Biology subjects

de Miranda, N. F. C. C.

Publications and source records attributed to de Miranda, N. F. C. C..

8 recordsLinked to original sources

bioRxiv2025

Immune infiltration is linked to increased transcriptional activity and distinct metabolic profiles in chordomas

Chordomas are ultra-rare cancers from the axial skeleton with limited treatment options. Chordomas can exhibit immunogenic features, and immune checkpoint blockade has demonstrated clinical activity in some patients, yet the determinants of these responses remain poorly understood. We aimed to elucidate the biological basis of immunogenicity in chordomas through spatial transcriptomic and metabolomic analyses. We applied GeoMx digital spatial profiling to 15 chordomas, analyzing tumor and stromal compartments separately and comparing inflamed and non-inflamed tumors. Consecutive tissue sections were examined using MALDI-mass spectrometry imaging (MSI) at 20 {micro}m spatial resolution. Findings were further explored through immunohistochemistry analyses. To assess whether transcriptional activity in tumor cells was associated with interferon-{gamma} (IFN-{gamma}) signaling, we tested the effect of IFN-{gamma} treatment on chordoma cell lines. Digital spatial profiling of inflamed and non-inflamed chordomas revealed striking differences in both the cancer cell and stromal compartments. Increased immune infiltration was strongly associated with elevated transcriptional activity in cancer cells. MALDI-MSI revealed distinct metabolic signatures and pronounced glycogen accumulation in inflamed chordomas. Nevertheless, IFN-{gamma} stimulation of chordoma cell lines did not induce expression of TBXT (brachyury), the master transcriptional regulator of chordoma biology. Collectively, our findings reveal a strong association between the transcriptomic and metabolic activity in chordomas and their immunogenicity. However, the causal direction of this relationship remains to be determined. Nevertheless, these findings are highly relevant for patient stratification, particularly in the context of immunotherapeutic strategies.

cancer biology↗

bioRxiv2025

GRIDGEN: Guided Region Identification based on Density of GENes - a transcript density-based approach to characterize tissues by spatial transcriptomics

Spatial omics brought unprecedented power to study biological processes within tissues while preserving spatial context and morphology. Most spatial proteomics and transcriptomics analyses methods are cell-centric, relying on cell segmentation to identify and characterize individual cells before downstream tasks. However, certain biological questions may be better addressed using cell-free approaches, which also eliminate unnecessary computations when cell segmentation is not essential. To address this need, we developed GRIDGENE (Guided Region Identification based on Density of GENEs), an approach for defining regions of interest based on transcript density. GRIDGENE enables the identification of biologically relevant tissue compartments, including interfaces between regions, phenotype-enriched areas, and zones defined by specific gene signatures, supporting analyses such as pathway enrichment. We demonstrated the utility of GRIDGENE by applying it to spatial transcriptomics data from CosMx and Xenium platforms in colorectal cancer (CRC) samples. By bypassing cell segmentation, our approach enables flexible analysis of spatial omics data, supporting the study of biological processes across diverse tissue structures and microenvironments. Nevertheless, GRIDGENE can be easily integrated with cell segmentation strategies for complementary analyses. GRIDGENE thus broadens the analytical toolkit for spatial omics, enabling both cell-free and cell-based insights.

bioinformatics↗

bioRxiv2025

Divergent Therapeutic and Prognostic Impacts of Immunogenic Features in Undifferentiated Soft Tissue Sarcoma and Myxofibrosarcoma

Myxofibrosarcoma and undifferentiated soft tissue sarcoma (USTS) are genetically complex soft tissue sarcomas with distinct morphological features. Treatment typically involves surgery, often combined with neoadjuvant chemo- or radiotherapy. To better understand the immunobiology of these sarcomas and its associations with treatment response and prognosis, we performed transcriptomic and immunophenotypic profiling. RNA sequencing was performed on 13 USTS and 10 myxofibrosarcomas and immunological profiles were compared with soft tissue sarcoma data from The Cancer Genome Atlas (n = 206 including 44 USTS and 17 myxofibrosarcomas). Immune contextures were further evaluated in 16 USTS and 11 myxofibrosarcomas using imaging mass cytometry. Characterization of T cell and macrophage infiltration in tumors was further assessed in 23 USTS and 22 myxofibrosarcomas through multispectral immunofluorescence and immunohistochemical analysis. USTS and myxofibrosarcomas demonstrated immunogenic features compared to other soft tissue sarcomas, with subsets of USTS and myxofibrosarcomas demonstrating high T cell infiltration while USTS demonstrated a higher infiltration by myeloid cells as compared to myxofibrosarcoma. Prognostically, T cells and CD68+CD163+ macrophages were associated with metastasis-free survival in USTS but not in myxofibrosarcomas. Notably, in USTS, neoadjuvant radiotherapy appeared to induce cytotoxic T cell infiltration and depletion of myeloid cells, whereas these effects were not observed in myxofibrosarcomas. These findings highlight important differences in the immunobiology of USTS and myxofibrosarcomas with therapeutic and prognostic implications. These differences should be taken into account given the growing availability of immunotherapeutic options for treating patients with soft tissue sarcomas.

cancer biology↗

bioRxiv2024

PENGUIN: A rapid and efficient image preprocessing tool for multiplexed spatial proteomics

Multiplex spatial proteomic methodologies can provide a unique perspective on the molecular and cellular composition of complex biological systems. Several challenges are associated to the analysis of imaging data, in particular regarding the normalization of signal-to-noise ratios across images and background noise subtraction. However, straightforward and user-friendly solutions for denoising multiplex imaging data that are applicable to large datasets are still lacking. We have developed PENGUIN -Percentile Normalization GUI Image deNoising: a rapid and efficient image preprocessing tool for multiplexed spatial proteomics. In comparison to existing approaches, PENGUIN stands out by eliminating the need for manual annotation or machine learning model training. It effectively preserves signal intensity differences and reduces noise, thereby enhancing downstream tasks like cell segmentation and phenotyping. PENGUINs simplicity, speed, and user-friendly interface, deployed both as script and as a Jupyter notebook, facilitate parameter testing and image processing. We illustrate the effectiveness of PENGUIN by comparing it with conventional image processing techniques and solutions tailored for multiplex imaging data. This comparison underscores PENGUINs capability to produce high-quality imaging data efficiently and consistently.

bioinformatics↗

bioRxiv2023

Multimodal profiling of chordoma immunity reveals distinct immune contextures

Chordomas are cancers from the axial skeleton presenting immunological hallmarks of unknown significance. In recent years, some clinical trials demonstrated that chordomas can respond to immunotherapy. We present a comprehensive characterisation of immunological features of 76 chordomas through application of a multimodal approach comprising transcriptional profiling, multidimensional immunophenotyping and TCR profiling. Chordomas generally presented an immune "hot" microenvironment in comparison to other sarcomas, as indicated by the immunologic constant of rejection transcriptional signature. We identified two distinct groups of chordomas based on T cell infiltration. The highly infiltrated group was further characterised by high dendritic cell infiltration and the presence of multicellular immune aggregates in tumours, whereas low T cell infiltration was associated with lower overall cell densities of immune and stromal cells. Interestingly, patients with higher T cell infiltration displayed a more pronounced clonal enrichment of the T cell receptor repertoire compared to those with low T cell counts. Furthermore, we observed that the majority of chordomas maintained HLA class I expression. Our findings shed light on the natural immunity against chordomas. Understanding their immune landscape could guide the development and application of immunotherapies in a tailored manner, ultimately leading to an improved clinical outcome for chordoma patients.

cancer biology↗

bioRxiv2021

OX40 agonism enhances efficacy of PD-L1 checkpoint blockade by shifting the cytotoxic T cell differentiation spectrum

Immune checkpoint therapy (ICT) has the potency to eradicate cancer but the mechanisms that determine effective versus non-effective therapy-induced immune responses are not fully understood. Here, using high-dimensional single-cell profiling we examined whether T cell states in the blood circulation could predict responsiveness to a combined ICT, sequentially targeting OX40 costimulatory and PD-1 inhibitory pathways, which effectively eradicated syngeneic mouse tumors. Unbiased assessment of transcriptomic alterations by single-cell RNA sequencing and profiling of cell-surface protein expression by mass cytometry revealed unique activation states for therapy-responsive CD4+ and CD8+ T cells. Effective ICT elicited T cells with dynamic expression of distinct NK cell and chemokine receptors, and these cells were systemically present in lymphoid tissues and in the tumor. Moreover, NK cell receptor-expressing CD8+ T cells were also present in the peripheral blood of immunotherapy-responsive cancer patients. Targeting of the NK cell and chemokine receptors in tumor-bearing mice showed their functional importance for therapy-induced anti-tumor immunity. These findings provide a better understanding of ICT and highlight the use of dynamic biomarkers on effector CD4+ and CD8+ T cells to improve cancer immunotherapy.

immunology↗

bioRxiv2021

γδ T cells are effectors of immune checkpoint blockade in mismatch repair-deficient colon cancers with antigen presentation defects

DNA mismatch repair deficient (MMR-d) cancers present an abundance of neoantigens that likely underlies their exceptional responsiveness to immune checkpoint blockade (ICB)1,2. However, MMR-d colon cancers that evade CD8+ T cells through loss of Human Leukocyte Antigen (HLA) class I-mediated antigen presentation3-6, frequently remain responsive to ICB7 suggesting the involvement of other immune effector cells. Here, we demonstrate that HLA class I-negative MMR-d cancers are highly infiltrated by {gamma}{delta} T cells. These {gamma}{delta} T cells are mainly composed of V{delta}1 and V{delta}3 subsets, and express high levels of PD-1, activation markers including cytotoxic molecules, and a broad repertoire of killer-cell immunoglobulin-like receptors (KIRs). In vitro, PD-1+ {gamma}{delta} T cells, isolated from MMR-d colon cancers, exhibited a cytolytic response towards HLA class I-negative MMR-d colon cancer cell lines and {beta}2-microglobulin (B2M)-knockout patient-derived tumor organoids (PDTOs), which was enhanced as compared to antigen presentation-proficient cells. This response was diminished after blocking the interaction between NKG2D and its ligands. By comparing paired tumor samples of MMR-d colorectal cancer patients obtained before and after dual PD-1 and CTLA-4 blockade, we found that ICB profoundly increased the intratumoral frequency of {gamma}{delta} T cells in HLA class I-negative cancers. Taken together, these data indicate that {gamma}{delta} T cells contribute to the response to ICB therapy in patients with HLA class I-negative, MMR-d colon cancers, and illustrate the potential of {gamma}{delta} T cells in cancer immunotherapy.

cancer biology↗

bioRxiv2020

Semi-automated background removal limits loss of data and normalises the images for downstream analysis of imaging mass cytometry data

Imaging mass cytometry (IMC) allows the detection of multiple antigens (approximately 40 markers) combined with spatial information, making it a unique tool for the evaluation of complex biological systems. Due to its widespread availability and retained tissue morphology, formalin-fixed, paraffin-embedded (FFPE) tissues are often a material of choice for IMC studies. However, antibody performance and signal-to-noise ratio can differ considerably between FFPE tissues as a consequence of variations in tissue processing, including fixation. We investigated the effect of immunodetection-related signal intensity fluctuations on IMC analysis and phenotype identification in a cohort of twelve colorectal cancer tissues. Furthermore, we explored different normalisation strategies and propose a workflow to normalise IMC data by semi-automated background removal, using publicly available tools. This workflow can be directly applied to previously obtained datasets and considerably improves the quality of IMC data, thereby supporting the analysis and comparison of multiple samples.

immunology↗