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Recent initiatives such as The Cancer Genome Atlas have mapped the genome-wide effect of individual genes on tumor growth. By unraveling genomic alterations in tumors, molecular subtypes of cancers have been identified, which is improving patient diagnostics and treatment. Uhlen et al. developed a computer-based modeling approach to examine different cancer types in nearly 8000 patients. They provide an open-access resource for exploring how the expression of specific genes influences patient survival in 17 different types of cancer. More than 900,000 patient survival profiles are available, including for tumors of colon, prostate, lung, and breast origin. This interactive data set can also be used to generate personalized patient models to predict how metabolic changes can influence tumor growth. Science , this issue p. eaan2507 A systems biology approach should allow genome-wide exploration of the effect of individual proteins on cancer clinical outcomes. Cancer is one of the leading causes of death, and there is great interest in understanding the underlying molecular mechanisms involved in the pathogenesis and progression of individual tumors. We used systems-level approaches to analyze the genome-wide transcriptome of the protein-coding genes of 17 major cancer types with respect to clinical outcome. A general pattern emerged: Shorter patient survival was associated with up-regulation of genes involved in cell growth and with down-regulation of genes involved in cellular differentiation. Using genome-scale metabolic models, we show that cancer patients have widespread metabolic heterogeneity, highlighting the need for precise and personalized medicine for cancer treatment. All data are presented in an interactive open-access database ( www.proteinatlas.org/pathology ) to allow genome-wide exploration of the impact of individual proteins on clinical outcomes.

Key Points Personalization of cancer therapy requires the identification of unambiguous diagnostic, prognostic and predictive biomarkers to facilitate the accurate stratification of patients and the monitoring of responses to targeted therapies. The systematic generation and validation of specific antibodies offers a high-throughput mechanism for the functional exploration of the proteome and a logical approach for fast-tracking the translation of identified biomarkers. Multiple approaches exist, each with specific characteristics and advantages that are suitable for a wide range of applications, which capitalize on the inherent specificity and sensitivity of antibodies as affinity reagents. The integration of antibody-based approaches with existing genomic and transcriptomic methods offers huge potential, and the clinical implementation of new high-throughput antibody-based approaches will depend on the integration of data across various platforms. The clinical application of new antibody-based assays demonstrates their utility as accurate, sensitive and robust diagnostic and prognostic tests and has led to the development of a new approach, known as pathway diagnostics, which is likely to have a crucial role in the design of future molecular therapeutic trials. Antibody-based proteomics facilitates the high-throughput evaluation of candidate biomarkers. What insights can be gained, and what are the clinical applications of antibody-based proteomics? The effective implementation of personalized cancer therapeutic regimens depends on the successful identification and translation of informative biomarkers to aid clinical decision making. Antibody-based proteomics occupies a pivotal space in the cancer biomarker discovery and validation pipeline, facilitating the high-throughput evaluation of candidate markers. Although the clinical utility of these emerging technologies remains to be established, the traditional use of antibodies as affinity reagents in clinical diagnostic and predictive assays suggests that the rapid translation of such approaches is an achievable goal. Furthermore, in combination with, or as alternatives to, genomic and transcriptomic methods for patient stratification, antibody-based proteomics approaches offer the promise of additional insight into cancer disease states. In this Review, we discuss the current status of antibody-based proteomics and its contribution to the development of new assays that are crucial for the realization of individualized cancer therapy.

Immunohistochemistry is an important extension to clinical information and morphology, and prevails as an invaluable tool for establishing a correct cancer diagnosis in clinical diagnostic pathology. The applicability of immunohistochemistry is limited by the availability of validated cell- and cancer-type specific antibodies, rendering an unmet need to discover, test, and validate novel markers. The SATB2 protein is selectively expressed in glandular cells from the lower gastrointestinal tract and expression is retained in a large majority of primary and metastatic colorectal cancers. We analyzed the expression of SATB2 in all clinical cases (n = 840), in which immunohistochemistry for detection of CK20 was deemed necessary for a final diagnosis. SATB2 showed a high sensitivity (93%) and specificity (77%) to determine a cancer of colorectal origin and in combination with CK7 and CK20, the specificity increased to 100%. We conclude that SATB2 provides a new and advantageous supplement for clinical differential diagnostics.

Objectives: Immunohistochemistry is an important extension to clinical information and morphology, and prevails as an invaluable tool for establishing a correct cancer diagnosis in clinical diagnostic pathology. The applicability of immunohistochemistry is limited by the availability of validated cell- and cancer-type specific antibodies, rendering an unmet need to discover, test, and validate novel markers. The SATB2 protein is selectively expressed in glandular cells from the lower gastrointestinal tract and expression is retained in a large majority of primary and metastatic colorectal cancers. Methods: We analyzed the expression of SATB2 in all clinical cases (n = 840), in which immunohistochemistry for detection of CK20 was deemed necessary for a final diagnosis. Results: SATB2 showed a high sensitivity (93%) and specificity (77%) to determine a cancer of colorectal origin and in combination with CK7 and CK20, the specificity increased to 100%. Conclusions: We conclude that SATB2 provides a new and advantageous supplement for clinical differential diagnostics.

RAS and BRAF mutations impact treatment and prognosis of metastatic colorectal cancer patients (mCRC), but the knowledge is based on trial patients usually not representative for the general cancer population. Patient characteristics, treatment and efficacy according to KRAS, BRAF and MSI status were analyzed in a prospectively collected unselected population-based cohort of 798 non-resectable mCRC patients. The cohort contained many patients with poor performance status (39% PS 2-4) and elderly (37% age>75), groups usually not included in clinical trials. Patients without available tissue micro array (TMA) (42%) had worse prognostic factors and inferior survival (all patients; 7m vs 11m, chemotherapy-treated;12m vs 17m). The 92 patients (21%) with BRAF mutation had a poor prognosis regardless of microsatellite instability, but receipt of 1-2nd chemotherapy was similar to wildtype BRAF patients. Median survival in this cohort varied from 1 month in BRAF mutated patients not given chemotherapy to 26 months in wildtype KRAS/BRAF patients <75 years in good PS. TMA availability, BRAF mutation and KRAS mutation were all independent prognostic factors for survival. The observed 21% BRAF mutation incidence is higher than the previously and repeatedly reported incidence of 5-12% in mCRC. Screening for BRAF mutations before selection of treatment is relevant for many patients, especially outside clinical trials. A BRAF mutation only partly explained the very poor prognosis of many mCRC patients. Survival in unselected metastatic colorectal cancer patients is extremely variable and subgroups have an extremely short survival compared to trial patients. Patients without available TMA had worse prognostic factors and shorter survival, which questions the total generalizability of present TMA studies and implies that we lack information on the biologically worst mCRC cases. Lack of available tissue is an important underexposed issue which introduces sample bias, and this should be recognized more clearly when conclusions are made from translational mCRC studies.

Analysis of the pattern of proteins or messenger RNAs (mRNAs) in histological tissue sections is a cornerstone in biomedical research and diagnostics. This typically involves the visualization of a few proteins or expressed genes at a time. We have devised a strategy, which we call \"spatial transcriptomics,\" that allows visualization and quantitative analysis of the transcriptome with spatial resolution in individual tissue sections. By positioning histological sections on arrayed reverse transcription primers with unique positional barcodes, we demonstrate high-quality RNA-sequencing data with maintained two-dimensional positional information from the mouse brain and human breast cancer. Spatial transcriptomics provides quantitative gene expression data and visualization of the distribution of mRNAs within tissue sections and enables novel types of bioinformatics analyses, valuable in research and diagnostics.

Background Tumor associated macrophages (TAMs) are alternatively activated macrophages that enhance tumor progression by promoting tumor cell invasion, migration and angiogenesis. TAMs have an anti-inflammatory function resembling M2 macrophages. CD163 is regarded as a highly specific monocyte/macrophage marker for M2 macrophages. In this study we evaluated the specificity of using the M2 macrophage marker CD163 as a TAM marker and compared its prognostic value with the more frequently used pan-macrophage marker CD68. We also analyzed the prognostic value of the localization of CD163 + and CD68 + myeloid cells in human breast cancer. Methods The extent of infiltrating CD163 + or CD68 + myeloid cells in tumor nest versus tumor stroma was evaluated by immunohistochemistry in tissue microarrays with tumors from 144 breast cancer cases. Spearman’s Rho and χ 2 tests were used to examine the correlations between CD163 + or CD68 + myeloid cells and clinicopathological parameters. Kaplan Meier analysis and Cox proportional hazards modeling were used to assess the impact of CD163 + and CD68 + myeloid cells in tumor stroma and tumor nest, respectively, on recurrence free survival, breast cancer specific and overall survival. Results We found that infiltration of CD163 + and CD68 + macrophages into tumor stroma, but not into tumor nest, were of clinical relevance. CD163 + macrophages in tumor stroma positively correlated with higher grade, larger tumor size, Ki67 positivity, estrogen receptor negativity, progesterone receptor negativity, triple-negative/basal-like breast cancer and inversely correlated with luminal A breast cancer. Some CD163 + areas lacked CD68 expression, suggesting that CD163 could be used as a general anti-inflammatory myeloid marker with prognostic impact. CD68 + macrophages in tumor stroma positively correlated to tumor size and inversely correlated to luminal A breast cancer. More importantly, CD68 in tumor stroma was an independent prognostic factor for reduced breast cancer specific survival. Conclusion These findings highlight the importance of analyzing the localization rather than merely the presence of TAMs as a prognostic marker for breast cancer patients.

Genome-wide analyses are increasingly providing resources for advances in basic and applied biomedical science. Uhlen et al. performed a global expression analysis of human blood cell types and integrated this data with data across all major human tissues and organs in the human protein atlas. This comprehensive compendium allows for classification of all human protein-coding genes with regard to their tissue- and cell-type distribution. Science , this issue p. eaax9198 Genome-wide expression profiles are analyzed across human immune cell populations and all major human tissues and organs. Blood is the predominant source for molecular analyses in humans, both in clinical and research settings. It is the target for many therapeutic strategies, emphasizing the need for comprehensive molecular maps of the cells constituting human blood. In this study, we performed a genome-wide transcriptomic analysis of protein-coding genes in sorted blood immune cell populations to characterize the expression levels of each individual gene across the blood cell types. All data are presented in an interactive, open-access Blood Atlas as part of the Human Protein Atlas and are integrated with expression profiles across all major tissues to provide spatial classification of all protein-coding genes. This allows for a genome-wide exploration of the expression profiles across human immune cell populations and all major human tissues and organs.

Merkel cell carcinoma (MCC) is a rare aggressive skin cancer with neuroendocrine differentiation. With immunohistochemistry, the tumor cells stain for both neuroendocrine (i.e., synaptophysin and chromogranin A) and epithelial markers. The epithelial marker cytokeratin 20 (CK20) stains positive with immunohistochemistry in a vast majority of MCCs. The expression of the special AT-rich sequence-binding protein (SATB2) was analyzed in MCC ( n  = 20) together with other forms of skin cancer and neuroendocrine tumors ( n  = 51) using immunohistochemistry. The results were compared to the expression of CK20, synaptophysin, and chromogranin A. The majority of the MCCs stained positive for synaptophysin and chromogranin A (95 vs 80 % respectively), and 75 % of the MCCs showed cytoplasmic positivity for CK20 and nuclear positivity for SATB2, with two discordant cases lacking expression of one of these markers. We conclude that immunohistochemistry for SATB2 can be used as an additional marker with similar sensitivity and specificity as CK20 for the diagnosis of Merkel cell carcinoma, suggesting a clinical utility in difficult cases where MCC is suspected.

The diverse physiology of the brain is reflected in its complex organization at regional, cellular, and subcellular levels. Sjöstedt et al. combined data—both newly acquired and from other large-scale brain mapping projects—from transcriptomics, single-cell genomics, in situ hybridization, and antibody-based protein profiling to map the molecular profiles in human, pig, and mouse brain. The analysis is consistent with a conserved basic brain architecture during mammalian evolution, but it does show differences in regional gene expression profiles. Science , this issue p. eaay5947 The Brain Atlas compares the expression of protein-coding genes in the mammalian 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.