Technology Focus Areas

Advanced data analytics

Clinical bioinformatics and AI play a crucial role in translating large-scale datasets into actionable insights for personalized medicine. We focus on:

• Optimization of current algorithms following FAIR guidelines
• Integration of diverse data types (e-records, imaging, omics) to create comprehensive patient profiles
• Evaluation and validation of AI models to ensure their reliability and relevance
• Increasing scalability in diagnostics, improving outcomes and healthcare delivery

Coordinating node: Gothenburg 

Epigenetics

Recent years have witnessed the development of methylation-based classifiers for several cancer types and the CG platform has been instrumental in assessing the clinical utility of this tool for correct identification and treatment of central nervous system tumors. We are now in the process of transitioning this to a national service for implementation of this new technique, which results in the change in diagnosis of one in ten CNS tumors. We have also contributed to the development and implementation of new methylation analysis pipelines, as well as a new classifier for brain tumors, used to support an international clinical trial with diagnostic methylation profiling. Future plans include creating classifiers for cardiopulmonary and infectious diseases. We are also evaluating the use of custom methylome panels as well as  long-read sequencing-based methods for real-time tumor classification during surgerys. 

Coordinating node: Linköping 

Long-read sequencing

Recent advancements in long-read sequencing technologies improve SNV, structural variant, repeat expansion, and methylation profile identification, potentially serving as a comprehensive diagnostic tool. Clinical tests now include SARS-CoV-2 and BCR::ABL1 fusion gene sequencing. Long-read sequencing is anticipated to dramatically increase in clinical research and diagnostics. Collaboration with the Genomics Platform aims to: i) Enhance rare disease diagnostic yield beyond 40% reached by short-read WGS; ii) Replace laborious methods like chromosome analysis in cancer diagnostics; iii) Expedite complete microbial genome assembly, reducing turnaround time for species identification, antibiotic resistance prediction, and epidemiological surveillance; iv) Detect all structural variant classes, including challenging genomic regions, via optical mapping. 

Coordinating node: Uppsala 

Metagenomics

Comprehensive analysis ofmicrobial and host genetic material holds great potential for diagnosis and treatment of infectious disease. We serve as the technical backbone for several national projects and focus on:

• Clinically validated, rapid metagenomic sequencing assays for detection of known and unknown pathogens
• Human background depletion or microbial enrichment
• Antimicrobial resistance prediction
• Publicly available bioinformatic pipelines

Coordinating node: Örebro 

Multi-omics

The addition of multiple data layers has been shown to improve diagnostic yield in several disease areas. For example, transcriptome sequencing facilitates interpretation of genomic variants in regulatory and intronic regions as well as identification of abnormal expression and splicing patterns, allelic imbalances and gene fusion events. We have established bioinformatic workflows for detection of these types of events, which in the next few years will be further refined and integrated with DNA data into a joint variant prioritization model as well as with methylation data for analysis of gene inactivation. During the next funding period, we also plan to initiate collaborations with the Clinical Proteomics platform to explore offering a joint service in proteogenomics.

Coordinating node: Stockholm 

Single-cell and spatial omics

In recent years, single-cell and spatial omics applications have demonstrated great potential to advance future healthcare diagnostics, prognostics, and disease monitoring. Due to an increasing demand for these technologies, the platform has recently established single-cell transcriptomics, epigenetics, and multimodal applications using two complementary technologies (10x Genomics and MissionBio) as services. We use two instruments (NanoString GeoMx and 10x Genomics CytAssist) to offer spatial transcriptomics analyses. Looking ahead, we aim to enhance cost-effectiveness, throughput, and efficiency, particularly for analyzing low-input samples, collaborating with other platforms (mainly NGI and Spatial Biology) for broader modalities (e.g., proteomics) and spatial omics at single-cell or sub-cellular levels (in situ sequencing).

Coordinating node: Lund 

Ultrasensitive detection

Ultra-sensitive assays for identification of low frequency mutations play a crucial role in cancer diagnosis, prognosis and monitoring treatment response. No single method meets all criteria for number of markers screened, sensitivity, time-efficiency, and cost-efficiency. We therefore use a combination of methods, including digital PCR, deep sequencing with UMIs, and superRCA, and we plan to incorporate the SimSen-Seq technology for highly sensitive multi-marker detection as a national service by our platform. We have developed and implemented diagnostic tests for several cancers using liquid biopsies (i.e., detection of variants in circulating tumor DNA), a rapidly expanding area. A major development project is a clinical study in myelodysplastic syndrome, utilizing digital PCR and super RCA post stem-cell transplantation for early relapse prediction and optimized treatment.

Coordinating node: Uppsala