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  • American Association for Cancer Research (AACR)  (3)
  • Kaufmann, Martin  (3)
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  • American Association for Cancer Research (AACR)  (3)
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  • 1
    Online Resource
    Online Resource
    American Association for Cancer Research (AACR) ; 2021
    In:  Clinical Cancer Research Vol. 27, No. 5_Supplement ( 2021-03-01), p. PO-005-PO-005
    In: Clinical Cancer Research, American Association for Cancer Research (AACR), Vol. 27, No. 5_Supplement ( 2021-03-01), p. PO-005-PO-005
    Abstract: BACKGROUND: In recent years AI and deep learning have transformed the ability to use large amounts of medical data to augment diagnosis and prognosis processes for cancer. For developing AI methodology, histopathologic assessment serves as the gold standard “labels”, enabling investigators to finely map (or annotate) biologically and clinically important features. Yet correlating high dimensional data (radiomic, morphometric, genomic, metabolomic, etc.) with expert histopathologic diagnosis for dataset generation remains a major challenge. CHALLENGE: Traditionally, labels have been extracted from a snapshot that contains all of the annotation layers overlaid on the original tissue through image processing techniques. This implies the use of distinct colors for annotation, which severely constrain the number of possible labels. Particularly, this is most noticeable for heterogeneous tissues like prostate that require complex annotation. Furthermore, the resolution with which the labels can be mapped is limited by the area of the extracted region. OBJECTIVE: Here we present a workflow for pathology-oriented dataset generation for AI studies that is compatible with standard annotation platforms, and addresses these limitations. We introduce a detailed multi-grade and multi-scale annotation protocol for prostate biopsies. The proposed method is capable of exporting labels as independent layers (representing specific grades of the pathology), and resampling them to the desired resolution. METHODS: A collection of 38 prostate biopsy sections from 19 patients fixed on slides were used. The proposed grading annotation protocol is based on the spatial distribution of cancer cells. Nine layers of annotation were considered depicting stroma, benign tissue, low grade (Gleason pattern 3) and high grade cancer (Gleason patterns 4 and 5), two mixed cancer patterns, prostatic intraepithelial neoplasia (PIN), intraductal carcinoma (IDC), and artifact. The coordinates of the annotation boundaries are post-processed and combined into a label image containing all 9 pathological classes. The metabolomic profiles of the prostate biopsies acquired by desorption electrospray ionization (DESI) is considered for data features in this study. The generated image labels are therefore spatially registered to corresponding DESI data of each slide. RESULTS: The generated dataset through proposed method is used in the application of prostate cancer detection. The dataset is validated through qualitative visualization and quantitative analysis. High correlation is observed between label images of the slides and unsupervised linear representation of corresponding DESI spectra. The pixel-based supervised identification of tissue types based on the DESI also shows high accuracy. CONCLUSION: The proposed digitized pathology annotation protocol and dataset generation workflow is compatible with AI oriented cancer research and is capable of handling large number of pathological classes and high dimensional imaging modalities. Citation Format: Amoon Jamzad, Tamara Jamaspishvili, Rachael Iseman, Martin Kaufmann, David Berman, Parvin Mousavi. An efficient digitized annotation platform for pathology-oriented dataset generation in AI research [abstract]. In: Proceedings of the AACR Virtual Special Conference on Artificial Intelligence, Diagnosis, and Imaging; 2021 Jan 13-14. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(5_Suppl):Abstract nr PO-005.
    Type of Medium: Online Resource
    ISSN: 1078-0432 , 1557-3265
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2021
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  • 2
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 75, No. 15_Supplement ( 2015-08-01), p. 5321-5321
    Abstract: RG7787 is composed of a Fab fragment from an anti-MSLN antibody fused to a de-immunized and truncated pseudomonas endotoxin A variant. Once RG7787 is bound and internalized by MSLN positive cells, the toxin is transported to the cytosol, where it inhibits protein synthesis, eventually causing tumor cell death. Mesothelin (MSLN) is a tumor specific differentiation antigen. On normal tissue, its expression is restricted to differentiated mesothelial cells that line as single cell layer body cavities and major organs (e.g. pleura, pericardium, and peritoneum). In cancer, MSLN is highly expressed not only on mesotheliomas but also on a number of other types of solid tumors like ovarian and pancreatic cancer. In both indications patients frequently also have significant serum levels of the cancer antigen-125 (CA-125), sometimes even & gt;1000 U/ml. MSLN has been described to bind CA-125 and this interaction has been suggested to play a role for the ability of cancer cells to metastasize e.g. to the peritoneum. The region in MSLN that is responsible for its interaction with CA-125 has been reported to overlap with the binding epitope of RG7787 potentially resulting in competition between CA-125 and RG7787 for binding to MSLN. The high percentage of MSLN positive cases as well as a clear unmet medical need makes ovarian and pancreatic cancer promising indications for clinical development of RG7787. We investigated, whether abundance of CA-125 can negatively affect ability of RG7787 to bind and be taken up by tumor cells thereby antagonizing RG7787 treatment. We found that indeed RG7787 competes with CA-125 for binding to mesothelin. However, in SPR experiments, the interaction of MSLN with CA-125 was not strong enough to block binding of the anti-MSLN Fab moiety that targets RG7787 to tumor cells. At 20°C the absolute affinity (KD) of RG7787 for human MSLN was determined to be 12.5 pM using two orthogonal “affinity in solution” methods, ELISA and SPR. In agreement with such high affinity binding, we found that adding soluble CA-125 to cell viability assays did not reduce the cytotoxic potency of RG7787. In one set of assays, ascites fluid containing a 10 fold excess of CA-125 compared to the average levels observed in sera of ovarian patients was used for competition. In another set of assays, we used a 100 fold excess of a truncated recombinant CA-125 fragment, containing the domain that interacts with MSLN. Neither the ascites fluid, nor the recombinant CA-125 fragment had any effect on the in-vitro potency of RG7787, indicating that soluble CA-125 levels in patients will not antagonize RG7787 treatment. Finally we demonstrated in cell-cell interaction assays that RG7787 can efficiently block the attachment of MSLN positive cells to OVCAR3 cells that express high levels of CA-125 on their surface. Based on these encouraging data we are currently evaluating in-vivo efficacy of RG7787 in a patient-derived ovarian cancer model. Citation Format: Gwendlyn Kollmorgen, Klara Palme, Annette Seidl, Stefan Scheiblich, Christian Clemens, Edgar Voss, Martin Kaufmann, Klaus Hirzel, Pamela Wilfert, Moritz Marcinowski, Bernd Satzinger, Frank Herting, Gerhard Niederfellner. Preclinical validation for treatment with RG7787 in ovarian 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 5321. doi:10.1158/1538-7445.AM2015-5321
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2015
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  • 3
    In: Cancer Prevention Research, American Association for Cancer Research (AACR), Vol. 5, No. 11_Supplement ( 2012-11-01), p. B97-B97
    Abstract: Background: Vitamin D may be important in the causal pathway to breast cancer (BC) by influencing breast density, a potential intermediate biomarker for carcinogenesis. However, previous study results are inconsistent, particularly among postmenopausal women. Our objectives were to prospectively examine the relationship between blood biomarkers of vitamin D (serum 25-OH-D) and mammographic breast density (MD) in postmenopausal women at northern latitudes. Potential effect modifications by calcium or exemestane therapy on the relationship between serum 25-OH-D and follow-up MD were also examined. Methods: The NCIC Clinical Trials Group conducted a randomized controlled trial (RCT) comparing exemestane (E) with placebo (P) in 4560 postmenopausal women at high risk for developing BC (MAP.3) (Goss, NEJM 2011). Using a nested observational design, we evaluated a cohort of participants from across Canada and Buffalo, NY. BC risk factor information was previously collected; primary exposure and outcome data were obtained from serum samples and mammograms. Serum 25-OH-D was measured using state-of-the-art LC-MS/MS from samples collected at baseline and year 1. Values for year 1 samples were adjusted to match the month of sampling for the baseline sample month and these samples were averaged. Baseline and ≥ 3 year follow-up percent MD were centrally assessed, blinded to treatment allocation and vitamin D levels, using Cumulus software. Linear regression was used to estimate the effect of serum 25-OH-D on log transformed percent MD at ≥ 3 year follow-up controlling for month of sampling and potential confounders of age, body mass index, first degree family history of BC and calcium. Results: Percent MD was measured for 568 participants (E=287, P=281) with a ≥ 3 year follow-up mammogram obtained from 21 (91%) Canadian sites participating in MAP.3 and one US site in Buffalo, NY. The mean age of these women at study entry was 62 years and they were followed for a mean of 3.7 years. The geometric mean percent MD of the follow-up mammograms was 4.3%. A random sample of 10% (N=102) of mammograms was repeated with high intra-rater reliability (correlation coefficient = 0.95). Unadjusted for month of blood collection, the mean serum 25-OH-D concentration was 36.5 ng/mL (SD=10.6) based on pooled baseline and year one serum samples. After controlling for month of sampling and potential confounders, serum 25-OH-D was not predictive of log transformed percent MD (p=0.25). Statistically significant interactions with calcium (above vs. below the median calcium value p=0.30) or exemestane (p=0.99) on the serum 25-OH-D and MD relationship were not detected. Preliminary results suggest some evidence that low vitamin D ( & lt;25 ng/mL) is associated with increased breast density in the presence of low calcium. Final results will be reported at the time of the AACR meeting. Conclusion: In this nested observational study, no association between serum 25-OH-D levels and percent MD at ≥ 3 year follow-up was detected after controlling for month of sampling and many well established BC risk factors. This study was funded by the Canadian Breast Cancer Foundation. The MAP.3 trial was supported by Pfizer. The NCIC CTG is supported by the Canadian Cancer Society Research Institute. Citation Format: Melanie Walker, Harriet Richardson, Paul Goss, Doris Jabs, Glenville Jones, Martin Kaufmann, Jean Wactawski-Wende, Angela Cheung, Eric Winquist, Silvana Spadafora, Susan Ellard, Amanda Hey, Andrew Cooke, Andrea Eisen, Shailendra Verma, Lavina Lickley, Dongsheng Tu, Karen Gelmon, Ralph Meyer, Will King. Vitamin D and mammographic density in postmenopausal women: A cohort study nested within the NCIC CTG MAP.3 chemoprevention trial. [abstract]. In: Proceedings of the Eleventh Annual AACR International Conference on Frontiers in Cancer Prevention Research; 2012 Oct 16-19; Anaheim, CA. Philadelphia (PA): AACR; Cancer Prev Res 2012;5(11 Suppl):Abstract nr B97.
    Type of Medium: Online Resource
    ISSN: 1940-6207 , 1940-6215
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2012
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