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  • 1
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    ANHIR: Automatic Non-Rigid Histological Image Registration Challenge
    Institute of Electrical and Electronics Engineers (IEEE) ; 2020
    In:  IEEE Transactions on Medical Imaging Vol. 39, No. 10 ( 2020-10), p. 3042-3052
    Details
    In: IEEE Transactions on Medical Imaging, Institute of Electrical and Electronics Engineers (IEEE), Vol. 39, No. 10 ( 2020-10), p. 3042-3052
    Type of Medium: Online Resource
    ISSN: 0278-0062 , 1558-254X
    URL: Journal
    URL: Article
    DOI: 10.1109/TMI.42
    DOI: 10.1109/TMI.2020.2986331
    RVK:
    XA 48667
    Language: Unknown
    Publisher: Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2020
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  • 2
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    Cytoskeleton-interacting LIM-domain protein CRP1 suppresses cell proliferation and protects from stress-induced cell death
    Elsevier BV ; 2008
    In:  Experimental Cell Research Vol. 314, No. 4 ( 2008-02), p. 738-747
    Details
    In: Experimental Cell Research, Elsevier BV, Vol. 314, No. 4 ( 2008-02), p. 738-747
    Type of Medium: Online Resource
    ISSN: 0014-4827
    URL: Article
    DOI: 10.1016/j.yexcr.2007.11.024
    RVK:
    WA 15000
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2008
    detail.hit.zdb_id: 1466780-0
    SSG: 12
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  • 3
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    p53 and MDM2 are regulated by PI-3-kinases on multiple levels under stress induced by UV radiation and proteasome dysfunction
    Elsevier BV ; 2003
    In:  Cellular Signalling Vol. 15, No. 1 ( 2003-01), p. 95-102
    Details
    In: Cellular Signalling, Elsevier BV, Vol. 15, No. 1 ( 2003-01), p. 95-102
    Type of Medium: Online Resource
    ISSN: 0898-6568
    URL: Article
    DOI: 10.1016/S0898-6568(02)00044-X
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2003
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    SSG: 12
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  • 4
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    Cellular UV damage responses—Functions of tumor suppressor p53
    Elsevier BV ; 2005
    In:  Biochimica et Biophysica Acta (BBA) - Reviews on Cancer Vol. 1755, No. 2 ( 2005-7), p. 71-89
    Details
    In: Biochimica et Biophysica Acta (BBA) - Reviews on Cancer, Elsevier BV, Vol. 1755, No. 2 ( 2005-7), p. 71-89
    Type of Medium: Online Resource
    ISSN: 0304-419X
    URL: Article
    DOI: 10.1016/j.bbcan.2005.04.003
    RVK:
    WA 15000
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2005
    detail.hit.zdb_id: 2209610-3
    SSG: 12
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  • 5
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    Spatial analysis of histology in 3D: quantification and visualization of organ and tumor level tissue environment
    Elsevier BV ; 2022
    In:  Heliyon Vol. 8, No. 1 ( 2022-01), p. e08762-
    Details
    In: Heliyon, Elsevier BV, Vol. 8, No. 1 ( 2022-01), p. e08762-
    Type of Medium: Online Resource
    ISSN: 2405-8440
    URL: Article
    DOI: 10.1016/j.heliyon.2022.e08762
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2022
    detail.hit.zdb_id: 2835763-2
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  • 6
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    Abstract 3060: Target genes of chromosomal 9p13.3 amplification in prostate cancer
    American Association for Cancer Research (AACR) ; 2011
    In:  Cancer Research Vol. 71, No. 8_Supplement ( 2011-04-15), p. 3060-3060
    Details
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 71, No. 8_Supplement ( 2011-04-15), p. 3060-3060
    Abstract: The development and progression of cancer is caused by alterations that accumulate in the genome of malignant cells. We are studying genetic alterations occurring in prostate cancer, the most common male malignancy in Western countries. We have previously identified a frequent (39%) gain at 9p13-q21 in 13 prostate cancer xenografts and 5 cell lines by aCGH (Saramäki et al., Int J Cancer 119:1322-1329, 2006). Preliminary results indicate that in clinical prostatectomy samples, gains and amplifications are found in approximately 30% and 10% of the cases, respectively, and that the amplification frequency seems to increase with disease progression to hormone-refractory stage. The 9p13.3 amplification is also found from several breast cancer cell lines, raising the possibility that the amplification target gene(s) in this area may take part in breast cancer formation in addition to prostate cancer. We aim at identifying the target gene of the 9p13.3 amplification in prostate cancer. A minimal region for the 9p13.3 amplification, determined by fluorescence in situ hybridisation (FISH), spans nearly 3.5 Mb and contains more than 40 known and hypothetical protein-coding genes. We initially screened mRNA expression levels by quantitative RT-PCR and chromosomal copy number alterations by FISH for these genes in 7 prostate cancer cell lines and 19 prostate cancer xenografts. Thus, we narrowed down the list of amplification target candidates to eight protein-coding genes (C9orf25, GALT, PIGO, UBAP1, UBAP2, UBE2R2, UNC13B and VCP). We have performed siRNA-mediated downregulation of these genes in cell lines with either a normal copy number status or a gain/amplification in 9p13.3 (prostate cancer cell lines PC-3 and 22Rv1; breast cancer cell lines MCF-7 and BT-474). Downregulation of several of these genes decrease the proliferation rate of the cells significantly (GALT, PIGO, UBAP1, UBAP2, VCP). As decreased levels of VCP induce cell death in PC-3 cells, downregulation of UBAP1 induces a cell cycle arrest in the G2/M phase. In addition, invasion of PC-3 cells in Boyden chamber assay is affected by knock-down of GALT and PIGO. Genes exhibiting alterations in the siRNA assays have been further analyzed for their expression in clinical prostate cancer tumor material by qRT-PCR and immunohistochemistry. These genes are also studied by overexpressing their cDNAs in cell lines with normal 9p13.3 copy number status and screening for altered cellular growth, survival and invasion in vitro. We aim at identifying a novel diagnostic and/or prognostic marker for prostate cancer, and potentially also a target for new cancer therapies, from the 9p13.3 region. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 3060. doi:10.1158/1538-7445.AM2011-3060
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    URL: Article
    DOI: 10.1158/1538-7445.AM2011-3060
    RVK:
    XA 36000
    RVK:
    XA 10000
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2011
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  • 7
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    Abstract 46: 3D reconstruction and quantitative analysis of histology for prostate cancer
    American Association for Cancer Research (AACR) ; 2019
    In:  Cancer Research Vol. 79, No. 13_Supplement ( 2019-07-01), p. 46-46
    Details
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 79, No. 13_Supplement ( 2019-07-01), p. 46-46
    Abstract: The integration of serial sectioning of tissue, digital whole slide imaging (WSI) and computational reconstruction algorithms enable the examination of histological samples in 3D at subcellular resolution. This allows visualizing and analyzing the imaged sample in its true three-dimensional context, offering a more comprehensive view on its spatial and morphological characteristics than that obtained via typical 2D examination. The advantages of reconstructing 3D models computationally using WSI over direct 3D imaging include the combination of high resolution, large sample sizes and compatibility with existing biochemical techniques such as in situ hybridization, immunohistochemistry and established histological staining and interpretation protocols. For this purpose, we developed a software pipeline to perform routine 3D reconstruction tasks for large image sizes and datasets in a fully automatic manner. The steps in our 3D reconstruction process are image acquisition, alignment of images to a shared coordinate space, and visualization of the reconstructed 3D data. We optimized algorithm selection and computationally intensive hyperparameter tuning using a quantitative benchmarking framework and Bayesian optimization. Further, we applied our existing pipeline for feature based analysis of tissue and extended it into 3D, allowing quantification and visualization of hundreds of features characterizing the tissue. We currently apply this system to characterize prostate cancer tumors. Prostate cancer is a heterogenous, often multifocal disease. In order to understand why and how certain tumor foci develop to a life-threatening disease over others, the tissue growth patterns and evolution of tumors with different genetic backgrounds need to be studied. We use mouse models of prostate cancer to study early tumor development connected to common genetic cancer alterations. By computing hundreds of features from the histology, and studying these in the spatial context, we gain important information of tumor characteristics as well as intra- and intertumor heterogeneity. In the future, we will further scale up the protocol to perform 3D reconstruction for serially sectioned human prostates in the near future. Citation Format: Pekka Ruusuvuori, Kimmo Kartasalo, Mira Valkonen, Masi Valkonen, Tapio Visakorpi, Matti Nykter, Leena Latonen. 3D reconstruction and quantitative analysis of histology for prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 46.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    URL: Article
    DOI: 10.1158/1538-7445.AM2019-46
    RVK:
    XA 36000
    RVK:
    XA 10000
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2019
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    detail.hit.zdb_id: 410466-3
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  • 8
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    Abstract 148: Transcriptome sequencing reveals PCAT5 - new ERG-regulated non-coding transcript in prostate cancer
    American Association for Cancer Research (AACR) ; 2015
    In:  Cancer Research Vol. 75, No. 15_Supplement ( 2015-08-01), p. 148-148
    Details
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 75, No. 15_Supplement ( 2015-08-01), p. 148-148
    Abstract: Background: Prostate cancer (PC) is the second most common cancer among men. Most PC-related deaths are due to invasive tumors that are treated with therapies inhibiting androgen production or androgen receptor (AR) activity. After an initial response, tumors invariably progress to castration resistant prostate cancers (CRPCs) for which no effective cure exists. Methods and Results: We used transcriptome sequencing to study fresh-frozen tissue specimens from 12 benign prostatic hyperplasias (BPHs), 28 PCs, and 13 CRPCs. Reference-based transcriptome assembly uncovered 145 previously unannotated intergenic PC and CRPC associated long non-coding transcripts (lncRNAs) or isoforms. One third of the transcripts were CRPC-specific. We showed that one of the novel transcripts, Prostate Cancer Associated Transcript 5 (PCAT5), expressed in half of the tumors, was likely regulated by ERG, the key transcription factor in ∼50% of prostate cancers. Genome-wide expression analysis of a PCAT5-positive prostate cancer cell line after PCAT5 knockdown suggested significant alterations in proliferation pathways. In vitro validation of the pathway alterations revealed concordantly dramatic effects in phenotype: stalling of cell growth, migration, invasion, and colony forming potential, and increase in the rate of apoptosis. Conclusions: We identified the key differences between PC and CRPC in transcriptome level, and validated the oncogenic potential of a novel lncRNA in ERG-positive prostate cancers, PCAT5. Our study presents a number of putative lncRNA biomarkers for CRPC, and opportunities for therapeutic intervention. Citation Format: Antti Ylipää, Kati Kivinummi, Matti Annala, Annika Kohvakka, Leena Latonen, Mauro Scaravilli, Kimmo Kartasalo, Simo-Pekka Leppänen, Serdar Karakurt, Janne Seppälä, Olli Yli-Harja, Teuvo L.J. Tammela, Wei Zhang, Tapio Visakorpi, Matti Nykter. Transcriptome sequencing reveals PCAT5 - new ERG-regulated non-coding transcript in prostate cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 148. doi:10.1158/1538-7445.AM2015-148
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    URL: Article
    DOI: 10.1158/1538-7445.AM2015-148
    RVK:
    XA 36000
    RVK:
    XA 10000
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2015
    detail.hit.zdb_id: 2036785-5
    detail.hit.zdb_id: 1432-1
    detail.hit.zdb_id: 410466-3
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  • 9
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    Abstract A9: Androgen-regulated miR-32 targets BTG2 and is overexpressed in castration-resistant prostate cancer
    American Association for Cancer Research (AACR) ; 2012
    In:  Cancer Research Vol. 72, No. 4_Supplement ( 2012-02-06), p. A9-A9
    Details
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 72, No. 4_Supplement ( 2012-02-06), p. A9-A9
    Abstract: The androgen receptor (AR) signaling pathway is central to the emergence of castration-resistant prostate cancer (CRPC). We set out to identify androgen-regulated microRNAs (miRNAs) that may contribute to the development of CRPC. We found miR-32 to be an androgen regulated miRNA which is differentially expressed in CRPC compared to benign prostate hyperplasia (BPH) according to microarray analyses. qRT-PCR analyses confirmed that miR-32 expression increases in CRPC compared to BPH, and that in untreated prostate cancer (PC) miR-32 expression is higher in tumors of stage pT3 compared to pT2. Transfection of pre-miR-32 to prostate cancer cell line LNCaP provided a significant growth advantage to the cells, and miR-32 was further demonstrated to reduce apoptosis. To identify target genes for miR-32, an mRNA microarray analysis was performed with LNCaP cells transfected with pre-miR-32. In this assay, B cell translocation gene 2 (BTG2) was identified as a novel putative target for miR-32. BTG2 was reduced both at mRNA and protein level in the cells transfected with pre-miR-32, and BTG2 was confirmed to be a miR-32 target by 3′-UTR-luciferase assay. Furthermore, BTG2 was able to partially rescue the growth advantage of miR-32 in LNCaP cells. Immunostainings of prostate cancer patient material showed a statistically significant (p & lt; 0.0001) reduction of BTG2 protein in CRPCs compared to PC. The lack of BTG2 staining was also associated (p=0.0021) with a short progression-free time in patients who underwent prostatectomy and inversely correlated to miR-32 expression levels. In conclusion, we find that miR-32 is an androgen-regulated miRNA targeting BTG2 and overexpressed in CRPC. Thus, miR-32 is a potential marker for aggressive disease and is a putative drug target in PC. Citation Format: Sanni E. Jalava, Leena Latonen, Mauro Scaravilli, Kati K. Waltering, Janne Seppälä, Harri Lähdesmäki, Teuvo L.J. Tammela, Tapio Visakorpi. Androgen-regulated miR-32 targets BTG2 and is overexpressed in castrationresistant prostate cancer [abstract]. In: Proceedings of the AACR Special Conference on Advances in Prostate Cancer Research; 2012 Feb 6-9; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2012;72(4 Suppl):Abstract nr A9.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    URL: Article
    DOI: 10.1158/1538-7445.PRCA2012-A9
    RVK:
    XA 36000
    RVK:
    XA 10000
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2012
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    detail.hit.zdb_id: 1432-1
    detail.hit.zdb_id: 410466-3
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  • 10
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    Metastasis detection from whole slide images using local features and random forests
    Wiley ; 2017
    In:  Cytometry Part A Vol. 91, No. 6 ( 2017-06), p. 555-565
    Details
    In: Cytometry Part A, Wiley, Vol. 91, No. 6 ( 2017-06), p. 555-565
    Abstract: Digital pathology has led to a demand for automated detection of regions of interest, such as cancerous tissue, from scanned whole slide images. With accurate methods using image analysis and machine learning, significant speed‐up, and savings in costs through increased throughput in histological assessment could be achieved. This article describes a machine learning approach for detection of cancerous tissue from scanned whole slide images. Our method is based on feature engineering and supervised learning with a random forest model. The features extracted from the whole slide images include several local descriptors related to image texture, spatial structure, and distribution of nuclei. The method was evaluated in breast cancer metastasis detection from lymph node samples. Our results show that the method detects metastatic areas with high accuracy (AUC = 0.97–0.98 for tumor detection within whole image area, AUC = 0.84–0.91 for tumor vs. normal tissue detection) and that the method generalizes well for images from more than one laboratory. Further, the method outputs an interpretable classification model, enabling the linking of individual features to differences between tissue types. © 2017 International Society for Advancement of Cytometry
    Type of Medium: Online Resource
    ISSN: 1552-4922 , 1552-4930
    URL: Issue
    URL: Article
    DOI: 10.1002/cyto.a.v91.6
    DOI: 10.1002/cyto.a.23089
    Language: English
    Publisher: Wiley
    Publication Date: 2017
    detail.hit.zdb_id: 2180639-1
    SSG: 12
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