Transcriptomics and Spatial Proteomics for Discovery and Validation of Missing Proteins in the Human Ovary.

Efforts to understand the complexities of human biology encompass multidimensional aspects, with proteins emerging as crucial components. However, studying the human ovary introduces unique challenges due to its complex dynamics and changes over a lifetime, varied cellular composition, and limited sample access. Here, four new RNA-seq samples of ovarian cortex spanning ages of 7 to 32 were sequenced and added to the existing data in the Human Protein Atlas (HPA) database www.proteinatlas.org, opening the doors to unique possibilities for exploration of oocyte-specific proteins. Based on transcriptomics analysis of the four new tissue samples representing both prepubertal girls and women of fertile age, we selected 20 protein candidates that lacked previous evidence at the protein level, so-called "missing proteins" (MPs). The proteins were validated using high-resolution antibody-based profiling and single-cell transcriptomics. Fourteen proteins exhibited consistent single-cell expression patterns in oocytes and granulosa cells, confirming their presence in the ovary and suggesting that these proteins play important roles in ovarian function, thus proposing that these 14 proteins should no longer be classified as MPs. This research significantly advances the understanding of MPs, unearthing fresh avenues for prospective exploration. By integrating innovative methodologies and leveraging the wealth of data in the HPA database, these insights contribute to refining our understanding of protein roles within the human ovary and opening the doors for further investigations into missing proteins and human reproduction.

Expression of cancer-testis antigens in the immune microenvironment of non-small cell lung cancer.

The antigenic repertoire of tumors is critical for successful anti-cancer immune response and the efficacy of immunotherapy. Cancer-testis antigens (CTAs) are targets of humoral and cellular immune reactions. We aimed to characterize CTA expression in non-small cell lung cancer (NSCLC) in the context of the immune microenvironment. Of 90 CTAs validated by RNA sequencing, eight CTAs (DPEP3, EZHIP, MAGEA4, MAGEB2, MAGEC2, PAGE1, PRAME, and TKTL1) were selected for immunohistochemical profiling in cancer tissues from 328 NSCLC patients. CTA expression was compared with immune cell densities in the tumor environment and with genomic, transcriptomic, and clinical data. Most NSCLC cases (79%) expressed at least one of the analyzed CTAs, and CTA protein expression correlated generally with RNA expression. CTA profiles were associated with immune profiles: high MAGEA4 expression was related to M2 macrophages (CD163) and regulatory T cells (FOXP3), low MAGEA4 was associated with T cells (CD3), and high EZHIP was associated with plasma cell infiltration (adj. P-value < 0.05). None of the CTAs correlated with clinical outcomes. The current study provides a comprehensive evaluation of CTAs and suggests that their association with immune cells may indicate in situ immunogenic effects. The findings support the rationale to harness CTAs as targets for immunotherapy.

DeepHistoClass: A Novel Strategy for Confident Classification of Immunohistochemistry Images Using Deep Learning.

A multitude of efforts worldwide aim to create a single-cell reference map of the human body, for fundamental understanding of human health, molecular medicine, and targeted treatment. Antibody-based proteomics using immunohistochemistry (IHC) has proven to be an excellent technology for integration with large-scale single-cell transcriptomics datasets. The golden standard for evaluation of IHC staining patterns is manual annotation, which is expensive and may lead to subjective errors. Artificial intelligence holds much promise for efficient and accurate pattern recognition, but confidence in prediction needs to be addressed. Here, the aim was to present a reliable and comprehensive framework for automated annotation of IHC images. We developed a multilabel classification of 7848 complex IHC images of human testis corresponding to 2794 unique proteins, generated as part of the Human Protein Atlas (HPA) project. Manual annotation data for eight different cell types was generated as a basis for training and testing a proposed Hybrid Bayesian Neural Network. By combining the deep learning model with a novel uncertainty metric, DeepHistoClass (DHC) Confidence Score, the average diagnostic performance improved from 86.9% to 96.3%. This metric not only reveals which images are reliably classified by the model, but can also be utilized for identification of manual annotation errors. The proposed streamlined workflow can be developed further for other tissue types in health and disease and has important implications for digital pathology initiatives or large-scale protein mapping efforts such as the HPA project.

Combined RNA/tissue profiling identifies novel Cancer/testis genes.

Cancer/Testis (CT) genes are induced in germ cells, repressed in somatic cells, and derepressed in somatic tumors, where these genes can contribute to cancer progression. CT gene identification requires data obtained using standardized protocols and technologies. This is a challenge because data for germ cells, gonads, normal somatic tissues, and a wide range of cancer samples stem from multiple sources and were generated over substantial periods of time. We carried out a GeneChip-based RNA profiling analysis using our own data for testis and enriched germ cells, data for somatic cancers from the Expression Project for Oncology, and data for normal somatic tissues from the Gene Omnibus Repository. We identified 478 candidate loci that include known CT genes, numerous genes associated with oncogenic processes, and novel candidates that are not referenced in the Cancer/Testis Database (www.cta.lncc.br). We complemented RNA expression data at the protein level for SPESP1, GALNTL5, PDCL2, and C11orf42 using cancer tissue microarrays covering malignant tumors of breast, uterus, thyroid, and kidney, as well as published RNA profiling and immunohistochemical data provided by the Human Protein Atlas (www.proteinatlas.org). We report that combined RNA/tissue profiling identifies novel CT genes that may be of clinical interest as therapeutical targets or biomarkers. Our findings also highlight the challenges of detecting truly germ cell-specific mRNAs and the proteins they encode in highly heterogenous testicular, somatic, and tumor tissues.

Enhanced Validation of Antibodies Enables the Discovery of Missing Proteins.

The localization of proteins at a tissue- or cell-type-specific level is tightly linked to the protein function. To better understand each protein's role in cellular systems, spatial information constitutes an important complement to quantitative data. The standard methods for determining the spatial distribution of proteins in single cells of complex tissue samples make use of antibodies. For a stringent analysis of the human proteome, we used orthogonal methods and independent antibodies to validate 5981 antibodies that show the expression of 3775 human proteins across all major human tissues. This enhanced validation uncovered 56 proteins corresponding to the group of "missing proteins" and 171 proteins of unknown function. The presented strategy will facilitate further discussions around criteria for evidence of protein existence based on immunohistochemistry and serves as a useful guide to identify candidate proteins for integrative studies with quantitative proteomics methods.

The protein expression profile of ACE2 in human tissues.

The novel SARS-coronavirus 2 (SARS-CoV-2) poses a global challenge on healthcare and society. For understanding the susceptibility for SARS-CoV-2 infection, the cell type-specific expression of the host cell surface receptor is necessary. The key protein suggested to be involved in host cell entry is angiotensin I converting enzyme 2 (ACE2). Here, we report the expression pattern of ACE2 across > 150 different cell types corresponding to all major human tissues and organs based on stringent immunohistochemical analysis. The results were compared with several datasets both on the mRNA and protein level. ACE2 expression was mainly observed in enterocytes, renal tubules, gallbladder, cardiomyocytes, male reproductive cells, placental trophoblasts, ductal cells, eye, and vasculature. In the respiratory system, the expression was limited, with no or only low expression in a subset of cells in a few individuals, observed by one antibody only. Our data constitute an important resource for further studies on SARS-CoV-2 host cell entry, in order to understand the biology of the disease and to aid in the development of effective treatments to the viral infection.

An atlas of the protein-coding genes in the human, pig, and mouse brain.

The brain, with its diverse physiology and intricate cellular organization, is the most complex organ of the mammalian body. To expand our basic understanding of the neurobiology of the brain and its diseases, we performed a comprehensive molecular dissection of 10 major brain regions and multiple subregions using a variety of transcriptomics methods and antibody-based mapping. This analysis was carried out in the human, pig, and mouse brain to allow the identification of regional expression profiles, as well as to study similarities and differences in expression levels between the three species. The resulting data have been made available in an open-access Brain Atlas resource, part of the Human Protein Atlas, to allow exploration and comparison of the expression of individual protein-coding genes in various parts of the mammalian brain.

TGFBR3L-An Uncharacterised Pituitary Specific Membrane Protein Detected in the Gonadotroph Cells in Non-Neoplastic and Tumour Tissue.

Here, we report the investigation of transforming growth factor beta-receptor 3 like (TGFBR3L), an uncharacterised pituitary specific membrane protein, in non-neoplastic anterior pituitary gland and pituitary neuroendocrine tumours. A polyclonal antibody produced within the Human Protein Atlas project (HPA074356) was used for TGFBR3L staining and combined with SF1 and FSH for a 3-plex fluorescent protocol, providing more details about the cell lineage specificity of TGFBR3L expression. A cohort of 230 pituitary neuroendocrine tumours were analysed. In a subgroup of previously characterised gonadotroph tumours, correlation with expression of FSH/LH, E-cadherin, oestrogen (ER) and somatostatin receptors (SSTR) was explored. TGFBR3L showed membranous immunolabeling and was found to be gonadotroph cell lineage-specific, verified by co-expression with SF1 and FSH/LH staining in both tumour and non-neoplastic anterior pituitary tissues. TGFBR3L immunoreactivity was observed in gonadotroph tumours only and demonstrated intra-tumour heterogeneity with a perivascular location. TGFBR3L immunostaining correlated positively to both FSH (R = 0.290) and LH (R = 0.390) immunostaining, and SSTR3 (R = 0.315). TGFBR3L correlated inversely to membranous E-cadherin staining (R = -0.351) and oestrogen receptor ß mRNA (R = -0.274). In conclusion, TGFBR3L is a novel pituitary gland specific protein, located in the membrane of gonadotroph cells in non-neoplastic anterior pituitary gland and in a subset of gonadotroph pituitary tumours.

Cell Type-Specific Expression of Testis Elevated Genes Based on Transcriptomics and Antibody-Based Proteomics.

One of the most complex organs in the human body is the testis, where spermatogenesis takes place. This physiological process involves thousands of genes and proteins that are activated and repressed, making testis the organ with the highest number of tissue-specific genes. However, the function of a large proportion of the corresponding proteins remains unknown and testis harbors many missing proteins (MPs), defined as products of protein-coding genes that lack experimental mass spectrometry evidence. Here, an integrated omics approach was used for exploring the cell type-specific protein expression of genes with an elevated expression in testis. By combining genome-wide transcriptomics analysis with immunohistochemistry, more than 500 proteins with distinct testicular protein expression patterns were identified, and these were selected for in-depth characterization of their in situ expression in eight different testicular cell types. The cell type-specific protein expression patterns allowed us to identify six distinct clusters of expression at different stages of spermatogenesis. The analysis highlighted numerous poorly characterized proteins in each of these clusters whose expression overlapped with that of known proteins involved in spermatogenesis, including 85 proteins with an unknown function and 60 proteins that previously have been classified as MPs. Furthermore, we were able to characterize the in situ distribution of several proteins that previously lacked spatial information and cell type-specific expression within the testis. The testis elevated expression levels both at the RNA and protein levels suggest that these proteins are related to testis-specific functions. In summary, the study demonstrates the power of combining genome-wide transcriptomics analysis with antibody-based protein profiling to explore the cell type-specific expression of both well-known proteins and MPs. The analyzed proteins constitute important targets for further testis-specific research in male reproductive disorders.