Scientific Highlights from ‘Cancer Genomics, Multiomics and Computational Biology’ 2026

The EACR’s Cancer Genomics, Multiomics and Computational Biology conference (Essen, 12–14 May 2026) centred on integrating high-resolution genomic and multi-omic data with advanced computational and AI-driven approaches to dissect tumour initiation, evolution, heterogeneity, and therapeutic response. At its 7^th edition (previously known as Cancer Genomics), the meeting brought together just under 200 delegates from 33 countries. This was a truly multidisciplinary meeting, with topics discussed spanning cancer genomics and immune genomics, cell plasticity and non-genetic evolution, genetic and epigenetic regulation, and genomic instability, alongside methods for data integration and convergence across modalities in a pan-cancer context. The transdisciplinary approach was appreciated by attendees with the conference being highly recommended by 99% of feedback respondents.

The programme

The programme placed single-cell omics and spatial organisation at its core, using these approaches to dissect cellular diversity and spatio-temporal context within the tumour ecosystem.

Itay Tirosh (Weizmann Institute of Science, Israel) focused his talk on metastasis and senescence in head and neck cancer, illustrating how single-cell and spatial profiling can define distinct cell states and map their spatial architecture [1,2], while Mor Nitzan (The Hebrew University of Jerusalem, Israel) presented computational strategies for decoding layered spatial and temporal organisation in multicellular systems [3,4]. Complementing these spatial perspectives, Jamie Blundell (University of Cambridge, UK) focused on reconstructing clonal histories (recapitulate phylogeny) at single-cell resolution and described an in vivo lineage tracing method that uses methylation barcodes in the PCDH gene cluster. This method could improve early detection of individuals at risk of developing cancer [5]. Andrea Sottoriva (Human Technopole, Italy) showed how single-cell multi-omics can quantify epigenetic evolution and plasticity in colorectal cancer and its microenvironment, linking epigenetic changes to Darwinian selection [6-8]. On the translational side, Ewa Szczurek (Helmholtz Munich, Germany) highlighted how AI-driven analyses can reveal clinically meaningful spatial neighbourhoods and cell–cell interactions in tumours [9], and Raza Ali (CRUK Cambridge Institute, UK) focused on spatial predictors of response to neoadjuvant immuno-oncology therapy [10]. Bringing these insights toward clinical application, Eduard Porta (Josep Carreras Leukaemia Research Institute, Spain) outlined how spatial maps can be transformed into diagnostic and decision-support tools, positioning spatial biology as an emerging layer in precision oncology [11,12].

Continuing on this theme, the EMBO Closing Keynote Lecture delivered by Carlos Caldas (Hebrew University of Jerusalem, Israel, and University of Cambridge, UK) captivated the audience with a helicopter view of his research: genomics to post-genomics approaches applied to the study of breast cancer. Starting from genomic driver-based stratification of breast cancer [13] and moving on to understanding the genomic subgroups that underlie the dynamics of breast cancer relapse [14] and the development of tools that can predict breast cancer therapy response [15-17], Dr Caldas’ lecture offered fantastic insights into the evolution of the cancer genomics research field from uncovering tumour heterogeneity to charting the tumor microenvironment; from genomic data to multi-omics integration; from uncovering and understanding biological processes to practical clinical implications. Dr Caldas also delighted the audience by sharing the latest unpublished results from his research.

Relevant themes and research advances

A theme mentioned throughout the conference was that tumour ecosystems underlie all cancer features, whilst malignant cells instruct the tumour ecosystems, creating an ever more complex feedback loop. The trajectory is clearly from artificial model systems toward human tissues, with computational biology and advanced data analysis positioned as a pillar in the future of cancer research. Poster sessions and proffered papers reinforced these directions, while dedicated discussions with the Scientific Programme Committee underscored how recent technical advances have transformed our understanding of cancer, enabling a shift from studying isolated genes to interrogating cells and tissues in an increasingly multidisciplinary framework that integrates physics, mathematics and biology. While the range of topics covered at the conference was remarkably diverse, a recurring message was that the biggest current challenge is no longer data generation but “data immigration” – moving data across platforms and scales in ways that are biologically meaningful. The committee also stressed that a significant limitation is the reliance on correlative studies. While modelling and simulation are advancing rapidly, truly predictive, mechanistic models of tumours will require deeper causal insight and more rigorous integration of multi-scale data. Looking ahead, the scientific committee highlighted an ambitious next goal for the community: to realistically “compute tumours” in the way we are now able to compute gastrulation and embryonic development [18]?

Survey feedback on Cancer Genomics, Multiomics and Computational Biology

References:

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