| 1. |
- Arvidsson, Ida, et al.
(författare)
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Domain-adversarial neural network for improved generalization performance of gleason grade classification
- 2020
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Ingår i: Medical Imaging 2020 : Digital Pathology - Digital Pathology. - : SPIE. - 1605-7422. - 9781510634077 ; 11320
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Konferensbidrag (refereegranskat)abstract
- When training a deep learning model, the dataset used is of great importance to make sure that the model learns relevant features of the data and that it will be able to generalize to new data. However, it is typically difficult to produce a dataset without some bias toward any specific feature. Deep learning models used in histopathology have a tendency to overfit to the stain appearance of the training data - if the model is trained on data from one lab only, it will usually not be able to generalize to data from other labs. The standard technique to overcome this problem is to use color augmentation of the training data which, artificially, generates more variations for the network to learn. In this work we instead test the use of a so called domain-adversarial neural network, which is designed to prevent the model from being biased towards features that in reality are irrelevant such as the origin of an image. To test the technique, four datasets from different hospitals for Gleason grading of prostate cancer are used. We achieve state of the art results for these particular datasets, and furthermore for two of our three test datasets the approach outperforms the use of color augmentation.
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| 2. |
- Arvidsson, Ida, et al.
(författare)
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Generalization of prostate cancer classification for multiple sites using deep learning
- 2018
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Ingår i: 2018 IEEE 15th International Symposium on Biomedical Imaging, ISBI 2018. - 9781538636367 ; 2018-April, s. 191-194
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Konferensbidrag (refereegranskat)abstract
- Deep learning has the potential to drastically increase the accuracy and efficiency of prostate cancer diagnosis, which would be of uttermost use. Today the diagnosis is determined manually from H&E stained specimens using a light microscope. In this paper several different approaches based on convolutional neural networks for prostate cancer classification are presented and compared, using three different datasets with different origins. The issue that algorithms trained on a certain site might not generalize to other sites, due to for example inevitable stain variations, is highlighted. Two different techniques to overcome this complication are compared; by training the networks using color augmentation and by using digital stain separation. Furthermore, the potential of using an autoencoder to get a more efficient downsampling is investigated, which turned out to be the method giving the best generalization. We achieve accuracies of 95% for classification of benign versus malignant tissue and 81% for Gleason grading for data from the same site as the training data. The corresponding accuracies for images from other sites are in average 88% and 52% respectively.
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| 3. |
- Canesin, Giacomo, et al.
(författare)
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Cytokines and Janus kinase/signal transducer and activator of transcription signaling in prostate cancer : overview and therapeutic opportunities
- 2020
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Ingår i: Current Opinion in Endocrine and Metabolic Research. - : Elsevier BV. - 2451-9650. ; 10, s. 36-42
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Forskningsöversikt (refereegranskat)abstract
- The Janus kinase (JAK)/signal transducer and activator of transcription (STAT) pathway was originally identified as a key cellular mechanism mediating the action of cytokines, interferons, and growth factors for the control of gene expression. Extracellular signals mediated by cytokines are thus transduced through this pathway into transcriptional programs that regulate cell growth, differentiation, proliferation, invasion, survival, and inflammation. In prostate cancer, an aberrant or persistent activation of the JAK/STAT signaling is related to tumor growth and disease progression, making this pathway an ideal therapeutic target. Here, we review the most recent literature on this topic, and we summarize the latest advances and future challenges in therapeutically targeting the JAK/STAT pathway in prostate cancer.
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| 4. |
- Canesin, Giacomo, et al.
(författare)
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Scavenging of Labile Heme by Hemopexin Is a Key Checkpoint in Cancer Growth and Metastases
- 2020
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Ingår i: Cell Reports. - : Elsevier BV. - 2211-1247. ; 32:12
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Tidskriftsartikel (refereegranskat)abstract
- Canesin et al. describe a role and mechanism for labile heme as a key player in regulating gene expression to promote carcinogenesis via binding to G-quadruplex in the c-MYC promoter. Hemopexin, a heme scavenger, may be used as a strategy to block progression of cancer.
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| 5. |
- Canesin, Giacomo, et al.
(författare)
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The STAT3 Inhibitor Galiellalactone Effectively Reduces Tumor Growth and Metastatic Spread in an Orthotopic Xenograft Mouse Model of Prostate Cancer.
- 2016
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Ingår i: European Urology. - : Elsevier BV. - 1873-7560 .- 0302-2838. ; 69:3, s. 400-404
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Tidskriftsartikel (refereegranskat)abstract
- Signal transducer and activator of transcription 3 (STAT3) is known to be involved in the progression of prostate cancer (PCa) and is a key factor in drug resistance and tumor immunoescape. As a result, it represents a promising target for PCa therapy. We studied the effects of the STAT3 inhibitor galiellalactone (GL) on tumor growth and metastatic spread in vitro and in vivo. The effect of GL on cell viability, apoptosis, and invasion was studied in vitro using androgen-independent DU145 and DU145-Luc cell lines. For in vivo studies, mice were injected orthotopically with DU145-Luc cells and treated with daily intraperitoneal injections of GL for 6 wk. GL significantly reduced the growth of the primary tumor and the metastatic spread of PCa cells to regional and distal lymph nodes in vivo. Treatment with GL also resulted in decreased cell proliferation and increased apoptosis compared with controls. In vitro, GL reduces the viability and invasive abilities of DU145-Luc cells and induces apoptosis. Our results showed that tumor growth and early metastatic dissemination of PCa can be significantly reduced by GL, indicating its potential use as a therapeutic compound in advanced metastatic PCa.
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| 6. |
- Canesin, Giacomo, et al.
(författare)
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Treatment with the WNT5A-mimicking peptide Foxy-5 effectively reduces the metastatic spread of WNT5A-low prostate cancer cells in an orthotopic mouse model
- 2017
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 12:9
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Tidskriftsartikel (refereegranskat)abstract
- Prostate cancer patients with high WNT5A expression in their tumors have been shown to have more favorable prognosis than those with low WNT5A expression. This suggests that reconstitution of Wnt5a in low WNT5A-expressing tumors might be an attractive therapeutic approach. To explore this idea, we have in the present study used Foxy-5, a WNT5A mimicking peptide, to investigate its impact on primary tumor and metastasis in vivo and on prostate cancer cell viability, apoptosis and invasion in vitro. We used an in vivo orthotopic xenograft mouse model with metastatic luciferase-labeled WNT5A-low DU145 cells and metastatic luciferase-labeled WNT5A-high PC3prostate cancer cells. We provide here the first evidence that Foxy-5 significantly inhibits the initial metastatic dissemination of tumor cells to regional and distal lymph nodes by 90% and 75%, respectively. Importantly, this effect was seen only with the WNT5A-low DU145 cells and not with the WNT5A-high PC3 cells. The inhibiting effect in the DU145-based model occurred despite the fact that no effects were observed on primary tumor growth, apoptosis or proliferation. These findings are consistent with and supported by the in vitro data, where Foxy-5 specifically targets invasion without affecting apoptosis or viability of WNT5A-low prostate cancer cells. To conclude, our data indicate that the WNT5A-mimicking peptide Foxy-5, which has been recently used in a phase 1 clinical trial, is an attractive candidate for complimentary anti-metastatic treatment of prostate cancer patients with tumors exhibiting absent or low WNT5A expression.
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| 7. |
- Don-Doncow, Nicholas, et al.
(författare)
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Expression of STAT3 in Prostate Cancer Metastases
- 2017
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Ingår i: European Urology. - : Elsevier BV. - 0302-2838. ; 71:3, s. 313-316
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Tidskriftsartikel (refereegranskat)abstract
- STAT3 and its upstream activator IL6R have been implicated in the progression of prostate cancer and are possible future therapeutic targets. We analyzed 223 metastatic samples from rapid autopsies of 71 patients who had died of castration-resistant prostate cancer (CRPC) to study protein and gene expression of pSTAT3 and IL6R. Immunohistochemical analysis revealed that 95% of metastases were positive for pSTAT3 and IL6R, with varying expression levels. Bone metastases showed significantly higher expression of both pSTAT3 and IL6R in comparison to lymph node and visceral metastases. STAT3 mRNA levels were significantly higher in bone than in lymph node and visceral metastases, whereas no significant difference in IL6R mRNA expression was observed. Our study strongly supports the suggested view of targeting STAT3 as a therapeutic option in patients with metastatic CRPC. Patient summary We studied the levels of two proteins (pSTAT3 and IL6R) in metastases from patients who died from castration-resistant prostate cancer. We found high levels of pSTAT3and IL6R in bone metastases, suggesting that these proteins could be used as targets for new anticancer drugs.
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| 8. |
- Flores-Morales, Amilcar, et al.
(författare)
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Proteogenomic characterization of patient-derived xenografts highlights the role of REST in neuroendocrine differentiation of castration-resistant prostate cancer
- 2019
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Ingår i: Clinical Cancer Research. - 1078-0432. ; 25:2, s. 595-608
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: An increasing number of castration-resistant prostate cancer (CRPC) tumors exhibit neuroendocrine (NE) features. NE prostate cancer (NEPC) has poor prognosis, and its development is poorly understood. Experimental Design: We applied mass spectrometry–based proteomics to a unique set of 17 prostate cancer patient–derived xenografts (PDX) to characterize the effects of castration in vivo, and the proteome differences between NEPC and prostate adenocarcinomas. Genome-wide profiling of REST-occupied regions in prostate cancer cells was correlated to the expression changes in vivo to investigate the role of the transcriptional repressor REST in castration-induced NEPC differentiation. Results: An average of 4,881 proteins were identified and quantified from each PDX. Proteins related to neurogenesis, cell-cycle regulation, and DNA repair were found upregulated and elevated in NEPC, while the reduced levels of proteins involved in mitochondrial functions suggested a prevalent glycolytic metabolism of NEPC tumors. Integration of the REST chromatin bound regions with expression changes indicated a direct role of REST in regulating neuronal gene expression in prostate cancer cells. Mechanistically, depletion of REST led to cell-cycle arrest in G1, which could be rescued by p53 knockdown. Finally, the expression of the REST-regulated gene secretagogin (SCGN) correlated with an increased risk of suffering disease relapse after radical prostatectomy. Conclusions: This study presents the first deep characterization of the proteome of NEPC and suggests that concomitant inhibition of REST and the p53 pathway would promote NEPC. We also identify SCGN as a novel prognostic marker in prostate cancer.
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| 9. |
- Gummeson, Anna, et al.
(författare)
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Automatic Gleason grading of H&E stained microscopic prostate images using deep convolutional neural networks
- 2017
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Ingår i: Medical Imaging 2017: Digital Pathology. - : SPIE. - 9781510607255 ; 10140
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Konferensbidrag (refereegranskat)abstract
- Prostate cancer is the most diagnosed cancer in men. The diagnosis is confirmed by pathologists based on ocular inspection of prostate biopsies in order to classify them according to Gleason score. The main goal of this paper is to automate the classification using convolutional neural networks (CNNs). The introduction of CNNs has broadened the field of pattern recognition. It replaces the classical way of designing and extracting hand-made features used for classification with the substantially different strategy of letting the computer itself decide which features are of importance. For automated prostate cancer classification into the classes: Benign, Gleason grade 3, 4 and 5 we propose a CNN with small convolutional filters that has been trained from scratch using stochastic gradient descent with momentum. The input consists of microscopic images of haematoxylin and eosin stained tissue, the output is a coarse segmentation into regions of the four different classes. The dataset used consists of 213 images, each considered to be of one class only. Using four-fold cross-validation we obtained an error rate of 7.3%, which is significantly better than previous state of the art using the same dataset. Although the dataset was rather small, good results were obtained. From this we conclude that CNN is a promising method for this problem. Future work includes obtaining a larger dataset, which potentially could diminish the error margin.
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| 10. |
- Krzyzanowska, Agnieszka, et al.
(författare)
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Development, Validation, and Clinical Utility of a Six-gene Signature to Predict Aggressive Prostate Cancer
- 2023
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Ingår i: European Urology Focus. - 2405-4569. ; 9:6, s. 983-991
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Tidskriftsartikel (refereegranskat)abstract
- Background: Molecular signatures in prostate cancer (PCa) tissue can provide useful prognostic information to improve the understanding of a patient's risk of harbouring aggressive disease. Objective: To develop and validate a gene signature that adds independent prognostic information to clinical parameters for better treatment decisions and patient management. Design, setting, and participants: Expression of 14 genes was evaluated in radical prostatectomy (RP) tissue from an Irish cohort of PCa patients (n = 426). A six-gene molecular risk score (MRS) was identified with strong prognostic performance to predict adverse pathology (AP) at RP or biochemical recurrence (BCR). The MRS was combined with the Cancer of the Prostate Risk Assessment (CAPRA) score, to create a molecular and clinical risk score (MCRS), and validated in a Swedish cohort (n = 203). Outcome measurements and statistical analysis: The primary AP outcome was assessed by the likelihood ratio statistics and area under the receiver operating characteristics curves (AUC) from logistic regression models. The secondary time to BCR outcome was assessed by likelihood ratio statistics and C-indexes from Cox proportional hazard regression models. Results and limitations: The six-gene signature was significantly (p < 0.0001) prognostic and added significant prognostic value to clinicopathological features for AP and BCR outcomes. For both outcomes, both the MRS and the MCRS increased the AUC/C-index when added to European Association of Urology (EAU) and CAPRA scores. Limitations include the retrospective nature of this study. Conclusions: The six-gene signature has strong performance for the prediction of AP and BCR in an independent clinical validation study. MCRS improves prognostic evaluation and can optimise patient management after RP. Patient summary: We found that the expression panel of six genes can help predict whether a patient is likely to have a disease recurrence after radical prostatectomy surgery.
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| 11. |
- Krzyzanowska, Agnieszka, et al.
(författare)
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Expression of tSTAT3, pSTAT3 727 , and pSTAT3 705 in the epithelial cells of hormone-naïve prostate cancer
- 2019
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Ingår i: Prostate. - : Wiley. - 0270-4137. ; 79:7, s. 784-797
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Tidskriftsartikel (refereegranskat)abstract
- Background: The signal transducer and activator of transcription 3 (STAT3) pathway is observed to be constitutively activated in several malignancies including prostate cancer (PCa). In the present study, we investigated the expression of total STAT3 (tSTAT3) and two forms of activated phosphorylated STAT3 (pSTAT3 727 and pSTAT3 705 ) in tissue microarrays (TMA) of two cohorts of localized hormone-naïve PCa patients and analyzed associations between the expression and disease outcome. Methods: The expression of tSTAT3, pSTAT3 727 , and pSTAT3 705 was scored in the nuclei and cytoplasm of prostatic gland epithelial cells in two TMAs of paraffin-embedded prostatic tissue. The TMAs consisted of tissue originated from hormone-naïve radical prostatectomy patients from two different sites: Malmö, Sweden (n = 300) and Dublin, Ireland (n = 99). Results: The nuclear expression levels of tSTAT3, pSTAT3 727 , and pSTAT3 705 in the epithelial cells of benign glands were significantly higher than in the cancerous glands. Cytoplasmic tSTAT3 levels were also higher in benign glands. Patients with low pSTAT3 727 and pSTAT3 705 levels in the cancerous glands showed reduced times to biochemical recurrence, compared with those with higher levels. No significant trends in nuclear nor in cytoplasmic tSTAT3 were observed in relation to biochemical recurrence in the Malmö cohort. Higher cytoplasmic tSTAT3 was associated with reduced time to biochemical recurrence in the Dublin cohort. Adding the tSTAT3 and pSTAT3 expression data to Gleason score or pathological T stage did not improve their prognostic values. Conclusions: Low pSTAT3 727 and pSTAT3 705 expression in epithelial cells of cancerous prostatic glands in hormone-naïve PCa was associated with faster disease progression. However, pSTAT3 and tSTAT3 expression did not improve the prognostic value of Gleason score or pathological T stage and may not be a good biomarker in the early hormone naïve stages of PCa.
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| 12. |
- Krzyzanowska, Agnieszka, et al.
(författare)
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Quantitative Time-Resolved Fluorescence Imaging of Androgen Receptor and Prostate-Specific Antigen in Prostate Tissue Sections
- 2016
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Ingår i: Journal of Histochemistry and Cytochemistry. - : SAGE Publications. - 0022-1554 .- 1551-5044. ; 64:5, s. 311-322
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Tidskriftsartikel (refereegranskat)abstract
- Androgen receptor (AR) and prostate-specific antigen (PSA) are expressed in the prostate and are involved in prostate cancer (PCa). The aim of this study was to develop reliable protocols for reproducible quantification of AR and PSA in benign and malignant prostate tissue using time-resolved fluorescence (TRF) imaging techniques. AR and PSA were detected with TRF in tissue microarrays from 91 PCa patients. p63/ alpha-methylacyl-CoA racemase (AMACR) staining on consecutive sections was used to categorize tissue areas as benign or cancerous. Automated image analysis was used to quantify staining intensity. AR intensity was significantly higher in AMACR+ and lower in AMACR- cancer areas as compared with benign epithelium. The PSA intensity was significantly lower in cancer areas, particularly in AMACR- glands. The AR/PSA ratio varied significantly in the AMACR+ tumor cells as compared with benign glands. There was a trend of more rapid disease progression in patients with higher AR/PSA ratios in the AMACR- areas. This study demonstrates the feasibility of developing reproducible protocols for TRF imaging and automated image analysis to study the expression of AR and PSA in benign and malignant prostate. It also highlighted the differences in AR and PSA protein expression within AMACR- and AMACR+ cancer regions.
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| 13. |
- Krzyzanowska, Agnieszka, et al.
(författare)
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Reelin Immunoreactivity in the Adult Spinal Cord : A Comparative Study in Rodents, Carnivores, and Non-human Primates
- 2020
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Ingår i: Frontiers in Neuroanatomy. - : Frontiers Media SA. - 1662-5129. ; 13
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Tidskriftsartikel (refereegranskat)abstract
- Reelin is a large extracellular matrix (ECM) glycoprotein secreted by several neuronal populations in a specific manner in both the developing and the adult central nervous system. The extent of Reelin protein distribution and its functional role in the adult neocortex is well documented in different mammal models. However, its role in the adult spinal cord has not been well characterized and its distribution in the rodent spinal cord is fragmentary and has not been investigated in carnivores or primates as of yet. To gain insight into which neuronal populations and specific circuits may be influenced by Reelin in the adult spinal cord, we have conducted light and confocal microscopy study analysis of Reelin-immunoreactive cell types in the adult spinal cord. Here, we describe and compare Reelin immunoreactive cell type and distribution in the spinal cord of adult non-human primate (macaque monkeys, Macaca mulatta), carnivore (ferret, Mustela putorius) and rodent (rat, Rattus norvegicus). Our results show that in all three species studied, Reelin-immunoreactive neurons are present in the intermediate gray matter, ventricular zone and superficial dorsal horn and intermedio-lateral nucleus, while positive cells in the Clarke nucleus are only found in rats and primates. In addition, Reelin intermediolateral neurons colocalize with choline acetyltransferase (ChAT) only in macaque whilst motor neurons also colocalize Reelin and ChAT in macaque, ferret and rat spinal cord. The different expression patterns might reflect a differential role for Reelin in the pathways involved in the coordination of locomotor activity in the fore- and hind limbs.
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| 14. |
- Lundgren, Sebastian, et al.
(författare)
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The prognostic impact of NK/NKT cell density in periampullary adenocarcinoma differs by morphological type and adjuvant treatment
- 2016
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 11:6
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Tidskriftsartikel (refereegranskat)abstract
- Background: Natural killer (NK) cells and NK T cells (NKT) are vital parts of tumour immunosurveillance. However, their impact on prognosis and chemotherapy response in periampullary adenocarcinoma, including pancreatic cancer, has not yet been described. Methods: Immune cell-specific expression of CD56, CD3, CD68 and CD1a was analysed by immunohistochemistry on tissue microarrays with tumours from 175 consecutive cases of periampullary adenocarcinoma, 110 of pancreatobiliary type (PB-type) and 65 of intestinal type (Itype) morphology. Kaplan-Meier and Cox regression analysis were applied to determine the impact of CD56+ NK/NKT cells on 5-year overall survival (OS). Results: High density of CD56+ NK/NKT cells correlated with low N-stage and lack of perineural, lymphatic vessel and peripancreatic fat invasion. High density of CD56+ NK/NKT cells was associated with prolonged OS in Kaplan-Meier analysis (p = 0.003), and in adjusted Cox regression analysis (HR = 0.49; 95% CI 0.29-0.86). The prognostic effect of high CD56+ NK/NKT cell infiltration was only evident in cases not receiving adjuvant chemotherapy in PB-type tumours (p for interaction = 0.014). Conclusion: This study demonstrates that abundant infiltration of CD56+ NK/NKT cells is associated with a prolonged survival in periampullary adenocarcinoma. However, the negative interaction with adjuvant treatment is noteworthy. NK cell enhancing strategies may prove to be successful in the management of these cancers.
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| 15. |
- Marginean, Felicia, et al.
(författare)
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An Artificial Intelligence-based Support Tool for Automation and Standardisation of Gleason Grading in Prostate Biopsies
- 2021
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Ingår i: European Urology Focus. - : Elsevier BV. - 2405-4569. ; 7:5, s. 995-1001
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Gleason grading is the standard diagnostic method for prostate cancer and is essential for determining prognosis and treatment. The dearth of expert pathologists, the inter- and intraobserver variability, as well as the labour intensity of Gleason grading all necessitate the development of a user-friendly tool for robust standardisation.OBJECTIVE: To develop an artificial intelligence (AI) algorithm, based on machine learning and convolutional neural networks, as a tool for improved standardisation in Gleason grading in prostate cancer biopsies.DESIGN, SETTING, AND PARTICIPANTS: A total of 698 prostate biopsy sections from 174 patients were used for training. The training sections were annotated by two senior consultant pathologists. The final algorithm was tested on 37 biopsy sections from 21 patients, with digitised slide images from two different scanners.OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Correlation, sensitivity, and specificity parameters were calculated.RESULTS AND LIMITATIONS: The algorithm shows high accuracy in detecting cancer areas (sensitivity: 100%, specificity: 68%). Compared with the pathologists, the algorithm also performed well in detecting cancer areas (intraclass correlation coefficient [ICC]: 0.99) and assigning the Gleason patterns correctly: Gleason patterns 3 and 4 (ICC: 0.96 and 0.94, respectively), and to a lesser extent, Gleason pattern 5 (ICC: 0.82). Similar results were obtained using two different scanners.CONCLUSIONS: Our AI-based algorithm can reliably detect prostate cancer and quantify the Gleason patterns in core needle biopsies, with similar accuracy as pathologists. The results are reproducible on images from different scanners with a proven low level of intraobserver variability. We believe that this AI tool could be regarded as an efficient and interactive tool for pathologists.PATIENT SUMMARY: We developed a sensitive artificial intelligence tool for prostate biopsies, which detects and grades cancer with similar accuracy to pathologists. This tool holds promise to improve the diagnosis of prostate cancer.
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| 16. |
- Marginean, Felicia Elena, et al.
(författare)
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Nuclear expression of pSTAT3Tyr705 and pSTAT3Ser727 in the stromal compartment of localized hormone-naïve prostate cancer
- 2022
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Ingår i: Pathology Research and Practice. - : Elsevier BV. - 0344-0338. ; 232
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Tidskriftsartikel (refereegranskat)abstract
- Background: The signal transducer and activator of transcription 3 (STAT3) is involved in the progression of different tumors including prostate cancer (PCa). The expression of STAT3 in benign and malignant epithelium has been described previously but it has not been described in the stromal compartment. The aim of the present study was to evaluate the nuclear expression and prognostic value of different forms of phosphorylated STAT3 in the stromal compartment of non-cancer and cancer areas of prostatic tissue. Material and methods: Tissue microarray cores from radical prostatectomy of 225 patients with hormone-naïve localized PCa were immunostained for two phosphorylated forms of STAT3, pSTAT3Tyr705 and pSTAT3Ser727. The prognostic value of the expression levels was studied by Cox regression analysis and biochemical recurrence (BCR)-free survival illustrated by Kaplan-Meier curves. Results: Expression of pSTAT3Tyr705 and pSTAT3Ser727 in the stromal compartment of cancer tissue was lower compared with non-cancer areas. In univariable and multivariable Cox regression analysis, expression levels of pSTAT3Tyr705 and STAT3Ser727 showed similar prognostic value as pathological T-stage, Gleason score and surgical margin status. Kaplan–Meier survival analysis showed that low nuclear expression levels of pSTAT3Tyr705 and pSTAT3Ser727 in stromal cells in cancer compartment and in non-cancer areas were related to BCR-free survival. Conclusions: Nuclear expression of pSTAT3Tyr705 and pSTAT3Ser727 in the stromal cells mirrors previous findings in the epithelial component in that it displays prognostic value in men undergoing radical prostatectomy for localized hormone-naïve PCa.
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| 17. |
- Micke, Patrick, et al.
(författare)
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The prognostic impact of the tumour stroma fraction : A machine learning-based analysis in 16 human solid tumour types
- 2021
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Ingår i: EBioMedicine. - : Elsevier. - 2352-3964. ; 65
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Tidskriftsartikel (refereegranskat)abstract
- Background: The development of a reactive tumour stroma is a hallmark of tumour progression and pronounced tumour stroma is generally considered to be associated with clinical aggressiveness. The variability between tumour types regarding stroma fraction, and its prognosis associations, have not been systematically analysed.Methods: Using an objective machine-learning method we quantified the tumour stroma in 16 solid cancer types from 2732 patients, representing retrospective tissue collections of surgically resected primary tumours. Image analysis performed tissue segmentation into stromal and epithelial compartment based on pan-cytokeratin staining and autofluorescence patterns.Findings: The stroma fraction was highly variable within and across the tumour types, with kidney cancer showing the lowest and pancreato-biliary type periampullary cancer showing the highest stroma proportion (median 19% and 73% respectively). Adjusted Cox regression models revealed both positive (pancreato-biliary type periampullary cancer and oestrogen negative breast cancer, HR(95%CI)=0.56(0.34-0.92) and HR (95%CI)=0.41(0.17-0.98) respectively) and negative (intestinal type periampullary cancer, HR(95%CI)=3.59 (1.49-8.62)) associations of the tumour stroma fraction with survival.Interpretation: Our study provides an objective quantification of the tumour stroma fraction across major types of solid cancer. Findings strongly argue against the commonly promoted view of a general associations between high stroma abundance and poor prognosis. The results also suggest that full exploitation of the prognostic potential of tumour stroma requires analyses that go beyond determination of stroma abundance.
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| 18. |
- Winzell, Filip, et al.
(författare)
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Systematic Augmentation in HSV Space for Semantic Segmentation of Prostate Biopsies
- 2023
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Ingår i: Image Analysis : 23rd Scandinavian Conference, SCIA 2023, Proceedings, Part II - 23rd Scandinavian Conference, SCIA 2023, Proceedings, Part II. - 1611-3349 .- 0302-9743. - 9783031314384 - 9783031314377 ; 13886, s. 293-308
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Konferensbidrag (refereegranskat)abstract
- In recent years, the combination of the digitization of the field of pathology and increased computational power has led to a big increase in research of computer-aided diagnostics using systems based on artificial intelligence (AI). This includes detection and classification of prostate cancer, where several studies have shown great promise in automated prostate cancer grading using deep learning based AI systems. However, there is still work to be done to ensure that these algorithms are invariant to possible variations of the digitized microscopy images they are applied to. A standard method in deep learning to increase the variation of the training data is dataset augmentation. All of these studies apply some augmentation of their data, however, there is a lack of evaluation of different methods and their impact on this crucial part of the AI systems. In this study, we look into different color augmentation methods for the task of segmentation of prostate biopsies. Furthermore, we introduce a novel color augmentation method based on stereographic projection. Our results affirm the importance of studying different augmentation methods and indicate a gain in performance using our method.
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