Advancing Spatial Transcriptomics
From Method Development to Biological Insights
Time: Thu 2026-02-19 13.00
Location: Air & Fire, Scilifelab, Tomtebodavägen 23A, Solna
Video link: https://kth-se.zoom.us/j/62067477344?pwd=vAXl64uZBhErS5ly0Y37b4T3W6YDLa.1
Language: English
Subject area: Biotechnology
Doctoral student: Eva Gracia Villacampa , Science for Life Laboratory, SciLifeLab, Genteknologi, eva.gracia@scilifelab.se, Spatial Transcriptomics, Joakim Lundeberg
Opponent: Doktor Eduard Porta Pardo, Josep Carreras Leukaemia Research Institute
Supervisor: Professor Joakim Lundeberg, Science for Life Laboratory, SciLifeLab, Genteknologi; Doktor Kim Thrane, Genteknologi, Science for Life Laboratory, SciLifeLab
QC 2026-01-26
Abstract
Spatial transcriptomics (ST) revolutionized the study of gene expression within tissue sections, yet its application to clinically relevant material has remained limited by technical constraints related to sample characteristics and RNA quality. This thesis advances the use of spatial transcriptomics by establishing frameworks for profiling archival clinical specimens, ensuring tissue quality prior to ST, and combining spatial data and other complementary modalities to reveal the cellular, molecular and immune-clonal architecture of human cancer.
In Article I, we developed a method that adapted genome-wide spatial transcriptomics to formalinfixed paraffin embedded (FFPE) samples, which constitute the vast majority of clinical specimens, unlocking their potential. The workflow was validated on mouse brain tissue, showing high correlation with matched fresh-frozen data, and then applied on other various tissues to show its robustness across sample types. This development expanded spatial transcriptomics to previously inaccessible FFPE material. We also developed a TSO-based QC assay to assess spatial RNA accessibility directly in FFPE tissue sections, minimizing the risk of failed or biased spatial transcriptomics analysis.
In Article II, we developed an assay that enables evaluation of RNA integrity directly within tissue sections, the spatial RNA integrity number (sRIN) assay. Traditional RIN values are obtained from bulk tissue and therefore cannot reveal local variability in RNA quality. sRIN was developed as a practical quality-control step allowing users to identify well-preserved versus degraded regions before committing to costly downstream experiments.
In Article III, we analyzed genomic and clinical data from phase III melanoma trials and used NMF to define seven melanoma subtypes reflecting distinct differentiation states. By integrating bulk, single-cell, and spatial transcriptomics, we showed that these states coexist within tumors. Our analyses revealed that only differentiated melanoma becomes sensitized to immune checkpoint blockade therapy when combined with BRAF/MEK inhibition through enhanced antigen presentation, whereas undifferentiated states remain resistant, colocalize with CAF-rich niches, and could potentially be targeted by CDK7 inhibitors.
In Article IV, we combined single-cell RNA-seq, spatial transcriptomics and spatial V(D)J profiling to characterize the spatial and clonal organization of the immune landscape of sinonasal squamous cell carcinoma (SNSCC). Although immune infiltration was extensive, T- and B- cell clones were found preferentially within antigen presenting cell -rich stromal and peritumoral niches rather than undifferentiated tumor areas. We identified diverse CD8+ T-cell activation states that followed a bifurcated differentiation trajectory, and we also found an unusually large population of FOXP3+ regulatory T cells (Tregs), many expressing CXCR3 and TBX21 (T-bet). Integration of spatial gene expression with sV(D)J associated immune diversification and clonal expansion with CAF-associated matrix remodeling programs and interferon-activated antigen presenting cell programs. CXCL9+/CXCL10+ macrophages were found as drivers of lymphocyte recruitment and IDO1+ regulatory dendritic cells as immunosuppressive within the same niches.