EACR

Prevention and treatment of colorectal cancer liver metastases represent a significant clinical challenge, requiring novel approaches to characterize disease biology. Dr. Xenia Maria Ficht will focus on the pivotal roles of cell-cell interactions during metastatic growth and treatment response. By leveraging spatial biology techniques, such as spatial transcriptomics and automated high-plex imaging, she will talk about comprehensively profile metastatic heterogeneity and characterize local tumor niches. This multimodal approach enables the identification of critical cellular interactions linked to disease progression and functional outcomes, providing valuable insights into metastatic tumor ecosystems. In addition, we will demonstrate how Lunaphore provides end-to-end solutions for spatial biology from multiplexed images to image analysis. We will present how the COMET™ platform performs sequential immunofluorescence (seqIF™) to obtain high-quality and reproducible data with standard off-the-shelf antibodies. COMET™ also integrates a signal amplification technology to enhance signal sensitivity for low-expressed or challenging markers, without compromising accuracy. Additionally, attendees will explore our innovative multiomics application that combines RNAscope™ and seqIF™ to simultaneously identify RNA and protein targets on the same tissue section in a fully automated workflow. We will unveil HORIZON™ image analysis, which transforms multiplexed images into spatial data. Our distinctive spatial biology approach empowers scientists to identify new molecular signatures and bolster the development of targeted therapies.

INTRODUCTION:

Melanoma exhibits significant tumoral heterogeneity, with several melanoma cell states (mCS) identified through single-cell RNA sequencing (scRNA-seq). Although some mCS have been linked to poor immunotherapy response, their role in metastasis is still hypothetical. Immunohistochemistry, the most widely used diagnostic technique, identifies cellular phenotypes affecting diagnosis and treatment. However, since mCS signatures were discovered at the transcriptomic level, validating their protein expression is crucial. Moreover, while most ESpM cases have favorable prognoses and are not followed after excision, 10% of patients develop metastatic disease. Identifying biomarkers to predict progression is therefore essential. This study aims to (1) validate RNA-protein correlation at the single-cell level using an innovative spatial technology enabling simultaneous RNA and protein detection in the same cell; (2) investigate the presence of mCS in ESpM; (3) compare mCS enrichment and spatial distribution in metastatic (M+) vs. non-metastatic (M−) ESpM. 

MATERIAL AND METHOD: 

We assembled a cohort of 10 ESpM cases (5 M+ vs. 5 M−), matched for key clinicopathological prognostic factors to minimize bias. A single tissue section per case was analyzed using the Hyperplex multiomics technology on Lunaphore’s COMET instrument. A panel of 24 proteins (MITF, MelanA, AQP1, S100B, SOX10, SOX9, NGFR, TCF4, PDGFRb, BRAF, FAP, CD3, CD4, CD8, CD20, FOXP3, CD68, CD163, podoplanin, MECA79/pNA, αSMA, CK, CD31, and CD45) and 12 RNAs (THY1, MLANA, S100A1, S100B, SOX10, TCF4, ID3, PRAME, TYR, COL5A1, COL1A1, and PMEPA1) was selected to assess RNA-protein correlation for mCS markers and explore their spatial relationship with the inflammatory microenvironment. RNAs were chosen based on minimal signatures from relevant studies. Evaluating protein and RNA markers simultaneously was also evaluated. For data processing and integration, we developed a novel bioinformatics software, DISSCOVERY, specifically designed for the integrated analysis of high-dimensional multiplex IF and spatial transcriptomics data. 

RESULTS AND DISCUSSION: 

MelanA showed strong RNA-protein correlation, whereas SOX10, S100A1, and TCF4 protein expression did not align with their RNA levels. Significant heterogeneity in mCS was observed across samples. Trajectory analyses were performed using protein, RNA, and hybrid approaches. M+ ESpM showed enrichment in undifferentiated mCS subtypes, whereas M− cases, despite heterogeneous melanoma marker expression, had minimal undifferentiated mCS content. 

CONCLUSION: 

This study underscores the importance of multiomics approaches in translating RNA-based signatures into protein-level markers. Unique melanoma cell subtypes identified in this study may serve as potential prognostic markers for high-risk ESpM. 

INTRODUCTION:

Colorectal cancer (CRC) is one of the deadliest cancers worldwide. Increasing incidence and mortality rates highlight the need for a more in–depth understanding of its underlying characteristics. Since tumor heterogeneity contributes to therapy resistance and disease progression, it is crucial to identify biomarkers at both the protein and RNA levels. Long non–coding RNAs (lncRNAs) are considered promising biomarkers in CRC, but despite their potential role in cancer prognosis and diagnosis, their spatial distribution is not well understood. We aim to address this knowledge gap by leveraging the COMET™ multiomics platform. Here, immuno– fluorescence (mIF) has been recently integrated with RNAscope™ (RNA fluorescence in situ hybridization, RNA–FISH) to enable multiplexed imaging of RNA and protein on the same slide. This approach will provide an unprecedented view of lncRNA protein interactions in CRC.

MATERIAL AND METHOD:

We will select formalin–fixed, paraffin–embedded (FFPE) healthy and CRC specimens covering stages I–IV to construct a tissue microarray (TMA). Using the COMET™ system combined with RNAscope™ technology, we aim to dissect the spatial distribution of selected lncRNAs (MALAT1, ANRIL, NEAT1, and TUG1), which have been shown to play a role in CRC progression. The multiplex immunofluorescence panel consists of EMT markers (E–cadherin, N–cadherin, Vimentin, Fibronectin, ZEB1, ZEB2), proliferation markers (Ki–67, PCNA), stromal markers (CD44, Plexin B2, α–SMA, Desmin, CD31, CD45), and CRC–specific markers (Pan–CK, CDX2, SATB2).

RESULT AND DISCUSSION:

We assume that multiplex imaging will reveal distinct lncRNA expression patterns across CRC stages. Patients with MALAT1+/ZEB1+/N–cadherin+ profiles have been shown to have poorer outcomes. Our hypothesis is that MALAT1 and NEAT1 may be significantly upregulated in advanced CRC (Stages III–IV) and could correlate with an EMT shift, quantified by high N–cadherin/ZEB1/ ZEB2 and low E–cadherin expression. Similarly, ANRIL and TUG1, potentially localized predominantly in stromal regions, might increase in Stage II tumors, suggesting a role in microenvironment remodeling. We anticipate that ANRIL expression could correlate with stromal activation (α–SMA, Desmin, CD31), while high CD45 levels may inversely correlate with MALAT1 expression, potentially indicating immune evasion. Additionally, we hypothesize that the loss of CDX2 and SATB2 could be associated with EMT–driven dedifferentiation.

CONCLUSION:

Acquiring spatial information on lncRNAs associated with poor tumor prognosis and proteins involved in EMT activation across different CRC stages will provide key insights into their interactions. This may help link these lncRNA–protein interactions to both tumor progression and the functional role of the lncRNAs

INTRODUCTION:

Inflammation and immune cells in the tumor micro– environment play a critical role in colorectal cancer (CRC) progression. Notably, sex differences exist in CRC incidence, with men at higher risk. Estrogen has protective effects against CRC, and intestinal estrogen receptor beta (ERβ) has been shown to reduce colitis and CRC development. However, its role in shaping the colonic inflammatory immune landscape remains unclear.

MATERIAL AND METHOD:

Using the COMET multiplex immunofluorescence platform, we analyzed colonic tissues from wild–type (WT) and ERβKO–Vil mice (N=32) to assess immune cell infiltration with full spatial context. Unsupervised clustering, spatial image analysis (SPIAT), and manual quantification were performed to characterize immune cell populations. Additionally, plasma cytokine assays were used to evaluate systemic immune responses. Macrophage polarization assays were conducted to examine the effects of CRC signaling on macrophage differentiation in vitro.

RESULT AND DISCUSSION:

Our findings reveal that intestinal ERβ plays a role in modulating the colonic immune microenvironment under both healthy and inflammatory conditions. Loss of ERβ significantly alters macrophage infiltration, with a pronounced effect in males. Furthermore, we observed regional differences in immune cell distribution. ERβKOVil mice exhibited an amplified systemic immune response to colitis and CRC, suggesting a broader regulatory role for ERβ in inflammation. In vitro, macrophage polarization assay did not show ERβ– dependent differences.

CONCLUSION:

These findings highlight the sex–dependent effects of intestinal ERβ in shaping the colonic immune landscape. ERβ deficiency leads to altered macrophage dynamics and heightened systemic inflammation, particularly in males. This provides novel insights into the sex–specific development of CRC and suggests the possibility of using ERβ–selective ligands as immune modulators in CRC.

INTRODUCTION:

Perineural invasion (PNI), the spread of cancer cells along nerves, is a hallmark of pancreatic ductal adeno– carcinoma (PDAC) and is associated with poor prognosis, local recurrence, and metastasis. However, the biological processes underlying these outcomes remain unclear.

MATERIAL AND METHOD:
To address this gap, we used spatial transcriptomics (10x Genomics Visium) to profile cancer–invaded and non–invaded nerves from three PDAC patients in situ.

RESULT AND DISCUSSION:

Transcriptomic analysis, combined with multiplexed immunofluorescence, showed that cancer infiltration induces nerve damage, leading to changes in the nerve secretome. Among the upregulated factors, we identified DRAXIN, an axon–guidance protein involved in neural development but with a largely unexplored role in cancer. Functional assays, including in vitro proliferation studies and CRISPR–based screens, demonstrated that recombinant DRAXIN induces cancer cell death.

CONCLUSION:

These findings provide new insights into the molecular changes in cancer–infiltrated nerves and highlight DRAXIN as a nerve–derived factor with anti–tumor properties.

INTRODUCTION: 

 Multiplex immunofluorescence (mIF) is a crucial technique in studying the tumor microenvironment (TME) and identifying biomarkers (PMID: 31502166). The varying marker expression levels carry significant biological meaning, revealing insights into cellular functions (PMID: 34112666). Detecting markers at different expression levels is essential but challenging, often requiring signal amplification for improved detection (PMID: 25242720). Here, we introduce seqLA™, an automated method for amplifying individual markers in multiplex panels, providing adjustable amplification levels and efficient elution for consecutive staining cycles. 

MATERIAL AND METHOD: 

 Using COMET™ platform, which performs automated sequential immunofluorescence (seqIF™) assays (PMID: 37813886), the seqLA™ method augments the number of detection antibodies per primary antibody cyclically, leading to intensified signals. The amplification complex can be eluted, enabling successive staining cycles while upholding tissue integrity. Using formalin-fixed paraffin-embedded (FFPE) tissue sections from human colorectal and breast carcinoma, a 26-plex panel comprising 20 standard seqIF™ markers for immune and stroma compartments with 6 markers (LAG-3, ICOS, TCF-1, FOXP3, PD-1, and PD-L1) detected with the seqLA™ method. Staining was compared with single-plex chromogenic immunohistochemistry (IHC) for each amplified marker (PMID: 32414858). The dynamic range of FOXP3, PD-1, and PD-L1 signals between amplified and unamplified staining was compared. Lunaphore HORIZON™ software was used for image analysis, cell segmentation, classification, and phenotyping.. 

RESULTS AND DISCUSSION: 

We successfully incorporated 6 amplified markers into a 20-plex seqIF™ panel. Our amplification method yielded an adjustable signal intensity increase between low and high expressing cell populations, enabling a broader dynamic range compared to unamplified seqIF™ markers. Notably, amplification facilitated the detection of the full expression spectrum of PD-1 and PD-L1, delving into various low-expressing subtypes of regulatory immune cells like Treg and macrophages within the TME. Also, the staining patterns of amplified markers exhibited a strong correlation with chromogenic IHC staining. Combining amplified markers within a larger panel enabled an enhanced analysis of the TME and complex immune cell classification within tertiary lymphoid structures. 

CONCLUSION: 

 The integration of this novel amplification strategy into seqIF™ panels will empower the identification of markers expressed at low levels. This enhancement will capture the complete expression spectrum of crucial immune checkpoint markers. Analyzing multiple markers simultaneously while accommodating selective amplification will enhance the profiling of immune and tumoral cells within their distinct environments.