1.Predicting Clinically Significant Prostate Cancer Using Urine Metabolomics via Liquid Chromatography Mass Spectrometry
Chung-Hsin CHEN ; Hsiang-Po HUANG ; Kai-Hsiung CHANG ; Ming-Shyue LEE ; Cheng-Fan LEE ; Chih-Yu LIN ; Yuan Chi LIN ; William J. HUANG ; Chun-Hou LIAO ; Chih-Chin YU ; Shiu-Dong CHUNG ; Yao-Chou TSAI ; Chia-Chang WU ; Chen-Hsun HO ; Pei-Wen HSIAO ; Yeong-Shiau PU ;
The World Journal of Men's Health 2025;43(2):376-386
Purpose:
Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles.
Materials and Methods:
Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion.
Results:
The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column.
Conclusions
Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.
2.Predicting Clinically Significant Prostate Cancer Using Urine Metabolomics via Liquid Chromatography Mass Spectrometry
Chung-Hsin CHEN ; Hsiang-Po HUANG ; Kai-Hsiung CHANG ; Ming-Shyue LEE ; Cheng-Fan LEE ; Chih-Yu LIN ; Yuan Chi LIN ; William J. HUANG ; Chun-Hou LIAO ; Chih-Chin YU ; Shiu-Dong CHUNG ; Yao-Chou TSAI ; Chia-Chang WU ; Chen-Hsun HO ; Pei-Wen HSIAO ; Yeong-Shiau PU ;
The World Journal of Men's Health 2025;43(2):376-386
Purpose:
Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles.
Materials and Methods:
Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion.
Results:
The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column.
Conclusions
Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.
3.Predicting Clinically Significant Prostate Cancer Using Urine Metabolomics via Liquid Chromatography Mass Spectrometry
Chung-Hsin CHEN ; Hsiang-Po HUANG ; Kai-Hsiung CHANG ; Ming-Shyue LEE ; Cheng-Fan LEE ; Chih-Yu LIN ; Yuan Chi LIN ; William J. HUANG ; Chun-Hou LIAO ; Chih-Chin YU ; Shiu-Dong CHUNG ; Yao-Chou TSAI ; Chia-Chang WU ; Chen-Hsun HO ; Pei-Wen HSIAO ; Yeong-Shiau PU ;
The World Journal of Men's Health 2025;43(2):376-386
Purpose:
Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles.
Materials and Methods:
Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion.
Results:
The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column.
Conclusions
Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.
4.Predicting Clinically Significant Prostate Cancer Using Urine Metabolomics via Liquid Chromatography Mass Spectrometry
Chung-Hsin CHEN ; Hsiang-Po HUANG ; Kai-Hsiung CHANG ; Ming-Shyue LEE ; Cheng-Fan LEE ; Chih-Yu LIN ; Yuan Chi LIN ; William J. HUANG ; Chun-Hou LIAO ; Chih-Chin YU ; Shiu-Dong CHUNG ; Yao-Chou TSAI ; Chia-Chang WU ; Chen-Hsun HO ; Pei-Wen HSIAO ; Yeong-Shiau PU ;
The World Journal of Men's Health 2025;43(2):376-386
Purpose:
Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles.
Materials and Methods:
Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion.
Results:
The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column.
Conclusions
Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.
5.Predicting Clinically Significant Prostate Cancer Using Urine Metabolomics via Liquid Chromatography Mass Spectrometry
Chung-Hsin CHEN ; Hsiang-Po HUANG ; Kai-Hsiung CHANG ; Ming-Shyue LEE ; Cheng-Fan LEE ; Chih-Yu LIN ; Yuan Chi LIN ; William J. HUANG ; Chun-Hou LIAO ; Chih-Chin YU ; Shiu-Dong CHUNG ; Yao-Chou TSAI ; Chia-Chang WU ; Chen-Hsun HO ; Pei-Wen HSIAO ; Yeong-Shiau PU ;
The World Journal of Men's Health 2025;43(2):376-386
Purpose:
Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles.
Materials and Methods:
Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion.
Results:
The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column.
Conclusions
Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.
6.Application of 3D-printed auxiliary guides in adolescent scoliosis surgery.
Dong HOU ; Jian-Tao WEN ; Chen ZHANG ; Jin HUANG ; Chang-Quan DAI ; Kai LI ; Han LENG ; Jing ZHANG ; Shao-Bo YANG ; Xiao-Juan CUI ; Juan WANG ; Xiao-Yun YUAN
China Journal of Orthopaedics and Traumatology 2025;38(11):1119-1125
OBJECTIVE:
To investigate the accuracy and safety of pedicle screw placement using 3D-printed auxiliary guides in scoliosis correction surgery for adolescents.
METHODS:
A retrospective analysis was conducted on the clinical data of 51 patients who underwent posterior scoliosis correction surgery from January 2020 to March 2023. Among them, there were 35 cases of adolescent idiopathic scoliosis and 16 cases of congenital scoliosis. The patients were divided into two groups based on the auxiliary tool used:the 3D-printed auxiliary guide screw placement group (3D printing group) and the free-hand screw placement group (free-hand group, without auxiliary tools). The 3D printing group included 32 patients (12 males and 20 females) with an average age of (12.59±2.60) years;the free-hand group included 19 patients (7 males and 12 females) with an average age of (14.58±3.53) years. The two groups were compared in terms of screw placement accuracy and safety, spinal correction rate, intraoperative blood loss, number of intraoperative fluoroscopies, operation time, hospital stay, and preoperative and last follow-up scores of the Scoliosis Research Society-22 (SRS-22) questionnaire.
RESULTS:
A total of 707 pedicle screws were placed in the two groups, with 441 screws in the 3D printing group and 266 screws in the free-hand group. All patients in both groups successfully completed the surgery. There was a statistically significant difference in operation time between the two groups (P<0.05). The screw placement accuracy rate of the 3D printing group was 95.46% (421/441), among which the Grade A placement rate was 89.34% (394/441);the screw placement accuracy rate of the free-hand group was 86.47% (230/266), with a Grade A placement rate of 73.31% (195/266). There were statistically significant differences in the accuracy of Grade A, B, and C screw placements between the two groups (P<0.05), while no statistically significant differences were observed in intraoperative blood loss, number of fluoroscopies, correction rate, or hospital stay (P>0.05). In the SRS-22 questionnaire scores, the scores of functional status and activity ability, self-image, mental status, and pain of patients in each group at the last follow-up were significantly improved compared with those before surgery (P<0.05), but there were no statistically significant differences in all scores between the two groups (P>0.05).
CONCLUSION
In scoliosis correction surgery, compared with traditional free-hand screw placement, the use of 3D-printed auxiliary guides for screw placement significantly improves the accuracy and safety of screw placement and shortens the operation time.
Humans
;
Male
;
Scoliosis/surgery*
;
Female
;
Adolescent
;
Printing, Three-Dimensional
;
Retrospective Studies
;
Pedicle Screws
;
Child
7.A Study of Flow Sorting Lymphocyte Subsets to Detect Epstein-Barr Virus Reactivation in Patients with Hematological Malignancies.
Hui-Ying LI ; Shen-Hao LIU ; Fang-Tong LIU ; Kai-Wen TAN ; Zi-Hao WANG ; Han-Yu CAO ; Si-Man HUANG ; Chao-Ling WAN ; Hai-Ping DAI ; Sheng-Li XUE ; Lian BAI
Journal of Experimental Hematology 2025;33(5):1468-1475
OBJECTIVE:
To analyze the Epstein-Barr virus (EBV) load in different lymphocyte subsets, as well as clinical characteristics and outcomes in patients with hematologic malignancies experiencing EBV reactivation.
METHODS:
Peripheral blood samples from patients were collected. B, T, and NK cells were isolated sorting with magnetic beads by flow cytometry. The EBV load in each subset was quantitated by real-time quantitative polymerase chain reaction (RT-qPCR). Clinical data were colleted from electronic medical records. Survival status was followed up through outpatient visits and telephone calls. Statistical analyses were performed using SPSS 25.0.
RESULTS:
A total of 39 patients with hematologic malignancies were included, among whom 35 patients had undergone allogeneic hematopoietic stem cell transplantation (allo-HSCT). The median time to EBV reactivation was 4.8 months (range: 1.7-57.1 months) after allo-HSCT. EBV was detected in B, T, and NK cells in 20 patients, in B and T cells in 11 patients, and only in B cells in 4 patients. In the 35 patients, the median EBV load in B cells was 2.19×104 copies/ml, significantly higher than that in T cells (4.00×103 copies/ml, P <0.01) and NK cells (2.85×102 copies/ml, P <0.01). Rituximab (RTX) was administered for 32 patients, resulting in EBV negativity in 32 patients with a median time of 8 days (range: 2-39 days). Post-treatment analysis of 13 patients showed EBV were all negative in B, T, and NK cells. In the four non-transplant patients, the median time to EBV reactivation was 35 days (range: 1-328 days) after diagnosis of the primary disease. EBV was detected in one or two subsets of B, T, or NK cells, but not simultaneously in all three subsets. These patients received a combination chemotherapy targeting at the primary disease, with 3 patients achieving EBV negativity, and the median time to be negative was 40 days (range: 13-75 days).
CONCLUSION
In hematologic malignancy patients after allo-HSCT, EBV reactivation commonly involves B, T, and NK cells, with a significantly higher viral load in B cells compared to T and NK cells. Rituximab is effective for EBV clearance. In non-transplant patients, EBV reactivation is restricted to one or two lymphocyte subsets, and clearance is slower, highlighting the need for prompt anti-tumor therapy.
Humans
;
Hematologic Neoplasms/virology*
;
Herpesvirus 4, Human/physiology*
;
Epstein-Barr Virus Infections
;
Hematopoietic Stem Cell Transplantation
;
Virus Activation
;
Lymphocyte Subsets/virology*
;
Flow Cytometry
;
Killer Cells, Natural/virology*
;
Male
;
Female
;
B-Lymphocytes/virology*
;
Viral Load
;
Adult
;
T-Lymphocytes/virology*
;
Middle Aged
8.Resveratrol Attenuates Inflammation in Acute Lung Injury through ROS-Triggered TXNIP/NLRP3 Pathway.
Wen-Han HUANG ; Kai-Ying FAN ; Yi-Ting SHENG ; Wan-Ru CAI
Chinese journal of integrative medicine 2025;31(12):1078-1086
OBJECTIVE:
To evaluate the protective effects of resveratrol against acute lung injury (ALI) and investigate the potential mechanisms underlying the reactive oxygen species (ROS)-triggered thioredoxin-interacting protein (TXNIP)/NOD-, LRR- and pyrin domain-containing protein 3 (NLRP3) pathway.
METHODS:
C57BL/6 mice and J774A.1 cells were selected as the research subjects. Thirty Mice were randomly divided into 5 groups of 6 in each group: control with 0.9% saline, 5 mg/kg lipopolysaccharide (LPS) 24 h, 25 mg/kg resveratrol + 5 mg/kg LPS, 100 mg/kg resveratrol + 5 mg/kg LPS, and 4 mg/kg NLRP3 inhibitor CY-09 + 5 mg/kg LPS. For cell stimulation, cells were pretreated with 5 and 20 µmol/L resveratrol for 2 h, and stimulated with or without 1 µg/mL LPS and 3 mmol/L ATP for 2 h. The antioxidant N-acetyl-L-cysteine (NAC, 2 µmol/L) was used as the positive control group. Hematoxylin and eosin staining was used to evaluate the degree of lung LPS-induced tissue damage, and enzyme-linked immunosorbent assay was used to evaluate the contents of interleukin-1 β (IL-1 β) and IL-18 in the serum and cell supernatant. ROS and malondialdehyde (MDA) levels in the lung tissue were detected using the corresponding kits. Western blotting was used to detect the expressions of TXNIP, high-mobility group box 1 (HMGB1), NLRP3, as well as cysteine-aspartic acid protease 1 (caspase-1) and gasdermin D (GSDMD) along with their cleaved forms in lung tissue. Additionally, reverse transcription quantitative polymerase chain reaction was performed to analyze the expression of related inflammatory cytokines. ROS content was detected using flow cytometry and confocal laser microscopy. Mitochondrial morphological changes were observed using transmission electron microscopy, and HMGB1 expression was detected using immunofluorescence.
RESULTS:
Resveratrol significantly alleviated LPS-induced lung damage with reduced inflammation, interstitial edema, and leukocyte infiltration (P<0.01). It also decreased serum levels of IL-1 β and IL-18 (P<0.05), while downregulating the expressions of NLRP3, IL-6, and other inflammatory markers at both the protein and mRNA levels (P<0.05). Notably, the higher dose (100 mg/kg) demonstrated a better effect than the lower dose (25 mg/kg). In macrophages, resveratrol reduced IL-1 β and IL-18 following LPS and ATP stimulation, suppressed HMGB1 translocation, and inhibited formation and activation of the NLRP3 inflammasome (P<0.05 or P<0.01). These anti-inflammatory effects were mediated through the suppression ROS accumulation (P<0.01) and mitochondrial dysfunction. Transmission electron microscopy revealed that resveratrol preserved mitochondrial structure, preventing the mitochondrial damage seen in LPS-treated groups (P<0.01). The expressions of cleaved caspase-1, cleaved GSDMD, and cytoplasmic HMGB1 were all reduced following resveratrol treatment (P<0.01). Moreover, resveratrol inhibited dissociation of TXNIP from thioredoxin, blocking subsequent activation of NLRP3 and downstream inflammatory cytokines (P<0.01). Similarly, the higher concentration of resveratrol (20 µ mol/L) exhibited superior efficacy in vitro.
CONCLUSION
Resveratrol can reduce the inflammatory response following ALI and inhibit the activation of NLRP3 inflammasome and the level of HMGB1 in the cytoplasm by inhibiting ROS overproduction.
Acute Lung Injury/metabolism*
;
NLR Family, Pyrin Domain-Containing 3 Protein/metabolism*
;
Animals
;
Resveratrol/pharmacology*
;
Reactive Oxygen Species/metabolism*
;
Inflammation/complications*
;
Mice, Inbred C57BL
;
Carrier Proteins/metabolism*
;
Signal Transduction/drug effects*
;
Lipopolysaccharides
;
Thioredoxins/metabolism*
;
Mice
;
Lung/drug effects*
;
Male
;
Cell Line
;
Interleukin-1beta/metabolism*
;
Cell Cycle Proteins
;
Stilbenes/therapeutic use*
9.Research Progress on Gene Polymorphisms Related to Osteosarcoma
Peng ZHANG ; Kai CHEN ; Lingling HUANG ; Jinyan LIU ; Wen TIAN
Cancer Research on Prevention and Treatment 2024;51(8):625-629
Osteosarcoma,which primarily affects children and adolescents,is a highly malignant bone tumor with high rates of disability and mortality.Therefore,the exploration of biological markers related to its occurrence,development,and prognosis is crucial.Genome-wide association studies have revealed the vital role of genetic polymorphisms in the pathogenesis of osteosarcoma.This study aims to provide new insights into reliable biomarkers of osteosarcoma through the analysis of the functional single-nucleotide polymor-phisms of tumor-related genes.
10.Expert consensus on surgical treatment of oropharyngeal cancer
China Anti-Cancer Association Head and Neck Oncology Committee ; China Anti-Cancer Association Holistic Integrative Oral Cancer on Preventing and Screen-ing Committee ; Min RUAN ; Nannan HAN ; Changming AN ; Chao CHEN ; Chuanjun CHEN ; Minjun DONG ; Wei HAN ; Jinsong HOU ; Jun HOU ; Zhiquan HUANG ; Chao LI ; Siyi LI ; Bing LIU ; Fayu LIU ; Xiaozhi LV ; Zheng-Hua LV ; Guoxin REN ; Xiaofeng SHAN ; Zhengjun SHANG ; Shuyang SUN ; Tong JI ; Chuanzheng SUN ; Guowen SUN ; Hao TIAN ; Yuanyin WANG ; Yueping WANG ; Shuxin WEN ; Wei WU ; Jinhai YE ; Di YU ; Chunye ZHANG ; Kai ZHANG ; Ming ZHANG ; Sheng ZHANG ; Jiawei ZHENG ; Xuan ZHOU ; Yu ZHOU ; Guopei ZHU ; Ling ZHU ; Susheng MIAO ; Yue HE ; Jugao FANG ; Chenping ZHANG ; Zhiyuan ZHANG
Journal of Prevention and Treatment for Stomatological Diseases 2024;32(11):821-833
With the increasing proportion of human papilloma virus(HPV)infection in the pathogenic factors of oro-pharyngeal cancer,a series of changes have occurred in the surgical treatment.While the treatment mode has been im-proved,there are still many problems,including the inconsistency between diagnosis and treatment modes,the lack of popularization of reconstruction technology,the imperfect post-treatment rehabilitation system,and the lack of effective preventive measures.Especially in terms of treatment mode for early oropharyngeal cancer,there is no unified conclu-sion whether it is surgery alone or radiotherapy alone,and whether robotic minimally invasive surgery has better func-tional protection than radiotherapy.For advanced oropharyngeal cancer,there is greater controversy over the treatment mode.It is still unclear whether to adopt a non-surgical treatment mode of synchronous chemoradiotherapy or induction chemotherapy combined with synchronous chemoradiotherapy,or a treatment mode of surgery combined with postopera-tive chemoradiotherapy.In order to standardize the surgical treatment of oropharyngeal cancer in China and clarify the indications for surgical treatment of oropharyngeal cancer,this expert consensus,based on the characteristics and treat-ment status of oropharyngeal cancer in China and combined with the international latest theories and practices,forms consensus opinions in multiple aspects of preoperative evaluation,surgical indication determination,primary tumor re-section,neck lymph node dissection,postoperative defect repair,postoperative complication management prognosis and follow-up of oropharyngeal cancer patients.The key points include:① Before the treatment of oropharyngeal cancer,the expression of P16 protein should be detected to clarify HPV status;② Perform enhanced magnetic resonance imaging of the maxillofacial region before surgery to evaluate the invasion of oropharyngeal cancer and guide precise surgical resec-tion of oropharyngeal cancer.Evaluating mouth opening and airway status is crucial for surgical approach decisions and postoperative risk prediction;③ For oropharyngeal cancer patients who have to undergo major surgery and cannot eat for one to two months,it is recommended to undergo percutaneous endoscopic gastrostomy before surgery to effectively improve their nutritional intake during treatment;④ Early-stage oropharyngeal cancer patients may opt for either sur-gery alone or radiation therapy alone.For intermediate and advanced stages,HPV-related oropharyngeal cancer general-ly prioritizes radiation therapy,with concurrent chemotherapy considered based on tumor staging.Surgical treatment is recommended as the first choice for HPV unrelated oropharyngeal squamous cell carcinoma(including primary and re-current)and recurrent HPV related oropharyngeal squamous cell carcinoma after radiotherapy and chemotherapy;⑤ For primary exogenous T1-2 oropharyngeal cancer,direct surgery through the oral approach or da Vinci robotic sur-gery is preferred.For T3-4 patients with advanced oropharyngeal cancer,it is recommended to use temporary mandibu-lectomy approach and lateral pharyngotomy approach for surgery as appropriate;⑥ For cT1-2N0 oropharyngeal cancer patients with tumor invasion depth>3 mm and cT3-4N0 HPV unrelated oropharyngeal cancer patients,selective neck dissection of levels ⅠB to Ⅳ is recommended.For cN+HPV unrelated oropharyngeal cancer patients,therapeutic neck dissection in regions Ⅰ-Ⅴ is advised;⑦ If PET-CT scan at 12 or more weeks after completion of radiation shows intense FDG uptake in any node,or imaging suggests continuous enlargement of lymph nodes,the patient should undergo neck dissection;⑧ For patients with suspected extracapsular invasion preoperatively,lymph node dissection should include removal of surrounding muscle and adipose connective tissue;⑨ The reconstruction of oropharyngeal cancer defects should follow the principle of reconstruction steps,with priority given to adjacent flaps,followed by distal pedicled flaps,and finally free flaps.The anterolateral thigh flap with abundant tissue can be used as the preferred flap for large-scale postoperative defects.


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