Chao Tu

Prof. Chao Tu

The Second Xiangya Hospital of Central South University, Changsha, China

Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 August 2024 in Journal of Controlled Release
Verified
Journal Article
Closed access
XHXinyan Hao
Xinyan Hao
BJBuchan Jiang
Buchan Jiang
JWJunyong Wu
Junyong Wu
DXDaxiong Xiang
Daxiong Xiang
ZXZijian Xiong
Zijian Xiong
ZLZhihong Li
Zhihong Li

30 November 2024 in Molecular Cancer
Verified
Journal Article
Open access
PDF file
HWHua Wang
Hua Wang
TWTao Wang
Tao Wang
SYShuxiang Yan
Shuxiang Yan
JTJinxin Tang
Jinxin Tang
YZYibo Zhang
Yibo Zhang
Chao TuChao Tu
Chao Tu
In the realm of cancer research, the tumor microenvironment (TME) plays a crucial role in tumor initiation and progression, shaped by complex interactions between cancer cells and surrounding non-cancerous cells. Cytokines, as essential immunomodulatory agents, are secreted by various cellular constituents within the TME, including immune cells, cancer-associated fibroblasts, and cancer cells themselves. These cytokines facilitate intricate communication networks that significantly influence tumor initiation, progression, metastasis, and immune suppression. Pyroptosis contributes to TME remodeling by promoting the release of pro-inflammatory cytokines and sustaining chronic inflammation, impacting processes such as immune escape and angiogenesis. However, challenges remain due to the complex interplay among cytokines, pyroptosis, and the TME, along with the dual effects of pyroptosis on cancer progression and therapy-related complications like cytokine release syndrome. Unraveling these complexities could facilitate strategies that balance inflammatory responses while minimizing tissue damage during therapy. This review delves into the complex crosstalk between cytokines, pyroptosis, and the TME, elucidating their contribution to tumor progression and metastasis. By synthesizing emerging therapeutic targets and innovative technologies concerning TME, this review aims to provide novel insights that could enhance treatment outcomes for cancer patients.

4 April 2022 in Journal of Orthopaedic Surgery and Research
Verified
Journal Article
Open access
PDF file
BLBinfeng Liu
Binfeng Liu
CFChengyao Feng
Chengyao Feng
Chao TuChao Tu
Chao Tu
Background: The purpose of this study was to perform an updated meta-analysis to compare the outcomes of kinematic alignment (KA) and mechanical alignment (MA) in patients undergoing total knee arthroplasty. Methods: PubMed, EMBASE, Web of Science, Google Scholar, and the Cochrane Library were systematically searched. Eligible randomized controlled trials regarding the clinical outcomes of patients undergoing total knee arthroplasty with KA and MA were included for the analysis. Results: A total of 1112 participants were included in this study, including 559 participants with KA and 553 patients with MA. This study revealed that the Western Ontario and McMaster Universities Osteoarthritis Index, Knee Society Score (knee and combined), and knee flexion range were better in the patients with kinematic alignment than in the mechanical alignment. In terms of radiological results, the femoral knee angle, mechanical medial proximal tibial angle, and joint line orientation angle were significantly different between the two techniques. Perioperatively, the walk distance before discharge was longer in the KA group than in the MA group. In contrast, other functional outcomes, radiological results, perioperative outcomes, and postoperative complication rates were similar in both the kinematic and mechanical alignment groups. Conclusions: The KA technique achieved better functional outcomes than the mechanical technique in terms of KSS (knee and combined), WOMAC scores, and knee flexion range. PROSPERO trial registration number CRD42021264519. Date registration: July 28, 2021.

12 September 2021 in BMC Musculoskeletal Disorders
Verified
Journal Article
Open access
PDF file
XRXiaolei Ren
Xiaolei Ren
LLLin Ling
Lin Ling
LQLin Qi
Lin Qi
ZLZhongyue Liu
Zhongyue Liu
WZWenchao Zhang
Wenchao Zhang
ZLZhihong Li
Zhihong Li
Background: Periprosthetic joint infection (PJI) is a catastrophic complication after total hip arthroplasty (THA). Our meta-analysis aimed to identify the individual-related risk factors that predispose patients to PJI following primary THA. Methods: Comprehensive literature retrieval from Pubmed, Web of Science, and the Cochrane Library was performed from inception to Feb 20th, 2021. Patient-related risk factors were compared as per the modifiable factors (BMI, smoke and alcohol abuse), non-modifiable factors (gender, age), and medical history characteristics, such as diabetes mellitus (DM), avascular necrosis (AVN) of femoral head, femoral neck fracture, rheumatoid arthritis (RA), cardiovascular disease (CVD), and osteoarthritis (OA) etc. The meta-analysis was applied by using risk ratios with 95% corresponding intervals. Sensitivity analysis and publication bias were performed to further assess the credibility of the results. Results: Overall, 40 studies with 3,561,446 hips were enrolled in our study. By implementing cumulative meta-analysis, higher BMI was found associated with markedly increased PJI risk after primary THA [2.40 (2.01–2.85)]. Meanwhile, medical characteristics including DM [1.64 (1.25–2.21)], AVN [1.65 (1.07–2.56)], femoral neck fracture [1.75 (1.39–2.20)], RA [1.37 (1.23–1.54)], CVD [1.34 (1.03–1.74)], chronic pulmonary disease (CPD) [1.22 (1.08–1.37)], neurological disease [1.19 (1.05–1.35)], opioid use [1.53 (1.35–1.73)] and iron-deficiency anemia (IDA) [1.15 (1.13–1.17)] were also significantly correlated with higher rate of PJI. Conversely, dysplasia or dislocation [0.65 (0.45–0.93)], and OA [0.70 (0.62–0.79)] were protective factors. Of Note, female gender was protective for PJI only after longer follow-up. Besides, age, smoking, alcohol abuse, previous joint surgery, renal disease, hypertension, cancer, steroid use and liver disease were not closely related with PJI risk. Conclusion: Our finding suggested that the individual-related risk factors for PJI after primary THA included high BMI, DM, AVN, femoral neck fracture, RA, CVD, CPD, neurological disease, opioid use and IDA, while protective factors were female gender, dysplasia/ dislocation and OA.

8 October 2022 in Journal of Hematology & Oncology
Verified
Journal Article
Open access
PDF file
HWHua Wang
Hua Wang
XZXiaowen Zhou
Xiaowen Zhou
CLChenbei Li
Chenbei Li
SYShuxiang Yan
Shuxiang Yan
CFChengyao Feng
Chengyao Feng
Chao TuChao Tu
Chao Tu
Pediatric cancers are the driving cause of death for children and adolescents. Due to safety requirements and considerations, treatment strategies and drugs for pediatric cancers have been so far scarcely studied. It is well known that tumor cells tend to progressively evade cell death pathways, which is known as apoptosis resistance, one of the hallmarks of cancer, dominating tumor drug resistance. Recently, treatments targeting nonapoptotic cell death have drawn great attention. Pyroptosis, a newly specialized form of cell death, acts as a critical physiological regulator in inflammatory reaction, cell development, tissue homeostasis and stress response. The action in different forms of pyroptosis is of great significance in the therapy of pediatric cancers. Pyroptosis could be induced and consequently modulate tumorigenesis, progression, and metastasis if treated with local or systemic therapies. However, excessive or uncontrolled cell death might lead to tissue damage, acute inflammation, or even cytokine release syndrome, which facilitates tumor progression or recurrence. Herein, we aimed to describe the molecular mechanisms of pyroptosis, to highlight and discuss the challenges and opportunities for activating pyroptosis pathways through various oncologic therapies in multiple pediatric neoplasms, including osteosarcoma, neuroblastoma, leukemia, lymphoma, and brain tumors.

13 March 2025 in npj Precision Oncology
Verified
Journal Article
Open access
PDF file
HWHua Wang
Hua Wang
YHYu He
Yu He
LWLu Wan
Lu Wan
CLChenbei Li
Chenbei Li
ZLZhaoqi Li
Zhaoqi Li
Chao TuChao Tu
Chao Tu
Primary bone tumors (PBTs) present significant diagnostic challenges due to their heterogeneous nature and similarities with bone infections. This study aimed to develop an ensemble deep learning framework that integrates multicenter radiographs and extensive clinical features to accurately differentiate between PBTs and bone infections. We compared the performance of the ensemble model with four imaging models based solely on radiographs utilizing EfficientNet B3, EfficientNet B4, Vision Transformer, and Swin Transformers. The patients were split into external dataset (N = 423) and internal dataset [including training (N = 1044), test (N = 354), and validation set (N = 171)]. The ensemble model outperformed imaging models, achieving areas under the curve (AUCs) of 0.948 and 0.963 on internal and external sets, respectively, with accuracies of 0.881 and 0.895. Its performance surpassed junior and mid-level radiologists and was comparable to senior radiologists (accuracy: 83.6%). These findings underscore the potential of deep learning in enhancing diagnostic precision for PBTs and bone infections (Research Registration Unique Identifying Number (UIN): researchregistry10483 and with details are available at https://www.researchregistry.com/register-now#home/registrationdetails/6693845995ba110026aeb754/).