Tissue Microarray for Gynecological Pathology Studies: A Mini-Review.

Antibody-based proteomics provides a powerful approach for the functional study of the human proteome involving the systematic generation of protein-specific affinity reagents. We used this strategy to construct a comprehensive, antibody-based protein atlas for expression and localization profiles in 48 normal human tissues and 20 different cancers. Here we report a new publicly available database containing, in the first version, approximately 400,000 high resolution images corresponding to more than 700 antibodies toward human proteins. Each image has been annotated by a certified pathologist to provide a knowledge base for functional studies and to allow queries about protein profiles in normal and disease tissues. Our results suggest it should be possible to extend this analysis to the majority of all human proteins thus providing a valuable tool for medical and biological research.

The analysis of tissue-specific expression at both the gene and protein levels is vital for understanding human biology and disease. Antibody-based proteomics provides a strategy for the systematic generation of antibodies against all human proteins to combine with protein profiling in tissues and cells using tissue microarrays, immunohistochemistry and immunofluorescence. The Human Protein Atlas project was launched in 2003 with the aim of creating a map of protein expression patterns in normal cells, tissues and cancer. At present, 11,200 unique proteins corresponding to over 50% of all human protein-encoding genes have been analysed. All protein expression data, including underlying high-resolution images, are published on the free and publically available Human Protein Atlas portal (http://www.proteinatlas.org). This database provides an important source of information for numerous biomedical research projects, including biomarker discovery efforts. Moreover, the global analysis of how our genome is expressed at the protein level has provided basic knowledge on the ubiquitous expression of a large proportion of our proteins and revealed the paucity of cell- and tissue-type-specific proteins.

BACKGROUND Archival formalin fixed paraffin embedded (FFPE) tissues are an excellent and abundant source of human cancer and normal tissues, useful for cancer research and diagnosis. Moreover, FFPE tissue microarrays enable analysis of hundreds of samples from many different patients on the same slide. Super resolution microscopes have been used for cancer tissue imaging; however, these methods are expensive and require long recording times, limiting their usefulness for the cancer research community. Recently, a new approach (Expansion Microscopy) was developed to enable physical magnification and high resolution imaging of cell lines and fresh-frozen (and fixed) mouse brain with conventional microscopes (Chen F, Tillberg PW, Boyden ES, 2015, Science 347:543-548). In the current study, we developed expansion microscopy for expanding and imaging formalin fixed paraffin embedded normal and cancer human tissues, both in tissue microarrays and whole tissue slides. METHODS Expansion microscopy (ExM) physically magnifies tissue samples by embedding them in a dense swellable polymer, anchoring key biomolecules to the polymer mesh, and adding water to swell the polymer. ExM physically magnifies the brain tissue with nanoscale isotropy and a post-expansion measurement error of 2-4%. Proteins can also be visualized by a modified immunofluorescence assay (Chen F et al., Science, 2015). In the present study, we optimized the ExM chemistry, labeling, and imaging methodologies to enable ExM to be used in cancer research and diagnosis, for morphological and protein imaging and analysis of both tissue microarrays and whole tissue slides on a wide variety of human tissues. Nuclei were detected by DAPI, and protein markers, including those of stroma (vimentin) and epithelium (keratins), were detected using immunofluorescence. RESULTS and CONCLUSIONS We developed ExM protocols to enable expansion of human normal and cancer tissues ∼4.5x in linear dimension, with a post-expansion measurement error of 5% or less. We successfully expanded normal and cancer human FFPE tissue microarrays containing over eight different tissue origins, including breast, prostate, lung, colon, pancreas and ovary. We expanded fresh frozen tissue samples of normal and cancer tissues. Our method makes possible the use of ExM on routinely collected FFPE pathology samples, enabling super resolution optical investigation of morphology and protein expression/localization in tissue microarrays with conventional fluorescent microscopy. Future applications include both large-scale retrospective and prospective studies of carcinogenesis in clinical tissue samples. * Yongxin Zhao and Octavian Bucur contributed equally; # Edward Boyden (esb@media.mit.edu) and Andrew H. Beck are corresponding authors (abeck2@bidmc.harvard.edu); Citation Format: Octavian Bucur, Yongxin Zhao, Edward Boyden, Andrew H. Beck. Physical expansion of tissue microarrays for high-resolution imaging of normal and cancer samples with conventional microscopy. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4229.

Tissue micro array (TMA) is widely used in cancer research in search of new predictive and prognostic markers. Colon cancer is known to be heterogeneous and the present study addresses some methodological aspects using cores of different size and analysing markers with different cellular distribution. We selected 61 paraffin-embedded tissue blocks representing patients diagnosed with Dukes B colon cancer. Two 1 mm and two 2 mm cores were taken from both the centre and the invasive front of the tumour respectively. The immunostaining included MLH1, MSH2, PMS2, p53, COX-2, TIMP and Betacatenin. Twenty-five percent of the cores taken from paraffin blocks less than 0.5 cm was lost and the total loss was 8%. The homogeneous stains (MLH1, MSH2 and PMS2) all showed high agreement between TMA and whole tissue stains (kappa = 0.96,1 and 1 respectively). The COX-2, p53 and Betacatenin illustrated moderate to high agreement (kappa = 0.54-0.9) whereas TIMP-1 had the lowest score (kappa 0.19-0.25). The application of TMA in Dukes B colon cancer has several pitfalls and depends substantially on the immunohistochemical marker in question. Therefore a validation study seems justified before applying large scale TMA in this setting.

Chapter 5 - Tissue Microarrays in Studying Gynecological Cancers

Purpose: To develop a CAR T for solid tumors that hits a wide range of cancers, is effective and has little or no effect on normal tissues. We developed a MUC1* targeting CAR T that is scheduled for a 1st-in-human clinical trial for metastatic breast cancers at the Fred Hutchinson Cancer Research Center in Q1 2019. Unlike previous attempts at making an anti-MUC1 cancer therapeutic, huMNC2-CAR44 targets MUC1*, which is the transmembrane cleavage product. MUC1* is a growth factor receptor that is activated when onco-embryonic growth factor NME7AB dimerizes its truncated extra cellular domain. The binding site for NME7AB is masked in full-length MUC1; anti-MUC1* antibody huMNC2 binds to the same site. huMNC2 does not bind to full-length MUC1 nor other cleaved forms of MUC1 that are on some healthy tissues that need to rapidly divide. Monoclonal antibodies against the truncated MUC1* extra cellular domain were generated and screened by IHC for reactivity to cancerous tissue micro arrays (TMAs) and lack thereof on normal tissues. The best monoclonals were incorporated into CARs, transduced into human T cells and tested in vitro for specific killing of MUC1* positive but not MUC1* negative cells. We developed a novel cell line in which MUC1 is not cleaved. By adding specific cleavage enzymes, we identified antibodies that recognized conformational epitope that were created by specific cleavage enzymes. The final selection of an anti-MUC1* antibody for the targeting head of our CAR was based on its widespread binding to breast cancer tissues, low cross reactivity to normal tissues, and its recognition of a conformational epitope created when MUC1 is cleaved to MUC1* by a specific cleavage enzyme that is overexpressed in many cancers, especially breast cancers. In vivo we showed that injecting this cleavage enzyme near a MUC1/MUC1* breast tumor dramatically accelerated tumor growth, which was stopped by simultaneous injection of the cleavage enzyme and our CAR T cells. IHC studies of thousands of normal vs. cancerous human tissue specimens show that huMNC2-scFv almost exclusively binds to tumor tissues, hitting over 90% of breast, 83% ovarian, 78% pancreatic and 71% of lung cancers. Recognition of breast cancer specimens appears not to be limited by cancer sub-type. In vivo experiments of human tumors in NSG mice (n>300), show that huMNC2-CAR44 T cells inhibited or completely obliterated a variety of MUC1* positive solid tumors. Dual tumor experiments showed that adequate MUC1* density is required for a CAR T response, further supporting the idea that huMNC2-CAR44 T cells will selectively kill MUC1* positive tumors, while sparing normal tissues. Conclusion: MUC1* is the predominant form of MUC1 present on cancers. Antibodies that target conformational epitopes produced by specific subsets of cleavage enzymes make anti-MUC1* CAR T cells highly tumor selective. CARs could be patient specific based on which cleavage enzymes their tumors express. Citation Format: Cynthia C. Bamdad, Nelson D. Glennie, Andrew K. Stewart, Pengyu Huang, Benoit J. Smagghe, Tyler E. Swanson, Erin K. Hanahoe, Gregory L. Riley. First-in-human CAR T for solid tumors targets the MUC1 transmembrane cleavage product [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 2323.

BackgroundWith the introduction of tissue microarrays (TMAs) researchers can investigate gene and protein expression in tissues on a high-throughput scale. TMAs generate a wealth of data calling for extended, high level data management. Enhanced data analysis and systematic data management are required for traceability and reproducibility of experiments and provision of results in a timely and reliable fashion. Robust and scalable applications have to be utilized, which allow secure data access, manipulation and evaluation for researchers from different laboratories.ResultsTAMEE (Tissue Array Management and Evaluation Environment) is a web-based database application for the management and analysis of data resulting from the production and application of TMAs. It facilitates storage of production and experimental parameters, of images generated throughout the TMA workflow, and of results from core evaluation. Database content consistency is achieved using structured classifications of parameters. This allows the extraction of high quality results for subsequent biologically-relevant data analyses. Tissue cores in the images of stained tissue sections are automatically located and extracted and can be evaluated using a set of predefined analysis algorithms. Additional evaluation algorithms can be easily integrated into the application via a plug-in interface. Downstream analysis of results is facilitated via a flexible query generator.ConclusionWe have developed an integrated system tailored to the specific needs of research projects using high density TMAs. It covers the complete workflow of TMA production, experimental use and subsequent analysis. The system is freely available for academic and non-profit institutions from .

Recent studies in molecular biology and proteomics have identified a significant number of novel diagnostic, prognostic, and therapeutic disease markers. However, validation of these markers in clinical specimens with traditional histopathological techniques involves low throughput and is time consuming and labor intensive. Tissue microarrays (TMAs) offer a means of combining tens to hundreds of specimens of tissue onto a single slide for simultaneous analysis. This capability is particularly pertinent in the field of cancer for target verification of data obtained from cDNA microarrays and protein expression profiling of tissues, as well as in epidemiology-based investigations using histochemical/immunohistochemical staining or in situ hybridization. In combination with automated image analysis, TMA technology can be used in the global cellular network analysis of tissues. In particular, this potential has generated much excitement in cardiovascular disease research. The following review discusses recent advances in the construction and application of TMAs and the opportunity for developing novel, highly sensitive diagnostic tools for the early detection of cardiovascular disease.

Tissue microarray (TMA) technology is a high-throughput method that enables the simultaneous analysis of multiple tissue samples within a single paraffin block. By extracting small core biopsies from donor blocks and arranging them systematically into a recipient block, TMAs allow uniform experimental conditions, efficient biomarker evaluation, and preservation of valuable tissue resources. This review discusses the historical development of TMA technology, construction techniques, major applications in predictive, prognostic, validation, and progression studies, and its role in oncology and oral pathology research. The advantages, limitations—particularly tumor heterogeneity—and recent technological advancements in automation and digital pathology are critically evaluated. Special emphasis is placed on the application of TMAs in oral cavity diseases and bioimaging. TMA remains a powerful and evolving tool in molecular pathology and translational research

Oral cancer is a leading cause of cancer death worldwide. The goal of cancer-screening program is to detect tumours at early stage. Moreover the screening tool must be sufficiently non invasive and inexpensive to allow widespread applicability.Protein biomarker discovery for early detection of head and neck squamous cell carcinoma (HNSCC) is a crucial needs to improve patient outcomes. The proteins secreted from cancer tissues are an important molecules which play a vital role, involved in various biological processes related to cancer metastasis and progression which makes a tissue proteome a rich reservoir of potential biomarkers. Tissue based models are suitable for the studies as the differences in the secreted proteins between cancerous and normal tissues can be easily quantified in a controlled manage system. Mass spectrometry-based proteomics has emerged as an excellent tool for identification of Protein biomarkers in different types of cancer. Proteins secreted from cancerous tissue can be a potential biomarkers. We used isobaric tag for relative and absolute quantitation (iTRAQ) labeling methodology coupled with high resolution mass spectrometry to identify and quantitate secreted proteins from human tissue. In all, we identified 2074 proteins were identified of which 162 and 125 were up and down regulated proteins respectively expressed in HNSCC derived tissue sample as compared to the normal adjacent Tissue. We detected a higher abundance of some previously known markers for HNSCC including, zinc finger protein ZNF142 (11-fold) and peroxiredoxin-1, (PRDX1) (5 fold) etc demonstrating the validity of our approach. We also identified several novel secreted proteins in HNSCC including, S100A7, (7 fold), apolipoprotein D APOD (10-fold) and Thymosin beta-10 TMSB10 (5-fold). IHC-based validation was conducted in HNSCC using tissue microarrays which revealed over expression of S100A7, APOD and TMSB10 in 70% and 65% of the tested cases, respectively. This proteomic analysis will not only serve as a source of candidate biomarkers but will also enhance the current knowledge on the role of the candidate molecules towards disease progression. The selection of S100A7 was done by the earlier research work and it shows that it has a great role in cancer progression. So, by targeting S100A7 inhibits Oral Cancer Growth and Metastasis by RNA mediated Interference and this occurs through NF Kappa Beta mediated Pathway both in vitro and in vivo evaluation. To elucidate the role of S100A7 in Oral cancer, we inhibited the activity of S100A7 in an Oral cancer cell line using a siRNA directed silencing. This resulted in a significant decrease in cell viability, colony formation ability and invasive properties of cancer cells. Further studies are ongoing to explore the therapeutic potential of the candidate genes in HNSCC. Citation Format: Kaushik Kumar Dey, Mahitosh Mandal. Quantitative proteomic approaches to identify biomarkers for oral cancer & targeting S100A7 by RNA-mediated interference through NF kappa beta-mediated pathway. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 38. doi:10.1158/1538-7445.AM2014-38

Widespread applications of tissue microarrays (TMAs) in both cancer research and clinical pathology demonstrate a versatile and portable technology. The rapid integration of TMA technology into the biomarker discovery and validation process reflects the forward thinking of researchers who pioneered the high-density TMA. The precise arrangement of hundreds of archival clinical tissue samples into a composite paraffin block is now a proven method for efficient and standardized analyses of molecular markers. With applications in cancer research, TMAs are a valuable tool in viiidating candidate markers identified in highly sensitive genome-wide microarray experiments. With applications in clinical pathology, TMAs are used widely in immunohistochemistry for quality control and quality assurance. TMAs can demonstrate antibody thresholds on a single slide, which aid in optimization where high and low signal intensities can be seen. This type of application lends itself to clinical pathology and immunohistochemistry panels run daily to improve biomarker identification and characterization. The TMA industry now includes public and private resources with varying degrees of research utility. In this article, we will explore several potential TMA applications in basic research, prognostic oncology, and drug discovery. (The J Histotechnol 28:223, 2005)Submitted September 6, 2005; accepted with revisions December 6, 2005

Immunohistochemical expression of mTOR protein in breast carcinoma tissues

Widespread applications of tissue microarrays (TMAs) in both cancer research and clinical pathology demonstrate a versatile and portable technology. The rapid integration of TMA technology into the biomarker discovery and validation process reflects the forward thinking of researchers who pioneered the high-density TMA. The precise arrangement of hundreds of archival clinical tissue samples into a composite paraffin block is now a proven method for efficient and standardized analyses of molecular markers. With applications in cancer research, TMAs are a valuable tool in viiidating candidate markers identified in highly sensitive genome-wide microarray experiments. With applications in clinical pathology, TMAs are used widely in immunohistochemistry for quality control and quality assurance. TMAs can demonstrate antibody thresholds on a single slide, which aid in optimization where high and low signal intensities can be seen. This type of application lends itself to clinical pathology and immunohistochemistry panels run daily to improve biomarker identification and characterization. The TMA industry now includes public and private resources with varying degrees of research utility. In this article, we will explore several potential TMA applications in basic research, prognostic oncology, and drug discovery. (The J Histotechnol 28:223, 2005)Submitted September 6, 2005; accepted with revisions December 6, 2005

Polo-like kinase 5 (PLK5) is a member of the serine/threonine family of polo-like kinases (PLKs) which have been shown to play important role in cell cycle regulation. The Plk5 gene was identified to encode an expressed protein in humans over a decade ago; however, limited information is available regarding the functional significance of PLK5. A search of the ProteinAtlas database showed that PLK5 was expressed in several types of normal human tissues including the brain, eye, lung, testis, fallopian tubes, endometrium, and cervix. However, research regarding the role of PLK5 in cancer is still in its infancy, with little available information regarding its functional significance in human biology. Interestingly, one published study has demonstrated that PLK5 was downregulated in brain tumors, suggesting a potential tumor suppressive function in this neoplasm. The objective of this study was to determine the expression profile of PLK5 in a variety of normal and malignant tissues types to gain an insight into its function in cancer. We performed quantitative immunostaining of PLK5 employing tissue microarrays (TMAs) containing tissue cores from six different organs viz. cervix, endometrium, fallopian tubes, ovary, lung, and testis. Following immunohistochemical staining, the TMA slides were scanned via Vectra Imaging System and analyzed using the Inform software, yielding quantitative information of PLK5 protein levels in each tissue core, which was then subjected to further statistical analysis. Our data demonstrated that PLK5 protein levels were significantly downregulated in most malignant tissues when compared to normal tissues (p<0.03). Further, we determined the expression profiles of PLK5 in cancer and normal tissues from the organs of interest using publicly available TCGA (The Cancer Genome Atlas) data via the Genomic Data Commons (GDC) Data Portal. Using this data source, we were able to compare PLK5 levels in tumor versus normal tissues from cervix, endometrium, and ovary. We found that PLK5 had significantly lower expression in cancer than normal in all three tissue types (p<0.003). Additionally, we used the Genotype-Tissue Expression (GTEx) portal, which contains data from non-diseased tissues, to compare the PLK5 expression in normal samples from GTEx to the tumor samples from TCGA. We found that the PLK5 levels were higher in normal versus the malignant tissues from cervix, endometrium, ovary, and testis; however, there was no difference in terms of PLK5 levels between the normal and malignant tissues from lung. Taken together, our results demonstrate that PLK5 levels are downregulated in multiple cancers, suggesting a potential tumor suppressive function of PLK5 in the tissue types studied. However, additional detailed studies are required to fully understand the role and functional significance of PLK5 in cancer. Citation Format: Glorimar Guzmán-Pérez, Shengqin Su, Mary A. Ndiaye, Manish Patankar, Nihal Ahmad. A potential tumor suppressive role of polo-like kinase 5 in specific neoplasms [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1169.

Digital image-based scoring of immunohistochemistry (IHC) staining allows faster, more objective and potentially more reproducible quantification of area stained or cell counts compared to manual scoring. However, predictors of discrepancies between these two assessment methods are not well understood. We examined clinical and pathological characteristics associated with discordance between image-based and manual scoring using ovarian cancer tissue microarrays (TMA) across a range of IHC stains. We evaluated 2,159 TMA cores from 681 ovarian cancer cases stained by four tissue cytoplasmic stains quantified as percentage of the tumor area stained (POSTN, CXCL14, ADH1B, COL11A1) and two immune cell markers quantified by cell count of infiltrating immune cells (CD68, CD163). The TMA slides were scored manually using semi-quantitative scoring by gynecologic pathologists as well as digitally using image-based Definiens automated platform. We used generalized linear mixed models with individual patients and TMAs included as random effects and stain as fixed effect to examine predictors of discordance, defined as absolute difference of ≥1SD in z-scores between image-based and manual scoring, overall and by each stain. The multi-level model included characteristics of the TMA, core, and tumor factors as predictors. Overall, TMA construction by automated robotic system (vs manual), smaller core size or area, borderline (vs invasive tumors), and having no geographic necrosis in the tumor were significantly associated with greater discordance between image-based and manual scoring. Interestingly, all these factors, except geographic necrosis, were differentially associated with discordance across the stains (p-interaction <0.05). Having multiple loci of geographic necrosis was associated with less discordance (OR=0.84, 95%CI=0.72-0.97). Invasive tumors compared to borderline tumors were less likely to be discordantly scored overall (OR=0.80, 95%CI=0.65-1.00) and for tissue cytoplasmic stains (OR range: 0.42-0.73), with associations in the opposite direction for immune cell markers (OR range: 1.21-2.37). Core areas in the lowest quartile vs all other cores were associated with greater discordance (OR=1.18, 95%CI=1.05-1.32), which was more notable for the tissue cytoplasmic stains (OR range: 1.18-2.00) compared to immune cell markers (OR range: 0.83-0.86). TMAs created by robot vs by hand had 64% higher odds of discordance (95%CI=1.20-2.25), which was more apparent when blank rows and columns were included on the TMA. Overall, TMA, core, and tumor level factors were related to discordance between image-based and manual scoring. Some stain types may be more susceptible to specific pre-analytic factors suggesting that reproducibility studies of manual vs image-based scoring should be conducted on a proportion of cases in large scale projects. Citation Format: Naoko Sasamoto, Mary Townsend, Farnoosh Abbas-Aghababazadeh, Kathryn L. Terry, Joseph O. Johnson, Jonathan L. Hecht, Brooke L. Fridley, Shelley S. Tworoger. Predictors of discordance between image-based and manual scoring of immunohistochemical stains in ovarian cancer tissue microarrays [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 34.