from a population-based cohort study. Methods: In total, 5293 CVD-free participants were followed up to around 13 years in the Chinese Multi-provincial Cohort Study (CMCS). Considering the pathophysiologic progression of CKM health metrics abnormalities (comprising obesity, central adiposity, prediabetes, diabetes, hypertriglyceridemia, CKD, and metabolic syndrome), participants were divided into CKM stages 0, 1, and 2. The time-dependent Cox regression models were used to estimate the cardiovascular risk associated with CKM health metrics and stage. Additionally, broader CVD outcomes were examined, with a specific assessment of the impact of stage 3 in 2581 participants from the CMCS-Beijing subcohort. Results: Among participants, 91.2% (4825/5293) had at least one abnormal CKM health metric, 8.8% (468/5293), 13.3% (704/5293), and 77.9% (4121/5293) were in CKM stages 0, 1, and 2, respectively; and 710 incident CVD cases occurred during a median follow-up time of 13.3 years (interquartile range: 12.1 to 13.6 years). Participants with each poor CKM health metric exhibited significantly higher CVD risk. Compared with stage 0, the hazard ratio (HR) (95% confidence interval [CI]) for CVD incidence was 1.31 (0.84-2.04) in stage 1 and 2.27 (1.57-3.28) in stage 2. Significant interactive impacts existed between CKM stage and age or sex, with higher CVD risk related to increased CKM stages in participants aged <60 years or females. Conclusion: These findings highlight the contribution of CKM health metrics and CKM stage to the long-term risk of CVD, suggesting the importance of multi-component recognition and management of poor CKM health in CVD prevention.

Background: Peripheral helper T (TPH) cells are uniquely positioned within pathologically inflamed non-lymphoid tissues to stimulate B-cell responses and antibody production. However, the phenotype, function, and clinical relevance of TPH cells in hepatocellular carcinoma (HCC) are currently unknown. Methods: Blood, tumor, and peritumoral liver tissue samples from 39 HCC patients (Sep 2016-Aug 2017) and 101 HCC patients (Sep 2011-Dec 2012) at the Third Affiliated Hospital of Sun Yat-sen University were used. Flow cytometry was used to quantify the expression, phenotype, and function of TPH cells. Log-rank tests were performed to evaluate disease-free survival and overall survival in samples from 39 patients and 101 patients with HCC. TPH cells, CD19+ B cells, and T follicular helper (TFH) cells were cultured separately in vitro or isolated from C57/B6L mice in vivo for functional assays. Results: TPH cells highly infiltrated tumor tissues, which was correlated with tumor size, early recurrence, and shorter survival time. The tumor-infiltrated TPH cells showed a unique ICOShiCXCL13+IL-21-MAF+BCL-6- phenotype and triggered naïve B-cell differentiation into regulatory B cells. Triggering programmed cell death protein 1 (PD-1) induced the production of C-X-C motif chemokine ligand 13 (CXCL13) by TPH cells, which then suppressed tumor-specific immunity and promoted disease progression. Conclusion: Our study reveals a novel regulatory mechanism of TPH cell-regulatory B-cell-mediated immunosuppression and provides an important perspective for determining the balance between the differentiation of protumorigenic TPH cells and that of antitumorigenic TFH cells in the HCC microenvironment.

Background: Studies on the impact of blood glucose indicators on metabolism remain relatively scarce. The aim of this study was to investigate the associations between blood glucose indicators and metabolic disorders in China. Methods: Data were from the Thyroid disorders, Iodine status and Diabetes Epidemiological survey (TIDE survey), which randomly selected 31 cities from 31 provinces in the Chinese mainland. A total of 68,383 participants without preexisting diabetes and have complete data on blood glucose, lipids, and blood pressure were included in the analysis. The diabetic population was divided into seven groups based on different types of elevated blood glucose levels, including fasting plasma glucose (FPG), postprandial glucose (PPG), and hemoglobin A1c (HbA1c): FPG ≥7 mmol/L; PPG ≥11.1 mmol/L; HbA1c ≥6.5%; FPG ≥7 mmol/L and PPG ≥11.1 mmol/L; FPG ≥7 mmol/L and HbA1c ≥6.5%; PPG ≥11.1 mmol/L and HbA1c ≥6.5%; FPG ≥7 mmol/L, PPG ≥11.1 mmol/L, and HbA1c ≥6.5%. The effects of each blood glucose indicator on metabolism were investigated separately. Weighted calculation was applied during the analysis, with the weighting coefficient based on the number of people corresponding to the population characteristics of each sample in the 2010 Chinese Census. A logistic regression model with restricted cubic splines (RCS) was employed to characterize the nonlinear associations of age and body mass index (BMI) with the risk of diabetes subtypes defined by distinct blood glucose indicators elevations, as well as the relationships between different blood glucose indicators (FPG, PPG, HbA1c) and the risk of metabolic disorders such as hypertension, hypertriglyceridemia, hypercholesterolemia, high low-density lipoprotein cholesterol (high LDL-C) and low high-density lipoprotein cholesterol (low HDL-C). Results: Among individuals with diabetes, elevated PPG alone was the most common abnormality, affecting 26.96% (1382/5127) of the population. Among the seven groups with only one elevated blood glucose indicator, individuals with elevated PPG alone exhibited the highest mean levels of triglycerides (TG) at 2.11 mmol/L (95% confidence interval [CI]: 1.97-2.25 mmol/L, P = 0.004), total cholesterol (TC) at 5.26 mmol/L (95% CI: 5.18-5.33 mmol/L, P <0.001), and low-density lipoprotein cholesterol (LDL-C) at 3.12 mmol/L, (95% CI: 3.06-3.19 mmol/L, P = 0.001). Individuals with elevated PPG alone showed a high prevalence of hypertension (806/1382, 58.32%), hypertriglyceridemia (676/1382, 48.91%), hypercholesterolemia (694/1382, 50.22%), High LDL-C (525/1382, 37.94%), and Low HDL-C (364/1382, 26.34%). The association of age and BMI with the risk of diabetes revealed that the older the patient, the steeper the RCS curve for the odds ratio (OR) of diabetes with elevated PPG alone (age = 60, OR = 2.79, 95% CI [2.49-3.12], P <0.01). Similarly, as BMI increased, the RCS curve for the OR of diabetes with elevated HbA1c alone also steepened (BMI = 35, OR = 3.75, 95% CI [3.23-4.35], P <0.001). Additionally, the RCS yielded a positive association between blood glucose indicators and metabolic diseases risk. In individuals with diabetes, RCS for both the ORs of metabolic diseases (hypertension, hypertriglyceridemia, hypercholesterolemia, high LDL-C, low HDL-C) and the levels of metabolic indicators (TG, TC, LDL-C, HDL-C) revealed some inflection points within the ranges of FPG 5-6 mmol/L, PPG 6-8 mmol/L, and HbA1c 5.5-6.0%. Conclusions: PPG is more closely related to metabolic disorders than FPG and HbA1c in people with diabetes. For patients with diabetes and metabolic disorders, it may be necessary to monitor blood glucose fluctuations within specific ranges (FPG 5-6 mmol/L, PPG 6-8 mmol/L, and HbA1c 5.5-6.0%).

Background: Postoperative pulmonary complications (PPCs) are major adverse events in neurosurgical patients. This study aimed to develop and validate machine learning models predicting PPCs after neurosurgery. Methods: PPCs were defined according to the European Perioperative Clinical Outcome standards as occurring within 7 postoperative days. Data of cases meeting inclusion/exclusion criteria were extracted from the anesthesia information management system to create three datasets: The development (data of Huashan Hospital, Fudan University from 2018 to 2020), temporal validation (data of Huashan Hospital, Fudan University in 2021) and external validation (data of other three hospitals in 2023) datasets. Machine learning models of six algorithms were trained using either 35 retrievable and plausible features or the 11 features selected by Lasso regression. Temporal validation was conducted for all models and the 11-feature models were also externally validated. Independent risk factors were identified and feature importance in top models was analyzed. Results: PPCs occurred in 712 of 7533 (9.5%), 258 of 2824 (9.1%), and 207 of 2300 (9.0%) patients in the development, temporal validation and external validation datasets, respectively. During cross-validation training, all models except Bayes demonstrated good discrimination with an area under the receiver operating characteristic curve (AUC) of 0.840. In temporal validation of full-feature models, deep neural network (DNN) performed the best with an AUC of 0.835 (95% confidence interval [CI]: 0.805-0.858) and a Brier score of 0.069, followed by Logistic regression (LR), random forest and XGBoost. The 11-feature models performed comparable to full-feature models with very close but statistically significantly lower AUCs, with the top models of DNN and LR in temporal and external validations. An 11-feature nomogram was drawn based on the LR algorithm and it outperformed the minimally modified Assess respiratory RIsk in Surgical patients in CATalonia (ARISCAT) and Laparoscopic Surgery Video Educational Guidelines (LAS VEGAS) scores with a higher AUC (LR: 0.824, ARISCAT: 0.672, LAS: 0.663). Independent risk factors based on multivariate LR mostly overlapped with Lasso-selected features, but lacked consistency with the important features using the Shapley additive explanation (SHAP) method of the LR model. Conclusions: The developed models, especially the DNN model and the nomogram, had good discrimination and calibration, and could be used for predicting PPCs in neurosurgical patients. The establishment of machine learning models and the ascertainment of risk factors might assist clinical decision support for improving surgical outcomes.

Background: Senescent human skin primary fibroblast (FB) models have been established for studying aging-related, proliferative, and inflammatory skin diseases. The aim of this study was to compare the transcriptome characteristics of human primary dermal FBs from children and the elderly with four senescence models. Methods: Human skin primary FBs were obtained from healthy children (FB-C) and elderly donors (FB-E). Senescence models were generated by ultraviolet B irradiation (FB-UVB), D-galactose stimulation (FB-D-gal), atazanavir treatment (FB-ATV), and replication exhaustion induction (FB-P30). Flow cytometry, immunofluorescence staining, real-time quantitative polymerase chain reaction, co-culturing with immune cells, and bulk RNA sequencing were used for systematic comparisons of the models. Results: In comparison with FB-C, FB-E showed elevated expression of senescence-related genes related to the skin barrier and extracellular matrix, proinflammatory factors, chemokines, oxidative stress, and complement factors. In comparison with FB-E, FB-UVB and FB-ATV showed higher levels of senescence and expression of the genes related to the senescence-associated secretory phenotype (SASP), and their shaped immune microenvironment highly facilitated the activation of downstream immune cells, including T cells, macrophages, and natural killer cells. FB-P30 was most similar to FB-E in terms of general transcriptome features, such as FB migration and proliferation, and aging-related characteristics. FB-D-gal showed the lowest expression levels of senescence-related genes. In comparisons with the single-cell RNA sequencing results, FB-E showed almost complete simulation of the transcriptional spectrum of FBs in elderly patients with atopic dermatitis, followed by FB-P30 and FB-UVB. FB-E and FB-P30 showed higher similarity with the FBs in keloids. Conclusions: Each senescent FB model exhibited different characteristics. In addition to showing upregulated expression of natural senescence features, FB-UVB and FB-ATV showed high expression levels of senescence-related genes, including those involved in the SASP, and FB-P30 showed the greatest similarity with FB-E. However, D-galactose-stimulated FBs did not clearly present aging characteristics.