Abstract At the time of diagnosis, approximately 15%‐20% of patients with rectal cancer (RC) presented synchronous liver metastasis (SLM), which is the most common cause of death in patients with RC. Therefore, preoperative, noninvasive, and accurate prediction of SLM is crucial for personalized treatment strategies. Recently, radiomics has been considered as an advanced image analysis method to evaluate the neoplastic heterogeneity with respect to diagnosis of the tumor and prediction of prognosis. In this study, a total of 1409 radiomics features were extracted for each volume of interest (VOI) from high‐resolution T2WI images of the primary RC. Subsequently, five optimal radiomics features were selected based on the training set using the least absolute shrinkage and selection operator (LASSO) method to construct the radiomics signature. In addition, radiomics signature combined with carcinoembryonic antigen (CEA) and carbohydrate antigen 19‐9 (CA19‐9) was included in the multifactor logistic regression to construct the nomogram model. It showed an optimal predictive performance in the validation set as compared to that in the radiomics model. The favorable calibration of the radiomics nomogram showed a nonsignificant Hosmer‐Lemeshow test statistic ( P > .05). The decision curve analysis (DCA) showed that the radiomics nomogram is clinically superior to the radiomics model. Therefore, the nomogram amalgamating the radiomics signature and clinical risk factors serve as an effective quantitative approach to predict the SLM of primary RC.
Abstract Background This study aimed to evaluate the significance of MRI-based radiomics model derived from high-resolution T2-weighted images (T2WIs) in predicting tumor pathological features of rectal cancer. Methods A total of 152 patients with rectal cancer who underwent surgery without any neoadjuvant therapy between March 2017 and September 2018 were included retrospectively. The patients were scanned using a 3-T magnetic resonance imaging, and high-resolution T2WIs were obtained. Lesions were delineated, and 1029 radiomics features were extracted. Least absolute shrinkage and selection operator was used to select features, and multilayer perceptron (MLP), logistic regression (LR), support vector machine (SVM), decision tree (DT), random forest (RF), and K-nearest neighbor (KNN) were trained using fivefold cross-validation to build a prediction model. The diagnostic performance of the prediction models was assessed using the receiver operating characteristic curves. Results A total of 1029 features were extracted, and 15, 11, and 11 features were selected to predict the degree of differentiation, T stage, and N stage, respectively. The best performance of the radiomics model for the degree of differentiation, T stage, and N stage was obtained by SVM [area under the curve (AUC), 0.862; 95% confidence interval (CI), 0.750–0.967; sensitivity, 83.3%; specificity, 85.0%], MLP (AUC, 0.809; 95% CI, 0.690–0.905; sensitivity, 76.2%; specificity, 74.1%), and RF (AUC, 0.746; 95% CI, 0.622-0.872; sensitivity, 79.3%; specificity, 72.2%). Conclusion This study demonstrated that the high-resolution T2WI–based radiomics model could serve as pretreatment biomarkers in predicting pathological features of rectal cancer.
Abstract Background Hepatocellular carcinoma (HCC), a leading cause of cancer fatalities, challenges clinicians with high recurrence and metastasis rates, urging the need for novel prognostic markers and therapeutic avenues. Minichromosome maintenance complex component 3 (MCM3) has been implicated in various cancers but its role in HCC is not well-characterized. Methods We investigated MCM3 expression in HCC through cell line and patient sample analyses, functional assays to determine its effect on cellular behaviors, and signal pathway exploration. Results Elevated MCM3 expression was identified in both HCC cell lines and patient tissues, correlating with microvascular invasion, advanced cancer stage, and reduced survival. Functionally, MCM3 fueled HCC cellular proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT) in vitro, and expedited tumor growth in vivo. Mechanistically, MCM3 was found to potentiate EMT by upregulating Twist via the AKT signaling pathway. Conclusions MCM3 emerges as an oncogenic influencer in HCC, driving disease progression through the AKT/Twist axis. Its expression patterns hold prognostic value, and targeting MCM3 may offer a novel therapeutic strategy for HCC.
Prognosis of hepatocellular carcinoma (HCC) remains poor due to high recurrence rate and ineffective treatment options, highlighting the need to better understand the mechanism of recurrence and metastasis in HCC.We first collected messenger RNA (mRNA) expression data from 442 cases of HCC patients from The Cancer Genome Atlas (TCGA) database as well as 251 HCC patients from Zhongshan Hospital during 2009 and 2010 to analyze the expression pattern from tissue microarray (TMA) of baculoviral IAP repeat containing 3 (BIRC3). Then, we used BIRC3 gain-of-function (overexpression) and loss-of-function (knockdown) studies to examine the effect of BIRC3 on HCC cell proliferation and invasion. In addition, we also investigated the undying mechanism by which BIRC3 contributes to HCC tumor progression. Functionally, we also used a BIRC3-specific inhibitor AT-406 in HCC xenograft model to explore the potential therapeutic benefit of targeting BIRC3 in liver cancer.BIRC3 serves as a novel prognostic indicator for HCC patients undergoing curative resection. BIRC3 promotes HCC epithelial-mesenchymal transition (EMT), cell migration, and metastasis via upregulating MAP3K7, therefore, inducing ERK1/2 phosphorylation. The specific BIRC3 inhibitor AT-406 can inhibit HCC cell proliferation and reduce pulmonary metastases.BIRC3 induces tumor proliferation and metastasis in vitro and in vivo. BIRC3 may serve as a novel therapeutic target for liver cancer.
Abstract Background To construct and compare merged models integrating clinical factors, MRI-based radiomics features and deep learning (DL) models for predicting pathological complete response (pCR) to neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC). Methods Totally 197 patients with LARC administered surgical resection after nCRT were assigned to cohort 1 (training and test sets); meanwhile, 52 cases were assigned to cohort 2 as a validation set. Radscore and DL models were established for predicting pCR applying pre- and post-nCRT MRI data, respectively. Different merged models integrating clinical factors, Radscore and DL model were constituted. Their predictive performances were validated and compared by receiver operating characteristic (ROC) and decision curve analyses (DCA). Results Merged models were established integrating selected clinical factors, Radscore and DL model for pCR prediction. The areas under the ROC curves (AUCs) of the pre-nCRT merged model were 0.834 (95% CI: 0.737–0.931) and 0.742 (95% CI: 0.650–0.834) in test and validation sets, respectively. The AUCs of the post-nCRT merged model were 0.746 (95% CI: 0.636–0.856) and 0.737 (95% CI: 0.646–0.828) in test and validation sets, respectively. DCA showed that the pretreatment algorithm could yield enhanced clinically benefit than the post-nCRT approach. Conclusions The pre-nCRT merged model including clinical factors, Radscore and DL model constitutes an effective non-invasive tool for pCR prediction in LARC.
Hepatocellular carcinoma (HCC) is one of the most prevalent malignancies worldwide because of rapid progression and high incidence of metastasis or recurrence. Accumulating evidence shows that CD73-expressing tumor cell is implicated in development of several types of cancer. However, the role of CD73 in HCC cell has not been systematically investigated and its underlying mechanism remains elusive. CD73 expression in HCC cell was determined by RT-PCR, Western blot, and immunohistochemistry staining. Clinical significance of CD73 was evaluated by Cox regression analysis. Cell counting kit-8 and colony formation assays were used for proliferation evaluation. Transwell assays were used for motility evaluations. Co-immunoprecipitation, cytosolic and plasma membrane fractionation separation, and ELISA were applied for evaluating membrane localization of P110β and its catalytic activity. NOD/SCID/γc(null) (NOG) mice model was used to investigate the in vivo functions of CD73. In the present study, we demonstrate that CD73 was crucial for epithelial-mesenchymal transition (EMT), progression and metastasis in HCC. CD73 expression is increased in HCC cells and correlated with aggressive clinicopathological characteristics. Clinically, CD73 is identified as an independent poor prognostic indicator for both time to recurrence and overall survival. CD73 knockdown dramatically inhibits HCC cells proliferation, migration, invasion, and EMT in vitro and hinders tumor growth and metastasis in vivo. Opposite results could be observed when CD73 is overexpressed. Mechanistically, adenosine produced by CD73 binds to adenosine A2A receptor (A2AR) and activates Rap1, which recruits P110β to the plasma membrane and triggers PIP3 production, thereby promoting AKT phosphorylation in HCC cells. Notably, a combination of anti-CD73 and anti-A2AR achieves synergistic depression effects on HCC growth and metastasis than single agent alone. CD73 promotes progression and metastasis through activating PI3K/AKT signaling, indicating a novel prognostic biomarker for HCC. Our data demonstrate the importance of CD73 in HCC in addition to its immunosuppressive functions and revealed that co-targeting CD73 and A2AR strategy may be a promising novel therapeutic strategy for future HCC management.
Aim: To explore the application value of serum autoantibodies in the early diagnosis of esophageal cancer. Materials & methods: A total of 130 patients with esophageal cancer and 110 controls were included and tested by ELISA. Results: According to the receiver operating characteristic curve, total sensitivity is 83.08%, total specificity is 72.73%. A nomogram was established based on the positive judgment standard, the area under the receiver operating characteristic curve was calculated to be 0.880 after verification with the calibration curve. A 2-week follow-up analysis found compared with the preoperative control, the postoperative model integral value will significantly decrease. Conclusion: The combination of serum autoantibody groups has certain clinical application value in the early diagnosis of esophageal cancer and can be used as an auxiliary index for early diagnosis.
// Xiao-Lu Ma 1, * , Xing-Hui Gao 1, * , Zi-Jun Gong 2, * , Jiong Wu 1 , Lu Tian 1 , Chun-Yan Zhang 1 ,Yan Zhou 1 , Yun-Fan Sun 2 , Bo Hu 2 , Shuang-jian Qiu 2 , Jian Zhou 2 , Jia Fan 2 , Wei Guo 1 , Xin-Rong Yang 2 1 Department of Laboratory Medicine, Zhongshan Hospital, Fudan University, Shanghai, P. R. China 2 Department of Liver Surgery, Liver Cancer Institute, Zhongshan hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai, P. R. China * These authors have contributed equally to this work Correspondence to: Xin-Rong Yang, email: yang.xinrong@zs-hospital.sh.cn Wei Guo, email: guo.wei@zs-hospital.sh.cn Keywords: Apolipoprotein A1, hepatocellular carcinoma, serum biomarker, prognosis, circulating tumor cell Received: December 13, 2015 Accepted: September 12, 2016 Published: September 23, 2016 ABSTRACT As a major protein constituent of high density lipoprotein, Apolipoprotein A1 (ApoA-1) might be associated with cancer progression. Our study investigated the serum ApoA-1 level for the prognosis of 443 patients with hepatocellular carcinoma (HCC) and its effects on tumor cells. We found that the serum ApoA-1 level was significantly lower in HCC patients with tumor recurrence, and was an independent indicator of tumor-free survival and overall survival. Low serum ApoA-1 levels were significantly associated with multiple tumors and high Barcelona Clinic Liver Cancer stage. The circulating tumor cell (CTC) levels were significantly higher in patients with low serum ApoA-1 compared with those with high serum ApoA-1 levels (4.03 ± 0.98 vs. 1.48 ± 0.22; p =0.001). In patients with detectable CTCs, those with low ApoA-1 levels had higher recurrence rates and shorter survival times. In vitro experiments showed that ApoA-1 can inhibit tumor cell proliferation through cell cycle arrest and promote apoptosis through down regulating mitogen-activated protein kinase (MAPK) pathway. In addition, ApoA-1 might impair extracellular matrix degradation properties of tumor cells. Taken together, our findings indicate that decreased serum ApoA-1 levels are a novel prognostic factor for HCC, and the role of ApoA-1 in inhibition of proliferation and promotion of apoptosis for tumor cells during their hematogenous dissemination are presumably responsible for the poor prognosis of patients with low ApoA-1 levels. Furthermore, AopA-1 might be a promising therapeutic target to reduce recurrence and metastasis for HCC patients after resection.
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