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.Biological principles of "food and medicine homologous"
Jin-wen DING ; Xiang-yin CHI ; Yu ZHANG ; Lu-lu WANG ; Jian-dong JIANG ; Yuan LIN
Acta Pharmaceutica Sinica 2024;59(6):1509-1518
With the rapid society development and broad recognition of "Healthy China", the demands for good life and health are increasing. Accordingly, the concept of "food and medicine homologous" have been attractive. The concept of "food and medicine homologous" has a long history in China, and is an essence of various ideas in traditional Chinese medicine, such as diet therapy, medicated diet, regimen and preventive treatment of disease, representing an important field in health science. Many studies have found that the active ingredients of "food and medicine homologous" substances are multiple types, multiple mechanisms and multiple targets, exerting their biological effects after oral administration and chemical or metabolic transformation. In this review, the chemical basis and biological principles of various "food and medicine homologous" substances were summarized as compounds, biological macromolecules and intestinal flora. By focusing on the intestinal flora, we discussed the detailed biological principles of several classic "food and medicine homologous" substances. The scientific significance of "food and medicine homologous" concept were also discussed. This review explores the concept of "food and medicine homologous" from the perspective of modern medicine, in order to provide insights for future drug development and human health.
7.Protective loop ileostomy or colostomy? A risk evaluation of all common complications
Yi-Wen YANG ; Sheng-Chieh HUANG ; Hou-Hsuan CHENG ; Shih-Ching CHANG ; Jeng-Kai JIANG ; Huann-Sheng WANG ; Chun-Chi LIN ; Hung-Hsin LIN ; Yuan-Tzu LAN
Annals of Coloproctology 2024;40(6):580-587
Purpose:
Protective ileostomy and colostomy are performed in patients undergoing low anterior resection with a high leakage risk. We aimed to compare surgical, medical, and daily care complications between these 2 ostomies in order to make individual choice.
Methods:
Patients who underwent low anterior resection for rectal tumors with protective stomas between January 2011 and September 2018 were enrolled. Stoma-related complications were prospectively recorded by wound, ostomy, and continence nurses. The cancer stage and treatment data were obtained from the Taiwan Cancer Database of our Big Data Center. Other demographic data were collected retrospectively from medical notes. The complications after stoma creation and after the stoma reversal were compared.
Results:
There were 176 patients with protective colostomy and 234 with protective ileostomy. Protective ileostomy had higher proportions of high output from the stoma for 2 consecutive days than protective colostomy (11.1% vs. 0%, P<0.001). Protective colostomy resulted in more stoma retraction than protective ileostomy (21.6% vs. 9.4%, P=0.001). Female, open operation, ileostomy, and carrying stoma more than 4 months were also significantly associated with a higher risk of stoma-related complications during diversion. For stoma retraction, the multivariate analysis revealed that female (odds ratio [OR], 4.00; 95% confidence interval [CI], 2.13–7.69; P<0.001) and long diversion duration (≥4 months; OR, 2.33; 95% CI, 1.22–4.43; P=0.010) were independent risk factors, but ileostomy was an independent favorable factor (OR, 0.40; 95% CI, 0.22–0.72; P=0.003). The incidence of complication after stoma reversal did not differ between colostomy group and ileostomy group (24.3% vs. 20.9%, P=0.542).
Conclusion
We suggest avoiding colostomy in patients who are female and potential prolonged diversion when stoma retraction is a concern. Otherwise, ileostomy should be avoided for patients with impaired renal function. Wise selection and flexibility are more important than using one type of stoma routinely.
8.Video Head Impulse Test Coherence Predicts Vertigo Recovery in Sudden Sensorineural Hearing Loss With Vertigo
Sheng-Chiao LIN ; Ming-Yee LIN ; Bor-Hwang KANG ; Yaoh-Shiang LIN ; Yu-Hsi LIU ; Chi-Yuan YIN ; Po-Shing LIN ; Che-Wei LIN
Clinical and Experimental Otorhinolaryngology 2024;17(4):282-291
Objectives:
. Our study aimed to explore the role of the potassium channel KCNK1 in head and neck squamous cell carcinoma, focusing on its impact on tumor growth, invasion, and metastasis. We also investigated the therapeutic potential of quinidine, a known KCNK1 inhibitor, in both in vitro cell lines and a zebrafish patient-derived xenograft (PDX) model.
Methods:
. We established primary cell cultures from head and neck cancer tissues and employed the FaDu cell line for in vitro studies, modulating KCNK1 expression through overexpression and knockdown techniques. We evaluated cell migration, invasion, and proliferation. Additionally, we developed a zebrafish PDX model to assess the impact of quinidine on tumor growth and metastasis in vivo. RNA sequencing and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were conducted to elucidate the molecular mechanisms underlying the role of KCNK1 in cancer progression.
Results:
. Overexpression of KCNK1 in FaDu cells resulted in enhanced cell migration and invasion, whereas its knockdown diminished these processes. In the zebrafish PDX model, quinidine markedly inhibited tumor growth and metastasis, demonstrating a significant reduction in tumor volume and micrometastasis rates compared to the control groups. The molecular analyses indicated that KCNK1 plays a role in critical signaling pathways associated with tumor growth, such as the Ras and MAPK pathways.
Conclusion
. Our findings highlight the critical role of KCNK1 in promoting tumor growth and metastasis in head and neck cancer. The inhibitory effect of quinidine on tumor progression in the zebrafish PDX model highlights the therapeutic potential of targeting KCNK1. These results suggest that KCNK1 could serve as a valuable therapeutic target for head and neck cancer, warranting further investigation into treatments that target KCNK1.
9.Protective loop ileostomy or colostomy? A risk evaluation of all common complications
Yi-Wen YANG ; Sheng-Chieh HUANG ; Hou-Hsuan CHENG ; Shih-Ching CHANG ; Jeng-Kai JIANG ; Huann-Sheng WANG ; Chun-Chi LIN ; Hung-Hsin LIN ; Yuan-Tzu LAN
Annals of Coloproctology 2024;40(6):580-587
Purpose:
Protective ileostomy and colostomy are performed in patients undergoing low anterior resection with a high leakage risk. We aimed to compare surgical, medical, and daily care complications between these 2 ostomies in order to make individual choice.
Methods:
Patients who underwent low anterior resection for rectal tumors with protective stomas between January 2011 and September 2018 were enrolled. Stoma-related complications were prospectively recorded by wound, ostomy, and continence nurses. The cancer stage and treatment data were obtained from the Taiwan Cancer Database of our Big Data Center. Other demographic data were collected retrospectively from medical notes. The complications after stoma creation and after the stoma reversal were compared.
Results:
There were 176 patients with protective colostomy and 234 with protective ileostomy. Protective ileostomy had higher proportions of high output from the stoma for 2 consecutive days than protective colostomy (11.1% vs. 0%, P<0.001). Protective colostomy resulted in more stoma retraction than protective ileostomy (21.6% vs. 9.4%, P=0.001). Female, open operation, ileostomy, and carrying stoma more than 4 months were also significantly associated with a higher risk of stoma-related complications during diversion. For stoma retraction, the multivariate analysis revealed that female (odds ratio [OR], 4.00; 95% confidence interval [CI], 2.13–7.69; P<0.001) and long diversion duration (≥4 months; OR, 2.33; 95% CI, 1.22–4.43; P=0.010) were independent risk factors, but ileostomy was an independent favorable factor (OR, 0.40; 95% CI, 0.22–0.72; P=0.003). The incidence of complication after stoma reversal did not differ between colostomy group and ileostomy group (24.3% vs. 20.9%, P=0.542).
Conclusion
We suggest avoiding colostomy in patients who are female and potential prolonged diversion when stoma retraction is a concern. Otherwise, ileostomy should be avoided for patients with impaired renal function. Wise selection and flexibility are more important than using one type of stoma routinely.
10.Protective loop ileostomy or colostomy? A risk evaluation of all common complications
Yi-Wen YANG ; Sheng-Chieh HUANG ; Hou-Hsuan CHENG ; Shih-Ching CHANG ; Jeng-Kai JIANG ; Huann-Sheng WANG ; Chun-Chi LIN ; Hung-Hsin LIN ; Yuan-Tzu LAN
Annals of Coloproctology 2024;40(6):580-587
Purpose:
Protective ileostomy and colostomy are performed in patients undergoing low anterior resection with a high leakage risk. We aimed to compare surgical, medical, and daily care complications between these 2 ostomies in order to make individual choice.
Methods:
Patients who underwent low anterior resection for rectal tumors with protective stomas between January 2011 and September 2018 were enrolled. Stoma-related complications were prospectively recorded by wound, ostomy, and continence nurses. The cancer stage and treatment data were obtained from the Taiwan Cancer Database of our Big Data Center. Other demographic data were collected retrospectively from medical notes. The complications after stoma creation and after the stoma reversal were compared.
Results:
There were 176 patients with protective colostomy and 234 with protective ileostomy. Protective ileostomy had higher proportions of high output from the stoma for 2 consecutive days than protective colostomy (11.1% vs. 0%, P<0.001). Protective colostomy resulted in more stoma retraction than protective ileostomy (21.6% vs. 9.4%, P=0.001). Female, open operation, ileostomy, and carrying stoma more than 4 months were also significantly associated with a higher risk of stoma-related complications during diversion. For stoma retraction, the multivariate analysis revealed that female (odds ratio [OR], 4.00; 95% confidence interval [CI], 2.13–7.69; P<0.001) and long diversion duration (≥4 months; OR, 2.33; 95% CI, 1.22–4.43; P=0.010) were independent risk factors, but ileostomy was an independent favorable factor (OR, 0.40; 95% CI, 0.22–0.72; P=0.003). The incidence of complication after stoma reversal did not differ between colostomy group and ileostomy group (24.3% vs. 20.9%, P=0.542).
Conclusion
We suggest avoiding colostomy in patients who are female and potential prolonged diversion when stoma retraction is a concern. Otherwise, ileostomy should be avoided for patients with impaired renal function. Wise selection and flexibility are more important than using one type of stoma routinely.

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