Antibodies validated for routinely processed tissues stain frozen sections unpredictably

Seeing or believing in hyperplexed spatial proteomics via antibodies: New and old biases for an image-based technology

Hyperplexed in-situ targeted proteomics via antibody immunodetection (i.e., >15 markers) is changing how we classify cells and tissues. Differently from other high-dimensional single-cell assays (flow cytometry, single-cell RNA sequencing), the human eye is a necessary component in multiple procedural steps: image segmentation, signal thresholding, antibody validation, and iconographic rendering. Established methods complement the human image evaluation, but may carry undisclosed biases in such a new context, therefore we re-evaluate all the steps in hyperplexed proteomics. We found that the human eye can discriminate less than 64 out of 256 gray levels and has limitations in discriminating luminance levels in conventional histology images. Furthermore, only images containing visible signals are selected and eye-guided digital thresholding separates signal from noise. BRAQUE, a hyperplexed proteomic tool, can extract, in a marker-agnostic fashion, granular information from markers which have a very low signal-to-noise ratio and therefore are not visualized by traditional visual rendering. By analyzing a public human lymph node dataset, we also found unpredicted staining results by validated antibodies, which highlight the need to upgrade the definition of antibody specificity in hyperplexed immunostaining. Spatially hyperplexed methods upgrade and supplant traditional image-based analysis of tissue immunostaining, beyond the human eye contribution.

Validation of an organ mapping antibody panel for cyclical immunofluorescence microscopy on normal human kidneys

The lack of standardization in antibody validation remains a major contributor to irreproducibility of human research. To address this, we have applied a standardized approach to validate a panel of antibodies to identify 18 major cell types and 5 extracellular matrix compartments in the human kidney by immunofluorescence (IF) microscopy. We have used these to generate an organ mapping antibody panel for two-dimensional (2-D) and three-dimensional (3-D) cyclical IF (CyCIF) to provide a more detailed method for evaluating tissue segmentation and volumes using a larger panel of markers than would normally be possible using standard fluorescence microscopy. CyCIF also makes it possible to perform multiplexed IF microscopy of whole slide images, which is a distinct advantage over other multiplexed imaging technologies that are applicable to limited fields of view. This enables a broader view of cell distributions across larger anatomical regions, allowing a better chance to capture localized regions of dysfunction in diseased tissues. These methods are broadly accessible to any laboratory with a fluorescence microscope, enabling spatial cellular phenotyping in normal and disease states. We also provide a detailed solution for image alignment between CyCIF cycles that can be used by investigators to perform these studies without programming experience using open-sourced software. This ability to perform multiplexed imaging without specialized instrumentation or computational skills opens the door to integration with more highly dimensional molecular imaging modalities such as spatial transcriptomics and imaging mass spectrometry, enabling the discovery of molecular markers of specific cell types, and how these are altered in disease.NEW & NOTEWORTHY We describe here validation criteria used to define on organ mapping panel of antibodies that can be used to define 18 cell types and five extracellular matrix compartments using cyclical immunofluorescence (CyCIF) microscopy. As CyCIF does not require specialized instrumentation, and image registration required to assemble CyCIF images can be performed by any laboratory without specialized computational skills, this technology is accessible to any laboratory with access to a fluorescence microscope and digital scanner.

A DNA damage response-like phenotype defines a third of colon cancers at onset

Colon adenocarcinoma (COAD) has a limited range of diversified, personalized therapeutic opportunities, besides DNA hypermutating cases; thus, both new targets or broadening existing strategies for personalized intervention are of interest. Routinely processed material from 246 untreated COADs with clinical follow-up was probed for evidence of DNA damage response (DDR), that is, the gathering of DDR-associated molecules at discrete nuclear spots, by multiplex immunofluorescence and immunohistochemical staining for DDR complex proteins (γH2AX, pCHK2, and pNBS1). We also tested the cases for type I interferon response, T-lymphocyte infiltration (TILs), and mutation mismatch repair defects (MMRd), known to be associated with defects of DNA repair. FISH analysis for chromosome 20q copy number variations was obtained. A total of 33.7% of COAD display a coordinated DDR on quiescent, non-senescent, non-apoptotic glands, irrespective of TP53 status, chromosome 20q abnormalities, and type I IFN response. Clinicopathological parameters did not differentiate DDR+ cases from the other cases. TILs were equally present in DDR and non-DDR cases. DDR+ MMRd cases were preferentially retaining wild-type MLH1. The outcome after 5FU-based chemotherapy was not different in the two groups. DDR+ COAD represents a subgroup not aligned with known diagnostic, prognostic, or therapeutic categories, with potential new targeted treatment opportunities, exploiting the DNA damage repair pathways.

BRAQUE: Bayesian Reduction for Amplified Quantization in UMAP Embedding

Single-cell biology has revolutionized the way we understand biological processes. In this paper, we provide a more tailored approach to clustering and analyzing spatial single-cell data coming from immunofluorescence imaging techniques. We propose Bayesian Reduction for Amplified Quantization in UMAP Embedding (BRAQUE) as an integrative novel approach, from data preprocessing to phenotype classification. BRAQUE starts with an innovative preprocessing, named Lognormal Shrinkage, which is able to enhance input fragmentation by fitting a lognormal mixture model and shrink each component towards its median, in order to help further the clustering step in finding more separated and clear clusters. Then, BRAQUE's pipeline consists of a dimensionality reduction step performed using UMAP, and a clustering performed using HDBSCAN on UMAP embedding. In the end, clusters are assigned to a cell type by experts, using effects size measures to rank markers and identify characterizing markers (Tier 1), and possibly characterize markers (Tier 2). The number of total cell types in one lymph node detectable with these technologies is unknown and difficult to predict or estimate. Therefore, with BRAQUE, we achieved a higher granularity than other similar algorithms such as PhenoGraph, following the idea that merging similar clusters is easier than splitting unclear ones into clear subclusters.

Rejuvenated Vintage Tissue Sections Highlight Individual Antigen Fate During Processing and Long-term Storage

Antigen-bearing proteins become progressively unavailable to immunodetection after prolonged storage of routine sections, exposed to a variety of agents, such as moisture, oxygen, and temperature. By proteomic analysis, the antigens are retained in the sections and definitely in the tissue block, pointing to fixation-independent, storage time–dependent protein modifications. Based on previous experience, we hypothesized that a combined exposure to a reducing agent and to chemicals favoring protein conformation changes would reverse the masking in aged sections. Disaccharides, lactose and sucrose, and a surfactant, added to a standard antigen retrieval buffer, reverse the negative changes in aged sections. Furthermore, they provide enhanced access to antigens in freshly cut sections, but not universally, revealing additional factors, besides heat and calcium chelation, required for antigen retrieval of individual proteins: