Highly Multiplexed Immunohistochemical MALDI-MS Imaging of Biomarkers in Tissues

Yagnik, Gargey; Liu, Ziying; Rothschild, Kenneth J.; Lim, Mark J.

doi:10.1021/jasms.0c00473

Cited by 74 publications

(111 citation statements)

References 68 publications

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“…Mass spectrometry imaging (MSI), the combination of molecular mass analysis and spatial information, can provide information on the spatial distribution of endogenous and exogenous species in tissue sections, without the need to disrupt sample integrity [146,147]. It enables both untargeted and direct targeted investigations for the discovery of disease or host immune response-related biomarkers, although the sensitivity for intact macromolecules, such as proteins, is still limited [148,149]. Matrix-assisted laser desorption/ionization (MALDI) is the most popular ionization technique for MSI due to its ability to image a wide range of molecular weights and molecular species (e.g., metabolites and proteins).…”

Section: Ex Vivo Multiparametric Analysesmentioning

confidence: 99%

Predictive Markers of Immunogenicity and Efficacy for Human Vaccines

et al. 2021

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Vaccines represent one of the major advances of modern medicine. Despite the many successes of vaccination, continuous efforts to design new vaccines are needed to fight “old” pandemics, such as tuberculosis and malaria, as well as emerging pathogens, such as Zika virus and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Vaccination aims at reaching sterilizing immunity, however assessing vaccine efficacy is still challenging and underscores the need for a better understanding of immune protective responses. Identifying reliable predictive markers of immunogenicity can help to select and develop promising vaccine candidates during early preclinical studies and can lead to improved, personalized, vaccination strategies. A systems biology approach is increasingly being adopted to address these major challenges using multiple high-dimensional technologies combined with in silico models. Although the goal is to develop predictive models of vaccine efficacy in humans, applying this approach to animal models empowers basic and translational vaccine research. In this review, we provide an overview of vaccine immune signatures in preclinical models, as well as in target human populations. We also discuss high-throughput technologies used to probe vaccine-induced responses, along with data analysis and computational methodologies applied to the predictive modeling of vaccine efficacy.

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Section: Ex Vivo Multiparametric Analysesmentioning

confidence: 99%

Predictive Markers of Immunogenicity and Efficacy for Human Vaccines

et al. 2021

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“…Here, the identical IHC stained section could be used for targeting not only specific cell types, but their surrounding niche. Combinations of multiplexed IHC with targeted proteomic access could greatly expand our knowledge of cell subtypes in cancer [61]. Current quantitative approaches in imaging mass spectrometry include on-tissue spotting of standards, internal standards and the mimetic models [62][63][64][65][66].…”

Section: Discussionmentioning

confidence: 99%

Defining the Tumor Microenvironment by Integration of Immunohistochemistry and Extracellular Matrix Targeted Imaging Mass Spectrometry

Rujchanarong

Lefler

Saunders

et al. 2021

Cancers

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Breast stroma plays a significant role in breast cancer risk and progression yet remains poorly understood. In breast stroma, collagen is the most abundantly expressed protein and its increased deposition and alignment contributes to progression and poor prognosis. Collagen post-translation modifications such as hydroxylated-proline (HYP) control deposition and stromal organization. The clinical relevance of collagen HYP site modifications in cancer processes remains undefined due to technical issues accessing collagen from formalin-fixed, paraffin-embedded (FFPE) tissues. We previously developed a targeted approach for investigating collagen and other extracellular matrix proteins from FFPE tissue. Here, we hypothesized that immunohistochemistry staining for fibroblastic markers would not interfere with targeted detection of collagen stroma peptides and could reveal peptide regulation influenced by specific cell types. Our initial work demonstrated that stromal peptide peak intensities when using MALD-IMS following IHC staining (αSMA, FAP, P4HA3 and PTEN) were comparable to serial sections of nonstained tissue. Analysis of histology-directed IMS using PTEN on breast tissues and TMAs revealed heterogeneous PTEN staining patterns and suggestive roles in stromal protein regulation. This study sets the foundation for investigations of target cell types and their unique contribution to collagen regulation within extracellular matrix niches.

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“…Multiplex immunohistochemistry (IHC) as well as imaging Cytometry by time of flight (CyTOF) technologies [41] enable the spatial protein target analysis in tissue sections and, thus, represent capable tools to verify identified protein alterations from MALDI-MSI studies. In order to verify protein findings in large-scale cohorts a highly multiplexed IHC MALDI-MSI approach (up to 12-plex) is promising to confirm proteins from MALDI-MSI findings as parallel untargeted label-free investigation of small molecules [42].…”

Section: Discussionmentioning

confidence: 99%

Peptide Signatures for Prognostic Markers of Pancreatic Cancer by MALDI Mass Spectrometry Imaging

Loch

Klein

Beyer

et al. 2021

Biology

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Despite the overall poor prognosis of pancreatic cancer there is heterogeneity in clinical courses of tumors not assessed by conventional risk stratification. This yields the need of additional markers for proper assessment of prognosis and multimodal clinical management. We provide a proof of concept study evaluating the feasibility of Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) to identify specific peptide signatures linked to prognostic parameters of pancreatic cancer. On 18 patients with exocrine pancreatic cancer after tumor resection, MALDI imaging analysis was performed additional to histopathological assessment. Principal component analysis (PCA) was used to explore discrimination of peptide signatures of prognostic histopathological features and receiver operator characteristic (ROC) to identify which specific m/z values are the most discriminative between the prognostic subgroups of patients. Out of 557 aligned m/z values discriminate peptide signatures for the prognostic histopathological features lymphatic vessel invasion (pL, 16 m/z values, eight proteins), nodal metastasis (pN, two m/z values, one protein) and angioinvasion (pV, 4 m/z values, two proteins) were identified. These results yield proof of concept that MALDI-MSI of pancreatic cancer tissue is feasible to identify peptide signatures of prognostic relevance and can augment risk assessment.

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Highly Multiplexed Immunohistochemical MALDI-MS Imaging of Biomarkers in Tissues

Cited by 74 publications

References 68 publications

Predictive Markers of Immunogenicity and Efficacy for Human Vaccines

Predictive Markers of Immunogenicity and Efficacy for Human Vaccines

Defining the Tumor Microenvironment by Integration of Immunohistochemistry and Extracellular Matrix Targeted Imaging Mass Spectrometry

Peptide Signatures for Prognostic Markers of Pancreatic Cancer by MALDI Mass Spectrometry Imaging

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