Biology subjects

de Souza, T.

Publications and source records attributed to de Souza, T..

4 recordsLinked to original sources

bioRxiv2025

Integrative immune subtyping of HNSCC reveals clinically relevant phenotypes and treatment-associated transitions

Head and neck squamous cell carcinoma (HNSCC) exhibits profound heterogeneity in clinical presentation, treatment response, and immune landscape. While prior classification systems have identified molecular and immune subtypes in this disease, their applicability to real-world clinical settings remains restricted to small, homogeneous cohorts and limited by lack of multimodal data integration and interpretation. We performed integrated multi-omics analysis including transcriptomic, genomic (copy number, single-nucleotide variants) on 1,149 tumors from 1,102 HNSCC patients across treatment settings. Using the Similarity Network Fusion (SNF) algorithm, we defined immune subtype clusters (ISCs) based on the full immune gene landscape. These clusters were characterized using mutational, transcriptional, and immune cell enrichment analyses, and mapped to hypoxia and traditional subtypes. Associations with clinical outcomes, including progression-free survival, were evaluated across first-line and post-metastatic treatment settings. Four distinct immune subtype clusters (ISC1-ISC4) were identified: ISC1: immune-cold and EMT-enriched; ISC2: immune activated; ISC3: mixed immune-regulatory and stromal-enriched phenotype; and ISC4: immunosuppressed. Distinct treatment response patterns were observed across subtypes in subjects treated with checkpoint inhibitors, chemotherapy, and combination regimens. 44 Patients with matched pre/post treatment tumors revealed treatment-associated transitions between immune subtypes: checkpoint inhibitor treatment enriched for immune activation, while chemotherapy treatment enriched for immunosuppressive signaling pathways. This study provides a clinically relevant immune subtyping framework for HNSCC based on real-world, multi-omics data. These subtypes reflect dynamic tumor-immune states and associated with treatment response and survival, supporting their use in guiding immune-based therapy in HNSCC.

immunology↗

bioRxiv2023

An engineered tumor organoid model reveals cellular identity and signaling trajectories underlying translocation RCC.

Translocation renal cell carcinoma (tRCC) is a rare, aggressive type of kidney cancer primarily occurring in children. They are genetically defined by translocations involving MiT/TFE gene family members, TFE3 or, in rare cases, TFEB. The biology underlying tRCC development remains poorly understood, partly due to the lack of representative experimental models. Here, we utilized human kidney organoids, or tubuloids, to engineer a tRCC model by expression of one of the most common MiT/TFE fusions, SFPQ-TFE3. Fusion expressing tubuloids adopt a tRCC-like phenotype and gene expression signature in vitro and grow as clear cell RCC upon xenotransplantation in mice. Genome-wide binding analysis reveals that SFPQ-TFE3 reprograms gene expression signatures by aberrant, gain-of-function genome-wide DNA binding. Combining these analyses with single-cell mRNA readouts reveals an epithelium-to-mesenchymal differentiation trajectory underlying tRCC transformation, potentially caused by deregulated Wnt signaling. Our study demonstrates that SFPQ-TFE3 expression is sufficient to transform kidney epithelial cells into tRCC and defines the trajectories underlying malignant transformation, thereby facilitating the development of new therapeutic interventions.

cancer biology↗

bioRxiv2022

Single-cell transcriptomics reveals immune suppression and cell states predictive of patient outcomes in rhabdomyosarcoma.

Paediatric rhabdomyosarcoma (RMS) is a soft tissue malignancy of mesenchymal origin which is thought to arise as a consequence of derailed myogenic differentiation. Despite intensive treatment regimens, the prognosis for high-risk patients remains dismal. The cellular differentiation states underlying RMS and how these relate to patient outcomes remain largely elusive. Here, we used single-cell mRNA-sequencing to generate a transcriptomic atlas of RMS. Analysis of the RMS tumour niche revealed evidence of an immunosuppressive microenvironment. We also identified an interaction between NECTIN3 and TIGIT, specific to the more aggressive fusion-positive (FP) RMS subtype, as a putative cause of tumour-induced T-cell dysfunction. In malignant RMS cells we defined transcriptional programs reflective of normal myogenic differentiation. Furthermore, we showed that these cellular differentiation states are predictive of patient outcomes in both FP RMS and the more clinically homogenous fusion-negative subtype. Our study reveals the potential of therapies targeting the immune microenvironment of RMS and suggests that assessing tumour differentiation states may enable a more refined risk stratification.

cancer biology↗

bioRxiv2022

Mesenchymal tumor organoid models recapitulate rhabdomyosarcoma subtypes

Rhabdomyosarcomas (RMS) are mesenchyme-derived tumors and the most common childhood soft tissue sarcomas. Treatment is intense, with a nevertheless poor prognosis for high-risk patients. Discovery of new therapies would benefit from additional preclinical models. Here we describe the generation of a collection of pediatric RMS tumor organoid (tumoroid) models comprising all major subtypes. For aggressive tumors, tumoroid models can often be established within four to eight weeks, indicating the feasibility of personalized drug screening. Molecular, genetic and histological characterization show that the models closely resemble the original tumors, with genetic stability over extended culture periods of up to six months. Importantly, drug screening reflects established sensitivities and the models can be modified by CRISPR/Cas9 with TP53 knockout in an embryonal RMS model resulting in replicative stress drug sensitivity. Tumors of mesenchymal origin can therefore be used to generate organoid models, relevant for a variety of preclinical and clinical research questions.

cancer biology↗