European Society for Spatial Biology (ESSB)

Multiplexed immunofluorescence (mIF) and RNA in situ hybridization (ISH) allow simultaneous detection of multiple protein and RNA biomarkers. Combining spatial assays on the same tissue section is essential to increasing our knowledge of complex tissues, such as tumor microenvironments or neural tissues. Extracting precise information on cellular interconnections, neuronal connectivity, and signaling activity is key to understanding the biological processes involved in development and disease.  

Here, we present a novel, fully automated approach that integrates the RNAscope™ HiPlexPro assay and sequential immunofluorescence (seqIF™) protocols for the co-detection of RNA and protein targets on the same tissue section on the COMET™ platform. The multiomics protocol was applied to mouse tissues and frozen sections for the first time, demonstrating the versatility and robustness of the approach.    

We automated RNAscope™ and seqIF™ protocols on COMET™  for the simultaneous detection of RNAs and proteins. The system ensures precise temperature control and reagent distribution, critical for maintaining the integrity of frozen sections, and allows for a multiplexing capability of up to 12-plex RNA and 24-plex protein targets.   

We demonstrated that the combination of RNAscope™ and seqIF™ protocols on COMET™ enables the simultaneous detection of RNA and protein biomarkers on sensitive frozen tissues while ensuring high reproducibility and minimal user intervention.  

RNAscope™ probes targeting biomarkers relevant to neuronal function, including neurotransmitters and receptors, and other glial cells, were combined to protein markers profiling multiple cell types in their microenvironment, including several types of infiltrating immune cells (such as CD3+, F4/80+, CD11c+, or CD56+ cells).  

Our findings demonstrate the successful application of the combined RNAscope™ and seqIF™ protocols on the COMET™ platform to analyze delicate, high-autofluorescence tissues and non-human tissues. These results demonstrate the approach’s versatility and robustness and open the door to potential new applications in the immuno-oncology field, including biomarker and drug development.  

Multiplex immunofluorescence (mIF) has become fundamental for tumor microenvironment (TME). Markers with different expression levels can provide crucial insights, but detecting low-expressed markers often benefits from signal amplification. Here, we demonstrate a new automated method enabling the amplification of individual markers within multiplex panels.  

COMET™ is an automated platform that performs sequential immunofluorescence (seqIF™) assays. This amplification method increases the number of detection antibodies per primary antibody in a cyclic manner, leading to a stronger signal. The amplification complex can be eluted, enabling subsequent staining cycles while preserving tissue integrity. Human colorectal and breast carcinoma samples were stained using a 26-plex panel including 20 markers in standard seqIF™ and 6 amplified markers, together covering most basic immune cells, functions, and stroma. The performance was assessed by comparing marker expression with and without amplification and amplified staining to single-plex chromogenic immunohistochemistry (IHC) for each marker. 

Six amplified markers were integrated within a 20-plex seqIF™ panel. Amplified low-expressed markers were reliably detected with a controllable signal intensity increase between low and high-expressing cell populations, providing a higher dynamic range than unamplified seqIF™. Amplification enabled the detection of the full spectrum of PD-1 and PD-L1 expression intensity and the identification of several low-expressing subtypes of regulatory immune cells, such as Treg and macrophages, within the TME. The staining patterns of amplified markers showed a good correlation with chromogenic IHC, and elution of the amplification complex did not damage the tissue.  

Hyperplex seqIF™ panels integrating this novel amplification technique will enable the detection of low-expressed markers, such as the full expression range of critical immune checkpoint markers that could not robustly capture with non-amplified methods. Analyzing a high number of markers simultaneously while allowing selective amplification will improve the profiling of immune and tumoral cells within their environment.  

Spatial omics technologies enable detailed molecular analyses directly from tissue. In parallel, multi-omics approaches that combine different omics levels to obtain a holistic view are increasingly in demand. However, performing spatial multi-omics data analysis presents several challenges. Data is typically acquired on serial tissue sections, at different spatial resolutions, in a variety of data formats, requiring expertise across multiple domains to obtain the best results from each individual technology. We present software that addresses the need for spatial multi-omics bioinformatics solutions, enabling efficient integration and joint visualization of different assays.

Weave is a cloud-based spatial omics data management and data analysis software platform. We demonstrate the software via two spatial multi-omics use cases:

• Combining lipid MSI (timsTOF fleX, Bruker) with multiplexed sequential immunofluorescence (mIF, COMET, Lunaphore) and histology images of fresh-frozen mouse brain
• The comparison of two antibody-based spatial proteomic assays; MALDI-IHC (Ambergen) and IMC (Standard Biotools) measured on mouse lymph node.

Image registration was performed using a non-rigid algorithm, allowing accurate translation of the data acquired from different modalities. Data integration was conducted to obtain a homogeneous data structure across assays of different spatial resolutions, providing a foundation for joint downstream data analysis and visualization. Joint visualization and data analysis reveals spatial correlations between different lipids and proteins in the mouse brain. Similarities and differences in readouts between IMC and MALDI-IHC were confirmed by overlaying both datasets onto H&E-stained images of the samples.

This work introduces an innovative spatial multiomics methodology for the simultaneous analysis of RNA and protein within tumor tissue. The approach offers in-depth characterization of the tumor microenvironment, facilitating the discovery of critical biomarkers and therapeutic targets.