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Abstract Background To study the pattern and treatment outcome of rectal cancer (RC) with concurrent locoregional recurrence (LR) and distant metastasis (DM) after total mesorectal excision (TME) and to identify patient-, disease-, and treatment-related factors associated with differences in prognosis after concurrent LR and DM. Methods RC patients who were diagnosed with concurrent LR and DM after TME from May 2015 to June 2019 were included in our study. All patients received single or multiple treatment modalities under the guidance of multidisciplinary team (MDT) of colorectal cancer in Fudan University Shanghai Cancer Center. The prognostic value of various clinicopathological factors for survival were calculated by Kaplan–Meier curves and Cox regression analyses. Results A total of 74 RC patients with concurrent LR and DM who had undergone TME with a median follow-up of 27 months were eligible for analysis. The median survival of the included patients was 34 months, and 30 patients (41%) died. Fifty-nine patients (80%) underwent comprehensive treatments. Patients with oligometastatic disease (OMD) achieved no evidence of disease (NED) status more frequently than those with multiple metastases (P = 0.003). In the univariate analysis, patients achieving NED, diagnosed with OMD and five or less peritoneal metastases tended to have longer survival after LR and DM diagnosis (P

Abstract Background Abnormal expression of protein tyrosine phosphatases (PTPs) has been reported to be a crucial cause of cancer. As a member of PTPs, protein tyrosine phosphatase receptor type O (PTPRO) has been revealed to play tumor suppressive roles in several cancers, while its roles in colorectal cancer (CRC) remains to be elucidated. Hence, we aimed to explore the roles and mechanisms of PTPRO in CRC initiation and progression. Methods The influences of PTPRO on the growth and liver metastasis of CRC cells and the expression patterns of different lipid metabolism enzymes were evaluated in vitro and in vivo. Molecular and biological experiments were conducted to uncover the underpinning mechanisms of dysregulated de novo lipogenesis and fatty acid β‐oxidation. Results PTPRO expression was notably downregulated in CRC liver metastasis compared to the primary cancer, and such a downregulation was associated with poor prognosis of patients with CRC. PTPRO silencing significantly promoted cell growth and liver metastasis. Compared with PTPRO wild‐type mice, PTPRO‐knockout mice developed more tumors and harbored larger tumor loads under treatment with azoxymethane and dextran sulfate sodium. Gene set enrichment analysis revealed that PTPRO downregulation was significantly associated with the fatty acid metabolism pathways. Blockage of fatty acid synthesis abrogated the effects of PTPRO silencing on cell growth and liver metastasis. Further experiments indicated that PTPRO silencing induced the activation of the AKT serine/threonine kinase (AKT)/mammalian target of rapamycin (mTOR) signaling axis, thus promoting de novo lipogenesis by enhancing the expression of sterol regulatory element‐binding protein 1 (SREBP1) and its target lipogenic enzyme acetyl‐CoA carboxylase alpha (ACC1) by activating the AKT/mTOR signaling pathway. Furthermore, PTPRO attenuation decreased the fatty acid oxidation rate by repressing the expression of peroxisome proliferator‐activated receptor alpha (PPARα) and its downstream enzyme peroxisomal acyl‐coenzyme A oxidase 1 (ACOX1) via activating the p38/extracellular signal‐regulated kinase (ERK) mitogen‐activated protein kinase (MAPK) signaling pathway. Conclusions PTPRO could suppress CRC development and metastasis via modulating the AKT/mTOR/SREBP1/ACC1 and MAPK/PPARα/ACOX1 pathways and reprogramming lipid metabolism.

Introduction: Most advanced colorectal cancers are aggressive, and there is a lack of effective methods for selecting appropriate anticancer regimens. Patient-derived organoids (PDOs) have emerged as preclinical platforms for modeling clinical responses to cancer therapy.Methods: In this study, we successfully constructed a living biobank with 42 organoids derived from primary and metastatic lesions of metastatic colorectal cancer patients. Tumor tissue was obtained from patients undergoing surgical resection of the primary or metastatic lesion and then used to establish PDOs. Immunohistochemistry (IHC) and drug sensitivity assays were performed to analyze the properties of these organoids.Results: The mCRC organoids were successfully established with an 80% success rate. The PDOs maintained the genetic and phenotypic heterogeneity of their parental tumors. The IC50 values of5-fluorouracil (5-FU), oxaliplatin, and irinotecan (CPT11) were determined for mCRC organoids using drug sensitivity assays. The in vitro chemosensitivity data revealed the potential value of PDOs for clinical applications in predicting chemotherapy response and clinical outcomes in mCRC patients.Discussion: In summary, the PDO model is an effective platform for in vitro assessment of patient-specific drug sensitivity, which can guide personalized treatment decisions for patients with end-stage CRC.

Abstract Early detection can benefit cancer patients with more effective treatments and better prognosis, but existing early screening tests are limited, especially for multi-cancer detection. This study investigated the most prevalent and lethal cancer types, including primary liver cancer (PLC), colorectal adenocarcinoma (CRC), and lung adenocarcinoma (LUAD). Leveraging the emerging cell-free DNA (cfDNA) fragmentomics, we developed a robust machine learning model for multi-cancer early detection. 1,214 participants, including 381 PLC, 298 CRC, 292 LUAD patients, and 243 healthy volunteers, were enrolled. The majority of patients (N = 971) were at early stages (stage 0, N = 34; stage I, N = 799). The participants were randomly divided into a training cohort and a test cohort in a 1:1 ratio while maintaining the ratio for the major histology subtypes. An ensemble stacked machine learning approach was developed using multiple plasma cfDNA fragmentomic features. The model was trained solely in the training cohort and then evaluated in the test cohort. Our model showed an Area Under the Curve (AUC) of 0.983 for differentiating cancer patients from healthy individuals. At 95.0% specificity, the sensitivity of detecting all cancer reached 95.5%, while 100%, 94.6%, and 90.4% for PLC, CRC, and LUAD, individually. The cancer origin model demonstrated an overall 93.1% accuracy for predicting cancer origin in the test cohort (97.4%, 94.3%, and 85.6% for PLC, CRC, and LUAD, respectively). Our model sensitivity is consistently high for early-stage and small-size tumors. Furthermore, its detection and origin classification power remained superior when reducing sequencing depth to 1× (cancer detection: ≥ 91.5% sensitivity at 95.0% specificity; cancer origin: ≥ 91.6% accuracy). In conclusion, we have incorporated plasma cfDNA fragmentomics into the ensemble stacked model and established an ultrasensitive assay for multi-cancer early detection, shedding light on developing cancer early screening in clinical practice.

Abstract Background Organoids are three-dimensional structures that closely recapitulate tissue architecture and cellular composition, thereby holding great promise for organoid-based drug screening. Although growing in three-dimensional provides the possibility for organoids to recapitulate main features of corresponding tissues, it makes it incommodious for imaging organoids in two-dimensional and identifying surviving organoids from surrounding dead cells after organoids being treated by irradiation or chemotherapy. Therefore, significant work remains to establish high-quality controls to standardize organoid analyses and make organoid models more reproducible. Methods In this study, the Z-stack imaging technique was used for the imaging of three-dimensional organoids to gather all the organoids’ maximum cross sections in one imaging. The combination of live cell staining fluorescent dye Calcein-AM and ImageJ assessment was used to analyze the survival of organoids treated by irradiation or chemotherapy. Results We have established a novel quantitative high-throughput imaging assay that harnesses the scalability of organoid cultures. Using this assay, we can capture organoid growth over time, measure multiple whole-well organoid readouts, and show the different responses to drug treatments. Conclusions In summary, combining the Z-stack imaging technique and fluorescent labeling methods, we established an assay for the imaging and analysis of three-dimensional organoids. Our data demonstrated the feasibility of using organoid-based platforms for high-throughput drug screening assays. Graphical Abstract

Abstract Background Necroptosis is a new form of programmed cell death that is associated with cancer initiation, progression, immunity, and chemoresistance. However, the roles of necroptosis-related genes (NRGs) in colorectal cancer (CRC) have not been explored comprehensively. Methods In this study, we obtained NRGs and performed consensus molecular subtyping by “ConsensusClusterPlus” to determine necroptosis-related subtypes in CRC bulk transcriptomic data. The ssGSEA and CIBERSORT algorithms were used to evaluate the relative infiltration levels of different cell types in the tumor microenvironment (TME). Single-cell transcriptomic analysis was performed to confirm classification related to NRGs. NRG_score was developed to predict patients’ survival outcomes with low-throughput validation in a patients’ cohort from Fudan University Shanghai Cancer Center. Results We identified three distinct necroptosis-related classifications (NRCs) with discrepant clinical outcomes and biological functions. Characterization of TME revealed that there were two stable necroptosis-related phenotypes in CRC: a phenotype characterized by few TME cells infiltration but with EMT/TGF-pathways activation, and another phenotype recognized as immune-excluded. NRG_score for predicting survival outcomes was established and its predictive capability was verified. In addition, we found NRCs and NRG_score could be used for patient or drug selection when considering immunotherapy and chemotherapy. Conclusions Based on comprehensive analysis, we revealed the potential roles of NRGs in the TME, and their correlations with clinicopathological parameters and patients’ prognosis in CRC. These findings could enhance our understanding of the biological functions of necroptosis, which thus may aid in prognosis prediction, drug selection, and therapeutics development.

Abstract Background The association between tumour microenvironment (TME) in colorectal cancer (CRC) and cell death patterns requires further exploration. Cuproptosis may provide new insight into analyzing CRC's TME. Methods We used cuproptosis‐related genes (CRGs) to stratify the meta‐Gene‐Expression Omnibus cohort by the “non‐negative matrix factorization” consistency matrix algorithm. To clarify the relative abundance of different cells in TME, CIBERSORT and single‐sample gene set enrichment methods were performed. Then, CRGs’ transcription in different cell types and the spatial position of CRGs’ enrichment were demonstrated through single‐cell spatial transcriptomics (STs) analysis. Prediction of clinical outcomes and response rate of immunotherapy was also conducted by constructing CRG_score. Results Three cuproptosis‐related TME phenotypes were figured out in CRC with distinctive clinicopathological and prognostic features. Three phenotypes were identical to immune‐inflamed, immune‐desert and immune‐excluded profiles, respectively. Interestingly, cuproptosis‐related cluster 3 (CPRC3) phenotype‐related gene_score was predominantly upregulated in the fibroblast region, consisting of stromal cells. This result was in line with CPRC3's immune‐excluded profile. Based on the robust cuproptosis‐related risk_score and nomogram, CRC patients’ clinical outcome and response to PD1/PD‐L1 immunotherapy can be well predicted. Conclusions This study characterized three cuproptosis‐related TME patterns with unique immune infiltration and prognosis in both bulk and single‐cell ST profiling. Risk_score was also built to help clinicians decide on personalized anticancer treatment and immunotherapy applications for CRC patients.

Summary: Background: Early detection and prognosis prediction of colorectal cancer (CRC) can significantly reduce CRC-related mortality. Recently, circulating tumour DNA (ctDNA) methylation has shown good application foreground in the early detection and prognosis prediction of multiple tumours. Methods: This multicentre cohort study evaluated ctDNA methylation haplotype patterns based on archived plasma samples (collected between 2010 and 2018) from 1138 individuals at two medical centres: Fudan University Shanghai Cancer Center (Shanghai, China) and Southern Medical University Nanfang Hospital (Guangzhou, Guangdong, China), including 366 healthy individuals, 182 patients with advanced adenoma (AA), and 590 patients with CRC. Samples were processed using the ColonES assay, a targeted bisulfite sequencing method that detects ctDNA methylation haplotype patterns in 191 genomic regions. Among these 1138 samples, 748 were used to develop a classification model, and 390 served as a blinded cohort for independent validation. The study is registered at https://register.clinicaltrials.gov with the unique identifier NCT03737591. Results: The model obtained from unblinded samples discriminated patients with CRC or AA from normal controls with high accuracy. In the blinded validation set, the ColonES assay achieved sensitivity values of 79.0% (95% confidence interval (CI), 66%–88%) in AA patients and 86.6% (95% CI, 81%–91%) in CRC patients with a specificity of 88.1% (95% CI, 81%–93%) in healthy individuals. The model area under the curve (AUC) for the blinded validation set was 0.903 for AA samples and 0.937 for CRC samples. Additionally, the prognosis of patients with high preoperative ctDNA methylation levels was worse than that of patients with low ctDNA methylation levels (p = 0.001 for relapse-free survival and p = 0.004 for overall survival). Interpretation: We successfully developed and validated an accurate, noninvasive detection method based on ctDNA methylation haplotype patterns that may enable early detection and prognosis prediction for CRC. Funding: The Grant of National Natural Science Foundation of China (No.81871958), National Natural Science Foundation of China (No. 82203215), Shanghai Science and Technology Committee (No. 19140902100), Scientific Research Fund of Fudan University (No.IDF159052), Shanghai Municipal Health Commission (SHWJRS 2021-99), and Shanghai Sailing Program (22YF1408800).

Abstract Background Resistance to oxaliplatin is a major obstacle for the management of locally advanced and metastatic colon cancer (CC). Although long noncoding RNAs (lncRNAs) play key roles in CC, the relationships between lncRNAs and resistance to oxaliplatin have been poorly understood yet. Methods Chemo-sensitive and chemo-resistant organoids were established from colon cancer tissues of the oxaliplatin-sensitive or -resistant patients. Analysis of the patient cohort indicated that lnc-RP11-536 K7.3 had a potential oncogenic role in CC. Further, a series of functional in vitro and in vivo experiments were conducted to assess the effects of lnc-RP11-536 K7.3 on CC proliferation, glycolysis, and angiogenesis. RNA pull-down assay, luciferase reporter and fluorescent in situ hybridization assays were used to confirm the interactions between lnc-RP11-536 K7.3, SOX2 and their downstream target HIF-1α. Results In this study, we identified a novel lncRNA, lnc-RP11-536 K7.3, was associated with resistance to oxaliplatin and predicted a poor survival. Knockout of lnc-RP11-536 K7.3 inhibited the proliferation, glycolysis, and angiogenesis, whereas enhanced chemosensitivity in chemo-resistant organoids and CC cells both in vitro and in vivo. Furthermore, we found that lnc-RP11-536 K7.3 recruited SOX2 to transcriptionally activate USP7 mRNA expression. The accumulative USP7 resulted in deubiquitylation and stabilization of HIF-1α, thereby facilitating resistance to oxaliplatin. Conclusion In conclusion, our findings indicated that lnc-RP11-536 K7.3 could promote proliferation, glycolysis, angiogenesis, and chemo-resistance in CC by SOX2/USP7/HIF-1α signaling axis. This revealed a new insight into how lncRNA could regulate chemosensitivity and provide a potential therapeutic target for reversing resistance to oxaliplatin in the management of CC.

Abstract Previous studies on liquid biopsy-based early detection of advanced colorectal adenoma (advCRA) or adenocarcinoma (CRC) were limited by low sensitivity. We performed a prospective study to establish an integrated model using fragmentomic profiles of plasma cell-free DNA (cfDNA) for accurately and cost-effectively detecting early-stage CRC and advCRA. The training cohort enrolled 310 participants, including 149 early-stage CRC patients, 46 advCRA patients and 115 healthy controls. Plasma cfDNA samples were prepared for whole-genome sequencing. An ensemble stacked model differentiating healthy controls from advCRA/early-stage CRC patients was trained using five machine learning models and five cfDNA fragmentomic features based on the training cohort. The model was subsequently validated using an independent test cohort (N = 311; including 149 early-stage CRC, 46 advCRA and 116 healthy controls). Our model showed an area under the curve (AUC) of 0.988 for differentiating advCRA/early-stage CRC patients from healthy individuals in an independent test cohort. The model performed even better for identifying early-stage CRC (AUC 0.990) compared to advCRA (AUC 0.982). At 94.8% specificity, the sensitivities for detecting advCRA and early-stage CRC reached 95.7% and 98.0% (0: 94.1%; I: 98.5%), respectively. Promisingly, the detection sensitivity has reached 100% and 97.6% in early-stage CRC patients with negative fecal occult or CEA blood test results, respectively. Finally, our model maintained promising performances (AUC: 0.982, 94.4% sensitivity at 94.8% specificity) even when sequencing depth was down-sampled to 1X. Our integrated predictive model demonstrated an unprecedented detection sensitivity for advCRA and early-stage CRC, shedding light on more accurate noninvasive CRC screening in clinical practice.

Abstract There is no effective method to predict chemotherapy response and postoperative prognosis of colorectal cancer liver metastasis (CRLM) patients. Patient‐derived organoid (PDO) has become an important preclinical model. Herein, a living biobank with 50 CRLM organoids derived from primary tumors and paired liver metastatic lesions is successfully constructed. CRLM PDOs from the multiomics levels (histopathology, genome, transcriptome and single‐cell sequencing) are comprehensively analyzed and confirmed that this organoid platform for CRLM could capture intra‐ and interpatient heterogeneity. The chemosensitivity data in vitro reveal the potential value of clinical application for PDOs to predict chemotherapy response (FOLFOX or FOLFIRI) and clinical prognosis of CRLM patients. Taken together, CRLM PDOs can be utilized to deliver a potential application for personalized medicine.

Abstract Tumor metastasis accounts for the majority of cancer-related deaths; it is therefore important to develop preclinical models that faithfully recapitulate disease progression. Here, we generated paired organoids derived from primary tumors and matched liver metastases in the same colorectal cancer (CRC) patients. Despite the fact that paired organoids exhibit comparable gene expression and cell morphology, organoids from metastatic lesions demonstrate more aggressive phenotypes, tumorigenesis, and metastatic capacity than those from primary lesions. Transcriptional analyses of the paired organoids reveal signature genes and pathways altered during the progression of CRC, including SOX2. Further study shows that inducible knockdown of SOX2 attenuated invasion, proliferation, and liver metastasis outgrowth. Taken together, we use patient-derived paired primary and metastatic cancer organoids to model CRC metastasis and illustrate that SOX2 is associated with CRC progression and may serve as a potential prognostic biomarker and therapeutic target of CRC.

Abstract Background Survival outcomes are significantly different in stage II colorectal cancer (CRC) patients with diverse clinicopathological features. The objective of this study is to establish a credible prognostic nomogram incorporating easily obtained parameters for stage II CRC patients. Methods A total of 1708 stage II CRC patients seen at Fudan University Shanghai Cancer Center (FUSCC) from 2008 to 2013 were retrospectively analyzed in this study. Cases were randomly separated into a training set (n = 1084) and a validation set (n = 624). Univariate and multivariate Cox regression analyses were used to identify independent prognostic factors that were subsequently incorporated into a nomogram. The performance of the nomogram was evaluated by the predicted concordance index (C-index) and ROC curve to calculate the area under the curve (AUC). The clinical utility of the nomogram was evaluated using decision curve analysis (DCA). Results In univariate and multivariate analyses, eight parameters were correlated with disease-free survival (DFS), which were subsequently selected to generate a prognostic nomogram based on DFS. For DFS predictions, the C-index values of the nomogram were 0.842 (95% confidence interval (CI) 0.710–0.980), and 0.701 (95% CI 0.610–0.770) for the training and validation sets, respectively. The AUC values of the ROC curves for the nomogram to predicted 1, 3 and 5-year survival were 0.869, 0.858, and 0.777 (training group) and 0.673, 0.714, and 0.706 (validation group), respectively. The recurrence probability calibration curve showed good consistency between actual observations and nomogram-based predictions. DCA showed better clinical application value for the nomogram than the TNM staging system. Conclusion A novel nomogram was established and validated in a large population, and the nomogram is a simple-to-use tool for physicians to facilitate postoperative personalized prognostic evaluation and determine therapeutic strategies for stage II CRC patients.

Abstract Accurate identification of patients with poor prognosis after radical surgery is essential for clinical management of colon cancer. Thus, we aimed to develop death and relapse specific radiomics signatures to individually estimate overall survival (OS) and relapse free survival (RFS) of colon cancer patients. In this study, 701 stage I‐III colon cancer patients were identified from Fudan University Shanghai Cancer Center. A total of 647 three‐dimensional features were extracted from computed tomography images. LASSO Cox was used to identify the significantly death‐ and relapse‐associated features and to build death and relapse specific radiomics signatures, respectively. A total of 13 death‐specific and 26 relapse‐specific features were identified from 647 screened radiomics features. The developed signatures can divide patients into two groups with significantly different death (Hazard Ratio (HR): 3.053; 95% CI, 1.78‐5.23; P

Abstract Background It is critical for determining the optimum therapeutic solutions for T1‐2 colorectal cancer (CRC) to accurately predict lymph node metastasis (LNM) status. The purpose of the present study is to establish and verify a nomogram to predict LNM status in T1‐2 CRCs. Methods A total of 16 600 T1‐2 CRC patients were enrolled and classified into the training, internal validation, and external validation cohorts. The independent predictive parameters were determined by univariate and multivariate analyses to develop a nomogram to predict the probability of LNM status. The calibration curve, the area under the receiver operating characteristic curve (AUROC), and decision curve analysis (DCA) were used to evaluate the performance of the nomogram, and an external verification cohort was to verify the applicability of the nomogram. Results Seven independent predictors of LNM in T1‐2 CRC were identified in the multivariable analysis, including age, tumor site, tumor grade, perineural invasion, preoperative carcinoembryonic antigen, clinical assessment of LNM, and T stage. A nomogram incorporating the seven predictors was constructed. The nomogram yielded good discrimination and calibration, with AUROCs of 0.72 (95% confidence interval [CI]: 0.70‐0.75), 0.70 (95% CI: 0.67‐0.74), and 0.74 (95% CI: 0.71‐0.79) in the training, internal validation, and external validation cohorts, respectively. DCA showed that the predictive scoring system had high clinical application value. Conclusions We proposed a novel predictive model for LNM in T1‐2 CRC patients to assist physicians in making treatment decisions. The nomogram is advantageous for tailoring therapy in T1‐2 CRC patients.

Abstract Background This study aims to develop functional nomograms to predict specific distant metastatic sites and overall survival (OS) of colorectal cancer (CRC) patients. Methods CRC case data were retrospectively recruited from a large population‐based public dataset. Nomograms were developed to predict the probabilities of specific distant metastatic sites and OS of CRC patients. The performance of nomogram was evaluated with the concordance index (C‐index), calibration curves, area under the curve (AUC), and decision curve analysis (DCA). Results A total of 142 343 cases were included in the current study. On the basis of univariate and multivariate analyses, clinicopathological features were correlated with specific distant metastatic sites and survival outcomes and were used to establish nomograms. The nomograms showed excellent accuracy in predicting specific distant metastatic sites. The C‐indexes for the prediction of liver, lung, bone, and brain metastases were 0.82 (95% confidence interval (CI), 0.81‐0.83), 0.80 (95% CI, 0.78‐0.81), 0.83 (95% CI, 0.79‐0.86), and 0.73 (95% CI, 0.72‐0.84), respectively. Then, a prognostic nomogram integrating clinicopathological features and specific distant metastatic sites was established to predict 1‐, 3‐, and 5‐year OS of CRC, with AUCs of 0.764 (95% CI, 0.741‐0.783), 0.762 (95% CI, 0.745‐0.781), and 0.745 (95% CI, 0.730‐0.761), respectively. DCA showed that the prognostic nomogram had a better clinical application value than current TNM staging system. Conclusions Based on clinicopathological features, original nomograms were constructed for clinicians to predict specific distant metastatic sites and OS of CRC patients. These models could help to support the postoperative personalized assessment.

Abstract Background Low expression of FOXE1, a member of Forkhead box (FOX) transcription factor family that plays vital roles in cancers, contributes to poor prognosis of colorectal cancer (CRC) patients. However, the underlying mechanism remains unclear. Materials and methods The effects of FOXE1 on the growth of colon cancer cells and the expression of glycolytic enzymes were investigated in vitro and in vivo. Molecular biological experiments were used to reveal the underlying mechanisms of altered aerobic glycolysis. CRC tissue specimens were used to determine the clinical association of ectopic metabolism caused by dysregulated FOXE1. Results FOXE1 is highly expressed in normal colon tissues compared with cancer tissues and low expression of FOXE1 is significantly associated with poor prognosis of CRC patients. Silencing FOXE1 in CRC cell lines dramatically enhanced cell proliferation and colony formation and promoted glucose consumption and lactate production, while enforced expression of FOXE1 manifested the opposite effects. Mechanistically, FOXE1 bound directly to the promoter region of HK2 and negatively regulated its transcription. Furthermore, the expression of FOXE1 in CRC tissues was negatively correlated with that of HK2. Conclusion FOXE1 functions as a critical tumor suppressor in regulating tumor growth and glycolysis via suppressing HK2 in CRC.

Abstract Background The purpose of this study was to build functional nomograms based on significant clinicopathological features to predict cause-specific survival (CSS) and overall survival (OS) in patients with stage I–III colon cancer. Methods Data on patients diagnosed with stage I–III colon cancer between 2010 and 2015 were downloaded from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox analyses were used to identify independent prognostic factors, which were used to construct nomograms to predict the probabilities of CSS and OS. The performance of the nomogram was assessed by C-indexes, receiver operating characteristic (ROC) curves and calibration curves. Decision curve analysis (DCA) was used to compare clinical usage between the nomogram and the tumor–node–metastasis (TNM) staging system. Results Based on the univariate and multivariate analyses, features that correlated with survival outcomes were used to establish nomograms for CSS and OS prediction. The nomograms showed favorable sensitivity at predicting 1-, 3-, and 5-year CSS and OS, with a C-index of 0.78 (95% confidence interval (CI) 0.77–0.80) for CSS and 0.74 (95% CI 0.73–0.75) for OS. Calibration curves and ROC curves revealed excellent predictive accuracy. The clinically and statistically significant prognostic performance of the nomogram generated with the entire group of patients and risk scores was validated by a stratified analysis. DCA showed that the nomograms were more clinically useful than TNM stage. Conclusion Novel nomograms based on significant clinicopathological characteristics were developed and can be used as a tool for clinicians to predict CSS and OS in stage I–III colon cancer patients. These models could help facilitate a personalized postoperative evaluation.

Lymph node metastasis (LNM) is closely related to the postoperative recurrence of colorectal cancer (CRC), and greatly affects patient survival. Conducting Gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA), we found that the epithelial-mesenchymal transition (EMT) signaling pathway is the signaling pathway most relevant to the process of LNM. An EMT-related gene signature was identified from a discovery dataset obtained 489 patients using LIMMA and LASSO Cox methods. Six external independent dataset analyses including a total of 1,045 CRC patients and stratification analysis showed that EMT-related gene signature could sort out those high- and low-risk CRC patients accurately. Functional analysis and loss-of-function exploration in vitro and in vivo indicated that the EMT-related-signature-associated coding genes might play functional roles in the sophisticated regulation of CRC proliferation and metastasis. Prognostic nomograms integrating the EMT-related gene signature and clinicopathological risk factors were constructed for use as numerical prediction tools to assess clinical prognosis and clinical decision-makings. The comprehensive transcriptomic analysis in this article highlights the prognostic value of an EMT-related gene signature for postoperative disease recurrence in CRC patients and reveals a potential prognostic and therapeutic biomarker for CRC.

BackgroundFecal immunochemical test (FIT), DNA mutation, DNA methylation, and microbial dysbiosis all showed promising in colorectal cancer (CRC) non-invasive detection. We assessed CRC detection with an assay combining all these strategies and investigated the effect of clinical features on the performance of this comprehensive test.MethodsWe performed a multidimensional analysis study using stool samples collected from 108 patients with CRC, 18 patients with colorectal adenoma, and 36 individuals with no evidence of colorectal disease. The multidimensional analysis of stool samples including FIT, stool DNA (sDNA) tests for three methylated genes (Septin9, NDRG4, BMP3) and three mutated genes (KRAS, BRAF, PI3KCA) using next generation sequencing as well as detection of stool bacteria level of Fusobacterium nucleatum and Parvimonas micra using qPCR method. We used a linear support vector classification model to analyze the data.ResultsThe sensitivity of FIT alone was 69.4% for CRC and 11.1% for adenoma. Separately, the sensitivity of the detection of intestinal bacteria, DNA mutation, and DNA methylation for CRC was 58.3, 50.0, and 51.9%, respectively. The combination of FIT and sDNA tests had a sensitivity of 81.5% for CRC (AUC: 0.93, better than FIT alone, P = 0.017) and 27.8% for adenoma with 94.4% specificity. Sensitivity of the multidimensional test to detect CRC with stage II (84.6%) and III (91.9%) CRC was relatively higher (88.2%) than that of patients with stage I (60.0%) and stage IV (75.0%) (P = 0.024). The rate of CRC detection increased with tumor size (P = 0.008) and age (P = 0.04). Interestingly, the rate of CRC detection was higher in smoking persons than non-smokers with marginal significance (P = 0.08).ConclusionsThe multidimensional assay of stool samples combining FIT and stool DNA tests further improved the diagnostic sensitivity for CRC. This could provide new approach for improvement of CRC screening and further demonstrations are warranted.

Previous studies found patients with POLE exonuclease domain mutations (EDMs) in targeted exons were related to significant better outcomes in stage II-III colorectal cancer (CRC). The detailed mutational profile of the entire POLE exonuclease domain, tumor mutation burden (TMB) and immune cell infiltration in POLE EDMs tumors, and the prognostic value of such mutations in stage II CRCs were largely unknown to us. This study was to clarify the characteristics, immune response and prognostic value of somatic POLE EDMs in stage II CRC. A total of 295 patients with stage II CRC were sequenced by next-generation sequencing with a targeted genetic panel. Simultaneous detection of the immune cells was conducted using a five-color immunohistochemical multiplex technique. The detailed molecular characteristics, tumor-infiltrating lymphocyte (TIL) and prognostic effect of POLE EDMs in stage II CRC were analyzed. For stage II CRCs, the POLE EDMs were detected in 3.1% of patients. Patients with POLE EDMs were more prone to be microsatellite instability-high (MSI-H) (33.3% vs 11.2%, p=0.043), younger at diagnosis (median 46 years vs 62 years, p

Purpose: To reveal changes in the incidence, treatment, and survival of patients with colorectal lymphoma.Methods: Patients diagnosed with primary colorectal lymphoma (PCL) or lymphoma between 1973 and 2014 were identified in the SEER registry. The incidence was estimated by age and join-point analysis. The incidence of different subtypes and the surgical resection rates were compared over different time periods.Results: The PCL incidence increased from 1.4 per 1 000 000 people in 1973 to 3.5 in 2014, with an annual percentage change (APC) of 1.98% (95% confidence interval [CI]: 1.29–2.68%, P < 0.001) from 1985 to 2014. No statistically significant change was found between 1973 and 1984. For people younger than 60 years, there was a slight increase in PCL incidence, from 0.6 to 1.4%, from 1973 to 2014. For people age 60 or older, there was a statistically significant increase in PCL incidence from 5.4 to 14.1% over the same time period. The 5-year cause-specific survival (CSS) for PCL improved markedly from 41.6% in the period 1973–1976 to 80.2% in the period 2009–2012 (P < 0.001). Conversely, the proportion of patients who received surgical therapy decreased gradually from 83.3–100 to 47.7–52.6% throughout the studied time period.Conclusions: The incidence of PLC has increased in recent decades. The 5-year CSS of PCL increased continuously, while the rate of surgical resection decreased steadily. These changes in survival trends and therapy strategies indicate that PCL can be well-managed with newer therapeutic reagents.

BackgroundMethylation of N6 adenosine (m6A) plays important regulatory roles in diverse biological processes. The purpose of this research was to explore the potential mechanism of m6A modification level on the clinical outcome of stage III colorectal cancer (CRC).MethodsGene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) were adopted to reveal the signal pathway which was most likely affected by m6A methylation. The linear models for microarray data (LIMMA) method and the least absolute shrink-age and selection operator (LASSO) Cox regression model were used to identify the signature. The signature can sensitively separate the patients into high and low risk indicating the relapse-free survival (RFS) time based on time-dependent receiver operating characteristic (ROC) analysis. Then, the multi-gene signature was validated in GSE14333 and the Cancer Genome Atlas (TCGA) cohort. The number of the samples in GSE14333 and TCGA cohort are 63 and 150. Finally, two nomograms were set up and validated to predict prognosis of patients with stage III CRC.ResultsThe hematopoietic cell lineage (HCL) signaling pathway was disclosed through GSEA and GSVA. Seven HCL-related genes were determined in the LASSO model to construct signature, with AUC 0.663, 0.708, and 0.703 at 1-, 3-, and 5-year RFS, respectively. Independent datasets analysis and stratification analysis indicated that the HCL-related signature was reliable in distinguishing high- and low-risk stage III CRC patients. Two nomograms incorporating the signature and pathological N stage were set up, which yielded good discrimination and calibration in the predictions of prognosis for stage III CRC patients.ConclusionsA novel HCL-related signature was developed as a predictive model for survival rate of stage III CRC patients. Nomograms based on the signature were advantageous to facilitate personalized counseling and treatment in stage III CRC.

Background/Aims: Alpha-fetoprotein-producing colorectal cancer (AFPP-CRC) is quite rarely seen. This study aimed to elucidate the clinicopathologic characteristics and prognostic factors of AFPP-CRC. Methods: Among 5,051 colorectal cancer patients receiving surgery in the Fudan University Shanghai Cancer Center from 2006 to 2016, we identified 78 patients with elevated serum level of AFP (> 10 µg/L) preoperatively. A propensity score matching (PSM) analysis was performed which matched 75 AFPP-CRC patients to the same number of AFP-negative colorectal cancer (AFPN-CRC) patients. Kaplan-Meier curves were compared using the log-rank test and multivariable analysis was performed to evaluate the effect of AFP-positivity while adjusting confounding factors. 27 patients were available for immunohistochemical analysis. We conducted functional experiments to characterize the tumorigenicity of AFP. Results: Patients with AFPP-CRC had a significantly higher incidence of advanced TNM stage and liver metastasis. Overall survival was significantly different between two groups before and after PSM, and AFP-positivity was one of the strongest predictors of overall survival in the multivariable model (HR 4.11, CI 95%: 1.43-11.76, p = 0.009) after PSM. We further investigated prognostic factors affecting prognosis in AFPP-CRC and found that the presence of liver metastasis was the only independent prognostic factor (HR 4.95, CI 95%: 1.48-16.48, p = 0.009). AFP expression was significantly positively correlated with HGF and c-Met expression. Transwell invasion assay revealed significantly increased cell motility with AFP overexpression. Conclusion: AFP-positivity is a significant negative predictor of overall survival in patients with colorectal cancer, which may be mediated by HGF/c-Met signaling pathway.

Colon cancer patients experiencing early relapse consistently exhibited poor survival. The aim of our study was to develop an mRNA signature that can help to detect early relapse cases in stage I–III colon cancer. Public microarray datasets of stage I–III colon cancer samples were extracted from the Gene Expression Omnibus database. Propensity score matching analysis was performed between patients in the early relapse group and the long‐term survival group from GSE39582 discovery series (N = 386), and patients were 1 : 1 matched. Global mRNA expression changes were then analyzed between the paired groups to identify the differentially expressed genes. Lasso Cox regression modeling analysis was conducted for the selection of prognostic mRNA. Fifteen mRNA were finally identified to build an early relapse classifier. With specific risk score formula, patients were classified into a high‐risk group and a low‐risk group. Relapse‐free survival was significantly different between the two groups in every series, including discovery [hazard ratio (HR): 2.547, 95% confidence interval (CI): 1.708–3.797, P

Five kinds of iron-chromium-aluminum (FeCrAl) alloy samples with different contents of aluminum (Al)—Fe-12Cr, Fe-12Cr-2Al, Fe-12Cr-4Al, Fe-12Cr-6Al, and Fe-12Cr-8Al—were designed and prepared. All samples were then irradiated with 200 keV argon ions (Ar2+) to the fluence of 9.3 × 1014 ions cm−2 at 330°C. The formations of dislocation loops induced by Ar2+ irradiation in these alloys were investigated by transmission electron microscopy. Both of a/2 and a dislocation loops were generated in all samples. The sizes of both a/2 and a dislocation loops decreased and total volume number densities increased with increasing Al content of the samples. The proportion of a/2 dislocation loops decreased first and then increased with Al content, and the ratio of a/2 to a average loop size increased first and then decreased with Al content. The experiment results indicate that the increase of Al content in alloys can enhance the nucleation and inhibit the growth of dislocation loops, the interaction between a/2 and a dislocation loops is affected by the Al content in alloys as well. The difference in dislocation loops in FeCrAl alloys with different Al contents after Ar2+ irradiation can be explained by the pinning of dislocation loops by the Al atoms. Keywords: FeCrAl alloy, Dislocation loops, Radiation damage, Accident tolerant fuel cladding

Background: Survival rates for Colorectal cancer (CRC) patients who experienced early relapse have usually been relatively low. Our study aims at developing an autophagy signature that could help to detect early relapse cases in CRC.Methods: Propensity score matching analysis was carried out between patients from the early relapse group and the long-term survival group from GSE39582. For both groups, respectively, global autophagy expression changes were then analyzed to identify the differentially expressed prognostic autophagy related genes by conducting Linear Models for Microarray data method analysis. Then, the multi-gene signature was validated in TCGA and Fudan University Shanghai Cancer Center (FUSCC) cohorts. Time-dependent ROC were used to test the efficiency of this signature feature in predicting the prognosis of CRC patients.Results: 5 autophagy genes were finally identified to build an early relapse classifier. With specific risk score formula, patients were classified into low- or high-risk group. Time-dependent ROC analyses proved its prognostic accuracy, with AUC 0.841 and 0.803 at 1 and 3 years, respectively. Then, we validated its prognostic value in two external validation series (GSE17538 and GSE33113) and proved that the result is indeed significant irrespective of datasets in two external independent validation cohorts (TCGA and FUSCC cohorts). A nomogram was constructed to guide individualized treatment of patients with CRC.Conclusions: The identification of robust autophagy-related features can effectively classify CRC patients into groups with low and high risk of early relapse. This signature may be used to help select high-risk CRC patients who require more aggressive treatment interventions.

Peritoneum is one of the common sites of metastasis in advanced stage colorectal cancer patients. Colorectal cancer patients with peritoneal metastases (PM) are traditionally believed to have poor prognosis, which indicates it is of no value to adopt surgical treatment. With the advancement of surgical techniques, hyperthermic intraperitoneal chemotherapy (HIPEC), and multidisciplinary treatment in recent years, the cognition and treatment strategies of colorectal peritoneal metastases (CPM) have changed dramatically. In terms of prognosis, CPM under the palliative systemic treatment shows an inferior outcome compared with nonperitoneal metastasis. Nevertheless, some CPM patients amenable to the complete peritoneal cytoreductive surgery (CRS) combined with HIPEC may achieve long-term survival. The prognostic factors of CPM comprise peritoneal carcinomatosis index (PCI), completeness of cytoreduction score (CC score), the presence of extraperitoneal metastasis (liver, etc.), Peritoneal Surface Disease Severity Score (PSDSS), Japanese peritoneal staging, and so forth. Taken together, literature data suggest that a multimodality approach combining complete peritoneal CRS plus HIPEC, systemic chemotherapy, and targeted therapy may be the best treatment option for PM from colorectal cancer.