| 1. |
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| 2. |
- Guo, Jinan, et al.
(författare)
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A non-invasive 25-Gene PLNM-Score urine test for detection of prostate cancer pelvic lymph node metastasis
- 2024
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Ingår i: Prostate Cancer and Prostatic Diseases. - : Nature Publishing Group. - 1365-7852 .- 1476-5608.
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Tidskriftsartikel (refereegranskat)abstract
- Background: Prostate cancer patients with pelvic lymph node metastasis (PLNM) have poor prognosis. Based on EAU guidelines, patients with >5% risk of PLNM by nomograms often receive pelvic lymph node dissection (PLND) during prostatectomy. However, nomograms have limited accuracy, so large numbers of false positive patients receive unnecessary surgery with potentially serious side effects. It is important to accurately identify PLNM, yet current tests, including imaging tools are inaccurate. Therefore, we intended to develop a gene expression-based algorithm for detecting PLNM. Methods: An advanced random forest machine learning algorithm screening was conducted to develop a classifier for identifying PLNM using urine samples collected from a multi-center retrospective cohort (n = 413) as training set and validated in an independent multi-center prospective cohort (n = 243). Univariate and multivariate discriminant analyses were performed to measure the ability of the algorithm classifier to detect PLNM and compare it with the Memorial Sloan Kettering Cancer Center (MSKCC) nomogram score. Results: An algorithm named 25 G PLNM-Score was developed and found to accurately distinguish PLNM and non-PLNM with AUC of 0.93 (95% CI: 0.85-1.01) and 0.93 (95% CI: 0.87-0.99) in the retrospective and prospective urine cohorts respectively. Kaplan-Meier plots showed large and significant difference in biochemical recurrence-free survival and distant metastasis-free survival in the patients stratified by the 25 G PLNM-Score (log rank P < 0.001 and P < 0.0001, respectively). It spared 96% and 80% of unnecessary PLND with only 0.51% and 1% of PLNM missing in the retrospective and prospective cohorts respectively. In contrast, the MSKCC score only spared 15% of PLND with 0% of PLNM missing. Conclusions: The novel 25 G PLNM-Score is the first highly accurate and non-invasive machine learning algorithm-based urine test to identify PLNM before PLND, with potential clinical benefits of avoiding unnecessary PLND and improving treatment decision-making.
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| 3. |
- Guo, Jinan, et al.
(författare)
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A panel of biomarkers for diagnosis of prostate cancer using urine samples
- 2018
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Ingår i: Anticancer research. - : Anticancer Research USA Inc.. - 0250-7005 .- 1791-7530. ; 38:3, s. 1471-1477
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Tidskriftsartikel (refereegranskat)abstract
- Background/Aim: Prostate cancer (PCa) diagnosis using patient urine samples represents a non-invasive and more convenient method than the conventional biopsy and prostate-specific antigen (PSA) test. This study intended to identify a biomarker panel to distinguish PCa from benign prostate using urine samples. Materials and Methods: We identified six biomarkers with differential gene expression in 154 PCa and benign prostate specimens. We then determined mRNA expression signature and the diagnostic performance of the 6-biomarker panel in 156 urine samples from patients with PCa and benign disease. Results: The 6-biomarker panel distinguished PCa from benign prostate cases with sensitivity of 80.6%, specificity of 62.9% and area under the curve (AUC) of 0.803 (p<0.0001), whereas serum PSA at 4 ng/ml cutoff had sensitivity of 95.5%, specificity of 20.2% and AUC of 0.521 (p<0.0001). Conclusion: The 6-biomarker panel for use in urine samples was able to distinguish PCa from benign prostate with higher specificity and accuracy than PSA and may be useful in clinical settings.
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| 4. |
- Guo, Jinan, et al.
(författare)
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Establishing a Urine-Based Biomarker Assay for Prostate Cancer Risk Stratification
- 2020
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Ingår i: Frontiers in Cell and Developmental Biology. - Swiss : Frontiers Media S.A.. - 2296-634X. ; 8
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Tidskriftsartikel (refereegranskat)abstract
- One of the major features of prostate cancer (PCa) is its heterogeneity, which often leads to uncertainty in cancer diagnostics and unnecessary biopsies as well as overtreatment of the disease. Novel non-invasive tests using multiple biomarkers that can identify clinically high-risk cancer patients for immediate treatment and monitor patients with low-risk cancer for active surveillance are urgently needed to improve treatment decision and cancer management. In this study, we identified 14 promising biomarkers associated with PCa and tested the performance of these biomarkers on tissue specimens and pre-biopsy urinary sediments. These biomarkers showed differential gene expression in higher- and lower-risk PCa. The 14-Gene Panel urine test (PMP22, GOLM1, LMTK2, EZH2, GSTP1, PCA3, VEGFA, CST3, PTEN, PIP5K1A, CDK1, TMPRSS2, ANXA3, and CCND1) was assessed in two independent prospective and retrospective urine study cohorts and showed high diagnostic accuracy to identify higher-risk PCa patients with the need for treatment and lower-risk patients for surveillance. The AUC was 0.897 (95% CI 0.939–0.855) in the prospective cohort (n = 202), and AUC was 0.899 (95% CI 0.964–0.834) in the retrospective cohort (n = 97). In contrast, serum PSA and Gleason score had much lower accuracy in the same 202 patient cohorts [AUC was 0.821 (95% CI 0.879–0.763) for PSA and 0.860 (95% CI 0.910–0.810) for Gleason score]. In addition, the 14-Gene Panel was more accurate at risk stratification in a subgroup of patients with Gleason scores 6 and 7 in the prospective cohort (n = 132) with AUC of 0.923 (95% CI 0.968–0.878) than PSA [AUC of 0.773 (95% CI 0.852–0.794)] and Gleason score [AUC of 0.776 (95% CI 0.854–0.698)]. Furthermore, the 14-Gene Panel was found to be able to accurately distinguish PCa from benign prostate with AUC of 0.854 (95% CI 0.892–0.816) in a prospective urine study cohort (n = 393), while PSA had lower accuracy with AUC of 0.652 (95% CI 0.706–0.598). Taken together, the 14-Gene Panel urine test represents a promising non-invasive tool for detection of higher-risk PCa to aid treatment decision and lower-risk PCa for active surveillance.
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| 5. |
- Guo, Jinan, et al.
(författare)
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Non-invasive Urine Test for Molecular Classification of Clinical Significance in Newly Diagnosed Prostate Cancer Patients
- 2021
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Ingår i: Frontiers in Medicine. - : Frontiers Media S.A.. - 2296-858X. ; 8
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Tidskriftsartikel (refereegranskat)abstract
- Objective: To avoid over-treatment of low-risk prostate cancer patients, it is important to identify clinically significant and insignificant cancer for treatment decision-making. However, no accurate test is currently available.Methods: To address this unmet medical need, we developed a novel gene classifier to distinguish clinically significant and insignificant cancer, which were classified based on the National Comprehensive Cancer Network risk stratification guidelines. A non-invasive urine test was developed using quantitative mRNA expression data of 24 genes in the classifier with an algorithm to stratify the clinical significance of the cancer. Two independent, multicenter, retrospective and prospective studies were conducted to assess the diagnostic performance of the 24-Gene Classifier and the current clinicopathological measures by univariate and multivariate logistic regression and discriminant analysis. In addition, assessments were performed in various Gleason grades/ISUP Grade Groups.Results: The results showed high diagnostic accuracy of the 24-Gene Classifier with an AUC of 0.917 (95% CI 0.892-0.942) in the retrospective cohort (n = 520), AUC of 0.959 (95% CI 0.935-0.983) in the prospective cohort (n = 207), and AUC of 0.930 (95% 0.912-CI 0.947) in the combination cohort (n = 727). Univariate and multivariate analysis showed that the 24-Gene Classifier was more accurate than cancer stage, Gleason score, and PSA, especially in the low/intermediate-grade/ISUP Grade Group 1-3 cancer subgroups.Conclusions: The 24-Gene Classifier urine test is an accurate and non-invasive liquid biopsy method for identifying clinically significant prostate cancer in newly diagnosed cancer patients. It has the potential to improve prostate cancer treatment decisions and active surveillance.
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| 6. |
- Guo, Min, et al.
(författare)
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SFRP2 induces a mesenchymal subtype transition by suppression of SOX2 in glioblastoma
- 2021
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Ingår i: Oncogene. - : Springer Nature. - 0950-9232 .- 1476-5594. ; 40:32, s. 5066-5080
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Tidskriftsartikel (refereegranskat)abstract
- Intratumoral heterogeneity is a characteristic of glioblastomas that contain an intermixture of cell populations displaying different glioblastoma subtype gene expression signatures. Proportions of these populations change during tumor evolution, but the occurrence and regulation of glioblastoma subtype transition is not well described. To identify regulators of glioblastoma subtypes we utilized a combination of in vitro experiments and in silico analyses, using experimentally generated as well as publicly available data. Through this combined approach SOX2 was identified to confer a proneural glioblastoma subtype gene expression signature. SFRP2 was subsequently identified as a SOX2-antagonist, able to induce a mesenchymal glioblastoma subtype signature. A subset of patient glioblastoma samples with high SFRP2 and low SOX2 expression was particularly enriched with mesenchymal subtype samples. Phenotypically, SFRP2 decreased tumor sphere formation, stemness as assessed by limiting dilution assay, and overall cell proliferation but increased cell motility, whereas SOX2 induced the opposite effects. Furthermore, an SFRP2/non-canonical-WNT/KLF4/PDGFR/phospho-AKT/SOX2 signaling axis was found to be involved in the mesenchymal transition. Analysis of human tumor tissue spatial gene expression patterns showed distinct expression of SFRP2- and SOX2-correlated genes in vascular and cellular areas, respectively. Finally, conditioned media from SFRP2 overexpressing cells increased CD206 on macrophages. Together, these findings present SFRP2 as a SOX2-antagonist with the capacity to induce a mesenchymal subtype transition in glioma cells located in vascular tumor areas, highlighting its role in glioblastoma tumor evolution and intratumoral heterogeneity.
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| 7. |
- Guo, Yongzhi, et al.
(författare)
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Beneficial and detrimental effects of plasmin(ogen) during infection and sepsis in mice
- 2011
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Ingår i: PLOS ONE. - : Public Library of Science. - 1932-6203. ; 6:9
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Tidskriftsartikel (refereegranskat)abstract
- Plasmin has been proposed to be an important mediator during inflammation/infection. In this study, by using mice lacking genes for plasminogen, tissue-type plasminogen activator (tPA), and urokinase-type PA (uPA), we have investigated the functional roles of active plasmin in infection and sepsis. Two models were used: an infection model by intravenous injection of 1x10(7) CFU of S. aureus, and a sepsis model by intravenous injection of 1.6x10(8) CFU of S. aureus. We found that in the infection model, wild-type (WT) mice showed significantly higher survival rates than plasminogen-deficient (plg(-/-)) mice. However, in the sepsis model, plg(-/-) or tPA(-/-)/uPA(-/-) mice showed the highest survival rate whereas WT and tPA(+/-)/uPA(+/-) mice showed the lowest survival rate, and plg(+/-), tPA(-/-), and uPA(-/-) mice had an intermediate survival rate. These results indicate that the levels of active plasmin are critical in determining the survival rate in the sepsis, partly through high levels of inflammatory cytokines and enhanced STAT3 activation. We conclude that plasmin is beneficial in infection but promotes the production of inflammatory cytokines in sepsis that may cause tissue destruction, diminished neutrophil function, and an impaired capacity to kill bacteria which eventually causes death of these mice.
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| 8. |
- Guo, Yongzhi, et al.
(författare)
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Protective effects of plasmin(ogen) in a mouse model of Staphylococcus aureus-induced arthritis
- 2008
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Ingår i: Arthritis and rheumatism. - : Wiley. - 0004-3591 .- 1529-0131. ; 58:3, s. 764-772
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Tidskriftsartikel (refereegranskat)abstract
- Objective: To assess the functional roles of plasmin in a murine model of Staphylococcus aureus-induced bacterial arthritis. Methods: Bacterial arthritis was induced in plasminogen-deficient (Plg-/-) and wild-type (Plg+/+) littermates by local injection of 1 × 106 colony-forming units of S aureus into the knee joints. Human plasminogen was administered to Plg-/- mice on days 0-7 or days 7-14. Antibiotic treatment was administered to Plg-/- mice on days 7-14. Bacteria counts and histologic, immunohistochemical, and Western blot analyses were performed. Results: In Plg+/+ mice, S aureus counts had declined within 2 days, and by day 28 the bacteria had been completely eliminated. However, S aureus was still detectable in all injected joints from Plg-/- mice, and bacteria counts were 27 times higher than the amount injected on day 0. The extent of macrophage and neutrophil recruitment to the infected joints was comparable for Plg+/+ and Plg-/- mice on days 1, 7, and 14. The activation of these inflammatory cells appeared to be impaired in Plg-/- mice, however. Treatment of Plg-/- mice with antibiotic (cloxacillin) resulted in successful killing of the bacteria, but the necrotic tissue remained in the infected joints. When human plasminogen was given intravenously to Plg-/- mice daily for 7 days, bacterial clearance was greatly improved as compared with their untreated counterparts, and the amount of necrotic tissue in the joint cavity was dramatically reduced. The expression of interleukin 6 (IL-6) and IL-10 was higher in Plg+/+ mice than in Plg-/- mice during bacterial arthritis. Conclusion: Our findings indicate that plasmin plays a pluripotent role in protecting against S aureus-induced arthritis by activating inflammatory cells, killing bacteria, removing necrotic tissue, and enhancing cytokine expression.
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| 9. |
- Johnson, Heather, et al.
(författare)
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Development and validation of a 25-Gene Panel urine test for prostate cancer diagnosis and potential treatment follow-up
- 2020
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Ingår i: BMC Medicine. - : BioMed Central. - 1741-7015. ; 18
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Tidskriftsartikel (refereegranskat)abstract
- Background: Heterogeneity of prostate cancer (PCa) contributes to inaccurate cancer screening and diagnosis, unnecessary biopsies, and overtreatment. We intended to develop non-invasive urine tests for accurate PCa diagnosis to avoid unnecessary biopsies. Methods: Using a machine learning program, we identified a 25-Gene Panel classifier for distinguishing PCa and benign prostate. A non-invasive test using pre-biopsy urine samples collected without digital rectal examination (DRE) was used to measure gene expression of the panel using cDNA preamplification followed by real-time qRTPCR. The 25-Gene Panel urine test was validated in independent multi-center retrospective and prospective studies. The diagnostic performance of the test was assessed against the pathological diagnosis from biopsy by discriminant analysis. Uni- and multivariate logistic regression analysis was performed to assess its diagnostic improvement over PSA and risk factors. In addition, the 25-Gene Panel urine test was used to identify clinically significant PCa. Furthermore, the 25-Gene Panel urine test was assessed in a subset of patients to examine if cancer was detected after prostatectomy. Results: The 25-Gene Panel urine test accurately detected cancer and benign prostate with AUC of 0.946 (95% CI 0.963–0.929) in the retrospective cohort (n = 614), AUC of 0.901 (0.929–0.873) in the prospective cohort (n = 396), and AUC of 0.936 (0.956–0.916) in the large combination cohort (n = 1010). It greatly improved diagnostic accuracy over PSA and risk factors (p < 0.0001). When it was combined with PSA, the AUC increased to 0.961 (0.980–0.942). Importantly, the 25-Gene Panel urine test was able to accurately identify clinically significant and insignificant PCa with AUC of 0.928 (95% CI 0.947–0.909) in the combination cohort (n = 727). In addition, it was able to show the absence of cancer after prostatectomy with high accuracy. Conclusions: The 25-Gene Panel urine test is the first highly accurate and non-invasive liquid biopsy method without DRE for PCa diagnosis. In clinical practice, it may be used for identifying patients in need of biopsy for cancer diagnosis and patients with clinically significant cancer for immediate treatment, and potentially assisting cancer treatment follow-up.
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| 10. |
- Li, Jinan, et al.
(författare)
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Contrasting roles of plasminogen deficiency in different rheumatoid arthritis models.
- 2005
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Ingår i: Arthritis and Rheumatism. - : Wiley. - 0004-3591 .- 1529-0131. ; 52:8, s. 2541-2548
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE: To investigate the contrasting roles of plasminogen deficiency between models of collagen-induced arthritis (CIA) and antigen-induced arthritis (AIA). METHODS: We developed a new animal model of arthritis, which we have called local injection-induced arthritis (LIA). In this model, we replaced methylated bovine serum albumin, which is normally used as an immunogen and is injected intraarticularly into the knee joint, with type II collagen (CII) to induce AIA. The severity of CIA, LIA, and AIA in wild-type and plasminogen-deficient mice was evaluated by clinical scoring or histologic grading. Necrosis was determined by histology and immunohistochemistry. RESULTS: After CII immunization alone, wild-type mice developed arthritis in most of the paws as well as in the knee joints, whereas plasminogen-deficient mice were totally resistant to the disease. Local knee injections of CII or saline slightly enhanced the severity of the knee arthritis in wild-type mice during a 60-day experimental period. Unexpectedly, the plasminogen-deficient mice also developed arthritis in joints that were injected with CII or saline. However, the arthritis was milder than that in their wild-type littermates. Sustained tissue necrosis was found only in the plasminogen-deficient mice after the local injection. CONCLUSION: Our data show that both the antigen and the joint trauma caused by the local injection are critical to explaining the contrasting roles of plasminogen deficiency in CIA and AIA. This further indicates that CIA and AIA have distinct pathogenic mechanisms. The data also suggest that plasmin may be required for the induction of these arthritis models that are critically dependent on complement activation.
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