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.

Purpose: Zinc finger protein 639 (ZNF639) is often found within the overlapping amplicon of PIK3CA, and previous studies suggest its involvement in the pathogenesis of esophageal and oral squamous cell carcinomas. However, its expression and significance in breast cancer remain uncharacterized. Methods: Immunohistochemical analysis of ZNF639 was performed using tissue microarrays.Functional studies, including colony formation, Transwell cell migration, and in vivo metastasis, were conducted on breast tumor cells with ZNF639 knockdown via small interfering RNA transfection. Results: Reduced ZNF639 immunoreactivity was observed in 82% of the breast cancer samples, independent of hormone receptor and human epidermal growth factor receptor 2 status. In multivariate Cox regression analyses, ZNF639 expression was associated with favorable survival outcomes, including recurrence-free survival (hazard ratio, 0.35; 95% confidence interval [CI], 0.14–0.89) and overall survival (hazard ratio, 0.41; 95% CI, 0.16– 1.05). ZNF639 knockdown increased clonogenicity, cell motility, and lung metastasis in NOD/ SCID mice. Following the ZNF639 knockdown, the expression of Snail1, vimentin, and C-C chemokine ligand 20 (CCL20) was upregulated, and the changes in cell phenotype mediated by ZNF639 were reversed by the subsequent knockdown of CCL20. Conclusion Low ZNF639 expression is a novel prognostic factor for recurrence-free survival in patients with breast cancer.

Purpose: Zinc finger protein 639 (ZNF639) is often found within the overlapping amplicon of PIK3CA, and previous studies suggest its involvement in the pathogenesis of esophageal and oral squamous cell carcinomas. However, its expression and significance in breast cancer remain uncharacterized. Methods: Immunohistochemical analysis of ZNF639 was performed using tissue microarrays.Functional studies, including colony formation, Transwell cell migration, and in vivo metastasis, were conducted on breast tumor cells with ZNF639 knockdown via small interfering RNA transfection. Results: Reduced ZNF639 immunoreactivity was observed in 82% of the breast cancer samples, independent of hormone receptor and human epidermal growth factor receptor 2 status. In multivariate Cox regression analyses, ZNF639 expression was associated with favorable survival outcomes, including recurrence-free survival (hazard ratio, 0.35; 95% confidence interval [CI], 0.14–0.89) and overall survival (hazard ratio, 0.41; 95% CI, 0.16– 1.05). ZNF639 knockdown increased clonogenicity, cell motility, and lung metastasis in NOD/ SCID mice. Following the ZNF639 knockdown, the expression of Snail1, vimentin, and C-C chemokine ligand 20 (CCL20) was upregulated, and the changes in cell phenotype mediated by ZNF639 were reversed by the subsequent knockdown of CCL20. Conclusion Low ZNF639 expression is a novel prognostic factor for recurrence-free survival in patients with breast cancer.

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.

Purpose: Zinc finger protein 639 (ZNF639) is often found within the overlapping amplicon of PIK3CA, and previous studies suggest its involvement in the pathogenesis of esophageal and oral squamous cell carcinomas. However, its expression and significance in breast cancer remain uncharacterized. Methods: Immunohistochemical analysis of ZNF639 was performed using tissue microarrays.Functional studies, including colony formation, Transwell cell migration, and in vivo metastasis, were conducted on breast tumor cells with ZNF639 knockdown via small interfering RNA transfection. Results: Reduced ZNF639 immunoreactivity was observed in 82% of the breast cancer samples, independent of hormone receptor and human epidermal growth factor receptor 2 status. In multivariate Cox regression analyses, ZNF639 expression was associated with favorable survival outcomes, including recurrence-free survival (hazard ratio, 0.35; 95% confidence interval [CI], 0.14–0.89) and overall survival (hazard ratio, 0.41; 95% CI, 0.16– 1.05). ZNF639 knockdown increased clonogenicity, cell motility, and lung metastasis in NOD/ SCID mice. Following the ZNF639 knockdown, the expression of Snail1, vimentin, and C-C chemokine ligand 20 (CCL20) was upregulated, and the changes in cell phenotype mediated by ZNF639 were reversed by the subsequent knockdown of CCL20. Conclusion Low ZNF639 expression is a novel prognostic factor for recurrence-free survival in patients with breast cancer.

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.

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.

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.

INTRODUCTION: Acute severe ulcerative colitis (ASUC) is a significant cause of disease morbidity. One-third of patients with ASUC are steroid refractory. Rescue therapy may not successfully induce remission, necessitating colectomy. We aimed to identify predictors of rescue therapy and colectomy in ASUC assessed within 24 h of admission for early risk stratification. METHODS: We conducted a retrospective cohort study of 58 admissions for ASUC among 47 patients from August 2002 to January 2022. Serum biomarkers assessed were measured on admission. Primary outcomes were the need for rescue therapy during the same admission and colectomy within 1 year of admission. RESULTS: Rescue therapy (all with infliximab) was given in 20 (34.5%) of the admissions. Colectomy was done within 1 year for nine (15.5%) of the admissions. An elevated C-reactive protein (CRP) of >30 mg/L (relative risk [RR] 1.63), a CRP-albumin ratio of >0.85 (RR 1.63), and a composite factor of both CRP > 30 mg/L and age ≥60 years (RR 2.37) were significantly associated with the need for rescue therapy. Hypoalbuminaemia ≤ 25 g/L (RR 4.35) and the use of biologics at presentation (RR 1.54) were significantly associated with colectomy within 1 year of admission, while a CRP of ≥ 80 mg/L was a significant protective factor (RR 0.70). CONCLUSION Patients with ASUC who have elevated CRP or CRP-albumin ratio on admission should be considered at risk for steroid-refractory disease. Those with hypoalbuminaemia on admission and using biologics at presentation are more likely to require colectomy in the first year after admission for ASUC.
Humans ; Colitis, Ulcerative/therapy* ; Colectomy ; Retrospective Studies ; Male ; Female ; Middle Aged ; Adult ; C-Reactive Protein/metabolism* ; Infliximab/therapeutic use* ; Biomarkers/blood* ; Acute Disease ; Aged ; Severity of Illness Index ; Treatment Outcome

OBJECTIVE: Based on the PTEN-induced hypothetical kinase 1 (PINK1)/Parkin pathway, the effect of acupuncture pretreatment on the expression of mitochondrial autophagy-related proteins in gastrocnemius muscle tissue of rats with exercise-induced muscle damage (EIMD) was observed, and the underlying mechanism of acupuncture pretreatment for the prevention and treatment of EIMD was explored. METHODS: Of 88 SD male rats, aged 6 weeks, 8 rats were randomly selected as a blank group, and the remaining 80 rats were randomized into a model group and an acupuncture pretreatment group, with 40 rats in each group. Either the model group or the acupuncture pretreatment group was subdivided randomly into 5 subgroups with 8 rats in each one according to the time points of sample collection, 0 h, 12 h, 24 h, 48 h and 72 h after modeling. An intermittent downhill running centrifugal exercise was carried out on an animal experimental treadmill to establish the EIMD model in the model group and the acupuncture pretreatment group. The rats in the acupuncture pretreatment group received acupuncture at "Guanyuan" (CV6) and bilateral "Zusanli" (ST36), once a day for 20 min each time, for 7 consecutive days before EIMD model preparation. Transmission electron microscopy was used to observe the ultrastructure of gastrocnemius muscle tissue in each group. The contents of malondialdehyde (MDA), superoxide dismutase (SOD) and catalase (CAT) in serum were detected by ELISA. Western blot was used to detect the protein expression of PINK1, Parkin, sequestosome 1 (p62) and microtubule-associated protein light chain 3B (LC3B) in rat gastrocnemius muscle tissue. Real-time PCR was adopted to detect the mRNA expression of PINK1, Parkin, p62 and LC3B in rat gastrocnemius muscle tissue. RESULTS: Compared with the blank group, the mitochondria of gastrocnemius muscles showed obvious swelling in the 0 h, 12 h, 24 h, and 48 h model subgroups , autophagosomes were formed in the 12 h and 24 h model subgroups, and the mitochondrial morphology returned to normal gradually in the 72 h model subgroup. The serum MDA contents of rats in 5 model subgroups increased (P<0.01, P<0.05). The contents of SOD and CAT in the subgroups of 0 h, 12 h, 24 h and 48 h decreased (P<0.05, P<0.01). The protein and mRNA expression levels of PINK1, Parkin and LC3B in gastrocnemius muscle tissue of rats in 0 h, 12 h and 24 h subgroups were elevated (P<0.01); and the protein and mRNA expression levels of p62 in the 0 h, 12 h, 24 h and 48 h subgroups were reduced (P<0.01, P<0.05). Compared with the model subgroup at the same time point, the myofibril damage and the degree of mitochondrial swelling were mild in each acupuncture pretreatment subgroup, and the numbers of autophagosomes were fewer. The contents of MDA in the acupuncture pretreatment subgroups decreased at 0 h, 12 h, 24 h, and 48 h (P<0.05, P<0.01). The contents of SOD and CAT in the 12 h acupuncture pretreatment subgroup increased (P<0.05, P<0.01). The protein and mRNA expression levels of PINK1 and Parkin in the 0 h, 12 h, and 24 h acupuncture pretreatment subgroups decreased (P<0.01, P<0.05). The protein and mRNA expression levels of LC3B in the 12 h acupuncture pretreatment subgroup decreased (P<0.01), and that of p62 in the 0 h and 24 h acupuncture pretreatment subgroups increased (P<0.01, P<0.05). CONCLUSION The intermittent downhill running centrifugal exercise induces the excessive mitochondrial autophagy. Acupuncture pretreatment may attenuate EIMD, and the underlying mechanism is related to the regulation of PINK1/Parkin signaling pathway expression, reducing oxidative stress damage in skeletal muscle cells, and inhibiting mitochondrial autophagy overactivation.
Animals ; Ubiquitin-Protein Ligases/genetics* ; Male ; Rats ; Acupuncture Therapy ; Protein Kinases/genetics* ; Rats, Sprague-Dawley ; Mitophagy ; Humans ; Muscle, Skeletal/metabolism* ; Physical Conditioning, Animal ; Muscular Diseases/physiopathology* ; Signal Transduction