Quantification Of Protein Expression Research Articles

Quantitative tissue analysis reveals AK2, COL1A1, & PLG protein signatures: Targeted therapeutics for meningioma.

Meningioma is the most prevalent primary intracranial brain tumor and accounts for one-third of all CNS tumors. Meningioma is known to be the most common yet life-threatening brain tumor with a higher recurrence rate. Globally, there is an increase in the healthcare burden due to meningioma and hence in its research. The present clinical approach includes surgical resection, chemotherapy, and radiation therapies to which the malignancy does not seem to respond efficiently. Targeted therapies and molecular markers provide elite patient treatment and care for individuals suffering from meningiomas as compared to conventional measures. Although there is proteomic data on meningioma the knowledge of potential biomarkers differentiating the grades is scarce. To identify the best set of biomarkers, validation of reported markers in large and independent sample cohorts in the future is necessary. A total of 12 samples, 3 each of control (which made pool 1) Meningioma grade I (which made 2 sets: pool 2 and pool 3), and Meningioma grade II (which made pool 4) were taken for LC-MS/MS. After this, the expression of three proteins was checked by immunocytochemistry, flow cytometry, and western blotting. Protein expression was analyzed using various techniques like mass spectrometry, immunocytochemistry, flow cytometry, and western blotting. Mass spectrometry is the most commonly used standard and reliable technique for identifying and quantifying protein expression. We got three highly upregulated proteins namely AK2, COL1A1, and PLG using this technique. The biomarker potential of these proteins was further checked by ICC, western blotting, and flow cytometry. Three important proteins were found to be upregulated namely AK2 (Adenylate Kinase 2), COL1A1 (Collagen 1A1), and PLG (Plasminogen). The order of increased protein expression was control < MG grade I < MG grade II according to mass spectrometry and western blotting. In immunocytochemistry, we found that COL1A1 expression increases significantly with grades in comparison to control. Similarly, AK2 and PLG also showed little increase but not as much as COL1A1. In flow cytometry, PLG showed higher upregulation in grades than control. While AK2 and COL1A1 showed little increase in expression in grades than control. All techniques, especially mass spectrometry and western blotting presented higher expression of these proteins in grades as compared to control. In the quest to find a suitable therapeutic marker, this study incorporates quantitative labeling and detection followed by flow cytometry, Immunocytochemistry, and western blotting for early diagnosis and treatment of meningioma. The article further explores the efficacy of some proteins namely AK2, COL1A1 & PLG to be the targeted molecules.

Abstract B073: Organ-specific diversity of tumor immune microenvironment in metastatic pancreatic cancer

Abstract Pancreatic ductal adenocarcinoma (PDAC) that is refractory to treatment frequently leads to extensive systemic and multi-organ metastases. PDAC is characterized as an immune “cold” cancer; however, the persistence of this “cold” tumor immune microenvironment (TIME) across distant metastases, and the mechanisms by which metastases influence their respective TIME, remain poorly understood. In this study, we conducted spatial protein expression profiling of the TIME using the Nanostring GeoMx Digital Spatial Profiling (DSP) platform. We employed a 43- plex panel on 54 tissue samples, including 14 primary tumors and 40 matched metastases from organs commonly affected by PDAC metastases (liver, lung, and peritoneum), obtained through a rapid (“warm”) autopsy program. We quantified protein expression in three cellular compartments: PanCK+ epithelial cells, α-SMA+ fibroblasts, and CD45+ immune cells, across 181 regions of interest (ROIs). Our analysis revealed a significant enrichment of CD45+ immune cells in lung metastases compared to other organ sites, with a notably lower presence of these cells in liver metastases. Focusing on the immune cell compartment, we analyzed the CD45 segments for further investigation. After normalization using housekeeping proteins, including Histone H3, GAPDH, and ribosomal protein S6, we found that the immune profiles were most distinct between liver and lung metastases. Specifically, liver metastases exhibited the greatest deviation in immune profile compared to primary PDAC, lung, and peritoneal metastases. We scored protein expression signatures for various immune cell subsets based on specific marker expressions. When comparing liver to lung metastases, scores for T cells, myeloid cells, checkpoint markers, macrophages, and interferon signaling were significantly lower in the liver, underscoring the immune “coldness” of the liver metastasis environment. Our cohort included six untreated patients and nine patients treated with chemotherapies. We compared protein expressions in each organ site between untreated and treated patients. Notably, treatment induced divergent expression patterns of multiple proteins between liver and lung metastases. While treatment significantly reduced the expression of several immune markers, including CD45 (total immune), CD3 (T cell), CD4 (T helper cell), CD45RO (memory T cell), CD163 (M2 macrophage), and B7-H3 (checkpoint marker), in lung metastases, these markers were significantly upregulated in liver metastases of treated patients. This finding indicates a pronounced divergence in TIME modulation in response to treatment between liver and lung metastases, potentially fostering a treatment-resistant environment in PDAC patients with multi- organ metastasis. Consequently, this urges the need to develop tailored therapeutic strategies for PDAC metastasis, taking into account the distinct immune landscapes of different metastasis sites. Citation Format: Jimin Min, Vittorio Branchi, Kimal I Rajapakshe, Nisha Narayanan, Guangsheng Pei, Linghua Wang, Jean L Grem, Thomas C Caffrey, Paul M Grandgenett, Michael A Hollingsworth, Paola A Guerrero, Anirban Maitra. Organ-specific diversity of tumor immune microenvironment in metastatic pancreatic cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr B073.

281. PROTEOMIC, TRANSCRIPTOMIC AND GENOMIC ANALYSIS OF ESOPHAGEAL ADENOCARCINOMA UNCOVERS CANDIDATE THERAPEUTIC TARGETS AND CANCER-SELECTIVE POST-TRANSCRIPTIONAL REGULATION

Abstract Background Addressing the poor prognosis associated with esophageal adenocarcinoma (EAC) has been hindered by the absence of biomarkers for early disease detection and therapeutic targets. Despite extensive research on the somatic mutations associated with EAC, the impact of genomic aberrations on protein expression and cancer phenotype remains unclear. Methods We conducted a quantitative proteomic analysis using tumour tissue and patient-matched adjacent normal esophageal and gastric tissues from 23 patients undergoing resection for EAC. We further examined the relationship between transcript and protein levels using patient-matched whole transcriptome RNA sequencing and proteomic data from 7 patients and integrated these findings with data from a cohort of 264 EAC patients with RNA sequencing and 454 patients with whole-genome sequencing, as well as external published datasets. Results We quantified protein expression from 5897 genes in EAC and normal tissues. Several potential biomarkers showing selective expression in EAC, such as the transmembrane protein GPA33, were identified. We validated the EAC-specific expression of GPA33 in an external cohort of 115 patients, suggesting its utility as a diagnostic and therapeutic target. Additionally, integrated analysis of protein and RNA expression in EAC and normal tissues revealed genes with discordant protein and RNA levels, indicating post-transcriptional regulation of protein expression. These outlier genes, including SLC25A30, TAOK2, and AGMAT, exhibited rare somatic mutations, suggesting post-transcriptional mechanisms driving this EAC-specific phenotype. AGMAT, as an example, was found to be overexpressed at the protein level in EAC compared to adjacent normal tissues, with a proposed EAC-selective, post-transcriptional mechanism regulating protein abundance. Conclusion Through quantitative proteomic analysis, we identified GPA33 as a candidate EAC biomarker. Integrated analysis of the proteome, transcriptome, and genome in EAC uncovered genes with tumor-selective post-transcriptional regulation of protein expression, offering potential exploitable vulnerabilities for therapeutic intervention.

A cross-reactive imaging matrix of membrane protein profiling for single-cell analysis

Membrane proteins play a critical role in cellular processes such as chemical transport, signal transduction, and enzymatic catalysis. A comprehensive understanding of membrane protein types and accurately measuring their expression levels are essential for advancing cell biology. However, current methods often fail to characterize the types and amounts of multiple membrane proteins in specific cell types due to inherent measurement limitations. Here, we have developed a single-cell image analysis technique based on a cross-reactive imaging matrix using membrane protein tags. This technique allows quantitative and qualitative analysis of multiple membrane protein types and their expression levels within single cells. As a proof of concept, we used four specific DNA aptamers to tag four different membrane proteins in seven different cell types. The four proteins are MUC1, EGFR, HeR2, and TLR4. The seven cell lines are 3t3, 4T1, A549, CT26, HeLa, Hepa1–6, Raw, respectively. We captured a comprehensive image matrix using wide-field fluorescence imaging, allowing precise quantification of protein expression at the single-cell level. Our approach introduces a multi-labeling analysis method for membrane proteins and reveals the influence of membrane protein diversity on cell heterogeneity analysis. We found that the accuracy of cell heterogeneity recognition can be affected by adjusting the number of membrane proteins. As the diversity of membrane protein species increases, the accuracy of cell type recognition increases. Our approach facilitates the evaluation of heterogeneity in diverse cells, providing new insights into cellular diversity and a powerful tool for studying single-cell biology.

Multi-Omic Analysis of Esophageal Adenocarcinoma Uncovers Candidate Therapeutic Targets and Cancer-Selective Posttranscriptional Regulation

Efforts to address the poor prognosis associated with esophageal adenocarcinoma (EAC) have been hampered by a lack of biomarkers to identify early disease and therapeutic targets. Despite extensive efforts to understand the somatic mutations associated with EAC over the past decade, a gap remains in understanding how the atlas of genomic aberrations in this cancer impacts the proteome and which somatic variants are of importance for the disease phenotype. We performed a quantitative proteomic analysis of 23 EACs and matched adjacent normal esophageal and gastric tissues. We explored the correlation of transcript and protein abundance using tissue-matched RNA-seq and proteomic data from seven patients and further integrated these data with a cohort of EAC RNA-seq data (n = 264 patients), EAC whole-genome sequencing (n = 454 patients), and external published datasets. We quantified protein expression from 5879 genes in EAC and patient-matched normal tissues. Several biomarker candidates with EAC-selective expression were identified, including the transmembrane protein GPA33. We further verified the EAC-enriched expression of GPA33 in an external cohort of 115 patients and confirm this as an attractive diagnostic and therapeutic target. To further extend the insights gained from our proteomic data, an integrated analysis of protein and RNA expression in EAC and normal tissues revealed several genes with poorly correlated protein and RNA abundance, suggesting posttranscriptional regulation of protein expression. These outlier genes, including SLC25A30, TAOK2, and AGMAT, only rarely demonstrated somatic mutation, suggesting post-transcriptional drivers for this EAC-specific phenotype. AGMAT was demonstrated to be overexpressed at the protein level in EAC compared to adjacent normal tissues with an EAC-selective, post-transcriptional mechanism of regulation of protein abundance proposed. Integrated analysis of proteome, transcriptome, and genome in EAC has revealed several genes with tumor-selective, posttranscriptional regulation of protein expression, which may be an exploitable vulnerability.

Higher Synovial Immunohistochemistry Reactivity of IL-17A, Dkk1, and TGF-β1 in Patients with Early Psoriatic Arthritis and Rheumatoid Arthritis Could Predict the Use of Biologics.

Delay in diagnosis and therapy in patients with arthritis commonly leads to progressive articular damage. The study aimed to investigate the immunohistochemical reactivity of synovial cytokines associated with inflammation and the bone erosives/neoformatives processes among individuals diagnosed with psoriatic arthritis (PsA), rheumatoid arthritis (RA), osteoarthritis (OA), and radiographic axial spondyloarthritis (r-axSpA), with the intention of identifying potential biomarkers. Specimens were collected from the inflamed knee joints of patients referred for arthroscopic procedures, and the synovial tissue (ST) was prepared for quantifying protein expression through immunohistochemical analysis (% expressed in Ratio_Area-Intensity) for TGF-β1, IL-17A, Dkk1, BMP2, BMP4, and Wnt5b. The collected data underwent thorough analysis and examination of their predictive capabilities utilising receiver operating characteristic (ROC) curves. Valid synovial tissue samples were acquired from 40 patients for IHC quantification analysis. Initially, these patients had not undergone treatment with biologics. However, after 5 years, 4 out of 13 patients diagnosed with PsA and two out of nine patients diagnosed with RA had commenced biologic treatments. Individuals with early PsA who received subsequent biologic treatment exhibited significantly elevated IHC reactivity in ST for TGF-β1 (p = 0.015). Additionally, patients with both PsA and RA who underwent biologic therapy displayed increased IHC reactivity for IL-17A (p = 0.016), TGF-β1 (p = 0.009), and Dkk1 (p = 0.042). ROC curve analysis of IHC reactivity for TGF-β1, Dkk1, and IL-17A in the synovial seems to predict future treatment with biologics in the next 5 years with the area under the curve (AUC) of a combined sum of the three values: AUC: 0.828 (95% CI: 0.689-0.968; p 0.005) S 75% E 84.4%. Higher synovial immunohistochemistry reactivity of IL-17A, Dkk1, and TGF-β1 in patients with early psoriatic arthritis and rheumatoid arthritis may serve as potential indicators for predicting the necessity of utilising biologic treatments.

Design of a Stem Cell-Based Therapy for Ependymal Repair in Hydrocephalus Associated With Germinal Matrix Hemorrhages.

In preterm birth germinal matrix hemorrhages (GMHs) and the consequent posthemorrhagic hydrocephalus (PHH), the neuroepithelium/ependyma development is disrupted. This work is aimed to explore the possibilities of ependymal repair in GMH/PHH using a combination of neural stem cells, ependymal progenitors (EpPs), and mesenchymal stem cells. GMH/PHH was induced in 4-day-old mice using collagenase, blood, or blood serum injections. PHH severity was characterized 2 weeks later using magnetic resonance, immunofluorescence, and protein expression quantification with mass spectrometry. Ependymal restoration and wall regeneration after stem cell treatments were tested in vivo and in an ex vivo experimental approach using ventricular walls from mice developing moderate and severe GMH/PHH. The effect of the GMH environment on EpP differentiation was tested in vitro. Two-tailed Student t or Wilcoxon-Mann-Whitney U test was used to find differences between the treated and nontreated groups. ANOVA and Kruskal-Wallis tests were used to compare >2 groups with post hoc Tukey and Dunn multiple comparison tests, respectively. PHH severity was correlated with the extension of GMH and ependymal disruption (means, 88.22% severe versus 19.4% moderate). GMH/PHH hindered the survival rates of the transplanted neural stem cells/EpPs. New multiciliated ependymal cells could be generated from transplanted neural stem cells and more efficiently from EpPs (15% mean increase). Blood and TNFα (tumor necrosis factor alpha) negatively affected ciliogenesis in cells committed to ependyma differentiation (expressing Foxj1 [forkhead box J1] transcription factor). Pretreatment with mesenchymal stem cells improved the survival rates of EpPs and ependymal differentiation while reducing the edematous (means, 18% to 0.5% decrease in severe edema) and inflammatory conditions in the explants. The effectiveness of this therapeutical strategy was corroborated in vivo (means, 29% to 0% in severe edema). In GMH/PHH, the ependyma can be restored and edema decreased from either neural stem cell or EpP transplantation in vitro and in vivo. Mesenchymal stem cell pretreatment improved the success of the ependymal restoration.

Abstract 4121: Unveiling discordant views of a novel drug's influence on cell motility from proteomics and immunofluorescence perspectives

Abstract Introduction: Metastasis is a leading cause of death in patients with solid tumors. Our group has discovered KBU2046, a selective inhibitor of cell motility (Nature Communications 2018). We conducted a time-course immunofluorescent staining to investigate the impact of KBU2046 on the cell adhesion and motility components of human prostate cancer cells. Our objective was to compare our findings with our proteomic analysis results in order to gain insights into the novel molecular mechanisms of KBU2046 in modulating cell motility. Experimental Procedures: Proteomics analysis. We treated PC3 cells with KBU2046 or vehicle (N=3/group) and quantified protein expression using Liquid Chromatography/Tandem Mass Spectrometry (LC-MS/MS). In separate experiments (N=4), we performed LC-MS/MS after Tandem Mass Tag (TMT) labeling on isolated membrane fractions. We used bioinformatics tools, including Gene Set Enrichment Analysis (GSEA), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Ingenuity Pathway Analysis (IPA), and protein-protein interaction (PPI) network analysis, to characterize significantly differentially expressed proteins upon KBU2046 treatment and tried to verify by Western blots. Immunofluorescence (IF) staining. Following treatment of PC3, 1532CPTX, and 1532NPTX cells with KBU2046 or vehicle at various intervals, cells were stained for β1, β5 integrin, actin, and DAPI. Images were acquired by a Zeiss LSM 800 Confocal Laser Scanning Microscope. Results: The proteomics analysis demonstrated that KBU2046 was having a major impact on cell motility processes, consistent with our prior functional studies. Despite conducting Western blot analysis, we could not confirm the candidate proteins linked to cell adhesion. Using IF, we examined changes in cell adhesion proteins over time in response to KBU2046 treatment. The time-course IF investigation revealed that KBU2046 affects adhesion proteins kinetically by altering their subcellular localization over time rather than altering their total expression level. This finding corroborates KBU2046's known effects on cell motility, demonstrating that a kinetic-based analysis yields important new information not directly represented in a single time point screen, although functionally related. Conclusions: Our study underscores the importance of integrating proteomic and imaging methodologies to procure a holistic comprehension of the molecular mechanisms that govern cell behavior, especially those that relate to highly dynamic processes. Through these methodologies, we have obtained a more profound understanding of how cells regulate motility and how that process can be therapeutically modulated. Citation Format: Weining Chen, Nicholas Woods, Henry Chun Hin Law, Fangfang Qiao, Sankarasubramanian Jagadesan, Chittibabu Guda, Raymond Bergan. Unveiling discordant views of a novel drug's influence on cell motility from proteomics and immunofluorescence perspectives [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4121.

Abstract 5481: Spatial multiplex proteins profiling of tumor microenvironment to decipher de novo metastasis in nasopharyngeal carcinoma

Abstract Background: Nasopharyngeal carcinoma (NPC) has a high incidence rate in Southeast Asia, where more than 90% of NPC cases are associated with Epstein-Barr virus (EBV). Although NPC patients are generally sensitive to radiotherapy and chemotherapy, about 20-30% of patients have treatment failure due to the development of distant metastasis, i.e. de novo metastasis. In this study, we utilized GeoMx Digital Spatial Profiler (DSP), a multiplex and high-throughput sequencing platform designed for spatially- and morphologically resolved protein expression profiling to investigate the intra-tumoral and inter-tumoral heterogeneity of tumor microenvironment (TME) and identify the mechanisms underlying distant failure in NPC. Methods: We utilized GeoMx Protein Assays consisting of 147 proteins from 15 functional modules to compare the difference between NPC cases developing distant failure (DF) (n=21) and stage-, age-, gender- and treatment-matched NPC cases without developing distant failure (noDF) (n=15) within five years of treatment. Two fluorescent morphological markers including PanCK and CD45, were used for delineating the structural architecture of the tissues, identifying cell types, and selecting regions of interest (ROIs), followed by sequencing for protein expression quantification. NanoString GeoMx DSP Analysis Suite was used for quality control and data normalization. The NPC TME heterogeneity was further investigated by the 10X Visum platform for spatial transcriptome. The public single-cell RNA sequencing (scRNA-Seq) and bulk RNA sequencing datasets were obtained for the downstream analyses. Results: By analyzing protein expression profiles, the study revealed the intratumoral and intertumoral heterogeneity associated with EBV latent infection in the TME of NPC. Regions with high EBV latent gene expression exhibited a noticeable reduction in T cell infiltration, indicating an "immune cold" phenotype, whereas regions with low EBV latent gene expression displayed heavy T cell infiltration, indicating an "immune hot" phenotype. Moreover, the study identified a panel of autophagic and anti-apoptotic proteins that were significantly upregulated in the cancer cells of NPC cases developing distant failure after treatment. This observation, supported by the single-cell RNA sequencing datasets, further implicated EBV latent infection for the upregulation of autophagic and anti-apoptotic genes. Notably, the study also demonstrated that the genes upregulated in the immune cells in NPC cases with distant failure were associated with poor progression-free survival in an independent NPC cohort. Conclusions: These findings shed light on the crucial role of EBV latent infection in TME heterogeneity and highlight the potential involvement of autophagy and anti-apoptosis in de novo metastasis in NPC. Citation Format: Larry Ka-Yue Chow, Ying Wang, Lanqi Gong, Siqi Xu, Zhaozheng Hou, Xinyuan Guan, Dora Lai-Wan Kwong, Victor Ho-Fun Lee, Wai To ng, Anne Wing-Mui Lee, Zhonghua Liu, Yunfei Xia, Wei Dai. Spatial multiplex proteins profiling of tumor microenvironment to decipher de novo metastasis in nasopharyngeal carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5481.

In vitro broad-spectrum antiviral activity of MIT-001, a mitochondria-targeted reactive oxygen species scavenger, against severe acute respiratory syndrome coronavirus 2 and multiple zoonotic viruses

The COVID-19 pandemic caused by SARS-CoV-2 becomes a serious threat to global health and requires the development of effective antiviral therapies. Current therapies that target viral proteins have limited efficacy with side effects. In this study, we investigated the antiviral activity of MIT-001, a small molecule reactive oxygen species (ROS) scavenger targeting mitochondria, against SARS-CoV-2 and other zoonotic viruses in vitro. The antiviral activity of MIT-001 was quantified by RT-qPCR and plaque assay. We also evaluated the functional analysis of MIT-001 by JC-1 staining to measure mitochondrial depolarization, total RNA sequencing to investigate gene expression changes, and immunoblot to quantify protein expression levels. The results showed that MIT-001 effectively inhibited the replication of B.1.617.2 and BA.1 strains, Zika virus, Seoul virus, and Vaccinia virus. Treatment with MIT-001 restored the expression of heme oxygenase-1 (HMOX1) and NAD(P)H: quinone oxidoreductase 1 (NqO1) genes, anti-oxidant enzymes reduced by SARS-CoV-2, to normal levels. The presence of MIT-001 also alleviated mitochondrial depolarization caused by SARS-CoV-2 infection. These findings highlight the potential of MIT-001 as a broad-spectrum antiviral compound that targets for zoonotic RNA and DNA viruses, providing a promising therapeutic approach to combat viral infection.

Unveiling proteomic diversity: A quantitative study of antibody drug conjugate and chemotherapy targets in gastroesophageal cancer.

261 Background: Gastroesophageal cancer (GEC), is a significant global health concern with a 5-year relative survival of 7% for metastatic GEC. Standard treatments often include surgery, chemotherapy, and radiation therapy, but their effectiveness can be limited. Chemotherapy is frequently utilized in the treatment of GEC, although no biomarkers for chemotherapy are used in the selection of the chemo agent. There are several well-known biomarkers of resistance and sensitivity for various chemo agents. We used targeted proteomics to quantify protein expression levels of several protein biomarkers associated with chemotherapy efficiency in 125 GEC patients. These include resistance markers for platinum agents (ERCC1), and tubulin inhibitors (TUBB3). It also includes sensitivity markers for irinotecan/topotecan (Topo1), and doxorubicin/etoposide (Topo2A). We also assessed the protein levels of several antibodies-drug conjugate markers (EGFR, Her2, Trop2, FR-alpha, Mesothelin, Axl, CLDN18.2, and Nectin-4). Methods: FFPE tumor tissues from 125 clinical GC patients were microdissected and solubilized for mass spectrometry-based targeted proteomic analysis in our CLIA-certified laboratory. 72 proteins were quantified from 2-3 sections of FFPE tissue. Results: 5-Fluorouracil (5-FU), taxanes, and platinum agents (such as carboplatin) are among the chemotherapy agents that are frequently used to treat GEC. TYMP, a sensitivity marker for 5-FU, was expressed in 32% of GEC cases. ERCC1, a resistance marker for platinum drugs, was expressed at 34%. Additionally, 48% of GEC exhibited TUBB3, a resistance marker for paclitaxel and docetaxel. Topoisomerase 1 (Topo1) is the target for irinotecan or topotecan, and is also the target for some ADCs (e.g. trastuzumab deruxtecan, sacituzumab govitecan etc.). Topo1 was expressed in 92% of GEC with a 10x range (415 - 4195 amol/μg). Another topoisomerase, Topo2A, targetable by etoposide, epirubicin, and doxorubicin, was expressed in 59% of GEC with 19x range (402-7804 amol/μg). ADC targets, such as EGFR (82% detected with 184x range of distribution), Her3 (18%, 4x), AXL (18%,7x), MET (27%, 19x), and Trop2 (50%, 57x) showed a wide range of protein expression. With a 56x range (318 - 17786 amol/μg), Her2 was found in 46% of GEC, of which 12% of GEC had overexpression of Her2 (&gt;740 amol/μg), suggesting that the majority of GEC has low levels of Her2 (318-690 amol/μg), which is potentially targetable by newer anti-Her2 agents. Conclusions: Every cancer is different, and the ability to quantitate simultaneously 72 protein biomarkers from 2-3 FFPE sections provides a wealth of actionable information that, when combined with other multi-omics biomarker data, will help guide clinical treatment or patient stratification for clinical trials.

Novel quantitative immunohistochemistry method using histone H3, family 3B as the internal reference standard for measuring human epidermal growth factor receptor 2 expression in breast cancer.

Immunohistochemistry (IHC) is an essential technique in surgical and clinical pathology for detecting diagnostic, prognostic, and predictive biomarkers for personalized cancer therapy. However, the lack of standardization and reference controls results in poor reproducibility, and a reliable tool for IHC quantification is urgently required. The objective of this study was to describe a novel approach in which H3F3B (histone H3, family 3B) can be used as an internal reference standard to quantify protein expression levels using IHC. The authors enrolled 89 patients who had human epidermal growth factor receptor 2 (HER2)-positive breast cancer (BC). They used a novel IHC-based assay to measure protein expression using H3F3B as the internal reference standard. H3F3B was uniformly expressed at the protein level in all tumor regions in cancer tissues. HER2 expression levels were measured with the H-score using HALO software. Kaplan-Meier analysis indicated that, among patients who had HER2-positive BC in The Cancer Genome Atlas data set and the authors' data set, the subgroup with low HER2 expression had a significantly better prognosis than the subgroup with high HER2 expression. Furthermore, the authors observed that HER2 expression levels were precisely evaluated using the proposed method, which can classify patients who are at higher risk of HER2-positive BC to receive trastuzumab-based adjuvant therapy. Dual-color IHC with H3F3B is an excellent tool for internal and external quality control of HER2 expression assays. The proposed IHC-based quantification method accurately assesses HER2 expression levels and provides insights for predicting clinical prognosis in patients with HER2-positive BC who receive trastuzumab-based adjuvant therapy.

A Chromogenic Quantification of Protein Expression in Zebrafish Larvae.

Western blot is a versatile and widely used technique in many areas of molecular biology and biotechnology for studying different protein characteristics. In general, the Western blot technique involves the extraction of proteins from the samples such as cells or tissues, which, after denaturation, are separated by molecular size using electrophoresis. The protein is then transferred to a membrane, typically PVDF or nitrocellulose, which, after blocking, is probed with specific antibodies labeled with a detection agent. Overall, this allows the recognition and binding to the target protein allowing the visualization of bands, a step called immunodetection. Over the years, new approaches to the Western blotting technique have been proposed to overcome performance limitations.This chapter describes a routine procedure for protein evaluation in zebrafish (Danio rerio) larvae, a widely used animal model for predicting the toxicity of drugs, by using a chromogenic substrate and allowing the proper execution of the technique without the costly equipment needed for detection.

KDM4A-AS1 Promotes Cell Proliferation, Migration, and Invasion via the miR-4306/STX6 Axis in Hepatocellular Carcinoma.

As a primary liver malignancy, hepatocellular carcinoma (HCC) is commonly induced by chronic liver disease and cirrhosis. Bioinformatics analysis reveals that long noncoding RNA KDM4A antisense RNA 1 (KDM4A-AS1) may be aberrantly expressed in HCC and its abnormal expression might influence prognosis in patients. We conducted this study to illustrate the functions and mechanism of KDM4A-AS1 in regulating HCC malignant cell behavior. KD-M4A-AS1, microRNA (miR)-4306 and messenger RNA syntaxin 6 (STX6) expression was examined by reverse transcription-quantitative polymerase chain reaction (RT-qPCR). HCC cell proliferation, apoptosis, migration, and invasion were measured by colony forming assays, flow cytometry, wound healing and Transwell assays. The interaction between genes was verified by RNA immunoprecipitation and luciferase reporter assays. Western blotting was performed to quantify protein expression of STX6 or apoptotic markers. KDM4A-AS1 was highly expressed in HCC cells and tissues. KDM4A-AS1 knockdown led to enhanced HCC cell apoptosis and suppressed HCC cell proliferation, migration, and invasion. MiR-4306 bound to and negatively regulated STX6. KDM4A-AS1 directly bound to miR-4306 and thus up-regulated STX6. STX6 overexpression reversed the inhibitory influence of KDM4A-AS1 depletion on HCC malignant behavior. KDM4A-AS1 promotes HCC cell migration, invasion, and growth by upregulating STX6 via miR-4306.

Filleting and Immunostaining of Larvae to Visualize Drosophila Dendritic Arborization Neuron Dendrite Arbors.

Nervous system formation involves the specification of neuron identity, followed by precise circuit construction; this includes controlling the pattern and connectivity of the dendrite arbor. Drosophila dendritic arborization (da) neurons are a powerful experimental model for studying dendrite arbor differentiation mechanisms. da neuron dendrite arbors elaborate in two dimensions in the body wall, making it easy to visualize them with high resolution. Immunostaining is a conventional method to examine arbor pattern and the subcellular distribution of proteins. In addition, images acquired from immunostaining protocols can amplify weaker signals from fluorescent transgenic proteins and be used to quantify protein expression levels. This protocol describes a broadly applicable dissection, fixation, and immunostaining approach in Drosophila larvae.

Emerging role and clinical implication of mRNA scavenger decapping enzyme in colorectal cancer

BackgroundTurnover of RNA is a regulated process that in part controls gene expression. This process is partly controlled by the scavenger decapping enzyme (DcpS). This study aimed to investigate the expression of DcpS in colorectal cancer (CRC) tissue, to evaluate its prognostic significance in patients with CRC and to investigate potentially targeted genes by DcpS. MethodsImmunohistochemical analysis was used to determine localization of DcpS in normal and CRC tissue, western blot analysis for quantification of protein expression and qPCR for mRNA expression in normal and CRC tissue and expression in cell lines after silencing using siRNA. Gene array analysis was used to study regulation of genes after silencing of DcpS. Proliferation was studied using BRDU. ResultsDcpS expression was localized to the epithelial cells of both control and cancer tissue. Tumor and paired control tissue samples from 100 patients who underwent surgical resection for primary colorectal adenocarcinomas were utilized. mRNA and protein of DcpS was significantly up-regulated in the patients with CRC and the mRNA level was higher in rectal cancer tissue compared to colon cancer tissue (p < 0.05). Lowest tertile levels of DcpS mRNA in cancer tissue was associated with a decreased cancer-specific survival rate with a hazard ratio (HR) of 4.7 (95% CI=1.02–12.3), independent of disease stage. The low level of DcpS mRNA was a predictor of poorer survival in patients with rectal and disseminated cancer and in patients receiving adjuvant treatment (p < 0.05). After silencing DcpS in Caco-2 cancer cells, altered expression of several genes associated with RNA, cell cycle regulation, alternative splicing and microRNA was observed and resulted in 23% increase in proliferation. ConclusionsThese results indicate that DcpS has potential as a prognostic factor for CRC but further studies in a broader cohort are warranted to evaluate the significance of the findings in the clinic.

Multiplex fluorescence detection of single-cell droplet microfluidics and its application in quantifying protein expression levels.

This study presented a platform of multiplex fluorescence detection of single-cell droplet microfluidics with demonstrative applications in quantifying protein expression levels. The platform of multiplex fluorescence detection mainly included optical paths adopted from conventional microscopy enabling the generation of three optical spots from three laser sources for multiple fluorescence excitation and capture of multiple fluorescence signals by four photomultiplier tubes. As to platform characterization, microscopic images of three optical spots were obtained where clear Gaussian distributions of intensities without skewness confirmed the functionality of the scanning lens, while the controllable distances among three optical spots validated the functionality of fiber collimators and the reflector lens. As to demonstration, this platform was used to quantify single-cell protein expression within droplets where four-type protein expression of α-tubulin, Ras, c-Myc, and β-tubulin of CAL 27 (Ncell = 1921) vs WSU-HN6 (Ncell = 1881) were quantitatively estimated, which were (2.85 ± 0.72) × 105 vs (4.83 ± 1.58) × 105, (3.69 ± 1.41) × 104 vs (5.07 ± 2.13) × 104, (5.90 ± 1.45) × 104 vs (9.57 ± 2.85) × 104, and (3.84 ± 1.28) × 105 vs (3.30 ± 1.10) × 105, respectively. Neural pattern recognition was utilized for the classification of cell types, achieving successful rates of 69.0% (α-tubulin), 75.4% (Ras), 89.1% (c-Myc), 65.8% (β-tubulin), and 99.1% in combination, validating the capability of this platform of multiplex fluorescence detection to quantify various types of single-cell proteins, which could provide comprehensive evaluations on cell status.

Investigating neuronal senescence marker, p19INK4d, in mouse and human brains

AbstractBackgroundThe cellular senescence stress response allows damaged, toxic cells to survive. Clearing senescent cells is a promising therapeutic approach and has moved to clinical trials for Alzheimer’s disease and related dementias (ADRD). We previously identified a link between the cell cycle inhibitor CDKN2D/p19INK4d and neuronal senescence in human postmortem brains with various levels of AD neuropathology. We hypothesized that senescence could be induced by overexpressing this gene in mouse neurons in vivo.MethodAdeno‐associated virus 9 (AAV9) with the neuron specific human Synapsin I (hSyn1) promoter was used to deliver experimental Cdkn2d‐GFP, or control GFP gene expression. Precise delivery of 0.5µl of 1013 IU virus into four neuronal populations per mouse, bilateral hippocampal CA1 and cortical layer 5 neurons was accomplished with the assistance of a stereotaxic robot. Male and female wild type, human tau transgenic and mouse tau knockout mice were used (12‐13 months‐old, n = 47). Mice were euthanized at either two weeks or eight weeks post‐surgery to determine the short‐ and long‐term effects of Cdkn2d expression. GeoMx digital spatial profiler was utilized to quantify protein expression between Cdkn2d infected and uninfected neighboring neurons. ROI selection is displayed in Figure 1.ResultHistological analyses confirmed p19INK4d protein expression in AAV9‐infected cells. GeoMx DSP analyses performed on hippocampus, cortex, and thalamus revealed a protein expression pattern consistent with senescence (i.e., resistance to apoptosis), in Cdkn2d‐expressing neurons of the hippocampus and cortex compared to the un‐infected thalamus (Figure 2). Moreover, proteins associated with apoptosis were higher in the thalamus compared to the cortex and hippocampus.ConclusionsThe data indicates that AAV9‐hSyn1‐Cdkn2d‐GFP is an appropriate method to increase p19INK4d expression in mouse neurons in vivo. Over‐expressing p19INK4d caused neurons to acquire a protein expression signature consistent with senescence. The concomitant expression of apoptosis proteins in the thalamus leads me to hypothesize that the senescent cells in the cortex may cause cell death in the thalamus through the corticothalamic tract. Further studies with increased sample size are needed to confirm the results and continue exploring the effects of Cdkn2d on neuronal senescence, and how tau protein may influence this stress response.

Deep Learning–Based H-Score Quantification of Immunohistochemistry-Stained Images

Immunohistochemistry (IHC) is a well-established and commonly used staining method for clinical diagnosis and biomedical research. In most IHC images, the target protein is conjugated with a specific antibody and stained using diaminobenzidine (DAB), resulting in a brown coloration, whereas hematoxylin serves as a blue counterstain for cell nuclei. The protein expression level is quantified through the H-score, calculated from DAB staining intensity within the target cell region. Traditionally, this process requires evaluation by 2 expert pathologists, which is both time consuming and subjective. To enhance the efficiency and accuracy of this process, we have developed an automatic algorithm for quantifying the H-score of IHC images. To characterize protein expression in specific cell regions, a deep learning model for region recognition was trained based on hematoxylin staining only, achieving pixel accuracy for each class ranging from 0.92 to 0.99. Within the desired area, the algorithm categorizes DAB intensity of each pixel as negative, weak, moderate, or strong staining and calculates the final H-score based on the percentage of each intensity category. Overall, this algorithm takes an IHC image as input and directly outputs the H-score within a few seconds, significantly enhancing the speed of IHC image analysis. This automated tool provides H-score quantification with precision and consistency comparable to experienced pathologists but at a significantly reduced cost during IHC diagnostic workups. It holds significant potential to advance biomedical research reliant on IHC staining for protein expression quantification.

Adapting an Isobaric Tag-Labeled Yeast Peptide Standard to Develop Targeted Proteomics Assays.

Targeted proteomics strategies present a streamlined hypothesis-driven approach to analyze specific sets of pathways or disease related proteins. goDig is a quantitative, targeted tandem mass tag (TMT)-based assay that can measure the relative abundance differences for hundreds of proteins directly from unfractionated mixtures. Specific protein groups or entire pathways of up to 200 proteins can be selected for quantitative profiling, while leveraging sample multiplexing permits the simultaneous analysis of up to 18 samples. Despite these benefits, implementing goDig is not without challenges, as it requires access to an instrument application programming interface (iAPI), an elution order and spectral library, a web-based method builder, and dedicated companion software. In addition, the absence of an example test assay may dissuade researchers from testing or implementing goDig. Here, we repurpose the TKO11 standard─which is commercially available but may also be assembled in-lab─and establish it as a de facto test assay for goDig. We build a proteome-wide goDig yeast library, quantify protein expression across several gene ontology (GO) categories, and compare these results to a fully fractionated yeast gold-standard data set. Essentially, we provide a guide detailing the goDig-based quantification of TKO11, which can also be used as a template for user-defined assays in other species.