slides were fixed with 4 % paraformaldehyde in pbs for 10 min, washed three times in pbs, permeabilized using a 1: 1, 000 dilution of trit on x - 100 in casein solution, washed another three times in pbs and then blocked for 30 min with casein solution ( thermo fisher ). antibod ies were diluted in casein solution, and the slides were incubated overnight at 4 °c. the slide was then washed three times in pbs, and nuclei were stained with dna intercalator - iridium ( fluidigm ) at a dilution of 1: 400 in pbs for 30 min. the slide was washed three times in pbs, 30 s in deionized water and then dried at room temperature. a region for imc analysis was selected using consecutive h & e - stained sections and the desi - msi data. imc analysis was performed using a hyperion instrument ( fluidigm corporation ) with an ablation energy of 4 db and an ablation frequency of 200 hz. imc images were produced using mcd viewer ( v. 1. 0; fluidigm ), and analysis was performed using halo ( indica labs ). tumour - bearing rat brains were snap - frozen in liquid nitrogen and sectioned at 6 μm thickness for immunoh istochemistry analysis using leica ’ s polymer refine kit ( antibod ies listed in supplementary table 6 ). images were analysed using aperio image - viewing software and halo ( v. 3. 6. 4134. 137 ). halo ( v. 3. 6. 4134. 137 ) and highplex fl ( v. 4. 1. 3 ) modules were used for automate d image analysis. optical densities for weakly, moderately and strongly stained cells used for the automate d quantitative analysis of scanned sections were as follows: ki67 – ( nuclear ) 7, 40. 7522, 54. 385, p53 – ( nuclear ) 1. 8, 3. 5929, 5. 1327, cc3 – ( cytoplasm ) 1. 9427, 4. 646, 6. 1947, vimentin – ( cytoplasm ) 13. 3343, 25. 7522, 41. 2035, cd3 – ( nuclear ) 2. 2832, 32. 6875, 63, gzmb – ( nuclear ) 0. 6956, 0. 8673, 1. 6106, cd4 – ( cytoplasm ) 3. 9823, 6. 7699, 10. 354, cd8a – ( nuclear ) 1. 6327, 18. 7679, 26, cd68 – ( cytoplasm ) 10. 4106, 45. 9027, 78. 6903, cd45 – ( cytoplasm ) 2, 5. 3363, 7. 115, asma – ( cytoplasm ) 2. 8, 12. 1327, 18. 6239, cd31 – ( cytoplasm ) 2. 274, 4. 5841, 6. 876, panck – ( cytoplasm ) 1. 836, 2. 8673, 3. 9823, collagen i – ( cytoplasm ) 28. 293, 104. 7301, 179. 58. five cellular phenotypes were identified: cd4 helper t cells ( cd45 cd4 cd3 ); cytotoxic t cells ( cd3 cd45 cd8a ); activated cytotoxic t cells ( cd3 cd45 cd8a gzmb ); natural killer cells and neutrophils ( cd45 gzmb ); and macrophages and microglia ( cd68 ). a random forest classifier was used to disting uish vessels and non - vessels within the images. large vessels were positive for collagen i and cd31. annotations were created manually on several images, and these were used to train the classifier. the five cellular phenotypes were plotted spatially, three 60 µm bands travelling out from the vessels were defined and the total number of cells displaying these cellular phenotypes in each band was determined. sample size for human tumour collection was determined intra - operatively based on patient and tumour factors ( for example, proximity to eloquent brain ). a minimum of six samples were collected for each tumour region. for xenograft and neurosphere studies, a minimum of three independent biological replicates were used ( three different rats; three different cell line passages with a minimum of six technical replicates ). no randomization or blinding was used, and all data were included in the analysis. statistical analyses were performed using graphpad prism ( v. 10. 0. 3 ), r ( v. 4. 3. 0 ) and scils. bioinformatics analyses were performed in r. statistical tests were two - sided unless stated otherwise. student ’ s t - tests and one - way anova with tukey ’ s multiplicity correction were used to test the equality of means between two or more groups, respectively. further information on research design is available in the nature portfol io reporting summary linked to this article. backgroundusing antibod ies to specific protein antigens is the method of choice to assign and identify cell lineage through simultaneous analysis of surface molecules and intracellular markers. embryonic stem cell research can be benefited from using antibod ies specific to transcriptional factors / markers that contribute to the " stemness " phenotype or critical for cell lineage. resultsin this report, we have developed and validated antibod ies ( either monoclonal or polyclonal ) specific to human embryonic stem cell antigens and early differentiation transcriptional factors / markers that are critical for cell differentiation into definite lineage. conclusionthese antibod ies enable stem cell biologists to conveniently identify stem cell characteristics and to quantitatively assess differentiation. although the stem cell concept was introduced decades ago, to date, stem cells can only be defined functionally, not morphologically or phenotypically. two functions define stem cells. firstly, they are self - renewing, thus able to propagate to generate additional stem cells. secondly they can differentiate into various progenitor cells, which commit to further maturation along a specific lineage. while stem cells can be best defined functionally, a good number of molecular markers have been used to prospectively identify various stem cell populations. although the functional importance of many of these antigens remains unknown, their unique expression pattern and timing of expression provide a useful tool for scientists to identify as well as isolate stem cells. embryonic stem cells ( esc ), derived from the inner cell mass of pre - implantation embryos, have been recognized as the earliest stem cell population [ 1, 2 ]. this pluripotent population can differentiate into all somatic tissue including germ cells. in the case of human esc, they can differentiate into some extra - embryonic derivatives as well. like mouse esc, human es cells can be maintained and propagated on mouse fibroblast feeders for extended periods in media containing basic fibroblast growth factor ( bfgf ) [ 3 ]. gene expression of undifferentiated human es cells has been investigated among several es cell lines by a variety of techniques. they include comparison with databases, reverse transcriptase-polymerase chain reaction, focused cdna microarrays, and immunocytochemistry. a list of molecules comprised of known es - specific or - highly expressed genes and candidates that can serve as markers for human escs and may also contribute to the " stemness " phenotype has been established [ 3 - 11 ]. for example, pluripotent esc can be characterized by high level expression of oct3 / 4 ( pou domain, class 5, transcription factor 1, pou5f1 ) and nanog, which are a member of pou domain and homeobox transcription factors respectively. a critical amount of oct3 / 4 and nanog expression is required to sustain stem - cell pluripotency and both of these markers are downregulated as cells differentiate in vitro and in vivo [ 4 - 9 ]. antibod ies to oct3 / 4 which cross react with human oct 3 / 4 have been widely used to monitor the presence of undifferentiated esc. no single marker however is sufficient or unique for identifying escs. oct3 / 4 for example is expressed by germ cells and may be expressed by specific populations later in development. likewise, nanog has been shown to express in other tissues. we and other have noted however, that while no single marker is sufficient a constellation of positive and negative markers can in concert unambiguously allow one to define the state of esc cultures and that surface markers in combination can be used to prospectively sort for esc. based on published data at the level of gene expression, we have cloned a number of candidate marker genes. we have also expressed the recombinant protein and generated a panel of monoclonal or polyclonal antibod ies to these proteins.