Christian M. Schuerch

Genomic events and their timing that grant a primary tumour the competence to disseminate remain poorly defined. We performed sequencing of 247 stage I/II primary cutaneous melanomas (CMs) and 60 matched metastases without intervening therapy from a prospectively followed registry cohort with a median followup of 92 months, integrating copy-number, mutational, protein and spatial-transcriptomic analyses. Relapse was not distinguished by oncogenic point mutations, which were largely shared between primaries and metastases, but by somatic copy-number alterations (SCNAs) and global chromosomal instability. We defined OncoCycle, a six-gene copy-number signature (amplification of CDK4 , MCL1 and CD276 ; biallelic loss of CDKN2A , CDKN2B and TP53BP1 ) that predicted relapse independently of established clinicopathological features in melanoma, and a pan-cancer analysis. In matched pairs, metastatic progression was driven by continued copy-number evolution and reduction in intra-tumoural heterogeneity, rather than by acquired point mutations, and OncoCycle alterations from primary tumours were preserved in metastasis seeding clones. Clonal reconstruction revealed both monoclonal and polyclonal metastasis seeding, and spatial transcriptomics resolved copy-number-defined metastatic subclones occupying and programming distinct immune and stromal niches. Thus, metastatic competence was primed early by focal SCNAs on a background of chromosomal instability, elaborated by continued copy-number evolution during dissemination and spatio-temporal interactions with the tumour-microenvironment.

Aberrant expression of T‐cell markers in B‐cell lymphomas is rare and can pose diagnostic challenges. We report a case of a 65‐year‐old man presenting with newly developed scalp nodules. Histopathology revealed nodular lymphoid infiltrates composed of large centrocytes and centroblasts. Immunohistochemistry demonstrated CD20, BCL6, CD10, and MEF2B positivity with monotypic kappa light chain expression, confirming B‐cell lineage. Notably, aberrant co‐expression of multiple T‐cell markers (CD2, CD3, CD4, and partial CD5), with weaker intensity than surrounding T‐cells, was observed. Molecular studies showed clonal immunoglobulin heavy chain rearrangement with a polyclonal T‐cell receptor pattern. These findings established the diagnosis of primary cutaneous follicle center lymphoma (PCFCL) with aberrant T‐cell marker expression. This represents the first reported case of PCFCL with aberrant expression of multiple T‐cell markers, emphasizing the importance of comprehensive immunophenotyping for accurate lymphoma classification.

Patient metadata for the DLBCL cohorts included in this study.

Cost-calculator for IN-DEPTH experimental planning.

GSVA pathways identified in DLBCL datasets at multicellular and single-cell resolution using SGCC.

Additional supporting data for single-cell SGCC analysis in the DLBCL study.

Additional validation and parameter optimization of the SGCC method, including simulation benchmarking against classical spatial statistical methods and robustness testing across parameter settings.

Spatial transcriptomics and proteomics have enabled profound insights into tissue organization, yet these technologies remain largely disparate, and emerging same-slide multiomics approaches are limited in plex, spatial resolution, signal retention, and integrative analytics. We introduce IN-situ DEtailed Phenotyping To High-resolution transcriptomics (IN-DEPTH), a streamlined, resource-efficient, commercially compatible workflow using single-cell spatial proteomics-derived imaging to guide transcriptomic capture on the same slide without RNA signal loss. To integrate modalities beyond niche-level mapping, we developed Spectral Graph Cross-Correlation (SGCC), a proteomic–transcriptomic framework resolving spatially coordinated functional state changes across interacting cell populations. Applied to diffuse large B-cell lymphoma (DLBCL), IN-DEPTH and SGCC enabled stepwise discovery from Epstein–Barr virus (EBV)–positive and EBV-negative tumor comparisons with single-cell resolution, revealing coordinated tumor–macrophage–CD4 T-cell remodeling, immunosuppressive C1Q macrophage enrichment, CD4 T-cell dysfunction, and a candidate IL27–STAT3 signaling axis. Collectively, IN-DEPTH enables scalable spatial multiomics to uncover clinically relevant microenvironmental mechanisms and toward robust spatial multimodal AI models. Significance:IN-DEPTH enables same-slide spatial multiomics across commercial platforms via a protein-first strategy preserving protein epitopes, RNA quality, and tissue integrity. Coupled with SGCC, it resolves coordinated spatial immune remodeling, revealing EBV/LMP1-driven C1Q macrophage polarization and CD4 T-cell dysfunction in DLBCL, with broad applicability to other diseases.

GSVA pathways identified in the tonsil datasets using SGCC at multicellular level.