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  • 1
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 41, No. 16_suppl ( 2023-06-01), p. e15181-e15181
    Abstract: e15181 Background: Carcinoembryonic antigen (CEA) is a cell surface glycoprotein which is overexpressed in various cancers but reported prevalence data vary considerably for many tumor types. Because of its overexpression in various cancer types and the limited expression in normal tissue CEA has become a potential drug target with several potential drug candidates currently being evaluated. CEA is also shed into the blood stream, so that CEA measurement in the serum is used as a tool for early detection and recurrence monitoring of cancer. Methods: To comprehensively determine CEA expression in normal and neoplastic tissues, a tissue microarray containing 15,413 samples from 120 different tumor types and subtypes as well as 76 different normal tissue types were analyzed by immunohistochemistry. Results: CEA was detectable in 65 (54.2%) of 120 tumor categories including 49 (40.8%) tumor types with at least one strongly positive case. CEA positivity was most common in colorectal adenomas (100%) and carcinomas (98.7%), other gastrointestinal adenocarcinomas (61.1%-80.3%), medullary carcinomas of the thyroid (96.3%), pulmonary adenocarcinoma (73.7%), mucinous carcinomas of the ovary (79.8%) and the breast (43.2%), squamous cell carcinomas of various sites (30.2%-69.1%), and small cell carcinomas of the lung (64.3%), the urinary bladder (38.9%), and the prostate (50.0%) as well as non-invasive papillary urothelial carcinoma pTa G3 (33,6%), pTa G2 high-grade (25,0%) and pTa G2 low-grade (5,7%). High CEA expression was linked to high grade tumors (p 〈 0.0001) and invasive growth (p 〈 0.0001) in urinary bladder cancer as well as estrogen receptor positivity (p = 0.0005) and HER2 positivity (p = 0,0158) in invasive breast cancer of no special type. In 1.250 colorectal adenocarcinomas, reduced CEA expression was associated with mismatch repair deficiency (p 〈 0.0001) but not with pT and pN stage. CEA expression level was unrelated to clinico-pathological tumor parameters in adenocarcinomas of the pancreas and the stomach, endometroid endometrium carcinoma as well as in serous and endometroid carcinomas of the ovaries. Conclusions: In summary, CEA is abundantly expressed in a broad range of epithelial neoplasms. Our data thus identify various tumor entities where CEA positive cancers might best benefit from CEA serum monitoring and anti-CEA therapies.
    Type of Medium: Online Resource
    ISSN: 0732-183X , 1527-7755
    RVK:
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    Language: English
    Publisher: American Society of Clinical Oncology (ASCO)
    Publication Date: 2023
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  • 2
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 83, No. 7_Supplement ( 2023-04-04), p. 6649-6649
    Abstract: Background: A combination of different immune-checkpoint-inhibitors (ICIs) have shown remarkable success in several tumor entities. However, the likelihood of positive response to ICIs is poor in most tumor entities and recent evidence suggests that the quantity and the expression level of immune checkpoints such as TIM3, CTLA-4, PD-1 of tumor infiltrating lymphocytes (TILs) influences the likelihood of response to immune checkpoint inhibitors. Design: To assess the density and spatial interplay of 42 immune checkpoint expressing leukocyte subpopulations in 6031 tumor samples from 49 carcinoma (sub)entities two different types of tissue microarrays (0.6 mm and 4 mm in diameter) were stained with 21 antibodies using our BLEACH & STAIN multiplex fluorescence immunohistochemistry approach. A deep learning-based framework comprising two different convolutional neuronal networks (U-Net and DeepLabv3+) was used for image analysis. Results: We found that the mean overall fraction of TIM3, PD-1, PD-L1 and CTLA-4 expression on M1, M2 macrophages, cD11c+ dendritic cells, CD8+ cytotoxic T-cells, CD4+ T-helper cells, FOXP3+ Tregs and CD20+ B-cells, ranged from 10% (sum of the fractions of immune checkpoint expression) in small cell carcinomas of the prostate up to 123 % in squamous cell carcinoma of the lung. Tumor types approved for checkpoint inhibitor therapy, including adenocarcinomas of the lung (121 %), small cell carcinoma of the lung (74%), malignant melanoma (59 %), and clear cell renal cell cancer (49%) were all ranking among the upper half of our list of mean fractions of overall immune checkpoint expression. Spatial analysis and the shift in immune cell compositions revealed that in most carcinoma (sub)entities, the overall immune cell density and fraction of immune checkpoint expression of individual patients occasionally exceeded the average immune cell density and fraction of tumors for which checkpoint inhibitors have been approved. Conclusion: These data support the concept that among most carcinoma entities at least some individual patients may benefit from treatment with immune checkpoint inhibitors. Citation Format: Zhihao Huang, Nicolaus F. Debatin, Elena Bady, Jan H. Mueller, Tim Mandelkow, Magalie C. Lurati, Ronald Simon, David Dum, Guido Sauter, Franziska Büscheck, Doris Hoeflmayer, Sören Weidemann, Claudia Hube-Magg, Till Clauditz, Maximilian Lennartz, Eike Burandt, Niclas C. Blessin. Prevalence and spatial interplay of mononuclear phagocyte and lymphocyte subpopulations in 49 carcinoma entities in respect to its TIM3, PD-1, PD-L1 and CTLA-4 expression using BLEACH & STAIN [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 6649.
    Type of Medium: Online Resource
    ISSN: 1538-7445
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2023
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  • 3
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 83, No. 7_Supplement ( 2023-04-04), p. 5144-5144
    Abstract: Background: The composition and functional state of T-cell subpopulations can highly impact patient’s outcome and response to immune checkpoint therapy. However, only little is known about the spatial interplay of most rare T-cell subpopulations. Design: To assess the density, composition, degree of immune checkpoint expression, and spatial interplay of T-cell subpopulations in 5989 tumor samples from more than 100 tumor entities, two different types of tissue microarrays (0.6 mm and 4 mm in diameter) were stained with antibodies directed against CD3, CD4, CD8, FOXP3, T-bet, GATA3, RORyT, BCL6, FOXP3, CD56, CD45RA, CD45RO, TIM3, PD-1, CTLA-4 Granzym B, and Ki67 using our BLEACH & STAIN multiplex fluorescence immunohistochemistry approach. A deep learning-based framework comprising two different convolutional neuronal networks (U-Net and DeepLabv3+) was used for image analysis. Results: For identification and definition of immune cell subpopulations unsupervised X-shift clustering and 2D/3D t-distributed stochastic neighbor embedding (t-SNE) using the “Rtsne” package (Rtsne (RRID:SCR_016342)) were applied and revealed 102 T-cell subpopulations at certain functional state. Within these subpopulations, the well-characterized expression profiles were visually matched with single T-cell expression profiles and documented as digital images. This process resulted in 12 main T-cell subsets that were further subclassified according to their functional state (proliferation, immune checkpoint expression) and studied according to their spatial orchestration. Interestingly, the vast majority of T-cell subsets were found in all analyzed tumor entities. However, their spatial orchestration, immune checkpoint expression profile was highly variable between different tumor entities. Conclusion: This study provides a comprehensive overview of rare T-cells subpopulations and its spatial orchestration in more than 100 different tumor entities. Citation Format: Zhihao Huang, Elena Bady, Jan H. Müller, Tim Mandelkow, Magalie C. Lurati, Ronald Simon, Christian Bernreuther, Frank Jacobsen, Guido Sauter, Katharina Möller, Andreas Luebke, Andrea Hinsch, Till S. Clauditz, Eike Burandt, Niclas C. Blessin. Spatial T-cell atlas in more than 100 different tumor entities using BLEACH & STAIN. [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 5144.
    Type of Medium: Online Resource
    ISSN: 1538-7445
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2023
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  • 4
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 82, No. 12_Supplement ( 2022-06-15), p. 1934-1934
    Abstract: The assessment of prognostic markers in routine clinical practice of breast cancer is currently performed using multi gene RNA panels. However, the unknown proportion of normal breast tissue in relation to malignant breast tissue can reduce the predictive value of such tests. Immunohistochemistry holds the potential for a better assessment of tumors because tumor cells can be separately analyzed. To enable automated prognosis marker detection (i.e. HER2, GATA3, progesterone receptor [PR], estrogen receptor [ER] , androgen receptor [AR], TOP2A, Ki-67, TROP2, Mammaglobin), we have developed and validated a framework for automated breast cancer identification, which comprises three different artificial intelligence analysis steps and an algorithm for cel l-distance analysis of 12+1 marker BLEACH & STAIN multiplex fluorescence immunohistochemistry staining, in 2004 breast cancers. The optimal distance between Myosin+ basal cells and benign panCK+ benign cells was identified as 31µm and used to exclude benign glands from the analysis combined with and deep learning-based algorithm for benign gland detection. Our deep learning-based framework discriminated normal glands from malignant glands with an area under receiver-operating characteristic curves (AUC) of 0.96 (95% confidence interval [CI], 0.92 to 0.99). The accuracy of the approach was also validated by several well-characterized biological findings, such as the identification of 13% HER2+, 73% PR+/ER+, and 14% triple negative cases in the study cohort as well as a significant higher Fraction of TOP2A in the HER2+ cases as compared to the HER2- cases (p & lt;0.001). Furthermore, the automated assessment of GATA3, PR, ER, TOP2A-LI, Ki-67-LI, TROP2, and Mammaglobin was significantly liked to the tumor grade (p & lt;0.001 each). Furthermore, a high expression level of HER2, GATA3, PR, and ER was associated with a prolonged overall survival (p≥0.002 each). In conclusion, a deep learning-based framework for automated breast cancer identification using BLEACH & STAIN multiplex fluorescence IHC facilitates automated prognosis marker quantification in breast cancer. Citation Format: Tim Mandelkow, Elena Bady, Magalie C. Lurati, Claudia Hube-Magg, Maximilian Lennartz, Guido Sauter, Niclas C. Blessin, Ronald Simon. An artificial intelligence-based framework for BLEACH & STAIN mfIHC facilitates automated prognosis marker assessment in breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1934.
    Type of Medium: Online Resource
    ISSN: 1538-7445
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2022
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  • 5
    In: Cancer Immunology Research, American Association for Cancer Research (AACR), Vol. 10, No. 1_Supplement ( 2022-01-01), p. P069-P069
    Abstract: Introduction: CTLA-4 is an inhibitory immune checkpoint receptor and a negative regulator of anti-tumor T-cell function. This study aimed at a comparative analysis of CTLA-4+ cells between different tumor entities. Methods: To quantify CTLA-4+ cells, 4,582 tumor samples from 90 different tumor entities as well as 608 samples of 76 different normal tissue types were analyzed by immunohistochemistry in a tissue microarray format. Two different antibody clones (MSVA-152R and CAL49) were validated and quantified using a deep learning framework for automated exclusion of unspecific immunostaining. Results: Comparing both CTLA-4 antibodies revealed a clone dependent cytoplasmic cross-reactivity in adrenal cortical adenoma (63%) for MSVA-152R and in pheochromocytoma (67%) as well as hepatocellular carcinoma (36%) for CAL49. After automated exclusion of non-specific staining reaction (3.6%), a strong correlation was observed for the densities of CTLA-4+ lymphocytes obtained by both antibodies (r=0.87; p & lt;0.0001). The mean density of CTLA-4+ cells was 674±1482 cells/mm2 and ranged from 71±175 cells/mm2 in leiomyoma to 5916±3826 cells/mm2 in Hodgkin's lymphoma. Within epithelial tumors, the density of CTLA-4+ lymphocytes were higher in squamous cell (421±467 cells/mm2) and urothelial carcinomas (419±347 cells/mm2) than in adenocarcinomas (269±375 cells/mm2) and renal cell neoplasms (256±269 cells/mm2). A high CTLA-4+ cell density was linked to low pT category (p & lt;0.0001), absent lymph node metastases (p=0.0354), and PD-L1 expression in tumor cells or inflammatory cells (p & lt;0.0001 each). A high CTLA-4/CD3-ratio was linked to absent lymph node metastases (p=0.0295) and to PD-L1 positivity on immune cells (p & lt;0.0026). Conclusion: Marked differences exist in the number of CTLA-4+ lymphocytes between tumors. Analyzing two independent antibodies by a deep learning framework identifies clone-specific cross-reactivity and facilitates automated quantification of target proteins such as CTLA-4. Citation Format: David Dum, Tjark L. C. Henke, Tim Mandelkow, Elena Bady, Jonas B. Raedler, Ronald Simon, Guido Sauter, Maximilian Lennartz, Waldemar Wilczak, Eike Burandt, Stefan Steurer, Niclas C. Blessin. Semi-automated validation and quantification of CTLA-4 in 90 different Tumor entities using multiple antibodies and artificial intelligence [abstract]. In: Abstracts: AACR Virtual Special Conference: Tumor Immunology and Immunotherapy; 2021 Oct 5-6. Philadelphia (PA): AACR; Cancer Immunol Res 2022;10(1 Suppl):Abstract nr P069.
    Type of Medium: Online Resource
    ISSN: 2326-6066 , 2326-6074
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2022
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  • 6
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 41, No. 16_suppl ( 2023-06-01), p. 3137-3137
    Abstract: 3137 Background: Detection of low level HER2 expression (HER2 low) is a prerequisite for therapy with new HER2 inhibitors in advanced breast cancer. Currently, tumors with immunohistochemical 1+ expression, and possibly also those with lower expression, are considered HER2 low. Therefore, the question of optimal sensitivity of HER2 assays is of increasing importance for clinical HER2 testing. In addition, there is hope that tumor types other than those with typical 3+ positivity may also benefit from these therapies. The aim of this study was to systematically investigate the influence of HER2 immunohistochemistry assay parameters on the detection rate of tumors with HER2 low expression in different tumor types. Methods: A tissue microarray containing 〉 10,000 tissue samples from more than 100 different tumor types and subtypes was analyzed for immunohistochemical expression of HER2 using different immunohistochemistry protocols and anti-HER2 antibodies, including the HercepTest and laboratory developed tests designed for high sensitivity. HER2 IHC evaluation included the recording of HER2 low (1+), ultralow (any staining, less than 1+), and 0 (completely negative). Results: Irrespective of the assay sensitivity all assays showed the expected/tolerable association with HER2 fluorescence in situ data in a cohort of 356 breast cancers. For the HercepTest, HER2 amplification was seen in 93% of 28 3+ cases, 55% of 11 2+ cases and in 1.5% of 274 0 and 1+ cases. For the most sensitive assay, amplification was seen in 90% of 30 3+ cases, 19% of 37 2+ cases and in 0.8% of 249 0 and 1+ cases. In non-breast cancers, the use of different assays resulted in highly variable results regarding the range of tumors with low or ultra-low HER2 expression in different tumor entities. For example, low (1+) and ultra-low (+) expression was observed in 7-24% (1+) and 11-28% (+) of serous ovarian cancers, 6.2-24% (1+) and 3.4-19% (+) of endometrioid endometrial cancers, 5.5-14% (1+) and 7.7-13% (+) of intestinal gastric cancers, 1.8-9.2% (1+) and 4.5-11% (+) of ductal adenocarcinomas of the pancreas, 19-33% (1+) and 5.5-11% (+) of muscle invasive urinary bladder cancers, 2.9-16% (1+) and 4.3-12% (+) of adenocarcinomas of the colon, 0-7.7% (1+) and 2.4-4.6% (+) of clear cell renal cell carcinomas, 4.8-6.5% (1+) and 6.0-8.6% (+) squamous cell carcinomas (SQCC) of the larynx, 6.3-7.1% (1+) and 2.4-6.3% (+) SQCC of the esophagus, 0.8-26% (1+) and 2.4-12% (+) SQCC of the cervix, as well as 1.5-5.1% (1+) and 1.5-2.2% (+) SQCC of the vulva. Conclusions: Low level HER2 expression occurs commonly in many cancer types. The rate of identifiable tumors with HER2 low or HER2 ultra-low expression greatly varies depending on assay parameters that can easily be modified. Clinical trials are needed to identify the HER2 expression thresholds to identify patients who may benefit from anti-HER2-low therapies.
    Type of Medium: Online Resource
    ISSN: 0732-183X , 1527-7755
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    Language: English
    Publisher: American Society of Clinical Oncology (ASCO)
    Publication Date: 2023
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  • 7
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 82, No. 12_Supplement ( 2022-06-15), p. 1935-1935
    Abstract: An increasing number of therapy regimens using a combination of different immune checkpoint inhibitors (ICIs) have shown remarkable results in several different tumor entities. However, the likelihood of a positive response rate to combined ICIs is poor in most tumor entities and depends on several parameters including the tumor microenvironment. Particularly little is known about the spatial orchestration and spatial interplay between different immune checkpoint expressing cells. Given that the T-cell immunoglobulin and mucin domain-containing protein 3 (TIM3) is expressed on both immune cells as well as tumor cells and that several phase I/II studies are currently evaluating anti-TIM3 drugs, the interplay between these immune checkpoints in human cancers is of topical interest. To study the spatial orchestration and interplay between TIM3, CTLA-4, PD-1, and PD-L1 expression on T-cell subsets, macrophage subsets, CD11c+ dendritic cells, CD20+B-cells in relation to panCK+ malignant cells, CD31+ vessels and other structural tumor compartments, a multiplex fluorescence immunohistochemistry approach was used to stain 18 different antibodies on a set of tissue microarrays containing samples from more than 3000 carcinoma samples. In addition, a deep learning-based framework for cell type identification was developed and validated in this study. TIM3, PD-1, PD-L1, and CTLA-4 expression was measured on tumor cells (panCK+), cytotoxic T-cells (CD3+CD8+), T-helper cells (CD3+CD4+), regulatory T-cells (CD3+CD4+FOXP3+), subsets of macrophages (CD68+CD163+/CD68+iNOS+) and dendritic cells (CD11c+). Interestingly, TIM3 as well as CTLA-4 expression on CD3+CD8+ cytotoxic T-cells and CD3+CD4+FOXP3+ regulatory T-cells showed a spatially more diverse expression pattern - particularly inverse expression profile - compared to PD-1 expression on all analyzed T-cells subsets that was consistently accompanied by PD-L1 expression on immune and tumor cells (p & lt;0.001). Combined analysis of cell densities, expression patterns, intensity measurements, interaction and distance analysis between immune cells and tumor cells revealed distinct changes in the immune cell infiltration pattern that was linked to several major immune checkpoint receptor expression profiles. Previously uncharacterized immune cell-composition dynamics in clustered tumor phenotypes, according to the immune checkpoint expression, were detected. This included for instance, a significant inverse association between CTLA-4 expression on T-cells and high expression levels of the PD-1/PD-L1 axis. In conclusion, deep profiling of 18 biomarkers in more than 40 different carcinoma entities revealed complex changes in the spatial orchestration of a wide range of immune cell subsets that was driven by the expression profile and composition of TIM3, PD-1, PD-L1, and CTLA-4. Citation Format: Nicolaus F. Debatin, Elena Bady, Tim Mandelkow, Magalie C. Lurati, Ronald Simon, Claudia Hube-Magg, Maximilian Lennartz, Guido Sauter, Niclas C. Blessin. Interplay between TIM3+ immune cells and other immune checkpoints in more than 40 different human carcinoma entities using 18+1 BLEACH & STAIN mfIHC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1935.
    Type of Medium: Online Resource
    ISSN: 1538-7445
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2022
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  • 8
    In: Experimental and Molecular Pathology, Elsevier BV, Vol. 131 ( 2023-06), p. 104860-
    Type of Medium: Online Resource
    ISSN: 0014-4800
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2023
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  • 9
    In: Molecular Cancer Research, American Association for Cancer Research (AACR), Vol. 21, No. 6 ( 2023-06-01), p. 605-613
    Abstract: Multiplex fluorescence IHC (mfIHC) approaches were yet either limited to six markers or limited to a small tissue size that hampers translational studies on large tissue microarray cohorts. Here we have developed a BLEACH & STAIN mfIHC method that enabled the simultaneous analysis of 15 biomarkers (PD-L1, PD-1, CTLA-4, panCK, CD68, CD163, CD11c, iNOS, CD3, CD8, CD4, FOXP3, CD20, Ki67, and CD31) in 3,098 tumor samples from 44 different carcinoma entities within one week. To facilitate automated immune checkpoint quantification on tumor and immune cells and study its spatial interplay an artificial intelligence–based framework incorporating 17 different deep-learning systems was established. Unsupervised clustering showed that the three PD-L1 phenotypes (PD-L1+ tumor and immune cells, PD-L1+ immune cells, PD-L1−) were either inflamed or noninflamed. In inflamed PD-L1+patients, spatial analysis revealed that an elevated level of intratumoral M2 macrophages as well as CD11c+ dendritic cell (DC) infiltration (P & lt; 0.001 each) was associated with a high CD3+ CD4± CD8± FOXP3± T-cell exclusion and a high PD-1 expression on T cells (P & lt; 0.001 each). In breast cancer, the PD-L1 fluorescence intensity on tumor cells showed a significantly higher predictive performance for overall survival (OS; AUC, 0.72, P & lt; 0.001) compared with the commonly used percentage of PD-L1+ tumor cells (AUC, 0.54). In conclusion, our deep-learning–based BLEACH & STAIN framework facilitates rapid and comprehensive assessment of more than 60 spatially orchestrated immune cell subpopulations and its prognostic relevance. Implications: The development of an easy-to-use high-throughput 15+1 multiplex fluorescence approach facilitates the in-depth understanding of the immune tumor microenvironment (TME) and enables to study the prognostic relevance of more than 130 immune cell subpopulations.
    Type of Medium: Online Resource
    ISSN: 1541-7786 , 1557-3125
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2023
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  • 10
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 83, No. 7_Supplement ( 2023-04-04), p. 3436-3436
    Abstract: Background: Tumor protein 63 (p63) is a transcription factor of the p53 gene family which is regularly expressed in the normal urothelium. Recently proposed RNA expression based molecular classifiers of bladder cancer identified high p63 expression as a component of a basal/squamous subtype linked to poor patient prognosis. The interplay between p63 expression status and the anti-tumor immunity in bladder cancer is unknown. Design: To assess the prognostic impact of p63 expression and the relationship between p63 and the immune tumor microenvironment we have stained tissue microarrays containing more than 2300 urothelial bladder carcinomas with 22 antibodies (i.e., p63, CD3, CD8, CD4, FOXP3, CD20, CD68, CD163, CD11c, TIM3, PD-L1, PD-1, CTLA-4, panCK, Ki-67, CD31, Vimentin, HLA-DRa, Myosin-11, Desmoglein 3, PAX-8, CDH16) using conventional brightfield and multiplex fluorescence immunohistochemistry (BLEACH & STAIN). A framework of several neuronal networks for image analysis were used. Spatial immune parameters were compared with histopathological parameters and overall survival data. The area under (tAUC) time-dependent receiver operating characteristic curves was used to compare the prognostic relevance of different prognostic markers. Results: Nuclear p63 staining was seen in all cells of normal urothelium and in all pTaG2 tumors, mostly at high levels. The rate of p63 positive cases and the staining intensity was lower in pTaG3 tumors (93.2%, p & lt;0.0001 for pTaG3 vs pTaG2) and markedly lower in pT2-4 carcinomas (83.5%, p=0.0120 for pT2-4 vs. pTaG3). A low p63 expression was linked to a low density of T-helper cells (p=0.044) and regulatory T-cells (p=0.0053) localized in the intraepithelial tumor component as well as in the stroma, while all other analyzed T-cells and macrophages subsets where unrelated to p63 expression. Within pT2-4 carcinomas, low p63 expression was linked to nodal metastasis (p=0.0028) and overall survival (p=0.0005). The association of p63 loss with survival was independent of pT and pN (p=0.0109). The predictive performance of intraepithelial CD8+ cytotoxic T-cells (tAUC: 0.70) was even higher than the predictive performance of p63 expression (tAUC: 0.57, p=0.0017). Conclusion: In summary, our data show that p63 is downregulated in a fraction of urothelial neoplasms that are associated with a particularly poor prognosis and a low density of T-helper and regulatory T-cells. The even higher predictive performance of intraepithelial CD8+ cytotoxic T-cells underlines the strong prognostic role of the immune tumor microenvironment in muscle invasive bladder cancer. Citation Format: Henning Plage, Sebastian Hofbauer, Kira Kornienko, Paul G. Bruch, Sarah Weinberger, Florian Roßner, Simon Schallenberg, Sefer Elezkurtaj, Martina Kluth, Maximilian Lennartz, Tim Mandelkow, Elena Bady, Niclas C. Blessin, Andreas H. Marx, Henrik Samtleben, Margit Fisch, Michael Rink, Marcin Slojewski, Krystian Kaczmarek, Thorsten Ecke, Steffen Hallmann, Stefan Koch, Nico Adamini, Sarah Minner, Ronald Simon, Guido Sauter, Tobias Klatte, David Horst, Thorsten Schlomm, Henrik Zecha. Reduced p63 expression is linked to a low density of regulatory T-cells and unfavorable prognosis in muscle-invasive urothelial carcinoma of the bladder [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 3436.
    Type of Medium: Online Resource
    ISSN: 1538-7445
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2023
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