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  • 1
    Language: English
    In: Modern pathology, 2019-07-01, Vol.32 (7), p.1042-1052
    Description: Anti-angiogenic therapy and immune checkpoint inhibition are novel treatment strategies for patients with renal cell carcinoma. Various components and structures of the tumor microenvironment are potential predictive biomarkers and also attractive treatment targets. Macrophages, tumor infiltrating lymphocytes, vascular and lymphatic vessels represent an important part of the tumor immune environment, but their functional phenotypes and relevance for clinical outcome are yet ill defined. We applied Tissue Phenomics methods including image analysis for the standardized quantification of specific components and structures within the tumor microenvironment to profile tissue sections from 56 clear cell renal cell carcinoma patients. A characteristic composition and unique spatial relationship of CD68+ macrophages and tumor infiltrating lymphocytes correlated with overall survival. An inverse relationship was found between vascular (CD34) and lymphatic vessel (LYVE1) density. In addition, outcome was significantly better in patients with high blood vessel density in the tumors, whereas increased lymphatic vessel density in the tumors was associated with worse outcome. The Tissue Phenomics imaging analysis approach allowed visualization and simultaneous quantification of immune environment components, adding novel contextual information, and biological insights with potential applications in treatment response prediction.
    Subject(s): Aged ; Carcinoma, Renal Cell - metabolism ; Carcinoma, Renal Cell - pathology ; Female ; Humans ; Image Processing, Computer-Assisted ; Immunohistochemistry - methods ; Kidney Neoplasms - metabolism ; Kidney Neoplasms - pathology ; Life Sciences & Biomedicine ; Lymphatic Vessels - metabolism ; Lymphatic Vessels - pathology ; Lymphocytes, Tumor-Infiltrating - metabolism ; Lymphocytes, Tumor-Infiltrating - pathology ; Male ; Middle Aged ; Pathology ; Science & Technology ; Tumor Microenvironment - physiology
    ISSN: 0893-3952
    E-ISSN: 1530-0285
    Source: Nature Open Access
    Source: Web of Science - Science Citation Index Expanded - 2019〈img src="http://exlibris-pub.s3.amazonaws.com/fromwos-v2.jpg" /〉
    Source: Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals
    Source: Alma/SFX Local Collection
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  • 2
    Language: English
    In: Clinical cancer research, 2005-02-01, Vol.11 (3), p.1154-1159
    Description: Purpose: Breast cancer is composed of phenotypically diverse populations of cancer cells. The ability to form breast tumors has been shown by in vitro / in vivo studies to be restricted to epithelial tumor cells with CD44 + /CD24 −/low characteristics. Validation of these findings with respect to detection in clinical samples, prognosis, and clinical relevance is in demand. Experimental Design: We investigated breast cancer tissues for the prevalence of CD44 + /CD24 −/low tumor cells and their prognostic value. The study included paraffin-embedded tissues of 136 patients with and without recurrences. In addition, a breast cancer progression array with normal, carcinoma in situ , and carcinoma tissues was analyzed. We applied double-staining immunohistochemistry for the detection of CD44 + /CD24 −/low cells. Evaluation was by microscopic pathologic inspection and automated image analysis. Results: CD44 + /CD24 −/low cells ranged from 0% to 40% in normal breast and from 0% to 80% in breast tumor tissues. The prevalence of CD44 + /CD24 −/low tumor cells in 122 tumors was ≤10% in the majority (78%) of cases and 〉10% in the remainder. There was no significant correlation between CD44 + /CD24 −/low tumor cell prevalence and tumor progression. Although recurrences of tumors with high percentages of CD44 + /CD24 −/low tumor cells were mainly distant, preferably osseous metastasis, there was no correlation with the event-free and overall survival. There was no influence on the response to different treatment modalities. Conclusions: Our findings suggest that the prevalence of CD44 + /CD24 −/low tumor cells in breast cancer may not be associated with clinical outcome and survival but may favor distant metastasis.
    Subject(s): Adult ; Aged ; Aged, 80 and over ; Anthracyclines - administration & dosage ; Antigens, CD - analysis ; Antineoplastic agents ; Antineoplastic Combined Chemotherapy Protocols - therapeutic use ; Biological and medical sciences ; Breast Neoplasms - drug therapy ; Breast Neoplasms - pathology ; Breast Neoplasms - radiotherapy ; CD24 Antigen ; Combined Modality Therapy ; double-staining immunohistochemistry ; Female ; Gynecology. Andrology. Obstetrics ; Humans ; Hyaluronan Receptors - analysis ; Immunohistochemistry ; invasion ; Mammary gland diseases ; Medical sciences ; Membrane Glycoproteins - analysis ; Middle Aged ; Neoplasm Metastasis ; Pharmacology. Drug treatments ; Prognosis ; progression ; Survival Analysis ; Tamoxifen - administration & dosage ; Treatment Outcome ; tumor stem cells ; Tumors
    ISSN: 1078-0432
    E-ISSN: 1557-3265
    Source: HighWire Press (Free Journals)
    Source: Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals
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  • 3
    Language: English
    In: Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association, 2018-05-19, Vol.22 (1), p.77-90
    Description: Background Gastric cancer with lymphoid stroma (GCLS) is characterized by prominent stromal infiltration of T-lymphocytes. The aim of this study was to investigate GCLS biology through analysis of clinicopathological features, EBV infection, microsatellite instability (MSI), immune gene-expression profiling and PD-L1 status in neoplastic cells and tumor immune microenvironment. Methods Twenty-four GCLSs were analyzed by RNA in situ hybridization for EBV (EBER), PCR/fragment analysis for MSI, immunohistochemistry (PD-L1, cytokeratin, CD3, CD8), co-immunofluorescence (CK/PD-L1, CD68/PD-L1), NanoString gene-expression assay for immune-related genes and PD-L1 copy number alterations. CD3+ and CD8+ T-cell densities were calculated by digital analysis. Fifty-four non-GCLSs were used as control group. Results GCLSs displayed distinctive clinicopathological features, such as lower pTNM stage ( p  = 0.02) and better overall survival ( p  = 0.01). EBV+ or MSI-high phenotype was found in 66.7 and 16.7% cases, respectively. GCLSs harbored a cytotoxic T-cell-inflamed profile, particularly at the invasive front of tumors ( p  〈 0.01) and in EBV+ cases ( p  = 0.01). EBV+ GCLSs, when compared to EBV− GCLSs, showed higher mRNA expression of genes related to Th1/cytotoxic and immunosuppressive biomarkers. PD-L1 protein expression, observed in neoplastic and immune stromal cells (33.3 and 91.7%, respectively), and PD-L1 amplification (18.8%) were restricted to EBV+/MSI-high tumors and correlated with high values of PD-L1 mRNA expression. Conclusions This study shows that GCLS has a distinctive clinico-pathological and molecular profile. Furthermore, through an in-depth study of tumor immune microenvironment—by digital analysis and mRNA expression profiling—it highlights the role of EBV infection in promoting an inflamed tumor microenvironment, with putative therapeutic implications.
    Subject(s): Abdominal Surgery ; Cancer Research ; Epstein–Barr virus (EBV) ; Gastric cancer ; Gastroenterology ; Gastroenterology & Hepatology ; Gene expression profiling ; Life Sciences & Biomedicine ; Medicine ; Medicine & Public Health ; Microsatellite instability (MSI) ; Oncology ; Original Article ; PD-L1 ; Science & Technology ; Surgical Oncology
    ISSN: 1436-3291
    E-ISSN: 1436-3305
    Source: Web of Science - Science Citation Index Expanded - 2019〈img src="http://exlibris-pub.s3.amazonaws.com/fromwos-v2.jpg" /〉
    Source: Alma/SFX Local Collection
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  • 4
    Language: English
    In: Scientific reports, 2018-03-13, Vol.8 (1), p.4470-19
    Description: Tissue Phenomics is the discipline of mining tissue images to identify patterns that are related to clinical outcome providing potential prognostic and predictive value. This involves the discovery process from assay development, image analysis, and data mining to the final interpretation and validation of the findings. Importantly, this process is not linear but allows backward steps and optimization loops over multiple sub-processes. We provide a detailed description of the Tissue Phenomics methodology while exemplifying each step on the application of prostate cancer recurrence prediction. In particular, we automatically identified tissue-based biomarkers having significant prognostic value for low- and intermediate-risk prostate cancer patients (Gleason scores 6-7b) after radical prostatectomy. We found that promising phenes were related to CD8(+) and CD68(+) cells in the microenvironment of cancerous glands in combination with the local micro-vascularization. Recurrence prediction based on the selected phenes yielded accuracies up to 83% thereby clearly outperforming prediction based on the Gleason score. Moreover, we compared different machine learning algorithms to combine the most relevant phenes resulting in increased accuracies of 88% for tumor progression prediction. These findings will be of potential use for future prognostic tests for prostate cancer patients and provide a proof-of-principle of the Tissue Phenomics approach.
    Subject(s): Cancer surgery ; CD8 antigen ; Data processing ; Glands ; Image processing ; Learning algorithms ; Prostate ; Prostate cancer ; Vascularization
    ISSN: 2045-2322
    E-ISSN: 2045-2322
    Source: Nature Open Access
    Source: Academic Search Ultimate
    Source: PubMed Central
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  • 5
    Language: English
    In: Frontiers in genetics, 2018, Vol.9, p.72-72
    Description: We aimed to identify and quantify CD117 and CD90 endogenous cardiac progenitor cells (CPC) in human healthy and diseased hearts. We hypothesize that these cells perform a locally acting, contributing function in overcoming medical conditions of the heart by endogenous means. Human myocardium biopsies were obtained from 23 patients with the following diagnoses: Dilatative cardiomyopathy (DCM), ischemic cardiomyopathy (ICM), myocarditis, and controls from healthy cardiac patients. High-resolution scanning microscopy of the whole slide enabled a computer-based immunohistochemical quantification of CD117 and CD90. Those signals were evaluated by Definiens Tissue Phenomics® Technology. Co-localization of CD117 and CD90 was determined by analyzing comparable serial sections. CD117 /CD90 cardiac cells were detected in all biopsies. The highest expression of CD90 was revealed in the myocarditis group. CD117 was significantly higher in all patient groups, compared to healthy specimens ( 〈 0.05). The highest co-expression was found in the myocarditis group (6.75 ± 3.25 CD90 CD117 cells/mm ) followed by ICM (4 ± 1.89 cells/mm ), DCM (1.67 ± 0.58 cells/mm ), and healthy specimens (1 ± 0.43 cells/mm ). We conclude that the human heart comprises a fraction of local CD117 and CD90 cells. We hypothesize that these cells are part of local endogenous progenitor cells due to the co-expression of CD90 and CD117. With novel digital image analysis technologies, a quantification of the CD117 and CD90 signals is available. Our experiments reveal an increase of CD117 and CD90 in patients with myocarditis.
    Subject(s): c-Kit+ (CD117+) cells ; Cardiomyopathy ; Care and treatment ; CD90+ cells ; Development and progression ; Genetics ; Heart cells ; Heart diseases ; human myocardium biopsy ; local cardiac stem ; local cardiac stem/progenitor cells ; myocarditis ; Observations ; progenitor cells
    ISSN: 1664-8021
    E-ISSN: 1664-8021
    Source: PubMed Central
    Source: DOAJ Directory of Open Access Journals - Not for CDI Discovery
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  • 6
    Language: English
    In: Academic radiology, 2016, Vol.23 (8), p.940-952
    Description: Rationale and Objectives Quantifying changes in lung tumor volume is important for diagnosis, therapy planning, and evaluation of response to therapy. The aim of this study was to assess the performance of multiple algorithms on a reference data set. The study was organized by the Quantitative Imaging Biomarker Alliance (QIBA). Materials and Methods The study was organized as a public challenge. Computed tomography scans of synthetic lung tumors in an anthropomorphic phantom were acquired by the Food and Drug Administration. Tumors varied in size, shape, and radiodensity. Participants applied their own semi-automated volume estimation algorithms that either did not allow or allowed post-segmentation correction (type 1 or 2, respectively). Statistical analysis of accuracy (percent bias) and precision (repeatability and reproducibility) was conducted across algorithms, as well as across nodule characteristics, slice thickness, and algorithm type. Results Eighty-four percent of volume measurements of QIBA-compliant tumors were within 15% of the true volume, ranging from 66% to 93% across algorithms, compared to 61% of volume measurements for all tumors (ranging from 37% to 84%). Algorithm type did not affect bias substantially; however, it was an important factor in measurement precision. Algorithm precision was notably better as tumor size increased, worse for irregularly shaped tumors, and on the average better for type 1 algorithms. Over all nodules meeting the QIBA Profile, precision, as measured by the repeatability coefficient, was 9.0% compared to 18.4% overall. Conclusion The results achieved in this study, using a heterogeneous set of measurement algorithms, support QIBA quantitative performance claims in terms of volume measurement repeatability for nodules meeting the QIBA Profile criteria.
    Subject(s): Algorithms ; anthropomorphic phantoms ; challenge ; CT volumetry ; Humans ; Image Processing, Computer-Assisted - methods ; Lung - diagnostic imaging ; Lung - pathology ; Lung cancer ; Lung Neoplasms - diagnostic imaging ; Lung Neoplasms - pathology ; lung tumor ; Phantoms, Imaging ; QIBA ; Radiology ; Reproducibility of Results ; Solitary Pulmonary Nodule - diagnostic imaging ; Solitary Pulmonary Nodule - pathology ; Tomography, X-Ray Computed - methods ; Tumor Burden
    ISSN: 1076-6332
    E-ISSN: 1878-4046
    Source: Alma/SFX Local Collection
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  • 7
    Language: English
    In: Academic radiology, 2015, Vol.22 (11), p.1393-1408
    Description: Rationale and objectives Tumor volume change has potential as a biomarker for diagnosis, therapy planning, and treatment response. Precision was evaluated and compared among semiautomated lung tumor volume measurement algorithms from clinical thoracic computed tomography data sets. The results inform approaches and testing requirements for establishing conformance with the Quantitative Imaging Biomarker Alliance (QIBA) Computed Tomography Volumetry Profile. Materials and Methods Industry and academic groups participated in a challenge study. Intra-algorithm repeatability and inter-algorithm reproducibility were estimated. Relative magnitudes of various sources of variability were estimated using a linear mixed effects model. Segmentation boundaries were compared to provide a basis on which to optimize algorithm performance for developers. Results Intra-algorithm repeatability ranged from 13% (best performing) to 100% (least performing), with most algorithms demonstrating improved repeatability as the tumor size increased. Inter-algorithm reproducibility was determined in three partitions and was found to be 58% for the four best performing groups, 70% for the set of groups meeting repeatability requirements, and 84% when all groups but the least performer were included. The best performing partition performed markedly better on tumors with equivalent diameters greater than 40 mm. Larger tumors benefitted by human editing but smaller tumors did not. One-fifth to one-half of the total variability came from sources independent of the algorithms. Segmentation boundaries differed substantially, not ony in overall volume but also in detail. Conclusions Nine of the 12 participating algorithms pass precision requirements similar to what is indicated in the QIBA Profile, with the caveat that the present study was not designed to explicitly evaluate algorithm profile conformance. Change in tumor volume can be measured with confidence to within ±14% using any of these nine algorithms on tumor sizes greater than 10 mm. No partition of the algorithms was able to meet the QIBA requirements for interchangeability down to 10 mm, although the partition comprising best performing algorithms did meet this requirement for a tumor size of greater than approximately 40 mm.
    Subject(s): Algorithms ; Carcinoma, Non-Small-Cell Lung - diagnostic imaging ; Carcinoma, Non-Small-Cell Lung - pathology ; CT imaging ; Female ; Humans ; Linear Models ; Lung - diagnostic imaging ; Lung - pathology ; Lung cancer ; Lung Neoplasms - diagnostic imaging ; Lung Neoplasms - pathology ; Methods ; quantitative imaging ; Radiology ; Reproducibility of Results ; segmentation ; Tomography, X-Ray Computed ; Tumor Burden ; Tumors ; volumetry
    ISSN: 1076-6332
    E-ISSN: 1878-4046
    Source: Alma/SFX Local Collection
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  • 8
    Language: English
    In: International journal of clinical and experimental pathology, 2014, Vol.7 (8), p.4971
    Description: Manual evaluation of somatostatin receptor (SSTR) immunohistochemistry (IHC) is a time-consuming and cost-intensive procedure. Aim of the study was to compare manual evaluation of SSTR subtype IHC to an automated software-based analysis, and to in-vivo imaging by SSTR-based PET/CT. We examined 25 gastroenteropancreatic neuroendocrine tumor (GEP-NET) patients and correlated their in-vivo SSTR-PET/CT data (determined by the standardized uptake values SUVmax,-mean) with the corresponding ex-vivo IHC data of SSTR subtype (1, 2A, 4, 5) expression. Exactly the same lesions were imaged by PET/CT, resected and analyzed by IHC in each patient. After manual evaluation, the IHC slides were digitized and automatically evaluated for SSTR expression by Definiens XD software. A virtual IHC score "BB1" was created for comparing the manual and automated analysis of SSTR expression. BB1 showed a significant correlation with the corresponding conventionally determined Her2/neu score of the SSTR-subtypes 2A (rs: 0.57), 4 (rs: 0.44) and 5 (rs: 0.43). BB1 of SSTR2A also significantly correlated with the SUVmax (rs: 0.41) and the SUVmean (rs: 0.50). Likewise, a significant correlation was seen between the conventionally evaluated SSTR2A status and the SUVmax (rs: 0.42) and SUVmean (rs: 0.62). Our data demonstrate that the evaluation of the SSTR status by automated analysis (BB1 score), using digitized histopathology slides ("virtual microscopy"), corresponds well with the SSTR2A, 4 and 5 expression as determined by conventional manual histopathology. The BB1 score also exhibited a significant association to the SSTR-PET/CT data in accordance with the high affinity profile of the SSTR analogues used for imaging.
    Subject(s): Adult ; Aged ; Automation, Laboratory ; Biomarkers, Tumor - analysis ; Female ; Humans ; Image Interpretation, Computer-Assisted - methods ; Immunohistochemistry - methods ; Intestinal Neoplasms - diagnosis ; Intestinal Neoplasms - metabolism ; Magnetic Resonance Imaging ; Male ; Middle Aged ; Multimodal Imaging ; Neuroendocrine Tumors - diagnosis ; Neuroendocrine Tumors - metabolism ; Pancreatic Neoplasms - diagnosis ; Pancreatic Neoplasms - metabolism ; Receptors, Somatostatin - analysis ; Software ; Stomach Neoplasms - diagnosis ; Stomach Neoplasms - metabolism ; Tomography, X-Ray Computed
    E-ISSN: 1936-2625
    Source: PubMed Central
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  • 9
    Language: English
    Description: Anti-angiogenic therapy and immune checkpoint inhibition are novel treatment strategies for patients with renal cell carcinoma. Various components and structures of the tumor microenvironment are potential predictive biomarkers and also attractive treatment targets. Macrophages, tumor infiltrating lymphocytes, vascular and lymphatic vessels represent an important part of the tumor immune environment, but their functional phenotypes and relevance for clinical outcome are yet ill defined. We applied Tissue Phenomics methods including image analysis for the standardized quantification of specific components and structures within the tumor microenvironment to profile tissue sections from 56 clear cell renal cell carcinoma patients. A characteristic composition and unique spatial relationship of CD68+ macrophages and tumor infiltrating lymphocytes correlated with overall survival. An inverse relationship was found between vascular (CD34) and lymphatic vessel (LYVE1) density. In addition, outcome was significantly better in patients with high blood vessel density in the tumors, whereas increased lymphatic vessel density in the tumors was associated with worse outcome. The Tissue Phenomics imaging analysis approach allowed visualization and simultaneous quantification of immune environment components, adding novel contextual information, and biological insights with potential applications in treatment response prediction.
    Subject(s): Institute of Pathology and Molecular Pathology ; Medicine & health ; Urological Clinic
    ISSN: 0893-3952
    E-ISSN: 1530-0285
    Source: ZORA
    Source: Nature Open Access
    Source: Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals
    Source: Alma/SFX Local Collection
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  • 10
    Language: English
    In: Cancer research (Chicago, Ill.), 2018-08-15, Vol.78 (16 Supplement), p.A069-A069
    ISSN: 0008-5472
    E-ISSN: 1538-7445
    Source: HighWire Press (Free Journals)
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