Development and validation of nomograms to predict survival and recurrence after hepatectomy for intermediate/advanced (BCLC stage B/C) hepatocellular carcinoma.

BACKGROUND: Despite the Barcelona Clinic Liver Cancer system discouraging hepatectomy for intermediate/advanced hepatocellular carcinoma, the procedure is still performed worldwide, particularly in Asia. This study aimed to develop and validate nomograms for predicting survival and recurrence for these patients. METHODS: We analyzed patients who underwent curative-intent hepatectomy for intermediate/advanced hepatocellular carcinoma between 2010 and 2020 across 3 Chinese hospitals. The Eastern Hepatobiliary Surgery Hospital cohort was used as the training cohort for the nomogram construction, and the Jilin First Hospital and Fujian Mengchao Hepatobiliary Hospital cohorts served as the external validation cohorts. Independent preoperative predictors for survival and recurrence were identified through univariable and multivariable Cox regression analyses. Predictive accuracy was measured using the concordance index and calibration curves. The predictive performance between nomograms and conventional hepatocellular carcinoma staging systems was compared. RESULTS: A total of 1,328 patients met the inclusion criteria. The nomograms for predicting survival and recurrence were developed using 10 and 6 independent variables, respectively. Nomograms' concordance indices in the training cohort were 0.777 (95% confidence interval 0.759-0.800) and 0.719 (95% confidence interval 0.697-0.742) for survival and recurrence, outperforming 4 conventional staging systems (P < .001). Nomograms accurately stratified risk into low, intermediate, and high subgroups. These results were validated well by 2 external validation cohorts. CONCLUSION: We developed and validated nomograms predicting survival and recurrence for patients with intermediate/advanced hepatocellular carcinoma, contradicting Barcelona Clinic Liver Cancer surgical guidelines. These nomograms may facilitate clinicians to formulate personalized surgical decisions, estimate long-term prognosis, and strategize neoadjuvant/adjuvant anti-recurrence therapy.

Conversion therapy for advanced hepatocellular carcinoma in the era of precision medicine: Current status, challenges and opportunities.

Hepatocellular carcinoma (HCC), the most prevalent malignancy of the digestive tract, is characterized by a high mortality rate and poor prognosis, primarily due to its initial diagnosis at an advanced stage that precludes any surgical intervention. Recent advancements in systemic therapies have significantly improved oncological outcomes for intermediate and advanced-stage HCC, and the combination of locoregional and systemic therapies further facilitates tumor downstaging and increases the likelihood of surgical resectability for initially unresectable cases following conversion therapies. This shift toward high conversion rates with novel, multimodal treatment approaches has become a principal pathway for prolonged survival in patients with advanced HCC. However, the field of conversion therapy for HCC is marked by controversies, including the selection of potential surgical candidates, formulation of conversion therapy regimens, determination of optimal surgical timing, and application of adjuvant therapy post-surgery. Addressing these challenges and refining clinical protocols and research in HCC conversion therapy is essential for setting the groundwork for future advancements in treatment strategies and clinical research. This narrative review comprehensively summarizes the current strategies and clinical experiences in conversion therapy for advanced-stage HCC, emphasizing the unresolved issues and the path forward in the context of precision medicine. This work not only provides a comprehensive overview of the evolving landscape of treatment modalities for conversion therapy but also paves the way for future studies and innovations in this field.

The causal effects of immune cells on pancreatic cancer: A 2­sample Mendelian randomization study.

Leveraging publicly available genetic datasets, we conducted a comprehensive 2-sample Mendelian randomization (MR) analysis to explore the causal links between 731 immunophenotypes and the risk of pancreatic cancer (PC). To ensure the robustness of our findings, extensive sensitivity analyses were performed, evaluating stability, heterogeneity, and potential horizontal pleiotropy. Our analysis pinpointed 24 immunophenotypes significantly associated with the risk of PC. Notably, phenotypes such as CD4+ CD8dim %leukocyte (OR = 0.852, 95% CI = 0.729-0.995, P = .0430) and HLA DR+ CD4+ AC (OR = 0.933, 95% CI = 0.883-0.986) in TBNK were inversely correlated with PC risk. Conversely, phenotypes like CD28 on CD45RA- CD4 non-Treg (OR = 1.155, 95% CI = 1.028-1.297, P = .016) and CD25 on activated Treg (OR = 1.180, 95% CI = 1.014-1.374, P = .032) in Treg cells, among others, exhibited a positive correlation. These insights offer a valuable genetic perspective that could guide future clinical research in this area.

Benchmarking Supervised and Self-Supervised Learning Methods in A Large Ultrasound Muti-task Images Dataset.

Deep learning in ultrasound(US) imaging aims to construct foundational models that accurately reflect the modality's unique characteristics. Nevertheless, the limited datasets and narrow task types have restricted this field in recent years. To address these challenges, we introduce US-MTD120K, a multi-task ultrasound dataset with 120,354 real-world two-dimensional images. This dataset covers three standard plane recognition and two diagnostic tasks in ultrasound imaging, providing a rich basis for model training and evaluation. We detail the data collection, distribution, and labelling processes, ensuring a thorough understanding of the dataset's structure. Furthermore, we conduct extensive benchmark tests on 27 state-of-the-art methods from both supervised and self-supervised learning(SSL) perspectives. In the realm of supervised learning, we analyze the sensitivity of two main feature computation methods to ultrasound images at the representational level, highlighting that models which judiciously constrain global feature computation could potentially serve as a viable analytical approach for US image analysis. In the context of self-supervised learning, we delved into the modelling process of self-supervised learning models for medical images and proposed an improvement strategy, named MoCo-US, a solution that addresses the excessive reliance on pretext task design from the input side. It achieves competitive performance with minimal pretext task design and enhances other SSL methods simply. The dataset and the code will be available at https://github.com/JsongZhang/CDOA-for-UMTD.

Grading severity of microscopic vascular invasion was independently associated with recurrence and survival following hepatectomy for solitary hepatocellular carcinoma.

Background: Hepatectomy is the preferred treatment for solitary hepatocellular carcinoma (HCC) without macrovascular invasion and distant metastasis, but long-term survival remains unsatisfactory in certain patients. We sought to identify whether the grading severity of microscopic vascular invasion (MVI) was associated with recurrence and survival among patients with solitary HCC. Methods: Consecutive patients who underwent hepatectomy for solitary HCC were identified from a multicenter prospectively-collected database. Patients were categorized into three groups according to the MVI grading system proposed by the Liver Cancer Pathology Group of China: M0 (no MVI), M1 (1-5 sites of MVI occurring ≤1.0 cm away from the tumor), and M2 (>5 sites occurring ≤1.0 cm or any site occurring >1 cm away from the tumor). Recurrence-free survival (RFS) and overall survival (OS) were compared among the groups. Results: Among 227 patients, 97 (42.7%), 83 (36.6%), and 47 (20.7%) patients had M0, M1, and M2, respectively. Median RFS rates among patients with M0, M1, and M2 were 38.3, 35.1, 11.6 months, respectively, while OS rates were 66.8, 62.3, 30.6 months, respectively (both P<0.001). Multivariate Cox-regression analyses demonstrated that both M1 and M2 were independent risk factors for RFS (hazard ratio 1.20, 95% CI: 1.03-1.89, P=0.040; and hazard ratio 1.67, 95% CI: 1.06-2.64, P=0.027) and OS (hazard ratio 1.28, 95% CI: 1.05-2.07, P=0.035; and hazard ratio 1.97, 95% CI: 1.15-3.38, P=0.013). Conclusions: Grading severity of MVI was independently associated with RFS and OS after hepatectomy for solitary HCC. Enhanced surveillance for recurrence and potentially adjuvant therapy may be considered for patients with MVI, especially individuals with more severe MVI grading (M2).

Associations between the use of red yeast rice preparations and adverse health outcomes: An umbrella review of meta-analyses of randomized controlled trials.

BACKGROUND: Red yeast rice (RYR), a natural lipid-lowering agent, is widely used in clinical practice. However, the existing meta-analyses concerning the safety of RYR preparations have yielded inconsistent results, and the credibility of the evidence has not been quantified. OBJECTIVE: This study was designed to evaluate the existing evidence and offer a comprehensive understanding of the associations between the use of RYR preparations and various adverse health outcomes. SEARCH STRATEGY: Seven literature databases were searched from inception to May 5, 2023, using medical subject headings and free-text terms (e.g., "red yeast rice," "Xuezhikang," and "Zhibitai"). INCLUSION CRITERIA: Meta-analyses that investigated and quantitatively estimated associations between the use of RYR preparations and adverse health outcomes were included in this study. DATA EXTRACTION AND ANALYSIS: Two researchers independently extracted data using a standardized data collection table; any disagreements were resolved by consulting a third researcher. Based on the participant, intervention, comparator and outcome (PICO) framework in each eligible meta-analysis, a series of unique associations between the use of RYR preparations and adverse health outcomes were determined. The associations' effect estimates were re-evaluated using random-effect models. RESULTS: Fifteen meta-analyses, comprising 186 (164 unique) randomized controlled trials, were identified. Based on A MeaSurement Tool to Assess Systematic Reviews version 2, 3 (20%) and 12 (80%) of these meta-analyses had low and critically low confidence, respectively. A total of 61 unique associations between the use of RYR preparations and adverse health outcomes were extracted from eligible meta-analyses. Based on the random-effect models, 10 (16.4%) associations indicated a significant protective effect of RYR preparations against adverse health outcomes, while 5 (8.2%) indicated an increased risk of adverse health outcomes related to uric acid, alanine transaminase and aspartate transaminase levels. The other 46 (75.4%) associations showed no significant difference between the use of RYR preparations and control treatments. Regarding the credibility of the evidence, 21 (34.4%), 34 (55.7%) and 6 (9.8%) associations showed moderate, low and very low credibility, respectively. CONCLUSION: The evidence examined in this study suggests that RYR preparations are safe; however, the credibility of the evidence was not high. Further high-quality evidence is required. Please cite this article as: Ma ZY, Yang SP, Li Y, Xu TT, Yang YL, Yang HY, Li HB, Zhou LJ, Diao Y, Li SY. Associations between the use of red yeast rice preparations and adverse health outcomes: An umbrella review of meta-analyses of randomized controlled trials. J Integr Med. 2024; 22(2): 126-136.

Genome-wide profiles of DNA damage represent highly accurate predictors of mammalian age.

The identification of novel age-related biomarkers represents an area of intense research interest. Despite multiple studies associating DNA damage with aging, there is a glaring paucity of DNA damage-based biomarkers of age, mainly due to the lack of precise methods for genome-wide surveys of different types of DNA damage. Recently, we developed two techniques for genome-wide mapping of the most prevalent types of DNA damage, single-strand breaks and abasic sites, with nucleotide-level resolution. Herein, we explored the potential of genomic patterns of DNA damage identified by these methods as a source of novel age-related biomarkers using mice as a model system. Strikingly, we found that models based on genomic patterns of either DNA lesion could accurately predict age with higher precision than the commonly used transcriptome analysis. Interestingly, the informative patterns were limited to relatively few genes and the DNA damage levels were positively or negatively correlated with age. These findings show that previously unexplored high-resolution genomic patterns of DNA damage contain useful information that can contribute significantly to both practical applications and basic science.

Development and validation of prealbumin-bilirubin score (preALBI score) for predicting long-term survival after hepatectomy for hepatocellular carcinoma: A multicenter analysis versus ALBI score.

BACKGROUND: The Albumin-Bilirubin (ALBI) score, widely used in predicting long-term prognosis for patients with hepatocellular carcinoma (HCC), has limitations due to serum albumin variability. This study aimed to develop and validate the Prealbumin-Bilirubin (preALBI) score as a reliable alternative. METHODS: A multicenter cohort of HCC patients who underwent hepatectomy was randomly divided into the training and validation cohorts. The preALBI score was developed using Cox regression models within the training cohort, incorporating serum prealbumin and bilirubin levels as crucial determinants. The survival predictive accuracy was evaluated and compared between the preALBI score with two other staging systems, including the ALBI score and the Child-Pugh grade. RESULTS: A total of 2409 patients were enrolled. In the training cohort, the preALBI score demonstrated superior performance in predicting long-term survival after hepatectomy. The preALBI score was associated with the best monotonicity of gradients (linear trend χ2: 72.84) and homogeneity (likelihood ratio χ2: 74.69), and the highest discriminatory ability (the areas under curves for 1-, 3-, and 5-year mortality: 0.663, 0.654, and 0.644, respectively). In addition, the preALBI was the most informative staging system in predicting survival (Akaike information criterion: 11325.65).The results remained consistent in both training and validation cohorts, indicating its reliable performance across different populations. CONCLUSION: The preALBI score, leveraging the stability of prealbumin, represents a promising tool for better patient stratification, providing more accurate prognostic predictions than the ALBI score and the Child-Pugh grade.

ResD-Net: A model for rapid prediction of antioxidant activity in gentian root using FT-IR spectroscopy.

Gentian, an herb resource known for its antioxidant properties, has garnered significant attention. However, existing methods are time-consuming and destructive for assessing the antioxidant activity in gentian root samples. In this study, we propose a method for swiftly predicting the antioxidant activity of gentian root using FT-IR spectroscopy combined with chemometrics. We employed machine learning and deep learning models to establish the relationship between FT-IR spectra and DPPH free radical scavenging activity. The results of model fitting reveal that the deep learning model outperforms the machine learning model. The model's performance was enhanced by incorporating the Double-Net and residual connection strategy. The enhanced model, named ResD-Net, excels in feature extraction and also avoids gradient vanishing. The ResD-Net model achieves an R2 of 0.933, an RMSE of 0.02, and an RPD of 3.856. These results support the accuracy and applicability of this method for rapidly predicting antioxidant activity in gentian root samples.

Prognostic Value of Serum α-Fetoprotein Level as an Important Characteristic of Tumor Biology for Patients Undergoing Liver Resection of Early-Stage Hepatocellular Carcinoma (BCLC Stage 0/A): A Large Multicenter Analysis.

BACKGROUND AND OBJECTIVE: According to the Barcelona Clinic Liver Cancer (BCLC) algorithm, tumor burden and liver function, but not tumor biology, are the key factors in determining tumor staging and treatment modality, and evaluating treatment prognosis. The serum α-fetoprotein (AFP) level is an important characteristic of hepatocellular carcinoma (HCC) biology, and we aimed to evaluate its prognostic value for patients undergoing liver resection of early-stage HCC. METHODS: Patients who underwent curative liver resection for early-stage HCC were identified from a multi-institutional database. Patients were divided into three groups according to preoperative AFP levels: low (< 400 ng/mL), high (400-999 ng/mL), and extremely-high (≥ 1000 ng/mL) AFP groups. Overall survival (OS) and recurrence rates were compared among these three groups. RESULTS: Among 1284 patients, 720 (56.1%), 262 (20.4%), and 302 (23.5%) patients had preoperative low, high, and extremely-high AFP levels, respectively. The cumulative 5-year OS and recurrence rates were 71.3 and 38.9% among patients in the low AFP group, 66.3 and 48.5% in the high AFP group, and 45.7 and 67.2% in the extremely-high AFP group, respectively (both p < 0.001). Multivariate Cox regression analysis identified both high and extremely-high AFP levels to be independent risk factors of OS (hazard ratio [HR] 1.275 and 1.978, 95% confidence interval [CI] 1.004-1.620 and 1.588-2.464, respectively; p = 0.047 and p < 0.001, respectively) and recurrence (HR 1.290 and 2.050, 95% CI 1.047-1.588 and 1.692-2.484, respectively; p = 0.017 and p < 0.001, respectively). CONCLUSIONS: This study demonstrated the important prognostic value of preoperative AFP levels among patients undergoing resection for early-stage HCC. Incorporating AFP to prognostic estimation of the BCLC algorithm can help guide individualized risk stratification and identify neoadjuvant/adjuvant treatment necessity.

Bleomycin promotes rAAV2 transduction via DNA-PKcs/Artemis-mediated DNA break repair pathways.

Because it is safe and has a simple genome, recombinant adeno-associated virus (rAAV) is an extremely appealing vector for delivery in in vivo gene therapy. However, its low transduction efficiency for some cells, limits its further application in the field of gene therapy. Bleomycin is a chemotherapeutic agent approved by the FDA whose effect on rAAV transduction has not been studied. In this study, we systematically investigated the effect of Bleomycin on the second-strand synthesis and used CRISPR/CAS9 and RNAi methods to understand the effects of Bleomycin on rAAV vector transduction, particularly the effect of DNA repair enzymes. The results showed that Bleomycin could promote rAAV2 transduction both in vivo and in vitro. Increased transduction was discovered to be a direct result of decreased cytoplasmic rAAV particle degradation and increased second-strand synthesis. TDP1, PNKP, and SETMAR are required to repair the DNA damage gap caused by Bleomycin, TDP1, PNKP, and SETMAR promote rAAV second-strand synthesis. Bleomycin induced DNA-PKcs phosphorylation and phosphorylated DNA-PKcs and Artemis promoted second-strand synthesis. The current study identifies an effective method for increasing the capability and scope of in-vivo and in-vitro rAAV applications, which can amplify cell transduction at Bleomycin concentrations. It also supplies information on combining tumor gene therapy with chemotherapy.

The anti-photoaging effect of C-phycocyanin on ultraviolet B-irradiated BALB/c-nu mouse skin.

Introduction: C-phycocyanin (C-PC), a photosynthetic protein obtained from Spirulina, is regarded a highly promising commercially available biochemical. Numerous in vitro and in vivo studies have provided evidence of C-PC's ability to mitigate the inflammatory response, alleviate oxidative stress, and facilitate wound healing. However, despite the existing knowledge regarding C-PC's protective mechanism against cellular apoptosis induced by ultraviolet B (UVB) radiation, further in vivo experiments are needed to explore its anti-photoaging mechanism. Methods: In this study, a UVB-induced skin photoaging model was established using BALB/c-nu mice, and the potential protective effects of topically administered c-PC were investigated by various molecular biology tools. In addition, a novel delivery system, C-PC nanodispersion, was developed to facilitate the transdermal delivery of C-PC. Results: C- PC demonstrated significant anti-photoaging activities in the UVB-induced skin. The application of C-PC to the dorsal skin of the mice resulted in improved macroscopic characteristics, such as reduced sagging and coarse wrinkling, under UVB irradiation Histological analyses showed that C-PC treatment significantly decreased the symptoms of epidermal thickening, prevented dermal collagen fiber loosening, increased the hydroxyproline (Hyp) content and activities of antioxidant enzymes (such as superoxide dismutase, catalase, and glutathione peroxidase) in mouse skin, decreased malondialdehyde levels and expressions of inflammatory factors (interleukin-1α [IL-1α], IL-1ß, IL-6, and tumor necrosis factor-α), reduced matrix metalloproteinase [MMP-3 and MMP-9] expressions, and inhibited the phosphorylation of c-Jun N-terminal kinase, extracellular signal-regulated kinase, and p38 proteins in the mitogen-activated protein kinase family. Discussion: By analyzing the results of the study, a new drug delivery system, C-PC nano-dispersion, was proposed, and the anti-photoaging effect of C-PC and its mechanism were investigated.

Genome-Wide Profiling of Endogenous Single-Stranded DNA Using the SSiNGLe-P1 Method.

Endogenous single-stranded DNA (essDNA) can form in a mammalian genome as the result of a variety of molecular processes and can both play important roles inside the cell as well as have detrimental consequences to genome integrity, much of which remains to be fully understood. Here, we established the SSiNGLe-P1 approach based on limited digestion by P1 endonuclease for high-throughput genome-wide identification of essDNA regions. We applied this method to profile essDNA in both human mitochondrial and nuclear genomes. In the mitochondrial genome, the profiles of essDNA provide new evidence to support the strand-displacement model of mitochondrial DNA replication. In the nuclear genome, essDNA regions were found to be enriched in certain types of functional genomic elements, particularly, the origins of DNA replication, R-loops, and to a lesser degree, in promoters. Furthermore, interestingly, many of the essDNA regions identified by SSiNGLe-P1 have not been annotated and thus could represent yet unknown functional elements.

Identification of Gentian-Related Species Based on Two-Dimensional Correlation Spectroscopy (2D-COS) Combined with Residual Neural Network (ResNet).

Gentian is a traditional Chinese herb with heat-clearing, damp-drying, inflammation-alleviating and digestion-promoting effects, which is widely used in clinical practice. However, there are many species of gentian. According to the pharmacopoeia, Gentiana manshurica Kitag, Gentiana scabra Bge, Gentiana triflora Pall and Gentianarigescens Franch are included. Therefore, accurately identifying the species of gentian is important in clinical use. In recent years, with the advantages of low cost, convenience, fast analysis and high sensitivity, infrared spectroscopy (IR) has been extensively used in herbal identification. Unlike one-dimensional spectroscopy, a two-dimensional correlation spectrum (2D-COS) can improve the resolution of the spectrum and better highlight the details that are difficult to detect. In addition, the residual neural network (ResNet) is an important breakthrough in convolutional neural networks (CNNs) for significant advantages related to image recognition. Herein, we propose a new method for identifying gentian-related species using 2D-COS combined with ResNet. A total of 173 gentian samples from seven different species are collected in this study. In order to eliminate a large amount of redundant information and improve the efficiency of machine learning, the extracted feature band method was used to optimize the model. Four feature bands were selected from the infrared spectrum, namely 3500-3000 cm-1, 3000-2750 cm-1, 1750-1100 cm-1 and 1100-400 cm-1, respectively. The one-dimensional spectral data were converted into synchronous 2D-COS images, asynchronous 2D-COS images, and integrative 2D-COS images using Matlab (R2022a). The identification strategy for these three 2D-COS images was based on ResNet, which analyzes 2D-COS images based on single feature bands and full bands as well as fused feature bands. According to the results, (1) compared with the other two 2D-COS images, synchronous 2D-COS images are more suitable for the ResNet model, and (2) after extracting a single feature band 1750-1100 cm-1 to optimize ResNet, the model has the best convergence performance, the accuracy of training, test and external validation is 1 and the loss value is only 0.155. In summary, 2D-COS combined with ResNet is an effective and accurate method to identify gentian-related species.

Lessons from discovery of true ADAR RNA editing sites in a human cell line.

BACKGROUND: Conversion or editing of adenosine (A) into inosine (I) catalyzed by specialized cellular enzymes represents one of the most common post-transcriptional RNA modifications with emerging connection to disease. A-to-I conversions can happen at specific sites and lead to increase in proteome diversity and changes in RNA stability, splicing, and regulation. Such sites can be detected as adenine-to-guanine sequence changes by next-generation RNA sequencing which resulted in millions reported sites from multiple genome-wide surveys. Nonetheless, the lack of extensive independent validation in such endeavors, which is critical considering the relatively high error rate of next-generation sequencing, leads to lingering questions about the validity of the current compendiums of the editing sites and conclusions based on them. RESULTS: Strikingly, we found that the current analytical methods suffer from very high false positive rates and that a significant fraction of sites in the public databases cannot be validated. In this work, we present potential solutions to these problems and provide a comprehensive and extensively validated list of A-to-I editing sites in a human cancer cell line. Our findings demonstrate that most of true A-to-I editing sites in a human cancer cell line are located in the non-coding transcripts, the so-called RNA 'dark matter'. On the other hand, many ADAR editing events occurring in exons of human protein-coding mRNAs, including those that can recode the transcriptome, represent false positives and need to be interpreted with caution. Nonetheless, yet undiscovered authentic ADAR sites that increase the diversity of human proteome exist and warrant further identification. CONCLUSIONS: Accurate identification of human ADAR sites remains a challenging problem, particularly for the sites in exons of protein-coding mRNAs. As a result, genome-wide surveys of ADAR editome must still be accompanied by extensive Sanger validation efforts. However, given the vast number of unknown human ADAR sites, there is a need for further developments of the analytical techniques, potentially those that are based on deep learning solutions, in order to provide a quick and reliable identification of the editome in any sample.

MiR133b-mediated inhibition of EGFR-PTK pathway promotes rAAV2 transduction by facilitating intracellular trafficking and augmenting second-strand synthesis.

Recombinant adeno-associated virus (rAAV) is an extremely attractive vector in the in vivo delivery of gene therapy as it is safe and its genome is simple. However, challenges including low permissiveness to specific cells and restricted tissue specificity have hindered its clinical application. Based on the previous studies, epidermal growth factor receptor-protein tyrosine kinase (EGFR-PTK) negatively regulated rAAV transduction, and EGFR-positive cells were hardly permissive to rAAV transduction. We constructed a novel rAAV-miRNA133b vector, which co-expressed miRNA133b and transgene, and investigated its in vivo and in vitro transduction efficiency. Confocal microscopy, live-cell imaging, pharmacological reagents and labelled virion tracking were used to analyse the effect of miRNA133b on rAAV2 transduction and the underlying mechanisms. The results demonstrated that miRNA133b could promote rAAV2 transduction and the effects were limited to EGFR-positive cells. The increased transduction was found to be a direct result of decreased rAAV particles degradation in the cytoplasm and enhanced second-strand synthesis. ss-rAAV2-miRNA133b vector specifically increased rAAV2 transduction in EGFR-positive cells or tissues, while ss-rAAV2-Fluc-miRNA133b exerted an antitumor effect. rAAV-miRNA133b vector might emerge as a promising platform for delivering various transgene to treat EGFR-positive cell-related diseases, such as non-small-cell lung cancer.