Electrosynthesis of Transition Metal Coordinated Polymers for Active and Stable Oxygen Evolution.

Transition metal coordination polymers (TM-CP) are promising inexpensive and flexible electrocatalysts for oxygen evolution reaction in water electrolysis, while their facile synthesis and controllable regulation remain challenging. Here we report an anodic oxidation-electrodeposition strategy for the growth of TM-CP (TM = Fe, Co, Ni, Cr, Mn; CP = polyaniline, polypyrrole) films on a variety of metal substrates that act as both catalyst supports and metal ion sources. An exemplified bimetallic NiFe-polypyrrole (NiFe-PPy) features superior mechanical stability in friction and exhibits high activity with long-term durability in alkaline seawater (over 2000 h) and anion exchange membrane electrolyzer devices at current density of 500 mA cm-2. Spectroscopic and microscopic analysis unravels the configurations with atomically distributed metal sites induced by d-π conjugation, which transforms into a mosaic structure with NiFe (oxy)hydroxides embedded in PPy matrix during oxygen evolution. The superior catalytic performance is ascribed to the anchoring effect of PPy that inhibits the metal dissolution, the strong substrate-to-catalyst interaction that ensures good adhesion, and the Fe/Ni-N coordination that modulates the electronic structures to facilitate the deprotonation of *OOH intermediate. This work provides a general strategy and mechanistic insight into building robust inorganic/polymer composite electrodes for oxygen electrocatalysis.

ELMO1 ameliorates intestinal epithelial cellular senescence via SIRT1/p65 signaling in inflammatory bowel disease-related fibrosis.

Background: Intestinal fibrosis is a common complication in inflammatory bowel disease (IBD), which still lacks of reliable markers and therapeutic options. Cellular senescence has been considered an important mechanism of intestinal fibrosis, but the underlying molecular link remains elusive. Methods: Tissues were stained using α-smooth muscle actin (α-SMA), fibronectin, and collagen I as markers of myofibroblastic differentiation. Cellular senescence was confirmed through Lamin B1 staining, senescence-associated ß-galactosidase staining, and the expression of senescence-associated secretory phenotype (SASP) factors. We explored the relationship between senescence of intestinal epithelial cells (IECs) and intestinal fibrosis, as well as the molecular mechanism underlying this interaction. The effects of irisin on cellular senescence and fibrosis were determined. Results: Here, we identify engulfment and cell motility protein 1 (ELMO1) as a novel biomarker for intestinal cellular senescence and fibrosis. In fibrostrictured tissues from patients and murine models with IBD, significantly high levels of cellular senescence score and factors were noted, which positively correlated with the fibrotic regulator fibronectin. Senescent IECs, not fibroblast itself, released SASP factors to regulate fibroblast activation. Prolonging exposure to severe and persistent injurious stimuli decreased ELMO1 expression, which dampened SIRT1 deacetylase activity, enhanced NF-κB (p65) acetylation, and thereby accelerated cellular senescence. Deletion of ELMO1 led to senescent IECs accumulation and triggered premature fibrosis in murine colitis. Furthermore, irisin, inhibiting the degradation of ELMO1, could downregulate p65 acetylation, reduce IECs senescence, and prevent incipient intestinal fibrosis in murine colitis models. Conclusions: This study reveals ELMO1 downregulation is an early symbol of intestinal senescence and fibrosis, and the altered ELMO1-SIRT1-p65 pathway plays an important role in intestinal cellular senescence and IBD-related fibrosis.

The EIF3H-HAX1 axis increases RAF-MEK-ERK signaling activity to promote colorectal cancer progression.

Eukaryotic initiation translation factor 3 subunit h (EIF3H) plays critical roles in regulating translational initiation and predicts poor cancer prognosis, but the mechanism underlying EIF3H tumorigenesis remains to be further elucidated. Here, we report that EIF3H is overexpressed in colorectal cancer (CRC) and correlates with poor prognosis. Conditional Eif3h deletion suppresses colorectal tumorigenesis in AOM/DSS model. Mechanistically, EIF3H functions as a deubiquitinase for HAX1 and stabilizes HAX1 via antagonizing ßTrCP-mediated ubiquitination, which enhances the interaction between RAF1, MEK1 and ERK1, thereby potentiating phosphorylation of ERK1/2. In addition, activation of Wnt/ß-catenin signaling induces EIF3H expression. EIF3H/HAX1 axis promotes CRC tumorigenesis and metastasis in mouse orthotopic cancer model. Significantly, combined targeting Wnt and RAF1-ERK1/2 signaling synergistically inhibits tumor growth in EIF3H-high patient-derived xenografts. These results uncover the important roles of EIF3H in mediating CRC progression through regulating HAX1 and RAF1-ERK1/2 signaling. EIF3H represents a promising therapeutic target and prognostic marker in CRC.

Favoring CO Intermediate Stabilization and Protonation by Crown Ether for CO2 Electromethanation in Acidic Media.

The large-scale deployment of CO2 electroreduction is hampered by deficient carbon utilization in neutral and alkaline electrolytes due to CO2 loss into (bi)carbonates. Switching to acidic media mitigates carbonation, but suffers from low product selectivity because of hydrogen evolution. Here we report a crown ether decoration strategy on a Cu catalyst to enhance carbon utilization and selectivity of CO2 methanation under acidic conditions. Macrocyclic 18-Crown-6 is found to enrich potassium cations near the Cu electrode surface, simultaneously enhancing the interfacial electric field to stabilize the *CO intermediate and accelerate water dissociation to boost *CO protonation. Remarkably, the mixture of 18-Crown-6 and Cu nanoparticles affords a CH4 Faradaic efficiency of 51.2 % and a single pass carbon efficiency of 43.0 % toward CO2 electroreduction in electrolyte with pH=2. This study provides a facile strategy to promote CH4 selectivity and carbon utilization by modifying Cu catalysts with supramolecules.

Immunotherapy in leukaemia.

Leukaemia is the common name for a group of malignant diseases of the haematopoietic system with complex classifications and characteristics. Remarkable progress has been made in basic research and preclinical studies for acute leukaemia compared to that of the many other types/subtypes of leukaemia, especially the exploration of the biological basis and application of immunotherapy in acute myeloid leukaemia (AML) and B-cell acute lymphoblastic leukaemia (B-ALL). In this review, we summarize the basic approaches to immunotherapy for leukaemia and focus on the research progress made in immunotherapy development for AML and ALL. Importantly, despite the advances made to date, big challenges still exist in the effectiveness of leukaemia immunotherapy, especially in AML. Therefore, we use AML as an example and summarize the mechanisms of tumour cell immune evasion, describe recently reported data and known therapeutic targets, and discuss the obstacles in finding suitable treatment targets and the results obtained in recent clinical trials for several types of single and combination immunotherapies, such as bispecific antibodies, cell therapies (CAR-T-cell treatment), and checkpoint blockade. Finally, we summarize novel immunotherapy strategies for treating lymphocytic leukaemia and clinical trial results.

Effectiveness of mHealth diet interventions in cancer survivors: A systematic review and meta-analysis of randomized controlled trials.

Objective: To evaluate the effects of mobile health (mHealth) diet interventions on cancer survivors' diet intake, weight change, waist circumference, hip circumference, and quality of life (QoL). Methods: The PubMed, Embase, Web of Science, Cochrane Library, Scopus, ProQuest, China National Knowledge Infrastructure, Wanfang, and SinoMed databases were searched from their inception to September 25, 2022. Randomized controlled trials (RCTs) on the effects of mHealth diet interventions in cancer survivors were identified. Two researchers independently selected the included studies and appraised their quality. The methodological quality of the included studies was assessed using the Revised Cochrane risk-of-bias tool for RCTs (RoB2). Results: A total of 15 RCTs involving 2363 cancer survivors were included. MHealth diet interventions significantly improved fruit and vegetable intake (standardized mean difference [SMD] â€‹= â€‹0.19, 95% confidence interval [CI] [0.05, 0.33], P â€‹< â€‹0.01), and QoL (SMD â€‹= â€‹0.13, 95% CI [0.01, 0.26], P â€‹= â€‹0.04) and reduced fat intake (SMD â€‹= â€‹-0.22, 95% CI [-0.34, -0.11], P â€‹< â€‹0.01), weight (SMD â€‹= â€‹-0.35, 95% CI [-0.48, -0.22], P â€‹< â€‹0.01), waist circumference (MD â€‹= â€‹-1.43, 95% CI [-2.33, -0.53], P â€‹< â€‹0.01), and hip circumference (MD â€‹= â€‹-3.54, 95% CI [-4.88, -2.19], P < 0.01) in cancer survivors. No significant differences were observed in energy intake (P â€‹= â€‹0.46) or whole grain intake (P â€‹= â€‹0.14). Conclusions: MHealth diet interventions may be an effective strategy for cancer survivors. Large-scale RCTs with rigorous study designs are needed to examine the effect of diet intervention delivered via mHealth.

Prognostic factors and the necessity of chemotherapy for stage II gastric cancer: a model based on multicenter retrospective study.

BACKGROUND: This study aimed to construct a prognostic model for prognosis prediction and assess the response to adjuvant chemotherapy (ACT) of stage II gastric cancer (GC) patients on high and low survival risk stratifications. METHODS: We retrospectively reviewed 547 stage II gastric cancer patients who underwent D2 radical gastrectomy from January 2009 to May 2017 in Sixth Affiliated Hospital of Sun Yat-Sen University (SAH-SYSU), the Fujian Medical University Union Hospital (FJUUH), and the Sun Yat-Sen University Cancer Center (SYSUCC).The propensity score matching (PSM) of all variables was performed to balance selective bias between ACT and surgery alone (SA) groups. Kaplan-Meier survival and multivariate Cox regression analyses were carried out to identify independent prognostic factors. Independent factors selected by the Cox regression were integrated into the nomogram. The nomogram points stratified patients into high-risk and low-risk groups by the optimal cut-off value. RESULTS: 278 patients were selected after PSM. Age, tumor site, T stage and lymph-nodes-examined (LNE) selected by Cox regression as independent prognostic factors were integrated into the nomogram. The nomogram performed well with a C-index of 0.76 and with C-indexes of 0.73 in and 0.71 in two validate cohorts. AUCs of the 3 year and 5 year ROC curves were 0.81 and 0.78. High- and low-risk groups stratified by the cut-off value demonstrated different responses to ACT. CONCLUSIONS: The nomogram performed well in prognosis prediction. Patients in high- and low-risk groups demonstrated different responses to ACT, and high-risk patients might need ACT.

Hollow Hierarchical Cu2 O-Derived Electrocatalysts Steering CO2 Reduction to Multi-Carbon Chemicals at Low Overpotentials.

The electrochemical reduction of carbon dioxide into multi-carbon products (C2+ ) using renewably generated electricity provides a promising pathway for energy and environmental sustainability. Various oxide-derived copper (OD-Cu) catalysts have been showcased, but still require high overpotential to drive C2+ production owing to sluggish carbon-carbon bond formation and low CO intermediate (*CO) coverage. Here, the dilemma is circumvented by elaborately devising the OD-Cu morphology. First, computational studies propose a hollow and hierarchical OD-Cu microstructure that can generate a core-shell microenvironment to inhibit CO evolution and accelerate *CO dimerization via intermediate confinement and electric field enhancement, thereby boosting C2+ generation. Experimentally, the designed nanoarchitectures are synthesized through a heteroseed-induced approach followed by electrochemical activation. In situ spectroscopic studies further elaborate correlation between *CO dimerization and designed architectures. Remarkably, the hierarchical OD-Cu manifests morphology-dependent selectivity of CO2 reduction, giving a C2+ Faradaic efficiency of 75.6% at a considerably positive potential of -0.55 V versus reversible hydrogen electrode.

Advanced lung cancer inflammation index predicts the outcomes of patients with non-metastatic gastric cancer after radical surgical resection.

Background: The prognostic value of the advanced lung cancer inflammation index (ALI) has been demonstrated in various tumors. However, the prognostic significance of ALI in non-metastatic gastric cancer (GC) remains unclear. This study aimed to identify the prognostic values of ALI in patients with non-metastatic GC who underwent radical surgical resection. Methods: Patients who underwent radical surgery for non-metastatic GC from January 2008 to September 2020 were enrolled in this study. The preoperative ALI was calculated as follows: body mass index × serum albumin/neutrophil to lymphocyte ratio. The primary outcomes were overall survival (OS) and cancer-specific survival (CSS). Cox regression analyses were performed to assess the association between ALI and survival. The potential of ALI was supported by sensitivity testing based on the propensity score matching (PSM) analysis. Results: Low preoperative ALI was significantly correlated with male gender (P=0.037), older age (P=0.004), T3/4 stage (P=0.001), lymph node metastasis (P=0.030), Tumor Node Metastasis (TNM) stage classification progression (P=0.004), and vessel invasion (P=0.001). Patients with low ALI showed worse OS (P<0.001) and CSS (P=0.001) compared to those with high ALI. Multivariable analysis showed that ALI was an independent prognostic factor for both OS [hazard ratio (HR) =1.55; 95% confidence interval (CI), 1.11-2.16]; P=0.010] and CSS (HR =1.46; 95% CI, 1.01-2.10; P=0.043) in non-metastatic GC patients who underwent radical surgical resection. Further PSM analysis confirmed the prognostic value of ALI in the PSM cohort. Conclusions: The preoperative ALI is associated with survival outcomes in patients who have undergone radical surgical resection for non-metastatic GC. Low ALI appears to predict a worse prognosis.

DeepGA for automatically estimating fetal gestational age through ultrasound imaging.

Accurate estimation of gestational age (GA) is vital for identifying fetal abnormalities. Conventionally, GA is estimated by measuring the morphology of the cranium, abdomen, and femur manually and inputting them into the classic Hadlock formula to assess fetal growth. However, this procedure incurs considerable overhead and suffers from bias caused by the operators, yielding suboptimal estimations. To address this challenge, we develop an automatic DeepGA model to achieve fully automatic GA prediction in an end-to-end manner. Our model uses a deep segmentation model (DeepSeg) to accurately identify and segment three critical tissues, including the cranium, abdomen, and femur, in which their morphology is automatically extracted. After that, we are able to directly estimate the GA via a deep regression model (DeepReg). We evaluate DeepGA on a large dataset, including 10,413 ultrasound images from 7113 subjects. It achieves superior performance over the traditional measurement approach, with a mean absolute estimation error (MAE) of 5 days. Our DeepGA model is a novel automatic solution on the basis of artificial intelligence learning that can help radiologists improve the performance of GA estimation in various clinical scenarios, thereby enhancing the efficiency of prenatal examinations.

Nomogram for predicting overall survival time of patients with stage IV colorectal cancer.

Background: Prognosis varies among stage IV colorectal cancer (CRC). Our study aimed to build a robust prognostic nomogram for predicting overall survival (OS) of patients with stage IV CRC in order to provide evidence for individualized treatment. Method: We collected the information of 16,283 patients with stage IV CRC in the Surveillance, Epidemiology, and End Results (SEER) database and then randomized these patients in a ratio of 7:3 into a training cohort and an internal validation cohort. In addition, 501 patients in the Sixth Affiliated Hospital of Sun Yat-sen University (Guangzhou, China) database were selected and used as an external validation cohort. Univariate and multivariate Cox analyses were used to screen out significant variables for nomogram establishment. The nomogram model was assessed using time-dependent receiver-operating characteristic curve (time-dependent ROC), concordance index (C-index), calibration curve, and decision curve analysis. Survival curves were plotted using the Kaplan-Meier method. Result: The C-index of the nomogram for OS in the training, internal validation, and external validation cohorts were 0.737, 0.727, and 0.655, respectively. ROC analysis and calibration curves pronounced robust discriminative ability of the model. Further, we divided the patients into a high-risk group and a low-risk group according to the nomogram. Corresponding Kaplan-Meier curves showed that the prediction of the nomogram was consistent with the actual practice. Additionally, model comparisons and decision curve analysis proved that the nomogram for predicting prognosis was significantly superior to the tumor-node-metastasis (TNM) staging system. Conclusions: We constructed a nomogram to predict OS of the stage IV CRC and externally validate its generalization, which was superior to the TNM staging system.

SIRGs score may be a predictor of prognosis and immunotherapy response for esophagogastric junction adenocarcinoma.

Background: Esophagogastric junction adenocarcinoma (EGJA) is a special malignant tumor with unknown biological behavior. PD-1 checkpoint inhibitors have been recommended as first-line treatment for advanced EGJA patients. However, the biomarkers for predicting immunotherapy response remain controversial. Methods: We identified stromal immune-related genes (SIRGs) by ESTIMATE from the TCGA-EGJA dataset and constructed a signature score. In addition, survival analysis was performed in both the TCGA cohort and GEO cohort. Subsequently, we explored the differences in tumor-infiltrating immune cells, immune subtypes, immune-related functions, tumor mutation burden (TMB), immune checkpoint gene expression, immunophenoscore (IPS) between the high SIRGs score and low SIRGs score groups. Finally, two validation cohorts of patients who had accepted immunotherapy was used to verify the value of SIRGs score in predicting immunotherapy response. Results: Eight of the SIRGs were selected by LASSO regression to construct a signature score (SIRGs score). Univariate and multivariate analyses in the TCGA and GEO cohort suggested that SIRGs score was an independent risk factor for the overall survival (OS) and it could increase the accuracy of clinical prediction models for survival. However, in the high SIRGs score group, patients had more immune cell infiltration, more active immune-related functions, higher immune checkpoint gene expression and higher IPS-PD1 and IPS-PD1-CTLA4 scores, which indicate a better response to immunotherapy. The external validation illustrated that high SIRGs score was significantly associated with immunotherapy response and immune checkpoint inhibitors (ICIs) can improve OS in patients with high SIRGs score. Conclusion: The SIRGs score may be a predictor of the prognosis and immune-therapy response for esophagogastric junction adenocarcinoma.

Indications for Adjuvant Chemotherapy in Stage II Gastric Cancer After D2 Gastrectomy-A Chinese Multicenter Study.

BACKGROUND: The benefit of adjuvant chemotherapy (AC) for patients with stage II gastric cancer remains controversial. This study aimed to explore the indications for adjuvant chemotherapy in patients with stage II gastric cancer by constructing an individual prediction model. PATIENTS AND METHODS: In this Chinese multicenter study, a total of 1012 patients with stage II gastric cancer after D2 radical gastrectomy were retrospectively analyzed. All patients were randomly assigned to a training cohort (n = 674) or a validation cohort (n = 338). A nomogram was constructed according to the training cohort. Concordance index (C-index), the area under the receiver operating characteristic (ROC) curves (AUC), calibration curves, and decision curve analysis (DCA) were applied to evaluate the performance of the nomogram. ROC curves and stratified survival were used to determine the patients' cutoff score for a benefit from adjuvant chemotherapy. An additional 338 patients were used as a validation cohort to validate the feasibility of using this nomogram to guide individualized therapy for patients with stage II gastric cancer. RESULTS: Univariate and multivariate analyses illustrated that age, sex, tumor location, size, carcinoembryonic antigen (CEA), hemoglobin (HB), and T stage were independent prognostic factors for overall survival (OS), and they were used to establish a nomogram. The cutoff value was determined by ROC curve analysis, and patients were divided into a high-risk group (< 239 points) and a low-risk group (≥ 239 points). There was no significant difference in the OS of low-risk patients in either the training cohort or the validation cohort. However, the OS of high-risk patients in the AC group was better than that of patients in the surgery-only group. CONCLUSIONS: This prediction model can be applied to guide treatment of patients with stage II gastric cancer. High-risk patients (< 239 points) are likely to benefit from AC after D2 radical gastrectomy.

Predicting pathologic complete response in locally advanced rectal cancer patients after neoadjuvant therapy: a machine learning model using XGBoost.

PURPOSE: Watch and wait strategy is a safe and effective alternative to surgery in patients with locally advanced rectal cancer (LARC) who have achieved pathological complete response (pCR) after neoadjuvant therapy (NAT); present restaging methods do not meet clinical needs. This study aimed to construct a machine learning (ML) model to predict pCR preoperatively. METHODS: LARC patients who received NAT were included to generate an extreme gradient boosting-based ML model to predict pCR. The group was divided into a training set and a tuning set at a 7:3 ratio. The SHapley Additive exPlanations value was used to quantify feature importance. The ML model was compared with a nomogram model developed using independent risk factors identified by conventional multivariate logistic regression analysis. RESULTS: Compared with the nomogram model, our ML model improved the area under the receiver operating characteristics from 0.72 to 0.95, sensitivity from 43 to 82.2%, and specificity from 87.1 to 91.6% in the training set, the same trend applied to the tuning set. Neoadjuvant radiotherapy, preoperative carbohydrate antigen 125 (CA125), CA199, carcinoembryonic antigen level, and depth of tumor invasion were significant in predicting pCR in both models. CONCLUSION: Our ML model is a potential alternative to the existing assessment tools to conduct triage treatment for patients and provides reference for clinicians in tailoring individual treatment: the watch and wait strategy is used to avoid surgical trauma in pCR patients, and non-pCR patients receive surgical treatment to avoid missing the optimal operation time window.

Compliance with Oral Nutritional Supplementation among Gastric Cancer Patients at Nutritional Risk: A Cross-Sectional Study.

AIMS: To explore compliance with oral nutritional supplementation (ONS) and to identify the risk factors for noncompliance among gastric cancer patients based on the health belief model (HBM). METHODS: This prospective, observational study included gastric cancer patients at nutritional risk who were prescribed ONS from July to September 2020. Demographic factors, clinical factors, ONS-related factors, social factors and variables derived from the HBM were collected. The outcome of interest was compliance with ONS, which was measured by self-reported intake of ONS. Uni- and multivariate analyses of potential risk factors for noncompliance were performed. RESULTS: A total of 162 gastric cancer patients in the preoperative and adjuvant chemotherapy periods were analyzed. The compliance rate with ONS was 24.7%. Univariate analysis identified thirteen variables as risk factors for decreased compliance. Multivariate logistic analysis indicated that ONS compliance was independently associated with the treatment period, perceived barriers to ONS, the motivation to take ONS, and the timing of taking ONS. CONCLUSION: This study showed that overall ONS compliance among gastric cancer patients was notably low. Patients in the chemotherapy treatment period who took ONS at random times each day perceived more barriers to taking ONS and had a lower level of motivation were associated with lower compliance with ONS.

Endoscopy-Based Deep Convolutional Neural Network Predicts Response to Neoadjuvant Treatment for Locally Advanced Rectal Cancer.

Background and Aims: Although the wait and watch (W&W) strategy is a treatment choice for locally advanced rectal cancer (LARC) patients who achieve clinical complete response (cCR) after neoadjuvant therapy (NT), the issue on consistency between cCR and pathological CR (pCR) remains unsettled. Herein, we aimed to develop a deep convolutional neural network (DCNN) model using endoscopic images of LARC patients after NT to distinguish tumor regression grade (TRG) 0 from non-TRG0, thus providing strength in identifying surgery candidates. Methods: A total of 1000 LARC patients (6,939 endoscopic images) who underwent radical surgery after NT from April 2013 to April 2021 at the Sixth Affiliated Hospital, Sun Yat-sen University were retrospectively included in our study. Patients were divided into three cohorts in chronological order: the training set for constructing the model, the validation set, and the independent test set for validating its predictive capability. Besides, we compared the model's performance with that of three endoscopists on a class-balanced, randomly selected subset of 20 patients' LARC images (10 TRG0 patients with 70 images and 10 non-TRG0 patients with 72 images). The measures used to evaluate the efficacy for identifying TRG0 included overall accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the receiver operating characteristic curve (AUROC). Results: There were 219 (21.9%) cases of TRG0 in the included patients. The constructed DCNN model in the training set obtained an excellent performance with good accuracy of 94.21%, specificity of 94.39%, NPV of 98.11%, and AUROC of 0.94. The validation set showed accuracy, specificity, NPV, and AUROC of 92.13%, 93.04%, 96.69%, and 0.95, respectively; the corresponding values in the independent set were 87.14%, 92.98%, 91.37%, and 0.77, respectively. In the reader study, the model outperformed the three experienced endoscopists with an AUROC of 0.85. Conclusions: The proposed DCNN model achieved high specificity and NPV in detecting TRG0 LARC tumors after NT, with a better performance than experienced endoscopists. As a supplement to radiological images, this model may serve as a useful tool for identifying surgery candidates in LARC patients after NT.

Risk factors for recurrence of colorectal conventional adenoma and serrated polyp.

Background: Removal of colorectal polyps during screening could reduce the incidence of colorectal cancer (CRC). However, there is a lack of data on risk factors associated with recurrence of polyps, including conventional adenomas and serrated polyps (SPs). This study aimed to determine risk factors for recurrence of colorectal polyps and their subtypes based on the characteristics of the patients and polyps. Methods: A total of 1,165 patients diagnosed with conventional adenoma or SP in the Sixth Affiliated Hospital of Sun Yat-sen University between January 2013 and December 2019 were enrolled in this study, including 668 cases with conventional adenomas, 385 with SPs, and 112 with coexistence of adenomas and SPs. Univariate analysis and multivariate logistic regression were used to identify potential risk factors for polyp recurrence. A nomogram was established according to risk factors and the performance was evaluated using calibration plots. Results: During a median follow-up of 24 months, recurrent polyps were observed in 531 (45.6%) cases. Male, age ≥50 years, body mass index (BMI) ≥24 kg/m2, at least three polyps, smoking, alcohol consumption, family history of polyps, and family history of CRC were independent risk factors for polyp recurrence. The Harrell's C-index of the nomogram developed with these parameters was 0.69 and the calibration plots showed good agreement between actual polyp recurrence and nomogram-predicted recurrence probability. In the subtype analyses, conventional adenomas had the same risk factors for recurrence as all polyps, while smoking, alcohol consumption, family history of polyps, and family history of CRC were not risk factors for SP recurrence. Conclusions: We identified several risk factors for recurrence of colorectal polyps and found that some of them could increase the risk of adenoma recurrence but not SP recurrence, including smoking, alcohol consumption, and family history of polyps/CRC, which might help us to understand different etiology and biology between conventional adenomas and SPs.

Clinicopathologic characteristics and prognosis of synchronous colorectal cancer: a retrospective study.

BACKGROUND: The clinical characteristics of synchronous colorectal cancer (SCRC) reported in previous studies differ significantly. Furthermore, little is known about the characteristics of early-onset synchronous colorectal cancer (EO-SCRC). The aim of this retrospective study was to identify the clinicopathological characteristics of SCRC and EO-SCRC and define their relevant prognostic factors. METHODS: Patients who underwent surgery for SCRC and primary unifocal colorectal cancer (PCRC) between January 2007 and December 2020 were included in this study. The clinical, histological, and molecular characteristics of the patient's tumours were analysed. The primary endpoint was overall survival (OS). Univariate and multivariate Cox regression analyses were used to assess the association between clinicopathological factors and patient survival. RESULTS: A total of 1554 patients were included in the analysis. Of these, 1132 (72.84%) had PCRC and 422 (27.16%) had SCRC. SCRC occurred more frequently in the elderly (P < 0.001) and in male patients (P = 0.002). The 5-year OS rate was 73.7% ± 2.0% for PCRC and 61.9% ± 3.9% for SCRC (P < 0.05). However, the Cox regression analysis showed that SCRC was not an independent prognostic factor for the prediction of OS. A total of 64 patients (15.17%) in the SCRC group had early-onset colorectal cancer (EOCRC), whereas 257 (22.70%) in the PCRC group had EOCRC (P = 0.001). The proportion of patients with deficient mismatch repair proteins (dMMR) in EO-SCRC subgroup was significantly higher than that in late-onset synchronous colorectal cancer (LO-SCRC) subgroup (23.44% vs. 10.34%, P = 0.006). Patients with EO-SCRC had more TNM stage IV (P < 0.001) and fewer opportunities for radical surgery (79.69% vs. 92.22%, P = 0.007) than those with early-onset primary unifocal colorectal cancer (EO-PCRC). There was no significant difference in 5-year OS between the EO-SCRC and LO-SCRC subgroups (P = 0.091) and between the EO-SCRC and EO-PCRC subgroups (P = 0.094). Multivariate analysis revealed that EOCRC was an independent good prognostic parameter for colorectal cancer (CRC) and SCRC. CONCLUSION: For patients with operative treatment, EO-SCRC is different from LO-SCRC and EO-PCRC. Patients with SCRC show a poorer survival rate than those with PCRC. However, SCRC is not an independent prognostic factor for CRC, whereas EOCRC is a good prognostic factor for CRC and SCRC.