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  • 1
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    Online Resource
    An AI-based, automated workflow for identification and scoring of invasive tumors in Ki-67 stained breast cancer specimens.
    American Society of Clinical Oncology (ASCO) ; 2022
    In:  Journal of Clinical Oncology Vol. 40, No. 16_suppl ( 2022-06-01), p. e15108-e15108
    Details
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 40, No. 16_suppl ( 2022-06-01), p. e15108-e15108
    Abstract: e15108 Background: Understanding the rate of tumor cell growth in breast cancer specimens may be indicative of disease aggressiveness, a tumor characteristic which can be used to make an informed treatment decision. The nuclear protein Ki-67 is increased in cells as they prepare to divide or proliferate and is therefore widely used as a proliferation marker for tumor progression. This degree of tumor cell proliferation, or the proliferative index, is commonly detailed in pathology reports shared with the patient care team. Methods: In this study, we utilized the Ki-67 [K2] immunohistochemistry (IHC) assay to stain 10 breast cancer specimens. Stained slides were imaged using the AT2 scanner (Leica Biosystems, Buffalo Grove, IL) and analyzed using the Visiopharm Image Analysis platform. Results: Previous efforts to assess Ki-67 positivity utilizing image analysis have relied on the use of a secondary stain or manual effort by the pathologist to exclude non-invasive tumor regions. These antiquated methods are costly to the lab as they require additional materials or valuable pathologist time. Our novel image analysis approach utilizes artificial intelligence (AI) to automatically denote non-invasive verses invasive tumor regions, which can then be used to quantify the Ki-67 proliferative index. Conclusions: This valuable tool will allow for greater accuracy, cost-savings, and time efficiency when analyzing breast cancer samples compared to traditional methods.
    Type of Medium: Online Resource
    ISSN: 0732-183X , 1527-7755
    URL: Article
    DOI: 10.1200/JCO.2022.40.16_suppl.e15108
    RVK:
    XA 52760
    RVK:
    XA 10000
    Language: English
    Publisher: American Society of Clinical Oncology (ASCO)
    Publication Date: 2022
    detail.hit.zdb_id: 2005181-5
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  • 2
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    Precision immuno-oncology (IO) ISH/IF multiplex panel: Spatial detection of cytokines and IO biomarkers.
    American Society of Clinical Oncology (ASCO) ; 2023
    In:  Journal of Clinical Oncology Vol. 41, No. 16_suppl ( 2023-06-01), p. e14654-e14654
    Details
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 41, No. 16_suppl ( 2023-06-01), p. e14654-e14654
    Abstract: e14654 Background: Cytokines have a large impact on the tumor microenvironment by affecting cell growth, survival, inflammation, and differentiation. Understanding the spatial biology within the tumor microenvironment, including the cytokine organization within specific cell types, can lead to better treatment plans for patients. Methods: We developed a hybrid multiplex panel, using RNA in-situ hybridization (ISH) and immunofluorescence (IF) to investigate the spatial biology of the tumor microenvironment. This panel also enabled us to simultaneously detect the RNA of cytokines and protein of specific immuno-oncology (IO) biomarkers. This allows us to visualize spatially, not only the organization of cell types but also to identify the cellular sources of specific cytokines. In this study, we analyzed the tumor microenvironment of samples from non-small cell lung cancer (NSCLC) and breast cancer in two panels for cytokine RNAs and IO protein biomarkers. Panel 1 included TNFa and IL-2 cytokines combined with CD68 and CD163 IO protein biomarkers. Panel 2 consisted of IL-6 and IL-2 cytokines with PAX5 and CD3 IO protein biomarkers. Staining was completed on the Leica Bond RX autostainer, and slides were scanned using the PhenoImager Fusion. Visiopharm software wasused to analyze the tumor microenvironment of tissue samples and localize cytokines in specific cell types. Results: CD163 positive macrophages (M2 phenotype) were seen predominantly within the tumors (NSCLC and breast cancer) whereas CD68 positive macrophages were identified towards the periphery in the non-tumor microenvironment. NSCLC tumor cells showed higher expression levels of IL-2, IL-6 and TNFa compared to breast cancer tumor cells. Predominance of CD3 positive T cells was noted with relative lack of PAX5 positive B cells within both NSCLC and breast cancer tumors. Multiplexing enabled assessment of relative expression levels of IL-2, IL-6 and TNFa in T lymphocytes and macrophages and TNFa in dendritic cells. Conclusions: Our hybrid multiplex panel can provide insights into the visualization of spatial organization of tumor microenvironment. It also enables semi-quantitative assessments for the expression levels of cytokines and their relative expression within tumor and immune cells, thereby helping to correlate response to treatment, especially with checkpoint inhibitors.
    Type of Medium: Online Resource
    ISSN: 0732-183X , 1527-7755
    URL: Article
    DOI: 10.1200/JCO.2023.41.16_suppl.e14654
    RVK:
    XA 52760
    RVK:
    XA 10000
    Language: English
    Publisher: American Society of Clinical Oncology (ASCO)
    Publication Date: 2023
    detail.hit.zdb_id: 2005181-5
    Location Call Number Limitation Availability
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  • 3
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    Abstract 2322: Precision immuno-oncology (IO) ISH/IF multiplex panel: Spatial detection of cytokines and IO biomarkers
    American Association for Cancer Research (AACR) ; 2023
    In:  Cancer Research Vol. 83, No. 7_Supplement ( 2023-04-04), p. 2322-2322
    Details
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 83, No. 7_Supplement ( 2023-04-04), p. 2322-2322
    Abstract: Cytokines have a large impact on the tumor microenvironment by affecting cell growth, survival, inflammation, and differentiation. Understanding the spatial biology within the tumor microenvironment, including the cytokine organization within specific cell types, can lead to better treatment plans for patients. We developed a hybrid multiplex panel, using RNA in-situ hybridization (ISH) and immunofluorescence (IF) to investigate the spatial biology of the tumor microenvironment. This panel also enabled us to simultaneously detect the RNA of cytokines and protein of specific immuno-oncology (IO) biomarkers. This allows us to visualize spatially, not only the organization of cell types but also to identify the cellular sources of specific cytokines. In this study, we analyzed the tumor microenvironment of samples from non-small cell lung cancer (NSCLC) and breast cancer in two panels for cytokine RNAs and IO protein biomarkers. Panel 1 included TNFa and IL-2 cytokines combined with the CD68 and CD163 IO protein biomarkers. Panel 2 consisted of IL-6 and IL-2 cytokines with the PAX5 and CD3 IO protein biomarkers. Staining was completed on the Leica Bond RX autostainer, and slides were scanned using the PhenoImager™ Fusion. Visiopharm® software was used to analyze the tumor microenvironment of tissue samples and localize cytokines in specific cell types. CD163 positive macrophages (M2 phenotype) were seen predominantly within the tumors (NSCLC and breast cancer) whereas CD68 positive macrophages were identified towards the periphery in the non-tumor microenvironment. NSCLC tumor cells showed higher expression levels of IL-2, IL-6 and TNFa compared to breast cancer tumor cells. Predominance of CD3 positive T cells was noted with relative lack of PAX5 positive B cells within both NSCLC and breast cancer tumors. Multiplexing enabled assessment of relative expression levels of IL-2, IL-6 and TNFa in T lymphocytes and macrophages and TNFa in dendritic cells. Our hybrid multiplex panel can provide insights into the visualization of spatial organization of tumor microenvironment. It also enables semi-quantitative assessments for the expression levels of cytokines and their relative expression within tumor and immune cells, thereby helping to correlate response to treatment, especially with checkpoint inhibitors. Citation Format: Brenna Dennison, Stephanie Allen, Bhavika Patel, Jacob Stapleton, Roni Archuleta, Mary Lou Rath, Navi Mehra, Sameer S. Talwalkar. Precision immuno-oncology (IO) ISH/IF multiplex panel: Spatial detection of cytokines and IO biomarkers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2322.
    Type of Medium: Online Resource
    ISSN: 1538-7445
    URL: Article
    DOI: 10.1158/1538-7445.AM2023-2322
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2023
    detail.hit.zdb_id: 2036785-5
    detail.hit.zdb_id: 1432-1
    detail.hit.zdb_id: 410466-3
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  • 4
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    Online Resource
    Genomic characterization of vulvar squamous cell carcinoma to reveal differential gene expression based on clinical outcome.
    American Society of Clinical Oncology (ASCO) ; 2023
    In:  Journal of Clinical Oncology Vol. 41, No. 16_suppl ( 2023-06-01), p. e17633-e17633
    Details
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 41, No. 16_suppl ( 2023-06-01), p. e17633-e17633
    Abstract: e17633 Background: The greatest challenge in the management of vulvar squamous cell carcinoma (VSCC) is treatment of recurrent disease where options for surgery and radiation have been exhausted, or treatment of disease where distant metastasis is present. Identification of mutations differentially expressed between tumor from patients who died of aggressive disease and tumor from patients with an indolent course could reveal novel prognostic indicators and guide development of therapeutic drugs. Methods: From 202 consecutive patients with VSCC, patients who recurred and died of disease (group A) were identified and matched by age, tumor size, depth of invasion and nodal status with those whose disease did not recur (group B). Tumor and matched normal samples from 21 patients were assayed by a broad NGS panel covering 648 genes, including whole exome and transcriptome sequencing. Immunohistochemistry (IHC) for PD-L1 (22C3) and p16 was also performed. Results: Whole transcriptome data revealed 6 genes that were strongly differentially expressed between the aggressive and indolent groups: ACVR2A, TGM3, ROS1, NFEL2, CCND1 and BCL6. Biologically relevant DNA mutations were significantly greater in the aggressive cohort versus the indolent cohort: 7 vs 2.3 mutations per patient. The most common genomic alterations were mutations in TP53 and the promoter region of TERT. TP53 alterations occurred almost exclusively in group A. Other common genomic events include alterations of FAT1, CDKN2A, PIK3CA, CCND1, and LRP1B. All samples were MSI stable, and tumor mutational burden was similar in groups A and B. Most VSCC specimens (81%) were positive for PD-L1. Conclusions: We report that TGM3 and ACVR2A genes are significantly under-expressed in tumors with poor outcome. Further investigation into the silencing of these genes may advance knowledge of the pathogenesis of VSCC and potentially yield therapeutic targets. Clinical outcome of VSCC appears independent of MSI, TMB or PD-L1 status. [Table: see text]
    Type of Medium: Online Resource
    ISSN: 0732-183X , 1527-7755
    URL: Article
    DOI: 10.1200/JCO.2023.41.16_suppl.e17633
    RVK:
    XA 52760
    RVK:
    XA 10000
    Language: English
    Publisher: American Society of Clinical Oncology (ASCO)
    Publication Date: 2023
    detail.hit.zdb_id: 2005181-5
    Location Call Number Limitation Availability
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  • 5
    Online Resource
    Online Resource
    The utilization of artificial intelligence to produce clinically relevant scores on PD-L1 immunostained non-small cell lung cancer biopsies.
    American Society of Clinical Oncology (ASCO) ; 2022
    In:  Journal of Clinical Oncology Vol. 40, No. 16_suppl ( 2022-06-01), p. e14576-e14576
    Details
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 40, No. 16_suppl ( 2022-06-01), p. e14576-e14576
    Abstract: e14576 Background: Immunotherapies targeting complex programmed death-ligand 1 (PD-L1) interactions have been groundbreaking in the treatment of non-small cell lung cancer (NSCLC), offering new strategies for patients who are likely to respond. PD-L1 binds to the checkpoint PD-1 to regulate T cells, which has an important role in boosting the immune response. Identifying patients who may benefit from PD-L1 focused care is dependent on the interpretation of the drug’s associated companion diagnostic (CDx) immunohistochemistry (IHC) assay. PD-L1 IHC assays stratify NSCLC patients using a Tumor Proportion Score (TPS), a manual scoring paradigm which must be applied by a clinical pathologist. Application of the score is complex as it requires the reader to visually exclude stromal and tumor-infiltrating immune cells across a full sample, retaining PD-L1 expression information for true tumor cells only. Methods: In this study, we utilized the PD-L1 [28-8] immunohistochemistry (IHC) assay to stain 10 NCSLC specimens. Stained slides were then imaged using the AT2 scanner (Leica Biosystems, Buffalo Grove, IL) scanner and analyzed using the Visiopharm Image Analysis platform. Results: The intricacy of TPS application is time consuming for the pathologist and introduces opportunity for inter- and intra-reader variability. Our novel image analysis approach utilizes artificial intelligence (AI) to automatically denote tumor nests and exclude tumor-infiltrating immune cells. The remaining true tumor cells may then be quantified for PD-L1 expression across the full biopsy, producing a TPS for each sample. Conclusions: This method allows for great accuracy and time-efficiency in providing a TPS than traditional methods, which may result in improved patient care.
    Type of Medium: Online Resource
    ISSN: 0732-183X , 1527-7755
    URL: Article
    DOI: 10.1200/JCO.2022.40.16_suppl.e14576
    RVK:
    XA 52760
    RVK:
    XA 10000
    Language: English
    Publisher: American Society of Clinical Oncology (ASCO)
    Publication Date: 2022
    detail.hit.zdb_id: 2005181-5
    Location Call Number Limitation Availability
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  • 6
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    Abstract 6666: Multispectral imaging to detect immune phenotypes in pre and post therapy breast cancer patient specimens
    American Association for Cancer Research (AACR) ; 2023
    In:  Cancer Research Vol. 83, No. 7_Supplement ( 2023-04-04), p. 6666-6666
    Details
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 83, No. 7_Supplement ( 2023-04-04), p. 6666-6666
    Abstract: The immune microenvironment is an important component in cancer therapy. Immune cells can encourage tumor growth, leading to disease progression. A high number of immune cells may be predictive of disease prognosis and response to therapies. Therefore, understanding the immune cell phenotypes present within cancerous tissue can be valuable in developing strategies that aid in the treatment of cancer. In this study, we analyzed pre-and post-therapy samples from breast cancer patients, treated with neoadjuvant chemotherapy, using a 6-plex immunofluorescence assay which included clinically relevant immuno-oncology biomarkers (FoxP3, PD-L1, PanCK, CD4, CD8 and CD163). This assay was developed and optimized in-house prior to testing the cohort. Endpoints for this analysis were characterization of the tumor microenvironment and analysis of the individual immune cell subsets pre and post treatment. Staining was completed on the Leica Bond RX autostainer (Leica Biosystems) and slides were scanned using the PhenoImager™ Fusion (Akoya Biosciences). Using Visiopharm® software, the multiplex phenotyping module was used to analyze the high dimensional human tissue and cell phenotypes were detected using artificial intelligence. Qualitative and quantitative results revealed a change in immune cell phenotypes between pre- and post-therapy samples. These included an increase in intra-tumoral and stromal T cells, no significant difference in PD-L1 positive cells, and an increase in the FOXP3 positive T cells in post-treatment samples. Our data provides insights into the development and application of multispectral imaging for characterization of tumor microenvironment and its dynamics before and after treatment in breast cancer. This can be applied to other cancer types and can aid in making treatment decisions. Citation Format: Bhavika Patel, Stephanie Allen, Brenna Dennison, Jacob Stapleton, Roni Archuleta, Mary Lou Rath, Navi Mehra, Sameer S. Talwalkar. Multispectral imaging to detect immune phenotypes in pre and post therapy breast cancer patient specimens [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6666.
    Type of Medium: Online Resource
    ISSN: 1538-7445
    URL: Article
    DOI: 10.1158/1538-7445.AM2023-6666
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2023
    detail.hit.zdb_id: 2036785-5
    detail.hit.zdb_id: 1432-1
    detail.hit.zdb_id: 410466-3
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