Programmed death-ligand 1 expression in carcinoma of unknown primary.

We examined the expression of programmed death-ligand 1 (PD-L1) in carcinoma of unknown primary (CUP) and its potential implications. Tissue microarrays were constructed for 72 CUP cases (histologic subtypes: 22 adenocarcinoma, 15 poorly differentiated carcinoma, 19 squamous cell carcinoma, and 14 undifferentiated carcinoma; clinical subtype: favorable type 17 [23.6%], unfavorable type 55 [76.4%]), with immunohistochemical staining performed for PD-L1 (22C3, SP142, SP263, and 28 - 8), CK7, and CK20 to determine the association between staining results and clinicopathological parameters. In CUP, the PD-L1 positivity rate was 5.6-48.6% (tumor cells [TC] or tumor proportion score [TPS]: 5.6-36.1%, immune cell score [IC]: 8.3-48.6%, combined positive score [CPS]: 16.7%) using different cutoff values for 22C3 (TPS ≥ 1%, CPS ≥ 10), SP142 (TC ≥ 50%, IC ≥ 10%), SP263, and 28 - 8 (TC and IC ≥ 1%). PD-L1 SP142 TC and PD-L1 SP263 IC showed the lowest (5.6%) and highest (48.6%) positivity rates, respectively. The PD-L1 positivity rate did not significantly differ based on the histologic subtype, clinical subtype, or CK7/CK20 across clones. Considering TC κ ≥ 1%, TC κ ≥ 50%, IC κ ≥ 1%, and IC κ ≥ 10%, the PD-L1 positivity rate was TC = 4.2-36.1% and IC = 9.7-48.6%; the overall agreement between antibodies ranged from 69.4 to 93.1%, showing fair or better agreement (κ ≥ 0.21). In CUP, PD-L1 positivity varied depending on antibodies and scoring systems, with no difference observed according to histologic or clinical subtypes.

Novel approach to HER2 quantification using phosphor-integrated dots in human breast invasive cancer microarray.

HER2 expression in breast cancer is evaluated to select patients for anti-HER2 therapy. With the advent of newly approved HER2-targeted drugs for low HER2 expression breast cancer, more solid evidence on the whole spectrum of HER2 expression is needed. In this study, we quantitatively assessed HER2 expression from the whole core by combining high-intensity phosphor-integrated dot (PID) immunostaining and whole slide imaging (WSI) analysis. Two types of staining were performed using a 170-core tissue microarray of invasive breast cancer. First, HER2 was stained by immunohistochemistry (IHC), and IHC scores were determined by two practicing pathologists according to the ASCO/CAP HER2 guideline. Second, HER2 was stained with PID, and tentative PID scores were determined by quantitative analysis. The results show that PID can numerically classify HER2 expression status into scores 3+, 2+, 1+, and 0. The HER2 value quantified by PID strongly correlated with the 3, 3'-diaminobenzidine (DAB) IHC score determined by pathologists (R2 = 0.93). PID IHC score 1+ cases included both DAB IHC score 1+ and 0 cases, and low HER2 expression cases appeared to be often evaluated as DAB IHC score 0. Therefore, digital image analysis by PID and WSI can help stratify HER2 IHC. It may also help classify low HER2 expression.

CYP7B1 as a Biomarker for Prostate Cancer Risk and Progression: Metabolic and Oncogenic Signatures (Diagnostic Immunohistochemistry Analysis by Tissue Microarray in Prostate Cancer Patients-Diamond Study).

We aimed to analyze the association between CYP7B1 and prostate cancer, along with its association with proteins involved in cancer and metabolic processes. A retrospective analysis was performed on 390 patients with prostate cancer (PC) or benign prostatic hyperplasia (BPH). We investigated the interactions between CYP7B1 expression and proteins associated with PC and metabolic processes, followed by an analysis of the risk of biochemical recurrence based on CYP7B1 expression. Of the 139 patients with elevated CYP7B1 expression, 92.8% had prostate cancer. Overall, no increased risk of biochemical recurrence was associated with CYP7B1 expression. However, in a non-diabetic subgroup analysis, higher CYP7B1 expression indicated a higher risk of biochemical recurrence, with an HR of 1.78 (CI: 1.0-3.2, p = 0.05). PC is associated with elevated CYP7B1 expression. In a subgroup analysis of non-diabetic patients, elevated CYP7B1 expression was associated with an increased risk of biochemical recurrence, suggesting increased cancer aggressiveness.

Staining pattern of specific and cross-reacting Melan-A antibodies: A comparative study on 15,840 samples from 133 human tumor types.

The Melan-A (melanocyte antigen) protein, also termed 'melanoma antigen recognized by T cells 1' (MART-1) is a protein with unknown function whose expression is specific for the melanocyte lineage. Antibodies against Melan-A are thus used for identifying melanocytic tumors, but some Melan-A antibodies show an additional - diagnostically useful - cross-reactivity against an unspecified protein involved in corticosteroid hormone synthesis. To comprehensively compare the staining patterns of a specific and a cross-reactive Melan-A antibody in normal and neoplastic tissues, tissue microarrays containing 15,840 samples from 133 different tumor types and subtypes as well as 608 samples of 76 different normal tissue types were analyzed by immunohistochemistry. For the Melan-A-specific antibody 'Melan-A specific' (MSVA-900M), Melan-A positivity was seen in 96.0% of 25 benign nevi, 93.0% of 40 primary and 86.7% of 75 metastatic melanomas, 82.4% of 85 renal angiomyolipomas as well as 96.4% of 84 neurofibromas, 2.2% of 46 granular cell tumors, 1.0% of 104 schwannomas, and 1.1% of 87 leiomyosarcomas. The cross-reactive antibody 'Melan-A+' (MSVA-901M+) stained 98.1% of the tumors stained by 'Melan-A specific'. In addition, high positivity rates were seen in sex-cord-stroma tumors of the ovary (35.3%-100%) and the testis (86.7%) as well as for adrenocortical neoplasms (76.3%-83.0%). Only nine further tumor groups showed Melan-A+ staining, including five different categories of urothelial carcinomas. Our data provide a comprehensive overview on the staining patterns of specific and cross-reactive Melan-A antibodies. The data demonstrate that both antibodies are highly useful for their specific purpose. It is important for pathologists to distinguish these two Melan-A antibody subtypes for their daily work.

Topographic analysis of pancreatic cancer by TMA and digital spatial profiling reveals biological complexity with potential therapeutic implications.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal human malignancies. Tissue microarrays (TMA) are an established method of high throughput biomarker interrogation in tissues but may not capture histological features of cancer with potential biological relevance. Topographic TMAs (T-TMAs) representing pathophysiological hallmarks of cancer were constructed from representative, retrospective PDAC diagnostic material, including 72 individual core tissue samples. The T-TMA was interrogated with tissue hybridization-based experiments to confirm the accuracy of the topographic sampling, expression of pro-tumourigenic and immune mediators of cancer, totalling more than 750 individual biomarker analyses. A custom designed Next Generation Sequencing (NGS) panel and a spatial distribution-specific transcriptomic evaluation were also employed. The morphological choice of the pathophysiological hallmarks of cancer was confirmed by protein-specific expression. Quantitative analysis identified topography-specific patterns of expression in the IDO/TGF-ß axis; with a heterogeneous relationship of inflammation and desmoplasia across hallmark areas and a general but variable protein and gene expression of c-MET. NGS results highlighted underlying genetic heterogeneity within samples, which may have a confounding influence on the expression of a particular biomarker. T-TMAs, integrated with quantitative biomarker digital scoring, are useful tools to identify hallmark specific expression of biomarkers in pancreatic cancer.

EBV-Associated Gastric Cancer; An In Situ Hybridization Assay on Tissue Microarray: A Multi-Region Study from Four Major Provinces of Iran.

BACKGROUND: Gastric cancer is the fourth leading cause of cancer-related deaths in the world. The identification of gastric cancer subtypes related to recognizable microbial agents may play a pivotal role in the targeted prevention and treatment of this cancer. The current study is conducted to define the frequency of Epstein-Barr virus (EBV) infection in gastric cancers of four major provinces, with different incidence rates of gastric cancers, in Iran. METHODS: Paraffin blocks of 682 cases of various types of gastric cancer from Tehran, South and North areas of Iran were collected. Twelve tissue microarray (TMA) blocks were constructed from these blocks. Localization of EBV in tumors was assessed by in situ hybridization (ISH) for EBV-encoded RNA (EBER). Chi-squared test was used to evaluate the statistical significance between EBV-associated gastric cancer (EBVaGC) and clinicopathologic tumor characteristics. RESULTS: Fourteen out of 682 cases (2.1%) of gastric adenocarcinoma were EBER-positive. EBER was positive in 8 out of 22 (36.4%) of medullary carcinomas and 6 out of 660 (0.9%) of non-medullary type, which was a statistically significant difference (P<0.001). The EBVaGCs were more frequent in younger age (P=0.009) and also showed a trend toward the lower stage of the tumor (P=0.075). CONCLUSION: EBV-associated gastric adenocarcinoma has a low prevalence in Iran. This finding can be due to epidemiologic differences in risk factors and exposures, and the low number of gastric medullary carcinomas in the population. It may also be related to gastric tumor heterogeneity not detected with the TMA technique.

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.

Clinicopathological role of Cyclin A2 in uterine corpus endometrial carcinoma: Integration of tissue microarrays and ScRNA-Seq.

BACKGROUND: The comprehensive expression level and potential molecular role of Cyclin A2 (CCNA2) in uterine corpus endometrial carcinoma (UCEC) remains undiscovered. METHODS: UCEC and normal endometrium tissues from in-house and public databases were collected for investigating protein and messenger RNA expression of CCNA2. The transcription factors of CCNA2 were identified by the Cistrome database. The prognostic significance of CCNA2 in UCEC was evaluated through univariate and multivariate Cox regression as well as Kaplan-Meier curve analysis. Single-cell RNA-sequencing (scRNA-seq) analysis was performed to explore cell types in UCEC, and the AUCell algorithm was used to investigate the activity of CCNA2 in different cell types. RESULTS: A total of 32 in-house UCEC and 30 normal endometrial tissues as well as 720 UCEC and 165 control samples from public databases were eligible and collected. Integrated calculation showed that the CCNA2 expression was up-regulated in the UCEC tissues (SMD = 2.43, 95% confidence interval 2.23∼2.64). E2F1 and FOXM1 were identified as transcription factors due to the presence of binding peaks on transcription site of CCNA2. CCNA2 predicted worse prognosis in UCEC. However, CCNA2 was not an independent prognostic factor in UCEC. The scRNA-seq analysis disclosed five cell types: B cells, T cells, monocytes, natural killer cells, and epithelial cells in UCEC. The expression of CCNA2 was mainly located in B cells and T cells. Moreover, CCNA2 was active in T cells and B cells using the AUCell algorithm. CONCLUSION: CCNA2 was up-regulated and mainly located in T cells and B cells in UCEC. Overexpression of CCNA2 predicted unfavorable prognosis of UCEC.

Prognostic value of large amino acid transporter type 1 (LAT1) expression in pulmonary adenocarcinoma: A tissue microarray study.

BACKGROUND: Large amino acid transporter type 1 (LAT1) provides cancer cells with essential amino acids for both protein synthesis and cell growth and may predict patient prognosis. Additionally, LAT1 inhibition can be a therapeutic target. This study aimed to examine the prognostic significance of LAT1 expression in lung cancer, paying special attention to adenocarcinoma subtypes. METHODS: Tissue microarrays (TMA) of 1,560 total cores obtained from surgically resected lung cancer specimens between 1995 and 2008 at our hospital were used. Overall, 795 cases of adenocarcinoma were identified, and 717 underwent further evaluation. Immunohistochemical staining of whole slides and TMA cores were assessed to set H-score cutoff value.. Immunohistochemical expression of LAT1 was examined based on the subtypes of adenocarcinoma. Statistical analyses explored the prognostic significance of LAT1. RESULTS: Adenocarcinoma accounted for 71.8% of all cases (n = 795), and 216 cases (27.1%) expressed LAT1. The 795 cases were categorized into five subtypes: lepidic (n = 29, 3.6%), papillary (n = 601, 75.6%), acinar (n = 58, 7.3%), and solid (n = 9, 1.1%); 717 of the 795 cases were further assessed according to the exclusion criteria. The LAT1-positive ratio increased as the architectural grade increased. Notably, in papillary adenocarcinoma, the LAT1-positive group had significantly lower overall survival compared to the negative group (10-year survival: 45.6% vs. 60.8%, p < 0.001). CONCLUSION: LAT1 expression was higher in high-grade subtypes of pulmonary adenocarcinoma. Moreover, LAT1 expression is useful for predicting prognosis, particularly in papillary adenocarcinoma, facilitating prognostic stratification of papillary adenocarcinoma.

Tumor Heterogeneity Confounds Lymphocyte Metrics in Diagnostic Lung Cancer Biopsies.

CONTEXT.­: The immune microenvironment is involved in fundamental aspects of tumorigenesis, and immune scores are now being developed for clinical diagnostics. OBJECTIVE.­: To evaluate how well small diagnostic biopsies and tissue microarrays (TMAs) reflect immune cell infiltration compared to the whole tumor slide, in tissue from patients with non-small cell lung cancer. DESIGN.­: A TMA was constructed comprising tissue from surgical resection specimens of 58 patients with non-small cell lung cancer, with available preoperative biopsy material. Whole sections, biopsies, and TMA were stained for the pan-T lymphocyte marker CD3 to determine densities of tumor-infiltrating lymphocytes. Immune cell infiltration was assessed semiquantitatively as well as objectively with a microscopic grid count. For 19 of the cases, RNA sequencing data were available. RESULTS.­: The semiquantitative comparison of immune cell infiltration between the whole section and the biopsy displayed fair agreement (intraclass correlation coefficient [ICC], 0.29; P = .01; CI, 0.03-0.51). In contrast, the TMA showed substantial agreement compared with the whole slide (ICC, 0.64; P < .001; CI, 0.39-0.79). The grid-based method did not enhance the agreement between the different tissue materials. The comparison of CD3 RNA sequencing data with CD3 cell annotations confirmed the poor representativity of biopsies as well as the stronger correlation for the TMA cores. CONCLUSIONS.­: Although overall lymphocyte infiltration is relatively well represented on TMAs, the representativity in diagnostic lung cancer biopsies is poor. This finding challenges the concept of using biopsies to establish immune scores as prognostic or predictive biomarkers for diagnostic applications.

Spatial Transcriptomics: Emerging Technologies in Tissue Gene Expression Profiling.

In this Perspective, we discuss the current status and advances in spatial transcriptomics technologies, which allow high-resolution mapping of gene expression in intact cell and tissue samples. Spatial transcriptomics enables the creation of high-resolution maps of gene expression patterns within their native spatial context, adding an extra layer of information to the bulk sequencing data. Spatial transcriptomics has expanded significantly in recent years and is making a notable impact on a range of fields, including tissue architecture, developmental biology, cancer, and neurodegenerative and infectious diseases. The latest advancements in spatial transcriptomics have resulted in the development of highly multiplexed methods, transcriptomic-wide analysis, and single-cell resolution utilizing diverse technological approaches. In this Perspective, we provide a detailed analysis of the molecular foundations behind the main spatial transcriptomics technologies, including methods based on microdissection, in situ sequencing, single-molecule FISH, spatial capturing, selection of regions of interest, and single-cell or nuclei dissociation. We contextualize the detection and capturing efficiency, strengths, limitations, tissue compatibility, and applications of these techniques as well as provide information on data analysis. In addition, this Perspective discusses future directions and potential applications of spatial transcriptomics, highlighting the importance of the continued development to promote widespread adoption of these techniques within the research community.

Accounting for intensity variation in image analysis of large-scale multiplexed clinical trial datasets.

Multiplex immunofluorescence (mIF) imaging can provide comprehensive quantitative and spatial information for multiple immune markers for tumour immunoprofiling. However, application at scale to clinical trial samples sourced from multiple institutions is challenging due to pre-analytical heterogeneity. This study reports an analytical approach to the largest multi-parameter immunoprofiling study of clinical trial samples to date. We analysed 12,592 tissue microarray (TMA) spots from 3,545 colorectal cancers sourced from more than 240 institutions in two clinical trials (QUASAR 2 and SCOT) stained for CD4, CD8, CD20, CD68, FoxP3, pan-cytokeratin, and DAPI by mIF. TMA slides were multi-spectrally imaged and analysed by cell-based and pixel-based marker analysis. We developed an adaptive thresholding method to account for inter- and intra-slide intensity variation in TMA analysis. Applying this method effectively ameliorated inter- and intra-slide intensity variation improving the image analysis results compared with methods using a single global threshold. Correlation of CD8 data derived by our mIF analysis approach with single-plex chromogenic immunohistochemistry CD8 data derived from subsequent sections indicates the validity of our method (Spearman's rank correlation coefficients ρ between 0.63 and 0.66, p ≪ 0.01) as compared with the current gold standard analysis approach. Evaluation of correlation between cell-based and pixel-based analysis results confirms equivalency (ρ > 0.8, p ≪ 0.01, except for CD20 in the epithelial region) of both analytical approaches. These data suggest that our adaptive thresholding approach can enable analysis of mIF-stained clinical trial TMA datasets by digital pathology at scale for precision immunoprofiling.

Projecting RNA measurements onto single cell atlases to extract cell type-specific expression profiles using scProjection.

Multi-modal single cell RNA assays capture RNA content as well as other data modalities, such as spatial cell position or the electrophysiological properties of cells. Compared to dedicated scRNA-seq assays however, they may unintentionally capture RNA from multiple adjacent cells, exhibit lower RNA sequencing depth compared to scRNA-seq, or lack genome-wide RNA measurements. We present scProjection, a method for mapping individual multi-modal RNA measurements to deeply sequenced scRNA-seq atlases to extract cell type-specific, single cell gene expression profiles. We demonstrate several use cases of scProjection, including identifying spatial motifs from spatial transcriptome assays, distinguishing RNA contributions from neighboring cells in both spatial and multi-modal single cell assays, and imputing expression measurements of un-measured genes from gene markers. scProjection therefore combines the advantages of both multi-modal and scRNA-seq assays to yield precise multi-modal measurements of single cells.

Combination of Tissue Microarray Profiling and Multiplexed IHC Approaches to Investigate Transport Mechanism of Nucleoside Analog Drug Resistance.

Nucleoside analogs (NAs) are an established class of anticancer agents being used clinically for the treatment of diverse cancers, either as monotherapy or in combination with other established anticancer or pharmacological agents. To date, nearly a dozen anticancer NAs are approved by the FDA, and several novel NAs are being tested in preclinical and clinical trials for future applications. However, improper delivery of NAs into tumor cells because of alterations in expression of one or more drug carrier proteins (e.g., solute carrier (SLC) transporters) within tumor cells or cells surrounding the tumor microenvironment stands as one of the primary reasons for therapeutic drug resistance. The combination of tissue microarray (TMA) and multiplexed immunohistochemistry (IHC) is an advanced, high-throughput approach over conventional IHC that enables researchers to effectively investigate alterations to numerous such chemosensitivity determinants simultaneously in hundreds of tumor tissues derived from patients. In this chapter, taking an example of a TMA from pancreatic cancer patients treated with gemcitabine (a NA chemotherapeutic agent), we describe the step-by-step procedure of performing multiplexed IHC, imaging of TMA slides, and quantification of expression of some relevant markers in these tissue sections as optimized in our laboratory and discuss considerations while designing and carrying out this experiment.

Constructing high-density tissue microarrays with a novel method and a self-made tissue-arraying instrument.

Tissue microarrays (TMAs), also called tissue chips, contain hundreds to thousands of tissue cores obtained from different tissue donor blocks. By using TMA technology, a molecular marker, such as protein, RNA or DNA, can be simultaneously examined in hundreds of different specimens under the same experimental conditions. A growing number of previous studies have introduced different methods for constructing TMAs. Many authors tried to use various methods to implant more tissue cores in a single recipient block, and most of these methods involved reducing the diameter of the tissue cores and/or the spacing between adjacent tissue cores. However, when creating TMAs, it is difficult to reduce the distance between tissue cores to zero except with extremely expensive automatic TMA arrayers. Here, we introduce a novel method to construct a high-density TMA that does not have spacing between the tissue cores. We also introduce a method for preparing a self-made tissue-arraying instrument. With this method and the tissue-arraying instrument, we successfully created a TMA containing 126 tissue cores that were 2 mm in diameter. H&E staining and immunohistochemical staining were performed on the sections cut from the TMA without any tissue spot loss. This method is easy to operate, and the materials for creating the tissue-arraying instrument are inexpensive and can be purchased anywhere. Therefore, this method can be applied in all laboratories.

A versatile and tunable bio-patterning platform for the construction of various cell array biochips.

In this work, we report a versatile and tunable platform for the construction of various cell array biochips using a simple soft lithographic approach to pattern polydopamine (PDA) arrays via microcontact printing (µCP). Instead of direct polymerization of PDA on the polydimethylsiloxane (PDMS) tips, dopamine monomers were first printed on the substrate followed by a self-oxidative polymerization step facilitated by ammonia vapor to grow PDA in situ, which greatly reduced the reaction time and prevented the PDMS tips from damaging. The improved robustness and utility of the PDMS tips allows the formation of tunable PDA array chips with controllable PDA feature size and shape. As a result, single cell, multi-cells and cell line arrays can be constructed. The obtained cell array chips showed high single cell capture efficiency, providing a standardized single cell array analysis platform. Meanwhile, the adhered cells can maintain excellent viability and proliferation ability on the PDA chips. Moreover, a cytotoxicity sensor with single cell resolution was enabled on the single cell array chip. This work provides a promising cell array biochip platform for high-throughput cellular analysis and cell screening.

Effect of Age and Sex on Gene Expression-Based Radiation Biodosimetry Using Mouse Peripheral Blood.

Blood-based gene expression profiles that can reconstruct radiation exposure are being developed as a practical approach to radiation biodosimetry. However, age and sex could potentially limit the accuracy of the approach. In this study, we determined the impact of age on the peripheral blood cell gene expression profile of female mice exposed to radiation and identified differences and similarities with a previously obtained transcriptomic signature of male mice. Young (2 months) and old (24 months) female mice were irradiated with 4 Gy X-rays, total RNA was isolated from blood 24 hours later and subjected to whole-genome microarray analysis. Dose reconstruction analyses using a gene signature trained on gene expression data from irradiated young male mice showed accurate reconstruction of 0 or 4 Gy doses with root mean square error of ±0.75 Gy (R2 = 0.90) in young female mice. Although dose reconstruction for irradiated old female mice was less accurate than young female mice, the deviation from the actual radiation dose was not statistically significant. Pathway analysis of differentially expressed genes revealed that after irradiation, apoptosis-related functions were overrepresented, whereas functions related to quantities of various immune cell subtypes were underrepresented, among differentially expressed genes from young female mice, but not older animals. Furthermore, young mice significantly upregulated genes involved in phagocytosis, a process that eliminates apoptotic cells and preserves tissue homeostasis. Both functions were also overrepresented in young, but not old, male mice following 4 Gy X-irradiation. Lastly, functions associated with neutrophil activation that is essential for killing invading pathogens and regulating the inflammatory response were predicted to be uniquely enriched in young but not old female mice. This work supports the concept that peripheral blood gene expression profiles can be identified in mice that accurately predict physical radiation dose exposure irrespective of age and sex.

Cellular microarrays for assessing single-cell phenotypic changes in vascular cell populations.

Microengineering technologies provide bespoke tools for single-cell studies, including microarray approaches. There are many challenges when culturing adherent single cells in confined geometries for extended periods, including the ability of migratory cells to overcome confining cell-repellent surfaces with time. Following studies suggesting clonal expansion of only a few vascular smooth muscle cells (vSMCs) contributes to plaque formation, the investigation of vSMCs at the single-cell level is central to furthering our understanding of atherosclerosis. Herein, we present a medium throughput cellular microarray, for the tracking of single, freshly-isolated vSMCs as they undergo phenotypic modulation in vitro. Our solution facilitates long-term cell confinement (> 3 weeks) utilising novel application of surface functionalisation methods to define individual culture microwells. We demonstrate successful tracking of hundreds of native vSMCs isolated from rat aortic and carotid artery tissue, monitoring their proliferative capacity and uptake of oxidised low-density lipoprotein (oxLDL) by live-cell microscopy. After 7 days in vitro, the majority of viable SMCs remained as single non-proliferating cells (51% aorta, 78% carotid). However, a sub-population of vSMCs demonstrated high proliferative capacity (≥ 10 progeny; 18% aorta, 5% carotid), in line with reports that a limited number of medial SMCs selectively expand to populate atherosclerotic lesions. Furthermore, we show that, when exposed to oxLDL, proliferative cells uptake higher levels of lipoproteins, whilst also expressing greater levels of galectin-3. Our microwell array approach enables long-term characterisation of multiple phenotypic characteristics and the identification of new cellular sub-populations in migratory, proliferative adherent cell types.

Slide-to-Slide Tissue Transfer and Array Assembly From Limited Samples for Comprehensive Molecular Profiling.

Tissue microarrays (TMA) have become an important tool in high-throughput molecular profiling of tissue samples in the translational research setting. Unfortunately, high-throughput profiling in small biopsy specimens or rare tumor samples (eg, orphan diseases or unusual tumors) is often precluded owing to limited amounts of tissue. To overcome these challenges, we devised a method that allows tissue transfer and construction of TMAs from individual 2- to 5-µm sections for subsequent molecular profiling. We named the technique slide-to-slide (STS) transfer, and it requires a series of chemical exposures (so-called xylene-methacrylate exchange) in combination with rehydrated lifting, microdissection of donor tissues into multiple small tissue fragments (methacrylate-tissue tiles), and subsequent remounting on separate recipient slides (STS array slide). We developed the STS technique by assessing the efficacy and analytical performance using the following key metrics: (a) dropout rate, (b) transfer efficacy, (c) success rates using different antigen-retrieval methods, (d) success rates of immunohistochemical stains, (e) fluorescent in situ hybridization success rates, and (f) DNA and (g) RNA extraction yields from single slides, which all functioned appropriately. The dropout rate ranged from 0.7% to 6.2%; however, we applied the same STS technique successfully to fill these dropouts ("rescue" transfer). Hematoxylin and eosin assessment of donor slides confirmed a transfer efficacy of >93%, depending on the size of the tissue (range, 76%-100%). Fluorescent in situ hybridization success rates and nucleic acid yields were comparable with those of traditional workflows. In this study, we present a quick, reliable, and cost-effective method that offers the key advantages of TMAs and other molecular techniques-even when tissue is sparse. The perspectives of this technology in biomedical sciences and clinical practice are promising, given that it allows laboratories to create more data with less tissue.

Identification of novel biomarkers with potential for diagnosis and prognosis of gastric cancer: a bioinformatics approach

INTRODUCTION: Gastric cancer (GC) is the fifth most diagnosed neoplasia and the third leading cause of cancer-related deaths. A substantial number of patients exhibit an advanced GC stage once diagnosed. Therefore, the search for biomarkers contributes to the improvement and development of therapies. OBJECTIVE: This study aimed to identify potential GC biomarkers making use of in silico tools. METHODS: Gastric tissue microarray data available in Gene Expression Omnibus and The Cancer Genome Atlas Program was extracted. We applied statistical tests in the search for differentially expressed genes between tumoral and non-tumoral adjacent tissue samples. The selected genes were submitted to an in-house tool for analyses of functional enrichment, survival rate, histological and molecular classifications, and clinical follow-up data. A decision tree analysis was performed to evaluate the predictive power of the potential biomarkers. RESULTS: In total, 39 differentially expressed genes were found, mostly involved in extracellular structure organization, extracellular matrix organization, and angiogenesis. The genes SLC7A8, LY6E, and SIDT2 showed potential as diagnostic biomarkers considering the differential expression results coupled with the high predictive power of the decision tree models. Moreover, GC samples showed lower SLC7A8 and SIDT2 expression, whereas LY6E was higher. SIDT2 demonstrated a potential prognostic role for the diffuse type of GC, given the higher patient survival rate for lower gene expression. CONCLUSION: Our study outlines novel biomarkers for GC that may have a key role in tumor progression. Nevertheless, complementary in vitro analyses are still needed to further support their potential.