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Background: Immune checkpoint inhibitors (ICIs) have improved survival outcomes and resulted in long-term responses in primary liver cancer in some patients. Nevertheless, not all patients with PLC could benefit from immunotherapy. Therefore, it is necessary to identify patients suitable for such therapy., Methods: 215 patients with primary liver cancer with immunotherapy from Nanfang Hospital were screened between August 2018 and October 2020 as a training set and our validation set included 71 patients of hepatocellular carcinoma from Jiangxi Cancer Hospital from May 2019 to July 2021. The primary endpoint was the disease control rate (DCR), and the secondary endpoints were overall survival (OS) and progression-free survival., Results: In the training set, neutrophil-lymphocyte ratio (NLR) ≥3 and alpha-fetoprotein (AFP) level ≥20 ng/mL were independently associated with non-DCR in the training set after adjusting for distant metastasis at baseline and targeted therapy combination. Furthermore, a hepatic immune predictive index (HIPI) based on NLR and AFP level was developed and patients with poor HIPI associated with worse clinical outcomes. In validation set, high HIPI was associated with poor OS., Conclusion: HIPI, based on NLR and AFP level, is an effective indicator in ICI-treated patients with primary liver cancer. Our findings may help guide the selection and on-treatment strategies for immunotherapies for primary liver cancer patients., (© 2022 S. Karger AG, Basel.)

Background & Aims: Immune checkpoint inhibitors (ICIs) play an increasingly important role in the treatment of primary liver cancer (PLC). Some patients with PLC experience symptoms of splenomegaly. Splenomegaly may affect the efficacy of ICIs due to an imbalance of the immune microenvironment. Currently, there is a lack of evidence on the relationship between splenomegaly and prognosis in patients with PLC treated with ICIs. This study analyzed the relationship between splenomegaly and prognosis in patients with PLC treated with ICIs., Methods: In this retrospective cohort study of 161 patients with PLC treated with ICIs, splenomegaly was diagnosed using computed tomography or magnetic resonance imaging and the impact of splenomegaly on patient survival was analyzed., Results: Through univariate and multivariate Cox regression analyses, we determined that splenomegaly was associated with shortened overall survival (p = 0.002) and progression-free survival (p = 0.013) in patients with PLC treated with ICIs. Kaplan-Meier analysis further validated our results. The overall survival and progression-free survival of patients with splenomegaly were significantly shorter than those of patients without splenomegaly (p < 0.01 and p = 0.02, respectively)., Conclusions: We concluded that splenomegaly was a predictor of prognosis in patients with PLC treated with ICIs. This is the first study to report this important finding., (© 2022 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.)

PURPOSE The high rate of recurrence of hepatocellular carcinoma (HCC) after radical hepatectomy is an important factor that affects the long-term survival of patients. This study aimed to develop a computed tomography (CT) images-based 3-dimensional (3D) convolutional neural network (CNN) for the preoperative prediction of early recurrence (ER) (≤2 years) after radical hepatectomy in patients with solitary HCC and to compare the effects of segmentation sampling (SS) and non-segmentation sampling (NSS) on the prediction performance of 3D-CNN. METHODS Contrast-enhanced CT images of 220 HCC patients were used in this study (training group=178 and test group=42). We used SS and NSS to select the volume-of-interest to train SS-3D-CNN and NSS-3D-CNN separately. The prediction accuracy was evaluated using the test group. Finally, gradient-weighted class activation mappings (Grad-CAMs) were plotted to analyze the difference of prediction logic between the SS-3D-CNN and NSS-3D-CNN. RESULTS The areas under the receiver operating characteristic curves (AUCs) of the SS-3D-CNN and NSS3D-CNN in the training group were 0.824 (95% CI: 0.764-0.885) and 0.868 (95% CI: 0.815-0.921). The AUC of the SS-3D-CNN and NSS-3D-CNN in the test group were 0.789 (95% CI: 0.637-0.941) and 0.560 (95% CI: 0.378-0.742). The SS-3D-CNN could stratify patients into low- and high-risk groups, with significant differences in recurrence-free survival (RFS) (P < .001). But NSS-3D-CNN could not effectively stratify them in the test group. According to the Grad-CAMs, compared with SS-3D-CNN, NSS-3D-CNN was obviously interfered by the nearby tissues. CONCLUSION SS-3D-CNN may be of clinical use for identifying high-risk patients and formulating individualized treatment and follow-up strategies. SS is better than NSS in improving the performance of 3D-CNN in our study.

Objective: To explore the efficacy and safety of gemcitabine (GEM) combined with cisplatin (DDP) in the treatment of recurrent/metastatic nasopharyngeal carcinoma (NPC)., Methods: A total of 100 patients with recurrent/metastatic NPC treated in the First Affiliated Hospital, Hengyang Medical School, University of South China from January 2018 to March 2020 were retrospectively enrolled. Based on different chemotherapy schemes, they were assigned to an observation (Obs) group (DDP + GEM, n = 55) and a control (Con) group [DDP + FU (fluorouracil), n = 45]. The two groups were compared regarding the following items: therapeutic efficacy; serum levels of platelet-derived growth factor-BB (PDGF-BB), soluble epithelial cadherin (SE-CAD), and inflammation-related factors before and after treatment; toxic and side effects; 1-year survival rate; and quality of life (QOL) 6 months after treatment., Results: The Obs group outperformed the Con group in therapeutic efficacy (P < 0.05). There were no significant differences in the levels of PDGF-BB, SE-CAD, interleukin (IL)-6, IL-10 and tumor necrosis factor (TNF)-α between the two groups before treatment (P > 0.05). After treatment, better improvements in PDGF-BB, SE-CAD and inflammatory factors were observed in the Obs group (P < 0.05). The toxic and side effects were significantly lower and the 1-year survival rate and patients' QOL after 6 months of treatment were significantly higher in the Obs group compared with the Con group (P < 0.05)., Conclusion: GEM combined with DDP can provide more clinical benefits for patients with recurrent/metastatic advanced NPC, with less side effects, high tolerance and significant efficacy, which can be further promoted in clinical use., Competing Interests: The authors declare no competing interests in this work., (© 2022 Yang et al.)

Background: At present, some cancer patients experience hyperprogressive disease (HPD) after receiving immunotherapy. This study used the Response Evaluation Criteria in Solid Tumors 1.1 to evaluate the incidence of HPD in patients receiving immune checkpoint inhibitors (ICIs) for treating primary liver cancer (PLC) and to explore the risk factors for HPD., Methods: This retrospective, single-center study included patients with PLC who were treated with ICIs. The RECIST 1.1 was used to determine patients with HPD. Univariate and multivariate regression analyses were performed to explore the risk factors for HPD, and clinical variables with prognostic significance for HPD were included to establish a risk model., Results: Among 129 patients with PLC treated with ICIs, HPD occurred in 13 patients (10.1%). In the multivariate regression analysis, lymph node metastasis and lung metastasis were risk factors for HPD. The area under the curve of the risk model, established by including lymph node metastasis, lung metastasis, neutrophil-lymphocyte ratio, albumin, and performance status, was 0.801 (P<0.001). The progression-free survival of HPD patients was significantly worse than that of non-HPD patients (P<0.001)., Conclusions: In this study, 10.1% of patients with PLC had HPD. Compared with the non-HPD patients, lung metastasis and lymph node metastasis were independent risk factors of HPD.

Purpose: Despite the success of targeted therapy in c-ros oncogene 1 ( ROS1 )-rearranged cancers, especially non-small cell lung cancer (NSCLC), the clinical significance of ROS1 de novo mutation has not yet been understood. We sought to elucidate the predictive effect of ROS1 mutation for immune checkpoint inhibitor (ICI) therapy in melanoma., Methods: The Cancer Genome Atlas [TCGA ( n = 10967)] and Memorial Sloan Kettering Cancer Center [MSK ( n = 10,945)] datasets, as well as two clinical cohorts of melanoma received ICI [CA209-038 ( n = 73) and MEL-IPI ( n = 110)], were included to explore the prevalence, prognostic effect, and immunotherapeutic predictive effect of ROS1 mutation in melanoma. Overall survival (OS) was defined as the primary outcome., Results: Overall, melanoma accounted for the highest proportion of ROS1 mutation (~20%) which made up the majority (~95%) of the ROS1 -alterated cases. Remarkably, ROS1 mutation yielded longer OS from ICI than the wild-type counterpart in the MSK melanoma population [hazard ratio (HR) 0.47, 95% confidence interval (CI) 0.30-0.74], and two external melanoma cohorts (CA209-038: HR 0.42, 95% CI 0.20-0.89; MEL-IPI: HR 0.55, 95% CI 0.34-0.91), without affecting the prognosis of patients. Elevated tumor mutational burden and enrichment of DNA damage repair was observed in ROS1 mutated patients, providing an explanation for the favorable responses to ICI therapy. Precisely, ROS1 mutation in non-protein tyrosine kinase (PTK) domain but not PTK mutation was responsible for the immunotherapy-specific responses of the ROS1 mutated patients in melanoma., Conclusions: Collectively, ROS1 mutation, specifically the non-PTK mutation, is a potential predictor of ICI therapy in melanoma, which is distinct from the well-established role of ROS1 rearrangement for targeted therapy in NSCLC., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Ma, Zhu, Wang, Zhang, Guo, Long, Guo, Wu, Dong and Bai.)

Objective: To clarify the correlation between temperature and the COVID-19 pandemic in Hubei. Methods: We collected daily newly confirmed COVID-19 cases and daily temperature for six cities in Hubei Province, assessed their correlations, and established regression models. Results: For temperatures ranging from -3.9 to 16.5°C, daily newly confirmed cases were positively correlated with the maximum temperature ~0-4 days prior or the minimum temperature ~11-14 days prior to the diagnosis in almost all selected cities. An increase in the maximum temperature 4 days prior by 1°C was associated with an increase in the daily newly confirmed cases (~129) in Wuhan. The influence of temperature on the daily newly confirmed cases in Wuhan was much more significant than in other cities. Conclusion: Government departments in areas where temperatures range between -3.9 and 16.5°C and rise gradually must take more active measures to address the COVID-19 pandemic., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Hu, Xiao, Zhu, Zhu and Liu.)

Microsatellite instability (MSI) has been approved as a pan-cancer biomarker for immune checkpoint blockade (ICB) therapy. However, current MSI identification methods are not available for all patients. We proposed an ensemble multiple instance deep learning model to predict microsatellite status based on histopathology images, and interpreted the pathomics-based model with multi-omics correlation. Methods: Two cohorts of patients were collected, including 429 from The Cancer Genome Atlas (TCGA-COAD) and 785 from an Asian colorectal cancer (CRC) cohort (Asian-CRC). We established the pathomics model, named Ensembled Patch Likelihood Aggregation (EPLA), based on two consecutive stages: patch-level prediction and WSI-level prediction. The initial model was developed and validated in TCGA-COAD, and then generalized in Asian-CRC through transfer learning. The pathological signatures extracted from the model were analyzed with genomic and transcriptomic profiles for model interpretation. Results: The EPLA model achieved an area-under-the-curve (AUC) of 0.8848 (95% CI: 0.8185-0.9512) in the TCGA-COAD test set and an AUC of 0.8504 (95% CI: 0.7591-0.9323) in the external validation set Asian-CRC after transfer learning. Notably, EPLA captured the relationship between pathological phenotype of poor differentiation and MSI ( P < 0.001). Furthermore, the five pathological imaging signatures identified from the EPLA model were associated with mutation burden and DNA damage repair related genotype in the genomic profiles, and antitumor immunity activated pathway in the transcriptomic profiles. Conclusions: Our pathomics-based deep learning model can effectively predict MSI from histopathology images and is transferable to a new patient cohort. The interpretability of our model by association with pathological, genomic and transcriptomic phenotypes lays the foundation for prospective clinical trials of the application of this artificial intelligence (AI) platform in ICB therapy., Competing Interests: Competing Interests: F.Y., Y.Z., W.J.L., T.X.W., W.J.H., W.M.T and J.H.Y. are employed by Tencent and W.J.C. is employed by Shanghai Tongshu Biotechnology Co., Ltd., (© The author(s).)

Purpose: The aim of this study was to develop and validate a radiomics nomogram based on radiomics features and clinical data for the non-invasive preoperative prediction of early recurrence (≤2 years) in patients with hepatocellular carcinoma (HCC)., Methods: We enrolled 262 HCC patients who underwent preoperative contrast-enhanced computed tomography and curative resection (training cohort, n=214; validation cohort, n=48). We applied propensity score matching (PSM) to eliminate redundancy between clinical characteristics and image features, and the least absolute shrinkage and selection operator (LASSO) was used to prevent overfitting. Next, a radiomics signature, clinical nomogram, and combined clinical-radiomics nomogram were built to predict early recurrence, and we compared the performance and generalization of these models., Results: The radiomics signature stratified patients into low-risk and high-risk, which show significantly difference in recurrence free survival and overall survival (P ≤ 0.01). Multivariable analysis identified dichotomised radiomics signature, alpha fetoprotein, and tumour number and size as key early recurrence indicators, which were incorporated into clinical and radiomics nomograms. The radiomics nomogram showed the highest area under the receiver operating characteristic curve (AUC), with significantly superior predictive performance over the clinical nomogram in the training cohort (0.800 vs 0.716, respectively; P = 0.001) and the validation cohort (0.785 vs 0.654, respectively; P = 0.039)., Conclusion: The radiomics nomogram is a non-invasive preoperative biomarker for predicting early recurrence in patients with HCC. This model may be of clinical utility for guiding surveillance follow-ups and identifying optimal interventional strategies.

Circular RNAs (circRNAs) play an important role in cancer development and progression by regulating gene expression. The present study aimed to investigate the function of circRNA&#95;100859 in colon cancer. circRNA expression profiles from a human circRNAs chip were analyzed. The effects of circRNA&#95;100859 on cell proliferation and apoptosis were assessed in vitro and interactions between circRNA&#95;100859 and its micro (mi)RNA and target genes were analyzed. The diagnostic and prognostic significance of circRNA&#95;100859 was also investigated. It was identified that circRNA&#95;100859 was overexpressed in colon cancer tissues and promoted cell proliferation and inhibited cell apoptosis. Additionally, bioinformatics and a dual-luciferase reporter assay confirmed that circRNA&#95;100859 acted as a miR-217 sponge, and miR-217 directly targeted hypoxia-inducible factor (HIF)-1α. Rescue assays demonstrated that HIF-1α protein and mRNA expression levels and cell proliferation were regulated by the circRNA&#95;100859/miR-217 axis ( P <0.05). Furthermore, statistical analysis showed that the circRNA&#95;100859-miR-217-HIF-1α axis was associated with Tumor-Node-Metastasis (TNM) stage, histological grade, and KRAS mutations, and also showed high diagnostic and prognostic value for patients with colon cancer ( P <0.05). Therefore, it was concluded that circRNA&#95;100859 functions as an oncogene in colon cancer by sponging the miR-217-HIF-1α pathway. In addition, the circRNA&#95;100859-miR-217-HIF-1α axis may serve as a novel diagnostic and prognostic biomarker for patients with colon cancer.

Background: Information regarding risk factors associated with severe coronavirus disease (COVID-19) is limited. This study aimed to develop a model for predicting COVID-19 severity., Methods: Overall, 690 patients with confirmed COVID-19 were recruited between 1 January and 18 March 2020 from hospitals in Honghu and Nanchang; finally, 442 patients were assessed. Data were categorised into the training and test sets to develop and validate the model, respectively., Findings: A predictive HNC-LL (Hypertension, Neutrophil count, C-reactive protein, Lymphocyte count, Lactate dehydrogenase) score was established using multivariate logistic regression analysis. The HNC-LL score accurately predicted disease severity in the Honghu training cohort (area under the curve [AUC]=0.861, 95% confidence interval [CI]: 0.800-0.922; P<0.001); Honghu internal validation cohort (AUC=0.871, 95% CI: 0.769-0.972; P<0.001); and Nanchang external validation cohort (AUC=0.826, 95% CI: 0.746-0.907; P<0.001) and outperformed other models, including CURB-65 (confusion, uraemia, respiratory rate, BP, age ≥65 years) score model, MuLBSTA (multilobular infiltration, hypo-lymphocytosis, bacterial coinfection, smoking history, hypertension, and age) score model, and neutrophil-to-lymphocyte ratio model. The clinical significance of HNC-LL in accurately predicting the risk of future development of severe COVID-19 was confirmed., Interpretation: We developed an accurate tool for predicting disease severity among COVID-19 patients. This model can potentially be used to identify patients at risks of developing severe disease in the early stage and therefore guide treatment decisions., Funding: This work was supported by the National Nature Science Foundation of China (grant no. 81972897) and Guangdong Province Universities and Colleges Pearl River Scholar Funded Scheme (2015)., Competing Interests: Declaration of Competing Interest The authors declare that they do not have any conflicts of interest., (Copyright © 2020 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background: Genetic variations of some driver genes in non-small cell lung cancer (NSCLC) had shown potential impact on immune microenvironment and associated with response or resistance to programmed cell death protein 1 (PD-1) blockade immunotherapy. We therefore undertook an exploratory analysis to develop a genomic mutation signature (GMS) and predict the response to anti-PD-(L)1 therapy., Methods: In this multicohort analysis, 316 patients with non-squamous NSCLC treated with anti-PD-(L)1 from three independent cohorts were included in our study. Tumor samples from the patients were molecularly profiled by MSK-IMPACT or whole exome sequencing. We developed a risk model named GMS based on the MSK training cohort (n=123). The predictive model was first validated in the separate internal MSK cohort (n=82) and then validated in an external cohort containing 111 patients from previously published clinical trials., Results: A GMS risk model consisting of eight genes ( TP53 , KRAS , STK11 , EGFR , PTPRD , KMT2C , SMAD4 , and HGF ) was generated to classify patients into high and low GMS groups in the training cohort. Patients with high GMS in the training cohort had longer progression-free survival (hazard ratio (HR) 0.41, 0.28-0.61, p < 0.0001) and overall survival (HR 0.53, 0.32-0.89, p = 0.0275) compared with low GMS. We noted equivalent findings in the internal validation cohort and in the external validation cohort. The GMS was demonstrated as an independent predictive factor for anti-PD-(L)1 therapy comparing with tumor mutational burden. Meanwhile, GMS showed undifferentiated predictive value in patients with different clinicopathological features. Notably, both GMS and PD-L1 were independent predictors and demonstrated poorly correlated; inclusion of PD-L1 with GMS further improved the predictive capacity for PD-1 blockade immunotherapy., Conclusions: Our study highlights the potential predictive value of GMS for immunotherapeutic benefit in non-squamous NSCLC. Besides, the combination of GMS and PD-L1 may serve as an optimal partner in guiding treatment decisions for anti-PD-(L)1 based therapy., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Purpose: Although tumor mutation burden (TMB) has been well known to predict the response to immune checkpoint inhibitors (ICI), lack of randomized clinical trial data has restricted its clinical application. This study aimed to explore the significance and feasibility of biomarker combination based on TMB and copy-number alteration (CNA) for the prognosis of each tumor and prediction for ICI therapy in metastatic pan-cancer milieu., Experimental Design: Non-ICI-treated MSK pan-cancer cohort was used for prognosis analysis. Three independent immunotherapy cohorts, including non-small cell lung cancer ( n = 240), skin cutaneous melanoma ( n = 174), and mixed cancer (Dana-Farber, n = 98) patients from previous studies, were analyzed for efficacy of ICI therapy., Results: TMB and CNA showed optimized combination for the prognosis of most metastatic cancer types, and patients with TMB low CNA low showed better survival. In the predictive analysis, both TMB and CNA were independent predictive factors for ICI therapy. Remarkably, when TMB and CNA were jointly analyzed, those with TMB high CNA low showed favorable responses to ICI therapy. Meanwhile, TMB high CNA low as a new biomarker showed better prediction for ICI efficacy compared with either TMB-high or CNA-low alone. Furthermore, analysis of the non-ICI-treated MSK pan-cancer cohort supported that the joint stratification of TMB and CNA can be used to categorize tumors into distinct sensitivity to ICI therapy across pan-tumors., Conclusions: The combination of TMB and CNA can jointly stratify multiple metastatic tumors into groups with different prognosis and heterogeneous clinical responses to ICI treatment. Patients with TMB high CNA low cancer can be an optimal subgroup for ICI therapy., (©2019 American Association for Cancer Research.)

To study the chemical constituents of Camellia sinensis var. assamica. The compounds were isolated by NKA Macroporous resin silica gel, Sephadex LH-20, RP-C18 column chromatographies and semi-preparative HPLC,and their structures were elucidated by physicochemical properties and spectral analysis. Thirteen compounds were isolated and identified as caffeine (1), theobromine (2), gallic acid (3), (+)-catechin (4), ampelopsin (5), (-)-epicatechin (6), (-)-epiafzelechin (7), (-)-epicatechin-3-O-gallate (8), (-)-epiafzelechin-3-O-gallate (9) , (+)-catechin-3-O-gallate (10) , (+)-afzelechin-3-O-gallate (11), quemefin-3-O-alpha-L-arabinopyranosid (12), and (-)-epicatechin-3-O-p-hydroxybenzoate (13). Compounds 2, 5, 10-13 were isolated from this plant for the first time, and compound 11 is a new natural product.

Objective: To investigate the reversing effect of Bcl-XL small interfering RNA (siRNA) on the acquired resistance to tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) in human colon cancer., Methods: Human colon cancer cells DLD1-TRAIL/R, with acquired resistance to TRAIL, were firstly transfected with Bcl-XL siRNA for 24 h followed by the treatment of TRAIL protein. The survival rate of DLD1-TRAIL/R cells was assessed by FACS analysis and cell number counting, respectively, and activation of its apoptotic signaling was evaluated by Western blot., Results: Bcl-XL siRNA effectively downregulated the expression of Bcl-XL protein and reversed the acquired resistance to TRAIL in DLD1-TRAIL/R cells. After combination treatment of Bcl-XL siRNA and TRAIL protein, the apoptotic rate of DLD1-TRAIL/R cells was more than 50% and survival rate was less than 40%, whereas there was no effect on the survival of DLD1-TRAIL/R cells after treatment with control treatment or TRAIL protein treatment alone (P < 0.05). Western blot analysis demonstrated that caspase-8, caspase-9, Bid, caspase-3, and poly (ADP-ribose) polymerase (PARP) were obviously activated after combination treatment with Bcl-XL siRNA and TRAIL protein, and the release of cytochrome C was also significantly increased., Conclusion: Bcl-XL siRNA can effectively reverse the acquired resistance to TRAIL in human colon cancer cells, suggesting that it might be a new strategy for overcoming the resistance in cancer therapy.

Aim: Because of a major resistance to chemotherapy, prognosis of hepatocellular carcinoma (HCC) is still poor. New treatments are required and gene therapy may be an option. Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) induces apoptosis in multiple malignant tumors, and using adenoviral vectors has shown a targeted tumor-specific therapy. However, repeated administration of adenoviral vectors can lead to cell resistance, which may be caused by the initial coxsackie-adenovirus receptor (CAR). One technique to overcome resistance is the use of modified adenoviral vectors containing an Arg-Gly-Asp (RGD) sequence. In this study we constructed an adenoviral vector (designated Ad/TRAIL-F/RGD) with RGD-modified fibers, expressing the TRAIL gene from the human telomerase reverse transcriptase (hTERT) promoter, and evaluated its antitumor activity in HCC cell lines., Methods: To investigate the effects of Ad/TRAIL-F/RGD in human HCC cell lines Hep G2 and Hep 3b, cells were infected with Ad/CMV-GFP (vector control), Ad/gTRAIL (positive control), and Ad/TRAIL-F/RGD. Phosphate-buffered saline (PBS) was used as control. Cell viability was determined by proliferation assay (XTT), and apoptosis induction by fluorescence activated cell sorting (FACS)., Results: Cells treated with Ad/TRAIL-F/RGD and Ad/gTRAIL showed a significantly reduced cell viability in comparison to PBS and Ad/CMV-GFP treatment in both cell lines. Whereas, treatment with PBS and Ad/CMV-GFP had no cell-killing effect. The reduced cell viability was caused by induction of apoptosis as shown by FACS analysis. The amount of apoptotic cells was similar after incubation with Ad/gTRAIL and Ad/TRAIL-F/RGD., Conclusion: The new RGD modified vector Ad/TRAIL-F/RGD could become a potent therapeutic agent for the treatment of HCC, adenovirus resistant tumors, and CAR low or negative cancer cells.