PD-L1 expression in tumor and inflammatory cells is associated with favorable tumor features and favorable prognosis in muscle-invasive urothelial carcinoma of the bladder not treated by immune checkpoint inhibitors

BACKGROUND

A high level of PD-L1 expression is the most relevant predictive parameter for response to immune checkpoint inhibitor (CPI) therapy in urinary bladder cancer. Existing data on the relationship between PD-L1 expression and the natural course of disease are controversial and sparse.

METHODS

To expand our understanding of the relationship between PD-L1 expression and parameters of cancer aggressiveness, PD-L1 was analyzed on tissue microarrays containing 2710 urothelial bladder carcinomas including 512 patients with follow-up data who underwent radical cystectomy and follow-up therapies in the pre-immune checkpoint inhibitor therapy era.

RESULTS

Tumor cell positivity in ≥10% of cells were seen in 513 (20%) and an immune cell positivity occurred in 872 (34%) of 2566 interpretable cancers. PD-L1 positivity in tumor cells increased from pTaG2 low grade (0.9% positive) to pTaG3 high grade (4.1%; p = 0.0255) and was even higher in muscle-invasive (pT2-4) carcinomas (29.3%; p < 0.0001). However, within pT2-4 carcinomas, PD-L1 positivity was linked to low pT stage (p = 0.0028), pN0 (p < 0.0001), L0 status (p = 0.0005), and a better prognosis within 512 patients with cystectomy who never received CPIs (p = 0.0073 for tumor cells and p = 0.0086 for inflammatory cells). PD-L1 staining in inflammatory cells was significantly linked to PD-L1 staining in tumor cells (p < 0.0001) and both were linked to a positive p53 immunostaining (p < 0.0001).

CONCLUSION

It cannot be fully excluded that the strong statistical link between PD-L1 status and favorable histological tumor features as well as better prognosis could influence the outcome of studies evaluating CPIs in muscle-invasive urothelial carcinoma.

TRPS1 is a Highly Sensitive Marker for Breast Cancer: A Tissue Microarray Study Evaluating More Than 19,000 Tumors From 152 Different Tumor Entities

Trichorhinophalangeal syndrome 1 (TRPS1) is a nuclear protein highly expressed in breast epithelial cells. TRPS1 immunohistochemistry (IHC) has been suggested as a breast cancer marker. To determine the diagnostic and prognostic utility of TRPS1 IHC, tissue microarrays containing 19,201 samples from 152 different tumor types and subtypes were analyzed. GATA3 IHC was performed in a previous study. TRPS1 staining was seen in 86 of 152 tumor categories with 36 containing at least one strongly positive case. TRPS1 staining predominated in various types of breast carcinomas (51%-100%), soft tissue tumors (up to 100%), salivary gland tumors (up to 46%), squamous cell carcinomas (up to 35%), and gynecological cancers (up to 40%). TRPS1 positivity occurred in 1.8% of 1083 urothelial neoplasms. In invasive breast carcinoma of no special type, low TRPS1 expression was linked to high grade (P= 0.0547), high pT (P< 0.0001), nodal metastasis (P= 0.0571), loss of estrogen receptor and progesterone receptor expression (P< 0.0001 each), and triple-negative status (P< 0.0001) but was unrelated to patient survival (P= 0.8016). In squamous cell carcinomas from 11 different sites, low TRPS1 expression was unrelated to tumor phenotype. Positivity for both TRPS1 and GATA3 occurred in 47.4% to 100% of breast cancers, up to 30% of salivary gland tumors, and 29 (0.3%) of 9835 tumors from 134 other cancer entities. TRPS1 IHC has high utility for the identification of cancers of breast (or salivary gland) origin, especially in combination with GATA3. The virtual absence of TRPS1 positivity in urothelial neoplasms is useful for the distinction of GATA3-positive urothelial carcinoma from breast cancer.

Prognostic Impact and Spatial Interplay of Immune Cells in Urothelial Cancer

BACKGROUND

Quantity and the spatial relationship of specific immune cell types can provide prognostic information in bladder cancer.

OBJECTIVE

To characterize the spatial interplay and prognostic role of different immune cell subpopulations in bladder cancer.

DESIGN, SETTING, AND PARTICIPANTS

A total of 2463 urothelial bladder carcinomas were immunostained with 21 antibodies using BLEACH&STAIN multiplex fluorescence immunohistochemistry in a tissue microarray format and analyzed using a framework of neuronal networks for an image analysis.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Spatial immune parameters were compared with histopathological parameters and overall survival data.

RESULTS AND LIMITATIONS

The identification of > 300 different immune cell subpopulations and the characterization of their spatial relationship resulted in numerous spatial interaction patterns. Thirty-nine immune parameters showed prognostic significance in univariate analyses, of which 16 were independent from pT, pN, and histological grade in muscle-invasive bladder cancer. Among all these parameters, the strongest association with prolonged overall survival was identified for intraepithelial CD8+ cytotoxic T cells (time-dependent area under receiver operating characteristic curve [AUC]: 0.70), while stromal CD8+ T cells were less relevant (AUC: 0.65). A favorable prognosis of inflamed cancers with high levels of "exhaustion markers" suggests that TIM3, PD-L1, PD-1, and CTLA-4 on immune cells do not hinder antitumoral immune response in tumors rich of tumor infiltrating immune cells.

CONCLUSIONS

The density of intraepithelial CD8+ T cells was the strongest prognostic feature in muscle-invasive bladder cancer. Given that tumor cell killing by CD8+ cytotoxic T lymphocytes through direct cell-to-cell-contacts represents the "terminal end route" of antitumor immunity, the quantity of "tumor cell adjacent CD8+ T cells" may constitute a surrogate for the efficiency of cancer recognition by the immune system that can be measured straightaway in routine pathology as the CD8 labeling index.

PATIENT SUMMARY

Quantification of intraepithelial CD8+ T cells, the strongest prognostic feature identified in muscle-invasive bladder cancer, can easily be assessed by brightfield immunohistochemistry and is therefore "ready to use" for routine pathology.

Loss of Upk1a and Upk1b expression is linked to stage progression in urothelial carcinoma of the bladder

BACKGROUND

Uroplakin-1a (Upk1a) and uroplakin-1b (Upk1b) have recently been identified as diagnostic markers for the distinction of urothelial carcinomas from other solid tumor entities. Both proteins play an important role in the stabilization and strengthening of epithelial cells that line the bladder.

METHODS

To evaluate the prognostic role of uroplakin expression in urothelial carcinomas, more than 2700 urothelial neoplasms were analyzed in a tissue microarray format by immunohistochemistry. To further assess the diagnostic role of uroplakin immunohistochemistry, results were compared with preexisting GATA3 data.

RESULT

The fraction of Upk1a/Upk1b positive cases decreased slightly from pTaG2 low-grade (88% positive for Upk1a/87% positive for Upk1b) and pTaG2 high-grade (92%/89%) to pTaG3 (83%/88%; p > 0.05) and was lower in muscle-invasive (pT2-4) carcinomas (42%/64%; p < 0.0001/p < 0.0001 for pTa vs. pT2-4). Within pT2-4 carcinomas, high expression of Upk1a and Upk1b was linked to nodal metastasis and lymphatic vessel infiltration (p < 0.05) but unrelated to patient outcome. There were significant associations between Upk1a, Upk1b and GATA3 immunostaining (p < 0.0001 each), but 11% of GATA3 negative cancers were Upk1a/b positive and 8% of Upk1a/b negative cancers were GATA3 positive. Absence of GATA3/Upk1a/b staining was significantly linked to poor patient survival in the subgroup of 126 pT4 carcinomas (p = 0.0004) but not in pT2 and pT3 cancers.

CONCLUSIONS

In summary, the results of our study demonstrate that Upk1a and/or Upk1b immunohistochemistry can complement GATA3 for the distinction of urothelial carcinomas. Furthermore, a progressive loss of Upk1a/b expression during stage progression and a prognostic role of the combination GATA3/Upk1a/Upk1b in pT4 carcinomas is evident.

Altered p53/p16 expression is linked to urothelial carcinoma progression but largely unrelated to prognosis in muscle-invasive tumors

BACKGROUND

Most inactivating p53 mutations result in a nuclear p53 accumulation - detectable by immunohistochemistry (IHC). p53 alterations leading to a complete lack of p53 protein and absence of immunostaining do also occur - not easily detectable by IHC. p16 is upregulated in p53 inactivated cells. We hypothesized that a positive p16 IHC may help to distinguish p53 inactivation in IHC negative cases.

MATERIAL AND METHODS

We investigated p53 and p16 immunostaining on 2710 urothelial bladder carcinomas in a tissue microarray format to understand their impact in relation to clinicopathological parameters of disease progression and patient outcome.

RESULTS

p16 immunostaining was absent in normal urothelium but occurred in 63.5% (30.4% strong) of cancers. p16 strongly positive cases increased from pTaG2 low-grade (9.6%) to pTaG3 high-grade tumors (46.5%, p < .0001) but decreased from pTaG3 to pT4 (33.3%; p = .0030). Among pT2-4 carcinomas, p16 positivity was linked to high-grade (p = .0005) but unrelated to overall survival. p53 staining was negative in 8.4%, very weak in 15.4%, weak in 55.3%, strong in 4.7%, and very strong in 16.2% cancers. p53 negative (potentially p53 null phenotype), strong, and very strong p53 positivity increased from pTaG2 low-grade to pTaG3 high-grade tumors (p < .0001) and from pTaG3 to pT2-4 cancers (p = .0007). p53 staining was largely unrelated to histopathological parameters or patient prognosis among pT2-4 carcinomas, except of p53 strong/very strong immunostaining. p16 expression predominated in tumors with very strong, strong, and negative p53 staining and the combination of p53 negative/p16 strongly positive cancers was linked to features of tumor aggressiveness.

CONCLUSION

Aberrant p53 and p16 immunostaining increases during grade and stage progression although p53 negative and p16 positive immunostaining lack prognostic significance in pT2-4 carcinomas. Potential diagnostic features are that high level p16 expression is limited to neoplastic urothelium and p53 null phenotype to aggressive cancers (grade 3 and invasive).

Automated Prognosis Marker Assessment in Breast Cancers Using BLEACH&STAIN Multiplexed Immunohistochemistry

Prognostic markers in routine clinical management of breast cancer are often assessed using RNA-based multi-gene panels that depend on fluctuating tumor purity. Multiplex fluorescence immunohistochemistry (mfIHC) holds the potential for an improved risk assessment. To enable automated prognosis marker detection (i.e., progesterone receptor [PR], estrogen receptor [ER], androgen receptor [AR], GATA3, TROP2, HER2, PD-L1, Ki67, TOP2A), a framework for automated breast cancer identification was developed and validated involving thirteen different artificial intelligence analysis steps and an algorithm for cell distance analysis using 11+1-marker-BLEACH&STAIN-mfIHC staining in 1404 invasive breast cancers of no special type (NST). The framework for automated breast cancer detection discriminated normal glands from malignant glands with an accuracy of 98.4%. This approach identified that five (PR, ER, AR, GATA3, PD-L1) of nine biomarkers were associated with prolonged overall survival (p ≤ 0.0095 each) and two of these (PR, AR) were found to be independent risk factors in multivariate analysis (p ≤ 0.0151 each). The combined assessment of PR-ER-AR-GATA3-PD-L1 as a five-marker prognosis score showed strong prognostic relevance (p < 0.0001) and was an independent risk factor in multivariate analysis (p = 0.0034). Automated breast cancer detection in combination with an artificial intelligence-based analysis of mfIHC enables a rapid and reliable analysis of multiple prognostic parameters. The strict limitation of the analysis to malignant cells excludes the impact of fluctuating tumor purity on assay precision.

Cadherin-16 (CDH16) immunohistochemistry: a useful diagnostic tool for renal cell carcinoma and papillary carcinomas of the thyroid

Cadherin-16 (CDH16) plays a role in the embryonal development in kidney and thyroid. Downregulation of CDH16 RNA was found in papillary carcinomas of the thyroid. To determine the expression of CDH16 in tumors and to assess the diagnostic utility a tissue microarray containing 15,584 samples from 152 different tumor types as well as 608 samples of 76 different normal tissue types was analyzed. A membranous CDH16 immunostaining was predominantly seen in thyroid, kidney, cauda epididymis, and mesonephric remnants. In the thyroid, CDH16 staining was seen in 100% of normal samples, 86% of follicular adenomas, 60% of follicular carcinomas, but only 7% of papillary carcinomas (p < 0.0001). CDH16 positivity was frequent in nephrogenic adenomas (100%), oncocytomas (98%), chromophobe (97%), clear cell (85%), and papillary (76%) renal cell carcinomas (RCCs), various subtypes of carcinoma of the ovary (16-56%), various subtyped of carcinomas of the uterus (18-40%), as well as in various subtypes of neuroendocrine neoplasms (4-26%). Nineteen further tumor entities showed a weak to moderate CDH16 staining in up to 8% of cases. Our data suggest CDH16 as a potential diagnostic marker-as a part of a panel-for the identification of papillary carcinomas of the thyroid, nephrogenic adenomas, and the distinction of renal cell tumors from other neoplasms.

Abstract 3436: Reduced p63 expression is linked to a low density of regulatory T-cells and unfavorable prognosis in muscle-invasive urothelial carcinoma of the bladder

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.

Abstract 5438: The combination of artificial intelligence and BLEACH&STAIN multiplex fluorescence immunohistochemistry facilitates automated prostate and breast cancer detection

Background: Automated prognosis marker assessment in prostate and breast cancer using immunohistochemistry is currently hampered by the lack of a reliable differentiation between benign and malignant glands. To evaluate the patient’s risk in routine clinical practice in prostate cancer prognosis parameters such as the Gleason grading, that are accompanied by a high interobserver variability are used. In breast cancer multi-gene panels are used that are influenced by fluctuating tumor purity. A reproducible prognostic evaluation is lacking in both tumor entities.

Design: To enable automated prognosis marker quantification, we have developed and validated a framework for automated prostate and breast cancer detection that comprises three different artificial intelligence analysis steps and an algorithm for cell-distance analysis of multiplex fluorescence immunohistochemistry. Pan-cytokeratin (panCK) antibodies were used to detect epithelial cells and antibodies directed against Myosin and p63 were used to identify basal cells.

Results: The optimal distance between Myosin+ and p63+ basal cells and benign panCK+ cells was identified as 25 µm in breast and 23 µm in prostate cancer and used to exclude benign glands from the analysis combined with several deep learning-based algorithms. Our framework discriminated normal glands from malignant glands with an AUC of 0.96 in breast and 0.98 % in prostate cancer. The approach for automated prostate and breast cancer detection, by excluding benign gland from the analysis, improved the predictive performance of prognosis markers significantly (p&lt;0.001). To compare the multiplex fluorescence immunohistochemistry-based (mfIHC) automated prognosis marker assessment with “classical” bright field-based automated prostate cancer detection for prognosis marker assessment in a cohort of 30 biopsies from routine clinical practice prognosis markers were manually assessed and set as gold standard. An excellent agreement between the mfIHC-based automated cancer detection and the reference manual cancer identification was found (intraclass correlation [ICC]: 0.94 [95% CI 0.87 - 0.97]).

Conclusion: Automated prostate and breast cancer identification enables fully automated prognosis marker assessment in routine clinical practice using deep learning and multiplex fluorescence immunohistochemistry. BLEACH&STAIN as well as other multiplex fluorescence immunohistochemistry approaches that enable the simultaneous analysis of 20+ biomarkers can be used to established prognosis panels that can be now assessed in an automated manner.

Citation Format: Tim Mandelkow, Gisa Mehring, Elena Bady, Maximilian Lennartz, Christoph Fraune, Frank Jacobsen, Natalia Gorbokon, Till Krech, Eike Burandt, Anne Menz, Ria Uhlig, Till S. Clauditz, Guido Sauter, Markus Graefen, Sarah Minner, Niclas C. Blessin. The combination of artificial intelligence and BLEACH&STAIN multiplex fluorescence immunohistochemistry facilitates automated prostate and breast cancer detection. [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 5438.

Abstract 5144: Spatial T-cell atlas in more than 100 different tumor entities using BLEACH&STAIN

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.

Cytokeratin 20 expression is linked to stage progression and to poor prognosis in advanced (pT4) urothelial carcinoma of the bladder

Cytokeratin 20 (CK20) expression is limited to umbrella cells in the normal urothelium. Since CK20 is often upregulated in neoplastic urothelial cells including dysplasia and carcinoma in situ, immunohistochemical CK20 analysis is often used for the assessment of bladder biopsies. CK20 expression is a feature of luminal bladder cancer subtype, but its prognostic relevance is disputed. In this study, we investigated CK20 on >2700 urothelial bladder carcinomas in a tissue microarray format by immunohistochemistry. Cytoplasmic and membranous CK20 staining was seen in 1319 (51.8%) cancers. The fraction of CK20 positive and especially strongly positive cases increased from pTaG2 low grade (44.5% strongly positive) and pTaG2 high grade (57.7%) to pTaG3 high grade (62.3%; p = 0.0006) but was lower in muscle-invasive (pT2-4) carcinomas (51.1% in all pTa vs. 29.6% in pT2-4; p < 0.0001). Within pT2-4 carcinomas, CK20 positivity was linked to nodal metastasis and lymphatic vessel invasion (p < 0.0001 each) and to venous invasion (p = 0.0177). CK20 staining was unrelated to overall patient survival if all 605 pT2-4 carcinomas were jointly analyzed but subgroup analyses revealed a significant association of CK20 positivity with favorable prognosis in 129 pT4 carcinomas (p = 0.0005). CK20 positivity was strongly linked to the expression of GATA3 (p < 0.0001), another feature of luminal bladder cancer. The combined analysis of both parameters showed best prognosis for luminal A (CK20+/GATA3+, CK20+/GATA3-) and worst outcome for luminal B (CK20-/GATA3+) and basal/squamous (CK20-/GATA3-) in pT4 urothelial carcinomas (p = 0.0005). In summary, the results of our study demonstrate a complex role of CK20 expression in urothelial neoplasms including neoexpression in pTa tumors, a subsequent loss of CK20 expression in a subset of tumors progressing to muscle-invasion, and a stage dependent prognostic role in muscle-invasive cancers.

BLEACH&STAIN 15-marker multiplexed imaging in 3098 human carcinomas reveals 6 major PD-L1-driven immune phenotypes with distinct spatial orchestration

Multiplex fluorescence immunohistochemistry (mfIHC) approaches were yet either limited to 6 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, CD31) in 3098 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 negative) were either inflamed or non-inflamed. In the inflamed PD-L1+patients, spatial analysis revealed that an elevated intratumoral M2-macrophages as well as CD11c+dendritic cell infiltration (p<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<0.001 each). In breast cancer, the PD-L1 fluorescence intensity on tumor cells showed a significantly higher predictive performance for overall survival (AUC: 0.72, p<0.001) compared to 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 and enables to study the prognostic relevance of more than 130 immune cell subpopulations.

Automated Ki-67 labeling index assessment in prostate cancer using artificial intelligence and multiplex fluorescence immunohistochemistry

The Ki-67 labeling index (Ki-67 LI) is a strong prognostic marker in prostate cancer, although its analysis requires cumbersome manual quantification of Ki-67 immunostaining in 200-500 tumor cells. To enable automated Ki-67 LI assessment in routine clinical practice, a framework for automated Ki-67 LI quantification, which comprises three different artificial intelligence analysis steps and an algorithm for cell-distance analysis of multiplex fluorescence immunohistochemistry (mfIHC) staining, was developed and validated in a cohort of 12,475 prostate cancers. The prognostic impact of the Ki-67 LI was tested on a tissue microarray (TMA) containing one 0.6 mm sample per patient. A 'heterogeneity TMA' containing three to six samples from different tumor areas in each patient was used to model Ki-67 analysis of multiple different biopsies, and 30 prostate biopsies were analyzed to compare a 'classical' bright field-based Ki-67 analysis with the mfIHC-based framework. The Ki-67 LI provided strong and independent prognostic information in 11,845 analyzed prostate cancers (p < 0.001 each), and excellent agreement was found between the framework for automated Ki-67 LI assessment and the manual quantification in prostate biopsies from routine clinical practice (intraclass correlation coefficient: 0.94 [95% confidence interval: 0.87-0.97]). The analysis of the heterogeneity TMA revealed that the Ki-67 LI of the sample with the highest Gleason score (area under the curve [AUC]: 0.68) was as prognostic as the mean Ki-67 LI of all six foci (AUC: 0.71 [p = 0.24]). The combined analysis of the Ki-67 LI and Gleason score obtained on identical tissue spots showed that the Ki-67 LI added significant additional prognostic information in case of classical International Society of Urological Pathology grades (AUC: 0.82 [p = 0.002]) and quantitative Gleason score (AUC: 0.83 [p = 0.018]). The Ki-67 LI is a powerful prognostic parameter in prostate cancer that is now applicable in routine clinical practice. In the case of multiple cancer-positive biopsies, the sole automated analysis of the worst biopsy was sufficient. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

GATA3 Expression in Human Tumors: A Tissue Microarray Study on 16,557 Tumors

INTRODUCTION

GATA3 is a transcription factor involved in epithelial cell differentiation. GATA3 immunostaining is used as a diagnostic marker for breast and urothelial cancer but can also occur in other neoplasms.

METHODS

To evaluate GATA3 in normal and tumor tissues, a tissue microarray containing 16,557 samples from 131 different tumor types and subtypes and 608 samples of 76 different normal tissue types was analyzed by immunohistochemistry.

RESULTS

GATA3 positivity was found in 69 different tumor types including 23 types (18%) with at least one strongly positive tumor. Highest positivity rates occurred in noninvasive papillary urothelial carcinoma (92-99%), lobular carcinoma (98%), carcinoma of no special type of the breast (92%), basal cell carcinoma of the skin (97%), invasive urothelial carcinoma (73%), T-cell lymphoma (23%), adenocarcinoma of the salivary gland (16%), squamous cell carcinoma of the skin (16%), and colorectal neuroendocrine carcinoma (12%). In breast cancer, low GATA3 staining was linked to high pT stage (p = 0.03), high BRE grade (p < 0.0001), HER2 overexpression (p = 0.0085), estrogen and progesterone receptor negativity (p < 0.0001 each), and reduced survival (p = 0.03).

CONCLUSION

Our data demonstrate that GATA3 positivity can occur in various tumor entities. Low levels of GATA3 reflect cancer progression and poor patient prognosis in breast cancer.

PD-L1 expression and CD8 positive lymphocytes in human neoplasms: A tissue microarray study on 11,838 tumor samples

BACKGROUND

Programmed death ligand 1 (PD-L1) is the target of immune checkpoint inhibitor therapies in a growing number of tumor types, but a unanimous picture on PD-L1 expression across cancer types is lacking.

MATERIALS AND METHODS

We analyzed immunohistochemical PD-L1 expression in 11,838 samples from 118 human tumor types and its relationship with tumor infiltrating CD8 positive lymphocytes.

RESULTS

At a cut-off level of 10% positive tumor cells, PD-L1 positivity was seen in 85 of 118 (72%) tumor types, including thymoma (100% positive), Hodgkin's lymphoma (93%), anaplastic thyroid carcinoma (76%), Kaposi sarcoma (71%), sarcomatoid urothelial carcinoma (71%), and squamous cell carcinoma of the penis (67%), cervix (65%), floor of the mouth (61%), the lung (53%), and pharynx (50%). In immune cells, PD-L1 positivity was detectable in 103 (87%) tumor types, including tumors of haematopoetic and lymphoid tissues (75% to 100%), Warthin tumors of the parotid glands (95%) and Merkel cell carcinoma (82%). PD-L1 positivity in tumor cells was significantly correlated with the number of intratumoral CD8 positive lymphocytes across all tumor types as well as in individual tumor types, including serous carcinoma of the ovary, invasive breast carcinoma of no special type, intestinal gastric adenocarcinoma, and liposarcoma (p< 0.0001 each).

CONCLUSIONS

PD-L1 expression in tumor and inflammatory cells is found in a wide range of human tumor types. Higher rates of tumor infiltrating CD8 positive lymphocytes in PD-L1 positive than in PD-L1 negative cancers suggest that the antitumor immune response may trigger tumoral PD-L1 expression.

GATA3 expression loss is linked to stage progression but is unrelated to prognosis in muscle-invasive urothelial carcinoma of the bladder

The transcription factor GATA binding protein 3 (GATA3) is commonly used in surgical pathology as a diagnostic marker to distinguish urothelial carcinomas from other cancer entities. However, the clinical relevance of GATA3 expression in urothelial bladder cancer is not completely clarified. In this study, we investigated GATA3 immunostaining on 2710 urothelial bladder carcinomas on a tissue microarray platform by using two different antibodies to better understand its impact in relation to pathological parameters of disease progression and patient outcome. Nuclear GATA3 immunostaining was regularly seen in normal urothelium and found in 74%/82% of interpretable urothelial neoplasms depending on the antibody used. Within pTa tumors, the rate of GATA3 positive tumors decreased with advancing grade. GATA3 positivity was seen in 98.6%/99.8% of pTaG2 low-grade, 98.6%/100% of pTaG2 high-grade, and 94.9%/99.2% of pTaG3 high-grade tumors (P = .0002). As compared to pTa tumors, GATA3 positivity was markedly less common in muscle-invasive urothelial carcinoma (59.9%/71.6%; P < .0001). Within pT2-4 cancers, high-level GATA3 immunostaining was associated with the presence of lymph node metastasis (P = .0034), and blood vessel (P = .0290) or lymphatic invasion (P = .0005) but unrelated to pT stage. GATA3 immunostaining results for both antibodies were not associated with overall survival in 586 patients treated by cystectomy for pT2-4 urothelial carcinoma. The results of our study identify GATA3 expression as a frequent event in noninvasive urothelial carcinomas with favorable tumor features. Loss of GATA3 immunostaining is linked with muscle-invasive disease but is largely unrelated to pathological parameters and patient prognosis.

Automated Prostate Cancer Identification Facilitates Prognosis Marker Assessment in 11,845 Prostate Cancers Using Artificial Intelligence and BLEACH&STAIN Multiplex Fluorescence Immunohistochemistry

Introduction/Objective

Although most prostate cancers behave in an indolent manner, a small proportion is highly aggressive. To evaluate the patient’s risk, several prognosis parameters, that can be accompanied by a high interobserver variability has been established. A reproducible prognostic evaluation is lacking.

Methods/Case Report

To enable automated prognosis marker quantification, we have developed and validated a framework for automated prostate cancer detection that comprises three different artificial intelligence analysis steps and an algorithm for cell-distance analysis of BLEACH&STAIN multiplex fluorescence immunohistochemistry (mfIHC). We have used the analysis framework to measure PSA, PSMA, INSM1, AR, Ki-67, CD56, Chromogranin A, Synaptophysin, CD8 in a cohort of 11,845 prostate cancers.

Results (if a Case Study enter NA)

The Ki-67 labeling index provided the strongest prognostic information among all analyzed prognosis marker in 11,845 successfully analyzed prostate cancers (p&lt;0.001 each). The combined analysis of the Ki67-LI and Gleason grades obtained on identical tissue spots showed that the Ki67-LI added significant additional prognostic information in case of classical ISUP grades (AUC:0.82 [p=0.002]) and quantitative Gleason grades (AUC:0.83 [p=0.018]). Several combinations of these 8 prognosis markers were combined to prognosis scores and used for unsupervised clustering to identify a proportion of prostate cancers with a particularly poor prognosis (p&lt;0.001 each).

Conclusion

Automated prostate cancer identification enables fully automated prognosis marker assessment in routine clinical practice using deep learning and BLEACH&STAIN mfIHC.

Automated prognosis marker assessment in 2,004 breast cancers using an artificial intelligence-based framework for BLEACH&STAIN multiplex fluorescence immunohistochemistry

Introduction/Objective

Introduction: Prognostic markers in routine clinical practice of breast cancer are currently assessed using multi-gene panels. However, the fluctuating tumor purity can reduce the predictive value of such tests. Immunohistochemistry holds the potential for a better risk assessment.

Methods/Case Report

Methods: To enable automated prognosis marker detection (i.e. HER2, GATA3, progesterone-[PR], estrogen- [ER], and androgen receptor [AR], TOP2A, Ki-67, TROP2), we have developed and validated a framework for automated breast cancer identification, which comprises three different artificial intelligence analysis steps and an algorithm for cell-distance analysis of 11 + 1 marker BLEACH&STAIN multiplex fluorescence immunohistochemistry (mfIHC) staining in 2,004 breast cancers.

Results (if a Case Study enter NA)

Results: The optimal distance between Myosin+ basal cells and benign panCK+ cells was identified as 25 µm and used to exclude benign glands from the analysis combined with several deep learning-based algorithms. Our framework discriminated normal glands from malignant glands with an AUC of 0.96. The accuracy of the approach was also validated by well-characterized biological findings, such as the identification of 13% HER2+, 73% PR+/ER+, and 14 triple negative cases. Furthermore, the automated assessment of GATA3, PR, ER, TOP2A-LI, Ki-67-LI and TROP2 was significantly liked to the tumor grade (p&lt;0.001each). Furthermore, a high expression level of HER2, GATA3, PR, and ER was associated with a prolonged overall survival (p≥0.002 each).

Conclusion

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.

Cadherin-16 (CDH16) Immunohistochemistry: A Novel Diagnostic Tool for Renal Cell Carcinoma and Papillary Carcinomas of the Thyroid

Introduction/Objective

Introduction: Cadherin-16 (CDH16), also termed kidney specific cadherin (ksp-cadherin), is a membrane-associated glycoprotein with a role in the embryonal development of tubules in kidney and thyroid. Downregulation of CDH16 RNA was found in papillary carcinomas of the thyroid.

Methods/Case Report

Methods: A set of tissue microarrays containing 14,978 samples from 149 different tumor types and subtypes as well as 608 samples of 76 different normal tissue types was analyzed by immunohistochemistry to determine the expression of CDH16 in cancer and to assess the diagnostic utility of immunohistochemical CDH16 analysis.

Results (if a Case Study enter NA)

Results: Among normal tissues, a membranous CDH16 immunostaining predominated in thyroid, kidney, cauda epididymis, and in mesonephric remnants. In the thyroid, CDH16 staining was seen in 100% of normal samples, 83% of follicular adenomas, 58% of follicular carcinomas, but in only 9% of papillary carcinomas (p&lt;0.0001). Among non-thyroidal tumors, CDH16 positivity was particularly frequent in nephrogenic adenomas (100%), oncocytomas (98%), chromophobe (97%), clear cell (85%), and papillary (76%) renal cell carcinomas (RCCs), clear cell (56%), mucinous (36%), and endometroid (16%) carcinomas as well as carcinosarcomas (18%) of the ovary, adenocarcinomas of the cervix uteri (40%), serous (33%), clear cell (33%), and endometroid carcinomas (18%) of the endometrium and in various subtypes of neuroendocrine neoplasms (4-26%).

Conclusion

Given the massive loss of CDH16 expression in &gt;90% of papillary carcinomas of the thyroid, CDH16 is a highly useful diagnostic marker for these tumors. CDH16 immunohistochemistry is also useful for the identification of nephrogenic adenomas and the distinction of renal cell carcinomas from other neoplasms.

A Comparative Analysis of CPA1, bcl10 and Chymotrypsin for the Distinction of Pancreatic Acinar Cell Carcinomas

Introduction/Objective

Introduction: Pancreatic acinar cell carcinoma (PACC) is a rare tumor of the pancreas with an intermediate prognosis as compared to pancreatic neuroendocrine tumors (PNE) and pancreatic ductal adenocarcinoma (PDAC) from which it may be difficult to distinguish by morphology alone.

Methods/Case Report

Methods: To study was the efficiency of immunohistochemical markers, 18 PACCs, 531 PDACs, 64 PNEs, 117 extra pancreatic neuroendocrine neoplasms (EPNN), 826 colorectal carcinomas (CRC) and 252 gastric carcinomas (GC) were analyzed with antibodies for CPA1 (MSVA-601M), bcl10 (Santa Cruz sc5273), and chymotrypsin (Biorad 2100-0657) in a tissue microarray format.

Results (if a Case Study enter NA)

Results: CPA1 was positive in 18 of 18 (100%) of PACCs, 0 of 49 (0%) of PNEs, 0 of 88 (0%) of EPNNs, 10 of 404 (2.5%) of CRCs, and 0 of 178 (0%) of GCs. Chymotrypsin was positive in 16 (87,5%) PACCs, 1 (2%) PNEs, 2 (2.3%) EPNNs, 10 (2.5%) CRCs, and 1 (0.6%) GCs. Bcl10 was positive in 18 (100%) PACCs, 2 (4.1%) PNEs, 5 (1%) EPNNs, 109 (27%) CRCs, and 18 (10%) GCs. These data resulted in a sensitivity and specificity of 100%/99.2% for CPA1, 100%/88.4% for bcl10, and 94.4%/98.6% for chymotrypsin.

Conclusion

CPA1 and chymotrypsin are both highly specific and sensitive for ACC while bcl10 is sensitive but has markedly lower specificity. Because all “false positive” cases identified by CPA1 were CRCs that only showed a positive staining in goblet cells and an identical staining pattern was observed in all these cases for chymotrypsin and bcl10, a pancreatic origin of the mucus in these goblet cells is concluded.

DOG1 overexpression is associated with mismatch repair deficiency and BRAF mutations but unrelated to cancer progression in colorectal cancer

INTRODUCTION

The transmembrane channel protein DOG1 (Discovered on GIST1) is normally expressed in the gastrointestinal interstitial cells of Cajal and also in gastrointestinal stroma tumors arising from these cells. However, there is also evidence for a relevant role of DOG1 expression in colorectal cancers. This study was undertaken to search for associations between DOG1 expression and colon cancer phenotype and key molecular alterations.

METHODS

A tissue microarray containing samples from more than 1,800 colorectal cancer patients was analyzed by immunohistochemistry.

RESULTS

DOG1 immunostaining was detected in 503 (30.2%) of 1,666 analyzable colorectal cancers and considered weak in 360 (21.6%), moderate in 78 (4.7%), and strong in 65 (3.9%). Strong DOG1 immunostaining was associated with advanced pT stage (p=0.0367) and nodal metastases (p=0.0145) but these associations were not retained in subgroups of 1,135 mismatch repair proficient and 86 mismatch repair deficient tumors. DOG1 positivity was significantly linked to several molecular tumor features including mismatch repair deficiency (p=0.0034), BRAF mutations (p<0.0001), nuclear p53 accumulation (p=0.0157), and PD-L1 expression (p=0.0199) but unrelated to KRAS mutations and the density of tumor infiltrating CD8 positive lymphocytes.

CONCLUSION

Elevated DOG1 expression is frequent in colorectal cancer and significantly linked to important molecular alterations. However, DOG1 overexpression is largely unrelated to histopathological parameters of cancer aggressiveness and may thus not serve as a prognostic parameter for this tumor entity.

Abstract 1861: Trophoblast cell surface antigen 2 (TROP2) expression in human tumors: A tissue microarray study on 18,563 tumors

Trophoblast cell surface antigen 2 (TROP2) is the target of sacituzumab govitecan (SG), an antibody-drug conjugate that was recently approved for previously treated triple negative breast cancer and urothelial carcinomas. To comprehensively determine TROP2 expression in normal and neoplastic tissues, a tissue microarray containing 18,563 samples from 150 different tumor types and subtypes as well as 608 samples of 76 different normal tissue types was analyzed by immunohistochemistry. TROP2 positivity was found in most normal epithelial cell types and in 109 of 150 tumor categories, including 92 of 95 epithelial tumor categories. Particularly high rates of TROP2 positivity and highest expression levels were seen in squamous cell carcinomas of various origins and various categories of urothelial, breast, prostate, pancreatic, and ovarian cancers (&gt;95% positive). High TROP2 expression was linked to advanced stage (p=0.0069) and nodal metastasis (p&lt;0.0001) in colorectal cancer as well as to nodal metastasis in gastric adenocarcinoma (p=0.0246) and papillary thyroid cancer (p=0.0013). Low TROP2 expression was linked to advanced stage in urothelial carcinoma (p&lt;0.0001), high pT (p=0.0024) and high grade (p&lt;0.0001) in breast cancer, as well as with high grade (p=0.0005) and pT stage (p=0.0009) in papillary renal cell carcinomas. Associations between TROP2 expression and clinicopathological features were not found in clear cell renal cell carcinomas, high grade serous ovarian carcinomas, pancreatic adenocarcinomas and in endometroid endometrium carcinomas. In summary, TROP2 is abundantly expressed in a broad range of epithelial neoplasms. Both TROP2 upregulation and downregulation can be associated with cancer progression in a tumor type dependent manner. As anti-TROP2 cancer drugs have demonstrated efficiency and induce tolerable side effects they may be applicable to a broad range of tumor entities in the future.

Citation Format: David Dum, Claudia Hube-Magg, Ronald Simon, Elena Bady, Tim Mandelkow, Niclas C. Blessin, Maximilian Lennartz, Guido Sauter, Sarah Minner, Andreas M. Luebke. Trophoblast cell surface antigen 2 (TROP2) expression in human tumors: A tissue microarray study on 18,563 tumors [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 1861.

Abstract 597: BLEACH&STAIN 15 marker multiplexed imaging in 3098 human carcinomas revealed six major PD-L1 driven immune phenotypes with distinct spatial orchestration

Multiplex fluorescence immunohistochemistry (mfIHC) approaches were yet either limited to 6 markers or limited to a small (1.5cmx1.5cm) tissue size that hampers translational studies on large tissue microarray (TMA) cohorts. To be able to assess more marker in a large patient cohort, we have developed a BLEACH&STAIN multiplex fluorescence immunohistochemistry approach that enabled the simultaneous analysis of 15 biomarkers. To study the relationship of PD-L1 expression on multiple different cell types and the relationship with various lymphocyte subtypes, PD-L1, PD-1, CTLA-4, panCK, CD68, CD163, CD11c, iNOS, CD3, CD8, CD4, FOXP3, CD20, Ki67, and CD31 were analyzed in 3098 tumor samples from 44 different tumor types. An artificial intelligence-based framework - incorporating three different deep learning systems - for automated marker quantification on tumor as well as immune cells was further established to study the spatial interplay between PD-L1 expression and the composition of tumor infiltrating leucocytes (TILs). Comparing the automated deep learning-based PD-L1 quantification with conventional brightfield PD-L1 data revealed a high concordance in tumor cells (p&lt;0.0001) as well as immune cells (p&lt;0.0001) and an accuracy of the automated PD-L1 quantification ranging from 90% to 95.2%. Unsupervised clustering showed that a major proportion of the three PD-L1 phenotypes (i.e., PD-L1+ tumor and immune cells [G1], PD-L1+ immune cells [G2], PD-L1 negative [G3]) were either inflamed (G1.1, G2.1, G3.1) or non-inflamed (G1.2, G2.2, G3.2). In the inflamed PD-L1+ patients (G.1.1), spatial analysis revealed that an elevated intratumoral CD68+CD163+ M2 macrophages as well as CD11c+ dendritic cell 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, a particular poor prognosis for the non-inflamed PD-L1+ breast cancer patients (G1.2, G2.2) was found and the PD-L1 fluorescence intensity on tumor cells showed a significantly higher predictive performance for overall survival with an area under receiver operating curves (AUC) of 0.72 (p&lt;0.001) than the percentage of PD-L1+ tumor cells (AUC: 0.54). In conclusion, BLEACH&STAIN mfIHC in combination with a deep learning-based framework for automated PD-L1 assessment on tumor and immune cells enabled a rapid and comprehensive assessment of PD-L1 expression in different cell types and their interrelation with inflammatory cells. Our approach enabled the identification of six major PD-L1 phenotypes ranging from an PD-L1+ tumor cell inflamed phenotype (G1.1) with a spatial T-cell exclusion to a non-inflamed PD-L1+ immune cell phenotype showing a particular poor prognosis (G2.2) to a non-inflamed PD-L1 negative phenotype (G3.2).

Citation Format: Elena Bady, Katharina Möller, Tim Mandelkow, Ronald Simon, Maximilian Lennartz, Claudia Hube-Magg, Guido Sauter, Niclas C. Blessin. BLEACH&STAIN 15 marker multiplexed imaging in 3098 human carcinomas revealed six major PD-L1 driven immune phenotypes with distinct spatial orchestration [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 597.

Abstract 483: Automated Ki67-LI assessment in prostate cancer using artificial intelligence in multiplex fluorescence immunohistochemistry

The Ki67 labeling index (Ki67-LI) is a strong prognostic marker in prostate cancer. Its analysis requires cumbersome manual quantification of Ki67 immunostaining in at least 200 tumor cells. To enable automated Ki67-LI assessment in routine clinical practice, we have developed and validated a framework for automated Ki67-LI quantification, which comprises three different artificial intelligence analysis steps and an algorithm for cell-distance analysis of multiplex fluorescence immunohistochemistry staining. The prognostic impact of the Ki67-LI was tested on a tissue microarray (TMA) containing one sample each of 12475 prostate cancers. A “heterogeneity TMA” containing 3 to 6 samples from different tumor areas was used to model Ki67 analysis of multiple different biopsies. The Ki67-LI provided strong and independent prognostic information in 11845 successfully analyzed prostate cancers (p&lt;0.001 each). The analysis of the heterogeneity TMA revealed that the Ki67-LI of the sample with the highest Gleason score (AUC:0.68) was similarly prognostic as the mean Ki67-LI of all six foci (AUC:0.71 [p=0.24]). The combined analysis of the Ki67-LI and Gleason grades obtained on identical tissue spots showed that the Ki67-LI added significant additional prognostic information in case of classical ISUP grades (AUC:0.82 [p=0.002]) and quantitative Gleason grades (AUC:0.83 [p=0.018]). The Ki67-LI is a powerful prognostic parameter in prostate cancer, which can be efficiently analyzed in multiplex fluorescence IHC. In case of multiple cancer positive biopsies, the sole analysis of the worst biopsy can be sufficient.

Citation Format: Niclas C. Blessin, Tim Mandelkow, Elena Bady, Ronald Simon, Claudia Hube-Magg, Maximilian Lennartz, Guido Sauter, Markus Graefen, Stefan Steurer. Automated Ki67-LI assessment in prostate cancer using artificial intelligence in multiplex fluorescence immunohistochemistry [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 483.

Abstract 4148: Non-redundant upregulation of CD112R (PVRIG) and PD-1 on cytotoxic T-lymphocytes located in T-cell-nests of colorectal cancer

Focal T-lymphocyte aggregates occur commonly in colorectal cancer, but their biological significance is unknown. To study focal aggregates of T-lymphocytes, a deep learning-based framework for automated identification of T-cell accumulations (T-cell-nests) was developed using CD8, PD-1, CD112R, and Ki67 multiplex fluorescence immunohistochemistry. To evaluate the clinical significance of these parameters, a cohort of 523 colorectal cancers with clinical-follow up data was analyzed. The spatial analysis of locally enriched CD8+ T-cell densities and cell-to-cell contacts identified T-cell-nests in the tumor microenvironment of colorectal cancer. CD112R and PD-1 expression on CD8+ T-cells located in T-cell-nests was found elevated as compared to CD8+ T-cells in all other tumor compartments (p&lt;0.001 each). Although the highest mean CD112R expression on CD8+ T-cells was observed at the invasive margin, the PD-1 expression on CD8+ T-cells was elevated in the center of the tumor (p&lt;0.001 each). Across all tissue compartments, proliferating CD8+ T-cells showed higher relative CD112R and PD-1 expression compared to non-proliferating CD8+ T-cells (p&lt;0.001 each). Integration of all available spatial and immune checkpoint expression parameters (AUC: 0.65) revealed a superior predictive performance for overall survival compared to the commonly used CD8+ TILs density (AUC 0.57, p&lt;0.001). Cytotoxic T-cells with elevated CD112R and PD-1 expression levels are orchestrated in T-cells-nests of colorectal cancer, predict favorable patient’s outcome and the spatial non-redundancy underlies fundamental differences of both inhibitory immune checkpoints that provide a rationale for dual anti-CD112R/PD-1 immune checkpoint therapy.

Citation Format: Maximilian Lennartz, Cheng Yang, Tim Mandelkow, Elena Bady, Ronald Simon, Claudia Hube-Magg, Guido Sauter, Niclas C. Blessin. Non-redundant upregulation of CD112R (PVRIG) and PD-1 on cytotoxic T-lymphocytes located in T-cell-nests of colorectal 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 4148.

Abstract 1935: Interplay between TIM3+ immune cells and other immune checkpoints in more than 40 different human carcinoma entities using 18+1 BLEACH&STAIN mfIHC

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.

Abstract P069: Semi-automated validation and quantification of CTLA-4 in 90 different Tumor entities using multiple antibodies and artificial intelligence

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.

Semi-automated validation and quantification of CTLA-4 in 90 different tumor entities using multiple antibodies and artificial intelligence

CTLA-4 is an inhibitory immune checkpoint receptor and a negative regulator of anti-tumor T-cell function. This study is aimed for a comparative analysis of CTLA-4⁺ cells between different tumor entities. To quantify CTLA-4⁺ cells, 4582 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. Comparing both CTLA-4 antibodies revealed a clone dependent unspecific staining pattern 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 < 0.0001). A high CTLA-4⁺ cell density was linked to low pT category (p < 0.0001), absent lymph node metastases (p = 0.0354), and PD-L1 expression in tumor cells or inflammatory cells (p < 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 = 0.0026). Marked differences exist in the number of CTLA-4⁺ lymphocytes between tumors. Analyzing two independent antibodies by a deep learning framework can facilitate automated quantification of immunohistochemically analyzed target proteins such as CTLA-4.

Abstract P068: Automated cell type specific PD-L1 quantification by artificial intelligence using high throughput bleach & stain 15-marker multiplex fluorescence immunohistochemistry in human cancers

Introduction: The quantification of PD-L1 (programmed cell death ligand 1) has been used to predict patient's survival, to characterize the tumor immune microenvironment, and to predict response to immune checkpoint therapies. However, a framework to assess the PD-L1 status with a high interobserver reproducibility on tumor cells and different types of immune cells has yet to be established.

Methods: To study the impact of PD-L1 expression on the tumor immune microenvironment and patient outcome, a framework for fully automated PD-L1 quantification on tumor cells and immune cells was established and validated. Automated PD-L1 quantification was facilitated by incorporating three different deep learning steps for the analysis of more than 80 different neoplasms from more than 10'000 tumor specimens using a bleach & stain 15-marker multiplex fluorescence immunohistochemistry panel (i.e., PD-L1, PD-1, CTLA-4, panCK, CD68, CD163, CD11c, iNOS, CD3, CD8, CD4, FOXP3, CD20, Ki67, CD31). Clinicopathological parameter were available for more than 30 tumor entities and overall survival data were available for 1517 breast cancer specimens.

Results: Comparing the automated deep-learning based PD-L1 quantification with conventional brightfield PD-L1 data revealed a high concordance in tumor cells (p&lt;0.0001) as well as immune cells (p&lt;0.0001) and an accuracy of the automated PD-L1 quantification ranging from 90% to 95.2%. Across all tumor entities, the PD-L1 expression level was significantly higher in distinct macrophage/dendritic cell (DC) subsets (identified by CD68, CD163, CD11c, iNOS; p&lt;000.1) and in macrophages/DCs located in the Stroma (p&lt;0.0001) as compared to intratumoral macrophages/DC subsets. Across all different tumor entities, the PD-L1 expression was highly variable and distinct PD-L1 driven immune phenotypes were identified based on the PD-L1 intensity on both tumor and immune cells, the distance between non-exhausted T-cell subsets (i.e. PD-1 and CTLA-4 expression on CD3+CD8+ cytotoxic T-cells, CD3+CD4+ T-helper cells, CD3+CD4+FOXP3+ regulatory T-cells) and tumor cells as well as macrophage/(DC) subtypes. In breast cancer, the PD-L1 fluorescence intensity on tumor cells showed a significantly higher predictive performance for overall survival with an area under receiver operating curves (AUC) of 0.72 (p&lt;0.0001) than the percentage of PD-L1+ tumor cells (AUC: 0.54). In PD-L1 positive as well as negative breast cancers a close spatial relationship between T- cell subsets (CD3+CD4±CD8±FOXP3±PD-1±CTLA-4±) and Macrophage/DC subsets (CD68±CD163±CD11c±iNOS) was found prognostic relevant (p&lt;0.0001).

Conclusion: In conclusion, multiplex immunofluorescence PD-L1 assessment provides cutoff-free/continuous PD-L1 data which are superior to the conventional percentage of PD-L1+ tumor cells and of high prognostic relevance. The combined analysis of spatial PD-L1/PD-1 data and more than 20 different immune cell subtypes of the immune tumor microenvironment revealed distinct PD-L1 immune phenotypes.

Citation Format: Niclas C. Blessin, Elena Bady, Tim Mandelkow, Cheng Yang, Jonas B. Raedler, Ronald Simon, Christoph Fraune, Maximilian Lennartz, Sarah Minner, Eike Burandt, Doris Höflmayer, Guido Sauter, Katharina Möller, Sören A. Weidemann. Automated cell type specific PD-L1 quantification by artificial intelligence using high throughput bleach & stain 15-marker multiplex fluorescence immunohistochemistry in human cancers [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 P068.

Semi-automated validation and quantification of CTLA-4 in 90 different Tumor entities using multiple antibodies and artificial intelligence

Introduction/Objective

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+ entities. cells between different tumor

Methods/Case Report

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 (if a Case Study enter NA)

Results: Comparing both CTLA-4 antibodies revealed a clone dependent unspecific staining pattern 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 can facilitate automated quantification of immunohistochemically analyzed target proteins such as CTLA-4.

P02.03 Automated cell type specific PD-L1 quantification by artificial intelligence using high throughput bleach & stain 15-marker multiplex fluorescence immunohistochemistry in human cancers

Background

The quantification of PD-L1 (programmed cell death ligand 1) has been used to predict patient’s survival, to characterize the tumor immune microenvironment, and to predict response to immune checkpoint therapies. However, a framework to assess the PD-L1 status with a high interobserver reproducibility on tumor cells and different types of immune cells has yet to be established.

Materials and Methods

To study the impact of PD-L1 expression on the tumor immune microenvironment and patient outcome, a framework for fully automated PD-L1 quantification on tumor cells and immune cells was established and validated. Automated PD-L1 quantification was facilitated by incorporating three different deep learning steps for the analysis of more than 80 different neoplasms from more than 10’000 tumor specimens using a bleach & stain 15-marker multiplex fluorescence immunohistochemistry panel (i.e., PD-L1, PD-1, CTLA-4, panCK, CD68, CD163, CD11c, iNOS, CD3, CD8, CD4, FOXP3, CD20, Ki67, CD31). Clinicopathological parameter were available for more than 30 tumor entities and overall survival data were available for 1517 breast cancer specimens.

Results

Comparing the automated deep-learning based PD-L1 quantification with conventional brightfield PD-L1 data revealed a high concordance in tumor cells (p<0.0001) as well as immune cells (p<0.0001) and an accuracy of the automated PD-L1 quantification ranging from 90% to 95.2%. Across all tumor entities, the PD-L1 expression level was significantly higher in distinct macrophage/dendritic cell (DC) subsets (identified by CD68, CD163, CD11c, iNOS; p<000.1) and in macrophages/DCs located in the Stroma (p<0.0001) as compared to intratumoral macrophages/DC subsets. Across all different tumor entities, the PD-L1 expression was highly variable and distinct PD-L1 driven immune phenotypes were identified based on the PD-L1 intensity on both tumor and immune cells, the distance between non-exhausted T-cell subsets (i.e. PD-1 and CTLA-4 expression on CD3+CD8+ cytotoxic T-cells, CD3+CD4+ T-helper cells, CD3+CD4+FOXP3+ regulatory T-cells) and tumor cells as well as macrophage/(DC) subtypes. In breast cancer, the PD-L1 fluorescence intensity on tumor cells showed a significantly higher predictive performance for overall survival with an area under receiver operating curves (AUC) of 0.72 (p<0.0001) than the percentage of PD-L1+ tumor cells (AUC: 0.54). In PD-L1 positive as well as negative breast cancers a close spatial relationship between T- cell subsets (CD3+CD4±CD8±FOXP3±PD-1±CTLA-4±) and Macrophage/DC subsets (CD68±CD163±CD11c±iNOS) was found prognostic relevant (p<0.0001).

Conclusions

In conclusion, multiplex immunofluorescence PD-L1 assessment provides cutoff-free/continuous PD-L1 data which are superior to the conventional percentage of PD-L1+ tumor cells and of high prognostic relevance. The combined analysis of spatial PD-L1/PD-1 data and more than 20 different immune cell subtypes of the immune tumor microenvironment revealed distinct PD-L1 immune phenotypes.

Disclosure Information

N.C. Blessin: None. E. Bady: None. T. Mandelkow: None. C. Yang: None. J. Raedler: None. R. Simon: None. C. Fraune: None. M. Lennartz: None. S. Minner: None. E. Burandt: None. D. Höflmayer: None. G. Sauter: None. S.A. Weidemann: None.

High density of cytotoxic T-lymphocytes is linked to tumoral PD-L1 expression regardless of the mismatch repair status in colorectal cancer

BACKGROUND

Immune checkpoint-inhibitors targeting the PD-1/PD-L1 system are FDA approved in microsatellite instable (MSI) or mismatch repair deficient (dMMR) colorectal cancer (CRC). PD-L1 expression is tightly linked to features connected to immune checkpoint inhibitor response, but studies on large subsets of cancers analyzing the correlation between different status of MSI/dMMR, tumor infiltrating lymphocytes and PD-L1 expression are still lacking.

METHODS

More than 1800 CRC were analyzed for PD-L1 by immunohistochemistry in a tissue microarray format. Data were compared to MMR, the number of intratumoral CD8⁺ cytotoxic T-cells, and adverse clinico-pathological parameters. Different cutoff levels for defining PD-L1 positivity in tumor cells (1%, 5%, 10%, and 50%) yielded comparable results.

RESULTS

At a cutoff level of 5%, PD-L1 positivity was seen in 5.1% of tumors. PD-L1 was more often positive in dMMR (18.6%) than in MMR proficient (pMMR) cancers (4.1%; p < 0.0001). The number of intratumoral CD8⁺ lymphocytes was strikingly higher in PD-L1 positive (939.5 ± 118.2) than in PD-L1 negative cancers (310.5 ± 24.8). A higher number of intratumoral CD8⁺ lymphocytes was found in dMMR CRC (PD-L1 positive: 1999.7 ± 322.0; PD-L1 negative: 398.6 ± 128.0; p < 0.0001) compared to pMMR CRC (PD-L1 positive: 793.2 ± 124.8; PD-L1 negative: 297.2 ± 24.2; p < 0.0001). In dMMR and pMMR CRC, PD-L1 expression in tumor cells was unrelated to tumor stage, lymph node status or lymphatic/venous invasion. PD-L1 positivity in tumor associated immune cells was seen in 47.5% of cases and was significantly linked to high numbers of tumor infiltrating CD8⁺, low tumor stage, and absence of lymph node metastasis and lymphatic/venous invasion (p < 0.0001 each).

CONCLUSION

The data support the previously suggested fact that PD-L1 expression in tumor cells is driven by extensive cytotoxic T-cell infiltration in highly immunogenic dMMR and pMMR CRC. Frequent and intense PD-L1 expression in tumor cells of dMMR CRC may contribute to the high response rates of dMMR CRC to immune checkpoint-inhibitors.

Prevalence of proliferating CD8+ cells in normal lymphatic tissues, inflammation and cancer

CD8⁺ cytotoxic T-lymphocytes are essential components of the anti-tumor immunity. To better understand the expansion of CD8⁺ T-cells we used multiplex fluorescence immunohistochemistry to study Ki67⁺CD8⁺ cells in normal lymphoid tissues, selected inflammatory diseases and cancers in 41 large sections/ microenvironment tissue microarrays (TMAs) as well as 765 samples in a conventional TMA format. The evaluation of more than 20 different compartments of normal lymphoid tissues revealed that the percentage of proliferating (ki67⁺) CD8⁺ cells did commonly not exceed 3%. In inflammations, the percentage of Ki67⁺CD8⁺ cells was more variable and higher compared to normal tissues. In cancers, the percentage of Ki67⁺CD8⁺ cells was higher in the tumor center than at the invasive margin. In the tumor center of 765 colorectal cancers, the density of Ki67⁺CD8⁺ cells and the percentage of proliferating CD8⁺ cytotoxic T-cells was significantly associated with microsatellite instability (p<0.0001), pT (p<0.0002) and pN category (p<0.0098). In summary, these data show that the percentage of Ki67⁺CD8⁺ cells is usually at a baseline proliferation rate below 3% in healthy secondary lymphoid organs. This rate is often markedly higher in inflammatory and neoplastic diseases compared to normal tissues. The striking link with unfavorable tumor features in colorectal cancer suggest a potential clinical utility of assessing the percentage of Ki67⁺CD8⁺ cells to predict patients outcome.

Prognostic role of proliferating CD8+ cytotoxic Tcells in human cancers

PURPOSE

Expansion of CD8⁺ cytotoxic Tlymphocytes is a prerequisite for anti-cancer immune activity and has gained interest in the era of immune checkpoint therapy.

METHODS

To understand the CD8⁺ T cell dynamics in the tumor microenvironment, we used multiplex fluorescence immunohistochemistry to quantitate CD8⁺ proliferation (Ki67 co-expression) in tissue microarrays from 1107 colorectal, 642 renal cell, 1066 breast, 375 ovarian, 451 pancreatic and 347 gastric cancer samples.

RESULTS

The density and the percentage of proliferating (Ki67⁺) CD8⁺ T cells were both highly variable between tumor types as well as between patients with the same tumor type. Elevated density and percentage of proliferating CD8⁺ cytotoxic T cells were significantly associated with favorable tumor parameters such as low tumor stage, negative nodal stage (p ≤ 0.0041 each), prolonged overall survival (p ≤ 0.0028 each) and an inflamed immune phenotype (p = 0.0025) in colorectal cancer and, in contrast, linked to high tumor stage, advanced ISUP/Fuhrman/Thoenes grading (each p ≤ 0.003), shorter overall survival (p ≤ 0.0330 each) and an immune inflamed phenotype (p = 0.0094) in renal cell cancer. In breast, ovarian, pancreatic and gastric cancer the role of (Ki67⁺)CD8⁺ Tcells was not linked to clinicopathological data.

CONCLUSION

Our data demonstrate a tumor type dependent prognostic impact of proliferating (Ki67⁺)CD8⁺ Tcells and an inverse impact in colorectal and renal cell cancer.

Tumor cell PD-L1 expression is a strong predictor of unfavorable prognosis in immune checkpoint therapy-naive clear cell renal cell cancer

BACKGROUND

PD-L1 expression predicts response to immune checkpoint inhibitors in renal cell carcinomas (RCC), but has also been suggested to be linked to poor patient outcome.

METHODS

We analyzed PD-L1 in > 1400 RCC in a tissue microarray format by immunohistochemistry. Results were compared with histological tumor type, parameters of cancer aggressiveness, and intratumoral CD8⁺ cytotoxic cells.

RESULT

At a cut-off level of 5% PD-L1 positive tumor cells, PD-L1 positivity was seen in 6.3% of 633 clear cell RCC (ccRCC), 18.2% of 165 papillary RCC, 18.8% of 64 chromophobe RCC, and 41.7% of 103 oncocytomas. In ccRCC, PD-L1 positivity was significantly linked to high ISUP (p < 0.0001), Fuhrman (p < 0.0001), Thoenes grade (p < 0.0001), distant metastasis (p = 0.0042), short recurrence-free (p < 0.0001), and overall survival (p = 0.0002). Intratumoral CD8⁺ lymphocytes were more frequent in PD-L1 positive (1055 ± 109) than in PD-L1 negative ccRCC (407 ± 28; p < 0.0001). PD-L positive immune cells were seen in 8.2% of all RCC and 13.9% of papillary RCC. In ccRCC, PD-L1 positive immune cells were linked to high numbers of tumor-infiltrating CD8⁺ cells (p < 0.0001), high ISUP (p < 0.0001), Fuhrman (p = 0.0027), and Thoenes grade (p < 0.0001), and poor tumor-specific survival (p = 0.0280).

CONCLUSIONS

These data suggest that PD-L1 expression in highly immunogenic RCCs facilitates immune evasion and contributes to cancer aggressiveness.

Prevalence of CD8+ cytotoxic lymphocytes in human neoplasms

PURPOSE

Immune checkpoint inhibitors have recently been approved by the US FDA as first and/or second line therapy in a subset of cancer types. Recent evidence suggests that the quantity of tumor infiltrating lymphocytes (TILs) influences the likelihood of response to immune checkpoint inhibitors. Here, we set out to assess the density of CD8+ lymphocytes in a wide range of different cancer types and subtypes.

METHODS

The density of CD8+ lymphocytes was compared across different cancer types using tissue microarrays (TMAs) composed of up to 50 tumor samples each from 84 different cancer types and subtypes. In total 2652 cancers and 608 normal tissues were successfully analyzed by CD8 immunohistochemistry followed by automated image analysis of digitized slides.

RESULTS

We found that the median CD8+ lymphocyte counts ranged from 6 cells/mm2 in pleomorphic adenoma up to 1573 cells/mm2 in Hodgkin's lymphoma. The CD8 counts were generally lower in normal tissues compared to cancer tissues. Blood vessels of the spleen were the only non-lymphatic tissue staining positive for CD8. Tumor types approved for checkpoint inhibitor therapy, including malignant melanoma (81), muscle invasive urothelial carcinoma (119), small cell lung cancer (120), clear cell renal cell cancer (153), squamous cell carcinoma (189) and adenocarcinoma of the lung (328) as well as Hodgkin's lymphoma (1573) were all ranking among the upper half of our list. Comparably high CD8 densities (median cells/mm2) were also found in several rare and aggressive cancer types including Merkel cell carcinoma (70), angiosarcoma (95), anaplastic thyroid cancer (156) and embryonal carcinoma of the testis (186). In 73 of the 84 analyzed cancer types, the highly variable CD8 counts occasionally exceeded the average CD8 count of tumors for which checkpoint inhibitors have been approved.

CONCLUSION

These data support the concept that among most tumor types at least some individual cancers may benefit from treatment with immune checkpoint inhibitors.

High level of EZH2 expression is linked to high density of CD8-positive T-lymphocytes and an aggressive phenotype in renal cell carcinoma

Purpose

Enhancer of zeste homolog 2 (EZH2), the catalytic part of the Polycomb repressive complex 2 (PRC2), has a prognostic role in renal cell carcinoma (RCC) and was recently shown to modulate the immune response by reducing tumor cell immunogenicity.

Methods

To investigate whether the prognostic role of EZH2 might be driven by a modified immune environment, more than 1800 RCCs were analyzed in a tissue microarray for EZH2 expression and CD8 positive lymphocytes were quantitated by automated digital imaging.

Results

EZH2 positivity was found in 75.2% of 1603 interpretable tumors. In clear cell RCC, high EZH2 expression was significantly linked to high ISUP, Furmann, and Thoenes grade (p < 0.0001 each), advanced stage (p < 0.0001), nodal (p = 0.0190) and distant metastasis (p < 0.0001) as well as shortened overall (p < 0.0027) and recurrence free survival (p < 0.0001). The density of CD8+ cells varied from 0 to 5048 cells/mm² (Median 120 cells/mm²). A high CD8+ count was significantly associated with high ISUP, Fuhrmann, and Thoenes grade (p < 0.0001 each), advanced tumor stage (p = 0.0041), distant metastasis (p = 0.0026) as well as reduced overall survival (p = 0.0373) and recurrence free survival (p = 0.0450). The density of CD8+ cells continuously increased with raising EZH2 levels (p < 0.0001).

Conclusion

Our data support a striking prognostic role of both EZH2 expression and the density of CD8+ cells in RCC. The tight relationship of EZH2 expression and CD8+ cell counts in RCC is consistent with models suggesting that EZH2 overexpression can be caused by high lymphocyte content in certain tumor types. Such a mechanism could explain the unique finding of high lymphocyte counts driving poor prognosis in RCC patients.

High RSF1 protein expression is an independent prognostic feature in prostate cancer

Background: Remodelling and spacing factor 1 (RSF1) is involved in the regulation of chromatin remodelling and represents a potential therapeutic target. High RSF1 expression has been linked to adverse tumour features in many cancer types, but its role in prostate cancer is uncertain.Methods: In this study, RSF1 expression was analysed by immunohistochemistry on a tissue microarray with 17,747 prostate cancers.Results: Nuclear RSF1 staining of 16,456 interpetable cancers was considered strong, moderate, weak and negative in 25.2%, 48.7%, 5.3% and 20.8% of cancers respectively. Positive RSF1 expression was associated with advanced tumour stage, high Gleason grade, lymph node metastasis (p < .0001 each), early biochemical recurrence (p < .0003) and more frequent in the ERG positive than in the ERG negative subset (88% versus 71%; p < .0001). Subset analysis revealed, that associations between RSF1 expression and unfavourable tumour phenotype and PSA recurrence were present in both subgroups but stronger in the ERG negative than in the ERG positive subset. The univariate Cox proportional hazard ratio for PSA recurrence-free survival for strong versus negative RSF1 expression was a weak 1.60 compared with 5.91 for the biopsy Gleason grade ≥4 + 4 versus ≤3 + 3. The positive association of RSF1 protein detection with deletion of 3p13, 10q23 (PTEN), 12p13, 16q23, and 17p13 (p < .0001 each) suggest a role of high RSF1 expression in the development of genomic instability.Conclusion: In summary, the results of our study identify RSF1 as an independent prognostic marker in prostate cancer with a particularly strong role in ERG negative cases.

Loss of cytoplasmic survivin expression is an independent predictor of poor prognosis in radically operated prostate cancer patients

Survivin is an inhibitor of apoptosis. Aberrant survivin expression occurs in malignant tumors and has often been linked to unfavorable patient outcome. Here we analyzed 12 432 prostate cancers by immunohistochemistry. Survivin immunostaining was regularly expressed at high levels in normal prostate epithelium but expression was often reduced in prostate cancers. Among 9492 evaluable prostate cancers, 9% expressed survivin strongly, 19% moderately, 28% weakly, and 44% lacked it. Loss of cytoplasmic survivin was seen in advanced tumor stage, higher Gleason score, preoperative PSA levels, and Ki‐67 labeling index, and associated with earlier PSA recurrence (P < .0001). Survivin loss was significantly more common in cancers carrying TMPRSS2:ERG fusions (61% survivin negative) than in ERG wild‐type cancers (32% survivin negative; P < .0001). Multivariate analysis revealed that reduced cytoplasmic survivin expression predicted poor prognosis independent from Gleason score, pT, pN, and serum PSA level. This was valid for ERG‐positive and ERG‐negative cancers. Survivin expression loss even retained its prognostic impact in 1020 PTEN deleted cancers, a group that is already characterized by dismal patient prognosis. In conclusion, reduced survivin expression is associated with more aggressive tumors and inferior prognosis in prostate cancer.

Upregulation of SPDEF is associated with poor prognosis in prostate cancer

SAM pointed domain-containing Ets transcription factor (SPDEF), a member of the ETS transcription factor family, has been associated with prostate cancer development; however, its role in tumour development and progression is controversial. In the present study, SPDEF expression was analysed on a tissue microarray with >12,000 prostate cancer samples. SPDEF expression levels were higher in most prostate cancer samples than in normal prostate epithelium, suggesting SPDEF was upregulated in cancer. Nuclear SPDEF expression was identified in 80% of prostate cancer samples, and considered weak in 26.4%, moderate in 40.1% and strong in 13.5% of cases. SPDEF positivity was significantly associated with tumour stage, Gleason grade, lymph node metastasis and PSA recurrence (all P<0.0001). SPDEF overexpression was more common in ERG positive (94%) than in ERG negative cancer (69%; P<0.0001). Elevated SPDEF expression predicted poor prognosis independent from established prognostic parameters, including Gleason grade, pT, pN, serum PSA level and nodal status (P<0.01). In summary, SPDEF overexpression was associated with aggressive behaviour, particularly in ERG negative prostate cancer, and may have potential for clinical application.

Abstract 4104: Expression of the immune checkpoint receptor TIGIT in seminoma

A characteristic feature of testicular seminoma is the abundance of immune cells in the tumor microenvironment, raising the possibility that immune checkpoint inhibitors could be a therapeutic option in these tumors. TIGIT (T cell immunoreceptor with Ig and ITIM domains) is an inhibitory immune checkpoint receptor in analogy to PD-1 and drugs targeting TIGIT are currently tested in clinical trials. Little is known about the expression of these proteins in testicular seminomas. Here, we employed immunohistochemistry to determine the relative abundance of TIGIT and PD-1 in relation to the total CD3+immune cell infiltration in a tissue microarray (TMA) constructed from 78 seminoma patients. The fraction of TIGIT+and PD-1+lymphocytes was highly variable in individual cancers and ranged from 2.3% to 69.4% (mean:32.2±14.7%) for TIGIT and from 0.8% to 56.5% (mean:21.6±13.2%) for PD-1. The same high degree of variability was also found for the ratio of PD-1 to TIGITpositive cells that varied from a dominance of TIGIT (PD-1:TIGIT ratio=0.02) in 74% of patients to a predominance of PD-1 (PD-1:TIGIT ratio=12.5) in 23% of patients. In summary, the immune checkpoint receptors TIGIT and PD-1 are abundantly expressed in human seminomas. Once available, anti-TIGIT antibodies, possibly in combination with anti-PD-1 drugs, may be a promising therapeutic option for clinical studies in this cancer type.

Citation Format: Maximillian Lennartz, Niclas C. Blessin, Andrea Hinsch, Ronald Simon, Martina Kluth, Kristine Fischer, Claudia Hube-Magg, Wenchao Li, Tim Mandelkow, Nicolaus F. Debatin, Doris Höflmayer, Guido Sauter, Jakob R. Izbicki, Sarah Minner, Franziska Büscheck, Ria Uhlig, David Dum, Till Krech, Andreas M. Luebke, Corinna Wittmer, Frank Jacbosen, Eike Burandt, Stefan Steurer, Waldemar Wilczak. Expression of the immune checkpoint receptor TIGIT in seminoma [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 4104.

Abstract 4567: Distribution of CD8+cytotoxic lymphocytes in human neoplasms

Evidence suggests that the quantity of cytotoxic lymphocytes influences the likelihood for a successful application of immune checkpoint inhibitors. To compare the density of CD8+lymphocytes across various different tumor types, a tissue microarray (TMA) composed of up to 50 tumor samples each from 85 different cancer types and subtypes was analyzed. A total of 2652 cancers and 608 normal tissues were successfully analyzed by CD8 immunohistochemistry followed by automated image analysis of digitized slides. The median number of CD8+lymphocytes ranged from 6 cells/mm2in pleomorphic adenoma up to 1573 cells/mm2in Hodgkin’s lymphoma. CD8 counts were generally lower in normal tissues. Blood vessels of the spleen was the only non-lymphatic tissue staining for CD8.In solid tumors, highest CD8 densities (cells/mm2) were found in seminoma (median: 424), Warthin’s tumor (median: 425), squamous cell cervical cancer (median 468), medullary breast cancer (median: 657) and thymoma (median: 889).Tumor types approved for therapy with checkpoint inhibitors such malignant melanoma (median: 81), muscle invasive urothelial carcinomas (median: 119), small cell lung cancer (median: 120), clear cell kidney cancer (median: 153), squamous cell cancer (median: 189) and adenocarcinoma of the lung (median: 328) as well as Hodgkin’s lymphoma (median:1573) were all ranking among the upper half of our list. Comparably high CD8 densities (cells/mm2) were also found for several rare and aggressive cancer types including Merkel cell carcinoma (median: 70), angiosarcoma (median: 95), anaplastic thyroid cancer (median: 156), anal carcinoma (median: 104), squamous cell carcinoma of the vagina (median: 128) and embryonal carcinoma of the testis (median: 186). The CD8 cell count was highly variable within tumor types. In 73 of 84 analyzed cancer types, the CD8 count at least occasionally exceeded the average CD8 count of tumors for which checkpoint inhibitors have been approved.These data support the concept, that in most tumor types at least some individual cancers may benefit from treatment with immune checkpoint inhibitors.

Citation Format: Niclas C. Blessin, Florian Lutz, Patrick Spriesterbach, Wenchao Li, Tim Mandelkow, Vera Nickelsen, Ronald Simon, Claudia Hube-Magg, Florian Viehweger, Maximillian Lennartz, Christoph Fraune, Kristine Fischer, Katharina Möller, Stefan Steurer, Jacob R. Izbicki, Guido Sauter, Sarah Minner, Frank Jacobsen, Andreas M. Luebke, Franziska Büscheck, Doris Höflmayer, Waldemar Wilczak, Eike Burandt, Andrea Hinsch. Distribution of CD8+cytotoxic lymphocytes in human neoplasms [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 4567.

Expression of the immune checkpoint receptor TIGIT in seminoma

A characteristic feature of testicular seminoma is the abundance of immune cells in the tumor microenvironment, raising the possibility that immune checkpoint inhibitors may serve as a therapeutic option in these types of tumors. T cell immunoreceptor with Ig and ITIM domains (TIGIT) is an inhibitory immune checkpoint receptor in analogy to PD-1, and drugs targeting TIGIT are currently being investigated in clinical trials. Little is known about the expression of these proteins in testicular seminomas. Therefore the present study performed immunohistochemical analysis to determine the relative abundance of TIGIT and PD-1 in relation to the total CD3⁺ immune cell infiltration in a tissue microarray (TMA) constructed from 78 seminoma patients. The fraction of TIGIT⁺ and PD-1⁺ lymphocytes was highly variable in individual cancers and ranged from 2.3 to 69.4% (mean: 32.2±14.7%) for TIGIT and from 0.8 to 56.5% (mean: 21.6±13.2%) for PD-1. The same high degree of variability was also identified for the ratio of PD-1 to TIGIT positive cells, which varied from a dominance of TIGIT (PD-1: TIGIT ratio=0.02) in 74% of patients, to a predominance of PD-1 (PD-1: TIGIT ratio=12.5) in 23% of patients. In summary, the immune checkpoint receptors TIGIT and PD-1 are abundantly expressed in human seminomas. Once available, anti-TIGIT antibodies, possibly in combination with anti-PD-1 drugs, may be a reasonable therapeutic strategy for this type of cancer.

Expression of the immune checkpoint receptor TIGIT in Hodgkin's lymphoma

Hodgkin's lymphoma (HL) is characterized by a high background of inflammatory cells which play an important role for the pathogenesis of the disease. T cell immunoreceptor with Ig and ITIM domains (TIGIT) is an inhibitory immune checkpoint receptor and a putative target for novel immunotherapies. To study patterns of TIGIT expression in the T cell background surrounding malignant cells including Hodgkin cells, Reed-Sternberg cells and histiocytic cells, a microenvironment (ME) tissue microarray (TMA) was constructed from tissue punches measuring 2 mm in diameter obtained from formalin-fixed tissue samples of Hodgkin's lymphoma lymph nodes (n = 40) and normal human tonsil (n = 2). The ME-TMA was stained by brightfield and fluorescence multiplex immunohistochemistry (IHC) to evaluate expression levels of TIGIT and PD-1 as well as standard lymphocyte markers (CD3, CD8, CD4, FOXP3) in the lymphocytic background. All analyzed cases of HL contained 9-99% (median: 86%) of TIGIT+ lymphoid cells. In general, TIGIT localized to the same cells as PD-1. Strikingly, expression levels of TIGIT and PD-1 were highly variable among the analyzed samples. Highest levels of TIGIT and PD-1 were found in one sample of nodular lymphocytic-predominant HL (NLPHL). In conclusion, TIGIT expression is highly variable between patients with Hodgkin's lymphoma. Our results encourage further studies evaluating the role of TIGIT as a target for immunotherapies in Hodgkin's lymphoma.

High expression of class III β-tubulin in upper gastrointestinal cancer types

Class III β-tubulin (TUBB3) is a component of microtubules of neuronal cells that is upregulated in various cancer entities. To better understand the role of TUBB3 in upper gastrointestinal tract cancer types, the present study assessed TUBB3 expression in tissue microarrays including 189 gastric and 428 esophageal cancer. TUBB3 expression was detected in 62.4% of gastric cancer, 73.8% of esophageal adenocarcinoma and 88.7% of esophageal squamous cell cancer, while control samples of normal esophageal and gastric epithelium were TUBB3-negative. TUBB3 positivity was not associated with the International Union Against Cancer classification, World Health Organization grading, lymph node involvement or distant metastasis in any entity. Of note, TUBB3 expression was associated with tumor localization and prognosis in gastric cancer, with the tumor stage in esophageal adenocarcinoma, and with the resection margin in esophageal squamous cell cancer. In conclusion, the substantial rate of positivity for TUBB3 already in early stages of gastric cancer in combination with the lack of a further increase in frequency with tumor stage, may suggest, that TUBB3 upregulation is rather relevant for cancer development than for cancer progression. TUBB3 might be a suitable prognostic biomarker in gastric cancer types.

Abstract 696: Patterns of TIGIT expression in normal lymphatic tissue, inflammation and cancer

T cell immunoreceptor with Ig and ITIM domains (TIGIT) is an inhibitory immune checkpoint receptor and a putative target for novel immune therapies. To study patterns of TIGIT expression, “microenvironment tissue microarrays” containing 4mm tissue spots were constructed from lymph nodes of healthy (n=3) and HIV infected individuals (n=2), normal tonsils (n=3), Hashimoto thyroiditis (n=10), sarcoidosis (n=10), lichen sclerosus (n=2), IgG4-pancreatitis (n=2), rheumatoid arthritis (n=2) colorectal (n=5) and lung cancers (n=2) and analyzed for expression of TIGIT, PD-1 and standard lymphocyte markers by brightfield and multiplex fluorescence immunohistochemistry. TIGIT expression was seen in CD8+ cytotoxic T cells, CD4+ T-helper cells, FOXP3+ regulatory T cells and in NK cells, but not in CD11c+ dendritic cells, CD68+ macrophages and CD20+ B lymphocytes. TIGIT expression paralleled that of PD-1. More than 70% of TIGIT positive cells were PD-1 positive and more than 90% of the PD-1 positive cells were TIGIT positive. Expression of both proteins varied between different tissue compartments. TIGIT expression in tonsil gradually increased from the interfollicular area over the marginal/mantle zone to the germinal center in all T cell subtypes. Stronger expression of TIGIT and PD-1 than in tonsil germinal centers (2-3 fold) was only found in Hashimoto thyroiditis germinal centers. Marked location specific variations were also seen in other inflammatory diseases and in cancers. In general, TIGIT and PD-1 expression was higher in lymphocyte-dense compartments, such as areas of lymphocytic infiltration in sarcoidosis, IgG4 pancreatitis or rheumatoid arthritis, than in areas containing fewer and scattered lymphocytes. In lung and colorectal cancers, the density of TIGIT and PD-1 expressing T cells was highest at the invasion front. Also, the TIGIT and PD-1 expression levels were typically stronger in tumor adjacent stromal CD8+ cells than in tumor infiltrating CD8+ cells. In conclusion, TIGIT is regularly expressed in a large subset of T cells. The variable expression levels of TIGIT and PD-1 between cell types and tissue compartments illustrates the high complexity of immune response. The frequent co-expression of TIGIT and PD-1 may offer an opportunity for co-targeting these proteins with checkpoint inhibitor drugs.

Citation Format: Niclas C. Blessin, Ronald Simon, Martina Kluth, Kristine Fischer, Claudia Hube-Magg, Wenchao Li, Georgia Makrypidi-Fraune, Björn Wellge, Tim Mandelkow, Nicolaus F. Debatin, Guido Sauter, Waldemar Wilczak, Andrea Hinsch. Patterns of TIGIT expression in normal lymphatic tissue, inflammation and cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 696.

Abstract 2142: High variability of TIGIT expression in Hodgkin's lymphoma

Hodgkin's lymphoma (HL) is characterized by a high background of inflammatory cells which play an important role for the pathogenesis of the disease. T cell immunoreceptor with Ig and ITIM domains (TIGIT) is an inhibitory immune checkpoint receptor and a putative target for novel immune therapies. To study patterns of TIGIT expression in the T cell background surrounding malignant cells including Hodgkin cells, Reed-Sternberg cells and histiocytic cells, a microenvironment (ME) tissue microarray (TMA) was constructed from tissue punches measuring 2 mm in diameter obtained from formalin-fixed tissue samples of Hodgkin lymphoma lymph nodes (n=40) and normal human tonsil (n=2) as a reference. The ME-TMA was stained with brightfield and multiplex fluorescence immunohistochemistry (IHC) in order to evaluate expression levels of TIGIT and PD-1 as well as standard lymphocyte markers (CD8, CD4, FOXP3) in the lymphocytic background. TIGIT and PD-1 expression was found in all (100%) analyzed HL samples. In general, TIGIT localized to the same cells as PD-1. IHC based identification of T cell subtypes revealed TIGIT and PD-1 expression on CD8+ cytotoxic T cells, CD4+ helper T cells and FOXP3+ regulatory T cells. Strikingly, expression levels of TIGIT and PD-1 were highly variable among the analyzed samples irrespective of the histological subtype of HL. Interestingly, highest levels of both proteins were found in one sample of nodular lymphocytic-predominant HL (NLPHL). The high variability of TIGIT and PD-1 expression was also independent from the T cell subtype. HL with high TIGIT/PD-1 expression on CD8 positive cells sometimes showed low TIGIT/PD-1 expression on CD4 or FOXP3 positive T cells and vice versa. However, the T cell subtypes differed with respect to the TIGIT:PD-1 ratio. In the majority of analyzed HL, FOXP3+ regulatory T cells expressed higher levels of TIGIT than of PD-1. This was different for CD8+ and CD4+ cells, where similar fractions of HL showed either more TIGIT as PD-1, or more PD-1 as TIGIT, or comparable levels of both receptors. In conclusion, TIGIT (and PD-1) expression is highly variable between patients with Hodgkin's lymphoma. TIGIT may play a particularly important role in FOXP3 regulatory T cells in the lymphocytic background.

Citation Format: Ronald Simon, Niclas C. Blessin, Martina Kluth, Kristine Fischer, Claudia Hube-Magg, Wenchao Li, Georgia Makrypidi-Fraune, Björn Wellge, Tim Mandelkow, Nicolaus F. Debatin, Guido Sauter, Waldemar Wilczak, Andrea Hinsch. High variability of TIGIT expression in Hodgkin's lymphoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2142.