| 1. |
|
|
| 2. |
- El-Schich, Zahra, et al.
(författare)
-
Discrimination between Breast Cancer Cells and White Blood Cells by Non-Invasive Measurements : Implications for a Novel In Vitro-Based Circulating Tumor Cell Model Using Digital Holographic Cytometry
- 2020
-
Ingår i: Applied Sciences. - : MDPI. - 2076-3417. ; 10:14
-
Tidskriftsartikel (refereegranskat)abstract
- Breast cancer is the second most common cancer worldwide. Metastasis is the main reason for death in breast cancer, and today, there is a lack of methods to detect and isolate circulating tumor cells (CTCs), mainly due to their heterogeneity and rarity. There are some systems that are designed to detect rare epithelial cancer cells in whole blood based on the most common marker used today, the epithelial cell adhesion molecule (EpCAM). It has been shown that aggressive breast cancer metastases are of non-epithelial origin and are therefore not always detected using EpCAM as a marker. In the present study, we used an in vitro-based circulating tumor cell model comprising a collection of six breast cancer cell lines and white blood cell lines. We used digital holographic cytometry (DHC) to characterize and distinguish between the different cell types by area, volume and thickness. Here, we present significant differences in cell size-related parameters observed when comparing white blood cells and breast cancer cells by using DHC. In conclusion, DHC can be a powerful diagnostic tool for the characterization of CTCs in the blood.
|
|
| 3. |
- El-Schich, Zahra, et al.
(författare)
-
Sialic acid as a biomarker studied in breast cancer cell lines in vitro using fluorescent molecularly imprinted polymers
- 2021
-
Ingår i: Applied Sciences. - : MDPI. - 2076-3417. ; 11:7
-
Tidskriftsartikel (refereegranskat)abstract
- Sialylations are post-translational modifications of proteins and lipids that play important roles in many cellular events, including cell-cell interactions, proliferation, and migration. Tumor cells express high levels of sialic acid (SA), which are often associated with the increased invasive potential in clinical tumors, correlating with poor prognosis. To overcome the lack of natural SA-receptors, such as antibodies and lectins with high enough specificity and sensitivity, we have used molecularly imprinted polymers (MIPs), or “plastic antibodies”, as nanoprobes. Because high expression of epithelial cell adhesion molecule (EpCAM) in primary tumors is often associated with proliferation and a more aggressive phenotype, the expression of EpCAM and CD44 was initially analyzed. The SA-MIPs were used for the detection of SA on the cell surface of breast cancer cells. Lectins that specifically bind to the a-2,3 SA and a-2,6 SA variants were used for analysis of SA expression, with both flow cytometry and confocal microscopy. Here we show a correlation of EpCAM and SA expression when using the SA-MIPs for detection of SA. We also demonstrate the binding pattern of the SA-MIPs on the breast cancer cell lines using confocal microscopy. Pre-incubation of the SA-MIPs with SA-derivatives as inhibitors could reduce the binding of the SA-MIPs to the tumor cells, indicating the specificity of the SA-MIPs. In conclusion, the SA-MIPs may be a new powerful tool in the diagnostic analysis of breast cancer cells.
|
|
| 4. |
|
|
| 5. |
- Guo, Jinan, et al.
(författare)
-
A non-invasive 25-Gene PLNM-Score urine test for detection of prostate cancer pelvic lymph node metastasis
- 2024
-
Ingår i: Prostate Cancer and Prostatic Diseases. - : Nature Publishing Group. - 1365-7852 .- 1476-5608.
-
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.
|
|
| 6. |
- Guo, Jinan, et al.
(författare)
-
Non-invasive Urine Test for Molecular Classification of Clinical Significance in Newly Diagnosed Prostate Cancer Patients
- 2021
-
Ingår i: Frontiers in Medicine. - : Frontiers Media S.A.. - 2296-858X. ; 8
-
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.
|
|
| 7. |
- Johnson, Heather, et al.
(författare)
-
Development and validation of a 25-Gene Panel urine test for prostate cancer diagnosis and potential treatment follow-up
- 2020
-
Ingår i: BMC Medicine. - : BioMed Central. - 1741-7015. ; 18
-
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.
|
|
| 8. |
- Kopparapu, Pradeep Kumar, et al.
(författare)
-
Expression and localization of serotonin receptors in human breast cancer
- 2013
-
Ingår i: Anticancer Research. - : International Institute of Anticancer Research. - 0250-7005 .- 1791-7530. ; 33:2, s. 363-370
-
Tidskriftsartikel (refereegranskat)abstract
- The aim of this study was to examine the expression of serotonin receptors in patients with breast cancer and to explore their utility as diagnostic and prognostic markers. Immunohistochemical analysis was performed to examine the expression of serotonin (5-HT) receptor subtypes 1A, 1B, 2B and 4 in a tissue microarray containing tumor specimens from 102 patients. Statistical analysis was performed to correlate the expression of these proteins with regard to clinical parameters. We found that all four serotonin receptors (5-HTRs) exhibited different expression patterns in breast cancer specimens. In general strong staining for 5-HTR1A was observed on the membrane of cancer cells but it was detected only in the cytoplasm of non-malignant cells. 5-HTR1B and 5-HTR2B were predominantly expressed in the cytoplasm of breast cancer cells, while 5-HTR4 was exclusively found in the nucleus of malignant and non-malignant cells. Correlation analysis revealed a significant correlation of 5-HTR2B with estrogen receptor-α (ER-α) and 5-HTR4 with ER-α and progesterone (PR). In conclusion, the different expression patterns and subcellular localization of 5-HTRs in breast cancer may reflect their role in breast cancer progression.
|
|
| 9. |
- Larsson, Per, et al.
(författare)
-
The functional interlink between AR and MMP9/VEGF signaling axis is mediated through PIP5K1α/pAKT in prostate cancer
- 2020
-
Ingår i: International Journal of Cancer. - : Wiley. - 0020-7136 .- 1097-0215. ; 146:6, s. 1686-1699
-
Tidskriftsartikel (refereegranskat)abstract
- Currently, no effective targeted therapeutics exists for treatment of metastatic prostate cancer (PCa). Given that matrix metalloproteinases 9 (MMP9) and its associated vascular endothelial growth factor (VEGF) are critical for tumor vascularization and invasion under castration-resistant condition, it is therefore of great importance to define the functional association and interplay between androgen receptor (AR) and MMP9 and their associated key survival and invasion pathways in PCa cells. Here, we found that there was a significant correlation between MMP9 and AR protein expression in primary and metastatic PCa tissues, and a trend that high level of MMP9 expression was associated with poor prognosis. We demonstrated that constitutive activation of AR increased expression of MMP9 and VEGF/VEGF receptors. We further showed that AR exerts its effect on MMP9/VEGF signaling axis through PIP5K1α/AKT. We showed that MMP9 physically interacted with PIP5K1α via formation of protein–protein complexes. Furthermore, elevated expression of MMP9 enhanced ability of AR to activate its target gene cyclin A1. The elevated sequential activation of AR/PIP5K1α/AKT/MMP9/VEGF signaling axis contributed to increased invasiveness and growth of metastatic tumors. Conversely, treatment with PIP5K1α inhibitor significantly suppressed invasiveness of PCa cells expressing constitutively activated AR, this was coincident with its inhibitory effect of this inhibitor on AR/MMP9/VEGF pathways. Our results suggest that AR and MMP9-associated network proteins may be effectively targeted by blocking PIP5K1α/AKT pathways using PIP5K1α inhibitor in metastatic PCa.
|
|
| 10. |
- Sarwar, Martuza, et al.
(författare)
-
Targeted suppression of AR-V7 using PIP5K1 alpha inhibitor overcomes enzalutamide resistance in prostate cancer cells
- 2016
-
Ingår i: Oncotarget. - : Impact Journals, LLC. - 1949-2553. ; 7:39, s. 63065-63081
-
Tidskriftsartikel (refereegranskat)abstract
- One mechanism of resistance of prostate cancer (PCa) to enzalutamide (MDV3100) treatment is the increased expression of AR variants lacking the ligand binding-domain, the best characterized of which is AR-V7. We have previously reported that Phosphatidylinositol-4-phosphate 5-kinase alpha (PIP5K alpha), is a lipid kinase that links to CDK1 and AR pathways. The discovery of PIP5K alpha inhibitor highlight the potential of PIP5K1 alpha as a drug target in PCa. In this study, we show that AR-V7 expression positively correlates with PIP5K1 alpha in tumor specimens from PCa patients. Overexpression of AR-V7 increases PIP5K1 alpha, promotes rapid growth of PCa in xenograft mice, whereas inhibition of PIP5K1 alpha by its inhibitor ISA-2011B suppresses the growth and invasiveness of xenograft tumors overexpressing AR-V7. PIP5K1 alpha is a key co-factor for both AR-V7 and AR, which are present as protein-protein complexes predominantly in the nucleus of PCa cells. In addition, PIP5K1 alpha and CDK1 influence AR-V7 expression also through AKT-associated mechanism dependent on PTEN-status. ISA-2011B disrupts protein stabilization of AR-V7 which is dependent on PIP5K1 alpha, leading to suppression of invasive growth of AR-V7-high tumors in xenograft mice. Our study suggests that combination of enzalutamide and PIP5K1 alpha may have a significant impact on refining therapeutic strategies to circumvent resistance to antiandrogen therapies.
|
|
