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PurposeThe aim of this study is to investigate the survival benefit of adjuvant chemotherapy in patients with colon cancer with the solitary tumor deposit (TD).MethodsThe primary study outcomes used in this study were colon cancer–specific survival (CSS) and overall survival (OS). The differences of the distribution of categorical variables in patients with colon cancer with the solitary TD according to adjuvant chemotherapy administration were tested using the Pearson’s chi-square test. The Kaplan–Meier method was utilized to evaluate CSS and OS. Hazard ratio (HR) and 95% confidence interval (CI) were calculated on the basis of Cox regression models to assess the prognostic value of different demographic and clinicopathological characteristics.ResultsA total of 877 patients with TanyN1cM0 colon cancer with solitary TD were identified in our analysis. It was found that OS (75.4% vs. 42.8% for 5-year OS rate, p < 0.001) and CSS (82.9% vs. 69.3% for 5-year CSS rate, p < 0.001) of patients with colon cancer with adjuvant chemotherapy administration were significantly better than those without adjuvant chemotherapy administration. Multivariate Cox survival analyses revealed that the overall and colon cancer–specific mortality risks of patients with adjuvant chemotherapy administration were decreased by 64.4% (HR = 0.356, 95% CI = 0.265–0.479, p < 0.001) and 57.4% (HR = 0.426, 95% CI = 0.286–0.634, p < 0.001) compared with those without adjuvant chemotherapy administration, respectively.ConclusionsAdjuvant chemotherapy administration could significantly improve OS and CSS in patients with colon cancer with the solitary TD. This is the first study to investigate and demonstrate the survival benefit of adjuvant chemotherapy in patients with colon cancer with the solitary TD.

This study aimed to comprehensively examine the efficacy of chemotherapy in T1 colon cancer patients with lymph node metastasis.MethodsThe differences in categorical variables in colon cancer patients according to lymph node status were evaluated by Pearson’s chi-square test. The Kaplan-Meier method was used to assess Cancer-specific survival (CSS) and overall survival (OS) with the log-rank test. Cox proportional hazards models were built, multivariate Cox regression analyses were performed with the hazard ratio (HR) and 95% confidence interval (CI) to identify the potential independent prognostic factors. Propensity score matching was also undertaken to adjust for treatment bias due to measured confounders.ResultsYounger age (52.2% VS. 43.0% for ≤ 65 years old, p < 0.001), female gender (50.3% VS. 46.8% for female, p < 0.001), more lymph nodes harvested (68.1% VS. 46.6% for ≥12 lymph nodes harvested, p < 0.001), Black race (13.6% VS. 12.0% for the Black race, p < 0.001), and higher tumor grade (14.2% VS. 5.6% for grade III/IV, p < 0.001) were more prone to be diagnosed with lymph node involvement. The receipt of adjuvant chemotherapy following radical surgery significantly reduced the risk of colon cancer-specific mortality by 33.9% after propensity-score matching (HR = 0.661, 95%CI = 0.476-0.917, p = 0.013).ConclusionsYounger age, female gender, more lymph nodes harvested, Black race, and higher tumor grade were more prone to be diagnosed with lymph node involvement. The receipt of adjuvant chemotherapy following radical surgery also significantly decreased the risk of colon cancer-specific mortality by 33.9% in T1 colon cancer with lymph node involvement.

BackgroundPancreatic ductal adenocarcinoma (PDAC) is one of the most invasive solid malignancies. Immunotherapy and targeted therapy confirmed an existing certain curative effect in treating PDAC. The aim of this study was to develop an immune-related molecular marker to enhance the ability to predict Stages III and IV PDAC patients.MethodIn this study, weighted gene co-expression network (WGCNA) analysis and a deconvolution algorithm (CIBERSORT) that evaluated the cellular constituent of immune cells were used to evaluate PDAC expression data from the GEO (Gene Expression Omnibus) datasets, and identify modules related to CD4+ T cells. LASSO Cox regression analysis and Kaplan–Meier curve were applied to select and build prognostic multi-gene signature in TCGA Stages III and IV PDAC patients (N = 126). This was followed by independent Stages III and IV validation of the gene signature in the International Cancer Genome Consortium (ICGC, N = 62) and the Fudan University Shanghai Cancer Center (FUSCC, N = 42) cohort. Inherited germline mutations and tumor immunity exploration were applied to elucidate the molecular mechanisms in PDAC. Univariate and Multivariate Cox regression analyses were applied to verify the independent prognostic factors. Finally, a prognostic nomogram was created according to the TCGA-PDAC dataset.ResultsA four-gene signature comprising NAPSB, ZNF831, CXCL9 and PYHIN1 was established to predict overall survival of PDAC. This signature also robustly predicted survival in two independent validation cohorts. The four-gene signature could divide patients into high and low-risk groups with disparity overall survival verified by a Log-rank test. Expression of four genes positively correlated with immunosuppression activity (PD-L1 and PD1). Immune-related genes nomogram and corresponding calibration curves showed significant performance for predicting 3-year survival in TCGA-PDAC dataset.ConclusionWe constructed a novel four-gene signature to predict the prognosis of Stages III and IV PDAC patients by applying WGCNA and CIBERSORT algorithm scoring to transcriptome data different from traditional methods of filtrating for differential genes in cancer and healthy tissues. The findings may provide reference to predict survival and was beneficial to individualized management for advanced PDAC patients.

objectiveDespite the heterogeneous biology of pancreatic cancer, similar surveillance schemas have been used. Identifying the high recurrence risk population and conducting prompt intervention may improve prognosis and prolong overall survival.MethodsOne hundred fifty-six resectable pancreatic cancer patients who had undergone 18F-FDG PET/CT from January 2013 to December 2018 were retrospectively reviewed. The patients were categorized into a training cohort (n = 109) and a validation cohort (n = 47). LIFEx software was used to extract radiomic features from PET/CT. The risk stratification system was based on predictive factors for recurrence, and the index of prediction accuracy was used to reflect both the discrimination and calibration.ResultsOverall, seven risk factors comprising the rad-score and clinical variables that were significantly correlated with relapse were incorporated into the final risk stratification system. The 1-year recurrence-free survival differed significantly among the low-, intermediate-, and high-risk groups (85.5, 24.0, and 9.1%, respectively; p < 0.0001). The C-index of the risk stratification system in the development cohort was 0.890 (95% CI, 0.835–0.945).ConclusionThe 18F-FDG PET/CT-based radiomic features and clinicopathological factors demonstrated good performance in predicting recurrence after pancreatectomy in pancreatic cancer patients, providing a strong recommendation for an adequate adjuvant therapy course in all patients. The high-risk recurrence population should proceed with closer follow-up in a clinical setting.

BackgroundCancer stem cells (CSCs) are widely thought to contribute to the dismal prognosis of pancreatic ductal adenocarcinoma (PDAC). CSCs share biological features with adult stem cells, such as longevity, self-renewal capacity, differentiation, drug resistance, and the requirement for a niche; these features play a decisive role in cancer progression. A prominent characteristic of PDAC is metabolic reprogramming, which provides sufficient nutrients to support rapid tumor cell growth. However, whether PDAC stemness is correlated with metabolic reprogramming remains unknown.MethodRNA sequencing data of PDAC, including read counts and fragments per kilobase of transcript per million mapped reads (FPKM), were collected from The Cancer Genome Atlas-Pancreatic Adenocarcinoma (TCGA-PAAD) database. Single-sample gene set enrichment analysis (GSEA) was used to calculate the relative activities of metabolic pathways in each PDAC sample. Quantitative real-time PCR was performed to validate the expression levels of genes of interest.ResultsThe overall survival (OS) of patients with high mRNA expression-based stemness index (mRNAsi) values was significantly worse than that of their counterparts with low mRNAsi values (P = 0.003). This survival disadvantage was independent of baseline clinical characteristics. Gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and GSEA showed that the differentially expressed genes between patients with high and low mRNAsi values were mainly enriched in oncogenic and metabolic pathways. Weighted gene coexpression network analysis (WGCNA) revealed 8 independent gene modules that were significantly associated with mRNAsi and 12 metabolic pathways. Unsupervised clustering based on the key genes in each module identified two PDAC subgroups characterized by different mRNAsi values and metabolic activities. Univariate Cox regression analysis identified 14 genes beneficial to OS from 95 key genes selected from the eight independent gene modules from WGCNA. Among them, MAGEH1, MAP3K3, and PODN were downregulated in both pancreatic tissues and cell lines.ConclusionThe present study showed that PDAC samples with high mRNAsi values exhibited aberrant activation of multiple metabolic pathways, and the patients from whom these samples were obtained had a poor prognosis. Future studies are expected to investigate the underlying mechanism based on the crosstalk between PDAC stemness and metabolic rewiring.

PurposeHypodensity of pancreatic ductal adenocarcinoma (PDAC) during contrast-enhanced computed tomography (CECT) examination is common, but a minority of PDAC patients exhibit hyperdense images. The present study examined the clinical characteristics and protein landscape of PDAC with hyperdensity.Materials and MethodsA total of 844 pathologically confirmed PDAC patients who underwent CECT before surgery were included. During the parenchymal phase of CECT, patients were assigned to the hyperdense or hypodense group based on CT values. Clinical and CT characteristics for predicting relapse-free survival (RFS) and overall survival (OS) were analyzed using the Kaplan–Meier method and Cox proportional hazards model. The expression of the tumor angiogenesis marker CD31 and stroma-related protein CTHRC1 were analyzed using immunohistochemistry (IHC) assay to evaluate differences between the two groups. Proteomics was performed to compare the possible mechanisms underlying the differential enhancement on CT scans.ResultsBased on CECT, 43 and 801 PDAC patients had hyperdense and hypodense lesions, respectively. All 43 patients presented a hyperdense lesion in the parenchymal phase. The mean CECT values of the hyperdense group were higher than the hypodense group (102.5 ± 17.4 and 53.7 ± 18.7, respectively, P< 0.001). The hyperdense group had a better prognosis than the hypodense group (median RFS, 19.97 vs. 12.34 months, P = 0.0176; median OS, 33.6 vs. 20.3 months, P = 0.047). Multivariate analysis showed that age, higher CA19-9 levels (> 300 U/ml), tumor stage, tumor differentiation, tumor CT density, and adjuvant chemotherapy were significant independent prognostic factors for OS. CD31 immunohistochemical staining showed that the hyperdense PDACs had a higher microvessel density than the hypodense group (P< 0.001). CTHRC1 expression was higher in the hypodense group (P = 0.019). Sixty-eight differentially expressed proteins were found using the tandem mass tag labeling-based quantification of the proteomes of PDAC tissue samples, and 7 proteins (POFUT1, PKP2, P0DOX4, ITPR1, HBG2, IGLC3, SAA2) were related to angiogenesis.ConclusionPatients who presented with a hyperdense mass on CECT had a higher microvessel density and better prognosis. Anti-angiogenic therapy may be suitable for these patients.